Applying Two Change Frameworks to Address Change Processes and Barriers in Instructional Change: A Case of STEM Instructors’ Adoption of Active Learning During Abrupt Online Transition

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Marlor, Laura J. Carroll, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6285934/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background STEM higher education has been undergoing instructional changes, such as shifting from traditional lecturing to active learning, transitioning from physical classrooms to online or blended settings, and integrating transformative educational technologies. These instructional changes tend to be systemic (e.g., instructional changes across multiple STEM departments or institutions), yet research on such changes is limited. Change theories have been advocated to guide research on instructional changes, but their inappropriate or insufficient application partly contributes to the challenges in successfully adopting these changes. This study applies two change frameworks, the Concerns-Based Adoption Model (CBAM) and the Four-Category Barrier Framework (FCBF), to investigate a systemic instructional change and explore change processes and barriers at both individual and contextual levels. We used STEM instructors’ adoption of active learning during the abrupt transition to online learning as a case, conducting focus groups with 32 STEM instructors at U.S. higher education institutions. Results Regarding the change processes identified through CBAM, participants’ behaviors were primarily categorized as initial steps toward using active learning in online settings, although their concerns ranged from handling logistics to the impact of the abrupt transition on their students. In terms of barriers identified using FCBF, participants faced personal issues related to time, comfort, and control over their classes, as well as contextual barriers related to students (e.g., student participation), teaching (e.g., instructional support), and institutional factors (e.g., policies regarding support and teaching modes). We synthesized the results of the two change frameworks, finding that specific participants’ behaviors and concerns were intricately connected with contextual and individual barriers, which differed at various stages in the change process. This work, with concrete evidence from the synthesized results, demonstrates STEM instructors need tailored support and personalized assistance, especially when faced with abrupt systemic instructional changes. Conclusions: Applying two change frameworks enables us to investigate STEM instructors’ adoption of systemic instructional changes through the lenses of change processes and individual and contextual barriers, offering insightful and comprehensive findings. We recognize and advocate for using multiple change theories to take advantage of each framework and conduct thorough research on instructors’ adoption of systemic instructional changes. STEM instructors Instructional change Change processes Barriers Active learning Online COVID-19 pandemic Introduction U.S. higher education has undergone major instructional shifts from recitation to lecturing and, more recently, evolving toward student-centered instruction, such as active learning, to meet society’s evolving demands for graduates (Barr & Tagg, 1995 ; Cuban, 1999 ; Vonderwell & Turner, 2005 ; Zimmerman, 2020 ). This latter shift has been particularly emphasized in STEM higher education, where research over the past three decades demonstrated that active learning enhances student learning (Freeman et al., 2014 ; Haak et al., 2011 ; Prince et al., 2020 ; Singhal et al., 2021 ; Theobald et al., 2020 ; Ting et al., 2023 ; Yan et al., 2024 ). As a result, scholars have advocated for transition instruction from traditional lecturing to active learning in STEM courses. Active learning refers to student-centered instruction that engage students in learning through individual or group activities, such as solving problems in small groups or participating in think-pair-share exercises (Nguyen et al., 2021 ). When effectively implemented in online settings, active learning can increase student engagement (Chen et al., 2018 ; Khan et al., 2017 ; Hsu & Rowland-Goldsmith, 2021 ; Prince et al., 2020 ; Singhal et al., 2021 ), improve learning outcomes (Singhal et al., 2021 ; Willson et al., 2007), and create more positive learning experiences (Khan et al., 2017 ; Willson et al., 2007). Despite these benefits, active learning has been adopted slowly in higher education, and traditional instructional practices (e.g., lecturing) remain dominant (Børte et al., 2023 ; Reinholz & Andrews, 2020 ). STEM instructors[1] have expressed difficulties in integrating active learning into their courses, leading to its limited usage in undergraduate STEM education in both face-to-face and online settings (Andrews & Lemons, 2015 ; Authors, 2023 ; Borda et al., 2020 ; Finelli et al., 2014 ; Hall et al., 2002 ; Khan et al., 2017 ; Nelson et al., 2021 ; Stains et al., 2018 ). In response, researchers and funding agencies, such as the United States National Science Foundation, clearly state the application of at least one theory of change as a critical component in research proposals focusing on implementing instructional change processes (Reinholz & Andrews, 2020 ; Reinholz et al., 2021 ). This guidance emphasizes the integration of change theories for efforts aimed at achieving instructional changes in STEM higher education. Further, it helps ensure that planned activities are well-grounded in research and theory, providing a foundation on which to foster meaningful, generalizable, and lasting outcomes (Henderson et al., 2011 ; Borrego & Henderson, 2014 ; Reinholz & Andrews, 2020 ). Here, change theory refers to an evidence-based framework of ideas that extends beyond single change initiatives, generalizes observations of changes, and enriches collective knowledge for explaining how change occurs (adapted from Henderson et al., 2011 ; Reinholz & Andrews, 2020 ; Reinholz et al., 2021 ). Change theories have been increasingly applied in studies on instructional change; however, the slow implementation of instructional changes in STEM higher education can be attributed, in part, to the misusage, superficial utilization, or a limited understanding of change theories by researchers or change agents (Borrego & Henderson, 2014 ; Eblen-Zayas et al., 2023 ; Kezar et al., 2015 ; Reinholz et al., 2021 ). Change theories vary by rationale and assumptions, change strategies, and context (Henderson et al., 2011 ; Reinholz et al., 2021 ). For example, Rogers’ Diffusion of Innovation (2003) focuses on change processes, while expectancy-value theory has been applied to identify barriers or influences of adopting changes (e.g., Finelli et al., 2014 ). For a systemic instructional change (e.g., an instructional change across multiple STEM departments or institutions), it is difficult to identify a single change theory that can both study the change process and determine the related barriers. Moreover, our literature review of articles published between 2014 and 2024 in the International Journal of STEM Education , a peer-reviewed, high-impact STEM education journal, indicates that most research on applying change theories to understand STEM instructors’ adoption of active learning has primarily focused on face-to-face instruction (i.e., the traditional teaching modality) and has typically relied on a single theoretical framework. Of the 42 articles identified as research on active learning instructional practices, 37 explicitly delineated the theoretical frameworks guiding their research design and interpretation of results (Authors, accepted). Ten papers incorporated two or three theories, most applying these frameworks at different research stages (Authors, accepted). For example, Czajka & McConnell ( 2016 ) used the Interconnected Model to analyze the faculty’s professional development trajectory and identify the factors contributing to sustained instructional change. They also employed the theories of change to understand whether the instructor’s beliefs shifted before or after implementing reformed teaching strategies (Czajka & McConnell, 2016 ). Reinholz et al. ( 2021 ) noted that “a given project could benefit most from multiple theories tailored together to meet its goals” (p. 17), a perspective echoed in prior literature (e.g., Kezar & Holcombe, 2021 ; Reinholz & Andrews, 2020 ). From this, we can extrapolate the need for more research on instructional change applying multiple change theories to study instructional changes. The COVID-19 pandemic triggered systemic instructional changes in higher education, forcing STEM instructors who used active learning in person and who wished to continue using it to adopt it in online settings (Chamo et al., 2023 ; Keane et al., 2022 ; Nelson et al., 2021 ; Venton & Pompano, 2021 ; Zhao & Watterston, 2021 ) and motivating others to use active learning for the first time in an online setting. The pandemic emphasized the significance of student-centered instruction and learners’ autonomy due to unanticipated shifts from traditional face-to-face settings to fully online settings (Chamo et al., 2023 ; Keane et al., 2022 ; Zhao & Watterston, 2021 ). The abrupt transition of college courses to online environments during the pandemic challenged STEM instructors’ planned use of active learning (Huang, 2020 ; Luburić et al., 2021 ; Nelson et al., 2021 ; Venton & Pompano, 2021 ), as most instructors had little to no experience with online teaching environments and struggled to adjust to that context. Many instructors initially relied on recorded lectures and basic assignments, without much consideration for more sophisticated use of technology (e.g., Shim & Lee, 2020 ). In the post-COVID-19 setting, researchers report that instructors and students are more likely to prefer a blended or hybrid arrangement where face-to-face and online education are combined (Keane et al., 2022 ; Ng, 2022 ; Zhao & Watterston, 2022). To maximize the benefits of a blended arrangement, instructors need to redesign online and face-to-face course elements for their courses (O’Dea & Stern, 2022 ). This course redesign provides new and plentiful opportunities to support instructors as they implement active learning in both their face-to-face and online courses, especially as the pandemic may have shifted instructors’ views of the efficacy of online technology, feasibility of its implementation, and potential benefits for them and their students (e.g., Abrahams, 2010 ; Zhao & Watterston, 2021 ).The far-reaching impact of the COVID-19 pandemic on STEM higher education highlights the need for more research into systemic changes; however, existing research on instructional change typically addresses individual changes rather than changes across STEM disciplines or organizations (Borrego & Henderson, 2014 ; Reinholz et al., 2021 ). The case of STEM instructors from different institutions adopting active learning in online settings during the pandemic presents an ideal opportunity to explore systemic changes. Therefore, this study aims to showcase the dual application of two change frameworks to investigate instructional change, specifically focusing on STEM instructors’ adoption of active learning while abruptly transitioning to online instruction. The first framework is the Concerns-Based Adoption Model (CBAM; Hall & Hord, 2020 ), which views change as a process and is centered on the concerns of individual instructors. The second framework is the Four-Category Barrier Framework (FCBF; authors, 2023 ), which focuses on identifying barriers and emphasizes where the change is taking place. Using these two models together enables us to address change processes and barriers on both an individual and a systemic level. Hence, we seek to answer three main research questions: RQ1: How does CBAM illustrate the process of STEM instructors’ adoption of active learning during an abrupt transition to online instruction? RQ2: How does FCBF identify and explain the barriers faced by STEM instructors in adopting active learning during an abrupt transition to online instruction? RQ3: How do the two frameworks work together to shed insight on the challenges instructors face and the strategies they use when adopting active learning during an abrupt transition to online instruction? In this paper, we first review the two change frameworks, explaining why these were chosen. We then describe our research methods and present our results to address the three research questions. Lastly, we reflect on the application of the two frameworks, consider limitations of this study, and present our conclusions. Literature Review Concerns-Based Adoption Model (CBAM) The Concerns-Based Adoption Model (CBAM) is an empirically-grounded theoretical model that defines change as a process with a series of affective stages and behavioral levels through which individuals move (Anderson, 1997 ; Hall & Hord, 1987 ; Hall & Hord, 2020 ). CBAM was developed using data collected over more than two decades in an effort to understand, assess, and facilitate individuals (mainly teachers) who implement changes in educational institutions (Hall & Hord, 1987 ; Hall & Hord, 2020 ). The model has three independent diagnostic dimensions which can be used separately or combined with one another: Innovation Configuration (IC), Levels of Use (LoU), and Stages of Concern (SoC) (Hall & Hord, 2020 ). IC is used to clarify instructional change by describing the various operational forms of a change that are implemented. LoU identifies characteristic behavioral profiles of individuals by illustrating individual behaviors as they engage with the change. SoC identifies how individuals respond to change by describing the concerns (e.g., attitudes, beliefs, feelings, and perspectives) they have about implementing the change. As we apply the CBAM framework for our research, we define the “individual” to be the STEM instructor and the “change” to be adoption of active learning during an abrupt transition to online instruction. IC is outside the scope of our project because we focus on the processes of instructors’ abrupt adoption of active learning in online settings across multiple institutions, rather than on participants’ descriptions of the change itself. Accordingly, we use two dimensions (LoU and SoC) of CBAM to study change. The LoU dimension has been used frequently to study an individual’s behaviors when they prepare to use, begin to use, and obtain new skills and experiences. LoU has eight levels: 0-Nonuse, 1-Orientation, 2-Preparation, 3-Mechanical, 4a-Routine, 4b-Refinement, 5-Integration, and 6-Renewal (Table 1 ; Hall & Hord, 2020 ). The main distinction between the eight levels is whether the instructor is a Nonuser (characterized by the LoU levels of 0-Nonuse, 1-Orientation, and 2-Preparation) or a User (characterized by the remaining five LoU levels of 3-Mechanical Use through 6-Renewal). In our case, Nonusers are instructors who have not implemented online active learning; while Users are those who have begun to use active learning in an online setting. In addition, instructors’ behaviors categorized as Level 3-Mechanical Use suggest that they struggle with the initial steps of adopting active learning (Anderson, 1997 ; Hall & Hord, 1987 ; Hall & Hord, 2020 ). Although some may take strategies to make the adoption of online active learning easier, the implementation process may still be inefficient (Hall & Hord, 2020 ). Table 1 The Levels of Use and Stages of Concern dimensions of CBAM Levels of Use (LoU) Stages of Concern (SoC) Nonusers 0-Nonuse Unrelated 0-Unconcerned 1-Orientation Self 1-Informational 2-Preparation 2-Personal Users 3-Mechanical Task 3-Management 4a-Routine Impact 4-Consequence 4b-Refinement 5-Collaboration 5-Integration 6-Refocusing 6-Renewal The SoC dimension represents an individual’s attitudes, beliefs, and feelings about adopting a change. It comprises seven stages: 0-Unconcerned, 1-Informational, 2-Personal, 3-Management, 4-Consequence, 5-Collaboration, 6-Refocusing which are further grouped into four categories (Table 1 ; Hall & Hord, 2020 ): Unrelated (i.e., 0-Unconcerned), Self (i.e., 1-Informational and 2-Personal), Task (i.e., 3-Management), and Impact (i.e., 4-Consequence, 5-Collaboration, 6-Refocusing). The two concerns in the “Self” category indicate that the instructor is focused on what the instructional change will mean for them, personally, while the three concerns in the “Impact” category indicate that the instructor is focused on what is happening with students and what could be done to enhance outcomes. Hall and Hord ( 2020 ) state that instructors generally have concerns at more than one stage at the same time. For example, an instructor may have intense concerns at Stage 3-Management and additional concerns at Stage 4-Consequence. CBAM has been widely applied across different educational contexts and disciplines to study teachers’ adoption of instructional change (Anderson, 1997 ). Min ( 2017 ) used SoC to explore the concerns of four instructors adopting eBook-integrated curricula, showing that all instructors had used eBook for one semester or less, and their concerns were at the stages of 2-Personal, 4-Consequences, and 6-Refocusing. Each instructor expressed attitudes and beliefs at multiple stages, and each was motivated to adopt the novel eBook curriculum by concerns about their students (e.g., Impact concerns including 4-Consequences and 6-Refocusing). Min ( 2017 ) also found no direct connection between advancing through the SoC stages and experience with the instructional change. SoC has also been applied in research on active learning and online teaching. Luik and Lepp tested the applicability of SoC to explain the transition to online learning by analyzing 872 messages posted in a Facebook learning group from March to April 2020 (Luik & Lepp, 2021 ). Their results indicated that secondary-school teachers, students, and others’ concerns (e.g., Stage 2-Personal) mainly contributed to personal feelings and needs early in the change. Then, concerns moved to the management of change (e.g., workload, materials, logistics; Stage 3-Management), and finally they moved to the willingness to collaborate (e.g., Stage 5-Collaboration). The authors further stated that CBAM is suitable for explaining unexpected instructional changes. Researchers have also utilized a combination of LoU and SoC to study the implementation of instructional change. Olson and colleagues ( 2020 ) applied the two dimensions to evaluate the ongoing implementation of a K-12 school district’s strategic plan to promote deep learning. They identified many educators who had Unrelated and Self concerns and were at the 3-Mechanical or 4a-Routine levels, indicating initial steps to implementation. Olson et al. ( 2020 ) stated that many participants were interested in and involved in implementing the strategic plan but had limited information and preparation. The authors also concluded that the application of CBAM helped them “generate timely feedback and data-driven recommendations” to implement changes (p. 56, Olson et al., 2020 ). Four-Category Barrier Framework (FCBF) The Four-Category Barrier Framework (FCBF) is an instrument with validation evidence designed to assess instructors’ perceived barriers to implementing active learning (Authors, 2023 ). Drawing from data collected from approximately 1,000 engineering instructors across North American higher education institutions, the framework was developed based on Sturtevant and Wheeler’s ( 2019 ) Faculty Instructional Barriers and Identity Survey, which utilized Lattuca and Pollard’s ( 2016 ) Faculty Decision-Making Model. Through a 5-phase process that utilized factor analysis, the FCBF was constructed to provide a comprehensive understanding of the barriers perceived by instructors during their adoption of active learning. The framework suggests that an instructor’s motivation to engage in an instructional change involves both contextual factors (e.g., student, teaching, and institution) and individual factors (e.g., instructor). Authors ( 2023 ) presents four categories of barriers (Table 2 ): instructor (e.g., instructor comfort and confidence), student (e.g., student preparation and engagement), teaching (e.g., instructional support), and institution (e.g., institutional environment/rewards). Instructor barriers are related to instructors’ perceptions of their personal conditions, which include instructor attitudes and beliefs that challenge their adoption of active learning. Student barriers mainly pertain to challenges related to student engagement, student expectation, student preparation, and student response to active learning from the instructor’s perspectives. Teaching barriers refer to instructional support (e.g., technology, pedagogy, and logistics), assessment and evaluation, and learning environments (e.g., class size, classroom layout, and teaching and learning medium) from instructors’ perspectives. Institution barriers encompass the institutional environment which includes teaching policies, rewards, and collegial support. Table 2 The categories of FCBF Factor type Category Individual Instructor Contextual Student Teaching Institution Why use CBAM and FCBF together? We selected both CBAM and FCBF to guide our study because teaching is a complex and cultural activity (Davis & Sumara, 2006 ). It involves multiple stakeholders, including students, instructors, departments, and institutions, and is influenced by the context in which the teaching occurs (Stigler & Miller, 2018 ). Additionally, change theories differ in terms of assumptions, context, and rationale (Henderson et al., 2011 ; Reinholz et al., 2021 ), such as CBAM vs. Rogers’ Diffusion of Innovation. Using multiple theories provides a more comprehensive lens to study instructional changes, especially for a systemic instructional change. Rogers’ Diffusion of Innovation is one of the most well-known change theories applied in the education field and, like CBAM, regards change as a staged process, encompassing instructors’ decision-making period and overt behaviors (Roger, 2003). However, Rogers’ model carries limitations, and some researchers have involved other theories in their studies. Sturtevant and Wheeler ( 2019 ) utilized Lattuca and Pollard’s ( 2016 ) model when they modified Lund and Stains’ ( 2015 ) instrument (which was originally built upon Rogers’ theory). Andrews and Lemons ( 2015 ) also modified Rogers’ model because they noted it is not practical to distinguish between Persuasion (e.g., forming an attitude) and Decision (e.g., deciding to make an instructional change), and because Roger’s model is not ideally aligned with instructional context. In a similar vein, Çakıroğlu et al. ( 2021 ) found that their adopter distribution concept did not follow the S-shaped curve predicted by Rogers’ model, which may be due to the unprecedented instructional change of transitioning courses online. Unlike change theories based on Rogers’ model, CBAM was designed to understand, assess, and facilitate the process for individuals adopting changes in educational institutions (Hall & Hord, 1987 ; Hall & Hord, 2020 ), although it also has its own limitations. It provides explicit structures guiding researchers to study individuals’ behaviors and concerns that pertain to the implementation of an instructional change. However, CBAM does not involve factors such as institution management, teaching policies and support systems, and individual characteristics (e.g., Çetinkaya, 2012 ; Kwok, 2014 ; Min, 2017 ). As a result, it is difficult to identify influences that relate to a certain stage of concern or level of use. FCBF does focus on those contextual factors and is based on extensive empirical work. When combined with CBAM, we can use FBCF to study instructors’ adoption of active learning during abrupt transition online instruction from a more comprehensive perspective. Methods We applied a qualitative research method to study the change processes and relevant barriers for 32 STEM instructors adopting active learning during the abrupt transition to online instruction. We designed a focus group protocol primarily targeting barriers to adopting active learning in their online courses, while also allowing participants to share their experiences (e.g., what they did and how they felt). We then coded the transcripts using the CBAM and the FBCF separately before synthesizing the results from the two change frameworks. Participants This study is part of a larger research project about instructors’ adoption of active learning (Authors, 2022 ) which involves 165 instructors who taught first- or second-year STEM courses at 56 institutions in the Midwest region of the United States. After receiving human subjects research approval from the University of XXX’s Institutional Review Board (HUM###), we recruited participants for our study. From the population of instructors for our larger project, we randomly selected ten institutions across each of four categories (community colleges, bachelor-, master-, and doctoral-granting institutions) and invited an instructor for each of the resulting 40 institutions to participate in focus group discussions. Thirty-two instructors agreed to participate in one of our focus groups (Table 3 ). Table 3 Participant pool and online active learning methods they used Institution Category 1 # Instructors # Female # Male Community College 7 4 (Caitlin, Cerys, Chole, Charlotte) 3 (Cai, Calum, Cody) Bachelor-granting 8 6 (Babette, Barbara, Beatrice, Betty, Blessing, Bree) 2 (Ben, Blake) Master-granting 7 7 (Madeline, Margaret, Marjorie, Maxine, Melanie, Mia, Muriel) 0 Doctoral-granting 10 6 (Daphne, Darcy, Daria, Denise, Diana, Dylan) 4 (Daniel, Damian, Desmond, Donald) Total 32 23 9 Additionally, participants shared their disciplines and the active learning methods they used during the pandemic in the focus group discussions (Tables 3 & 4 ). Most participants were from mathematics (9 instructors) and biology (8 instructors), with five participants each from chemistry and engineering, three from physics, and one from architecture. All participants mentioned utilizing learning activities in synchronous and/or asynchronous online classes during the pandemic, but two participants did not specify the active learning methods they used (Table 4 ). Notably, small group activities and hands-on activities were the two most frequently discussed methods. Table 4 Online active learning methods used by participants Online active learning methods Participants Small group activities Beatrice, Blake, Bree, Calum, Cerys, Charlotte, Darcy, Damian, Daniel, Donald, Madeline, Margaret, Maxine, Melanie, Mia Hands-on activities Ben, Blessing, Calum, Cerys, Charlotte, Damian, Daniel, Daphne, Daria, Diana, Margaret, Marjorie, Muriel Quiz/worksheet-embedded videos Bree, Caitlin, Chole, Daniel, Denise Class problem-solving Beatrice, Cai, Calum, Cody, Desmond Flipping 1 Babette, Betty, Blake, Charlotte, Damian, Daniel, Donald, Muriel 1 Flipping represents active learning methods mentioned by instructors which involve assigning pre-class activities (such as videos) and using class time for problem solving, discussion, etc. Data Collection We conducted eight one-hour focus group interviews (two for each of the four institutional categories) using Zoom. During each focus group, we used a semi-structured protocol with four parts: (1) informed consent for participation and video recording, (2) focus group guidelines, (3) introductions by providing the definition of active learning to ensure that participants share a common understanding of the research focus, and (4) a discussion about barriers that instructors faced when adopting active learning for online instruction. The bulk of focus group time concentrated on part 4, barriers, and participants were prompted to identify barriers they perceived to using active learning in online settings, factors that might influence the relative significance of these barriers, and the extent to which they perceived engaging students in online active learning as an issue. The interviewer facilitated the session, while one or two other researchers took notes. Data Analysis We analyzed the data using a two-step approach. First, we coded the data set using the CBAM framework (i.e., LoU and SoC dimensions) and then separately for the FCBF. Next, we synthesized the results from the two frameworks by matching factors to each stage of concern and level of behavior. Below are the details of our coding analysis. All interviews were transcribed verbatim and anonymized. We assigned participant identifiers to align with the institution type – instructors from community colleges were assigned names starting with a C (such as Charlotte) and those from bachelor-, master-, and doctoral-granting universities were assigned names starting with B, M, or D, respectively (on reflection, we should have invited participants to inform us of their preferred anonymized names to better cater to their identities rather than selecting them ourselves). We then analyzed all transcripts using the dual lenses of CBAM and FCBF via MAXQDA 2020. We conducted the analysis through two coding cycles: (1) labeling codes and refining the codebook with a deductive approach to determine levels of use and stages of concern (for the CBAM round of coding) or categories of barriers (for the FCBF round of coding), and (2) categorizing codes and identifying patterns with an inductive approach to allow for emerging themes and subthemes (Azungah, 2018 ; Saldaña, 2013 ). For the CBAM round of coding, we used the LoU and SoC dimensions of CBAM to code all eight transcripts. In the first coding cycle, two researchers independently coded the first four of the eight transcripts by using the initial codebook of LoU ( Appendix , Table 11 ) and SoC ( Appendix , Table 12 ). Then the coders worked together to refine the codebooks and check the intercoder agreement using MAXQDA 2020 (Rädiker & Kuckartz, 2020). After coding the four transcripts, we noted that more than 80% of the LoU segments were coded as level 3-Mechanical Use. To better distribute the codes and more effectively illustrate differences related to logistics versus skills of online instruction, we defined two new sublevels (3a-Mechanical Logistics and 3b-Mechanical New Skills). The segments were recoded accordingly, with roughly half of the codes now falling into each of the new subcategories. Next, one researcher used the refined codebook to re-analyze the first four transcripts. Finally, in the second coding cycle, one researcher categorized coded data and determined themes and sub-themes of each code, and a second researcher reviewed the coding to validate the identified patterns. As a separate round of coding, we similarly used the FCBF to code the eight focus group transcripts in two coding cycles, determining segments that aligned with each of the four categories of challenges to online active learning from instructors’ perspectives (Appendix, Table 13 for the codebook). In the first cycle, three researchers used the initial codebook (Appendix, Table 13) to independently code the first two transcripts. They collaborated to check the intercoder agreement and refined the codebook. Then, two researchers coded a third transcript with the updated codebook and further finalized the codebook. After that, one researcher completed the coding for the remaining five transcripts. In the second coding cycle, one researcher grouped the coded data and determined the themes and sub-themes of each of the four categories. A second researcher reviewed the coding to validate the identified patterns. Results This section is structured into four sub-sections. The first two sub-sections target the first two research questions, describing change processes (i.e., themes identified when applying LoU and SoC of CBAM; Tables 5 & 6) and barriers or influences (i.e., themes identified when applying the FCBF; Table 7). In the third sub-section, we synthesize the results of CBAM and FCBF to illustrate challenges faced by participants during the abrupt adoption and their relevant influences (Tables 8 and 9). We also report the strategies employed by instructors while implementing active learning in online settings (Table 10). The last sub-section summarizes the key takeaways from studying the case of STEM instructors from different institutions adopting active learning during the pandemic. To maintain clarity and conciseness in the main text, we provide a primary summary of these results. The application of the CBAM Framework To answer our first research question (i.e., How does CBAM illustrate the processes of STEM instructors’ adoption of active learning during an abrupt transition to online instruction? ), we investigated the processes in terms of STEM instructors’ behavioral levels (i.e., results of CBAM-LoU) and affective stages (i.e. results of CBAM-SoC). When applying the LoU framework, we identified seven themes aligned with three levels: 3a-Mechanical Logistics, 3b-Mechanical New Skills, and 4a-Routine (Table 5). The application of the SoC framework resulted in four themes aligned with two stages of concerns (Table 6), with 3-Management having two themes and 4-Consequence having two themes. Results of CBAM-LoU Levels of Use refers to an individual’s behaviors when they prepare to use, begin to use, and obtain new skills and experiences. Based on the segments coded among the eight focus group transcripts, we identified three behavioral levels: 3a-Mechanical Logistics with two themes, 3b-Mechanical New Skills with two themes, and 4a-Routine with three themes (Table 5). The category of 3a-Mechanical Logistics represents the initial steps toward using active learning in an online setting. This level suggests that instructors primarily focused on their own needs for online active learning and expressed their inability to tackle these challenges amid the unexpected change. Behaviors at this level reported by instructors were mainly related to hands-on activities and logistical online teaching . Instructors reported their failure to successfully conduct hands-on activities due to students lacking access to learning resources and equipment or the requirement of extra fees. They also shared their attempts to engage students in synchronous classes , promote student motivation for online activities , and devote time to preparing online active learning . However, some instructors reported that it was time-consuming to design and search for effective learning activities and materials that truly engaged online students. Additionally, estimating the time required for online activities was more difficult than for face-to-face teaching. As Cerys said, “One of the problems that I’ve always struggled with active learning online is thinking about how long this active learning activity will take with students.” Level 3b Mechanical New Skills represents some instructors’ efforts to adopt advanced skills for online active learning despite other reports of ineffective online course design . Some participants endeavored to make adopting active learning in online classes easier by equipping themselves with and applying these skills. Instructors shared that they tried to integrate digital tools to engage students in synchronous classes, build in accountability to boost student engagement in group activities, and establish trust and rapport with students to reduce students’ anxiety and encourage student engagement during class. For example, Maxine said, “I always send a funny, very personal video before class starts, and let them know about me, my family, my dogs, how long I’ve been teaching, my teaching style. And then, I asked them to do that.” Instructors also provided one-on-one virtual meetings for office hours to develop trust and connections with and between students. At the level of 4a-Routine, instructors established a pattern of regular use of active learning online. Rather than focusing on learning new skills or strategies, some instructors set up specific steps or schedules to adopt active learning strategies in online environments. They shared that, to facilitate their adoption of active learning, they proposed flexible course policies and established connections with students through after-class surveys and office hours. Some instructors also mentioned their abilities to use technology for asynchronous and synchronous instruction . A conversation between Caitlin and Chole illustrates a good example of flexible course policies. They began by sharing their strict course policies; for example, Caitlin said, “I made them [students] have deadlines three times a week versus once a week…I have a policy of 50% off credit if [students] turn it in late.” They then mentioned providing flexibility for students. Chole said, “I polled the students before this class started and I said, ‘Do you want me to hold you to that same schedule or would you like me to give you more freedom and I can open a window for your exam?’” Both instructors reported positive results that seemed to translate to more effective active learning in the online setting. Results of CBAM-SoC The Stages of Concern dimension of CBAM represents an instructor’s concerns about adopting active learning in an online setting, and it reflects instructors’ attitudes, feelings, and perspectives. Based on the segments coded, both stages 3-Management and 4-Consequence comprised two themes (with up to three sub-themes each, Table 6). Stage 3-Management illustrates that, as instructors began to implement active learning in online settings, their concerns about logistics (e.g., classroom management and execution of active learning online) and considerations of new behaviors (e.g., strategies to engage students and transition laboratory courses online) intensified. Accordingly, this stage has two themes: anticipation of logistical issues and consideration of new behaviors . Some instructors mentioned that they could anticipate logistical issues related to classroom management and organization , while others reported feeling frustrated with the choice of asynchronous or synchronous teaching modes . Additionally, their concerns about execution of online activities , such as group activities, intensified when they discussed hybrid courses combining face-to-face and online instruction. Some instructors also stated that they considered actions to facilitate moving laboratory or hands-on courses to online settings and achieving the enhancement for student engagement. During the focus group, Mia described two plans to promote student engagement: (1) to find a way to allow students submit answers and discussion by using technology and (2) to develop rapport with and between students. The 4-Consequence stage illustrates that instructors focused on the impacts of online environments on students’ active learning. At this stage, instructors were predominantly concerned about the impacts of online active learning on students (i.e., awareness of impacts on students ) and how to assess the effectiveness of active learning in an online environment (i.e., assessment of the effectiveness of instruction ). Instructors reported that they became frustrated when they perceived low learning outcomes and limited learning experiences as a result of anticipated challenges in adopting active learning in online settings. Instructors’ awareness of impacts on students further represents their concerns about the differences between face-to-face and online teaching , inequity caused by students’ unequal access to resources , and the benefits of online active learning in terms of the learning experience, learning outcomes, skill development, and persistence. For example, Madeline stated that online biology education could not enable students to acquire the real-world skills needed in the field and further expressed strong anxieties about potential issues such as student attrition and department closures. The application of the FCBF framework To provide a separate lens (i.e., the FCBF) to our analysis of barriers faced by instructors when adopting active learning during an abrupt transition to online instruction and to answer our second research question (i.e., How does FCBF identify and explain the barriers faced by STEM instructors in adopting active learning during an abrupt transition to online instruction? ), we coded our segments into the four categories of this framework – instructor, student, teaching, and institution (Table 7). Three themes emerged in the instructor, student, and institution categories, and five emerged in the teaching category. Each theme has various sub-themes. The instructor category represents instructors’ perceptions of their personal conditions, which may influence the adoption of online active learning. Within this category, there are three main themes: time constraints , instructor comfort , and loss of control over class (e.g., Instructors felt disconnected with their students because they were unable to “read” the virtual room and see students’ facial expressions and body language). Time constraints represent a common concern shared by instructors. They reported that, compared with face-to-face classes, they had to spend much more time planning courses for asynchronous or synchronous modes and made additional efforts to build relationships with and among students online. Instructor comfort pertains to discomfort with their role change from teaching to learning, discomfort with hybrid teaching modes in subsequent semesters, and discomfort with online active learning when attempting to apply their preferred activities in online settings. For instance, Madeline said, “I love discussions, and I love asking tough questions and get people squirming, but it’s really kind of dangerous I feel to do it on this kind of platform.” The student category represents how student concerns, as perceived by instructors, can be a challenge when instructors abruptly implement active learning in an online setting. There are three main themes: student engagement , student preparation , and student expectations . Lack of student engagement is the primary theme in this category and comprises two sub-themes. Instructors shared that there was sometimes a lack of participation in learning activities even when students attended class. For example, Cai noted, “I find it to be a challenge with some of the students... it’s hard for them to show up online and do this [participate in activities] because they’re not accustomed to it [the online environment].” Some instructors also reported that although students may participate in activities, there was a lack of genuine engagement with learning activities , as noted by Charlotte: “...if the activity requested a bit more time, then they would complain, they would send me a lot of emails...” The teaching category pertains to challenges encountered by instructors while adopting active learning in online classes, and it has five main themes: instructional support , logistical issues , assessment and evaluation , course type , and class size . The theme of instructional support includes students’ inaccessibility to learning tools and a lack of support from staff[2] and teaching assistants (TAs). For instance, Daphne said, “In the online class, I do not have a TA or anyone to help. So, when I’m helping a student, other students are waiting.” The logistical issues theme covers barriers to the administration of group activities, the time to deliver synchronous courses as instructors mentioned that extra time and attention were needed to explain content clearly, and conducting courses in an asynchronous mode . Additionally, the theme of assessment and evaluation pertains to barriers related to a lack of knowledge for assessing online active learning , developing and communicating rubrics to students , and identifying the benefits of online active learning . Although instructors agreed on the advantages of online learning activities, they were unable to assess the extent to which students benefited from these activities. For class size , instructors reported different experiences. Some instructors, like Desmond, stated that large classes (e.g., more than 70 students) made it “intrinsically more challenging” to use active learning, while other instructors noted that small online classes were not conducive for active learning. As Darcy shared, “…if you have a really small class size and only six students, I’m definitely struggling with that [conducting group discussion].” Within institution as a category of challenges to online active learning, there are three main themes: institutional support , teaching modes , and support for adjunct faculty [3]. Institutional support illustrates that instructors noted institutions failed to provide sufficient and appropriate technology support (e.g., digital tools) to them and their students. Additionally, although some institutions offered related professional development which aimed to help instructors adjust to online teaching, the time required was unrealistic for instructors to commit to it. The theme of teaching modes refers to that, in some institutions, instructors did not have the option to select their teaching mode as synchronous or asynchronous – they were required to teach in an assigned mode. However, some instructors believed that it should be instructors who decide on how to teach instead of their institution. Diana stated, “...the way that you think that a course is best taught is not the way the institution wants it to be taught.” In contrast, the theme of institution category, support for adjunct faculty , was only shared by instructors from community colleges who noted that hiring adjunct faculty, who tend to be external and part-time instructors, was a common practice of community colleges. Full-time instructors reported that besides preparing for their own course, they had to prepare different course materials for adjunct faculty who declined to use active learning components. The application of the two frameworks together To answer our third research question (i.e., How do the two frameworks work together to shed insight on the challenges instructors faced and the strategies they used when adopting active learning during an abrupt transition to online instruction ), we matched the sub-themes of the results from the CBAM (i.e., categories of behaviors and stages) with the sub-themes of the results from the FCBF (i.e., individual and contextual barriers) (Tables 8-10). We also noted that some of the themes of LoU pertain to challenges (e.g., logistical online teaching ), while others represent concrete strategies (e.g., flexible course policies ). The themes of SoC mainly describe instructors’ attitudes, beliefs, and feelings that challenge their usage of active learning in online settings. We then classified the challenges STEM instructors faced while adopting active learning during an abrupt transition to online environments into two categories: behavior-based challenges with relevant barriers (Table 8) and concern-based challenges with relevant barriers (Table 9). In the following paragraphs, we elaborate on these two types of challenges and the strategies tackling relevant barriers (Table 10). Challenges Instructors Face When Using Active Learning While Abruptly Transitioning to Online Instruction Behavior-based challenges represent STEM instructors’ behavioral characteristics (i.e., those identified by the CBAM) and associated individual and contextual factors (i.e., those identified by the FCBF) that they encountered when using active learning in an online environment with very limited preparation. Concern-based challenges , on the other hand, address STEM instructors’ feelings, perceptions, and beliefs about using active learning in a suddenly shifting context (i.e., those identified by the CBAM) and associated individual and contextual factors (i.e., those identified by the FCBF). Behavior-based challenges focus on challenges faced by STEM instructors when they actually used active learning in their online courses during the pandemic, while concern-based challenges emphasize STEM instructors’ affective responses to anticipated issues, potential impacts on students, and decision-making on future plans and certain strategies. Behavior-based challenges include instructors’ difficulties mainly related to mechanical logistics (e.g., conducting hands-on activities in online settings and logistical online teaching ), with a theme of mechanical new skills (e.g., issues of online courses design ) (Table 8). Although we provided definitions of active learning during the focus groups and invited participants to share their experiences with adopting active learning during the pandemic, many challenges reported by STEM instructors are associated with 3a-Mechanical logistics. This finding indicates that most participants struggled with the initial steps of adopting active learning in online settings (Hall & Hord, 1987; Hall & Hord, 2020). The findings, intertwined with the broader challenges of online education, may suggest that instructors’ adoption of active learning is closely associated with their teaching modality (e.g., face-to-face, online, or blended settings), especially for those who are exposed to a specific modality for the first time. Our results also indicate that, without substantial preparation and support, it is challenging for instructors to successfully adopt active learning in online settings (Hall & Hord, 2020). It is noticeable that most behavior-based challenges are associated with both individual barriers (i.e., the instructor category in the FCBF) and contextual barriers (i.e., the categories of student, teaching, and institution in the FCBF). Take, for example, devote time to prepare online active learning (a sub-theme of CBAM-LoU’s Level 3a-Mechanical Logistics). Instructors who noted this as a challenge were influenced by contextual factors of the FCBF, such as student engagement (e.g., the difficulty of designing learning materials that actually engaged students) and logistical issues (e.g., the uncertainty of managing activities), as well as individual factors of the FCBF such as time constraints (e.g., searching for learning activities was time-consuming). This finding may suggest that certain behavioral characteristics of STEM instructors are associated with both contextual and individual barriers and these two types of barriers can be interconnected. Accordingly, to assist STEM instructors in avoiding or overcoming related challenges, researchers and support agents should investigate both underlying contextual and individual barriers comprehensively. In contrast to behavior-based challenges predominantly linked with 3b-Mechanical Logistics (Table 8), concern-based challenges involve two types of stages (i.e., Task and Impact in Table 1). Table 9 illustrates issues related to STEM instructors’ affect, widely covering both contextual and individual barriers. This suggests that STEM instructors were not only concerned with the process of their adoption of active learning in online settings but also with its impact on their students. In addition, the difference in the frequency of the FCBF’s sub-theme assessment and evaluation in Table 8 and 9 suggests that while participants reported fewer behaviors related to assessing the effects of their use of active learning, they expressed concerns about the potential consequences on their students while adopting active learning in their online courses. Table 9 also demonstrates that factors of the FCBF align well with SoC themes of 3-Management and 4-Consequence. For example, the SoC Stage 4-Consequence suggests instructors’ major concerns about online active learning pertain to barriers of teaching category in the FCBF, especially the sub-themes of assessment and evaluation . This may indicate that instructors who are concerned about the impacts of online active learning on students may need knowledge and resources for assessment and evaluation. In addition, institutional support is the other theme of the FCBF influencing instructors’ concerns about students’ unequal access to resources (a sub-theme of Stage 4-Consequence). Together, these issues raise the question of whether higher education institutions, in terms of instructors’ essential skills and support systems, are ready to implement a diverse educational model without increasing inequity and exclusivity. This question is worth considering, especially when many instructors and students prefer a blended instructional mode. The primary mapping of contextual factors of the FCBF, such as teaching (e.g., instructional support ) and institution (e.g., institutional support ), onto concern-based challenges in Table 9 suggests that instructors did not receive sufficient or appropriate support while adopting active learning during the abrupt transition to online instruction. Many participants had to manage logistics and handle issues on their own, which made it more difficult to adopt active learning in their courses. As novices, instructors typically faced challenges in applying relevant teaching strategies and using technology to engage students in online environments while making the initial steps towards active learning in online settings. Strategies Instructors Use When Using Active Learning While Abruptly Transitioning to Online Instruction Table 10 presents strategies employed by STEM instructors to address the challenges they faced while adopting active learning online during the pandemic. The strategies identified at level of 3b-Mechnical New Skills suggest that the adoption of active learning online by STEM instructors necessitates equipping them with relevant skills and knowledge. When they initially applied face-to-face active learning skills (e.g., in Level 3b-Mechanial New Skills), instructors focused on student engagement of the FCBF. When instructors were focused less on mechanical logistic issues, they attempted strategies that primarily engaged students (such as using online discussion forum and self-introduction videos for improving student-peer and student-instructor interactions and building trust between them). As instructors became familiar with these skills and more flexible in applying active learning pedagogies, they prioritized building connections and rapport with their students and utilized technologies to engage them with learning materials. They were more likely to establish regular patterns of use (e.g., in Level 4a-Routine) and to address other barriers such as the individual FBCF factor loss of control . Instructors perceived a loss of control and attributed it mainly to the disconnection with students in online environments. They instead used peer review, quizzes embedded in videos, and after-class reflection surveys to collect information about students’ learning outcomes and experiences. This implied that instructors not only focused on their personal needs while implementing online active learning, but they also valued student learning outcomes and learning experiences. However, some of them did not know how to effectively do these, which may suggest that, in this situation, instructors need more support to address the FCBF theme of assessment and evaluation . Interestingly, the FCBF theme of institution does not appear in Table 10, which suggests that at these two levels of use (i.e., Level 3b-Mechanical New Skills and Level 4a-Routine), instructors did not attempt to use strategies to address institutional barriers. This could imply that instructors paid more attention to their courses (e.g., engaging students, applying in-person active learning skills, or conducting assessment and evaluation), than addressing institution barriers (e.g., accessing to digital tools or determining teaching modes), or that there were no relevant institutional barriers. Summary Applying the CBAM framework enabled us to classify the primary behaviors and main concerns of STEM instructors during the process of adopting active learning in an abrupt transition to online instruction. Most behaviors were classified at levels 3a-Mechanical Logistics and 3b-Mechanical New Skills. Predominately focusing on dealing with logistics and attempting to learn new skills to facilitate their adoption indicates initial steps in using active learning in online settings (Anderson, 1997; Hall & Hord, 2020). Although some instructors established a pattern of regular use of active learning in online settings (i.e., 4a-routine), many participants experienced ineffective adoption in their online courses during the pandemic. Participants’ concerns spanned stages from 3-Management (Task category in Table 1) to 4-Consequence (Impact category in Table 1), reflecting intensified logistical concerns and considerations of new strategies in their implementation of active learning in online instruction. Instructors also shared concerns about the impact of online active learning on students’ learning and how to assess its effectiveness. Applying the FCBF framework allowed us to identify individual (i.e., instructor category) and contextual (i.e., teaching, student, and institution categories) barriers faced by STEM instructors in adopting active learning during an abrupt transition to online instruction. The instructor category represents individual factors and revealed that participants perceived personal conditions related to time, comfort, and control over the class as influencing factors. In contrast, the teaching, student, and institution categories of the FCBF framework represent contextual barriers impacting STEM instructors during the abrupt transition. From participants’ perspectives, teaching-related barriers included logistics, course characteristics (e.g., course type, class size), assessment methods, and instructional support. Participants also faced challenges in engaging students and meeting their expectations in the remote teaching modality. Institutional barriers included policies related to support and teaching modes and influenced their use of active learning in online settings. Our application of dual frameworks, and more specifically the relevance of the specific stages of adoption processes, indicates that tailored instructional support is a promising approach for supporting instructors. The dual application of the CBAM and FCBF frameworks revealed behavior-based and concern-based challenges with individual and contextual influences during STEM instructors’ rapid adoption of online active learning. For instance, the frequent associations of student engagement (a sub-theme of the FCBF) with different behavior-based and concern-based challenges (sub-themes of the CABM LoU and SoC) illustrate student engagement is a significant common factor influencing the process of instructors’ adoption of online active learning. In addition, the strategies instructors use to implement online active learning (e.g., build in accountability , establish trust and rapport , and applying flexible course policies ) are mainly applied to increase student engagement. These findings suggest that student engagement is a primary focus for STEM instructors throughout the process of adopting active learning in online settings. Compared with student engagement , time constraints (a sub-theme of the FCBF) seems to be less critical but remains a significant challenge for instructors, also spanning to contextual factors such as teaching and institution categories. Time constraints related to challenges instructors faced with the CBAM theme of logistical online teaching , online course design, and anticipation of logistical issues . In addition, it is identified as a theme within the instructor factor in the FCBF framework, but the time-related issues also emerge under the teaching factor – Logistical issues (Table 7). The association between devote time to prepare online active learning and support for adjunct faculty (Table 8) suggest that contextual factors related to institutions influence instructors’ time commitment to instructional change. These findings may emphasize that time is not a standalone barrier to instructors’ adoption of active learning for instructors (Authors, 2023). Limited time may stem from tensions between teaching and research, demands for classroom preparation, the need for professional development, or institutional policies (Authors, 2023; Finelli et al., 2014). In summary, applying both frameworks (the CBAM and the FCBF) offers a more nuanced perspective for mapping individual and contextual barriers across different stages of the instructional change process. This dual approach enables us to develop targeted strategies to deliver customized support for instructors’ specific needs while implementing an instructional change. Table 5 Themes about behaviors identified when applying CBAM Levels of Use Level Themes Sub-themes 3a-Mechanical Logistics Hands-on activities None Logistical online teaching Engage students in synchronous classes Promote student motivation for online activities Devote time to prepare online active learning 3b-Mechanical New Skills Online course design None Advanced skills for online active learning Integrate digital tools Build in accountability Establish trust and rapport 4a-Routine Flexible course policies None Technology for asynchronous and synchronous instruction None Connection with students None Table 6 Themes about concerns identified when applying CBAM Stages of Concern Stages Themes Sub-themes 3-Management Anticipation of logistical issues Classroom management and organization Asynchronous or synchronous teaching modes Execution of online activities Consideration of new behaviors Hands-on courses Enhancement for student engagement 4-Consequence Awareness of impacts on student Differences between face-to-face and online teaching Unequal access to resources Benefits of active learning online Assessment of the effectiveness of instruction None Table 7 Themes about barriers identified when applying the FCBF Category Theme Sub-theme Instructor Time constraints Planning courses Building relationships Instructor comfort Role change Online active learning Hybrid teaching modes Loss of control None Student Student engagement Participation in learning activities Engagement with learning activities Student preparation None Student expectations None Teaching Instructional support Learning tools Support from staff and teaching assistants Logistical issues Administration of group activities Time to deliver synchronous courses Asynchronous mode Assessment and evaluation Knowledge for assessing online active learning Communicating rubrics Benefits of online active learning Course type None Class size None Institution Institutional support Technology support Professional development Teaching modes None Support for adjunct faculty None Table 8 Behavior-based challenges faced by STEM instructors while their adoption of active learning during an abrupt transition to online instruction CBAM: Levels of Use FCBF Themes and sub-themes Level Themes Sub-themes 3a-Mechanical Logistics Hands-on activities None Teaching: Instructional support, Course type Institution: Institutional support Logistical online teaching Engage student in synchronous classes Student: Student engagement Instructor: Loss of control, Time constraints Teaching: Logistical issues Promote student motivation for online activities Student: Student engagement, Student expectation Devote time to prepare online active learning Student: Student engagement Teaching: Logistical issues Instructor: Time constraints Institution: Support for adjunct faculty 3b-Mechanical New Skills Online course design None Student: Student engagement, Student preparation Teaching: Logistical issues, Assessment and evaluation, Course type, Class Size Instructor: Time constraints Table 9 Concern-based challenges faced by STEM instructors while their adoption of active learning during an abrupt transition to online instruction CBAM: Stages of Concern FCBF Themes and sub-themes Stages Themes Sub-themes 3-Management Anticipation of logistical issues Classroom management and organization Student: Student engagement Teaching: Instructional support, Logistical issues Instructor: Time constraints Asynchronous or synchronous teaching modes Teaching: Instructional support, Logistical issues, Institution: Teaching Modes Execution of online activities Teaching: Logistical issues, Instructional support, Class size Instructor: Instructor comfort Institution: Teaching modes Consideration of new behaviors Courses with hands-on activities Teaching: Instructional support, Course type Enhancement for Student engagement Student: Student engagement 4-Consequence Awareness of impacts on student Differences between face-to-face and online teaching Teaching: Assessment and evaluation Unequal access to resources Teaching: Assessment and evaluation Institution: Institutional support Benefits of active learning online Teaching: Assessment and evaluation Assessment of the effectiveness of instruction None Teaching: Assessment and evaluation Table 10 Strategies used by instructors used by STEM instructors while their adoption of active learning during an abrupt transition to online instruction CBAM FCBF Themes and sub-themes Levels Themes Sub-themes 3b-Mechanical New Skills Advanced skills for online active learning Integrate digital tools Student: Student engagement Build in accountability Student: Student engagement, Student expectation Establish trust and rapport Student: Student engagement Instructor: Loss of control 4a-Routine Flexible course policies None Student: Student engagement, Student expectations Teaching: Assessment and evaluation Technology for asynchronous and synchronous instruction None Student: Student engagement, Student preparation Instructor: Instructor comfort, Loss of control Connection with students None Instructor: Loss of control Discussion Reflection on the Application of Two Frameworks Together As we stated, fully understanding the process of an instructor’s adoption of an instructional change and the relevant contextual and individual barriers is challenging when applying only one change theory. By applying multiple theories, we gain a more nuanced perspective on implementing instructional changes. These results from applying the two frameworks align with existing literature, particularly the barriers identified by the FCBF framework (e.g., Çakıroğlu et al., 2021 ; Dumont et al., 2021 ). However, using only one of the two change frameworks makes it challenging to comprehensively depict the barriers faced by STEM instructors at various stages of their adoption process. Failing to identify barriers at specific stages of STEM instructors’ adoption further complicates providing appropriate support, which may significantly increase the likelihood of unsuccessful adoption of active learning in online settings (Hall & Hord, 2020 ). In our case, while some strategies employed by STEM instructors facilitated more effective use of active learning in their online courses, others could not achieve the same level of effectiveness, especially if they were not at similar stages in their adoption process. For example, Çakıroğlu and colleagues ( 2021 ) quantitatively explored how factors such as instructional support, institutional guidance, student-instructor interaction, prior experiences, and teaching modes influenced Turkish instructors’ adoption of online teaching during the pandemic. They found support and interaction factors are crucial concerns for participants using technology in their online teaching. To enhance flexibility, many universities have recognized the need to equip their instructors with educational technology integrated with pedagogical knowledge, facilitating various modes of delivery (e.g., face-to-face, online, and blended instruction; Alexander et al., 2019 ; Huang, 2020 ; Keane et al., 2022 ; Peimani and Kamalipour, 2021 ; Rapanta et al., 2020 ). However, instructors vary in their pedagogical knowledge and process of integrating technology into their courses, suggesting the need for tailored support to accommodate different instructors’ adoption of instructional changes. The findings drawn by applying the CBAM and the FCBF together provide more comprehensive insight into the challenges instructors face and the strategies they use while adopting active learning during the abrupt transition to online instruction. Our synthesized findings indicate that specific behaviors and concerns of STEM instructors are intricately linked with contextual and individual barriers. These barriers vary at different points in the adoption process, which suggests the need for different types of support and resources. An instructional change process is not linear if the change is not carefully facilitated, appropriately supported, and well-prepared with sufficient time (Hall & Hord, 2020 ). In these situations, the change progress is more likely arrested at a certain point (e.g. most participants’ behaviors located at 3a-Mechanical Logistics with various barriers) or returned to previous levels or stages (e.g., instructors tended to give up on their favorite learning activities). The combined lens implies that supporting STEM instructors does not entail providing a one-size-fits-all approach, as such an approach can be overwhelming and inefficient. Instead, support agents should assist instructors in identifying their unique challenges and determining appropriate strategies. Moreover, instructors’ professional development is an intensive and ongoing activity in which there is a lag between obtaining pedagogical knowledge and implementing the practices, and instructors may encounter various barriers during the process of adoption (Borda et al., 2020 ; Hall & Hord, 2020 ; Stigler & Miller, 2018 ). This suggests that professional development should be adaptable and sustained in a way to address instructor’s needs at various stages (Borda et al., 2020 ). When one applies CBAM to address instructors’ behaviors and concerns, it is hard to identify the related factors influencing these problems. Although the CBAM’s SoC themes appear to be similar to those of the FCBF, CBAM tends to describe a challenge from the affective perspective of the instructor, while the FCBF is more likely to explain external causes behind the experience. For example, when an instructor challenged by asynchronous and asynchronous teaching modes (a sub-theme of CBAM’s SoC Stage 3-Management), the CBAM framework provides no additional insight. However, in combination with the FCBF, it is possible to determine whether the issue is related to the instructor’s teaching (e.g., instructional support and logistical issues) or institutional policies (e.g., teaching modes ). Accordingly, integrating the CBAM framework with the challenges aligned with the FCBF can shed insight on the challenges instructors face when they are forced to abruptly adopt online active learning and their responses. We found that when instructors initially adopted online active learning with very limited preparations, most of their behaviors are classified as Level 3-Mechanical Use. This prevented us from further categorizing faculty behaviors and identifying the challenges they face and the strategies they took, and it led us to subdivide that level into 3a-Mechanical Logistics and 3b-Mechanical New Skills. Instead, the FCBF seems well suited to the context of implementing online active learning. This may imply that challenges related to who teaches (instructor), who is taught (student), how to teach (teaching), and where to teach (institution), which are themes of the FCBF, emerge when making an instructional change, regardless of the educational delivery modes and pre-adoption conditions (e.g., preparation for instructional change). Limitations Despite interesting insights found in our study, it does have limitations related to both our application of two frameworks and our case sample. The primary limitation is that we did not incorporate both the CBAM and FCBF frameworks at the early stage of our research design. Ideally, the combination of CBAM and FCBF should have informed our research purposes and data collection; however, we decided to apply both change frameworks during the data analysis phase. The later inclusion of CBAM may have prevented us from collecting more enriched data related to change processes and indeed required additional time and effort. Nonetheless, given that our application of dual change frameworks was an evolving process, we adjusted our approach as the research progressed and drew meaningful insights from the combined frameworks. There are also limitations related to our case sample. First, the size and composition of our sample may hinder us from drawing a complete picture. We interviewed 32 instructors, and most (around 72%) were female instructors. Saw and colleagues ( 2023 ) claim that female faculty shared a higher level of anxiety and had more online teaching challenges during the pandemic than male faculty, so our data may be somewhat skewed. As well, we recruited only one instructor (including lecturers and professors) at each of the 32 institutions, so our study provides limited information related to some factors, such as instructors’ teaching roles and departmental environments. Our study is also limited because we did not fully consider instructors’ prior teaching experiences in terms of active learning and online instruction. Unfortunately, we collected only very basic information about instructors’ prior teaching experiences, and it was not sufficient to include in our analysis. We acknowledge that including more detailed information about instructors’ prior experience could enrich our findings. However, some evidence suggests that there is not a direct relationship between the length of teaching experience and the quality of teaching (Graham et al., 2020 ; Stigler & Miller, 2018 ). Another limitation is related to our broad definition of active learning, which may prevent us from drawing more in-depth conclusions about adopting specific types of active learning in online settings. We defined active learning as “using individual or group activities to engage students in their learning during class,” while some scholars may challenge that our definition of active learning is “an umbrella term that is not particularly useful in advancing research on learning.” (Lombard et al., 2021, p 8). Future studies could further investigate the process of STEM instructors’ adopting a specific active learning strategy in an online setting. Conclusion In this study, we demonstrate the dual application of two separate change frameworks to investigate a systemic instructional change: STEM instructors from different institutions adopting active learning during an abrupt transition to online environments. Our investigation focused on change processes and barriers at both individual and contextual levels. We applied the CBAM, a process-oriented instructional change theory, to illustrate STEM instructors’ behaviors and concerns throughout the adoption process. Simultaneously, we utilized the FCBF, a framework designed to identify barriers in face-to-face instruction, to explain individual and contextual influences. We then synthesized the results of CBAM and FCBF to identify challenges, strategies, and their relevant barriers, providing a combined lens to comprehensively study instructional changes. Our study also provides some sights for the study case (STEM instructors from different institutions adopting active learning during the pandemic). From the instructor’s perspective, the abrupt adoption of active learning in an online environment with limited preparation was more challenging than implementing active learning in a face-to-face setting. Although participants reported various challenges in teaching online (e.g., low student attendance due to different time zones, limited learning environments at home, or issues related to student honesty and ethics), we focused primarily on challenges and strategies pertaining to adopting active learning in online environments. Our results of applying two frameworks together to study the case sample demonstrate that, while abruptly transitioning to online settings, the STEM instructors in our study encountered various challenges related to mechanical issues (e.g., conducting hands-on activities, handling logistics of online teaching, and designing online courses). We found that some instructors attempted to use strategies (e.g., applying advanced skills for online active learning, implementing flexible course policies, using technology for asynchronous and synchronous instruction, and building connections with students) to overcome these issues. These challenges encompass both individual influences (e.g., time constraints, instructor comfort, and loss of control) and contextual influences (e.g., student engagement, student preparation, assessment and evaluation, instructional support, and institutional support). In addition, some instructors were able to anticipate challenges and consider potential solutions (e.g., anticipating logistical issues and considering new behaviors), and some were concerned about the impacts of unexpected change on their students and ways to assess them (e.g., being aware of impacts on student and attempting to assess the effectiveness of instruction). The findings from combining CBAM and FCBF suggest that when instructors adopt an instructional change without sufficient preparation and support, they are likely to face behavior-based challenges at the initial levels of use, although their concerns may be widely distributed across two categories of SoC (Task and Impact; See Table 1 ). It should be noted that a specific challenge may be triggered by both contextual and individual factors. Further, some factors of the FCBF are commonly present across different levels and stages of CBAM (e.g., student engagement in our study), while other factors of FCBF (e.g., assessment and evaluation in our study) are specific to certain levels and stages. We recommend that support (e.g., professional development and interventions) should be tailored to meet instructors’ needs and should address factors at various steps of instructors’ adoption of an instructional change. Declarations Acknowledgments The authors gratefully acknowledge the support of instructors who participated in the project. Authors’ contributions Author 1: Conceptualization, Methodology, Formal analysis, Writing- Original draft; Author 2: Conceptualization, Methodology, Formal analysis, Writing- Review and editing; Author 3: Methodology, Formal analysis, Writing- Review and editing; Author 4: Conceptualization, Methodology, Writing- Review and editing; Author 5: Conceptualization, Methodology, Supervision, Writing-Review & editing, Project administration. Funding This material is based upon work supported by the National Science Foundation (Grant #XXX). Any opinions, findings, conclusions, and recommendations expressed are those of the authors and do not necessarily reflect the views of the National Science Foundation. Availability of data and materials The datasets created and analyzed in this study are not available to the public because of participant privacy and confidentiality but are available to request from the corresponding author under reasonable circumstances. 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Teachers who initiate changes with an ebook-integrated curriculum: Revisiting the developmental assumptions of stages of concerns in the concerns-based adoption model. Alberta Journal of Educational Research, 63 (1), 21–42. Nelson, J. K., Rosenberg, J., Fernández, K., & Shank, J. (2021, July). Where’s my whiteboard?: The challenge of moving active-learning mathematics classes online. In 2021 ASEE Virtual Annual Conference Content Access. Ng, D. T. K. (2022). Online aviation learning experience during the COVID-19 pandemic in Hong Kong and Mainland China. British Journal of Educational Technology, 53 (3), 443–474. Nguyen, K. A., Borrego, M., Finelli, C. J., DeMonbrun, M., Crockett, C., Tharayil, S., Shekhar, P., Waters, C., & Rosenberg, R. (2021). Instructor strategies to aid implementation of active learning: A systematic literature review. International Journal of STEM Education, 8 (1), 1–18. Olson, K., Lannan, K., Cumming, J., MacGillivary, H. & Richards, K. (2020). The Concerns-Based Adoption Model and strategic plan evaluation: Multiple methodologies to understand complex change. Educational Research: Theory and Practice, 31 (3), 49–58. O’Dea, X.C., & Stern, J. (2022). Virtually the same?: Online higher education in the post Covid-19 era. British Journal of educational technology, 53 (3), 437. Peimani, N., & Kamalipour, H. (2021). Online education and the COVID-19 outbreak: A case study of online teaching during lockdown. Education Sciences, 11 (2), 72. Prince, M., Felder, R., & Brent, R. (2020). Active student engagement in online STEM classes: Approaches and recommendations. Advances in Engineering Education, 8 (4), 1–25. Radiker, S., & Kuckartz, U. (2020). Focused analysis of qualitative interviews with MAXQDA: Step by step . MAXQDA Press. Rapanta, C., Botturi, L., Goodyear, P., Guàrdia, L., & Koole, M. (2020). Online university teaching during and after the Covid-19 crisis: Refocusing teacher presence and learning activity. Postdigital science and education, 2 , 923–945. Reinholz, D. L., & Andrews, T. C. (2020). Change theory and theory of change: what’s the difference anyway?. International Journal of STEM Education, 7 , 1–12. Reinholz, D. L., White, I., & Andrews, T. (2021). Change theory in STEM higher education: A systematic review. International Journal of STEM Education, 8 (1), 1–22. Rogers, E. M. (2003). Diffusion of Innovations (5th ed., pp. 166–206). Free Press. Saldaña, J. (2013). The coding manual for qualitative researchers . Sage. Saw, G. K., Chang, C. N., & Lin, S. (2023). Gender disparities in remote teaching readiness and mental health problems among university faculty during the COVID-19 pandemic. Educational and Developmental Psychologist, 40 (1), 131–140. Shim, T. E., & Lee, S. Y. (2020). College students’ experience of emergency remote teaching due to COVID-19. Children and Youth Services Review, 119 , 105578. Singhal, R., Kumar, A., Singh, H., Fuller, S., & Gill, S. S. (2021). Digital device-based active learning approach using virtual community classroom during the COVID‐19 pandemic. Computer Applications in Engineering Education, 29 (5), 1007–1033. Stains, M., Harshman, J., Barker, M. K., Chasteen, S. V., Cole, R., DeChenne-Peters, S. E., … Young, A. M. (2018). Anatomy of STEM teaching in North American universities. Science, 359 (6383), 1468–1470. Stigler, J. W., & Miller, K. F. (2018). 24 Expertise and Expert Performance in Teaching. In Ericsson, K. A., Hoffman, R. R., Kozbelt, A., & Williams, A. M. (Eds.), The Cambridge handbook of expertise and expert performance (pp. 431–452). Cambridge University Press. Sturtevant, H., & Wheeler, L. (2019). The STEM faculty instructional barriers and identity survey (FIBIS): Development and exploratory results. International Journal of STEM Education, 6 , 1–22. Theobald, E. J., Hill, M. J., Tran, E., Agrawal, S., Arroyo, E. N., Behling, S., Chambwe, N., Cintrón, D. L., Cooper, J. D., Dunster, G., Grummer, J. A., Hennessey, K., Hsiao, J., Iranon, N., Jones, L., Jordt, H., Keller, M., Lacey, M. E., Littlefield, C. E., & Freeman, S. (2020). Active learning narrows achievement gaps for underrepresented students in undergraduate science, technology, engineering, and math. Proceedings of the National Academy of Sciences of the United States of America, 117 (12), 6476–6483. Ting, F. S., Shroff, R. H., Lam, W. H., Garcia, R. C., Chan, C. L., Tsang, W. K., & Ezeamuzie, N. O. (2023). A Meta-analysis of Studies on the Effects of Active Learning on Asian Students' Performance in Science, Technology, Engineering and Mathematics (STEM) Subjects. The Asia-Pacific Education Researcher, 32 (3), 379–400. Venton, B.J., & Pompano, R.R. (2021). Strategies for enhancing remote student engagement through active learning. Analytical and Bioanalytical Chemistry, 413 , 1507–1512. Vonderwell, S., & Turner, S. (2005). Active learning and preservice teachers’ experiences in an online course: A case study. Journal of technology and teacher education, 13 (1), 65–84. Wilson, B. M., Pollock, P. H., & Hamann, K. (2007). Does active learning enhance learner outcomes? Evidence from discussion participation in online classes. Journal of Political Science Education, 3 (2), 131–142. Yan, J., Liu, S., Armwood-Gordon, C., & Li, L. (2024). Factors affecting active flipped learning on underrepresented students in three STEM courses. Education and Information Technologies, 29 (9), 10791–10804. Zhao, Y., & Watterston, J. (2021). The changes we need: Education post COVID-19. Journal of Educational Change, 22 (1), 3–12. Zimmerman, J. (2020). The amateur hour: A history of college teaching in America . Johns Hopkins University Press. Footnotes Instructors here refers to individuals who teach college courses in American higher education institutions. They include tenure-track faculty (e.g., assistant professors, associate professors, and (full) professors), teaching-focused professors (e.g., teaching professors), and lecturers. In addition, Professor in the United States typically denotes academics employed to research and teach in higher education institutions (Macfarlane, 2013 ). Staff refers to employees who provide support for teaching and learning, research, and service programs within American higher education institutions. Adjunct faculty here refers to instructors who are temporarily employed to teach courses at American higher education institutions. They are also known as part-time or contract faculty, and they typically hold non-tenure track positions (Fagan‐Wilen et al., 2006). Additional Declarations No competing interests reported. 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This latter shift has been particularly emphasized in STEM higher education, where research over the past three decades demonstrated that active learning enhances student learning (Freeman et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Haak et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Prince et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Singhal et al., \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Theobald et al., \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Ting et al., \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Yan et al., \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). As a result, scholars have advocated for transition instruction from traditional lecturing to active learning in STEM courses. Active learning refers to student-centered instruction that engage students in learning through individual or group activities, such as solving problems in small groups or participating in think-pair-share exercises (Nguyen et al., \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). When effectively implemented in online settings, active learning can increase student engagement (Chen et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Khan et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Hsu \u0026amp; Rowland-Goldsmith, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Prince et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Singhal et al., \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), improve learning outcomes (Singhal et al., \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Willson et al., 2007), and create more positive learning experiences (Khan et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Willson et al., 2007).\u003c/p\u003e \u003cp\u003eDespite these benefits, active learning has been adopted slowly in higher education, and traditional instructional practices (e.g., lecturing) remain dominant (B\u0026oslash;rte et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Reinholz \u0026amp; Andrews, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). STEM instructors[1]\u003ca class=\"FNLink\" href=\"#Fn1\" id=\"#FNLinkFn1\"\u003e\u003c/a\u003e have expressed difficulties in integrating active learning into their courses, leading to its limited usage in undergraduate STEM education in both face-to-face and online settings (Andrews \u0026amp; Lemons, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Authors, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Borda et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Finelli et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Hall et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2002\u003c/span\u003e; Khan et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Nelson et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Stains et al., \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn response, researchers and funding agencies, such as the United States National Science Foundation, clearly state the application of at least one theory of change as a critical component in research proposals focusing on implementing instructional change processes (Reinholz \u0026amp; Andrews, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Reinholz et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). This guidance emphasizes the integration of change theories for efforts aimed at achieving instructional changes in STEM higher education. Further, it helps ensure that planned activities are well-grounded in research and theory, providing a foundation on which to foster meaningful, generalizable, and lasting outcomes (Henderson et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Borrego \u0026amp; Henderson, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Reinholz \u0026amp; Andrews, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Here, change theory refers to an evidence-based framework of ideas that extends beyond single change initiatives, generalizes observations of changes, and enriches collective knowledge for explaining how change occurs (adapted from Henderson et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Reinholz \u0026amp; Andrews, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Reinholz et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eChange theories have been increasingly applied in studies on instructional change; however, the slow implementation of instructional changes in STEM higher education can be attributed, in part, to the misusage, superficial utilization, or a limited understanding of change theories by researchers or change agents (Borrego \u0026amp; Henderson, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Eblen-Zayas et al., \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Kezar et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Reinholz et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Change theories vary by rationale and assumptions, change strategies, and context (Henderson et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Reinholz et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). For example, Rogers\u0026rsquo; Diffusion of Innovation (2003) focuses on change processes, while expectancy-value theory has been applied to identify barriers or influences of adopting changes (e.g., Finelli et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). For a systemic instructional change (e.g., an instructional change across multiple STEM departments or institutions), it is difficult to identify a single change theory that can both study the change process and determine the related barriers.\u003c/p\u003e \u003cp\u003eMoreover, our literature review of articles published between 2014 and 2024 in the \u003cem\u003eInternational Journal of STEM Education\u003c/em\u003e, a peer-reviewed, high-impact STEM education journal, indicates that most research on applying change theories to understand STEM instructors\u0026rsquo; adoption of active learning has primarily focused on face-to-face instruction (i.e., the traditional teaching modality) and has typically relied on a single theoretical framework. Of the 42 articles identified as research on active learning instructional practices, 37 explicitly delineated the theoretical frameworks guiding their research design and interpretation of results (Authors, accepted). Ten papers incorporated two or three theories, most applying these frameworks at different research stages (Authors, accepted). For example, Czajka \u0026amp; McConnell (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) used the Interconnected Model to analyze the faculty\u0026rsquo;s professional development trajectory and identify the factors contributing to sustained instructional change. They also employed the theories of change to understand whether the instructor\u0026rsquo;s beliefs shifted before or after implementing reformed teaching strategies (Czajka \u0026amp; McConnell, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Reinholz et al. (\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) noted that \u0026ldquo;a given project could benefit most from multiple theories tailored together to meet its goals\u0026rdquo; (p. 17), a perspective echoed in prior literature (e.g., Kezar \u0026amp; Holcombe, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Reinholz \u0026amp; Andrews, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). From this, we can extrapolate the need for more research on instructional change applying multiple change theories to study instructional changes.\u003c/p\u003e \u003cp\u003eThe COVID-19 pandemic triggered systemic instructional changes in higher education, forcing STEM instructors who used active learning in person and who wished to continue using it to adopt it in online settings (Chamo et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Keane et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Nelson et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Venton \u0026amp; Pompano, \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Zhao \u0026amp; Watterston, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) and motivating others to use active learning for the first time in an online setting. The pandemic emphasized the significance of student-centered instruction and learners\u0026rsquo; autonomy due to unanticipated shifts from traditional face-to-face settings to fully online settings (Chamo et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Keane et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Zhao \u0026amp; Watterston, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The abrupt transition of college courses to online environments during the pandemic challenged STEM instructors\u0026rsquo; planned use of active learning (Huang, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Luburić et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Nelson et al., \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Venton \u0026amp; Pompano, \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), as most instructors had little to no experience with online teaching environments and struggled to adjust to that context. Many instructors initially relied on recorded lectures and basic assignments, without much consideration for more sophisticated use of technology (e.g., Shim \u0026amp; Lee, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn the post-COVID-19 setting, researchers report that instructors and students are more likely to prefer a blended or hybrid arrangement where face-to-face and online education are combined (Keane et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Ng, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Zhao \u0026amp; Watterston, 2022). To maximize the benefits of a blended arrangement, instructors need to redesign online and face-to-face course elements for their courses (O\u0026rsquo;Dea \u0026amp; Stern, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). This course redesign provides new and plentiful opportunities to support instructors as they implement active learning in both their face-to-face and online courses, especially as the pandemic may have shifted instructors\u0026rsquo; views of the efficacy of online technology, feasibility of its implementation, and potential benefits for them and their students (e.g., Abrahams, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Zhao \u0026amp; Watterston, \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).The far-reaching impact of the COVID-19 pandemic on STEM higher education highlights the need for more research into systemic changes; however, existing research on instructional change typically addresses individual changes rather than changes across STEM disciplines or organizations (Borrego \u0026amp; Henderson, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Reinholz et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe case of STEM instructors from different institutions adopting active learning in online settings during the pandemic presents an ideal opportunity to explore systemic changes. Therefore, this study aims to showcase the dual application of two change frameworks to investigate instructional change, specifically focusing on STEM instructors\u0026rsquo; adoption of active learning while abruptly transitioning to online instruction. The first framework is the Concerns-Based Adoption Model (CBAM; Hall \u0026amp; Hord, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), which views change as a process and is centered on the concerns of individual instructors. The second framework is the Four-Category Barrier Framework (FCBF; authors, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), which focuses on identifying barriers and emphasizes where the change is taking place. Using these two models together enables us to address change processes and barriers on both an individual and a systemic level. Hence, we seek to answer three main research questions:\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eRQ1: How does CBAM illustrate the process of STEM instructors\u0026rsquo; adoption of active learning during an abrupt transition to online instruction?\u003c/p\u003e\u003cp\u003eRQ2: How does FCBF identify and explain the barriers faced by STEM instructors in adopting active learning during an abrupt transition to online instruction?\u003c/p\u003e\u003cp\u003eRQ3: How do the two frameworks work together to shed insight on the challenges instructors face and the strategies they use when adopting active learning during an abrupt transition to online instruction?\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003eIn this paper, we first review the two change frameworks, explaining why these were chosen. We then describe our research methods and present our results to address the three research questions. Lastly, we reflect on the application of the two frameworks, consider limitations of this study, and present our conclusions.\u003c/p\u003e"},{"header":"Literature Review","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eConcerns-Based Adoption Model (CBAM)\u003c/h2\u003e \u003cp\u003eThe Concerns-Based Adoption Model (CBAM) is an empirically-grounded theoretical model that defines change as a process with a series of affective stages and behavioral levels through which individuals move (Anderson, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e1997\u003c/span\u003e; Hall \u0026amp; Hord, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e1987\u003c/span\u003e; Hall \u0026amp; Hord, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). CBAM was developed using data collected over more than two decades in an effort to understand, assess, and facilitate individuals (mainly teachers) who implement changes in educational institutions (Hall \u0026amp; Hord, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e1987\u003c/span\u003e; Hall \u0026amp; Hord, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The model has three independent diagnostic dimensions which can be used separately or combined with one another: Innovation Configuration (IC), Levels of Use (LoU), and Stages of Concern (SoC) (Hall \u0026amp; Hord, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). IC is used to clarify instructional change by describing the various operational forms of a change that are implemented. LoU identifies characteristic behavioral profiles of individuals by illustrating individual behaviors as they engage with the change. SoC identifies how individuals respond to change by describing the concerns (e.g., attitudes, beliefs, feelings, and perspectives) they have about implementing the change.\u003c/p\u003e \u003cp\u003eAs we apply the CBAM framework for our research, we define the \u0026ldquo;individual\u0026rdquo; to be the STEM instructor and the \u0026ldquo;change\u0026rdquo; to be adoption of active learning during an abrupt transition to online instruction. IC is outside the scope of our project because we focus on the processes of instructors\u0026rsquo; abrupt adoption of active learning in online settings across multiple institutions, rather than on participants\u0026rsquo; descriptions of the change itself. Accordingly, we use two dimensions (LoU and SoC) of CBAM to study change.\u003c/p\u003e \u003cp\u003eThe LoU dimension has been used frequently to study an individual\u0026rsquo;s behaviors when they prepare to use, begin to use, and obtain new skills and experiences. LoU has eight levels: 0-Nonuse, 1-Orientation, 2-Preparation, 3-Mechanical, 4a-Routine, 4b-Refinement, 5-Integration, and 6-Renewal (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e; Hall \u0026amp; Hord, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The main distinction between the eight levels is whether the instructor is a Nonuser (characterized by the LoU levels of 0-Nonuse, 1-Orientation, and 2-Preparation) or a User (characterized by the remaining five LoU levels of 3-Mechanical Use through 6-Renewal). In our case, Nonusers are instructors who have not implemented online active learning; while Users are those who have begun to use active learning in an online setting. In addition, instructors\u0026rsquo; behaviors categorized as Level 3-Mechanical Use suggest that they struggle with the initial steps of adopting active learning (Anderson, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e1997\u003c/span\u003e; Hall \u0026amp; Hord, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e1987\u003c/span\u003e; Hall \u0026amp; Hord, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Although some may take strategies to make the adoption of online active learning easier, the implementation process may still be inefficient (Hall \u0026amp; Hord, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe Levels of Use and Stages of Concern dimensions of CBAM\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eLevels of Use (LoU)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eStages of Concern (SoC)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eNonusers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0-Nonuse\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eUnrelated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0-Unconcerned\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1-Orientation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSelf\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1-Informational\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2-Preparation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2-Personal\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eUsers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3-Mechanical\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTask\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3-Management\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4a-Routine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eImpact\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4-Consequence\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4b-Refinement\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5-Collaboration\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5-Integration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6-Refocusing\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6-Renewal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe SoC dimension represents an individual\u0026rsquo;s attitudes, beliefs, and feelings about adopting a change. It comprises seven stages: 0-Unconcerned, 1-Informational, 2-Personal, 3-Management, 4-Consequence, 5-Collaboration, 6-Refocusing which are further grouped into four categories (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e; Hall \u0026amp; Hord, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e): Unrelated (i.e., 0-Unconcerned), Self (i.e., 1-Informational and 2-Personal), Task (i.e., 3-Management), and Impact (i.e., 4-Consequence, 5-Collaboration, 6-Refocusing). The two concerns in the \u0026ldquo;Self\u0026rdquo; category indicate that the instructor is focused on what the instructional change will mean for them, personally, while the three concerns in the \u0026ldquo;Impact\u0026rdquo; category indicate that the instructor is focused on what is happening with students and what could be done to enhance outcomes. Hall and Hord (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) state that instructors generally have concerns at more than one stage at the same time. For example, an instructor may have intense concerns at Stage 3-Management and additional concerns at Stage 4-Consequence.\u003c/p\u003e \u003cp\u003eCBAM has been widely applied across different educational contexts and disciplines to study teachers\u0026rsquo; adoption of instructional change (Anderson, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e1997\u003c/span\u003e). Min (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) used SoC to explore the concerns of four instructors adopting eBook-integrated curricula, showing that all instructors had used eBook for one semester or less, and their concerns were at the stages of 2-Personal, 4-Consequences, and 6-Refocusing. Each instructor expressed attitudes and beliefs at multiple stages, and each was motivated to adopt the novel eBook curriculum by concerns about their students (e.g., Impact concerns including 4-Consequences and 6-Refocusing). Min (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) also found no direct connection between advancing through the SoC stages and experience with the instructional change.\u003c/p\u003e \u003cp\u003eSoC has also been applied in research on active learning and online teaching. Luik and Lepp tested the applicability of SoC to explain the transition to online learning by analyzing 872 messages posted in a Facebook learning group from March to April 2020 (Luik \u0026amp; Lepp, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Their results indicated that secondary-school teachers, students, and others\u0026rsquo; concerns (e.g., Stage 2-Personal) mainly contributed to personal feelings and needs early in the change. Then, concerns moved to the management of change (e.g., workload, materials, logistics; Stage 3-Management), and finally they moved to the willingness to collaborate (e.g., Stage 5-Collaboration). The authors further stated that CBAM is suitable for explaining unexpected instructional changes.\u003c/p\u003e \u003cp\u003eResearchers have also utilized a combination of LoU and SoC to study the implementation of instructional change. Olson and colleagues (\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) applied the two dimensions to evaluate the ongoing implementation of a K-12 school district\u0026rsquo;s strategic plan to promote deep learning. They identified many educators who had Unrelated and Self concerns and were at the 3-Mechanical or 4a-Routine levels, indicating initial steps to implementation. Olson et al. (\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) stated that many participants were interested in and involved in implementing the strategic plan but had limited information and preparation. The authors also concluded that the application of CBAM helped them \u0026ldquo;generate timely feedback and data-driven recommendations\u0026rdquo; to implement changes (p. 56, Olson et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eFour-Category Barrier Framework (FCBF)\u003c/h3\u003e\n\u003cp\u003eThe Four-Category Barrier Framework (FCBF) is an instrument with validation evidence designed to assess instructors\u0026rsquo; perceived barriers to implementing active learning (Authors, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Drawing from data collected from approximately 1,000 engineering instructors across North American higher education institutions, the framework was developed based on Sturtevant and Wheeler\u0026rsquo;s (\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) Faculty Instructional Barriers and Identity Survey, which utilized Lattuca and Pollard\u0026rsquo;s (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) Faculty Decision-Making Model. Through a 5-phase process that utilized factor analysis, the FCBF was constructed to provide a comprehensive understanding of the barriers perceived by instructors during their adoption of active learning. The framework suggests that an instructor\u0026rsquo;s motivation to engage in an instructional change involves both contextual factors (e.g., student, teaching, and institution) and individual factors (e.g., instructor).\u003c/p\u003e \u003cp\u003eAuthors (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) presents four categories of barriers (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e): instructor (e.g., instructor comfort and confidence), student (e.g., student preparation and engagement), teaching (e.g., instructional support), and institution (e.g., institutional environment/rewards). Instructor barriers are related to instructors\u0026rsquo; perceptions of their personal conditions, which include instructor attitudes and beliefs that challenge their adoption of active learning. Student barriers mainly pertain to challenges related to student engagement, student expectation, student preparation, and student response to active learning from the instructor\u0026rsquo;s perspectives. Teaching barriers refer to instructional support (e.g., technology, pedagogy, and logistics), assessment and evaluation, and learning environments (e.g., class size, classroom layout, and teaching and learning medium) from instructors\u0026rsquo; perspectives. Institution barriers encompass the institutional environment which includes teaching policies, rewards, and collegial support.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe categories of FCBF\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFactor type\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIndividual\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInstructor\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eContextual\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStudent\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTeaching\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInstitution\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eWhy use CBAM and FCBF together?\u003c/h3\u003e\n\u003cp\u003eWe selected both CBAM and FCBF to guide our study because teaching is a complex and cultural activity (Davis \u0026amp; Sumara, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). It involves multiple stakeholders, including students, instructors, departments, and institutions, and is influenced by the context in which the teaching occurs (Stigler \u0026amp; Miller, \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Additionally, change theories differ in terms of assumptions, context, and rationale (Henderson et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Reinholz et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), such as CBAM vs. Rogers\u0026rsquo; Diffusion of Innovation. Using multiple theories provides a more comprehensive lens to study instructional changes, especially for a systemic instructional change.\u003c/p\u003e \u003cp\u003eRogers\u0026rsquo; Diffusion of Innovation is one of the most well-known change theories applied in the education field and, like CBAM, regards change as a staged process, encompassing instructors\u0026rsquo; decision-making period and overt behaviors (Roger, 2003). However, Rogers\u0026rsquo; model carries limitations, and some researchers have involved other theories in their studies. Sturtevant and Wheeler (\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) utilized Lattuca and Pollard\u0026rsquo;s (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) model when they modified Lund and Stains\u0026rsquo; (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) instrument (which was originally built upon Rogers\u0026rsquo; theory). Andrews and Lemons (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) also modified Rogers\u0026rsquo; model because they noted it is not practical to distinguish between Persuasion (e.g., forming an attitude) and Decision (e.g., deciding to make an instructional change), and because Roger\u0026rsquo;s model is not ideally aligned with instructional context. In a similar vein, \u0026Ccedil;akıroğlu et al. (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) found that their adopter distribution concept did not follow the S-shaped curve predicted by Rogers\u0026rsquo; model, which may be due to the unprecedented instructional change of transitioning courses online.\u003c/p\u003e \u003cp\u003eUnlike change theories based on Rogers\u0026rsquo; model, CBAM was designed to understand, assess, and facilitate the process for individuals adopting changes in educational institutions (Hall \u0026amp; Hord, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e1987\u003c/span\u003e; Hall \u0026amp; Hord, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), although it also has its own limitations. It provides explicit structures guiding researchers to study individuals\u0026rsquo; behaviors and concerns that pertain to the implementation of an instructional change. However, CBAM does not involve factors such as institution management, teaching policies and support systems, and individual characteristics (e.g., \u0026Ccedil;etinkaya, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Kwok, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Min, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). As a result, it is difficult to identify influences that relate to a certain stage of concern or level of use. FCBF does focus on those contextual factors and is based on extensive empirical work. When combined with CBAM, we can use FBCF to study instructors\u0026rsquo; adoption of active learning during abrupt transition online instruction from a more comprehensive perspective.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eWe applied a qualitative research method to study the change processes and relevant barriers for 32 STEM instructors adopting active learning during the abrupt transition to online instruction. We designed a focus group protocol primarily targeting barriers to adopting active learning in their online courses, while also allowing participants to share their experiences (e.g., what they did and how they felt). We then coded the transcripts using the CBAM and the FBCF separately before synthesizing the results from the two change frameworks.\u003c/p\u003e\n\u003ch3\u003eParticipants\u003c/h3\u003e\n\u003cp\u003eThis study is part of a larger research project about instructors\u0026rsquo; adoption of active learning (Authors, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) which involves 165 instructors who taught first- or second-year STEM courses at 56 institutions in the Midwest region of the United States. After receiving human subjects research approval from the University of XXX\u0026rsquo;s Institutional Review Board (HUM###), we recruited participants for our study. From the population of instructors for our larger project, we randomly selected ten institutions across each of four categories (community colleges, bachelor-, master-, and doctoral-granting institutions) and invited an instructor for each of the resulting 40 institutions to participate in focus group discussions. Thirty-two instructors agreed to participate in one of our focus groups (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eParticipant pool and online active learning methods they used\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInstitution Category\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e# Instructors\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e# Female\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e# Male\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCommunity College\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4 (Caitlin, Cerys, Chole, Charlotte)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (Cai, Calum, Cody)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBachelor-granting\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (Babette, Barbara, Beatrice, Betty, Blessing, Bree)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (Ben, Blake)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaster-granting\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (Madeline, Margaret, Marjorie, Maxine, Melanie, Mia, Muriel)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDoctoral-granting\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (Daphne, Darcy, Daria, Denise, Diana, Dylan)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (Daniel, Damian, Desmond, Donald)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e32\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e23\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e9\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAdditionally, participants shared their disciplines and the active learning methods they used during the pandemic in the focus group discussions (Tables\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e \u0026amp; \u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Most participants were from mathematics (9 instructors) and biology (8 instructors), with five participants each from chemistry and engineering, three from physics, and one from architecture. All participants mentioned utilizing learning activities in synchronous and/or asynchronous online classes during the pandemic, but two participants did not specify the active learning methods they used (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Notably, small group activities and hands-on activities were the two most frequently discussed methods.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eOnline active learning methods used by participants\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOnline active learning methods\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eParticipants\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmall group activities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBeatrice, Blake, Bree, Calum, Cerys, Charlotte, Darcy, Damian, Daniel, Donald, Madeline, Margaret, Maxine, Melanie, Mia\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHands-on activities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBen, Blessing, Calum, Cerys, Charlotte, Damian, Daniel, Daphne, Daria, Diana, Margaret, Marjorie, Muriel\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQuiz/worksheet-embedded videos\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBree, Caitlin, Chole, Daniel, Denise\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClass problem-solving\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBeatrice, Cai, Calum, Cody, Desmond\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFlipping\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBabette, Betty, Blake, Charlotte, Damian, Daniel, Donald, Muriel\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"2\"\u003e\u003csup\u003e1\u003c/sup\u003eFlipping represents active learning methods mentioned by instructors which involve assigning pre-class activities (such as videos) and using class time for problem solving, discussion, etc.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eData Collection\u003c/h2\u003e \u003cp\u003eWe conducted eight one-hour focus group interviews (two for each of the four institutional categories) using Zoom. During each focus group, we used a semi-structured protocol with four parts: (1) informed consent for participation and video recording, (2) focus group guidelines, (3) introductions by providing the definition of active learning to ensure that participants share a common understanding of the research focus, and (4) a discussion about barriers that instructors faced when adopting active learning for online instruction.\u003c/p\u003e \u003cp\u003eThe bulk of focus group time concentrated on part 4, barriers, and participants were prompted to identify barriers they perceived to using active learning in online settings, factors that might influence the relative significance of these barriers, and the extent to which they perceived engaging students in online active learning as an issue. The interviewer facilitated the session, while one or two other researchers took notes.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eData Analysis\u003c/h2\u003e \u003cp\u003eWe analyzed the data using a two-step approach. First, we coded the data set using the CBAM framework (i.e., LoU and SoC dimensions) and then separately for the FCBF. Next, we synthesized the results from the two frameworks by matching factors to each stage of concern and level of behavior. Below are the details of our coding analysis.\u003c/p\u003e \u003cp\u003eAll interviews were transcribed verbatim and anonymized. We assigned participant identifiers to align with the institution type \u0026ndash; instructors from community colleges were assigned names starting with a C (such as Charlotte) and those from bachelor-, master-, and doctoral-granting universities were assigned names starting with B, M, or D, respectively (on reflection, we should have invited participants to inform us of their preferred anonymized names to better cater to their identities rather than selecting them ourselves).\u003c/p\u003e \u003cp\u003eWe then analyzed all transcripts using the dual lenses of CBAM and FCBF via MAXQDA 2020. We conducted the analysis through two coding cycles: (1) labeling codes and refining the codebook with a deductive approach to determine levels of use and stages of concern (for the CBAM round of coding) or categories of barriers (for the FCBF round of coding), and (2) categorizing codes and identifying patterns with an inductive approach to allow for emerging themes and subthemes (Azungah, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Salda\u0026ntilde;a, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFor the CBAM round of coding, we used the LoU and SoC dimensions of CBAM to code all eight transcripts. In the first coding cycle, two researchers independently coded the first four of the eight transcripts by using the initial codebook of LoU (\u003cspan refid=\"Sec23\" class=\"InternalRef\"\u003eAppendix\u003c/span\u003e, Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e11\u003c/span\u003e) and SoC (\u003cspan refid=\"Sec23\" class=\"InternalRef\"\u003eAppendix\u003c/span\u003e, Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e12\u003c/span\u003e). Then the coders worked together to refine the codebooks and check the intercoder agreement using MAXQDA 2020 (R\u0026auml;diker \u0026amp; Kuckartz, 2020). After coding the four transcripts, we noted that more than 80% of the LoU segments were coded as level 3-Mechanical Use. To better distribute the codes and more effectively illustrate differences related to logistics versus skills of online instruction, we defined two new sublevels (3a-Mechanical Logistics and 3b-Mechanical New Skills). The segments were recoded accordingly, with roughly half of the codes now falling into each of the new subcategories. Next, one researcher used the refined codebook to re-analyze the first four transcripts. Finally, in the second coding cycle, one researcher categorized coded data and determined themes and sub-themes of each code, and a second researcher reviewed the coding to validate the identified patterns.\u003c/p\u003e \u003cp\u003eAs a separate round of coding, we similarly used the FCBF to code the eight focus group transcripts in two coding cycles, determining segments that aligned with each of the four categories of challenges to online active learning from instructors\u0026rsquo; perspectives (Appendix, Table 13 for the codebook). In the first cycle, three researchers used the initial codebook (Appendix, Table 13) to independently code the first two transcripts. They collaborated to check the intercoder agreement and refined the codebook. Then, two researchers coded a third transcript with the updated codebook and further finalized the codebook. After that, one researcher completed the coding for the remaining five transcripts. In the second coding cycle, one researcher grouped the coded data and determined the themes and sub-themes of each of the four categories. A second researcher reviewed the coding to validate the identified patterns.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eThis section is structured into four sub-sections. The first two sub-sections target the first two research questions, describing change processes (i.e., themes identified when applying LoU and SoC of CBAM; Tables 5 \u0026amp; 6) and barriers or influences (i.e., themes identified when applying the FCBF; Table 7). In the third sub-section, we synthesize the results of CBAM and FCBF to illustrate challenges faced by participants during the abrupt adoption and their relevant influences (Tables 8 and 9). We also report the strategies employed by instructors while implementing active learning in online settings (Table 10). The last sub-section summarizes the key takeaways from studying the case of STEM instructors from different institutions adopting active learning during the pandemic. To maintain clarity and conciseness in the main text, we provide a primary summary of these results.\u0026nbsp;\u003c/p\u003e\u003ch2\u003eThe application of the CBAM Framework\u003c/h2\u003e\n\u003cp\u003eTo answer our first research question (i.e., \u003cstrong\u003e\u003cem\u003eHow does CBAM illustrate the processes of STEM instructors\u0026rsquo; adoption of active learning during an abrupt transition to online instruction?\u003c/em\u003e\u003c/strong\u003e), we investigated the processes in terms of STEM instructors\u0026rsquo; behavioral levels (i.e., results of CBAM-LoU) and affective stages (i.e. results of CBAM-SoC). When applying the LoU framework, we identified seven themes aligned with three levels: 3a-Mechanical Logistics, 3b-Mechanical New Skills, and 4a-Routine (Table 5). The application of the SoC framework resulted in four themes aligned with two stages of concerns (Table 6), with 3-Management having two themes and 4-Consequence having two themes.\u003c/p\u003e\n\u003ch3\u003eResults of CBAM-LoU\u003c/h3\u003e\n\u003cp\u003eLevels of Use refers to an individual\u0026rsquo;s \u003cem\u003ebehaviors\u003c/em\u003e when they prepare to use, begin to use, and obtain new skills and experiences. Based on the segments coded among the eight focus group transcripts, we identified three behavioral levels: 3a-Mechanical Logistics with two themes, 3b-Mechanical New Skills with two themes, and 4a-Routine with three themes (Table 5).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe category of 3a-Mechanical Logistics represents the initial steps toward using active learning in an online setting. This level suggests that instructors primarily focused on their own needs for online active learning and expressed their inability to tackle these challenges amid the unexpected change. Behaviors at this level reported by instructors were mainly related to \u003cem\u003ehands-on activities\u003c/em\u003e and \u003cem\u003elogistical online teaching\u003c/em\u003e. Instructors reported their failure to successfully conduct hands-on activities due to students lacking access to learning resources and equipment or the requirement of extra fees. They also shared their attempts to \u003cem\u003eengage students in synchronous classes\u003c/em\u003e, \u003cem\u003epromote student motivation for online activities\u003c/em\u003e, and \u003cem\u003edevote time to preparing online active learning\u003c/em\u003e. However, some instructors reported that it was time-consuming to design and search for effective learning activities and materials that truly engaged online students. Additionally, estimating the time required for online activities was more difficult than for face-to-face teaching. As Cerys said, \u0026ldquo;One of the problems that I\u0026rsquo;ve always struggled with active learning online is thinking about how long this active learning activity will take with students.\u0026rdquo;\u003c/p\u003e\n\u003cp\u003eLevel 3b Mechanical New Skills represents some instructors\u0026rsquo; efforts to adopt \u003cem\u003eadvanced skills for online active learning\u003c/em\u003e despite other reports of ineffective \u003cem\u003eonline course design\u003c/em\u003e. Some participants endeavored to make adopting active learning in online classes easier by equipping themselves with and applying these skills. Instructors shared that they tried to \u003cem\u003eintegrate digital tools\u003c/em\u003e to engage students in synchronous classes, \u003cem\u003ebuild in accountability\u003c/em\u003e to boost student engagement in group activities, and \u003cem\u003eestablish trust and rapport\u0026nbsp;\u003c/em\u003ewith students to reduce students\u0026rsquo; anxiety and encourage student engagement during class. For example, Maxine said, \u0026ldquo;I always send a funny, very personal video before class starts, and let them know about me, my family, my dogs, how long I\u0026rsquo;ve been teaching, my teaching style. And then, I asked them to do that.\u0026rdquo; Instructors also provided one-on-one virtual meetings for office hours to develop trust and connections with and between students.\u003c/p\u003e\n\u003cp\u003eAt the level of 4a-Routine, instructors established a pattern of regular use of active learning online. Rather than focusing on learning new skills or strategies, some instructors set up specific steps or schedules to adopt active learning strategies in online environments. They shared that, to facilitate their adoption of active learning, they proposed \u003cem\u003eflexible course policies\u003c/em\u003e and established \u003cem\u003econnections with students\u003c/em\u003e through after-class surveys and office hours. Some instructors also mentioned their abilities to use \u003cem\u003etechnology for asynchronous and synchronous instruction\u003c/em\u003e. A conversation between Caitlin and Chole illustrates a good example of flexible course policies. They began by sharing their strict course policies; for example, Caitlin said, \u0026ldquo;I made them [students] have deadlines three times a week versus once a week\u0026hellip;I have a policy of 50% off credit if [students] turn it in late.\u0026rdquo; They then mentioned providing flexibility for students. Chole said, \u0026ldquo;I polled the students before this class started and I said, \u0026lsquo;Do you want me to hold you to that same schedule or would you like me to give you more freedom and I can open a window for your exam?\u0026rsquo;\u0026rdquo; Both instructors reported positive results that seemed to translate to more effective active learning in the online setting.\u003c/p\u003e\n\u003ch3\u003eResults of CBAM-SoC\u003c/h3\u003e\n\u003cp\u003eThe Stages of Concern dimension of CBAM represents an instructor\u0026rsquo;s \u003cem\u003econcerns\u003c/em\u003e about adopting active learning in an online setting, and it reflects instructors\u0026rsquo; attitudes, feelings, and perspectives. Based on the segments coded, both stages 3-Management and 4-Consequence comprised two themes (with up to three sub-themes each, Table 6).\u003c/p\u003e\n\u003cp\u003eStage 3-Management illustrates that, as instructors began to implement active learning in online settings, their concerns about logistics (e.g., classroom management and execution of active learning online) and considerations of new behaviors (e.g., strategies to engage students and transition laboratory courses online) intensified. Accordingly, this stage has two themes: \u003cem\u003eanticipation of logistical issues\u003c/em\u003e and \u003cem\u003econsideration of new behaviors\u003c/em\u003e. Some instructors mentioned that they could anticipate logistical issues related to \u003cem\u003eclassroom management and organization\u003c/em\u003e, while others reported feeling frustrated with the choice of \u003cem\u003easynchronous or synchronous teaching modes\u003c/em\u003e. Additionally, their concerns about \u003cem\u003eexecution of online activities\u003c/em\u003e, such as group activities, intensified when they discussed hybrid courses combining face-to-face and online instruction. Some instructors also stated that they considered actions to facilitate moving\u003cem\u003e\u0026nbsp;laboratory or hands-on courses\u0026nbsp;\u003c/em\u003eto online settings and achieving the \u003cem\u003eenhancement for student engagement.\u0026nbsp;\u003c/em\u003eDuring the focus group, Mia described two plans to promote student engagement: (1) to find a way to allow students submit answers and discussion by using technology and (2) to develop rapport with and between students.\u003c/p\u003e\n\u003cp\u003eThe 4-Consequence stage illustrates that instructors focused on the impacts of online environments on students\u0026rsquo; active learning. At this stage, instructors were predominantly concerned about the impacts of online active learning on students (i.e., \u003cem\u003eawareness of impacts on students\u003c/em\u003e) and how to assess the effectiveness of active learning in an online environment (i.e., \u003cem\u003eassessment\u003c/em\u003e\u003cem\u003e\u0026nbsp;of the effectiveness of instruction\u003c/em\u003e). Instructors reported that they became frustrated when they perceived low learning outcomes and limited learning experiences as a result of anticipated challenges in adopting active learning in online settings. Instructors\u0026rsquo; awareness of impacts on students further represents their concerns about the \u003cem\u003edifferences between face-to-face and online teaching\u003c/em\u003e, inequity caused by students\u0026rsquo; \u003cem\u003eunequal access to resources\u003c/em\u003e, and the \u003cem\u003ebenefits of online active learning\u003c/em\u003e in terms of the learning experience, learning outcomes, skill development, and persistence. For example, Madeline stated that online biology education could not enable students to acquire the real-world skills needed in the field and further expressed strong anxieties about potential issues such as student attrition and department closures.\u003c/p\u003e\n\u003ch2\u003eThe application of the FCBF framework\u003c/h2\u003e\n\u003cp\u003eTo provide a separate lens (i.e., the FCBF) to our analysis of barriers faced by instructors when adopting active learning during an abrupt transition to online instruction and to answer our second research question (i.e., \u003cstrong\u003e\u003cem\u003eHow does FCBF identify and explain the barriers faced by STEM instructors in adopting active learning during an abrupt transition to online instruction?\u003c/em\u003e\u003c/strong\u003e\u003cem\u003e),\u003c/em\u003e we coded our segments into the four categories of this framework \u0026ndash; instructor, student, teaching, and institution (Table 7). Three themes emerged in the instructor, student, and institution categories, and five emerged in the teaching category. Each theme has various sub-themes.\u003c/p\u003e\n\u003cp\u003eThe instructor category represents instructors\u0026rsquo; perceptions of their personal conditions, which may influence the adoption of online active learning. Within this category, there are three main themes: \u003cem\u003etime constraints\u003c/em\u003e, \u003cem\u003einstructor comfort\u003c/em\u003e, and \u003cem\u003eloss of control\u003c/em\u003e over class (e.g., Instructors felt disconnected with their students\u003cem\u003e\u0026nbsp;\u003c/em\u003ebecause they were unable to \u0026ldquo;read\u0026rdquo; the virtual room and see students\u0026rsquo; facial expressions and body language). \u003cem\u003eTime constraints\u003c/em\u003e represent a common concern shared by instructors. They reported that, compared with face-to-face classes, they had to spend much more time \u003cem\u003eplanning courses\u003c/em\u003e for asynchronous or synchronous modes and made additional efforts to \u003cem\u003ebuild relationships\u003c/em\u003e with and among students online. \u003cem\u003eInstructor comfort\u003c/em\u003e pertains to discomfort with their \u003cem\u003erole change\u003c/em\u003e from teaching to learning, discomfort with \u003cem\u003ehybrid teaching modes\u003c/em\u003e in subsequent semesters, and discomfort with \u003cem\u003eonline active learning\u003c/em\u003e when attempting to apply their preferred activities in online settings. For instance, Madeline said, \u0026ldquo;I love discussions, and I love asking tough questions and get people squirming, but it\u0026rsquo;s really kind of dangerous I feel to do it on this kind of platform.\u0026rdquo;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe student category represents how student concerns, as perceived by instructors, can be a challenge when instructors abruptly implement active learning in an online setting. There are three main themes: \u003cem\u003estudent engagement\u003c/em\u003e, \u003cem\u003estudent preparation\u003c/em\u003e, and \u003cem\u003estudent expectations\u003c/em\u003e. Lack of \u003cem\u003estudent engagement\u003c/em\u003e is the primary theme in this category and comprises two sub-themes. Instructors shared that there was sometimes a lack of \u003cem\u003eparticipation in learning activities\u0026nbsp;\u003c/em\u003eeven when students attended class. For example, Cai noted, \u0026ldquo;I find it to be a challenge with some of the students... it\u0026rsquo;s hard for them to show up online and do this [participate in activities] because they\u0026rsquo;re not accustomed to it [the online environment].\u0026rdquo; Some instructors also reported that although students may participate in activities, there was a lack of genuine \u003cem\u003eengagement with learning activities\u003c/em\u003e, as noted by Charlotte: \u0026ldquo;...if the activity requested a bit more time, then they would complain, they would send me a lot of emails...\u0026rdquo;\u003c/p\u003e\n\u003cp\u003eThe teaching category pertains to challenges encountered by instructors while adopting active learning in online classes, and it has five main themes: \u003cem\u003einstructional support\u003c/em\u003e, \u003cem\u003elogistical issues\u003c/em\u003e, \u003cem\u003eassessment and evaluation\u003c/em\u003e, \u003cem\u003ecourse type\u003c/em\u003e, and \u003cem\u003eclass size\u003c/em\u003e. The theme of \u003cem\u003einstructional support\u003c/em\u003e includes students\u0026rsquo; inaccessibility to \u003cem\u003elearning tools\u003c/em\u003e and a lack of\u003cem\u003e\u0026nbsp;support from staff[2] and teaching assistants\u003c/em\u003e (TAs). For instance, Daphne said, \u0026ldquo;In the online class, I do not have a TA or anyone to help. So, when I\u0026rsquo;m helping a student, other students are waiting.\u0026rdquo; The \u003cem\u003elogistical issues\u003c/em\u003e theme covers barriers to the \u003cem\u003eadministration of group activities,\u0026nbsp;\u003c/em\u003ethe \u003cem\u003etime to deliver synchronous courses\u0026nbsp;\u003c/em\u003eas instructors mentioned that extra time and attention were needed to explain content clearly, and conducting courses in \u003cem\u003ean asynchronous mode\u003c/em\u003e. Additionally, the theme of \u003cem\u003eassessment and evaluation\u003c/em\u003e pertains to barriers related to a lack \u003cem\u003eof knowledge for assessing online active learning\u003c/em\u003e, developing and \u003cem\u003ecommunicating rubrics to students\u003c/em\u003e, and identifying the \u003cem\u003ebenefits of online active learning\u003c/em\u003e. Although instructors agreed on the advantages of online learning activities, they were unable to assess the extent to which students benefited from these activities. For \u003cem\u003eclass size\u003c/em\u003e, instructors reported different experiences. Some instructors, like Desmond, stated that large classes (e.g., more than 70 students) made it \u0026ldquo;intrinsically more challenging\u0026rdquo; to use active learning, while other instructors noted that small online classes were not conducive for active learning. As Darcy shared, \u0026ldquo;\u0026hellip;if you have a really small class size and only six students, I\u0026rsquo;m definitely struggling with that [conducting group discussion].\u0026rdquo;\u003c/p\u003e\n\u003cp\u003eWithin institution as a category of challenges to online active learning, there are three main themes: \u003cem\u003einstitutional support\u003c/em\u003e, \u003cem\u003eteaching modes\u003c/em\u003e, and \u003cem\u003esupport for adjunct faculty\u003c/em\u003e[3]. \u003cem\u003eInstitutional support\u003c/em\u003e illustrates that instructors noted institutions failed to provide sufficient and appropriate \u003cem\u003etechnology support\u003c/em\u003e (e.g., digital tools) to them and their students. Additionally, although some institutions offered related \u003cem\u003eprofessional development\u003c/em\u003e which aimed to help instructors adjust to online teaching, the time required was unrealistic for instructors to commit to it. The theme of \u003cem\u003eteaching\u003c/em\u003e\u003cem\u003e\u0026nbsp;modes\u003c/em\u003e refers to that, in some institutions, instructors did not have the option to select their teaching mode as synchronous or asynchronous \u0026ndash; they were required to teach in an assigned mode. However, some instructors believed that it should be instructors who decide on how to teach instead of their institution. Diana stated, \u0026ldquo;...the way that you think that a course is best taught is not the way the institution wants it to be taught.\u0026rdquo; In contrast, the theme of institution category, \u003cem\u003esupport\u003c/em\u003e\u003cem\u003e\u003cu\u003e\u0026nbsp;\u003c/u\u003efor adjunct faculty\u003c/em\u003e,\u003cem\u003e\u0026nbsp;\u003c/em\u003ewas only shared by instructors from community colleges who noted that hiring adjunct faculty, who tend to be external and part-time instructors, was a common practice of community colleges. Full-time instructors reported that besides preparing for their own course, they had to prepare different course materials for adjunct faculty who declined to use active learning components.\u003c/p\u003e\n\u003ch2\u003e\u003cstrong\u003eThe application of the two frameworks together\u003c/strong\u003e\u003c/h2\u003e\n\u003cp\u003eTo answer our third research question (i.e., \u003cstrong\u003e\u003cem\u003eHow do the two frameworks work together to shed insight on the challenges instructors faced and the strategies they used when adopting active learning during an abrupt transition to online instruction\u003c/em\u003e\u003c/strong\u003e), we matched the sub-themes of the results from the CBAM (i.e., categories of behaviors and stages) with the sub-themes of the results from the FCBF (i.e., individual and contextual barriers) (Tables 8-10). We also noted that some of the themes of LoU pertain to challenges (e.g., \u003cem\u003elogistical online teaching\u003c/em\u003e), while others represent concrete strategies (e.g., \u003cem\u003eflexible course policies\u003c/em\u003e). The themes of SoC mainly describe instructors\u0026rsquo; attitudes, beliefs, and feelings that challenge their usage of active learning in online settings. We then classified the challenges STEM instructors faced while adopting active learning during an abrupt transition to online environments into two categories: \u003cem\u003ebehavior-based challenges\u003c/em\u003e with relevant barriers (Table 8) and \u003cem\u003econcern-based challenges\u003c/em\u003e with relevant barriers (Table 9). In the following paragraphs, we elaborate on these two types of challenges and the strategies tackling relevant barriers (Table 10).\u0026nbsp;\u003c/p\u003e\n\u003ch3\u003eChallenges Instructors Face When Using Active Learning While Abruptly Transitioning to Online Instruction\u003c/h3\u003e\n\u003cp\u003e\u003cem\u003eBehavior-based challenges\u003c/em\u003e represent STEM instructors\u0026rsquo; behavioral characteristics (i.e., those identified by the CBAM) and associated individual and contextual factors (i.e., those identified by the FCBF) that they encountered when using active learning in an online environment with very limited preparation. \u003cem\u003eConcern-based challenges\u003c/em\u003e, on the other hand, address STEM instructors\u0026rsquo; feelings, perceptions, and beliefs about using active learning in a suddenly shifting context (i.e., those identified by the CBAM) and associated individual and contextual factors (i.e., those identified by the FCBF). \u003cem\u003eBehavior-based challenges\u003c/em\u003e focus on challenges faced by STEM instructors when they actually used active learning in their online courses during the pandemic, while \u003cem\u003econcern-based challenges\u0026nbsp;\u003c/em\u003eemphasize STEM instructors\u0026rsquo; affective responses to anticipated issues, potential impacts on students, and decision-making on future plans and certain strategies.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eBehavior-based challenges\u0026nbsp;\u003c/em\u003einclude instructors\u0026rsquo; difficulties mainly related to mechanical logistics (e.g., conducting \u003cem\u003ehands-on activities\u003c/em\u003e in online settings and \u003cem\u003elogistical online teaching\u003c/em\u003e), with a theme of mechanical new skills (e.g., issues of \u003cem\u003eonline courses design\u003c/em\u003e) (Table 8). Although we provided definitions of active learning during the focus groups and invited participants to share their experiences with adopting active learning during the pandemic, many challenges reported by STEM instructors are associated with 3a-Mechanical logistics. This finding indicates that most participants struggled with the initial steps of adopting active learning in online settings (Hall \u0026amp; Hord, 1987; Hall \u0026amp; Hord, 2020). The findings, intertwined with the broader challenges of online education, may suggest that instructors\u0026rsquo; adoption of active learning is closely associated with their teaching modality (e.g., face-to-face, online, or blended settings), especially for those who are exposed to a specific modality for the first time. Our results also indicate that, without substantial preparation and support, it is challenging for instructors to successfully adopt active learning in online settings (Hall \u0026amp; Hord, 2020).\u003c/p\u003e\n\u003cp\u003eIt is noticeable that most \u003cem\u003ebehavior-based challenges\u003c/em\u003e are associated with both individual barriers (i.e., the instructor category in the FCBF) and contextual barriers (i.e., the categories of student, teaching, and institution in the FCBF). Take, for example, \u003cem\u003edevote time to prepare online active learning\u003c/em\u003e (a sub-theme of CBAM-LoU\u0026rsquo;s Level 3a-Mechanical Logistics). Instructors who noted this as a challenge were influenced by contextual factors of the FCBF, such as \u003cem\u003estudent engagement\u003c/em\u003e (e.g., the difficulty of designing learning materials that actually engaged students) and \u003cem\u003elogistical issues\u003c/em\u003e (e.g., the uncertainty of managing activities), as well as individual factors of the FCBF such as \u003cem\u003etime constraints\u003c/em\u003e (e.g., searching for learning activities was time-consuming). This finding may suggest that certain behavioral characteristics of STEM instructors are associated with both contextual and individual barriers and these two types of barriers can be interconnected. Accordingly, to assist STEM instructors in avoiding or overcoming related challenges, researchers and support agents should investigate both underlying contextual and individual barriers comprehensively.\u003c/p\u003e\n\u003cp\u003eIn contrast to \u003cem\u003ebehavior-based challenges\u003c/em\u003e predominantly linked with 3b-Mechanical Logistics (Table 8), \u003cem\u003econcern-based challenges\u003c/em\u003e involve two types of stages (i.e., Task and Impact in Table 1). Table 9 illustrates issues related to STEM instructors\u0026rsquo; affect, widely covering both contextual and individual barriers. This suggests that STEM instructors were not only concerned with the process of their adoption of active learning in online settings but also with its impact on their students. In addition, the difference in the frequency of the FCBF\u0026rsquo;s sub-theme \u003cem\u003eassessment and evaluation\u0026nbsp;\u003c/em\u003ein Table 8 and 9 suggests that while participants reported fewer behaviors related to assessing the effects of their use of active learning, they expressed concerns about the potential consequences on their students while adopting active learning in their online courses.\u003c/p\u003e\n\u003cp\u003eTable 9 also demonstrates that factors of the FCBF align well with SoC themes of 3-Management and 4-Consequence. For example, the SoC Stage 4-Consequence suggests instructors\u0026rsquo; major concerns about online active learning pertain to barriers of teaching category in the FCBF, especially the sub-themes of \u003cem\u003eassessment and evaluation\u003c/em\u003e. This may indicate that instructors who are concerned about the impacts of online active learning on students may need knowledge and resources for assessment and evaluation. In addition, \u003cem\u003einstitutional support\u003c/em\u003e is the other theme of the FCBF influencing instructors\u0026rsquo; concerns about students\u0026rsquo; \u003cem\u003eunequal access to resources\u003c/em\u003e (a sub-theme of Stage 4-Consequence). Together, these issues raise the question of whether higher education institutions, in terms of instructors\u0026rsquo; essential skills and support systems, are ready to implement a diverse educational model without increasing inequity and exclusivity. This question is worth considering, especially when many instructors and students prefer a blended instructional mode.\u003c/p\u003e\n\u003cp\u003eThe primary mapping of contextual factors of the FCBF, such as teaching (e.g., \u003cem\u003einstructional support\u003c/em\u003e) and institution (e.g., \u003cem\u003einstitutional support\u003c/em\u003e), onto \u003cem\u003econcern-based challenges\u003c/em\u003e in Table 9 suggests that instructors did not receive sufficient or appropriate support while adopting active learning during the abrupt transition to online instruction. Many participants had to manage logistics and handle issues on their own, which made it more difficult to adopt active learning in their courses. As novices, instructors typically faced challenges in applying relevant teaching strategies and using technology to engage students in online environments while making the initial steps towards active learning in online settings.\u003c/p\u003e\n\u003ch3\u003eStrategies Instructors Use When Using Active Learning While Abruptly Transitioning to Online Instruction\u003c/h3\u003e\n\u003cp\u003eTable 10 presents strategies employed by STEM instructors to address the challenges they faced while adopting active learning online during the pandemic. The strategies identified at level of 3b-Mechnical New Skills suggest that the adoption of active learning online by STEM instructors necessitates equipping them with relevant skills and knowledge. When they initially applied face-to-face active learning skills (e.g., in Level 3b-Mechanial New Skills), instructors focused on \u003cem\u003estudent engagement\u003c/em\u003e of the FCBF. When instructors were focused less on mechanical logistic issues, they attempted strategies that primarily engaged students (such as using online discussion forum and self-introduction videos for improving student-peer and student-instructor interactions and building trust between them).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAs instructors became familiar with these skills and more flexible in applying active learning pedagogies, they prioritized building connections and rapport with their students and utilized technologies to engage them with learning materials. They were more likely to establish regular patterns of use (e.g., in Level 4a-Routine) and to address other barriers such as the individual FBCF factor \u003cem\u003eloss of control\u003c/em\u003e. Instructors perceived a loss of control and attributed it mainly to the disconnection with students in online environments. They instead used peer review, quizzes embedded in videos, and after-class reflection surveys to collect information about students\u0026rsquo; learning outcomes and experiences. This implied that instructors not only focused on their personal needs while implementing online active learning, but they also valued student learning outcomes and learning experiences. However, some of them did not know how to effectively do these, which may suggest that, in this situation, instructors need more support to address the FCBF theme of \u003cem\u003eassessment and evaluation\u003c/em\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eInterestingly, the FCBF theme of institution does not appear in Table 10, which suggests that at these two levels of use (i.e., Level 3b-Mechanical New Skills and Level 4a-Routine), instructors did not attempt to use strategies to address institutional barriers. This could imply that instructors paid more attention to their courses (e.g., engaging students, applying in-person active learning skills, or conducting assessment and evaluation), than addressing \u003cem\u003einstitution\u0026nbsp;\u003c/em\u003ebarriers (e.g., accessing to digital tools or determining teaching modes), or that there were no relevant institutional barriers.\u003c/p\u003e\n\u003ch2\u003eSummary\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eApplying the CBAM framework enabled us to classify the primary behaviors and main concerns of STEM instructors during the process of adopting active learning in an abrupt transition to online instruction. Most behaviors were classified at levels 3a-Mechanical Logistics and 3b-Mechanical New Skills. Predominately focusing on dealing with logistics and attempting to learn new skills to facilitate their adoption indicates initial steps in using active learning in online settings (Anderson, 1997; Hall \u0026amp; Hord, 2020). Although some instructors established a pattern of regular use of active learning in online settings (i.e., 4a-routine), many participants experienced ineffective adoption in their online courses during the pandemic. Participants\u0026rsquo; concerns spanned stages from 3-Management (Task category in Table 1) to 4-Consequence (Impact category in Table 1), reflecting intensified logistical concerns and considerations of new strategies in their implementation of active learning in online instruction. Instructors also shared concerns about the impact of online active learning on students\u0026rsquo; learning and how to assess its effectiveness.\u003c/p\u003e\n\u003cp\u003eApplying the FCBF framework allowed us to identify individual (i.e., instructor category) and contextual (i.e., teaching, student, and institution categories) barriers faced by STEM instructors in adopting active learning during an abrupt transition to online instruction. The instructor category represents individual factors and revealed that participants perceived personal conditions related to time, comfort, and control over the class as influencing factors. In contrast, the teaching, student, and institution categories of the FCBF framework represent contextual barriers impacting STEM instructors during the abrupt transition. From participants\u0026rsquo; perspectives, teaching-related barriers included logistics, course characteristics (e.g., course type, class size), assessment methods, and instructional support. Participants also faced challenges in engaging students and meeting their expectations in the remote teaching modality. Institutional barriers included policies related to support and teaching modes and influenced their use of active learning in online settings.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOur application of dual frameworks, and more specifically the relevance of the specific stages of adoption processes, indicates that tailored instructional support is a promising approach for supporting instructors. The dual application of the CBAM and FCBF frameworks revealed \u003cem\u003ebehavior-based\u003c/em\u003e and \u003cem\u003econcern-based\u003c/em\u003e \u003cem\u003echallenges\u003c/em\u003e with individual and contextual influences during STEM instructors\u0026rsquo; rapid adoption of online active learning. For instance, the frequent associations of \u003cem\u003estudent engagement\u003c/em\u003e (a sub-theme of the FCBF) with different \u003cem\u003ebehavior-based\u0026nbsp;\u003c/em\u003eand\u003cem\u003e\u0026nbsp;concern-based challenges\u0026nbsp;\u003c/em\u003e(sub-themes of the CABM LoU and SoC) illustrate \u003cem\u003estudent engagement\u003c/em\u003e is a significant common factor influencing the process of instructors\u0026rsquo; adoption of online active learning. In addition, the strategies instructors use to implement online active learning (e.g., \u003cem\u003ebuild in accountability\u003c/em\u003e, \u003cem\u003eestablish trust and rapport\u003c/em\u003e, and applying \u003cem\u003eflexible course policies\u003c/em\u003e) are mainly applied to increase student engagement. These findings suggest that student engagement is a primary focus for STEM instructors throughout the process of adopting active learning in online settings.\u003c/p\u003e\n\u003cp\u003eCompared with \u003cem\u003estudent engagement\u003c/em\u003e, \u003cem\u003etime constraints\u003c/em\u003e (a sub-theme of the FCBF) seems to be less critical but remains a significant challenge for instructors, also spanning to contextual factors such as teaching and institution categories. \u003cem\u003eTime constraints\u003c/em\u003e related to challenges instructors faced with the CBAM theme of \u003cem\u003elogistical online teaching\u003c/em\u003e, \u003cem\u003eonline course design,\u003c/em\u003e and \u003cem\u003eanticipation of logistical issues\u003c/em\u003e. In addition, it is identified as a theme within the instructor factor in the FCBF framework, but the time-related issues also emerge under the teaching factor \u0026ndash; \u003cem\u003eLogistical issues\u003c/em\u003e (Table 7). The association between \u003cem\u003edevote time to prepare online active learning\u003c/em\u003e and \u003cem\u003esupport for adjunct faculty\u003c/em\u003e (Table 8) suggest that contextual factors related to institutions influence instructors\u0026rsquo; time commitment to instructional change. These findings may emphasize that time is not a standalone barrier to instructors\u0026rsquo; adoption of active learning for instructors (Authors, 2023). Limited time may stem from tensions between teaching and research, demands for classroom preparation, the need for professional development, or institutional policies (Authors, 2023; Finelli et al., 2014).\u003c/p\u003e\n\u003cp\u003eIn summary, applying both frameworks (the CBAM and the FCBF) offers a more nuanced perspective for mapping individual and contextual barriers across different stages of the instructional change process. This dual approach enables us to develop targeted strategies to deliver customized support for instructors\u0026rsquo; specific needs while implementing an instructional change.\u003c/p\u003e\u003ctable id=\"Tab8\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 5\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eThemes about behaviors identified when applying CBAM Levels of Use\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLevel\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eThemes\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSub-themes\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e3a-Mechanical Logistics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHands-on activities\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003eLogistical online teaching\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEngage students in synchronous classes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePromote student motivation for online activities\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDevote time to prepare online active learning\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e3b-Mechanical New Skills\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOnline course design\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAdvanced skills for online active learning\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIntegrate digital tools\u003c/p\u003e\n \u003cp\u003eBuild in accountability\u003c/p\u003e\n \u003cp\u003eEstablish trust and rapport\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e4a-Routine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFlexible course policies\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTechnology for asynchronous and synchronous instruction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eConnection with students\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003cp\u003e\u003c/p\u003e\u0026nbsp;\u003ctable id=\"Tab9\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 6\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eThemes about concerns identified when applying CBAM Stages of Concern\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eStages\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eThemes\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSub-themes\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"5\"\u003e\n \u003cp\u003e3-Management\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003eAnticipation of logistical issues\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eClassroom management and organization\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAsynchronous or synchronous teaching modes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eExecution of online activities\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eConsideration of new behaviors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHands-on courses\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEnhancement for student engagement\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e4-Consequence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003eAwareness of impacts on student\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDifferences between face-to-face and online teaching\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnequal access to resources\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBenefits of active learning online\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAssessment of the effectiveness of instruction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003cp\u003e\u003c/p\u003e\u0026nbsp;\u003ctable id=\"Tab10\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 7\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eThemes about barriers identified when applying the FCBF\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCategory\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTheme\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSub-theme\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"6\"\u003e\n \u003cp\u003eInstructor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eTime constraints\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePlanning courses\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBuilding relationships\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003eInstructor comfort\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRole change\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOnline active learning\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHybrid teaching modes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLoss of control\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003eStudent\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eStudent engagement\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eParticipation in learning activities\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEngagement with learning activities\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStudent preparation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStudent expectations\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"10\"\u003e\n \u003cp\u003eTeaching\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eInstructional support\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLearning tools\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSupport from staff and teaching assistants\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003eLogistical issues\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAdministration of group activities\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTime to deliver synchronous courses\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAsynchronous mode\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003eAssessment and evaluation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eKnowledge for assessing online active learning\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCommunicating rubrics\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBenefits of online active learning\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCourse type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eClass size\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003eInstitution\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eInstitutional support\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTechnology support\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eProfessional development\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTeaching modes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSupport for adjunct faculty\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\u0026nbsp;\u0026nbsp;\u003ctable id=\"Tab11\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 8\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eBehavior-based challenges faced by STEM instructors while their adoption of active learning during an abrupt transition to online instruction\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eCBAM: Levels of Use\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eFCBF\u003c/p\u003e\n \u003cp\u003eThemes and sub-themes\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eLevel\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eThemes\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSub-themes\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e3a-Mechanical Logistics\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHands-on activities\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTeaching: Instructional support, Course type\u003c/p\u003e\n \u003cp\u003eInstitution: Institutional support\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003eLogistical online teaching\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eEngage student in synchronous classes\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eStudent: Student engagement\u003c/p\u003e\n \u003cp\u003eInstructor: Loss of control, Time constraints\u003c/p\u003e\n \u003cp\u003eTeaching: Logistical issues\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePromote student motivation for online activities\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eStudent: Student engagement, Student expectation\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDevote time to prepare online active learning\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eStudent: Student engagement\u003c/p\u003e\n \u003cp\u003eTeaching: Logistical issues\u003c/p\u003e\n \u003cp\u003eInstructor: Time constraints\u003c/p\u003e\n \u003cp\u003eInstitution: Support for adjunct faculty\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3b-Mechanical New Skills\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOnline course design\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStudent: Student engagement, Student preparation\u003c/p\u003e\n \u003cp\u003eTeaching: Logistical issues, Assessment and evaluation, Course type, Class Size\u003c/p\u003e\n \u003cp\u003eInstructor: Time constraints\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003cp\u003e\u003c/p\u003e\u0026nbsp;\u003ctable id=\"Tab12\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 9\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eConcern-based challenges faced by STEM instructors while their adoption of active learning during an abrupt transition to online instruction\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eCBAM: Stages of Concern\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eFCBF\u003c/p\u003e\n \u003cp\u003eThemes and sub-themes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStages\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThemes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSub-themes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"5\"\u003e\n \u003cp\u003e3-Management\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003eAnticipation of logistical issues\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eClassroom management and organization\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStudent: Student engagement\u003c/p\u003e\n \u003cp\u003eTeaching: Instructional support, Logistical issues\u003c/p\u003e\n \u003cp\u003eInstructor: Time constraints\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAsynchronous or synchronous teaching modes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTeaching: Instructional support, Logistical issues,\u003c/p\u003e\n \u003cp\u003eInstitution: Teaching Modes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eExecution of online activities\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTeaching: Logistical issues, Instructional support, Class size\u003c/p\u003e\n \u003cp\u003eInstructor: Instructor comfort\u003c/p\u003e\n \u003cp\u003eInstitution: Teaching modes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eConsideration of new behaviors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCourses with hands-on activities\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTeaching: Instructional support, Course type\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEnhancement for Student engagement\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStudent: Student engagement\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e4-Consequence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003eAwareness of impacts on student\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDifferences between face-to-face and online teaching\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTeaching: Assessment and evaluation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnequal access to resources\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTeaching: Assessment and evaluation\u003c/p\u003e\n \u003cp\u003eInstitution: Institutional support\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBenefits of active learning online\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTeaching: Assessment and evaluation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAssessment of the effectiveness of instruction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTeaching: Assessment and evaluation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003c/p\u003e\n\u003cp\u003e\u003c/p\u003e\u0026nbsp;\u003ctable id=\"Tab13\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 10\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eStrategies used by instructors used by STEM instructors while their adoption of active learning during an abrupt transition to online instruction\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eCBAM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eFCBF\u003c/p\u003e\n \u003cp\u003eThemes and sub-themes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLevels\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThemes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSub-themes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e3b-Mechanical New Skills\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003eAdvanced skills for online active learning\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIntegrate digital tools\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStudent: Student engagement\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBuild in accountability\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStudent: Student engagement, Student expectation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEstablish trust and rapport\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStudent: Student engagement\u003c/p\u003e\n \u003cp\u003eInstructor: Loss of control\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e4a-Routine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFlexible course policies\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStudent: Student engagement, Student expectations\u003c/p\u003e\n \u003cp\u003eTeaching: Assessment and evaluation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTechnology for asynchronous and synchronous instruction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStudent: Student engagement, Student preparation\u003c/p\u003e\n \u003cp\u003eInstructor: Instructor comfort, Loss of control\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eConnection with students\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInstructor: Loss of control\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n"},{"header":"Discussion","content":"\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eReflection on the Application of Two Frameworks Together\u003c/h2\u003e \u003cp\u003eAs we stated, fully understanding the process of an instructor\u0026rsquo;s adoption of an instructional change and the relevant contextual and individual barriers is challenging when applying only one change theory. By applying multiple theories, we gain a more nuanced perspective on implementing instructional changes.\u003c/p\u003e \u003cp\u003eThese results from applying the two frameworks align with existing literature, particularly the barriers identified by the FCBF framework (e.g., \u0026Ccedil;akıroğlu et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Dumont et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). However, using only one of the two change frameworks makes it challenging to comprehensively depict the barriers faced by STEM instructors at various stages of their adoption process. Failing to identify barriers at specific stages of STEM instructors\u0026rsquo; adoption further complicates providing appropriate support, which may significantly increase the likelihood of unsuccessful adoption of active learning in online settings (Hall \u0026amp; Hord, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). In our case, while some strategies employed by STEM instructors facilitated more effective use of active learning in their online courses, others could not achieve the same level of effectiveness, especially if they were not at similar stages in their adoption process.\u003c/p\u003e \u003cp\u003eFor example, \u0026Ccedil;akıroğlu and colleagues (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) quantitatively explored how factors such as instructional support, institutional guidance, student-instructor interaction, prior experiences, and teaching modes influenced Turkish instructors\u0026rsquo; adoption of online teaching during the pandemic. They found support and interaction factors are crucial concerns for participants using technology in their online teaching. To enhance flexibility, many universities have recognized the need to equip their instructors with educational technology integrated with pedagogical knowledge, facilitating various modes of delivery (e.g., face-to-face, online, and blended instruction; Alexander et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Huang, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Keane et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Peimani and Kamalipour, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Rapanta et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). However, instructors vary in their pedagogical knowledge and process of integrating technology into their courses, suggesting the need for tailored support to accommodate different instructors\u0026rsquo; adoption of instructional changes.\u003c/p\u003e \u003cp\u003eThe findings drawn by applying the CBAM and the FCBF together provide more comprehensive insight into the challenges instructors face and the strategies they use while adopting active learning during the abrupt transition to online instruction. Our synthesized findings indicate that specific behaviors and concerns of STEM instructors are intricately linked with contextual and individual barriers. These barriers vary at different points in the adoption process, which suggests the need for different types of support and resources. An instructional change process is not linear if the change is not carefully facilitated, appropriately supported, and well-prepared with sufficient time (Hall \u0026amp; Hord, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). In these situations, the change progress is more likely arrested at a certain point (e.g. most participants\u0026rsquo; behaviors located at 3a-Mechanical Logistics with various barriers) or returned to previous levels or stages (e.g., instructors tended to give up on their favorite learning activities).\u003c/p\u003e \u003cp\u003eThe combined lens implies that supporting STEM instructors does not entail providing a one-size-fits-all approach, as such an approach can be overwhelming and inefficient. Instead, support agents should assist instructors in identifying their unique challenges and determining appropriate strategies. Moreover, instructors\u0026rsquo; professional development is an intensive and ongoing activity in which there is a lag between obtaining pedagogical knowledge and implementing the practices, and instructors may encounter various barriers during the process of adoption (Borda et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Hall \u0026amp; Hord, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Stigler \u0026amp; Miller, \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). This suggests that professional development should be adaptable and sustained in a way to address instructor\u0026rsquo;s needs at various stages (Borda et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWhen one applies CBAM to address instructors\u0026rsquo; behaviors and concerns, it is hard to identify the related factors influencing these problems. Although the CBAM\u0026rsquo;s SoC themes appear to be similar to those of the FCBF, CBAM tends to describe a challenge from the affective perspective of the instructor, while the FCBF is more likely to explain external causes behind the experience. For example, when an instructor challenged by \u003cem\u003easynchronous and asynchronous teaching modes\u003c/em\u003e (a sub-theme of CBAM\u0026rsquo;s SoC Stage 3-Management), the CBAM framework provides no additional insight. However, in combination with the FCBF, it is possible to determine whether the issue is related to the instructor\u0026rsquo;s teaching (e.g., \u003cem\u003einstructional support\u003c/em\u003e and \u003cem\u003elogistical issues)\u003c/em\u003e or institutional policies (e.g., \u003cem\u003eteaching modes\u003c/em\u003e).\u003c/p\u003e \u003cp\u003eAccordingly, integrating the CBAM framework with the challenges aligned with the FCBF can shed insight on the challenges instructors face when they are forced to abruptly adopt online active learning and their responses. We found that when instructors initially adopted online active learning with very limited preparations, most of their behaviors are classified as Level 3-Mechanical Use. This prevented us from further categorizing faculty behaviors and identifying the challenges they face and the strategies they took, and it led us to subdivide that level into 3a-Mechanical Logistics and 3b-Mechanical New Skills. Instead, the FCBF seems well suited to the context of implementing online active learning. This may imply that challenges related to who teaches (instructor), who is taught (student), how to teach (teaching), and where to teach (institution), which are themes of the FCBF, emerge when making an instructional change, regardless of the educational delivery modes and pre-adoption conditions (e.g., preparation for instructional change).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eLimitations\u003c/h2\u003e \u003cp\u003eDespite interesting insights found in our study, it does have limitations related to both our application of two frameworks and our case sample. The primary limitation is that we did not incorporate both the CBAM and FCBF frameworks at the early stage of our research design. Ideally, the combination of CBAM and FCBF should have informed our research purposes and data collection; however, we decided to apply both change frameworks during the data analysis phase. The later inclusion of CBAM may have prevented us from collecting more enriched data related to change processes and indeed required additional time and effort. Nonetheless, given that our application of dual change frameworks was an evolving process, we adjusted our approach as the research progressed and drew meaningful insights from the combined frameworks.\u003c/p\u003e \u003cp\u003eThere are also limitations related to our case sample. First, the size and composition of our sample may hinder us from drawing a complete picture. We interviewed 32 instructors, and most (around 72%) were female instructors. Saw and colleagues (\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) claim that female faculty shared a higher level of anxiety and had more online teaching challenges during the pandemic than male faculty, so our data may be somewhat skewed. As well, we recruited only one instructor (including lecturers and professors) at each of the 32 institutions, so our study provides limited information related to some factors, such as instructors\u0026rsquo; teaching roles and departmental environments.\u003c/p\u003e \u003cp\u003eOur study is also limited because we did not fully consider instructors\u0026rsquo; prior teaching experiences in terms of active learning and online instruction. Unfortunately, we collected only very basic information about instructors\u0026rsquo; prior teaching experiences, and it was not sufficient to include in our analysis. We acknowledge that including more detailed information about instructors\u0026rsquo; prior experience could enrich our findings. However, some evidence suggests that there is not a direct relationship between the length of teaching experience and the quality of teaching (Graham et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Stigler \u0026amp; Miller, \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAnother limitation is related to our broad definition of active learning, which may prevent us from drawing more in-depth conclusions about adopting specific types of active learning in online settings. We defined active learning as \u0026ldquo;using individual or group activities to engage students in their learning during class,\u0026rdquo; while some scholars may challenge that our definition of active learning is \u0026ldquo;an umbrella term that is not particularly useful in advancing research on learning.\u0026rdquo; (Lombard et al., 2021, p 8). Future studies could further investigate the process of STEM instructors\u0026rsquo; adopting a specific active learning strategy in an online setting.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn this study, we demonstrate the dual application of two separate change frameworks to investigate a systemic instructional change: STEM instructors from different institutions adopting active learning during an abrupt transition to online environments. Our investigation focused on change processes and barriers at both individual and contextual levels. We applied the CBAM, a process-oriented instructional change theory, to illustrate STEM instructors\u0026rsquo; behaviors and concerns throughout the adoption process. Simultaneously, we utilized the FCBF, a framework designed to identify barriers in face-to-face instruction, to explain individual and contextual influences. We then synthesized the results of CBAM and FCBF to identify challenges, strategies, and their relevant barriers, providing a combined lens to comprehensively study instructional changes.\u003c/p\u003e \u003cp\u003eOur study also provides some sights for the study case (STEM instructors from different institutions adopting active learning during the pandemic). From the instructor\u0026rsquo;s perspective, the abrupt adoption of active learning in an online environment with limited preparation was more challenging than implementing active learning in a face-to-face setting. Although participants reported various challenges in teaching online (e.g., low student attendance due to different time zones, limited learning environments at home, or issues related to student honesty and ethics), we focused primarily on challenges and strategies pertaining to adopting active learning in online environments.\u003c/p\u003e \u003cp\u003eOur results of applying two frameworks together to study the case sample demonstrate that, while abruptly transitioning to online settings, the STEM instructors in our study encountered various challenges related to mechanical issues (e.g., conducting hands-on activities, handling logistics of online teaching, and designing online courses). We found that some instructors attempted to use strategies (e.g., applying advanced skills for online active learning, implementing flexible course policies, using technology for asynchronous and synchronous instruction, and building connections with students) to overcome these issues. These challenges encompass both individual influences (e.g., time constraints, instructor comfort, and loss of control) and contextual influences (e.g., student engagement, student preparation, assessment and evaluation, instructional support, and institutional support). In addition, some instructors were able to anticipate challenges and consider potential solutions (e.g., anticipating logistical issues and considering new behaviors), and some were concerned about the impacts of unexpected change on their students and ways to assess them (e.g., being aware of impacts on student and attempting to assess the effectiveness of instruction).\u003c/p\u003e \u003cp\u003eThe findings from combining CBAM and FCBF suggest that when instructors adopt an instructional change without sufficient preparation and support, they are likely to face behavior-based challenges at the initial levels of use, although their concerns may be widely distributed across two categories of SoC (Task and Impact; See Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). It should be noted that a specific challenge may be triggered by both contextual and individual factors. Further, some factors of the FCBF are commonly present across different levels and stages of CBAM (e.g., \u003cem\u003estudent engagement\u003c/em\u003e in our study), while other factors of FCBF (e.g., \u003cem\u003eassessment and evaluation\u003c/em\u003e in our study) are specific to certain levels and stages. We recommend that support (e.g., professional development and interventions) should be tailored to meet instructors\u0026rsquo; needs and should address factors at various steps of instructors\u0026rsquo; adoption of an instructional change.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eAcknowledgments\u003c/p\u003e\n\u003cp\u003eThe authors gratefully acknowledge the support of instructors who participated in the project.\u003c/p\u003e\n\u003cp\u003eAuthors\u0026rsquo; contributions\u003c/p\u003e\n\u003cp\u003eAuthor 1: Conceptualization, Methodology, Formal analysis, Writing- Original draft; Author 2: Conceptualization, Methodology, Formal analysis, Writing- Review and editing; Author 3: Methodology, Formal analysis, Writing- Review and editing; Author 4: Conceptualization, Methodology, Writing- Review and editing; Author 5: Conceptualization, Methodology, Supervision, Writing-Review \u0026amp; editing, Project administration.\u003c/p\u003e\n\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eThis material is based upon work supported by the National Science Foundation (Grant #XXX). Any opinions, findings, conclusions, and recommendations expressed are those of the authors and do not necessarily reflect the views of the National Science Foundation.\u003c/p\u003e\n\u003cp\u003eAvailability of data and materials\u003c/p\u003e\n\u003cp\u003eThe datasets created and analyzed in this study are not available to the public because of participant privacy and confidentiality but are available to request from the corresponding author under reasonable circumstances.\u003c/p\u003e\n\u003cp\u003eEthics approval and consent to participate\u003c/p\u003e\n\u003cp\u003eThe study was approved by XXXXX University Institutional Review Board (IRB) (ID: XXXXX).\u003c/p\u003e\n\u003cp\u003eCompeting interests\u003c/p\u003e\n\u003cp\u003eThere are no conflicts to declare.\u003c/p\u003e\n"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAbrahams. (2010). 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Factors affecting active flipped learning on underrepresented students in three STEM courses. Education and Information Technologies, \u003cem\u003e29\u003c/em\u003e(9), 10791\u0026ndash;10804.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhao, Y., \u0026amp; Watterston, J. (2021). The changes we need: Education post COVID-19. Journal of Educational Change, \u003cem\u003e22\u003c/em\u003e(1), 3\u0026ndash;12.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZimmerman, J. (2020). \u003cem\u003eThe amateur hour: A history of college teaching in America\u003c/em\u003e. Johns Hopkins University Press.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Footnotes","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003e\u003cem\u003eInstructors\u003c/em\u003e here refers to individuals who teach college courses in American higher education institutions. They include tenure-track faculty (e.g., assistant professors, associate professors, and (full) professors), teaching-focused professors (e.g., teaching professors), and lecturers. In addition, \u003cem\u003eProfessor\u003c/em\u003e in the United States typically denotes academics employed to research and teach in higher education institutions (Macfarlane, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e \u003cem\u003eStaff\u003c/em\u003e refers to employees who provide support for teaching and learning, research, and service programs within American higher education institutions.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003e \u003cem\u003eAdjunct faculty\u003c/em\u003e here refers to instructors who are temporarily employed to teach courses at American higher education institutions. They are also known as part-time or contract faculty, and they typically hold non-tenure track positions (Fagan‐Wilen et al., 2006).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"STEM instructors, Instructional change, Change processes, Barriers, Active learning, Online, COVID-19 pandemic","lastPublishedDoi":"10.21203/rs.3.rs-6285934/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6285934/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e STEM higher education has been undergoing instructional changes, such as shifting from traditional lecturing to active learning, transitioning from physical classrooms to online or blended settings, and integrating transformative educational technologies. These instructional changes tend to be systemic (e.g., instructional changes across multiple STEM departments or institutions), yet research on such changes is limited. Change theories have been advocated to guide research on instructional changes, but their inappropriate or insufficient application partly contributes to the challenges in successfully adopting these changes. This study applies two change frameworks, the Concerns-Based Adoption Model (CBAM) and the Four-Category Barrier Framework (FCBF), to investigate a systemic instructional change and explore change processes and barriers at both individual and contextual levels. We used STEM instructors’ adoption of active learning during the abrupt transition to online learning as a case, conducting focus groups with 32 STEM instructors at U.S. higher education institutions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults \u003c/strong\u003eRegarding the change processes identified through CBAM, participants’ behaviors were primarily categorized as initial steps toward using active learning in online settings, although their concerns ranged from handling logistics to the impact of the abrupt transition on their students. In terms of barriers identified using FCBF, participants faced personal issues related to time, comfort, and control over their classes, as well as contextual barriers related to students (e.g., student participation), teaching (e.g., instructional support), and institutional factors (e.g., policies regarding support and teaching modes). We synthesized the results of the two change frameworks, finding that specific participants’ behaviors and concerns were intricately connected with contextual and individual barriers, which differed at various stages in the change process. This work, with concrete evidence from the synthesized results, demonstrates STEM instructors need tailored support and personalized assistance, especially when faced with abrupt systemic instructional changes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions:\u003c/strong\u003e Applying two change frameworks enables us to investigate STEM instructors’ adoption of systemic instructional changes through the lenses of change processes and individual and contextual barriers, offering insightful and comprehensive findings. We recognize and advocate for using multiple change theories to take advantage of each framework and conduct thorough research on instructors’ adoption of systemic instructional changes.\u003c/p\u003e","manuscriptTitle":"Applying Two Change Frameworks to Address Change Processes and Barriers in Instructional Change: A Case of STEM Instructors’ Adoption of Active Learning During Abrupt Online Transition","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-16 10:59:53","doi":"10.21203/rs.3.rs-6285934/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"03f87c97-c498-4693-8651-d02799bd29ee","owner":[],"postedDate":"April 16th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-10-01T23:53:15+00:00","versionOfRecord":[],"versionCreatedAt":"2025-04-16 10:59:53","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6285934","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6285934","identity":"rs-6285934","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}