The Effects of Assignment Choice on Quiz Performance and Student Experience in Online Graduate Education

The Effects of Assignment Choice on Quiz Performance and Student Experience in Online Graduate Education | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The Effects of Assignment Choice on Quiz Performance and Student Experience in Online Graduate Education Kristin Foley, Paul Gavoni, Thomas Zane, David J Cox, Mary Jane Weiss This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9261351/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Effective instruction in higher education relies on structured engagement, frequent opportunities to respond, and meaningful feedback. Prior research suggests that offering students choices of assignments can improve engagement and performance; however, experimental evaluations of this practice in online settings are limited. In this study, an adapted alternating treatments design was used to evaluate the effects of assignment choice on quiz performance among 45 participants across six sections of asynchronous, online Master’s-level courses. Participants completed weekly proof-of-reading assignments, choosing between study questions and reading summaries during “choice weeks”, and being randomly assigned to one of these tasks during “no-choice weeks”. Weekly quiz scores served as the dependent variable. Visual and statistical analyses indicated that providing assignment choice did not improve quiz performance compared to no-choice conditions. However, participants consistently reported a preference for having a choice and reported having choice as helpful for increasing their perceived engagement with course material and preparation for assessments. These findings highlight the potential of assignment choice to enhance student satisfaction in online graduate education, which is important as on-line higher-education enrollment continues to grow. Keywords: student choice, higher education, online instruction, behavior science student choice higher education online instruction behavior science Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Instructional effectiveness is often determined by how well students acquire, retain, and apply knowledge and skills, with evidence-based teaching practices increasing the probability that learning occurs efficiently and meaningfully (Hattie, 2009 ). Effective teaching requires a combination of structured lesson delivery, continuous assessment, and constructive feedback. The delivery of such instruction is often characterized by structured student engagement, high rates of student participation, and frequent opportunities to respond to enhance comprehension and retention (Carter et al., 2024 ; Haydon et al., 2012 ; Means et al., 2013 ). Beyond engagement and feedback, well-defined learning objectives and effective course design can further support student success (Lockman & Schirmer, 2020 ). Applied behavior analysis (ABA) seeks to develop and evaluate socially significant interventions across applied settings (Baer et al., 1968 ; Penney, 2023; Rajaraman et al., 2023 ; Tincani et al., 2024 ). In educational contexts, these principles are often applied to increase student engagement, skill acquisition, and academic outcomes. With the expansion of online graduate education, improving instructional design and aligning coursework with student preferences has become increasingly important for maintaining quality and supporting positive learning experiences (Hamilton, 2024). From a behavior-analytic perspective, assignment choice represents an antecedent manipulation that may alter how students interact with academic tasks. By systematically evaluating the effects of such antecedent variables, the use of behavior-analytic methods may help ensure rigor and instructional effectiveness in on-line higher education. Over the past two decades, online education has become an increasingly integral component of higher education in the United States. According to the National Center for Education Statistics (2024), more than 10 million college students enrolled in at least one online course in 2022, including approximately 1.1 million students enrolled in programs delivered primarily online. This reflects a 16% increase in online course enrollment since 2011. During the height of the COVID-19 pandemic, 73.1% of all postsecondary students were enrolled in at least one online course. Although that proportion has declined since its peak, more than half of U.S. college students continue to take at least one online class (Hamilton, 2024). While effective instructional practices are essential, student choice has emerged as a potentially influential instructional variable in learning outcomes (Deci & Ryan, 2000 ; Thibodeaux et al., 2019 ). Research suggests that providing students with structured opportunities to choose aspects of their learning may evoke higher rates of responding (May, 2018 ), enhance student motivation (Dabrowski & Marshall, 2018 ), increase engagement (Jamero et al., 2023 ), and improve measures of academic performance such as quiz scores (Deci & Ryan, 2000 ). In educational settings, structured instructional methods may be supplemented by incorporating opportunities for student choice, allowing learners to engage with material in ways that align with their preferences, strengths, and prior experiences (Dabrowski & Marshall 2018 ; Patall, et al., 2008 ). Student-centered approaches that allow learners to choose how they engage with content are consistent with broader movements toward inclusive and responsive pedagogy (Gay, 2002 ; Rajaraman et al., 2023 ). Offering structured choice may contribute to perceptions of fairness and inclusivity in online learning environments. Prior research has linked opportunities for choice with increased participation and persistence in some educational contexts. However, despite growing advocacy for student-centered instruction, Harrington ( 2024 ) found that the prevalence of assignment choice has remained largely stagnant over the past 25 years, suggesting a disconnect between pedagogical discourse and instructional practice. From a behavior-analytic perspective, offering choice may function as an antecedent variable that alters the reinforcing value of task completion (Michael, 1993 ). For example, when students are permitted to select among functionally similar assignments, the opportunity to choose may increase the relative value of completing the selected task or decrease aversiveness associated with imposed formats (Jamero et al., 2023 ). In this way, choice may influence task initiation or completion. Beyond potential effects on academic performance, choice may also relate to constructs such as social validity and student experience. Social validity refers to acceptability and perceived value of procedures and outcomes from participants (Wolf, 1978 ). Providing structured opportunities for choice may increase the perceived fairness or acceptability of educational experiences. Some scholars have argued that student-focused practices may contribute to more inclusive and responsive educational environments (Ghaemmaghami et al., 2024 ; Penney et al., 2023 ). For example, Sinclair et al. ( 2021 ) identified instructional strategies such as reflective writing and service learning that were associated with increased student-reported persistence and engagement with coursework. Although these outcomes were not operationalized in the current study, they suggest that instructional variables such as choice may influence dimensions of student experience beyond quiz performance. Several empirical studies have explored how choice impacts student outcomes. For example, Lockhart et al. ( 1975 ) examined the impact of student choice on performance in a traditional in-person undergraduate psychology course, comparing multiple-choice and fill-in-the-blank test formats. The researchers found that students preferred multiple-choice questions and performed better when given their preferred format. Bird and Chase ( 2021 ) investigated the effects of assignment structure on procrastination and academic performance among graduate students in a hybrid Master's-level ABA course. Using an alternating treatments design with an embedded choice component, the researchers compared contingent access to practice quizzes (i.e., quizzes available only after completing specified tasks) and noncontingent access (i.e., quizzes available without prerequisite assignments). Dependent variables included quiz completion and accuracy. Although most students selected noncontingent access when given the choice, visual and statistical analyses found no consistent differences in quiz scores between conditions. These findings suggest that while students preferred noncontingent access to practice materials, having this choice did not alter academic performance. In one of the most directly relevant studies, Tereshko et al. ( 2024 ) evaluated how assignment choice affected quiz performance in online Master’s-level ABA courses using a modified alternating treatments design. Students completed weekly quizzes following either instructor-assigned tasks (no-choice condition) or self-selected assignments (choice condition). Across all sections, mean quiz scores were higher during choice weeks (M = 15.70, SD = 3.04) compared to no-choice weeks (M = 14.00, SD = 3.73). A nonparametric analysis indicated that this difference was statistically significant (p = .0052), suggesting that the opportunity to choose assignments was associated with improved quiz performance. However, variability differed across sections, with Section 3 demonstrating greater overlap between conditions than Sections 1 and 2. Although statistically significant, the mean difference of 1.7 points on a 20-point quiz reflects a modest effect size, raising questions about the magnitude and generalizability of the observed benefit. Additionally, potential differences in response effort and task structure between assignments were noted by the authors as possible contributing variables, warranting replication under conditions that more tightly control for instructional equivalence. Research on choice in education has yielded mixed findings regarding its impact on student performance. Some studies have reported positive effects of choice on academic outcomes (Flowerday et al., 2004 ; Hanewicz et al., 2017 ; Patall et al., 2010 ; Tereshko et al., 2024 ), whereas others have found minimal or no direct effects on performance (Bird & Chase, 2021 ; Flaherty, 2024; Jopp & Cohen, 2020 ; Patall et al., 2008 ). These discrepancies may reflect methodological differences across studies, including variation in the type of choice offered (e.g., assignment format, pacing, grading structure), differences in response effort between options, whether preference was experimentally established prior to choice exposure, and the extent to which research designs isolated the effect of choice itself from access to preferred tasks. Studies have also differed in instructional modality (online vs. face-to-face), participant population (undergraduate vs. graduate), and analytic approach (group statistical designs vs. single-case methodologies). An unresolved question, therefore, is whether assignment choice independently influences academic performance and student experience when task requirements, exposure history, and content equivalence are controlled. The present study evaluated this question within online graduate coursework by systematically manipulating assignment choice while equating task demands across conditions. Although the design functioned as a systematic replication of Tereshko et al. ( 2024 ), key methodological refinements, including expert-verified content equivalence and controlled exposure to assignment formats prior to the introduction of choice, were implemented to isolate the contribution of procedural choice to quiz performance. Accordingly, the present study asked: Does assignment choice independently influence quiz performance and student experiences when task requirements, response effort, and exposure history are held constant? Method Participants and Setting Forty-five graduate students in six sections of three different online Master’s-level courses in Applied Behavior Analysis (ABA) participated in this study. The courses took place on CANVAS®, a digital learning management system, and were asynchronous, meaning all class materials were available online with no synchronous meeting times. The study was approved by the college’s Institutional Review Board (IRB). Materials All instructional materials were delivered through the Canvas learning management system. Weekly course content included assigned readings, recorded lectures, discussion prompts, and a 20-item quiz assessing mastery of the assigned material. The primary materials relevant to the independent variable were two proof-of-reading assignments: (a) a structured study guide consisting of 20 open-ended questions and (b) a reading summary requiring a minimum three-page synthesis of the assigned readings. Both assignments were graded for completion and were required prior to quiz access. Dependent Variable The dependent measure was points earned on weekly quizzes, each comprised of 20 questions. The weekly quizzes included seven multiple-choice questions (i.e., one correct answer out of four options), seven multiple-answer questions (i.e., two or more correct answers out of four options), and six matching questions (i.e., selecting the correct definition or description for a term or concept). Each question was worth one point, for a total of 20 possible points per quiz. Participants received the same quiz regardless of which proof-of-reading task was completed. Quizzes were graded automatically within Canvas to ensure scoring consistency across participants and conditions, and no instructor feedback was provided to prevent differential post-quiz learning effects that could influence subsequent performance. Experimental Design An adapted alternating treatments design with a predetermined (Table 1 ) semi-randomized schedule (Cariveau & Fetzner, 2022 ) was used to assess the impact of choice and no-choice conditions on quiz scores. This design was chosen due to its ability to simultaneously compare the effectiveness of each task within the same participant (Sindelar, 1985). Table 1 Predetermined Schedule of Conditions Week 1 Week 2 Week 3 Week 4 Week 5 Week 6 Week 7 Week 8 Week 9 Week 10 Week 11 Condition NC NC C C C NC C C C NC C Not e. NC = No-choice week, C= Choice week Independent Variable The independent variable was the availability of assignment choice. During no-choice weeks, students were assigned either reading summaries or study questions without the opportunity to select their preferred option; assignment type was randomly determined to control for potential preference effects (see below for assignment descriptions). During choice weeks, students were permitted to select their preferred assignment from the same two options. The study question and reading summary tasks differed in format but were designed to be instructionally equivalent in content coverage, response expectations, and grading criteria, thereby assessing comprehension of the same assigned material (Bensoussan & Kreindler, 1990 ). Both assignments were evaluated using an all-or-nothing completion criterion. The study question assignment consisted of 20 open-ended questions aligned with the week’s assigned readings. To receive credit, responses were required to (a) contain 2–6 sentences per question, (b) address all components of each prompt using accurate terminology, and (c) be written in the student’s own words. Instructor review determined whether responses met these criteria. Submissions containing verbatim text from assigned readings without citation or substantive paraphrasing were scored as incomplete. For the reading summary assignment, students were required to submit an approximately three-page summary of the assigned readings that included (a) coverage of all required readings, (b) discussion of clinical and/or personal application, and (c) reflection on key concepts identified as meaningful. Summaries were evaluated for adherence to length requirements, inclusion of required components, and originality of expression. Submissions that reproduced source material verbatim without citation were scored as incomplete. Procedures Senior staff at the college who are doctoral-level Behavior Analysts (BCBA-Ds) evaluated the content difficulty level across each week and condition prior to the start of the study. These three professionals analyzed the content of every module of each course to determine the level of difficulty each. Modules were rated as 1 (low level of difficulty), 2 (moderate level of difficulty), or 3 (high level of difficulty). These scores were averaged across all raters. The average level of difficulty by course ranged from 1.70 to 2.00, with the overall average difficulty across all modules and courses being 1.87 ( SD = 0.43), indicating generally moderate difficulty with relatively low variability among raters. Additionally, these experts rated the overall equivalence of content difficulty across all modules of each class on a three-point scale with 1 indicating a minimal level of equivalence, 2 indicating a moderate level of equivalence, and 3 indicating a high level of equivalence across the semester. The overall equivalence of content across each class averaged 2.7 out of 3. At the start of the semester, the researcher informed all participants that they could choose whether to consent to having their de-identified data included in the study, and that the course would proceed as planned regardless of their decision. Participants were also informed that the researcher and instructors would remain blind to their consent status until after final grades were submitted. Additionally, participants were told that they could revoke their consent at any time during the study. Each module lasted one week, with assignments due on Sundays at 11:59 p.m. EST. Across the semester, students completed eleven proof-of-reading assignments and eleven corresponding quizzes. For each proof-of-reading assignment, students documented evidence of completing the assigned readings by submitting either study questions or a reading summary. The study questions assignment consisted of 20 open-ended questions; however, the assignment was graded as a single unit using a complete/incomplete criterion and was worth 25 points total, rather than one point per question. Similarly, the reading summary assignment was graded as complete or incomplete and was worth 25 points. The only feedback provided for proof-of-reading assignments was “full credit earned” (25 points) for submissions meeting all criteria or “no credit earned” (0 points) for submissions that did not meet criteria. No additional qualitative feedback was provided. Each week, regardless of the choice or no-choice condition, students completed a 20-question quiz on the assigned reading. The quiz remained the same regardless of which proof of reading task they completed. After finishing the reading assignment and the quiz, students completed a brief survey assessing their experience with the readings, assignments, and quizzes. The full survey is available in supplemental materials. During the first two weeks, the researcher randomly assigned students either study questions or reading summaries for the first proof of reading assignment, and the alternate format for the second assignment, to expose participants to both tasks before contacting the choice condition. For the next three modules, students chose their proof-of-reading assignment by selecting either reading summaries or study questions. They were able to switch between tasks for each choice opportunity and were not required to complete the same assignment type each time. During the choice weeks, both assignment options (study questions and reading summaries) were presented simultaneously within the Canvas module. To minimize potential positional bias, the order in which the options were displayed (i.e., study questions listed first and reading summaries listed second, or vice versa) was alternated across choice weeks. The three choice weeks were followed by a no-choice week (see Table 1 ). For this no-choice condition, the researcher randomly assigned each student to complete either their most-chosen or least-chosen assignment from the previous three weeks. The assigned task depended on each student’s selections during the previous three choice weeks. Students assigned to their most-chosen task completed the assignment they chose most frequently over the previous three weeks; either study questions or reading summaries. Conversely, students assigned to their least-chosen assignment completed the assignment they selected least often over the previous three weeks. The researcher assigned each student's proof of reading task in CANVAS, accordingly. Participants then completed the quiz and the weekly survey. This schedule of three choice weeks followed by one no-choice week was repeated a second time. Again, students chose which proof-of-reading task to complete for three consecutive weeks. After these three-choice weeks, the researcher assigned each student their most or least selected assignment, contacting the opposite of their previous no-choice condition. For example, if a student was previously assigned to their least-chosen assignment in the previous no-choice condition (e.g., Module 6), they were assigned their most-chosen assignment in the second no-choice week (e.g., Module 10), and vice versa. The researcher assigned study questions or reading summaries according to each student's choices during the previous three choice weeks and whether they were assigned to complete their most or least chosen task. The final choice week followed this no-choice condition and operated exactly like the previous choice weeks, allowing students to select between study questions or reading summaries. Data Validation, Interobserver Agreement and Procedural Fidelity Four secondary observers, all doctoral-level Board Certified Behavior Analysts (BCBA-D), collected data validation, interobserver agreement (IOA) and procedural fidelity data (Fig. 1). To ensure confidence in data migration for quiz scores, a secondary observer conducted a data validation (Vollmer, 2008) check on 54.5% of quiz scores across all classes. The primary researcher transferred quiz scores from CANVAS to the data validation worksheet and shared them with a secondary observer. The secondary observer verified whether the scores on the worksheet matched those recorded in CANVAS to ensure that data were correctly transferred from CANVAS. The primary researcher calculated the percentage of correctly transferred quiz scores. Across all classes, there was 100% agreement for both the initial and final modules, supporting the accuracy and integrity of the quiz score data used in the analyses. The primary researcher scored all proof-of-reading assignments across the six classes included in the study. To assess scoring reliability, four modules from each class were randomly selected for secondary review. Secondary observers independently scored all assignments within those selected modules as complete or incomplete according to the written grading criteria. Inter-observer agreement was calculated using total agreement by dividing the number of agreements by the number of agreements plus disagreements and multiplying by 100. IOA was assessed on 36% of all proof-of-reading assignments (180 of 495) and averaged 99.5% across classes. Secondary observers collected procedural fidelity data to ensure that assignments and quizzes were correctly set up and assigned. This included verifying that proof-of-reading tasks aligned with assigned conditions and participant choices, confirming the correct setup of study questions and reading summaries, and ensuring quizzes followed the intended format (seven multiple-choice, seven multiple-answer, and six matching questions). Procedural fidelity data were collected for 36% of proof-of-reading assignments and quizzes (180 out of 495 for each), with 100% adherence to the planned procedures. These results support the internal validity of the study by confirming accurate data migration, consistent set up of instructional materials and correctly implemented grading procedures. Social Validity A survey was distributed prior to the start of the study that included questions about demographics, participant experience with coursework choice, and the extent to which choices were valued. At the end of each module, students completed an additional survey that consisted of six questions that asked about the perceived helpfulness of having a choice in preparing them for the quiz, the amount of time and effort needed for each assignment, and if they would prefer to choose the next proof-of-reading task, or have the instructor assign it. At the end of the semester, participants completed a survey which included multiple-choice and Likert scale questions about the impact and value of choice in their coursework specifically, as well as in life more generally. Copies of each survey can be found in the Supplemental Online Materials. Results Participants A total of 45 graduate students in online master’s-level ABA classes participated in this study, ranging in age from 22 to 51 years old. Twenty percent of participants self-identified as male and 80% as female. Regarding race and ethnicity, 66.7% of participants identified as White/Caucasian (n = 30) and 4.4% identified as American Indian/Alaskan Native ( n = 2; see Table 2 ). Table 2 Participant Demographics Characteristics Category Frequency Percentage Range Sex Female 36 80% Male 9 20% Age > 18 45 100% 21–52 Race/Ethnicity American Indian and/or Alaskan Native 2 4% Asian and/or Pacific Islander 3 6% Black and/or African American 7 16% Hispanic 7 16% White and/or Caucasian 30 67% Prefer Not to Answer 1 2% Note . Participants were able to choose more than one response for sex and for race/ethnicity, which is why they do not equal exactly 100%. Data were graphed and analyzed for each participant to identify trends within and across conditions, as well as for level and stability. Upon visual analysis of each individual participant’s graphed data, three participants’ (6.7%) data showed differentiation based on condition, with each doing better in the no-choice condition. Differences in weekly quiz scores of these three participants were determined upon visual analysis, with similar trends and levels across conditions. Visual analysis of the remaining 42 (93.3%) participants showed no differentiation as determined by overlapping quiz scores, as well as similar trends and levels in the data across choice and no-choice conditions. A total of 315 quiz scores were recorded in the choice condition and 180 in the no-choice condition, consistent with the study design (seven choice weeks and four no-choice weeks). Data were analyzed both at the individual class level and in aggregate across all six classes (Table 3 ). Line graphs were created for each class, and a combined graph was constructed to visualize trends across all participants, and analyzed for level, trend, and stability within and between conditions (Fig. 1). Table 3 Means and Standard Deviations on Quiz Results Across Classes Class 1 Mean Quiz Score During Choice Weeks Standard Deviation Choice Weeks Mean Quiz Score during No-Choice Weeks Standard Deviation No-Choice Weeks 18.14 0.455 17.21 0.871 Class 2 17.13 0.854 16.84 0.470 Class 3 17.99 0.682 18.32 0.557 Aggregate 17.82 0.343 17.75 0.376 Visual inspection of individual class graphs (see Fig. 1) indicated no meaningful or consistent differentiation between choice and no-choice conditions. Performance across conditions demonstrated substantial overlap, comparable trends, and stable trajectories. Descriptive statistics supported this observation: quiz scores during no-choice weeks ranged from 11.50 to 20.00 (M = 17.75, SD = 1.80), whereas scores during choice weeks ranged from 11.17 to 20.00 (M = 17.82, SD = 1.55). Similarly, the aggregate graph (Fig. 2) showed closely aligned trends across conditions, with overlapping data points and minimal variability across weeks. A Shapiro-Wilk test (Shapiro & Wilk, 1965 ) indicated that quiz scores deviated significantly from normality (W = 0.92, p < .001), warranting nonparametric analysis. A Mann-Whitney U test (Mann & Whitney, 1947 ) revealed no statistically significant difference in quiz performance between choice and no-choice conditions (U = 28049, p = .844). Taken together, both visual and inferential analyses indicate that the presence or absence of assignment choice did not systematically affect quiz performance. At the start of the study, participants completed a questionnaire assessing their general attitudes toward choice by stating their level of agreement across two questions: “I value having choices in my life,” “In my coursework, I value having choices in assignments,” They were also asked “How often have you been exposed to meaningful options in your college coursework?” (see Fig. 4). Responses highlight that while many participants claimed to value having choices, especially in coursework, they have rarely encountered meaningful options in academic settings. Throughout the study, participants completed a brief survey following each weekly quiz. The survey included a self-report estimate of the time spent completing the assigned readings. Most participants reported spending between 1 and 3 hours per week on assigned readings, with no significant difference in reported reading time between choice and no-choice weeks, as indicated by a Mann-Whitney U test (U = 897, p = .35). Participants also rated the amount of time and effort required for each week’s proof-of-reading assignment by selecting one of three options: minimal, just right, or excessive. Across weeks, participants rated the time and effort as “just right” in 77% of responses (SD = 9.86), suggesting that both study questions and reading summaries were generally perceived as appropriately balanced in terms of workload. However, a Mann-Whitney U test revealed a statistically significant difference in perceived time and effort between choice weeks (Median = 2.00) and no-choice weeks (Median = 2.25; U = 637, p = .0015), indicating that participants reported slightly higher perceived effort during no-choice conditions. At the conclusion of the study, 41 of the 45 participants completed the post-semester social validity survey. Participants were asked to rate their level of agreements with statements about the impact of assignment choice on their learning, quiz performance, time and effort on their assignments, and their overall academic performance. Participants overwhelming agreed that having a choice positively impacted them across all of these areas. (see Fig. 5). Although there was not an actual impact on quiz performance based on choice, these findings suggest that students perceived academic choice as a positive influence on their learning, their performance, and their investment of effort. Participants were also asked whether they would prefer to choose their proof-of-reading tasks or to have them assigned by the instructor in future classes. A majority (90%) indicated a preference for making their own choice, while 5% preferred instructor selection and another 5% expressed no preference. Discussion The purpose of this study was to evaluate the impact of choice on quiz performance and student satisfaction for online ABA Master’s students. Using an adapted alternating treatments design replicated across six sections of three elective courses, the study examined quiz outcomes under choice and no-choice conditions, while also capturing students’ preferences, perceived task effectiveness, and social validity data. The choice and no-choice conditions showed substantial overlap and stable, parallel trends, with no consistent or meaningful divergence. These findings indicate that assignment choice did not affect overall performance outcomes. The findings from this study both align with and diverge from previous research on the impact of choice on student outcomes. Consistent with the mixed results reported in the literature, this study did not replicate the advantage of choice in improving quiz performance (Flowerday et al., 2004 ; Hanewicz et al., 2017 ; Patall et al., 2010 ; Tereshko et al., 2024 ). Specifically, although Tereshko et al. ( 2024 ) reported higher quiz scores during choice weeks, the present systematic replication did not observe differentiated performance across conditions; quiz scores during choice weeks closely mirrored those during no-choice weeks. One possible explanation for this divergence relates to methodological refinements implemented in the present study. Unlike prior research, task requirements were equated across conditions through expert review to ensure comparable content coverage and response demands. Additionally, students were exposed to both assignment formats prior to the introduction of choice, potentially reducing novelty effects or differential familiarity with task expectations. By isolating assignment choice from differences in task structure or exposure history, the present findings suggest that the opportunity to choose alone may not be sufficient to produce measurable changes in quiz performance within online graduate coursework. However, the current findings align with previous research demonstrating that choice can positively influence student experience (Flowerday et al., 2004 ; Hanewicz et al., 2017 ; Patall et al., 2010 ; Tereshko et al., 2024 ). In the present study, students reported favorable perceptions of assignment choice, suggesting that although quiz performance did not differ across conditions, perceived autonomy and satisfaction were enhanced. These results support the interpretation that the benefits of instructional choice may extend beyond measurable academic performance and into students’ subjective learning experiences. Taken together, the differential pattern of findings across performance and student-reported outcomes suggests that the effects of choice may be more nuanced. While assignment choice alone may not reliably produce changes in quiz performance when task requirements are equated, it may meaningfully influence how students experience and evaluate their coursework. Future research should therefore examine whether the primary value of instructional choice lies in enhancing student experience, or whether performance effects emerge only under specific instructional arrangements. Although assignment choice did not produce measurable differences in quiz performance, students consistently reported preferring the having a choice of tasks. Social validity data collected throughout the semester indicated strong support for choice, with 90% of participants endorsing its use. This pattern is consistent with prior literature suggesting that while choice does not reliably improve academic achievement, it often enhances perceived autonomy, satisfaction, and motivation (Patall et al., 2008 ; Jopp & Cohen, 2020 ). The absence of a performance effect in the present study is therefore not anomalous but aligned with research indicating that the value of instructional choice may lie more in student experience than in direct academic gains. From a behavior-analytic perspective, assignment choice may function as an antecedent variable that alters how students interact with academic tasks, potentially influencing task initiation or perceived relevance (Michael, 1993 ). However, the present study did not include direct behavioral measures (e.g., latency to begin assignments, time-on-task, or persistence), and therefore no conclusions can be drawn regarding the mechanisms underlying students’ preference for choice. It remains possible that the observed positive perceptions reflect changes in subjective experience rather than measurable changes in academic behavior. Future research should incorporate objective behavioral indicators to determine whether assignment choice produces functional changes in engagement or merely enhances students’ evaluations of instructional practices. One important methodological distinction raised by the current findings concerns the potential conflation of choice as a procedural variable with access to preferred tasks as a reinforcement variable. In some prior studies reporting positive effects of choice on performance or engagement, improved outcomes may have resulted not from the opportunity to choose itself, but from participants ultimately completing tasks with higher relative preference. Consistent with behavioral definitions, choice refers to the availability of multiple response options and the allocation of responding among them, whereas preference reflects differential responding indicative of the relative reinforcing value of those options (Cooper et al., 2020 ; Fisher et al., 1992 ). The present study sought to distinguish these variables by including no-choice conditions in which participants were assigned either their most frequently selected (presumably higher-preference) task or their least frequently selected task. Results indicated no significant differences in quiz performance across these conditions, suggesting that differential task preference alone did not account for performance variation. These findings highlight the need for further research to disentangle the independent and interactive effects of procedural choice, task preference, and instructional equivalence on academic outcomes. The present study also highlights the practicality of implementing assignment choice. Incorporating choice of tasks required minimal additional effort for the instructor, both in designing and grading the assignments, as the options did not necessitate complex adaptations. This simplicity contrasts with earlier studies in which choice was embedded through more elaborate systems, such as point-based grading or menus of dozens of assignments, which while potentially effective, required significantly more planning and instructional labor (e.g., Arendt et al., 2016 ; Hanewicz et al., 2017 ). In contrast, the current design offered structured choice without added logistical complexity. This may help explain why quiz performance did not improve: though students appreciated having choice, the relatively straightforward implementation may not have provided sufficient differentiation to impact learning outcomes (Jopp & Cohen, 2020 ; MacNaul et al., 2021 ; Patall at el., 2008). These findings suggest that while streamlined choice can improve student experience in scalable ways, more robust effects on performance may depend on either the nature of the choices or their integration into broader instructional systems. Nevertheless, this approach remains a low-cost, high-value strategy for asynchronous online learning, one that can enhance student autonomy without sacrificing instructional integrity. Even when improved academic performance is not achieved, the consistent pattern of student preference and reported satisfaction suggests that assignment choice may support a more personalized and student-valued learning experience, even in the absence of measurable academic gains (Deci & Ryan, 2000 ; Patall et al., 2008 , 2010 ). Importantly, the choices offered in this study were instructionally equivalent in content coverage and grading criteria, differing only in response format. This procedural equivalence suggests that incorporating structured choice can enhance student satisfaction without compromising academic rigor. Consistent with this interpretation, quiz performance did not decline during choice weeks, indicating that the opportunity to select assignment format did not adversely affect learning outcomes. Although the present study did not directly measure motivation or behavioral engagement, future research could evaluate whether structured choice influences persistence, task initiation, or time-on-task in online graduate coursework. Although the present study focused exclusively on student outcomes, future research may examine the instructional feasibility of implementing structured choice in online graduate coursework. While the choice arrangement used in this study was designed to minimize instructor burden through standardized grading criteria and equivalent task structures, other forms of choice may differentially affect grading time, planning demands, or course management. Investigating instructor workload, perceptions of fairness, and implementation fidelity may clarify the practical constraints and scalability of choice-based instructional arrangements. There were potential limitations in the current study related to design, procedure, and internal validity. In one course, links to content on an external website became inactive mid-semester, requiring substitution of materials. Additionally, two students in week one completed their quiz and weekly survey before submitting their assigned reading task. This procedural inconsistency was addressed in subsequent modules by modifying the learning management system settings to enforce sequential task submission. These changes ensured consistent sequencing across all remaining weeks. Potential threats to internal validity should also be considered. Although efforts were made to reduce selection bias by including electives from three distinct content areas, participants were not randomly assigned to course sections. As a result, self-selection into courses may have introduced uncontrolled differences in baseline academic ability, prior familiarity with course content, workload demands, or motivation across cohorts. Additionally, subtle differences in instructor delivery, peer interaction patterns, or course topic complexity may have influenced performance independent of assignment condition. Despite these limitations, several design features strengthen internal validity. Procedural sequencing was consistent across sections, grading criteria were standardized, and the experimental conditions were replicated across multiple classes. These controls reduce the likelihood that observed outcomes were attributable to extraneous variables rather than the presence or absence of assignment choice. While caution is warranted when generalizing beyond this instructional context, the findings reflect performance patterns observed under authentic graduate-level conditions. While the current study focused on choice between two types of reading-based assignments, future research could examine other forms of academic choice within online graduate programs. For example, offering students a choice between different content delivery methods (e.g., video lectures vs. readings), assessment formats (e.g., written response vs. oral presentation), or working alone vs. in a group options may reveal additional benefits or limitations of instructional choice. Investigating whether students demonstrate similar preferences and learning outcomes across various dimensions of coursework could help educators identify which types of choices are most meaningful and instructionally effective. Additionally, it may be useful to explore the impact of more complex or personalized choice options, such as offering students a menu of assignment options tailored to specific learning objectives or skill levels. Ultimately, this study contributes to the empirical literature on instructional choice in graduate education by isolating assignment choice from task structure and preference effects within online graduate coursework. When task requirements were equated and exposure history controlled, the opportunity to choose did not independently influence quiz performance. However, students consistently endorsed the availability of structured choice. These findings suggest that procedural choice may influence student experience without altering performance under equivalent instructional conditions. Continued research should identify the conditions under which instructional choice produces functional changes in academic behavior. Declarations Author Contribution All authors contributed to the writing and review of the manuscript. Data Availability All data supporting the findings of this study are available within the paper and its Supplementary Information. References Arendt, A., Trego, A., & Allred, J. (2016). Students reach beyond expectations with cafeteria style grading. Journal of Applied Research in Higher Education , 8 (1), 2–17. https://doi.org/10.1108/JARHE-03-2014-0048 Baer, D. M., Wolf, M. M., & Risley, T. R. (1968). Some current dimensions of applied behavior analysis. Journal of Applied Behavior Analysis , 1 (1), 91–97. https://doi.org/10.1901/jaba.1968.1-91 Bensoussan, M., & Kreindler, I. (1990). Improving advanced reading comprehension in a foreign language: Summaries vs. short-answer questions. Journal of Research in Reading , 13 (1), 55–68. https://doi.org/10.1111/j.1467-9817.1990.tb00322.x Bird, Z., & Chase, P. N. (2021). Student pacing in a master’s level course: Procrastination, preference, and performance. Journal of Applied Behavior Analysis , 54 (3), 1220–1234. https://doi.org/10.1002/jaba.806 Cariveau, T., & Fetzner, D. (2022). Experimental control in the adapted alternating treatments design: A review of procedures and outcomes. Behavioral Interventions , 37 (3), 805–818. https://doi.org/10.1002/bin.1865 Carter, E., Molina, E., Pushparatnam, A., Rimm-Kaufman, S., Tsapali, M., & Wong, K. K. Y. (2024). Evidence-based teaching: effective teaching practices in primary school classrooms. London Review of Education , 22 (1), 8. https://doi.org/10.14324/LRE.22.1.08 Cooper, J. O., Heron, T. E., & Heward, W. L. (2020). Applied behavior analysis (3rd ed.). Pearson. Dabrowski, J., & Marshall, T. R. (2018). Motivation and engagement in student assignments: The role of choice and relevancy. The Education Trust. https://edtrust.org/resource/motivation-and-engagement-in-student-assignments/ Deci, E. L., & Ryan, R. M. (2000). The what and why of goal pursuits: Human needs and the self-determination of behavior. Psychological Inquiry , 11 (4), 227–268. https://doi.org/10.1207/S15327965PLI1104_01 Fisher, W., Piazza, C. C., Bowman, L. G., Hagopian, L. P., Owens, J. C., & Slevin, I. (1992). A comparison of two approaches for identifying reinforcers for persons with severe and profound disabilities. Journal of Applied Behavior Analysis , 25 (2), 491–498. 10.1901/jaba.1992.25-491 Flaherty, C. (2024, July 31). When given the choice, college students select more rigorous courses. Inside Higher Ed. https://www.insidehighered.com/news/student-success/academic-life/2024/07/31/when-given-choice-college-students-select-rigorous Flowerday, T., Schraw, G., & Stevens, J. (2004). The role of choice and interest in reader engagement. Journal of Experimental Education , 72 (2), 93–114. https://doi.org/10.3200/JEXE.72.2.93-114 Gay, G. (2002). Preparing for culturally responsive teaching. Journal of Teacher Education , 53 (2), 106–116. https://doi.org/10.1177/0022487102053002003 Ghaemmaghami, M., Ruppel, K., & Cammilleri, A. P. (2024). Toward compassion in the assessment and treatment of severe problem behavior. Behavior Analysis in Practice . https://doi.org/10.1007/s40617-024-01012-1 Hamilton, I. (2024, May 31). 2024 online learning statistics . Forbes. https://www.forbes.com/advisor/education/online-colleges/online-learning-stats/ Hanewicz, C., Platt, A., & Arendt, A. (2017). Creating a learner-centered teaching environment using student choice in assignments. Distance Education , 38 (3), 273–287. https://doi.org/10.1080/01587919.2017.1369349 Harrington, C. (2024). How much assignment choice do students have? A descriptive study of syllabi. Currents in Teaching and Learning , 15 (2), 6–15. Hattie, J. (2009). Visible Learning: A Synthesis of Over 800 Meta-Analyses Relating to . Achievement Routledge. Haydon, T., Macsuga-Gage, A. S., Simonsen, B., & Hawkins, R. (2012). Opportunities to respond: A key component of effective instruction. Beyond Behavior , 22 (1), 23–31. https://doi.org/10.1177/107429561202200105 Jamero, J., Adelman, H. S., & Taylor, L. (2023). Empathy, compassion, and addressing student misbehavior. National Center for Mental Health in Schools at UCLA. Retrieved from http://smph.psych.ucla.edu Jopp, R., & Cohen, J. (2020). Choose your own assessment: Assessment choice for students in online higher education. Teaching in Higher Education. Advance online publication. https://doi.org/10.1080/13562517.2020.1742680 Lockhart, K. A., Sexton, J., & Lea, C. (1975). The Findley procedure: A method for examining choice-making behavior in academic settings. Behavior Research and Technical in Higher Education , 46 (3), 456–462. Lockman, A. S., & Schirmer, B. R. (2020). Online instruction in higher education: Promising, research-based, and evidence-based practices. Journal of Education and e-Learning Research , 7 (2), 130–152. http://dx.doi.org/10.20448/journal.509.2020.72.130.152 MacNaul, H., Garcia, R., Cividini-Motta, C., & Thacker, I. (2021). Effect of assignment choice on student academic performance in an online class. Behavior Analysis in Practice , 14 (4), 1074–1078. https://doi.org/10.1007/s40617-021-00566-8 Mann, H. B., & Whitney, D. R. (1947). On a test of whether one of two random variables is stochastically larger than the other. The Annals of Mathematical Statistics , 18 (1), 50–60. https://doi.org/10.1214/aoms/1177730491 May, M. E. (2018). Effects of differential consequences on choice making in students at risk for academic failure. Behavior Analysis in Pract ice. 2018;12(1):154–161. https://doi.org/10.1007/s40617-018-0267-3 Means, B., Toyama, Y., Murphy, R., Bakia, M., & Jones, K. (2013). The effectiveness of online and blended learning: A meta-analysis of the empirical literature. U.S. Department of Education, Office of Planning, Evaluation, and Policy Development. Retrieved from https://www2.ed.gov/rschstat/eval/tech/evidence-based-practices/finalreport.pdf Michael, J. (1993). Establishing operations. The Behavior Analyst , 16 (2), 191–206. https://doi.org/10.1007/BF03392623 National Center for Education Statistics, Postsecondary Education (2024, May). National Center for Education Statistics. https://nces.ed.gov/programs/coe/indicator/ctb/graduate-degree-fields Patall, E. A., Cooper, H., & Robinson, J. C. (2008). The effects of choice on intrinsic motivation and related outcomes: A meta-analysis of research findings. Psychological Bulletin , 134 (2), 270–300. https://doi.org/10.1037/0033-2909.134.2.270 Patall, E. A., Cooper, H., & Wynn, S. R. (2010). The effectiveness and relative importance of choice in the classroom. Journal of Educational Psychology , 102 (4), 896–915. https://doi.org/10.1037/a0019545 Penney, A. M., Bateman, K. J., Veverka, Y., Luna, A., & Schwartz, I. S. (2023). Compassion: The eighth dimension of applied behavior analysis. Behavior Analysis in Practice . https://doi.org/10.1007/s40617-023-00888-9 Rajaraman, A., Austin, J. L., & Gover, H. C. (2023). A practitioner's guide to emphasizing choice-making opportunities in behavioral services provided to individuals with intellectual and developmental disabilities. International Journal of Developmental Disabilities , 69 (1), 101–110. https://doi.org/10.1080/20473869.2022.2117911 Shapiro, S. S., & Wilk, M. B. (1965). An analysis of variance test for normality (complete. samples) Biometrika , 52 (3/4), 591–611. https://doi.org/10.1093/biomet/52.3-4.591 Sinclair, S., Kondejewski, J., Jaggi, P., Dennett, L., Roze des Ordons, A. L., & Hack, T. F. (2021). What is the state of compassion education? A systematic review of compassion training in health care. Academic medicine: Journal of the Association of American Medical Colleges , 96 (7), 1057–1070. https://doi.org/10.1097/ACM.0000000000004114 Sindelar, P. T., Rosenberg, M. S., & Wilson, R. J. (1985). An adapted alternating treatments. design for instructional research Education and Treatment of Children , 8(1), 67–76. http://jstor.org/stable/42898888. Tereshko, L. M., Zane, T., & Weiss, M. J. (2024). The effect of choice on student performance in online graduate classes. Journal of Behavioral Education . https://doi.org/10.1007/s10864-024-09543-x . Advance online publication. Thibodeaux, T., Harapnuik, D., & Cummings, C. (2019). Student perceptions of the influence of choice, ownership, and voice in learning and the learning environment. International Journal of Teaching and Learning in Higher Education, 31(1), 50–62. Retrieved from https://files.eric.ed.gov/fulltext/EJ1206966.pdf Tincani, M., Brodhead, M. T., & Dowdy, A. (2024). Aba promotes autonomy and choice of people with intellectual and developmental disabilities. Journal of Developmental and Physical Disabilities . https://doi.org/10.1007/s10882-024-09949-5 . Advance online publication. Vollmer, T. R., Sloman, K. N., & St. Peter Pipkin, C. (2008). Practical implications of data reliability and treatment integrity monitoring. Behavior Analysis in Practice , 1 , 4–11. https://doi.org/10.1007/BF03391722 Wolf, M. M. (1978). Social validity: The case for subjective measurement or how applied behavior analysis is finding its heart. Journal of Applied Behavior Analysis , 11 (2), 203–214. https://doi.org/10.1901/jaba.1978.11-203 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 20 Apr, 2026 Reviews received at journal 20 Apr, 2026 Reviewers agreed at journal 17 Apr, 2026 Reviewers invited by journal 16 Apr, 2026 Editor assigned by journal 02 Apr, 2026 Submission checks completed at journal 02 Apr, 2026 First submitted to journal 29 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9261351","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":628486204,"identity":"ef95d7e9-1c69-4782-a498-3c9b3854e854","order_by":0,"name":"Kristin Foley","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA20lEQVRIiWNgGAWjYBACCeYDjAcYGGyAzMQGqFgCAS1sCQxALWlQLQkGRGs5DFVJjBbJNuYDBz62nZczZ09u/PDxxx8GfvYcA7xapNnYEg7ObLttbNnzsFlyBtAWyZ43+LXIyfcYHOZtu5244UZiGzMPUIvBDQK2yLHxGBz+23auHq7FnpAWaZAWxrYDCQZwWyQIaJFsA/ql51yy4YYzIL+kGfNInHlWgFeLxDHmgw9+lNnJGxxPf/jhg42cHH978ga8WsCAkQ3B5iGsHAz+EKluFIyCUTAKRiYAAH/fSZn8lrWMAAAAAElFTkSuQmCC","orcid":"","institution":"Endicott College","correspondingAuthor":true,"prefix":"","firstName":"Kristin","middleName":"","lastName":"Foley","suffix":""},{"id":628486205,"identity":"75ff1cc4-0926-4457-b97c-1ef48ac55a4c","order_by":1,"name":"Paul Gavoni","email":"","orcid":"","institution":"Endicott College","correspondingAuthor":false,"prefix":"","firstName":"Paul","middleName":"","lastName":"Gavoni","suffix":""},{"id":628486206,"identity":"4b4731c7-7976-4b35-8105-0d319975c653","order_by":2,"name":"Thomas Zane","email":"","orcid":"","institution":"University of Kansas","correspondingAuthor":false,"prefix":"","firstName":"Thomas","middleName":"","lastName":"Zane","suffix":""},{"id":628486207,"identity":"aaa31e96-fac3-4306-9b0e-7e5726d8c7fb","order_by":3,"name":"David J Cox","email":"","orcid":"","institution":"Endicott College","correspondingAuthor":false,"prefix":"","firstName":"David","middleName":"J","lastName":"Cox","suffix":""},{"id":628486208,"identity":"1376cb81-a022-4b5b-91d4-73bdbe9ecfba","order_by":4,"name":"Mary Jane Weiss","email":"","orcid":"","institution":"Endicott College","correspondingAuthor":false,"prefix":"","firstName":"Mary","middleName":"Jane","lastName":"Weiss","suffix":""}],"badges":[],"createdAt":"2026-03-30 00:38:41","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9261351/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9261351/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":107834717,"identity":"ffa05df8-09f6-4947-b46f-03977f248f41","added_by":"auto","created_at":"2026-04-26 15:48:17","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":26745,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eAverage Quiz Scores per Class\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNote\u003c/em\u003e: The grey bars represent the Standard Error of the Mean (SEM).\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9261351/v1/5c3aa84d0e7cf5dca39fa019.png"},{"id":107834713,"identity":"12a3ff19-7e84-4c4b-bde6-b83fde136fc2","added_by":"auto","created_at":"2026-04-26 15:48:16","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":15826,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eAverage Quiz Scores for all Participants per Condition\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNote\u003c/em\u003e: The grey bars represent the SEM.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-9261351/v1/b6f2946d0427ca368235c398.png"},{"id":107870412,"identity":"d098190b-c151-4c1f-a7cc-13205dc5fc18","added_by":"auto","created_at":"2026-04-27 07:39:37","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":19383,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003ePoints Earned per Quiz in Each Condition\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eNote\u003c/em\u003e. Each light grey dot represents an individual quiz score. Horizontal lines indicate the\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-9261351/v1/9ca9a7eefd64f4972c92c16b.png"},{"id":107870196,"identity":"50cccbe3-e15e-4864-9acb-b709d68cd149","added_by":"auto","created_at":"2026-04-27 07:39:06","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":15068,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eValue and Exposure to Choice\u003c/em\u003e\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-9261351/v1/81d24fb6917bae7ed4c29e1c.png"},{"id":107834716,"identity":"3f44e9cb-e6f9-4f66-af33-3cbb88be252d","added_by":"auto","created_at":"2026-04-26 15:48:16","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":23984,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003ePerceived Impact of Choice\u003c/em\u003e\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-9261351/v1/2e691470305b9ec7637c9b4f.png"},{"id":107872241,"identity":"7405bcff-c58f-43e5-bf69-f837b881c3e5","added_by":"auto","created_at":"2026-04-27 07:56:23","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":429250,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9261351/v1/cb9569a8-ed5d-4f10-863b-9af19d23c674.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Effects of Assignment Choice on Quiz Performance and Student Experience in Online Graduate Education","fulltext":[{"header":"Introduction","content":"\u003cp\u003eInstructional effectiveness is often determined by how well students acquire, retain, and apply knowledge and skills, with evidence-based teaching practices increasing the probability that learning occurs efficiently and meaningfully (Hattie, \u003cspan class=\"CitationRef\"\u003e2009\u003c/span\u003e). Effective teaching requires a combination of structured lesson delivery, continuous assessment, and constructive feedback. The delivery of such instruction is often characterized by structured student engagement, high rates of student participation, and frequent opportunities to respond to enhance comprehension and retention (Carter et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e; Haydon et al., \u003cspan class=\"CitationRef\"\u003e2012\u003c/span\u003e; Means et al., \u003cspan class=\"CitationRef\"\u003e2013\u003c/span\u003e). Beyond engagement and feedback, well-defined learning objectives and effective course design can further support student success (Lockman \u0026amp; Schirmer, \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eApplied behavior analysis (ABA) seeks to develop and evaluate socially significant interventions across applied settings (Baer et al., \u003cspan class=\"CitationRef\"\u003e1968\u003c/span\u003e; Penney, 2023; Rajaraman et al., \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e; Tincani et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e). In educational contexts, these principles are often applied to increase student engagement, skill acquisition, and academic outcomes. With the expansion of online graduate education, improving instructional design and aligning coursework with student preferences has become increasingly important for maintaining quality and supporting positive learning experiences (Hamilton, 2024). From a behavior-analytic perspective, assignment choice represents an antecedent manipulation that may alter how students interact with academic tasks. By systematically evaluating the effects of such antecedent variables, the use of behavior-analytic methods may help ensure rigor and instructional effectiveness in on-line higher education.\u003c/p\u003e\n\u003cp\u003eOver the past two decades, online education has become an increasingly integral component of higher education in the United States. According to the National Center for Education Statistics (2024), more than 10\u0026nbsp;million college students enrolled in at least one online course in 2022, including approximately 1.1\u0026nbsp;million students enrolled in programs delivered primarily online. This reflects a 16% increase in online course enrollment since 2011. During the height of the COVID-19 pandemic, 73.1% of all postsecondary students were enrolled in at least one online course. Although that proportion has declined since its peak, more than half of U.S. college students continue to take at least one online class (Hamilton, 2024).\u003c/p\u003e\n\u003cp\u003eWhile effective instructional practices are essential, student choice has emerged as a potentially influential instructional variable in learning outcomes (Deci \u0026amp; Ryan, \u003cspan class=\"CitationRef\"\u003e2000\u003c/span\u003e; Thibodeaux et al., \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e). Research suggests that providing students with structured opportunities to choose aspects of their learning may evoke higher rates of responding (May, \u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e), enhance student motivation (Dabrowski \u0026amp; Marshall, \u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e), increase engagement (Jamero et al., \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e), and improve measures of academic performance such as quiz scores (Deci \u0026amp; Ryan, \u003cspan class=\"CitationRef\"\u003e2000\u003c/span\u003e). In educational settings, structured instructional methods may be supplemented by incorporating opportunities for student choice, allowing learners to engage with material in ways that align with their preferences, strengths, and prior experiences (Dabrowski \u0026amp; Marshall \u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e; Patall, et al., \u003cspan class=\"CitationRef\"\u003e2008\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eStudent-centered approaches that allow learners to choose how they engage with content are consistent with broader movements toward inclusive and responsive pedagogy (Gay, \u003cspan class=\"CitationRef\"\u003e2002\u003c/span\u003e; Rajaraman et al., \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e). Offering structured choice may contribute to perceptions of fairness and inclusivity in online learning environments. Prior research has linked opportunities for choice with increased participation and persistence in some educational contexts. However, despite growing advocacy for student-centered instruction, Harrington (\u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e) found that the prevalence of assignment choice has remained largely stagnant over the past 25 years, suggesting a disconnect between pedagogical discourse and instructional practice.\u003c/p\u003e\n\u003cp\u003eFrom a behavior-analytic perspective, offering choice may function as an antecedent variable that alters the reinforcing value of task completion (Michael, \u003cspan class=\"CitationRef\"\u003e1993\u003c/span\u003e). For example, when students are permitted to select among functionally similar assignments, the opportunity to choose may increase the relative value of completing the selected task or decrease aversiveness associated with imposed formats (Jamero et al., \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e). In this way, choice may influence task initiation or completion.\u003c/p\u003e\n\u003cp\u003eBeyond potential effects on academic performance, choice may also relate to constructs such as social validity and student experience. Social validity refers to acceptability and perceived value of procedures and outcomes from participants (Wolf, \u003cspan class=\"CitationRef\"\u003e1978\u003c/span\u003e). Providing structured opportunities for choice may increase the perceived fairness or acceptability of educational experiences. Some scholars have argued that student-focused practices may contribute to more inclusive and responsive educational environments (Ghaemmaghami et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e; Penney et al., \u003cspan class=\"CitationRef\"\u003e2023\u003c/span\u003e). For example, Sinclair et al. (\u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e) identified instructional strategies such as reflective writing and service learning that were associated with increased student-reported persistence and engagement with coursework. Although these outcomes were not operationalized in the current study, they suggest that instructional variables such as choice may influence dimensions of student experience beyond quiz performance.\u003c/p\u003e\n\u003cp\u003eSeveral empirical studies have explored how choice impacts student outcomes. For example, Lockhart et al. (\u003cspan class=\"CitationRef\"\u003e1975\u003c/span\u003e) examined the impact of student choice on performance in a traditional in-person undergraduate psychology course, comparing multiple-choice and fill-in-the-blank test formats. The researchers found that students preferred multiple-choice questions and performed better when given their preferred format. Bird and Chase (\u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e) investigated the effects of assignment structure on procrastination and academic performance among graduate students in a hybrid Master's-level ABA course. Using an alternating treatments design with an embedded choice component, the researchers compared contingent access to practice quizzes (i.e., quizzes available only after completing specified tasks) and noncontingent access (i.e., quizzes available without prerequisite assignments). Dependent variables included quiz completion and accuracy. Although most students selected noncontingent access when given the choice, visual and statistical analyses found no consistent differences in quiz scores between conditions. These findings suggest that while students preferred noncontingent access to practice materials, having this choice did not alter academic performance.\u003c/p\u003e\n\u003cp\u003eIn one of the most directly relevant studies, Tereshko et al. (\u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e) evaluated how assignment choice affected quiz performance in online Master\u0026rsquo;s-level ABA courses using a modified alternating treatments design. Students completed weekly quizzes following either instructor-assigned tasks (no-choice condition) or self-selected assignments (choice condition). Across all sections, mean quiz scores were higher during choice weeks (M\u0026thinsp;=\u0026thinsp;15.70, SD\u0026thinsp;=\u0026thinsp;3.04) compared to no-choice weeks (M\u0026thinsp;=\u0026thinsp;14.00, SD\u0026thinsp;=\u0026thinsp;3.73). A nonparametric analysis indicated that this difference was statistically significant (p = .0052), suggesting that the opportunity to choose assignments was associated with improved quiz performance. However, variability differed across sections, with Section 3 demonstrating greater overlap between conditions than Sections 1 and 2. Although statistically significant, the mean difference of 1.7 points on a 20-point quiz reflects a modest effect size, raising questions about the magnitude and generalizability of the observed benefit. Additionally, potential differences in response effort and task structure between assignments were noted by the authors as possible contributing variables, warranting replication under conditions that more tightly control for instructional equivalence.\u003c/p\u003e\n\u003cp\u003eResearch on choice in education has yielded mixed findings regarding its impact on student performance. Some studies have reported positive effects of choice on academic outcomes (Flowerday et al., \u003cspan class=\"CitationRef\"\u003e2004\u003c/span\u003e; Hanewicz et al., \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e; Patall et al., \u003cspan class=\"CitationRef\"\u003e2010\u003c/span\u003e; Tereshko et al., \u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e), whereas others have found minimal or no direct effects on performance (Bird \u0026amp; Chase, \u003cspan class=\"CitationRef\"\u003e2021\u003c/span\u003e; Flaherty, 2024; Jopp \u0026amp; Cohen, \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e; Patall et al., \u003cspan class=\"CitationRef\"\u003e2008\u003c/span\u003e). These discrepancies may reflect methodological differences across studies, including variation in the type of choice offered (e.g., assignment format, pacing, grading structure), differences in response effort between options, whether preference was experimentally established prior to choice exposure, and the extent to which research designs isolated the effect of choice itself from access to preferred tasks. Studies have also differed in instructional modality (online vs. face-to-face), participant population (undergraduate vs. graduate), and analytic approach (group statistical designs vs. single-case methodologies).\u003c/p\u003e\n\u003cp\u003eAn unresolved question, therefore, is whether assignment choice independently influences academic performance and student experience when task requirements, exposure history, and content equivalence are controlled. The present study evaluated this question within online graduate coursework by systematically manipulating assignment choice while equating task demands across conditions. Although the design functioned as a systematic replication of Tereshko et al. (\u003cspan class=\"CitationRef\"\u003e2024\u003c/span\u003e), key methodological refinements, including expert-verified content equivalence and controlled exposure to assignment formats prior to the introduction of choice, were implemented to isolate the contribution of procedural choice to quiz performance. Accordingly, the present study asked: Does assignment choice independently influence quiz performance and student experiences when task requirements, response effort, and exposure history are held constant?\u003c/p\u003e"},{"header":"Method","content":"\u003cdiv id=\"Sec2\" class=\"Section2\"\u003e \u003ch2\u003eParticipants and Setting\u003c/h2\u003e \u003cp\u003eForty-five graduate students in six sections of three different online Master\u0026rsquo;s-level courses in Applied Behavior Analysis (ABA) participated in this study. The courses took place on CANVAS\u0026reg;, a digital learning management system, and were asynchronous, meaning all class materials were available online with no synchronous meeting times. The study was approved by the college\u0026rsquo;s Institutional Review Board (IRB).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eMaterials\u003c/h2\u003e \u003cp\u003eAll instructional materials were delivered through the Canvas learning management system. Weekly course content included assigned readings, recorded lectures, discussion prompts, and a 20-item quiz assessing mastery of the assigned material. The primary materials relevant to the independent variable were two proof-of-reading assignments: (a) a structured study guide consisting of 20 open-ended questions and (b) a reading summary requiring a minimum three-page synthesis of the assigned readings. Both assignments were graded for completion and were required prior to quiz access.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eDependent Variable\u003c/h3\u003e\n\u003cp\u003eThe dependent measure was points earned on weekly quizzes, each comprised of 20 questions. The weekly quizzes included seven multiple-choice questions (i.e., one correct answer out of four options), seven multiple-answer questions (i.e., two or more correct answers out of four options), and six matching questions (i.e., selecting the correct definition or description for a term or concept). Each question was worth one point, for a total of 20 possible points per quiz. Participants received the same quiz regardless of which proof-of-reading task was completed. Quizzes were graded automatically within Canvas to ensure scoring consistency across participants and conditions, and no instructor feedback was provided to prevent differential post-quiz learning effects that could influence subsequent performance.\u003c/p\u003e\n\u003ch3\u003eExperimental Design\u003c/h3\u003e\n\u003cp\u003eAn adapted alternating treatments design with a predetermined (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) semi-randomized schedule (Cariveau \u0026amp; Fetzner, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2022\u003c/span\u003e) was used to assess the impact of choice and no-choice conditions on quiz scores. This design was chosen due to its ability to simultaneously compare the effectiveness of each task within the same participant (Sindelar, 1985).\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\u003e\u003cem\u003ePredetermined Schedule of Conditions\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"12\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWeek 1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWeek 2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWeek 3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eWeek 4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eWeek 5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eWeek 6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eWeek 7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eWeek 8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eWeek 9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eWeek 10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eWeek 11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCondition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003eNC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c12\"\u003e \u003cp\u003eC\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"12\"\u003e\u003cem\u003eNot\u003c/em\u003ee. NC\u0026thinsp;=\u0026thinsp;No-choice week, C= Choice week\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003eIndependent Variable\u003c/h3\u003e\n\u003cp\u003eThe independent variable was the availability of assignment choice. During no-choice weeks, students were assigned either reading summaries or study questions without the opportunity to select their preferred option; assignment type was randomly determined to control for potential preference effects (see below for assignment descriptions). During choice weeks, students were permitted to select their preferred assignment from the same two options. The study question and reading summary tasks differed in format but were designed to be instructionally equivalent in content coverage, response expectations, and grading criteria, thereby assessing comprehension of the same assigned material (Bensoussan \u0026amp; Kreindler, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e1990\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBoth assignments were evaluated using an all-or-nothing completion criterion. The study question assignment consisted of 20 open-ended questions aligned with the week\u0026rsquo;s assigned readings. To receive credit, responses were required to (a) contain 2\u0026ndash;6 sentences per question, (b) address all components of each prompt using accurate terminology, and (c) be written in the student\u0026rsquo;s own words. Instructor review determined whether responses met these criteria. Submissions containing verbatim text from assigned readings without citation or substantive paraphrasing were scored as incomplete.\u003c/p\u003e \u003cp\u003eFor the reading summary assignment, students were required to submit an approximately three-page summary of the assigned readings that included (a) coverage of all required readings, (b) discussion of clinical and/or personal application, and (c) reflection on key concepts identified as meaningful. Summaries were evaluated for adherence to length requirements, inclusion of required components, and originality of expression. Submissions that reproduced source material verbatim without citation were scored as incomplete.\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eProcedures\u003c/h2\u003e \u003cp\u003eSenior staff at the college who are doctoral-level Behavior Analysts (BCBA-Ds) evaluated the content difficulty level across each week and condition prior to the start of the study. These three professionals analyzed the content of every module of each course to determine the level of difficulty each. Modules were rated as 1 (low level of difficulty), 2 (moderate level of difficulty), or 3 (high level of difficulty). These scores were averaged across all raters. The average level of difficulty by course ranged from 1.70 to 2.00, with the overall average difficulty across all modules and courses being 1.87 (\u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.43), indicating generally moderate difficulty with relatively low variability among raters. Additionally, these experts rated the overall equivalence of content difficulty across all modules of each class on a three-point scale with 1 indicating a minimal level of equivalence, 2 indicating a moderate level of equivalence, and 3 indicating a high level of equivalence across the semester. The overall equivalence of content across each class averaged 2.7 out of 3.\u003c/p\u003e \u003cp\u003e At the start of the semester, the researcher informed all participants that they could choose whether to consent to having their de-identified data included in the study, and that the course would proceed as planned regardless of their decision. Participants were also informed that the researcher and instructors would remain blind to their consent status until after final grades were submitted. Additionally, participants were told that they could revoke their consent at any time during the study.\u003c/p\u003e \u003cp\u003eEach module lasted one week, with assignments due on Sundays at 11:59 p.m. EST. Across the semester, students completed eleven proof-of-reading assignments and eleven corresponding quizzes. For each proof-of-reading assignment, students documented evidence of completing the assigned readings by submitting either study questions or a reading summary. The study questions assignment consisted of 20 open-ended questions; however, the assignment was graded as a single unit using a complete/incomplete criterion and was worth 25 points total, rather than one point per question. Similarly, the reading summary assignment was graded as complete or incomplete and was worth 25 points. The only feedback provided for proof-of-reading assignments was \u0026ldquo;full credit earned\u0026rdquo; (25 points) for submissions meeting all criteria or \u0026ldquo;no credit earned\u0026rdquo; (0 points) for submissions that did not meet criteria. No additional qualitative feedback was provided.\u003c/p\u003e \u003cp\u003eEach week, regardless of the choice or no-choice condition, students completed a 20-question quiz on the assigned reading. The quiz remained the same regardless of which proof of reading task they completed. After finishing the reading assignment and the quiz, students completed a brief survey assessing their experience with the readings, assignments, and quizzes. The full survey is available in supplemental materials.\u003c/p\u003e \u003cp\u003eDuring the first two weeks, the researcher randomly assigned students either study questions or reading summaries for the first proof of reading assignment, and the alternate format for the second assignment, to expose participants to both tasks before contacting the choice condition. For the next three modules, students chose their proof-of-reading assignment by selecting either reading summaries or study questions. They were able to switch between tasks for each choice opportunity and were not required to complete the same assignment type each time. During the choice weeks, both assignment options (study questions and reading summaries) were presented simultaneously within the Canvas module. To minimize potential positional bias, the order in which the options were displayed (i.e., study questions listed first and reading summaries listed second, or vice versa) was alternated across choice weeks.\u003c/p\u003e \u003cp\u003eThe three choice weeks were followed by a no-choice week (see Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). For this no-choice condition, the researcher randomly assigned each student to complete either their most-chosen or least-chosen assignment from the previous three weeks. The assigned task depended on each student\u0026rsquo;s selections during the previous three choice weeks. Students assigned to their most-chosen task completed the assignment they chose most frequently over the previous three weeks; either study questions or reading summaries. Conversely, students assigned to their least-chosen assignment completed the assignment they selected least often over the previous three weeks. The researcher assigned each student's proof of reading task in CANVAS, accordingly. Participants then completed the quiz and the weekly survey.\u003c/p\u003e \u003cp\u003eThis schedule of three choice weeks followed by one no-choice week was repeated a second time. Again, students chose which proof-of-reading task to complete for three consecutive weeks. After these three-choice weeks, the researcher assigned each student their most or least selected assignment, contacting the opposite of their previous no-choice condition. For example, if a student was previously assigned to their least-chosen assignment in the previous no-choice condition (e.g., Module 6), they were assigned their most-chosen assignment in the second no-choice week (e.g., Module 10), and vice versa. The researcher assigned study questions or reading summaries according to each student's choices during the previous three choice weeks and whether they were assigned to complete their most or least chosen task.\u003c/p\u003e \u003cp\u003eThe final choice week followed this no-choice condition and operated exactly like the previous choice weeks, allowing students to select between study questions or reading summaries.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eData Validation, Interobserver Agreement and Procedural Fidelity\u003c/h3\u003e\n\u003cp\u003eFour secondary observers, all doctoral-level Board Certified Behavior Analysts (BCBA-D), collected data validation, interobserver agreement (IOA) and procedural fidelity data (Fig.\u0026nbsp;1). To ensure confidence in data migration for quiz scores, a secondary observer conducted a data validation (Vollmer, 2008) check on 54.5% of quiz scores across all classes. The primary researcher transferred quiz scores from CANVAS to the data validation worksheet and shared them with a secondary observer. The secondary observer verified whether the scores on the worksheet matched those recorded in CANVAS to ensure that data were correctly transferred from CANVAS. The primary researcher calculated the percentage of correctly transferred quiz scores. Across all classes, there was 100% agreement for both the initial and final modules, supporting the accuracy and integrity of the quiz score data used in the analyses.\u003c/p\u003e \u003cp\u003eThe primary researcher scored all proof-of-reading assignments across the six classes included in the study. To assess scoring reliability, four modules from each class were randomly selected for secondary review. Secondary observers independently scored all assignments within those selected modules as complete or incomplete according to the written grading criteria.\u003c/p\u003e \u003cp\u003eInter-observer agreement was calculated using total agreement by dividing the number of agreements by the number of agreements plus disagreements and multiplying by 100. IOA was assessed on 36% of all proof-of-reading assignments (180 of 495) and averaged 99.5% across classes.\u003c/p\u003e \u003cp\u003eSecondary observers collected procedural fidelity data to ensure that assignments and quizzes were correctly set up and assigned. This included verifying that proof-of-reading tasks aligned with assigned conditions and participant choices, confirming the correct setup of study questions and reading summaries, and ensuring quizzes followed the intended format (seven multiple-choice, seven multiple-answer, and six matching questions). Procedural fidelity data were collected for 36% of proof-of-reading assignments and quizzes (180 out of 495 for each), with 100% adherence to the planned procedures. These results support the internal validity of the study by confirming accurate data migration, consistent set up of instructional materials and correctly implemented grading procedures.\u003c/p\u003e\n\u003ch3\u003eSocial Validity\u003c/h3\u003e\n\u003cp\u003eA survey was distributed prior to the start of the study that included questions about demographics, participant experience with coursework choice, and the extent to which choices were valued. At the end of each module, students completed an additional survey that consisted of six questions that asked about the perceived helpfulness of having a choice in preparing them for the quiz, the amount of time and effort needed for each assignment, and if they would prefer to choose the next proof-of-reading task, or have the instructor assign it. At the end of the semester, participants completed a survey which included multiple-choice and Likert scale questions about the impact and value of choice in their coursework specifically, as well as in life more generally. Copies of each survey can be found in the Supplemental Online Materials.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003eParticipants\u003c/h2\u003e\n \u003cp\u003eA total of 45 graduate students in online master\u0026rsquo;s-level ABA classes participated in this study, ranging in age from 22 to 51 years old. Twenty percent of participants self-identified as male and 80% as female. Regarding race and ethnicity, 66.7% of participants identified as White/Caucasian (n\u0026thinsp;=\u0026thinsp;30) and 4.4% identified as American Indian/Alaskan Native (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2; see Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003e\u003cem\u003eParticipant Demographics\u003c/em\u003e\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCharacteristics\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCategory\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eFrequency\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePercentage\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eRange\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\u003eSex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e80%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21\u0026ndash;52\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRace/Ethnicity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAmerican Indian and/or Alaskan Native\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAsian and/or Pacific Islander\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBlack and/or African American\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHispanic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWhite and/or Caucasian\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e67%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrefer Not to Answer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003e\u003cem\u003eNote\u003c/em\u003e. Participants were able to choose more than one response for sex and for race/ethnicity, which is why they do not equal exactly 100%.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eData were graphed and analyzed for each participant to identify trends within and across conditions, as well as for level and stability. Upon visual analysis of each individual participant\u0026rsquo;s graphed data, three participants\u0026rsquo; (6.7%) data showed differentiation based on condition, with each doing better in the no-choice condition. Differences in weekly quiz scores of these three participants were determined upon visual analysis, with similar trends and levels across conditions. Visual analysis of the remaining 42 (93.3%) participants showed no differentiation as determined by overlapping quiz scores, as well as similar trends and levels in the data across choice and no-choice conditions.\u003c/p\u003e\n \u003cp\u003eA total of 315 quiz scores were recorded in the choice condition and 180 in the no-choice condition, consistent with the study design (seven choice weeks and four no-choice weeks). Data were analyzed both at the individual class level and in aggregate across all six classes (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). Line graphs were created for each class, and a combined graph was constructed to visualize trends across all participants, and analyzed for level, trend, and stability within and between conditions (Fig.\u0026nbsp;1).\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv class=\"colspec\" align=\"left\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003cdiv class=\"colspec\" align=\"char\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003cdiv class=\"colspec\" align=\"char\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003cdiv class=\"colspec\" align=\"char\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003cdiv class=\"colspec\" align=\"char\"\u003e\u0026nbsp;\u003c/div\u003e\n \u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003e\u003cem\u003eMeans and Standard Deviations on Quiz Results Across Classes\u003c/em\u003e\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth rowspan=\"2\" align=\"left\"\u003e\n \u003cp\u003eClass 1\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMean Quiz Score During Choice Weeks\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eStandard Deviation\u003c/p\u003e\n \u003cp\u003eChoice Weeks\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMean Quiz Score during No-Choice Weeks\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eStandard Deviation\u003c/p\u003e\n \u003cp\u003eNo-Choice Weeks\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e18.14\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e0.455\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e17.21\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e0.871\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\u003eClass 2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e17.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e0.854\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e16.84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e0.470\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eClass 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e17.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e0.682\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e18.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e0.557\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAggregate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e17.82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e0.343\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e17.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\"\u003e\n \u003cp\u003e0.376\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003eVisual inspection of individual class graphs (see Fig.\u0026nbsp;1) indicated no meaningful or consistent differentiation between choice and no-choice conditions. Performance across conditions demonstrated substantial overlap, comparable trends, and stable trajectories. Descriptive statistics supported this observation: quiz scores during no-choice weeks ranged from 11.50 to 20.00 (M\u0026thinsp;=\u0026thinsp;17.75, SD\u0026thinsp;=\u0026thinsp;1.80), whereas scores during choice weeks ranged from 11.17 to 20.00 (M\u0026thinsp;=\u0026thinsp;17.82, SD\u0026thinsp;=\u0026thinsp;1.55).\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003cp\u003eSimilarly, the aggregate graph (Fig.\u0026nbsp;2) showed closely aligned trends across conditions, with overlapping data points and minimal variability across weeks.\u003c/p\u003e\n \u003cp\u003eA Shapiro-Wilk test (Shapiro \u0026amp; Wilk, \u003cspan class=\"CitationRef\"\u003e1965\u003c/span\u003e) indicated that quiz scores deviated significantly from normality (W\u0026thinsp;=\u0026thinsp;0.92, p \u0026lt; .001), warranting nonparametric analysis. A Mann-Whitney U test (Mann \u0026amp; Whitney, \u003cspan class=\"CitationRef\"\u003e1947\u003c/span\u003e) revealed no statistically significant difference in quiz performance between choice and no-choice conditions (U\u0026thinsp;=\u0026thinsp;28049, p = .844). Taken together, both visual and inferential analyses indicate that the presence or absence of assignment choice did not systematically affect quiz performance.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n \u003cp\u003eAt the start of the study, participants completed a questionnaire assessing their general attitudes toward choice by stating their level of agreement across two questions: \u003cem\u003e\u0026ldquo;I value having choices in my life,\u0026rdquo; \u0026ldquo;In my coursework, I value having choices in assignments,\u0026rdquo;\u003c/em\u003e They were also asked \u003cem\u003e\u0026ldquo;How often have you been exposed to meaningful options in your college coursework?\u0026rdquo;\u003c/em\u003e (see Fig.\u0026nbsp;4). Responses highlight that while many participants claimed to value having choices, especially in coursework, they have rarely encountered meaningful options in academic settings.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\n \u003cp\u003eThroughout the study, participants completed a brief survey following each weekly quiz. The survey included a self-report estimate of the time spent completing the assigned readings. Most participants reported spending between 1 and 3 hours per week on assigned readings, with no significant difference in reported reading time between choice and no-choice weeks, as indicated by a Mann-Whitney U test (U\u0026thinsp;=\u0026thinsp;897, p = .35). Participants also rated the amount of time and effort required for each week\u0026rsquo;s proof-of-reading assignment by selecting one of three options: minimal, just right, or excessive. Across weeks, participants rated the time and effort as \u0026ldquo;just right\u0026rdquo; in 77% of responses (SD\u0026thinsp;=\u0026thinsp;9.86), suggesting that both study questions and reading summaries were generally perceived as appropriately balanced in terms of workload. However, a Mann-Whitney U test revealed a statistically significant difference in perceived time and effort between choice weeks (Median\u0026thinsp;=\u0026thinsp;2.00) and no-choice weeks (Median\u0026thinsp;=\u0026thinsp;2.25; U\u0026thinsp;=\u0026thinsp;637, p = .0015), indicating that participants reported slightly higher perceived effort during no-choice conditions.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\n \u003cp\u003eAt the conclusion of the study, 41 of the 45 participants completed the post-semester social validity survey. Participants were asked to rate their level of agreements with statements about the impact of assignment choice on their learning, quiz performance, time and effort on their assignments, and their overall academic performance. Participants overwhelming agreed that having a choice positively impacted them across all of these areas. (see Fig.\u0026nbsp;5). Although there was not an actual impact on quiz performance based on choice, these findings suggest that students perceived academic choice as a positive influence on their learning, their performance, and their investment of effort.\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\n \u003cp\u003eParticipants were also asked whether they would prefer to choose their proof-of-reading tasks or to have them assigned by the instructor in future classes. A majority (90%) indicated a preference for making their own choice, while 5% preferred instructor selection and another 5% expressed no preference.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe purpose of this study was to evaluate the impact of choice on quiz performance and student satisfaction for online ABA Master\u0026rsquo;s students. Using an adapted alternating treatments design replicated across six sections of three elective courses, the study examined quiz outcomes under choice and no-choice conditions, while also capturing students\u0026rsquo; preferences, perceived task effectiveness, and social validity data. The choice and no-choice conditions showed substantial overlap and stable, parallel trends, with no consistent or meaningful divergence. These findings indicate that assignment choice did not affect overall performance outcomes.\u003c/p\u003e \u003cp\u003eThe findings from this study both align with and diverge from previous research on the impact of choice on student outcomes. Consistent with the mixed results reported in the literature, this study did not replicate the advantage of choice in improving quiz performance (Flowerday et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Hanewicz et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Patall et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Tereshko et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). Specifically, although Tereshko et al. (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) reported higher quiz scores during choice weeks, the present systematic replication did not observe differentiated performance across conditions; quiz scores during choice weeks closely mirrored those during no-choice weeks.\u003c/p\u003e \u003cp\u003eOne possible explanation for this divergence relates to methodological refinements implemented in the present study. Unlike prior research, task requirements were equated across conditions through expert review to ensure comparable content coverage and response demands. Additionally, students were exposed to both assignment formats prior to the introduction of choice, potentially reducing novelty effects or differential familiarity with task expectations. By isolating assignment choice from differences in task structure or exposure history, the present findings suggest that the opportunity to choose alone may not be sufficient to produce measurable changes in quiz performance within online graduate coursework.\u003c/p\u003e \u003cp\u003eHowever, the current findings align with previous research demonstrating that choice can positively influence student experience (Flowerday et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Hanewicz et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Patall et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Tereshko et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). In the present study, students reported favorable perceptions of assignment choice, suggesting that although quiz performance did not differ across conditions, perceived autonomy and satisfaction were enhanced. These results support the interpretation that the benefits of instructional choice may extend beyond measurable academic performance and into students\u0026rsquo; subjective learning experiences.\u003c/p\u003e \u003cp\u003eTaken together, the differential pattern of findings across performance and student-reported outcomes suggests that the effects of choice may be more nuanced. While assignment choice alone may not reliably produce changes in quiz performance when task requirements are equated, it may meaningfully influence how students experience and evaluate their coursework. Future research should therefore examine whether the primary value of instructional choice lies in enhancing student experience, or whether performance effects emerge only under specific instructional arrangements.\u003c/p\u003e \u003cp\u003eAlthough assignment choice did not produce measurable differences in quiz performance, students consistently reported preferring the having a choice of tasks. Social validity data collected throughout the semester indicated strong support for choice, with 90% of participants endorsing its use. This pattern is consistent with prior literature suggesting that while choice does not reliably improve academic achievement, it often enhances perceived autonomy, satisfaction, and motivation (Patall et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Jopp \u0026amp; Cohen, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The absence of a performance effect in the present study is therefore not anomalous but aligned with research indicating that the value of instructional choice may lie more in student experience than in direct academic gains.\u003c/p\u003e \u003cp\u003eFrom a behavior-analytic perspective, assignment choice may function as an antecedent variable that alters how students interact with academic tasks, potentially influencing task initiation or perceived relevance (Michael, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e1993\u003c/span\u003e). However, the present study did not include direct behavioral measures (e.g., latency to begin assignments, time-on-task, or persistence), and therefore no conclusions can be drawn regarding the mechanisms underlying students\u0026rsquo; preference for choice. It remains possible that the observed positive perceptions reflect changes in subjective experience rather than measurable changes in academic behavior. Future research should incorporate objective behavioral indicators to determine whether assignment choice produces functional changes in engagement or merely enhances students\u0026rsquo; evaluations of instructional practices.\u003c/p\u003e \u003cp\u003eOne important methodological distinction raised by the current findings concerns the potential conflation of choice as a procedural variable with access to preferred tasks as a reinforcement variable. In some prior studies reporting positive effects of choice on performance or engagement, improved outcomes may have resulted not from the opportunity to choose itself, but from participants ultimately completing tasks with higher relative preference. Consistent with behavioral definitions, \u003cem\u003echoice\u003c/em\u003e refers to the availability of multiple response options and the allocation of responding among them, whereas \u003cem\u003epreference\u003c/em\u003e reflects differential responding indicative of the relative reinforcing value of those options (Cooper et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Fisher et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e1992\u003c/span\u003e). The present study sought to distinguish these variables by including no-choice conditions in which participants were assigned either their most frequently selected (presumably higher-preference) task or their least frequently selected task. Results indicated no significant differences in quiz performance across these conditions, suggesting that differential task preference alone did not account for performance variation. These findings highlight the need for further research to disentangle the independent and interactive effects of procedural choice, task preference, and instructional equivalence on academic outcomes.\u003c/p\u003e \u003cp\u003eThe present study also highlights the practicality of implementing assignment choice. Incorporating choice of tasks required minimal additional effort for the instructor, both in designing and grading the assignments, as the options did not necessitate complex adaptations. This simplicity contrasts with earlier studies in which choice was embedded through more elaborate systems, such as point-based grading or menus of dozens of assignments, which while potentially effective, required significantly more planning and instructional labor (e.g., Arendt et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Hanewicz et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). In contrast, the current design offered structured choice without added logistical complexity. This may help explain why quiz performance did not improve: though students appreciated having choice, the relatively straightforward implementation may not have provided sufficient differentiation to impact learning outcomes (Jopp \u0026amp; Cohen, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; MacNaul et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Patall at el., 2008). These findings suggest that while streamlined choice can improve student experience in scalable ways, more robust effects on performance may depend on either the nature of the choices or their integration into broader instructional systems. Nevertheless, this approach remains a low-cost, high-value strategy for asynchronous online learning, one that can enhance student autonomy without sacrificing instructional integrity. Even when improved academic performance is not achieved, the consistent pattern of student preference and reported satisfaction suggests that assignment choice may support a more personalized and student-valued learning experience, even in the absence of measurable academic gains (Deci \u0026amp; Ryan, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Patall et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2008\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2010\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eImportantly, the choices offered in this study were instructionally equivalent in content coverage and grading criteria, differing only in response format. This procedural equivalence suggests that incorporating structured choice can enhance student satisfaction without compromising academic rigor. Consistent with this interpretation, quiz performance did not decline during choice weeks, indicating that the opportunity to select assignment format did not adversely affect learning outcomes. Although the present study did not directly measure motivation or behavioral engagement, future research could evaluate whether structured choice influences persistence, task initiation, or time-on-task in online graduate coursework.\u003c/p\u003e \u003cp\u003eAlthough the present study focused exclusively on student outcomes, future research may examine the instructional feasibility of implementing structured choice in online graduate coursework. While the choice arrangement used in this study was designed to minimize instructor burden through standardized grading criteria and equivalent task structures, other forms of choice may differentially affect grading time, planning demands, or course management. Investigating instructor workload, perceptions of fairness, and implementation fidelity may clarify the practical constraints and scalability of choice-based instructional arrangements.\u003c/p\u003e \u003cp\u003eThere were potential limitations in the current study related to design, procedure, and internal validity. In one course, links to content on an external website became inactive mid-semester, requiring substitution of materials. Additionally, two students in week one completed their quiz and weekly survey before submitting their assigned reading task. This procedural inconsistency was addressed in subsequent modules by modifying the learning management system settings to enforce sequential task submission. These changes ensured consistent sequencing across all remaining weeks.\u003c/p\u003e \u003cp\u003ePotential threats to internal validity should also be considered. Although efforts were made to reduce selection bias by including electives from three distinct content areas, participants were not randomly assigned to course sections. As a result, self-selection into courses may have introduced uncontrolled differences in baseline academic ability, prior familiarity with course content, workload demands, or motivation across cohorts. Additionally, subtle differences in instructor delivery, peer interaction patterns, or course topic complexity may have influenced performance independent of assignment condition.\u003c/p\u003e \u003cp\u003eDespite these limitations, several design features strengthen internal validity. Procedural sequencing was consistent across sections, grading criteria were standardized, and the experimental conditions were replicated across multiple classes. These controls reduce the likelihood that observed outcomes were attributable to extraneous variables rather than the presence or absence of assignment choice. While caution is warranted when generalizing beyond this instructional context, the findings reflect performance patterns observed under authentic graduate-level conditions.\u003c/p\u003e \u003cp\u003eWhile the current study focused on choice between two types of reading-based assignments, future research could examine other forms of academic choice within online graduate programs. For example, offering students a choice between different content delivery methods (e.g., video lectures vs. readings), assessment formats (e.g., written response vs. oral presentation), or working alone vs. in a group options may reveal additional benefits or limitations of instructional choice. Investigating whether students demonstrate similar preferences and learning outcomes across various dimensions of coursework could help educators identify which types of choices are most meaningful and instructionally effective. Additionally, it may be useful to explore the impact of more complex or personalized choice options, such as offering students a menu of assignment options tailored to specific learning objectives or skill levels.\u003c/p\u003e \u003cp\u003eUltimately, this study contributes to the empirical literature on instructional choice in graduate education by isolating assignment choice from task structure and preference effects within online graduate coursework. When task requirements were equated and exposure history controlled, the opportunity to choose did not independently influence quiz performance. However, students consistently endorsed the availability of structured choice. These findings suggest that procedural choice may influence student experience without altering performance under equivalent instructional conditions. Continued research should identify the conditions under which instructional choice produces functional changes in academic behavior.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAll authors contributed to the writing and review of the manuscript.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eAll data supporting the findings of this study are available within the paper and its Supplementary Information.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eArendt, A., Trego, A., \u0026amp; Allred, J. (2016). Students reach beyond expectations with cafeteria style grading. \u003cem\u003eJournal of Applied Research in Higher Education\u003c/em\u003e, \u003cem\u003e8\u003c/em\u003e(1), 2\u0026ndash;17. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1108/JARHE-03-2014-0048\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003eBaer, D. M., Wolf, M. M., \u0026amp; Risley, T. R. (1968). Some current dimensions of applied behavior analysis. \u003cem\u003eJournal of Applied Behavior Analysis\u003c/em\u003e, \u003cem\u003e1\u003c/em\u003e(1), 91\u0026ndash;97.\u0026nbsp;\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1901/jaba.1968.1-91\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003eBensoussan, M., \u0026amp; Kreindler, I. (1990). Improving advanced reading comprehension in a foreign language: Summaries vs. short-answer questions. \u003cem\u003eJournal of Research in Reading\u003c/em\u003e, \u003cem\u003e13\u003c/em\u003e(1), 55\u0026ndash;68. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/j.1467-9817.1990.tb00322.x\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003eBird, Z., \u0026amp; Chase, P. N. (2021). Student pacing in a master\u0026rsquo;s level course: Procrastination, preference, and performance. \u003cem\u003eJournal of Applied Behavior Analysis\u003c/em\u003e, \u003cem\u003e54\u003c/em\u003e(3), 1220\u0026ndash;1234. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/jaba.806\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003eCariveau, T., \u0026amp; Fetzner, D. (2022). Experimental control in the adapted alternating treatments design: A review of procedures and outcomes. \u003cem\u003eBehavioral Interventions\u003c/em\u003e, \u003cem\u003e37\u003c/em\u003e(3), 805\u0026ndash;818. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/bin.1865\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003eCarter, E., Molina, E., Pushparatnam, A., Rimm-Kaufman, S., Tsapali, M., \u0026amp; Wong, K. K. Y. (2024). Evidence-based teaching: effective teaching practices in primary school classrooms. \u003cem\u003eLondon Review of Education\u003c/em\u003e, \u003cem\u003e22\u003c/em\u003e(1), 8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.14324/LRE.22.1.08\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003eCooper, J. O., Heron, T. E., \u0026amp; Heward, W. L. (2020). Applied behavior analysis (3rd ed.). Pearson.\u003c/li\u003e\n\u003cli\u003eDabrowski, J., \u0026amp; Marshall, T. R. (2018). \u003cem\u003eMotivation and engagement in student assignments: The role of choice and relevancy.\u003c/em\u003e The Education Trust. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://edtrust.org/resource/motivation-and-engagement-in-student-assignments/\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003eDeci, E. L., \u0026amp; Ryan, R. M. (2000). The what and why of goal pursuits: Human needs and the self-determination of behavior. \u003cem\u003ePsychological Inquiry\u003c/em\u003e, \u003cem\u003e11\u003c/em\u003e(4), 227\u0026ndash;268. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1207/S15327965PLI1104_01\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003eFisher, W., Piazza, C. C., Bowman, L. G., Hagopian, L. P., Owens, J. C., \u0026amp; Slevin, I. (1992). A comparison of two approaches for identifying reinforcers for persons with severe and profound disabilities. \u003cem\u003eJournal of Applied Behavior Analysis\u003c/em\u003e, \u003cem\u003e25\u003c/em\u003e(2), 491\u0026ndash;498. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1901/jaba.1992.25-491\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003eFlaherty, C. (2024, July 31). When given the choice, college students select more rigorous courses. Inside Higher Ed. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.insidehighered.com/news/student-success/academic-life/2024/07/31/when-given-choice-college-students-select-rigorous\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003eFlowerday, T., Schraw, G., \u0026amp; Stevens, J. (2004). The role of choice and interest in reader engagement. \u003cem\u003eJournal of Experimental Education\u003c/em\u003e, \u003cem\u003e72\u003c/em\u003e(2), 93\u0026ndash;114. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3200/JEXE.72.2.93-114\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003eGay, G. (2002). Preparing for culturally responsive teaching. \u003cem\u003eJournal of Teacher Education\u003c/em\u003e, \u003cem\u003e53\u003c/em\u003e(2), 106\u0026ndash;116. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1177/0022487102053002003\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003eGhaemmaghami, M., Ruppel, K., \u0026amp; Cammilleri, A. P. (2024). Toward compassion in the assessment and treatment of severe problem behavior. \u003cem\u003eBehavior Analysis in Practice\u003c/em\u003e. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s40617-024-01012-1\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003eHamilton, I. (2024, May 31). \u003cem\u003e2024 online learning statistics\u003c/em\u003e. Forbes. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.forbes.com/advisor/education/online-colleges/online-learning-stats/\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003eHanewicz, C., Platt, A., \u0026amp; Arendt, A. (2017). Creating a learner-centered teaching environment using student choice in assignments. \u003cem\u003eDistance Education\u003c/em\u003e, \u003cem\u003e38\u003c/em\u003e(3), 273\u0026ndash;287. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/01587919.2017.1369349\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003eHarrington, C. (2024). How much assignment choice do students have? A descriptive study of syllabi. \u003cem\u003eCurrents in Teaching and Learning\u003c/em\u003e, \u003cem\u003e15\u003c/em\u003e(2), 6\u0026ndash;15.\u003c/li\u003e\n\u003cli\u003eHattie, J. (2009). \u003cem\u003eVisible Learning: A Synthesis of Over 800 Meta-Analyses Relating to\u003c/em\u003e.\u003c/li\u003e\n\u003cli\u003eAchievement Routledge.\u003c/li\u003e\n\u003cli\u003eHaydon, T., Macsuga-Gage, A. S., Simonsen, B., \u0026amp; Hawkins, R. (2012). Opportunities to respond: A key component of effective instruction. \u003cem\u003eBeyond Behavior\u003c/em\u003e, \u003cem\u003e22\u003c/em\u003e(1), 23\u0026ndash;31.\u0026nbsp;\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1177/107429561202200105\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003eJamero, J., Adelman, H. S., \u0026amp; Taylor, L. (2023). Empathy, compassion, and addressing student misbehavior. National Center for Mental Health in Schools at UCLA. Retrieved from \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://smph.psych.ucla.edu\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003eJopp, R., \u0026amp; Cohen, J. (2020). Choose your own assessment: Assessment choice for students in online higher education. Teaching in Higher Education. Advance online publication. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/13562517.2020.1742680\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003eLockhart, K. A., Sexton, J., \u0026amp; Lea, C. (1975). The Findley procedure: A method for examining choice-making behavior in academic settings. \u003cem\u003eBehavior Research and Technical in Higher Education\u003c/em\u003e, \u003cem\u003e46\u003c/em\u003e(3), 456\u0026ndash;462.\u003c/li\u003e\n\u003cli\u003eLockman, A. S., \u0026amp; Schirmer, B. R. (2020). Online instruction in higher education: Promising, research-based, and evidence-based practices. \u003cem\u003eJournal of Education and e-Learning Research\u003c/em\u003e, \u003cem\u003e7\u003c/em\u003e(2), 130\u0026ndash;152. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://dx.doi.org/10.20448/journal.509.2020.72.130.152\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003eMacNaul, H., Garcia, R., Cividini-Motta, C., \u0026amp; Thacker, I. (2021). Effect of assignment choice on student academic performance in an online class. \u003cem\u003eBehavior Analysis in Practice\u003c/em\u003e, \u003cem\u003e14\u003c/em\u003e(4), 1074\u0026ndash;1078. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s40617-021-00566-8\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003eMann, H. B., \u0026amp; Whitney, D. R. (1947). On a test of whether one of two random variables is stochastically larger than the other. \u003cem\u003eThe Annals of Mathematical Statistics\u003c/em\u003e, \u003cem\u003e18\u003c/em\u003e(1), 50\u0026ndash;60. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1214/aoms/1177730491\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003eMay, M. E. (2018). Effects of differential consequences on choice making in students at risk for academic failure. \u003cem\u003eBehavior Analysis in Pract\u003c/em\u003eice. 2018;12(1):154\u0026ndash;161. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s40617-018-0267-3\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003eMeans, B., Toyama, Y., Murphy, R., Bakia, M., \u0026amp; Jones, K. (2013). The effectiveness of online and blended learning: A meta-analysis of the empirical literature. U.S. Department of Education, Office of Planning, Evaluation, and Policy Development. Retrieved from \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www2.ed.gov/rschstat/eval/tech/evidence-based-practices/finalreport.pdf\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003eMichael, J. (1993). Establishing operations. \u003cem\u003eThe Behavior Analyst\u003c/em\u003e, \u003cem\u003e16\u003c/em\u003e(2), 191\u0026ndash;206. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/BF03392623\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003eNational Center for Education Statistics, Postsecondary Education (2024, May). National Center for Education Statistics. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://nces.ed.gov/programs/coe/indicator/ctb/graduate-degree-fields\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003ePatall, E. A., Cooper, H., \u0026amp; Robinson, J. C. (2008). The effects of choice on intrinsic motivation and related outcomes: A meta-analysis of research findings. \u003cem\u003ePsychological Bulletin\u003c/em\u003e, \u003cem\u003e134\u003c/em\u003e(2), 270\u0026ndash;300. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1037/0033-2909.134.2.270\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003ePatall, E. A., Cooper, H., \u0026amp; Wynn, S. R. (2010). The effectiveness and relative importance of choice in the classroom. \u003cem\u003eJournal of Educational Psychology\u003c/em\u003e, \u003cem\u003e102\u003c/em\u003e(4), 896\u0026ndash;915. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1037/a0019545\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003ePenney, A. M., Bateman, K. J., Veverka, Y., Luna, A., \u0026amp; Schwartz, I. S. (2023). Compassion: The eighth dimension of applied behavior analysis. \u003cem\u003eBehavior Analysis in Practice\u003c/em\u003e. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s40617-023-00888-9\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003eRajaraman, A., Austin, J. L., \u0026amp; Gover, H. C. (2023). A practitioner's guide to emphasizing choice-making opportunities in behavioral services provided to individuals with intellectual and developmental disabilities. \u003cem\u003eInternational Journal of Developmental Disabilities\u003c/em\u003e, \u003cem\u003e69\u003c/em\u003e(1), 101\u0026ndash;110. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1080/20473869.2022.2117911\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003eShapiro, S. S., \u0026amp; Wilk, M. B. (1965). An analysis of variance test for normality (complete.\u003c/li\u003e\n\u003cli\u003esamples) \u003cem\u003eBiometrika\u003c/em\u003e, \u003cem\u003e52\u003c/em\u003e(3/4), 591\u0026ndash;611. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/biomet/52.3-4.591\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003eSinclair, S., Kondejewski, J., Jaggi, P., Dennett, L., Roze des Ordons, A. L., \u0026amp; Hack, T. F. (2021). What is the state of compassion education? A systematic review of compassion training in health care. \u003cem\u003eAcademic medicine: Journal of the Association of American Medical Colleges\u003c/em\u003e, \u003cem\u003e96\u003c/em\u003e(7), 1057\u0026ndash;1070. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1097/ACM.0000000000004114\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003eSindelar, P. T., Rosenberg, M. S., \u0026amp; Wilson, R. J. (1985). An adapted alternating treatments. design for instructional research \u003cem\u003eEducation and Treatment of Children\u003c/em\u003e, 8(1), 67\u0026ndash;76. http://jstor.org/stable/42898888.\u003c/li\u003e\n\u003cli\u003eTereshko, L. M., Zane, T., \u0026amp; Weiss, M. J. (2024). The effect of choice on student performance in online graduate classes. \u003cem\u003eJournal of Behavioral Education\u003c/em\u003e. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s10864-024-09543-x\u003c/span\u003e\u003c/span\u003e. Advance online publication.\u003c/li\u003e\n\u003cli\u003eThibodeaux, T., Harapnuik, D., \u0026amp; Cummings, C. (2019). Student perceptions of the influence of choice, ownership, and voice in learning and the learning environment. International Journal of Teaching and Learning in Higher Education, 31(1), 50\u0026ndash;62. Retrieved from \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://files.eric.ed.gov/fulltext/EJ1206966.pdf\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003eTincani, M., Brodhead, M. T., \u0026amp; Dowdy, A. (2024). Aba promotes autonomy and choice of people with intellectual and developmental disabilities. \u003cem\u003eJournal of Developmental and Physical Disabilities\u003c/em\u003e. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s10882-024-09949-5\u003c/span\u003e\u003c/span\u003e. Advance online publication.\u003c/li\u003e\n\u003cli\u003eVollmer, T. R., Sloman, K. N., \u0026amp; St. Peter Pipkin, C. (2008). Practical implications of data reliability and treatment integrity monitoring. \u003cem\u003eBehavior Analysis in Practice\u003c/em\u003e, \u003cem\u003e1\u003c/em\u003e, 4\u0026ndash;11. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/BF03391722\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\n\u003cli\u003eWolf, M. M. (1978). Social validity: The case for subjective measurement or how applied behavior analysis is finding its heart. \u003cem\u003eJournal of Applied Behavior Analysis\u003c/em\u003e, \u003cem\u003e11\u003c/em\u003e(2), 203\u0026ndash;214. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1901/jaba.1978.11-203\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"journal-of-behavioral-education","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jobe","sideBox":"Learn more about [Journal of Behavioral Education](http://link.springer.com/journal/10864)","snPcode":"10864","submissionUrl":"https://submission.springernature.com/new-submission/10864/3","title":"Journal of Behavioral Education","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"student choice, higher education, online instruction, behavior science","lastPublishedDoi":"10.21203/rs.3.rs-9261351/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9261351/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Effective instruction in higher education relies on structured engagement, frequent opportunities to respond, and meaningful feedback. Prior research suggests that offering students choices of assignments can improve engagement and performance; however, experimental evaluations of this practice in online settings are limited. In this study, an adapted alternating treatments design was used to evaluate the effects of assignment choice on quiz performance among 45 participants across six sections of asynchronous, online Master’s-level courses. Participants completed weekly proof-of-reading assignments, choosing between study questions and reading summaries during “choice weeks”, and being randomly assigned to one of these tasks during “no-choice weeks”. Weekly quiz scores served as the dependent variable. Visual and statistical analyses indicated that providing assignment choice did not improve quiz performance compared to no-choice conditions. However, participants consistently reported a preference for having a choice and reported having choice as helpful for increasing their perceived engagement with course material and preparation for assessments. These findings highlight the potential of assignment choice to enhance student satisfaction in online graduate education, which is important as on-line higher-education enrollment continues to grow.\nKeywords: student choice, higher education, online instruction, behavior science","manuscriptTitle":"The Effects of Assignment Choice on Quiz Performance and Student Experience in Online Graduate Education","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-26 15:48:12","doi":"10.21203/rs.3.rs-9261351/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"137570138044885514989390822146426208353","date":"2026-04-20T21:50:03+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-20T19:59:08+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"289411452921863656790848575476952812127","date":"2026-04-17T20:49:35+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-17T01:16:08+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-03T02:49:29+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-03T02:48:30+00:00","index":"","fulltext":""},{"type":"submitted","content":"Journal of Behavioral Education","date":"2026-03-30T00:25:35+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"journal-of-behavioral-education","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jobe","sideBox":"Learn more about [Journal of Behavioral Education](http://link.springer.com/journal/10864)","snPcode":"10864","submissionUrl":"https://submission.springernature.com/new-submission/10864/3","title":"Journal of Behavioral Education","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"591d3b0d-dc2d-45d4-8d75-216dfcd08099","owner":[],"postedDate":"April 26th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-26T15:48:12+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-26 15:48:12","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9261351","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9261351","identity":"rs-9261351","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}