A Bibliometric Study of Blended Learning in Higher Education (2001- 2024)

A Bibliometric Study of Blended Learning in Higher Education (2001- 2024) | 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 Article A Bibliometric Study of Blended Learning in Higher Education (2001- 2024) Xin Li, Malaysia Zexun Huang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5302006/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This study presents a comprehensive bibliometric analysis of blended learning in higher education (BLHE) research from 2001 to 2024. Using CiteSpace, we analyzed 2,125 publications from the Web of Science Core Collection to map the intellectual structure and evolution of the field. Our findings reveal a significant increase in BLHE research from 2013 onwards, with peak productivity in 2018 and 2019. Conference proceedings emerged as dominant publication venues, reflecting the field's dynamic nature. Document co-citation analysis identified influential works, with Garrison and Kanuka's (2004) Community of Inquiry framework emerging as particularly impactful. Cluster analysis revealed 11 distinct research areas, including blended learning foundations, self-regulated learning, game-based learning, and work-integrated learning. These clusters highlight the multifaceted nature of BLHE research and its integration with various pedagogical approaches and technologies. Our analysis also uncovered several research gaps, including a need for more diverse cultural perspectives, longitudinal studies examining long-term impacts, and research on innovative assessment strategies in blended environments. While the field has made significant progress in understanding BLHE implementation, challenges remain in addressing cultural diversity and long-term effectiveness. This study provides researchers, educators, and policymakers with insights into the field's intellectual structure, emerging trends, and future directions. As blended learning continues to shape higher education, addressing identified research gaps will be crucial for developing more effective, inclusive, and transformative learning experiences. Social science/Education Social science/Science technology and society Figures Figure 1 Figure 2 Figure 3 Figure 4 1. Introduction The educational landscape is evolving owing to technological advancements, historical occurrences, labour market transformations, and economic fluctuations. These pressures are transforming educational objectives and methodologies. Contemporary studies underscore the need for varied pedagogical methods (Markauskaite et al., 2024 ). In this context, blended learning (BL) has arisen as an innovative instructional method, receiving considerable attention in scholarly literature (Kang & Kim, 2021 ). The past global pandemic has accelerated the use of blended learning approaches, positioning them at the front of educational innovation. By using technology advancements, BL has preserved its relevance and reinforced its significance in contemporary educational systems. The concept of BL, also known as mixed or hybrid learning (Atwa et al., 2019 ) has been subject to numerous interpretations in international literature. Despite the variety of definitions that exist, a common thread emerges: BL aims to harmonize the strengths of distance and face-to-face teaching methodologies (Garrison & Kanuka, 2004 ). At its core, BL is characterized by the seamless integration of online and traditional in-person educational processes. This integration is not merely a theoretical concept but a practical approach that has been tested and refined over time. The dynamic nature of BL has become particularly evident with the changing structure of both learners and learning environments. The COVID-19 pandemic, which forced a rapid and widespread adoption of online learning, has served as a catalyst for this change. The experiences gained during this period have boldly underlined the utility and resilience of the blended learning model. As a result, such cases have indicated a significant shift towards preferring this model in the future, a tendency that is both observable and likely to continue growing (Bozkurt & Sharma, 2022 ; Pelletier et al., 2021 ; Cruz-Cárdenas et al., 2023 ; Hebebci & Ozer, 2023 ). In the realm of higher education, blended learning has become increasingly pivotal (Harasim, 2000 ). Universities and colleges worldwide are recognizing its potential to enhance the learning experience and outcomes for students (Adebayo et al., 2019 ). By combining the flexibility and resource-rich environment of online platforms with the interpersonal dynamics of face-to-face instruction, Blended Learning in Higher Education (BLHE) has offered a unique opportunity to cater to diverse learning styles and needs(Bhowmik et al., 2019 ). It has allowed for the optimization of both independent study and collaborative learning, preparing students for the digital-forward yet human-centric workplaces of the future (Stepanova, 2020 ). Moreover, BLHE has not merely been a matter of integrating technology; it has been a fundamental change in the pedagogical approach that promotes digital literacy, critical thinking, and active learning, all of which are essential in the knowledge economy of today (Laufer et al., 2021 ). As higher education institutions grow, BL has emerged as a fundamental innovation, aiming to reconcile conventional academic excellence with the requirements of our increasingly linked and digital landscape(Harasim, 2000 ). Furthermore, its significance in higher education has grown exponentially, arousing the interest of scholars from various disciplines including education, psychology, technology, and sociology (Just, 2021 ; Ma & Lee, 2021 ). The complex characteristics of BL have resulted in a substantial and varied body of research, indicating its capacity to transform educational practices in higher education globally. BL has significantly evolved since its inception, influenced by technological breakthroughs and shifting pedagogical methodologies. Over the past two decades, researchers from different fields have contributed to our understanding of blended learning, exploring its impact on student engagement, learning outcomes, and institutional effectiveness (Bhowmik et al., 2019 ; Cacciamani et al., 2021 ; Zhu et al., 2021 ). Blended learning in higher education (BLHE) has been the subject of numerous review papers in recent years, each addressing different subtopics within this broad field of inquiry. For instance, Balakrishnan et al. (2020) conducted a systematic review and meta-analysis focusing on the effectiveness of blended learning in pharmacy education, demonstrating significant enhancements in knowledge and abilities among pharmacy students compared to conventional teaching approaches. Short et al. ( 2021 ) performed a systematic mapping evaluation of research trends regarding teacher preparation for K-12 mixed contexts, highlighting the insufficient emphasis on K-12 blended learning and underscoring the need for more extensive studies in this domain. While these reviews provided valuable insights into specific aspects of blended learning, they do not offer a comprehensive bibliometric analysis of the field. Some researchers have attempted to address this gap. Specifically, Ibarra-Vargas et al. ( 2023 ) undertook a bibliometric and cluster analysis of blended learning literature, establishing six topic groupings and emphasizing the prevalence of qualitative studies of hybrid course experiences. Similarly, Limaymanta et al. ( 2021 ) carried out a bibliometric analysis of the flipped classroom in higher education, proposing a framework for its implementation in various learning modalities. More recently, Cruz-Cárdenas et al. ( 2023 ) and Hebebci and Ozer (2022) have conducted bibliometric analyses specifically focusing on BLHE. Cruz-Cárdenas's study identified four main areas of interest, including the impact of COVID-19, the effectiveness of blended learning, its organization and design, and the technological tools used. Hebebci and Ozer's analysis mapped the development of blended learning research from 2005 to 2021, identifying key contributing countries and authors. Building upon this existing body of research, the present study aims to contribute an updated perspective to the field's bibliometric analysis of BLHE. While recent reviews have made significant strides, this study differentiates itself in two key aspects. Firstly, while both Cruz-Cárdenas et al. ( 2023 ) and Hebebci and Ozer (2022) utilized VOSviewer for their analyses, this study employs CiteSpace, a powerful tool for visualizing and analyzing trends in scientific literature. Education research has seen a significant adoption of CiteSpace, as evidenced by studies like Chu et al. ( 2023 ) on STEM interventions and Geng ( 2024 ) on Chinese cultural integration in English education. This methodological variation offers an alternative approach to visualizing and analyzing the research landscape in BLHE. Secondly, this analysis extends the temporal scope to incorporate research conducted after the onset of the COVID-19 pandemic. This addresses a future research direction suggested by Hebebci and Ozer ( 2023 ), who proposed examining post-COVID-19 studies. By including this more recent data, the present study offers a more current perspective on BLHE, complementing the COVID-19 impact area identified by Cruz-Cárdenas et al. ( 2023 ). Through these approaches, this study aims to provide a comprehensive and up-to-date bibliometric analysis of BLHE, contributing to the ongoing development of this interdisciplinary field. Specifically, this CiteSpace-assisted review seeks to uncover prolific journals and conference proceedings, prominent researchers, significant institutions, and dynamic research issues, while creating a visual representation of related terms and dominant topics using keyword co-occurrence analysis. To achieve these objectives, the following research questions are proposed: Q1: What are the key trends and patterns in the development of blended learning research in higher education over the past two decades? Q2: In what ways can the temporal and geospatial analysis of research output contribute to our understanding of the global diffusion and adoption of blended learning practices in higher education? Q3: To what extent can the cluster analysis of keywords and research topics identify critical research features and potential gaps in the current body of knowledge on BLHE? Based on these research questions, it is hypothesized that the bibliometric analysis will reveal significant evolution in BLHE research, shifting from technological implementation to more nuanced explorations of pedagogical strategies and student outcomes. The study anticipates uncovering distinct patterns of global diffusion and identifying critical research features and potential gaps, particularly in areas related to faculty development and institutional policy-making. 2. Methodology 2.1 Data collection This study employed a comprehensive bibliometric analysis approach to examine the landscape of blended learning research in higher education. To ensure a robust and representative dataset, an advanced search was conducted in the Web of Science (WoS) Core Collection of Thomson Reuters. This database was selected due to its extensive coverage, rigorous indexing process, and compatibility with the chosen bibliometric analysis tools. The search encompassed multiple citation indices, including the Science Citation Index Expanded (SCIE), Social Sciences Citation Index (SSCI), Arts and Humanities Citation Index (AHCI), Conference Proceedings Citation Index (CPCI), and Emerging Sources Citation Index (ESCI). This multi-index approach allowed for a broad and interdisciplinary collection of literature pertinent to the research focus. To capture the full spectrum of research on BLHE from 2001 to 2024, a comprehensive literature search was conducted. This time frame was chosen to encompass the early stages of blended learning adoption in higher education through to its current state, allowing for a thorough analysis of trends and developments over more than two decades. A set of key search terms was carefully selected to ensure comprehensive coverage: ‘blended learning’, ‘blended education’, ‘blended courses’, ‘integrated learning’, ‘hybrid learning’, and ‘higher education’. This selection was based on common terminology used in the field (Hrastinski, 2019 ). On July 22, 2024, an advanced search was executed in the Web of Science (WoS) database using the following search string: TS= (blended learning* OR blended education* OR blended course* OR integrated learning* OR hybrid learning*) AND (higher education). This strategy ensured retrieval of articles containing the specified terms in their title, abstract, or keywords. The search was limited to research articles and review articles to focus on original research and comprehensive syntheses of the field, a common practice in bibliometric studies(Zupic & Čater, 2015 ). Importantly, no language restrictions were applied, recognizing that valuable contributions might exist in non-English publications. The initial search yielded 2144 results from WoS. A meticulous screening process was then undertaken to refine the dataset. Book reviews, book chapters, editorial materials, letters, and retracted publications were excluded from the analysis, following standard bibliometric practices (Aria & Cuccurullo, 2017 ). This screening process resulted in a final dataset of 2125 research articles and review articles. These documents spanned various WoS categories, predominantly including 'Education', 'Computer Science', 'Social Sciences', and 'Linguistics', reflecting the interdisciplinary nature of BLHE research. This refined dataset formed the basis for subsequent bibliometric analysis, providing a comprehensive overview of the field's development, key trends, and influential works in blended learning within higher education of more than two decades. The use of such a dataset for bibliometric analysis has been well-established in educational research (Chen, et al. 2020 ). 2.2 Descriptive Analysis Prior to the in-depth bibliometric analysis, a comprehensive descriptive analysis of the dataset was conducted. This preliminary analysis aimed to provide an overview of publication trends and identify key contributors to the field of BLHE. The analysis began with an examination of the yearly publication trends from 2001 to 2024. This temporal analysis allowed for tracing the evolution of research interest in blended learning over time, identifying periods of rapid growth or potential plateaus in scholarly output. To visualize this trend, SPSS software was used to generate a bar graph depicting the number of publications per year. The WoS website provided data on the number of publications for each journal, author, and institution. For journals and conference proceedings, we selected the top 5 for in-depth analysis, while for authors and institutions, we examined the top 10. These rankings offer insights into the key contributors and platforms driving research in this field. The analysis of the most productive journals and conference proceedings has revealed which publications have been most influential in disseminating research on BLHE. Similarly, identifying the most prolific authors has provided an understanding of the key thought leaders and researchers shaping the field. The examination of the most productive institutions highlightd the academic centers that have been at the forefront of blended learning research and implementation in higher education settings. 2.3 CiteSpace Analysis While the descriptive analysis based on Web of Science (WoS) data has provided a valuable initial overview of the research field of BLHE, it has limitations in fully capturing the intellectual structure and emerging trends of this rapidly evolving domain (Zupic & Čater, 2015 ). The basic statistics on publication counts, top journals conference proceedings, authors, and institutions have offered a general picture but couldn’t provide an exhaustive account of the field's development of the past more than two decades or identify the most recent directions for future research (Chen, 2006 ). Traditional literature reviews in the field of blended learning have often relied on researchers' prior knowledge and subjective judgement (Halverson et al., 2014 ). This approach, while valuable, risks overlooking crucial information or emerging trends, particularly given the interdisciplinary nature and rapid technological advancements characteristic of blended learning research. The complex interplay between education, technology, and pedagogy in blended learning has made it challenging for individual researchers to comprehensively track all relevant developments. To move beyond the limitations of basic descriptive statistics and gain deeper insights into the intellectual structure and evolution of BLHE research, CiteSpace, an information visualization analysis software designed to present the structure and distribution of scientific knowledge through visualization (Chen, 2006 ; Kim et al., 2016 ; Hou et al., 2020 ) has been employed for the bibliometric analysis. This approach allows us to examine the structures and characteristics of the existing knowledge regarding BLHE in a more systematic and data-driven manner (Chen, 2018 ). A key feature of CiteSpace is its ability to select a particular field based on a time sequence and link both together, enabling the deduction of developmental trends and changes within the area of BLHE (Chen et al., 2009 ). In our study, the bibliographic data files collected from WoS were in the field-tagged Institute for Scientific Information Export Format. We selected the ‘full record and cited references’ as the content, allowing CiteSpace to easily identify the files. Once the files were loaded into CiteSpace, the following procedural operations were performed: time slicing, thresholding, modeling, pruning, merging, and mapping (Chen, 2004 ). These operations allowed for a comprehensive analysis of the blended learning literature. We conducted two separate visualizing analyses of the data: a. Document Co-citation Analysis: This analysis helped identify important documents in blended learning research. A co-cited reference was called a node, and when several nodes were strongly related to one another, they formed a cluster. This analysis revealed the intellectual structure and key influencers in the field of BLHE; b. Keyword Co-occurrence Analysis: The purpose of this analysis was to identify the most-discussed areas in research on BLHE. This helped in understanding the main themes and trends in the field over time. 3. Results Publication years, journals and conference proceedings, productive authors, and institutions on BLHE. Figure 1 indicated the Annual publications on BLHE research. In the web of Science core collection, this research field experienced a slow start from 2001 to 2008, with fewer than 20 publications per year. A noticeable increase began in 2009, with 22 publications, marking the beginning of more significant interest in the topic. Rapid growth was observed from 2013 onwards, with publications more than doubling from 67 in 2012 to 138 in 2015. The field reached its peak in terms of publications in 2018 and 2019, with 196 and 194 papers respectively. Interestingly, there was a slight dip in 2020 to 182 papers, possibly due to the disruptions caused by the COVID-19 pandemic. However, the field quickly rebounded in 2021 with 194 publications, suggesting a renewed interest in blended learning strategies as institutions adapted to new educational paradigms. The most recent years has shown a gradual decline in the number of publications, with 162 in 2022, 140 in 2023, and 101 in the partial year of 2024. This trend could indicate a maturation of the field or a shift in research focus within higher education. Figure 1 . Annual publications on BLHE. The diagram reveals the publication number for each year and the general trend. Examining 2,125 articles and reviews revealed a diverse landscape of publication venues, encompassing both traditional journals and conference proceedings. Notably, conference proceedings dominated the upper echelons of this bibliometric analysis. At the forefront, Edulearn Proceedings stood out with an impressive 177 papers, closely followed by Inted Proceedings and Iceri Proceedings , contributing 138 and 87 publications respectively. Occupying the fourth position, Lecture Notes in Computer Science , a book series frequently utilized for conference proceedings, accounted for 63 publications. Education and Information Technolog ies emerged as the first traditional journal on the list, securing the fifth rank with 60 papers. Subsequently, another conference proceeding, Proceedings of the European Conference on E-Learning , claimed the sixth spot with 49 publications. Further down the list, two more journals make their appearance: Higher Education Research Development and Procedia Social and Behavioral Sciences , contributing 40 and 36 papers respectively. Rounding out the top ten were Elearning and Software for Education , a hybrid publication featuring both journal articles and conference proceedings, and the journal Sustainability , both tied at 34 publications each. Table 1 Top 10 most fruitful journals and conference proceedings for BLHE research. Ranking Journals The number of published papers 1 Edulearn Proceedings 177 2 Inted Proceedings 138 3 Iceri Proceedings 87 4 Lecture Notes in Computer Science 63 5 Education And Information Technologies 60 6 Proceedings On the European Conference of E Learning 49 7 Higher Education Research Development 40 8 Procedia Social and Behavioral Sciences 36 9 Elearning And Software for Education 34 10 Sustainability 34 Table 2 presented the top 10 most productive authors for BLHE research. The table ranked authors based on their number of published papers in this field. Jesús Sergio Artal-Sevil led the list with 19 publications, followed by Chang Zhu with 14 publications. Denise Jackson and Enrique Romero shared the third position, each with 10 publications. The remaining authors in the top 10 had between 7 and 9 publications each, with Yang Harrison Hao rounding out the list at 10th place with 7 published papers. Table 2 Top 10 most productive authors for BLHE research Ranking Authors The number of published papers 1 Artal-Sevil, Jesús Sergio 19 2 Zhu, Chang 14 3 Jackson, Denise 10 4 Romero, Enrique 10 5 Han, Feifei 9 6 Graham, Charles R. 9 7 Simonova, Ivana 9 8 Manuel Artacho, J. 9 9 Castro, Manuel 8 10 Yang, Harrison Hao 7 Turning to institutional productivity (Table 3 ), we noticed a landscape dominated by university systems rather than individual institutions. Griffith University topped the list with 29 published papers. Deakin University, Instituto Politécnico do Porto, and University of Zaragoza were tied for second place, each with 23 publications. The list included universities from various countries, including Australia, Portugal, Spain, Belgium, and China. Interestingly, the Ministry of Education and Science of Ukraine appeared in the 9th position with 16 publications, indicating significant governmental involvement in this research area. The number of published papers for these institutions ranged from 29 to 16, with the University of Granada completing the top 10 with 16 publications. Table 3 Top 10 most productive institutions for BLHE research Ranking Institutions The number of published papers 1 Griffith University 29 2 Deakin University 23 3 Instituto Politécnico do Porto 23 4 University of Zaragoza 23 5 Vrije Universiteit Brusse 18 6 Central China Normal University 17 7 Universidad Nacional de Educación a Distancia (UNED) 17 8 Hong Kong Polytechnic University 16 9 Ministry of Education and Science of Ukraine 16 10 University of Granada 16 Document co-citation analysis. The document co-citation analysis of 2125 publications on BLHE, spanning from 2001 to 2024, revealed a comprehensive picture of the field's intellectual structure. Using CiteSpace, we generated a visualization of the co-citation network, which comprised 674 nodes representing cited publications and 2801 links indicating co-citation relationships, as shown in Fig. 2 . The network was constructed by selecting the top 50 most-cited papers per 3-year time slice, allowing for a more granular view of the field's evolution over time. The resulting visualization presented a dense and intricate network structure with node sizes reflecting citation frequency and a color spectrum from cool to warm tones representing the temporal progression of publications. The modularity Q score of 0.8165 indicated a well-structured network with clearly defined communities, while the mean silhouette value of 0.3607 suggested reasonable clarity in the cluster divisions. Figure 2 Crucial documents in BLHE study. The diagram of document co-citations revealed the top 5 most cited articles among the 2125 publications collected from the WoS. Table 4 The top 10 most cited publications in BLHE research. Ranking Citation count Author(year) Publication name Journal or press 1 241 Garrison and Kanuka ( 2004 ) Blended learning: Uncovering its transformative potential in higher education The Internet and Higher Education 2 116 Graham (2006) The Handbook of Blended Learning: Global Perspectives, Local Designs San Francisco: Pfeiffer Publishing 3 76 Garrison and Vaughan (2007) Blended Learning in Higher Education: Framework, Principles, and Guidelines. San Francisco: Jossey-Bass. 4 75 Lopez-Perez et al. (2011) Blended Learning in Higher Education: Students' Perceptions and Their Relation to Outcomes Computers & Education 5 75 Graham et al. ( 2013 ) A framework for institutional adoption and implementation of blended learning in higher education Internation and higher education The most cited work, Garrison and Kanuka's (2004) ‘ Blended learning: Uncovering its transformative potential in higher education ’ (241 citations), stood as a cornerstone in the field. Its high citation count reflected its seminal role in introducing the Community of Inquiry (CoI) framework to blended learning contexts. This framework, emphasizing the interplay of cognitive, social, and teaching presence, has profoundly shaped subsequent research and practice. The work's enduring influence suggested that it successfully captured a fundamental conceptual need in the emerging field of blended learning. Graham's (2006) ‘ The Handbook of Blended Learning: Global Perspectives, Local Designs ’ (116 citations) marked a significant shift in the field's focus. While building on the theoretical foundations laid by Garrison and Kanuka ( 2004 ), Graham's work (2006) expanded the scope to include diverse global perspectives and implementation strategies. The substantial citation count, despite being published later, indicated a growing recognition of the importance of contextual factors in blended learning design. This work bridged the gap between theoretical frameworks and practical implementation, a theme that became increasingly prominent in later works. The next three works, all with similar citation counts (75–76), represented a diversification of research approaches in the field. Garrison and Vaughan's (2007) ‘ Blended Learning in Higher Education: Framework, Principles, and Guidelines ’ (76 citations) further developed the CoI framework, providing more detailed guidance for practitioners. Its similar citation count to Graham's work suggested that the field valued both theoretical refinement and practical application equally. López-Pérez et al.'s (2011) ‘ Blended Learning in Higher Education: Students' Perceptions and Their Relation to Outcomes ’ (75 citations) marked a crucial turn towards empirical validation. This study's quantitative approach, correlating student perceptions with learning outcomes, filled a critical gap in the literature. Its rapid accumulation of citations, despite being published later, indicated a strong demand for evidence-based research in the field. Graham et al.'s ( 2013 ) ‘ A framework for institutional adoption and implementation of blended learning in higher education ’ (75 citations) represented another significant shift, focusing on the institutional level of blended learning adoption. Its quick rise to prominence suggested a growing recognition of the need for systemic approaches to blended learning implementation. Methodologically, these works demonstrated a clear evolution in research approaches. Garrison and Kanuka ( 2004 ) as well as Graham (2006) primarily employed theoretical and conceptual analyses, laying the groundwork for the field. Garrison and Vaughan (2007) introduced more practical, design-based research approaches, bridging theory and practice. López-Pérez et al. (2011) marked a shift towards empirical, quantitative methods, using statistical analyses to correlate student perceptions with learning outcomes. This methodological diversity reflected the field's maturation and the growing recognition of the need for multiple research approaches to fully understand the complexities of blended learning. Theoretically, while the CoI framework dominates, particularly in the earlier works, there's a notable trend towards theoretical pluralism. None of these highly cited works adhered exclusively to a single learning theory. Instead, they drew from various constructivist and social learning principles, reflecting the inherently hybrid nature of blended learning. This theoretical eclecticism suggested that the field recognized the need for flexible, adaptable frameworks to accommodate the diverse contexts in which blended learning was implemented. Thematically, all five works emphasized the transformative potential of blended learning in higher education, but approached this potential from different angles. Garrison and Kanuka ( 2004 ) and Garrison and Vaughan (2007) focused on pedagogical transformation through the CoI framework. Graham (2006) emphasized the importance of contextual adaptation and cultural sensitivity in blended learning design. López-Pérez et al. (2011) highlighted the potential for improved student outcomes, while Graham et al. ( 2013 ) addressed the broader institutional transformations necessary for successful blended learning adoption. The evolution of these themes over time reflected the field's growing sophistication. Early works focused on defining blended learning and establishing theoretical frameworks. Later works moved towards providing practical implementation guidelines, empirical evidence of effectiveness, and strategies for institutional adoption. This progression mirrored the typical development of a maturing field of study, moving from conceptual foundations to practical applications and empirical validation. Interestingly, the balanced citation counts across the later works suggested that the field valued theoretical development, practical implementation, and empirical research equally. This balance indicated a holistic approach to understanding blended learning, recognizing that effective implementation required a combination of strong theoretical grounding, practical know-how, and evidence-based practice. The geographic diversity of the authors and their institutional affiliations (spanning North America and Europe) suggested that blended learning research was an international endeavor. However, the dominance of English-language publications from Western institutions also pointed to potential gaps in the literature, particularly regarding blended learning implementation in other cultural contexts. Co-occurring terms analysis. Keyword co-occurrence analysis is a powerful tool for identifying research areas and dominant topics within a field (Chen et al., 2016 ). This method leverages the principle that keywords in academic papers serve as concise summaries of the work's subject matter. When two or more keywords frequently appear together across multiple publications, it suggests a strong thematic relationship between these terms. This metric quantifies the strength of relationships between terms, allowing researchers to predict the likelihood of term co-occurrences even in related topics. Keywords with high Betweenness Centrality values are often particularly significant within the field of study. In our analysis of blended learning literature, we examined keywords that co-occurred in at least two separate publications. We employed a three-year slice length and set the Look Back Years (LBY) parameter to all years to ensure a comprehensive view of the field's evolution. The network of related keywords is shown in Fig. 3 . This approach allowed for the identification of research hotspots, as terms with high frequency often indicated areas of intense scholarly interest. The results of our analysis revealed that the top five most frequently occurring terms were blended learning, higher education, students, (online) learning, and flipped classroom. These keywords provided insight into the central themes and preoccupations of blended learning research during the studied period. Additionally, all terms that appeared more than 30 times in the analyzed literature were listed in Table 5 , providing a more comprehensive view of the field's vocabulary and research foci. Figure 3 Keyword co-occurrence network. The keyword co-occurrence network diagram revealed the most popular keywords in BLHE research. Table 5 co-occurring terms with high frequency count central keyword count central keyword count central keyword 955 0.26 blended learning 74 0.02 design 43 0.02 outcome 827 0.13 higher education 74 0.04 satisfaction 43 0.03 teachers 170 0.03 students 74 0.04 work-integrated learning 41 0.00 learning analytics 157 0.04 online 65 0.04 hybrid learning 40 0.04 distance education 134 0.01 online learning 57 0.03 motivation 37 0.02 flipped learning 113 0.02 flipped classroom 57 0.04 achievement 37 0.02 distance learning 107 0.03 perceptions 55 0.02 engagement 35 0.03 acceptance 105 0.05 performance 55 0.02 university 34 0.01 adoption 92 0.04 technology 46 0.01 student engagement 34 0.03 instruction 89 0.01 education 46 0.01 classroom 33 0.00 challenges 79 0.01 impact 46 0.04 experiences 32 0.01 knowledge 78 0.03 model 45 0.06 collaborative learning 31 0.03 framework Cluster interpretations. We utilized CiteSpace to conduct a cluster analysis based on keyword co-occurrences in the field of BLHE. The analysis, using a 3-year time slice, yielded a total of 674 nodes in the co-citation network, and 11 distinct clusters, providing a comprehensive overview of the research landscape in this field. Figure 4 illustrated these clusters, with warmer colors indicating more recent research topics and cooler colors representing older research themes. Table 6 presented the important clusters of keywords in BLHE research, including cluster size, silhouette value, and key terms associated with each cluster. The 11 clusters were named blended learning, collaborative learning, continuance intention, self-regulated learning, curriculum design, work-integrated learning, teaching/ learning strategies, hybrid learning, game-based learning, learning communities, community of inquiry . The largest cluster (#0) is labeled ‘blended learning,’ representing the core concept of the field. This cluster's high silhouette value (0.903) indicates its coherence and distinctiveness. Key terms within this cluster, such as ‘higher education,’ ‘flipped classroom,’ ‘online learning,’ and ‘student engagement,’ suggest a focus on innovative pedagogical approaches within tertiary education settings. Blended learning, as the central concept, has been extensively studied in higher education contexts (Garrison & Kanuka, 2004 ). Its transformative potential lies in its ability to integrate the strengths of face-to-face and online learning modalities. The inclusion of ‘flipped classroom’ in this cluster is particularly noteworthy, as it represents a specific implementation of blended learning that has gained significant attention in recent (Bergmann & Sams, 2012 ). The flipped classroom model inverts traditional teaching methods, delivering instructional content outside of the classroom and moving activities traditionally considered ‘homework’ into the classroom. This approach aligns well with the principles of blended learning, leveraging technology to enhance face-to-face interactions. The presence of ‘student engagement’ in this cluster underscores the potential of blended learning to increase student participation and motivation. Research has shown that well-designed blended learning environments could lead to higher levels of student engagement compared to traditional face-to-face or fully online courses (Halverson & Graham, 2019 ). This engagement is often attributed to the flexibility and interactivity offered by blended approaches. Closely related to this foundational cluster are ‘hybrid learning’ (#7) and ‘collaborative learning’ (#1). The hybrid learning cluster, with terms like ‘digital competence,’ ‘distance learning,’ and ‘learning technologies,’ reflects the evolving nature of blended learning as it incorporates more sophisticated digital elements. The emergence of hybrid learning as a distinct cluster suggests a nuanced approach to integrating face-to-face and online learning, potentially incorporating more advanced technologies and pedagogies. Within this cluster, the emphasis on digital competence underscores the significance of cultivating students' technological prowess alongside domain-specific knowledge, thus equipping them for a digitally-driven workforce. The collaborative learning cluster (#1), encompassing terms such as 'web 2.0,' 'English for academic purposes,' and 'bilingual education,' accentuates the value of interactive and participatory methodologies in blended environments. The prominence of this cluster signifies a paradigm shift from conventional, instructor-centric approaches towards more learner-oriented, dynamic models. This transition resonates with constructivist learning theories and illustrated the capacity of blended environments to nurture meaningful interactions among peers and between students and instructors (Szeto & Cheng, 2016 ). The inclusion of language-specific terms (English for academic/specific purposes, bilingual education) in the collaborative learning cluster suggests that blended learning is being actively explored in language education contexts. This may be due to the unique advantages blended approaches offer for language learning, such as opportunities for authentic communication, access to diverse language resources, and the ability to practice language skills both synchronously and asynchronously (Ahmad, 2021 ). Figure 4 | Cluster view of keyword co-occurrence for BLHE research Several clusters focus on the theoretical underpinnings and learning processes in blended environments. These include ‘self-regulated learning’ (#3), ‘community of inquiry’ (#10), and ‘learning communities’ (#9). The self-regulated learning cluster (#3), with terms like ‘mixed methods,’ ‘learning strategies,’ and ‘social network analysis,’ highlights the importance of learner autonomy and metacognition in blended contexts. This reflects a growing recognition that successful blended learning requires students to develop skills in managing their own learning processes (Garrison & Kanuka, 2004 ). The inclusion of ‘social network analysis’ in this cluster is intriguing, suggesting that researchers are exploring the social aspects of self-regulated learning in blended environments, perhaps examining how students' social connections influence their self-regulation strategies. The presence of ‘critical thinking’ in this cluster aligns with the idea that self-regulated learning could foster higher-order thinking skills. Blended learning environments, by their nature, often require students to navigate complex information landscapes, make decisions about their learning paths, and reflect on their progress – all activities that could promote critical thinking (Garrison & Kanuka, 2004 ). The community of inquiry framework (cluster #10), with its emphasis on teaching presence, social presence, and cognitive presence, has been particularly influential in blended learning research (Garrison et al., 1999). Its appearance as a distinct cluster underscores its significance in understanding the dynamics of blended learning environments. The inclusion of terms like ‘deep learning’ and ‘synchronous teaching model’ within this cluster suggests ongoing research into how to foster meaningful, collaborative learning experiences in blended settings. The CoI framework provides a valuable lens for understanding the complex interactions that occur in blended learning environments. Teaching presence refers to the design, facilitation, and direction of cognitive and social processes for the purpose of realizing personally meaningful and educationally worthwhile learning outcomes. Social presence is the ability of learners to project their personal characteristics into the community of inquiry, thereby presenting themselves as 'real people.' Cognitive presence is the extent to which learners are able to construct and confirm meaning through sustained reflection and discourse (Garrison et al., 1999). The learning communities cluster (#9), featuring terms such as ‘technology-enhanced learning,’ ‘undergraduate education,’ and ‘reflective practice,’ reflects the growing recognition of social learning theories in blended education. This cluster emphasizes the importance of creating supportive, interactive learning environments that extend beyond the traditional classroom (Wenger, 1998 ). The inclusion of ‘digital immigrants’ and ‘digital natives’ in this cluster suggests that researchers are considering generational differences in technology use and learning preferences when designing blended learning communities. Table 6 Important clusters of keywords in BLHE research. cluster ID size silhouette cluster names (LLR) LSI primary LSI secondary LLR 0 51 0.903 blended learning blended learning; collaborative learning; teaching evaluations; instructional change; online education online learning; student satisfaction; learning strategy; physical education; virtual learning blended learning (133.65, 1.0E-4); higher education (68.21, 1.0E-4); flipped classroom (38.68, 1.0E-4); online learning (35.66, 1.0E-4); student engagement (17.75, 1.0E-4) 1 49 0.789 collaborative learning blended learning; collaborative learning; continuous assessment; adaptive tests; technology quality formative assessment; learning report; formative feedback; teaching bpm; distance learning education collaborative learning (24.22, 1.0E-4); web 2.0 (23.61, 1.0E-4); English for academic purposes (23.36, 1.0E-4); English for specific purposes (18.68, 1.0E-4); bilingual education (18.68, 1.0E-4) 2 48 0.873 continuance intention blended learning; mobile learning; technology adoption; mixed methods; new technologies continuance intention; academic self-efficacy; intrinsic motivation; mandatory environments; success model continuance intention (21.51, 1.0E-4); grounded theory (16.25, 1.0E-4); technology acceptance (16.25, 1.0E-4); utaut (15.3, 1.0E-4); technology acceptance model (12.53, 0.001) 3 47 0.759 self-regulated learning blended learning; online learning; social capital; learning strategies; education self-regulated learning; blended course designs: academic success; czech republic; self-reported measures self-regulated learning (27.89, 1.0E-4); mixed methods (14.77, 0.001); learning strategies (13.85, 0.001); social network analysis (12.31, 0.001); critical thinking (10.37, 0.005) 4 47 0.731 curriculum design blended learning: public health; educational modality; work-integrated learning; sustainability assessment online learning; educational technology; hybrid learning; multi-criteria decision; decision making curriculum design (14.38, 0.001); continuing professional development (14.38, 0.001); online and blended learning (14.38, 0.001); communities of practice (14.37, 0.001); professional development (12.18, 0.001) 5 41 0.854 work-integrated learning work-integrated learning; scoping review; learning design; self-directed learning; study behaviors blended learning; transparency assessment; research methods; descriptive review; work placements work-integrated learning (100.14, 1.0E-4); blended learning (40, 1.0E-4); employability (30.82, 1.0E-4); online learning (17.18, 1.0E-4); work integrated learning (16.01, 1.0E-4) 6 31 0.866 teaching/learning strategies blended learning; digital content; hybrid learning; management studies; student-generated media learning strategies; pedagogical issues; improving classroom teaching; adult learning; digital content teaching learning strategies (37.5, 1.0E-4); pedagogical issues (25.6, 1.0E-4); improving classroom teaching (20.84, 1.0E-4); distributed learning environments (20.33, 1.0E-4); lifelong learning (19.58, 1.0E-4) 7 29 0.86 hybrid learning blended learning; online learning. social science; academic health; information technology hybrid learning; engineering education; computer-aided design; linear auto-regression; data mining hybrid learning (30 35, 1.0E-4); digital competence (24.71, 1.0E-4); distance learning (24.49, 1.0E-4); learning design (15.34, 1.0E-4); learning technologies (15.12, 0.001) 8 27 0.925 game-based learning Blended learning; game-based learning; advanced classroom technology; interactive tools; traditional learning Open educational resources; advanced classroom applications; learning space design; serious games; didactical innovations Game-based learning (41.77, 1.0E-4); flipped learning (41.77, 1.0E-4); learning by-doing (36.33, 1.0E-4); serious games (36.53, 1.0E-4); learning space design (36.53, 1.0E-4) 9 24 0.834 learning communities blended learning; reflective practice; digital immigrants; digital natives; digital storytelling technology-enhanced learning; undergraduate education༛ gross anatomy education: medical education; task-based language learning communities (15.39, 1.0E-4); technology-enhanced learning (13.42, 0.001); undergraduate education (13.23, 0.001); community of practice (13.2, 0.001) 10 20 0.871 community of inquiry blended learning;learning style model༛ learning level; deep learning: synchronous teaching model teaching presence; social presence; cognitive presence; blended learning contexts; inquiry framework community of inquiry (25.79, 1.0E-4); teaching presence (25.09, 1.0E-4); social presence (17.17, 1.0E-4); cognitive presence (12.7, 0.001); adult education (9.84, 0.005) Clusters related to technological aspects include ‘game-based learning’ (#8) and elements of ‘continuance intention’ (#2), which often deals with technology adoption. These clusters reflect the ongoing integration of innovative technologies in blended learning environments. Game-based learning's emergence as a distinct cluster (#8), with terms like ‘serious games,’ ‘learning by-doing,’ and ‘learning space design,’ suggests a growing interest in leveraging gamification and interactive technologies to enhance engagement and learning outcomes in blended settings (Tsay et al., 2018 ). This cluster highlights the potential of game-based approaches to create immersive, motivating learning experiences that complement traditional instructional methods. The integration of game-based learning in blended environments offers several potential benefits. Games could provide immediate feedback, allow for experimentation and failure in safe environments, and often incorporate elements of storytelling and problem-solving that can enhance engagement and knowledge retention, according to Tsay et al., ( 2018 ). Moreover, the ‘learning by-doing’ approach inherent in many games aligns well with constructivist learning theories that underpin much of blended learning design (Moreno-Ger et al., 2008 ). The continuance intention cluster (#2), featuring terms such as ‘technology acceptance,’ ‘UTAUT’ (Unified Theory of Acceptance and Use of Technology), and ‘grounded theory,’ indicates researchers' interest in understanding factors that influence the sustained use of blended learning technologies. They are crucial for ensuring the long-term success and adoption of blended learning approaches (Bhattacherjee, 2001 ). The presence of ‘grounded theory’ in this cluster suggests that researchers are employing qualitative, inductive approaches to understand technology acceptance in blended learning contexts. This methodological choice allows for the development of context-specific theories that could capture the nuanced factors influencing technology adoption in diverse educational settings. Clusters focused on design aspects include ‘curriculum design’ (#4), ‘work-integrated learning’ (#5), and elements of ‘teaching/learning strategies’ embedded in other clusters. These clusters highlight the importance of thoughtful design in blended learning implementations. The curriculum design cluster (#4), with terms like ‘continuing professional development,’ ‘communities of practice,’ and ‘multi-criteria decision,’ underscores the need for intentional and pedagogically sound approaches to blended learning. This cluster suggests a focus on designing blended learning experiences that are aligned with professional development needs and foster ongoing learning communities. The inclusion of ‘multi-criteria decision’ in this cluster is particularly interesting, as it suggests that researchers are exploring complex decision-making processes in curriculum design for blended learning. This could involve balancing various factors such as learning objectives, technological constraints, student preferences, and institutional resources when designing blended curricula. The work-integrated learning cluster (#5), featuring terms such as ‘employability,’ ‘scoping review,’ and ‘self-directed learning,’ suggests a trend towards aligning blended learning with professional and vocational education (Wuxue, 2023 ). This cluster highlights the potential of blended approaches to bridge the gap between academic learning and workplace requirements, potentially enhancing students' employability and career readiness. The emphasis on ‘self-directed learning’ within this cluster aligns well with the demands of many modern workplaces, where employees are often expected to take initiative in their own learning and professional development. Blended learning approaches, by offering flexibility and promoting self-regulation, may be particularly well-suited to preparing students for these workplace expectations. While not appearing as a distinct cluster, assessment and evaluation themes are present within several clusters, particularly in ‘collaborative learning’ (#1) and ‘curriculum design’ (#4). Terms like ‘continuous assessment,’ ‘formative feedback,’ and ‘adaptive tests’ within these clusters reflect the ongoing challenges and innovations in assessing student learning in blended environments (Gikandi et al., 2011 ). This cross-cutting theme suggests that researchers have been exploring ways to leverage both online and face-to-face components of blended learning for more effective and diverse assessment strategies. Continuous assessment and formative feedback, in particular, align well with the iterative and interactive nature of many blended learning approaches. These assessment strategies could provide ongoing insights into student progress, allowing for timely interventions and personalized support. The presence of ‘adaptive tests’ in the curriculum design cluster points to an interest in using technology to create more personalized assessment experiences. Adaptive testing, which adjusts the difficulty or content of questions based on a student's performance, could be particularly powerful in blended learning environments (Barla et al., 2010 ) where data on student performance can be collected and analyzed in real-time. 4. Discussion and implications for future studies Discussion The bibliometric analysis of BLHE research from 2001 to 2024 revealed a field that has undergone significant evolution, characterized by the development of robust theoretical frameworks, methodological diversification, and an increasing focus on practical applications. This study addressed three key research questions, providing insights into the intellectual structure, global diffusion, and critical research features of BLHE. The document co-citation analysis revealed a clear progression in the intellectual structure of blended learning research of the past more than two decades. The field's foundation was laid by Garrison and Kanuka's (2004) seminal work, which introduced the Community of Inquiry (CoI) framework to blended learning contexts. This framework, emphasizing the interplay of cognitive, social, and teaching presence, has become a cornerstone in conceptualizing effective blended learning environments. The enduring influence of this work, evidenced by its high citation count (241), suggested that it successfully captured a fundamental conceptual need in the emerging field of blended learning. The CoI framework's dominance in blended learning research aligned with broader trends in educational theory that emphasized the social nature of learning. As Garrison and Arbaugh (2007) noted, the CoI framework provided a valuable lens for understanding the complex interactions that occured in blended learning environments (Garrison & Arbaugh, 2007). However, as Rourke and Kanuka (2009) pointed out, there was a need for more research on how the CoI framework translated into measurable learning outcomes, suggesting a potential area for future investigation (Rourke & Kanuka, 2009). The progression of highly cited works demonstrated a clear evolution in the field's focus. Graham's (2006) ‘ The Handbook of Blended Learning: Global Perspectives, Local Designs ’ marked a shift towards contextual considerations in blended learning design. This work bridged the gap between theoretical frameworks and practical implementation, a theme that became increasingly prominent in later works. The emphasis on global perspectives and local designs resonated with calls from researchers like Uzuner (2009) for more cross-cultural studies in online and blended learning environments. Subsequent highly cited works by Garrison and Vaughan (2007), López-Pérez et al. (2011), and Graham et al. (2013) demonstrated a progression from theoretical foundations to empirical validation and institutional adoption strategies. This evolution mirrored the typical development pattern of maturing fields of study, as described by Kuhn (1962). in his work on the structure of scientific revolutions. The balanced citation counts across these later works suggested that the field valued theoretical development, practical implementation, and empirical research equally. This holistic approach recognized that effective implementation of blended learning required a combination of strong theoretical grounding, practical know-how, and evidence-based practice. This analysis examined the implications of the observed publication trends for the global diffusion and adoption of blended learning practices in higher education. This trend alignd with broader patterns of educational technology adoption and the increasing digitalization of higher education (Zawacki-Richter & Latchem, 2018). The slight dip in publications in 2020, followed by a quick rebound in 2021, likely reflected the impact of the COVID-19 pandemic and subsequent renewed interest in blended learning strategies. This observation was consistent with findings from other educational technology research areas, where the pandemic acted as a catalyst for increased interest and adoption of online and blended learning approaches (Ferdig et al., 2020). The geographic diversity of top institutions, spanning countries such as Australia, Portugal, Spain, and China, indicated that blended learning research is indeed a global endeavor. This diversity was crucial for developing a comprehensive understanding of blended learning, as it allowed for the exploration of cultural and contextual factors that may influence the effectiveness of blended learning approaches (Tarhini et al., 2015). However, the dominance of English-language publications from Western institutions also pointed to potential gaps in the literature, particularly regarding blended learning implementation in other cultural contexts. This observation aligned with concerns raised by Zawacki-Richter and Latchem (2018) about the need for more diverse perspectives in educational technology research. The prominence of conference proceedings among the most productive outlets suggested a field that valued rapid dissemination of ideas and practices. This was congruent with observations by Halverson et al. (2014), who noted the importance of conferences in disseminating emerging educational technology research. The preference for conference proceedings may be particularly beneficial in a fast-evolving area like blended learning, where practitioners and researchers alike benefited from timely access to new insights and best practices. This aligned with observations by Martin et al., (2018), who noted the importance of conferences in disseminating emerging educational technology research. The preference for conference proceedings may be particularly beneficial in a fast-evolving area like blended learning, where practitioners and researchers alike benefit from timely access to new insights and best practices. The cluster analysis revealed a rich tapestry of research areas within blended learning, providing a nuanced picture of the field's current focus. The emergence of distinct clusters around foundational concepts, theoretical frameworks, technological integration, curriculum design, and assessment methods reflected the multifaceted nature of blended learning research. The largest cluster, labeled ‘blended learning,’ encompassed core concepts such as ‘higher education,’ ‘flipped classroom,’ and ‘student engagement.’ The prominence of the ‘flipped classroom’ within this cluster reflected a growing interest in pedagogical models that leveraged technology to restructure traditional learning environments. As Bergmann and Sams (2012) argued, the flipped classroom model represented a specific implementation of blended learning that aimed to enhance face-to-face interactions by shifting content delivery to online platforms. However, the concentration of research on this particular model raised questions about whether other innovative blended learning approaches were being overlooked. The clusters focused on theoretical frameworks and learning processes, including ‘self-regulated learning,’ ‘community of inquiry,’ and ‘learning communities,’ underscore the field's strong theoretical grounding. The emergence of self-regulated learning as a distinct cluster resonated with findings from Broadbent and Poon (2015), who highlighted the importance of self-regulation skills in online and blended learning environments. This focus suggested that successful blended learning required students to develop skills in managing their own learning processes, a crucial competency in increasingly flexible and personalized learning environments (Schunk & Zimmerman, 2011). However, the emphasis on self-regulated learning also raised important questions about equity and access in blended learning environments. Students with well-developed self-regulation skills may thrive in these settings, while those who struggled with self-regulation may be at a disadvantage. This concern echoed broader issues of educational equity in digital learning environments, as highlighted by Broadbent and Poon (2015). Future research could explore interventions to support the development of self-regulation skills in blended learning contexts, particularly for students from diverse educational backgrounds. The persistence of the Community of Inquiry (CoI) framework, nearly two decades after its introduction, speaks to its robustness and applicability in understanding the complex interactions that occur in blended learning environments. However, as Rourke and Kanuka (2009) pointed out, there was a need for more research on how the CoI framework translated into measurable learning outcomes. This gap suggests a potential area for future research that could bridge theoretical understanding with practical outcomes. Clusters related to technological integration and innovation, such as ‘game-based learning’ and ‘continuance intention,’ reflect the ongoing integration of innovative technologies in blended learning environments. The game-based learning cluster, with terms like ‘serious games’ and ‘learning by-doing,’ aligns with findings from Dicheva et al. (2015), who identified positive effects of gamification on student engagement and motivation in various educational contexts, including blended learning. However, the enthusiasm for game-based learning and other technological innovations in blended environments should be tempered with critical consideration of their long-term effectiveness and potential drawbacks, as it was stressed by Meoreno-Ger et al. (2008) in his study. The continuance intention cluster, featuring terms such as ‘technology acceptance’ and ‘UTAUT’ (Unified Theory of Acceptance and Use of Technology), indicates ongoing interest in understanding the factors that influence the adoption and sustained use of blended learning technologies. This research stream, building on the work of Venkatesh et al. (2003), is crucial for ensuring the long-term success and sustainability of blended learning initiatives. The focus on technology acceptance and continuance intention also highlights a potential blind spot in the field. While understanding the factors that influence adoption is important, there is a risk of technological determinism – the assumption that technological innovation alone can drive educational improvement. Clusters focused on curriculum design and work-integrated learning highlight the importance of thoughtful design in blended learning implementations. The emergence of work-integrated learning as a distinct cluster suggests a trend towards aligning blended learning with professional and vocational education, reflecting broader trends in higher education towards more career-focused curricula (Bonk & Graham, 2012). While this trend is promising, it also raises questions about the broader purpose of higher education. There is a risk that an overemphasis on vocational skills could come at the expense of critical thinking, creativity, and other transferable skills that are crucial for long-term career success and civic engagement. The cross-cutting theme of assessment, evident across multiple clusters, reflected the ongoing challenges and innovations in evaluating student learning in blended environments. Terms like ‘continuous assessment,’ ‘formative feedback,’ and ‘adaptive tests’ suggested that researchers have been exploring ways to leverage both online and face-to-face components of blended learning for more effective and diverse assessment strategies. This aligns with the findings of Gikandi et al. (2011), who highlighted the potential of online formative assessment in blended and online learning contexts. However, the integration of these assessment strategies with traditional evaluation methods remains a challenge, particularly in institutional contexts where established assessment practices are deeply entrenched. Despite the rich insights provided by this analysis, several significant gaps and potential areas for future research emerge. The relatively low representation of studies from non-Western contexts suggests a pressing need for more diverse cultural perspectives on blended learning. This gap resonates with calls from researchers like Uzuner (2009) for more cross-cultural studies in online learning environments. Future research could explore how cultural factors influence the design, implementation, and effectiveness of blended learning approaches in different global contexts. Moreover, while the field has made significant progress in understanding the implementation of blended learning, there is still a critical need for more longitudinal studies that examine the long-term impacts on student outcomes and institutional transformation. Most of the highly cited works focus on short-term outcomes or implementation processes, leaving questions about the sustained effects of blended learning initiatives largely unanswered. This gap aligns with observations by Halverson and Graham (2019) about the need for more rigorous, long-term studies of blended learning effectiveness. The analysis also reveals potential methodological gaps in the field. While there is a mix of theoretical, quantitative, and qualitative approaches represented in the highly cited works, there appears to be a lack of large-scale, mixed-methods studies that combine the depth of qualitative insights with the breadth of quantitative data. Future research could benefit from more integrated methodological approaches, as suggested by Creswell and Plano Clark (2017), to provide a more comprehensive understanding of blended learning phenomena. As blended learning continues to evolve, the integration of emerging technologies such as artificial intelligence and virtual reality presents both opportunities and challenges. While these technologies have the potential to significantly reshape blended learning practices, their integration must be approached thoughtfully, with careful consideration of both pedagogical implications and ethical concerns. Implications for future studies. Based on the discussion, two critical issues that deserve more consideration in future studies on BLHE. Future research should focus on exploring how cultural factors influence the design, implementation, and effectiveness of blended learning approaches in diverse global contexts. The current literature is dominated by Western perspectives, leaving a significant gap in our understanding of how blended learning can be effectively adapted and implemented in non-Western educational systems. This line of inquiry is crucial as higher education becomes increasingly globalized. As Shadiev et al. (2024) points out, there is a pressing need for more cross-cultural studies in online and blended learning environments. Such research could investigate how different cultural values, learning styles, and educational traditions impact the acceptance and effectiveness of blended learning models. For instance, studies could explore how the Community of Inquiry (CoI) framework, which has been primarily developed and tested in Western contexts, translates to educational settings in Asia, Africa, or the Middle East. This research could build on the work of Garrison and Arbaugh (2007) but extend it to diverse cultural contexts, potentially leading to refinements or adaptations of the framework. Moreover, as Nistor et al. (2013) demonstrated in their cross-cultural examination of educational technology acceptance, factors influencing technology adoption can vary significantly across cultures. Future studies could extend this work to blended learning specifically, examining how cultural factors impact not just technology acceptance, but also engagement with different aspects of blended learning, such as online discussions, collaborative projects, or flipped classroom approaches. There is a critical need for more longitudinal studies that examine the long-term impacts of blended learning on student outcomes, skill development, and institutional transformation. As Versteijlen et al. (2023) observed, much of the existing research focuses on short-term outcomes or implementation processes, leaving questions about the sustained effects of blended learning initiatives largely unanswered. Future research should aim to track cohorts of students through blended learning programs and into their early career stages, examining not only academic outcomes but also the development of lifelong learning skills, digital literacy, and career readiness. Such studies could build on the work of Ingkavara et al. (2022) on self-regulated learning in online environments, extending it to long-term outcomes in blended learning contexts. Additionally, research should investigate the institutional factors that contribute to the sustainability of blended learning initiatives over time. This could involve examining how institutions successfully embed blended learning into their long-term strategic plans, adapt to evolving technologies, and maintain faculty engagement and development. The framework for institutional adoption proposed by Graham et al. (2013) could serve as a starting point for such investigations, but with a focus on long-term sustainability rather than initial adoption(Graham et al., 2013). Furthermore, as the educational technology landscape continues to evolve rapidly, longitudinal studies could explore how institutions successfully integrate emerging technologies like artificial intelligence and virtual reality into their blended learning models over time. This research could build on the work of Zawacki-Richter et al. (2019) on AI in higher education(Zawacki-Richter et al., 2019), but with a specific focus on its long-term integration and impact in blended learning environments. By addressing these two critical areas, future research can contribute to a more comprehensive and nuanced understanding of BLHE, informing both policy and practice in an increasingly diverse and technology-driven educational landscape. 5. Conclusion Blended learning has emerged as a significant area of research in higher education over the past two decades. This study aimed to systematically review the literature on BLHE using bibliometric tools, specifically CiteSpace. Our analysis of 2,125 publications from the Web of Science Core Collection spanning from 2001 to 2024 provides a comprehensive overview of the field's evolution, intellectual structure, and emerging trends. The descriptive analysis revealed a substantial increase in publications from 2013 onwards, with peak productivity in 2018 and 2019, indicating growing academic interest in blended learning across various disciplines. The slight dip in 2020 followed by a rebound in 2021 reflects the impact of the COVID-19 pandemic and the subsequent renewed focus on blended learning strategies. Our findings highlight the dominance of conference proceedings in disseminating blended learning research, with Edulearn Proceedings, Inted Proceedings, and Iceri Proceedings leading in publication output. This trend underscores the field's dynamic nature and the need for rapid knowledge exchange, as noted by Martin et al. (2020) in their recent review of educational technology research dissemination. Garrison and Kanuka's (2004) Community of Inquiry framework emerges as particularly influential in shaping blended learning research. The evolution of highly cited works demonstrates a clear progression from theoretical foundations to practical implementation strategies and empirical validation, reflecting the field's maturation. The cluster analysis identified 11 distinct research areas, including blended learning foundations, self-regulated learning, game-based learning, and work-integrated learning. These clusters highlighted the multifaceted nature of blended learning research and its integration with various pedagogical approaches and technologies. The prominence of self-regulated learning and technology acceptance models in these clusters resonated with recent findings by Junaštíková (2024) on the importance of learner autonomy and technology integration in successful blended learning implementations. Our analysis also revealed several gaps and potential areas for future research. Firstly, there is a pressing need for more diverse cultural perspectives on blended learning, particularly from non-Western contexts. As Serradell-Lopez et al. (2012) argued, understanding the cultural dimensions of blended learning is crucial for its effective global implementation(Serradell-Lopez et al., 2012). Secondly, longitudinal studies examining the long-term impacts of blended learning on student outcomes and institutional transformation are scarce(Ashraf et al., 2021). Future research should address this gap to provide insights into the sustained effects of blended learning initiatives. Furthermore, the integration of emerging technologies such as artificial intelligence and virtual reality in blended learning environments presents both opportunities and challenges that warrant further investigation(Zawacki-Richter et al., 2019). Additionally, as blended learning continues to evolve, research on innovative assessment strategies that leverage both online and face-to-face components will be crucial(Buhl-Wiggers et al., 2023). While this study aimed to provide a comprehensive review of blended learning research in higher education, it has some limitations. The analysis was limited to publications in the Web of Science Core Collection, potentially excluding relevant studies from other databases. Additionally, the rapid pace of technological advancements and the recent impact of the COVID-19 pandemic may not be fully reflected in the analyzed literature due to publication time lags. Despite these limitations, this bibliometric analysis offers a valuable overview of global research on BLHE. It provides researchers, educators, and policymakers with insights into the field's intellectual structure, emerging trends, and future directions. As blended learning continues to play a crucial role in shaping the future of higher education, addressing the identified research gaps and embracing new challenges will be essential for developing more effective, inclusive, and transformative learning experiences. The findings of this review have significant implications for both theory and practice in blended learning. They highlight the need for more integrated theoretical frameworks that can account for the complex interplay of pedagogical, technological, and institutional factors in blended learning environments. Practically, they underscore the importance of thoughtful design, ongoing assessment, and institutional support in successful blended learning implementations. As higher education continues to navigate the challenges of the digital age, the insights from this study can guide the development of more robust and effective blended learning strategies. Declarations Author Contribution author A conceptualized the study, conducted the bibliometric analysis using CiteSpace, and wrote the main manuscript text. author B contributed to the methodology design, assisted with data interpretation, and reviewed the results. Both author A and author B conducted the literature review, discussed the findings, and critically revised the manuscript. 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Educational technology acceptance across national and professional cultures: A European study. Educational Technology Research and Development , 61 (4), 733–749. https://doi.org/10.1007/s11423-013-9292-7 Pelletier, K., Brown, M., Brooks, D. C., McCormack, M., Reeves, J., Arbino, N., Bozkurt, A., Crawford, S., Czerniewicz, L., Gibson, R., Linder, K., Mason, J., & Mondelli, V. (2021). 2021 EDUCAUSE Horizon Report Teaching and Learning Edition (pp. 2–50). EDU. https://www.learntechlib.org/p/219489/ Rourke, L., & Kanuka, H. (2009). Learning in communities of inquiry: A review of the literature. Journal of Distance Education , 23 , 19–48. Schunk, D. H., & Zimmerman, B. (Eds.). (2011). Handbook of Self-Regulation of Learning and Performance . Routledge. https://doi.org/10.4324/9780203839010 Serradell-Lopez, E., Lara-Navarra, P., & Casado-Lumbreras, C. (2012). Higher education scenario from a cross-cultural perspective: eLearning implications. International Journal of Distance Education Technologies , 10 (4), 44–56. Shadiev, R., Chen, X., Reynolds, B. L., Song, Y., & Altinay, F. (2024). Facilitating cognitive development and addressing stereotypes with a cross-cultural learning activity supported by interactive 360-degree video technology. British Journal of Educational Technology , 55 (6), 2668–2696. https://doi.org/10.1111/bjet.13461 Short, C. R., Graham, C. R., Holmes, T., Oviatt, L., & Bateman, H. (2021). Preparing Teachers to Teach in K-12 Blended Environments: A Systematic Mapping Review of Research Trends, Impact, and Themes. TechTrends , 65 (6), 993–1009. https://doi.org/10.1007/s11528-021-00626-4 Stepanova, E. V. (2020). The Blended Learning in Higher Education. European Proceedings of Social and Behavioural Sciences , Economic and Social Trends for Sustainability of Modern Society (ICEST 2020) . https://doi.org/10.15405/epsbs.2020.10.03.103 Szeto, E., & Cheng, A. Y. N. (2016). Towards a framework of interactions in a blended synchronous learning environment: What effects are there on students’ social presence experience? Interactive Learning Environments , 24 (3), 487–503. https://doi.org/10.1080/10494820.2014.881391 Tarhini, A., Hone, K., & Liu, X. (2015). A cross-cultural examination of the impact of social, organisational and individual factors on educational technology acceptance between British and Lebanese university students. British Journal of Educational Technology , 46 (4), 739–755. https://doi.org/10.1111/bjet.12169 Tsay, C. H.-H., Kofinas, A., & Luo, J. (2018). Enhancing student learning experience with technology-mediated gamification: An empirical study. Computers & Education , 121 , 1–17. https://doi.org/10.1016/j.compedu.2018.01.009 Uzuner, S. (2009). Questions of Culture in Distance Learning: A Research Review. The International Review of Research in Open and Distributed Learning , 10 (3). https://doi.org/10.19173/irrodl.v10i3.690 Venkatesh, Morris, Davis, & Davis. (2003). User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly , 27 (3), 425. https://doi.org/10.2307/30036540 Versteijlen, M., & Wals, A. E. J. (2023). Developing Design Principles for Sustainability-Oriented Blended Learning in Higher Education. Sustainability , 15 (10), Article 10. https://doi.org/10.3390/su15108150 Wenger, E. (1998). Communities of practice: Learning, meaning, and identity (pp. xv, 318). Cambridge University Press. https://doi.org/10.1017/CBO9780511803932 Wuxue, J. (2023). The Influence of Optimized Blended Learning Mode on Learning Effectiveness for Higher Vocational College Students: A Quasi-Experimental Study in Higher Vocational College. Turkish Online Journal of Educational Technology - TOJET , 22 (2), 121–130. Zawacki-Richter, O., & Latchem, C. (2018). Exploring four decades of research in Computers & Education . Computers & Education , 122 , 136–152. https://doi.org/10.1016/j.compedu.2018.04.001 Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education – where are the educators? International Journal of Educational Technology in Higher Education , 16 (1), 39. https://doi.org/10.1186/s41239-019-0171-0 Zhu, M., Berri, S., & Zhang, K. (2021). Effective instructional strategies and technology use in blended learning: A case study. Education and Information Technologies , 26 (5), 6143–6161. https://doi.org/10.1007/s10639-021-10544-w Zupic, I., & Čater, T. (2015). Bibliometric Methods in Management and Organization. Organizational Research Methods , 18 (3), 429–472. https://doi.org/10.1177/1094428114562629 Additional Declarations No competing interests reported. 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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-5302006","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":368376123,"identity":"facd6a31-897f-4a36-971e-93854270a3cb","order_by":0,"name":"Xin Li","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABAklEQVRIiWNgGAWjYDACZsbGBxIVNnIMzBC+AYiQwKuFnbnZwOJMmjEJWvjZ2yQqWw4nNjAQq8WcmbFN4mbD4fT57ezPJH4wHDbWbWA+eJuHYRvcEHRg2czYbDlzR3ruhsM8ZpI9DIfNzA6wJVvzMNzGqcXgMGPjbckz1rkbmHnYbvAwHLYxO8BjJk1AS4P03zbmdPlm9mc3/4C18H8jpKVJQrLNOYHhMIMZ0Asgh/Gw4dUC8ouBxJk0Q6BfzH/LGKQbmx1mM7acY3DbGJcWc/7jD0FRKS/ff/yx4ZsKa8Ntx5sf3nhTcVsWp8MwucwQhiORWpCAPU6ZUTAKRsEoGGkAAP3/VzbrpcsLAAAAAElFTkSuQmCC","orcid":"","institution":"Universiti Kebangsaan Malaysia","correspondingAuthor":true,"prefix":"","firstName":"Xin","middleName":"","lastName":"Li","suffix":""},{"id":368376124,"identity":"fbc5b760-0b18-45f0-b5e5-4720e6daa917","order_by":1,"name":"Malaysia Zexun Huang","email":"","orcid":"","institution":"Universiti Kebangsaan Malaysia","correspondingAuthor":false,"prefix":"","firstName":"Malaysia","middleName":"Zexun","lastName":"Huang","suffix":""}],"badges":[],"createdAt":"2024-10-21 07:23:23","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5302006/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5302006/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":68141820,"identity":"3db527e7-0830-4fa4-b024-45e9f15b791a","added_by":"auto","created_at":"2024-11-04 05:09:14","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":41302,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAnnual publications on BLHE. The diagram reveals the publication number for each year and the general trend.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-5302006/v1/2d87879d887876c1b3b87dba.png"},{"id":68143053,"identity":"a85f24ff-14c0-4272-ac94-49b2f41e39b3","added_by":"auto","created_at":"2024-11-04 05:25:14","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":149536,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCrucial documents in BLHE study.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-5302006/v1/8270b4bb42cc25e908d1e8dc.png"},{"id":68141821,"identity":"41d36a54-e8e6-4e48-b2e5-74a98cacd237","added_by":"auto","created_at":"2024-11-04 05:09:14","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":395346,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eKeyword co-occurrence network. \u003c/strong\u003eThe keyword co-occurrence network diagram revealed the most popular keywords in BLHE research.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-5302006/v1/18fe472f15bb125b2007af2a.png"},{"id":68141823,"identity":"8c75d03c-392f-408a-bba2-ec319341f4f3","added_by":"auto","created_at":"2024-11-04 05:09:14","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":238182,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCluster view of keyword co-occurrence for BLHE research\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-5302006/v1/ade1fa3d82c77dc2b3b79d2d.png"},{"id":70449637,"identity":"643f74b3-8483-4a79-856c-dc84cee1abe0","added_by":"auto","created_at":"2024-12-03 09:25:09","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1742442,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5302006/v1/46913f5a-b90f-4cfc-8638-10d93a6cae9e.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"A Bibliometric Study of Blended Learning in Higher Education (2001- 2024)","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eThe educational landscape is evolving owing to technological advancements, historical occurrences, labour market transformations, and economic fluctuations. These pressures are transforming educational objectives and methodologies. Contemporary studies underscore the need for varied pedagogical methods (Markauskaite et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). In this context, blended learning (BL) has arisen as an innovative instructional method, receiving considerable attention in scholarly literature (Kang \u0026amp; Kim, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The past global pandemic has accelerated the use of blended learning approaches, positioning them at the front of educational innovation. By using technology advancements, BL has preserved its relevance and reinforced its significance in contemporary educational systems. The concept of BL, also known as mixed or hybrid learning (Atwa et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) has been subject to numerous interpretations in international literature. Despite the variety of definitions that exist, a common thread emerges: BL aims to harmonize the strengths of distance and face-to-face teaching methodologies (Garrison \u0026amp; Kanuka, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). At its core, BL is characterized by the seamless integration of online and traditional in-person educational processes. This integration is not merely a theoretical concept but a practical approach that has been tested and refined over time. The dynamic nature of BL has become particularly evident with the changing structure of both learners and learning environments. The COVID-19 pandemic, which forced a rapid and widespread adoption of online learning, has served as a catalyst for this change. The experiences gained during this period have boldly underlined the utility and resilience of the blended learning model. As a result, such cases have indicated a significant shift towards preferring this model in the future, a tendency that is both observable and likely to continue growing (Bozkurt \u0026amp; Sharma, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Pelletier et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Cruz-C\u0026aacute;rdenas et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Hebebci \u0026amp; Ozer, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn the realm of higher education, blended learning has become increasingly pivotal (Harasim, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). Universities and colleges worldwide are recognizing its potential to enhance the learning experience and outcomes for students (Adebayo et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). By combining the flexibility and resource-rich environment of online platforms with the interpersonal dynamics of face-to-face instruction, Blended Learning in Higher Education (BLHE) has offered a unique opportunity to cater to diverse learning styles and needs(Bhowmik et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). It has allowed for the optimization of both independent study and collaborative learning, preparing students for the digital-forward yet human-centric workplaces of the future (Stepanova, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Moreover, BLHE has not merely been a matter of integrating technology; it has been a fundamental change in the pedagogical approach that promotes digital literacy, critical thinking, and active learning, all of which are essential in the knowledge economy of today (Laufer et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). As higher education institutions grow, BL has emerged as a fundamental innovation, aiming to reconcile conventional academic excellence with the requirements of our increasingly linked and digital landscape(Harasim, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). Furthermore, its significance in higher education has grown exponentially, arousing the interest of scholars from various disciplines including education, psychology, technology, and sociology (Just, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Ma \u0026amp; Lee, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The complex characteristics of BL have resulted in a substantial and varied body of research, indicating its capacity to transform educational practices in higher education globally. BL has significantly evolved since its inception, influenced by technological breakthroughs and shifting pedagogical methodologies. Over the past two decades, researchers from different fields have contributed to our understanding of blended learning, exploring its impact on student engagement, learning outcomes, and institutional effectiveness (Bhowmik et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Cacciamani et al., \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Zhu et al., \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBlended learning in higher education (BLHE) has been the subject of numerous review papers in recent years, each addressing different subtopics within this broad field of inquiry. For instance, Balakrishnan et al. (2020) conducted a systematic review and meta-analysis focusing on the effectiveness of blended learning in pharmacy education, demonstrating significant enhancements in knowledge and abilities among pharmacy students compared to conventional teaching approaches. Short et al. (\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) performed a systematic mapping evaluation of research trends regarding teacher preparation for K-12 mixed contexts, highlighting the insufficient emphasis on K-12 blended learning and underscoring the need for more extensive studies in this domain. While these reviews provided valuable insights into specific aspects of blended learning, they do not offer a comprehensive bibliometric analysis of the field. Some researchers have attempted to address this gap. Specifically, Ibarra-Vargas et al. (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) undertook a bibliometric and cluster analysis of blended learning literature, establishing six topic groupings and emphasizing the prevalence of qualitative studies of hybrid course experiences. Similarly, Limaymanta et al. (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) carried out a bibliometric analysis of the flipped classroom in higher education, proposing a framework for its implementation in various learning modalities. More recently, Cruz-C\u0026aacute;rdenas et al. (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) and Hebebci and Ozer (2022) have conducted bibliometric analyses specifically focusing on BLHE. Cruz-C\u0026aacute;rdenas's study identified four main areas of interest, including the impact of COVID-19, the effectiveness of blended learning, its organization and design, and the technological tools used. Hebebci and Ozer's analysis mapped the development of blended learning research from 2005 to 2021, identifying key contributing countries and authors.\u003c/p\u003e \u003cp\u003eBuilding upon this existing body of research, the present study aims to contribute an updated perspective to the field's bibliometric analysis of BLHE. While recent reviews have made significant strides, this study differentiates itself in two key aspects. Firstly, while both Cruz-C\u0026aacute;rdenas et al. (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) and Hebebci and Ozer (2022) utilized VOSviewer for their analyses, this study employs CiteSpace, a powerful tool for visualizing and analyzing trends in scientific literature. Education research has seen a significant adoption of CiteSpace, as evidenced by studies like Chu et al. (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2023\u003c/span\u003e) on STEM interventions and Geng (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2024\u003c/span\u003e) on Chinese cultural integration in English education. This methodological variation offers an alternative approach to visualizing and analyzing the research landscape in BLHE. Secondly, this analysis extends the temporal scope to incorporate research conducted after the onset of the COVID-19 pandemic. This addresses a future research direction suggested by Hebebci and Ozer (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), who proposed examining post-COVID-19 studies. By including this more recent data, the present study offers a more current perspective on BLHE, complementing the COVID-19 impact area identified by Cruz-C\u0026aacute;rdenas et al. (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Through these approaches, this study aims to provide a comprehensive and up-to-date bibliometric analysis of BLHE, contributing to the ongoing development of this interdisciplinary field. Specifically, this CiteSpace-assisted review seeks to uncover prolific journals and conference proceedings, prominent researchers, significant institutions, and dynamic research issues, while creating a visual representation of related terms and dominant topics using keyword co-occurrence analysis. To achieve these objectives, the following research questions are proposed:\u003c/p\u003e \u003cp\u003eQ1: What are the key trends and patterns in the development of blended learning research in higher education over the past two decades?\u003c/p\u003e \u003cp\u003eQ2: In what ways can the temporal and geospatial analysis of research output contribute to our understanding of the global diffusion and adoption of blended learning practices in higher education?\u003c/p\u003e \u003cp\u003eQ3: To what extent can the cluster analysis of keywords and research topics identify critical research features and potential gaps in the current body of knowledge on BLHE?\u003c/p\u003e \u003cp\u003eBased on these research questions, it is hypothesized that the bibliometric analysis will reveal significant evolution in BLHE research, shifting from technological implementation to more nuanced explorations of pedagogical strategies and student outcomes. The study anticipates uncovering distinct patterns of global diffusion and identifying critical research features and potential gaps, particularly in areas related to faculty development and institutional policy-making.\u003c/p\u003e"},{"header":"2. Methodology","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003e2.1 Data collection\u003c/h2\u003e\n \u003cp\u003eThis study employed a comprehensive bibliometric analysis approach to examine the landscape of blended learning research in higher education. To ensure a robust and representative dataset, an advanced search was conducted in the Web of Science (WoS) Core Collection of Thomson Reuters. This database was selected due to its extensive coverage, rigorous indexing process, and compatibility with the chosen bibliometric analysis tools. The search encompassed multiple citation indices, including the Science Citation Index Expanded (SCIE), Social Sciences Citation Index (SSCI), Arts and Humanities Citation Index (AHCI), Conference Proceedings Citation Index (CPCI), and Emerging Sources Citation Index (ESCI). This multi-index approach allowed for a broad and interdisciplinary collection of literature pertinent to the research focus.\u003c/p\u003e\n \u003cp\u003eTo capture the full spectrum of research on BLHE from 2001 to 2024, a comprehensive literature search was conducted. This time frame was chosen to encompass the early stages of blended learning adoption in higher education through to its current state, allowing for a thorough analysis of trends and developments over more than two decades. A set of key search terms was carefully selected to ensure comprehensive coverage: \u0026lsquo;blended learning\u0026rsquo;, \u0026lsquo;blended education\u0026rsquo;, \u0026lsquo;blended courses\u0026rsquo;, \u0026lsquo;integrated learning\u0026rsquo;, \u0026lsquo;hybrid learning\u0026rsquo;, and \u0026lsquo;higher education\u0026rsquo;. This selection was based on common terminology used in the field (Hrastinski, \u003cspan class=\"CitationRef\"\u003e2019\u003c/span\u003e). On July 22, 2024, an advanced search was executed in the Web of Science (WoS) database using the following search string: TS= (blended learning* OR blended education* OR blended course* OR integrated learning* OR hybrid learning*) AND (higher education). This strategy ensured retrieval of articles containing the specified terms in their title, abstract, or keywords. The search was limited to research articles and review articles to focus on original research and comprehensive syntheses of the field, a common practice in bibliometric studies(Zupic \u0026amp; Čater, \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e). Importantly, no language restrictions were applied, recognizing that valuable contributions might exist in non-English publications.\u003c/p\u003e\n \u003cp\u003eThe initial search yielded 2144 results from WoS. A meticulous screening process was then undertaken to refine the dataset. Book reviews, book chapters, editorial materials, letters, and retracted publications were excluded from the analysis, following standard bibliometric practices (Aria \u0026amp; Cuccurullo, \u003cspan class=\"CitationRef\"\u003e2017\u003c/span\u003e). This screening process resulted in a final dataset of 2125 research articles and review articles. These documents spanned various WoS categories, predominantly including \u0026apos;Education\u0026apos;, \u0026apos;Computer Science\u0026apos;, \u0026apos;Social Sciences\u0026apos;, and \u0026apos;Linguistics\u0026apos;, reflecting the interdisciplinary nature of BLHE research. This refined dataset formed the basis for subsequent bibliometric analysis, providing a comprehensive overview of the field\u0026apos;s development, key trends, and influential works in blended learning within higher education of more than two decades. The use of such a dataset for bibliometric analysis has been well-established in educational research (Chen, et al. \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003e2.2 Descriptive Analysis\u003c/h3\u003e\n\u003cp\u003ePrior to the in-depth bibliometric analysis, a comprehensive descriptive analysis of the dataset was conducted. This preliminary analysis aimed to provide an overview of publication trends and identify key contributors to the field of BLHE. The analysis began with an examination of the yearly publication trends from 2001 to 2024. This temporal analysis allowed for tracing the evolution of research interest in blended learning over time, identifying periods of rapid growth or potential plateaus in scholarly output. To visualize this trend, SPSS software was used to generate a bar graph depicting the number of publications per year.\u003c/p\u003e\n\u003cp\u003eThe WoS website provided data on the number of publications for each journal, author, and institution. For journals and conference proceedings, we selected the top 5 for in-depth analysis, while for authors and institutions, we examined the top 10. These rankings offer insights into the key contributors and platforms driving research in this field. The analysis of the most productive journals and conference proceedings has revealed which publications have been most influential in disseminating research on BLHE. Similarly, identifying the most prolific authors has provided an understanding of the key thought leaders and researchers shaping the field. The examination of the most productive institutions highlightd the academic centers that have been at the forefront of blended learning research and implementation in higher education settings.\u003c/p\u003e\n\u003ch3\u003e2.3 CiteSpace Analysis\u003c/h3\u003e\n\u003cp\u003eWhile the descriptive analysis based on Web of Science (WoS) data has provided a valuable initial overview of the research field of BLHE, it has limitations in fully capturing the intellectual structure and emerging trends of this rapidly evolving domain (Zupic \u0026amp; Čater, \u003cspan class=\"CitationRef\"\u003e2015\u003c/span\u003e). The basic statistics on publication counts, top journals conference proceedings, authors, and institutions have offered a general picture but couldn\u0026rsquo;t provide an exhaustive account of the field\u0026apos;s development of the past more than two decades or identify the most recent directions for future research (Chen, \u003cspan class=\"CitationRef\"\u003e2006\u003c/span\u003e). Traditional literature reviews in the field of blended learning have often relied on researchers\u0026apos; prior knowledge and subjective judgement (Halverson et al., \u003cspan class=\"CitationRef\"\u003e2014\u003c/span\u003e). This approach, while valuable, risks overlooking crucial information or emerging trends, particularly given the interdisciplinary nature and rapid technological advancements characteristic of blended learning research. The complex interplay between education, technology, and pedagogy in blended learning has made it challenging for individual researchers to comprehensively track all relevant developments.\u003c/p\u003e\n\u003cp\u003eTo move beyond the limitations of basic descriptive statistics and gain deeper insights into the intellectual structure and evolution of BLHE research, CiteSpace, an information visualization analysis software designed to present the structure and distribution of scientific knowledge through visualization (Chen, \u003cspan class=\"CitationRef\"\u003e2006\u003c/span\u003e; Kim et al., \u003cspan class=\"CitationRef\"\u003e2016\u003c/span\u003e; Hou et al., \u003cspan class=\"CitationRef\"\u003e2020\u003c/span\u003e) has been employed for the bibliometric analysis. This approach allows us to examine the structures and characteristics of the existing knowledge regarding BLHE in a more systematic and data-driven manner (Chen, \u003cspan class=\"CitationRef\"\u003e2018\u003c/span\u003e). A key feature of CiteSpace is its ability to select a particular field based on a time sequence and link both together, enabling the deduction of developmental trends and changes within the area of BLHE (Chen et al., \u003cspan class=\"CitationRef\"\u003e2009\u003c/span\u003e). In our study, the bibliographic data files collected from WoS were in the field-tagged Institute for Scientific Information Export Format. We selected the \u0026lsquo;full record and cited references\u0026rsquo; as the content, allowing CiteSpace to easily identify the files.\u003c/p\u003e\n\u003cp\u003eOnce the files were loaded into CiteSpace, the following procedural operations were performed: time slicing, thresholding, modeling, pruning, merging, and mapping (Chen, \u003cspan class=\"CitationRef\"\u003e2004\u003c/span\u003e). These operations allowed for a comprehensive analysis of the blended learning literature. We conducted two separate visualizing analyses of the data:\u003c/p\u003e\n\u003cp\u003e\u003cspan\u003e\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003ea. Document Co-citation Analysis: This analysis helped identify important documents in blended learning research. A co-cited reference was called a node, and when several nodes were strongly related to one another, they formed a cluster. This analysis revealed the intellectual structure and key influencers in the field of BLHE;\u003c/p\u003e\u003cspan\u003e\n \u003cp\u003eb. Keyword Co-occurrence Analysis: The purpose of this analysis was to identify the most-discussed areas in research on BLHE. This helped in understanding the main themes and trends in the field over time.\u003c/p\u003e\n\u003c/span\u003e"},{"header":"3. Results","content":"\u003cp\u003e \u003cb\u003ePublication years, journals and conference proceedings, productive authors, and institutions on BLHE.\u003c/b\u003e Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e indicated the Annual publications on BLHE research. In the web of Science core collection, this research field experienced a slow start from 2001 to 2008, with fewer than 20 publications per year. A noticeable increase began in 2009, with 22 publications, marking the beginning of more significant interest in the topic. Rapid growth was observed from 2013 onwards, with publications more than doubling from 67 in 2012 to 138 in 2015. The field reached its peak in terms of publications in 2018 and 2019, with 196 and 194 papers respectively. Interestingly, there was a slight dip in 2020 to 182 papers, possibly due to the disruptions caused by the COVID-19 pandemic. However, the field quickly rebounded in 2021 with 194 publications, suggesting a renewed interest in blended learning strategies as institutions adapted to new educational paradigms. The most recent years has shown a gradual decline in the number of publications, with 162 in 2022, 140 in 2023, and 101 in the partial year of 2024. This trend could indicate a maturation of the field or a shift in research focus within higher education.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. \u003cb\u003eAnnual publications on BLHE. The diagram reveals the publication number for each year and the general trend.\u003c/b\u003e\u003c/p\u003e \u003cp\u003eExamining 2,125 articles and reviews revealed a diverse landscape of publication venues, encompassing both traditional journals and conference proceedings. Notably, conference proceedings dominated the upper echelons of this bibliometric analysis. At the forefront, \u003cem\u003eEdulearn Proceedings\u003c/em\u003e stood out with an impressive 177 papers, closely followed by \u003cem\u003eInted Proceedings\u003c/em\u003e and \u003cem\u003eIceri Proceedings\u003c/em\u003e, contributing 138 and 87 publications respectively. Occupying the fourth position, \u003cem\u003eLecture Notes in Computer Science\u003c/em\u003e, a book series frequently utilized for conference proceedings, accounted for 63 publications. \u003cem\u003eEducation and Information Technolog\u003c/em\u003eies emerged as the first traditional journal on the list, securing the fifth rank with 60 papers. Subsequently, another conference proceeding, \u003cem\u003eProceedings of the European Conference on E-Learning\u003c/em\u003e, claimed the sixth spot with 49 publications. Further down the list, two more journals make their appearance: \u003cem\u003eHigher Education Research Development\u003c/em\u003e and \u003cem\u003eProcedia Social and Behavioral Sciences\u003c/em\u003e, contributing 40 and 36 papers respectively. Rounding out the top ten were \u003cem\u003eElearning and Software for Education\u003c/em\u003e, a hybrid publication featuring both journal articles and conference proceedings, and the journal \u003cem\u003eSustainability\u003c/em\u003e, both tied at 34 publications each.\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\u003eTop 10 most fruitful journals and conference proceedings for BLHE research.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRanking\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJournals\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eThe number of published papers\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eEdulearn Proceedings\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e177\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eInted Proceedings\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e138\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eIceri Proceedings\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e87\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eLecture Notes in Computer Science\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eEducation And Information Technologies\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e60\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eProceedings On the European Conference of E Learning\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eHigher Education Research Development\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eProcedia Social and Behavioral Sciences\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eElearning And Software for Education\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eSustainability\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presented the top 10 most productive authors for BLHE research. The table ranked authors based on their number of published papers in this field. Jes\u0026uacute;s Sergio Artal-Sevil led the list with 19 publications, followed by Chang Zhu with 14 publications. Denise Jackson and Enrique Romero shared the third position, each with 10 publications. The remaining authors in the top 10 had between 7 and 9 publications each, with Yang Harrison Hao rounding out the list at 10th place with 7 published papers.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTop 10 most productive authors for BLHE research\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRanking\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAuthors\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eThe number of published papers\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eArtal-Sevil, Jes\u0026uacute;s Sergio\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eZhu, Chang\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eJackson, Denise\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRomero, Enrique\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHan, Feifei\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGraham, Charles R.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSimonova, Ivana\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eManuel Artacho, J.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCastro, Manuel\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYang, Harrison Hao\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTurning to institutional productivity (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), we noticed a landscape dominated by university systems rather than individual institutions. Griffith University topped the list with 29 published papers. Deakin University, Instituto Polit\u0026eacute;cnico do Porto, and University of Zaragoza were tied for second place, each with 23 publications. The list included universities from various countries, including Australia, Portugal, Spain, Belgium, and China. Interestingly, the Ministry of Education and Science of Ukraine appeared in the 9th position with 16 publications, indicating significant governmental involvement in this research area. The number of published papers for these institutions ranged from 29 to 16, with the University of Granada completing the top 10 with 16 publications.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTop 10 most productive institutions for BLHE research\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRanking\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInstitutions\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eThe number of published papers\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGriffith University\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDeakin University\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInstituto Polit\u0026eacute;cnico do Porto\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUniversity of Zaragoza\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVrije Universiteit Brusse\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCentral China Normal University\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUniversidad Nacional de Educaci\u0026oacute;n a Distancia (UNED)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHong Kong Polytechnic University\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMinistry of Education and Science of Ukraine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUniversity of Granada\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eDocument co-citation analysis.\u003c/b\u003e The document co-citation analysis of 2125 publications on BLHE, spanning from 2001 to 2024, revealed a comprehensive picture of the field's intellectual structure. Using CiteSpace, we generated a visualization of the co-citation network, which comprised 674 nodes representing cited publications and 2801 links indicating co-citation relationships, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The network was constructed by selecting the top 50 most-cited papers per 3-year time slice, allowing for a more granular view of the field's evolution over time. The resulting visualization presented a dense and intricate network structure with node sizes reflecting citation frequency and a color spectrum from cool to warm tones representing the temporal progression of publications. The modularity Q score of 0.8165 indicated a well-structured network with clearly defined communities, while the mean silhouette value of 0.3607 suggested reasonable clarity in the cluster divisions.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e \u003cb\u003eCrucial documents in BLHE study.\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThe diagram of document co-citations revealed the top 5 most cited articles among the 2125 publications collected from the WoS.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe top 10 most cited publications in BLHE research.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRanking\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCitation count\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAuthor(year)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePublication name\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eJournal or press\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e241\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGarrison and Kanuka (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2004\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBlended learning: Uncovering its transformative potential in higher education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eThe Internet and Higher Education\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGraham (2006)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eThe Handbook of Blended Learning: Global Perspectives, Local Designs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSan Francisco: Pfeiffer Publishing\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGarrison and Vaughan (2007)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBlended Learning in Higher Education: Framework, Principles, and Guidelines.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSan Francisco: Jossey-Bass.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLopez-Perez et al. (2011)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBlended Learning in Higher Education: Students' Perceptions and Their Relation to Outcomes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eComputers \u0026amp; Education\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGraham et al. (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2013\u003c/span\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eA framework for institutional adoption and implementation of blended learning in higher education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eInternation and higher education\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe most cited work, Garrison and Kanuka's (2004) \u0026lsquo;\u003cem\u003eBlended learning: Uncovering its transformative potential in higher education\u003c/em\u003e\u0026rsquo; (241 citations), stood as a cornerstone in the field. Its high citation count reflected its seminal role in introducing the Community of Inquiry (CoI) framework to blended learning contexts. This framework, emphasizing the interplay of cognitive, social, and teaching presence, has profoundly shaped subsequent research and practice. The work's enduring influence suggested that it successfully captured a fundamental conceptual need in the emerging field of blended learning. Graham's (2006) \u0026lsquo;\u003cem\u003eThe Handbook of Blended Learning: Global Perspectives, Local Designs\u003c/em\u003e\u0026rsquo; (116 citations) marked a significant shift in the field's focus. While building on the theoretical foundations laid by Garrison and Kanuka (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2004\u003c/span\u003e), Graham's work (2006) expanded the scope to include diverse global perspectives and implementation strategies. The substantial citation count, despite being published later, indicated a growing recognition of the importance of contextual factors in blended learning design. This work bridged the gap between theoretical frameworks and practical implementation, a theme that became increasingly prominent in later works. The next three works, all with similar citation counts (75\u0026ndash;76), represented a diversification of research approaches in the field. Garrison and Vaughan's (2007) \u0026lsquo;\u003cem\u003eBlended Learning in Higher Education: Framework, Principles, and Guidelines\u003c/em\u003e\u0026rsquo; (76 citations) further developed the CoI framework, providing more detailed guidance for practitioners. Its similar citation count to Graham's work suggested that the field valued both theoretical refinement and practical application equally. L\u0026oacute;pez-P\u0026eacute;rez et al.'s (2011) \u0026lsquo;\u003cem\u003eBlended Learning in Higher Education: Students' Perceptions and Their Relation to Outcomes\u003c/em\u003e\u0026rsquo; (75 citations) marked a crucial turn towards empirical validation. This study's quantitative approach, correlating student perceptions with learning outcomes, filled a critical gap in the literature. Its rapid accumulation of citations, despite being published later, indicated a strong demand for evidence-based research in the field. Graham et al.'s (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) \u0026lsquo;\u003cem\u003eA framework for institutional adoption and implementation of blended learning in higher education\u003c/em\u003e\u0026rsquo; (75 citations) represented another significant shift, focusing on the institutional level of blended learning adoption. Its quick rise to prominence suggested a growing recognition of the need for systemic approaches to blended learning implementation.\u003c/p\u003e \u003cp\u003eMethodologically, these works demonstrated a clear evolution in research approaches. Garrison and Kanuka (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2004\u003c/span\u003e) as well as Graham (2006) primarily employed theoretical and conceptual analyses, laying the groundwork for the field. Garrison and Vaughan (2007) introduced more practical, design-based research approaches, bridging theory and practice. L\u0026oacute;pez-P\u0026eacute;rez et al. (2011) marked a shift towards empirical, quantitative methods, using statistical analyses to correlate student perceptions with learning outcomes. This methodological diversity reflected the field's maturation and the growing recognition of the need for multiple research approaches to fully understand the complexities of blended learning. Theoretically, while the CoI framework dominates, particularly in the earlier works, there's a notable trend towards theoretical pluralism. None of these highly cited works adhered exclusively to a single learning theory. Instead, they drew from various constructivist and social learning principles, reflecting the inherently hybrid nature of blended learning. This theoretical eclecticism suggested that the field recognized the need for flexible, adaptable frameworks to accommodate the diverse contexts in which blended learning was implemented. Thematically, all five works emphasized the transformative potential of blended learning in higher education, but approached this potential from different angles. Garrison and Kanuka (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2004\u003c/span\u003e) and Garrison and Vaughan (2007) focused on pedagogical transformation through the CoI framework. Graham (2006) emphasized the importance of contextual adaptation and cultural sensitivity in blended learning design. L\u0026oacute;pez-P\u0026eacute;rez et al. (2011) highlighted the potential for improved student outcomes, while Graham et al. (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) addressed the broader institutional transformations necessary for successful blended learning adoption. The evolution of these themes over time reflected the field's growing sophistication. Early works focused on defining blended learning and establishing theoretical frameworks. Later works moved towards providing practical implementation guidelines, empirical evidence of effectiveness, and strategies for institutional adoption. This progression mirrored the typical development of a maturing field of study, moving from conceptual foundations to practical applications and empirical validation. Interestingly, the balanced citation counts across the later works suggested that the field valued theoretical development, practical implementation, and empirical research equally. This balance indicated a holistic approach to understanding blended learning, recognizing that effective implementation required a combination of strong theoretical grounding, practical know-how, and evidence-based practice. The geographic diversity of the authors and their institutional affiliations (spanning North America and Europe) suggested that blended learning research was an international endeavor. However, the dominance of English-language publications from Western institutions also pointed to potential gaps in the literature, particularly regarding blended learning implementation in other cultural contexts.\u003c/p\u003e \u003cp\u003e \u003cb\u003eCo-occurring terms analysis.\u003c/b\u003e Keyword co-occurrence analysis is a powerful tool for identifying research areas and dominant topics within a field (Chen et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). This method leverages the principle that keywords in academic papers serve as concise summaries of the work's subject matter. When two or more keywords frequently appear together across multiple publications, it suggests a strong thematic relationship between these terms. This metric quantifies the strength of relationships between terms, allowing researchers to predict the likelihood of term co-occurrences even in related topics. Keywords with high Betweenness Centrality values are often particularly significant within the field of study. In our analysis of blended learning literature, we examined keywords that co-occurred in at least two separate publications. We employed a three-year slice length and set the Look Back Years (LBY) parameter to all years to ensure a comprehensive view of the field's evolution. The network of related keywords is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. This approach allowed for the identification of research hotspots, as terms with high frequency often indicated areas of intense scholarly interest. The results of our analysis revealed that the top five most frequently occurring terms were blended learning, higher education, students, (online) learning, and flipped classroom. These keywords provided insight into the central themes and preoccupations of blended learning research during the studied period. Additionally, all terms that appeared more than 30 times in the analyzed literature were listed in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, providing a more comprehensive view of the field's vocabulary and research foci.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e \u003cb\u003eKeyword co-occurrence network.\u003c/b\u003e The keyword co-occurrence network diagram revealed the most popular keywords in BLHE research.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eco-occurring terms with high frequency\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" 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=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ecount\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ecentral\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ekeyword\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ecount\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ecentral\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ekeyword\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ecount\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003ecentral\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003ekeyword\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e955\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eblended learning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003edesign\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eoutcome\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e827\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ehigher education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003esatisfaction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eteachers\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e170\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003estudents\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ework-integrated learning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003elearning analytics\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e157\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eonline\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ehybrid learning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003edistance education\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e134\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eonline learning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003emotivation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eflipped learning\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e113\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eflipped classroom\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eachievement\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003edistance learning\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e107\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eperceptions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eengagement\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eacceptance\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eperformance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003euniversity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eadoption\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003etechnology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003estudent engagement\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003einstruction\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eeducation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eclassroom\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003echallenges\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eimpact\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e46\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eexperiences\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eknowledge\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003emodel\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ecollaborative learning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eframework\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eCluster interpretations.\u003c/b\u003e We utilized CiteSpace to conduct a cluster analysis based on keyword co-occurrences in the field of BLHE. The analysis, using a 3-year time slice, yielded a total of 674 nodes in the co-citation network, and 11 distinct clusters, providing a comprehensive overview of the research landscape in this field. Figure\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e illustrated these clusters, with warmer colors indicating more recent research topics and cooler colors representing older research themes. Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e presented the important clusters of keywords in BLHE research, including cluster size, silhouette value, and key terms associated with each cluster. The 11 clusters were named \u003cem\u003eblended learning, collaborative learning, continuance intention, self-regulated learning, curriculum design, work-integrated learning, teaching/ learning strategies, hybrid learning, game-based learning, learning communities, community of inquiry\u003c/em\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe largest cluster (#0) is labeled \u0026lsquo;blended learning,\u0026rsquo; representing the core concept of the field. This cluster's high silhouette value (0.903) indicates its coherence and distinctiveness. Key terms within this cluster, such as \u0026lsquo;higher education,\u0026rsquo; \u0026lsquo;flipped classroom,\u0026rsquo; \u0026lsquo;online learning,\u0026rsquo; and \u0026lsquo;student engagement,\u0026rsquo; suggest a focus on innovative pedagogical approaches within tertiary education settings. Blended learning, as the central concept, has been extensively studied in higher education contexts (Garrison \u0026amp; Kanuka, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Its transformative potential lies in its ability to integrate the strengths of face-to-face and online learning modalities. The inclusion of \u0026lsquo;flipped classroom\u0026rsquo; in this cluster is particularly noteworthy, as it represents a specific implementation of blended learning that has gained significant attention in recent (Bergmann \u0026amp; Sams, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). The flipped classroom model inverts traditional teaching methods, delivering instructional content outside of the classroom and moving activities traditionally considered \u0026lsquo;homework\u0026rsquo; into the classroom. This approach aligns well with the principles of blended learning, leveraging technology to enhance face-to-face interactions. The presence of \u0026lsquo;student engagement\u0026rsquo; in this cluster underscores the potential of blended learning to increase student participation and motivation. Research has shown that well-designed blended learning environments could lead to higher levels of student engagement compared to traditional face-to-face or fully online courses (Halverson \u0026amp; Graham, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). This engagement is often attributed to the flexibility and interactivity offered by blended approaches. Closely related to this foundational cluster are \u0026lsquo;hybrid learning\u0026rsquo; (#7) and \u0026lsquo;collaborative learning\u0026rsquo; (#1). The hybrid learning cluster, with terms like \u0026lsquo;digital competence,\u0026rsquo; \u0026lsquo;distance learning,\u0026rsquo; and \u0026lsquo;learning technologies,\u0026rsquo; reflects the evolving nature of blended learning as it incorporates more sophisticated digital elements. The emergence of hybrid learning as a distinct cluster suggests a nuanced approach to integrating face-to-face and online learning, potentially incorporating more advanced technologies and pedagogies. Within this cluster, the emphasis on digital competence underscores the significance of cultivating students' technological prowess alongside domain-specific knowledge, thus equipping them for a digitally-driven workforce. The collaborative learning cluster (#1), encompassing terms such as 'web 2.0,' 'English for academic purposes,' and 'bilingual education,' accentuates the value of interactive and participatory methodologies in blended environments. The prominence of this cluster signifies a paradigm shift from conventional, instructor-centric approaches towards more learner-oriented, dynamic models. This transition resonates with constructivist learning theories and illustrated the capacity of blended environments to nurture meaningful interactions among peers and between students and instructors (Szeto \u0026amp; Cheng, \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). The inclusion of language-specific terms (English for academic/specific purposes, bilingual education) in the collaborative learning cluster suggests that blended learning is being actively explored in language education contexts. This may be due to the unique advantages blended approaches offer for language learning, such as opportunities for authentic communication, access to diverse language resources, and the ability to practice language skills both synchronously and asynchronously (Ahmad, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e \u003cb\u003e| Cluster view of keyword co-occurrence for BLHE research\u003c/b\u003e\u003c/p\u003e \u003cp\u003eSeveral clusters focus on the theoretical underpinnings and learning processes in blended environments. These include \u0026lsquo;self-regulated learning\u0026rsquo; (#3), \u0026lsquo;community of inquiry\u0026rsquo; (#10), and \u0026lsquo;learning communities\u0026rsquo; (#9). The self-regulated learning cluster (#3), with terms like \u0026lsquo;mixed methods,\u0026rsquo; \u0026lsquo;learning strategies,\u0026rsquo; and \u0026lsquo;social network analysis,\u0026rsquo; highlights the importance of learner autonomy and metacognition in blended contexts. This reflects a growing recognition that successful blended learning requires students to develop skills in managing their own learning processes (Garrison \u0026amp; Kanuka, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). The inclusion of \u0026lsquo;social network analysis\u0026rsquo; in this cluster is intriguing, suggesting that researchers are exploring the social aspects of self-regulated learning in blended environments, perhaps examining how students' social connections influence their self-regulation strategies. The presence of \u0026lsquo;critical thinking\u0026rsquo; in this cluster aligns with the idea that self-regulated learning could foster higher-order thinking skills. Blended learning environments, by their nature, often require students to navigate complex information landscapes, make decisions about their learning paths, and reflect on their progress \u0026ndash; all activities that could promote critical thinking (Garrison \u0026amp; Kanuka, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). The community of inquiry framework (cluster #10), with its emphasis on teaching presence, social presence, and cognitive presence, has been particularly influential in blended learning research (Garrison et al., 1999). Its appearance as a distinct cluster underscores its significance in understanding the dynamics of blended learning environments. The inclusion of terms like \u0026lsquo;deep learning\u0026rsquo; and \u0026lsquo;synchronous teaching model\u0026rsquo; within this cluster suggests ongoing research into how to foster meaningful, collaborative learning experiences in blended settings. The CoI framework provides a valuable lens for understanding the complex interactions that occur in blended learning environments. Teaching presence refers to the design, facilitation, and direction of cognitive and social processes for the purpose of realizing personally meaningful and educationally worthwhile learning outcomes. Social presence is the ability of learners to project their personal characteristics into the community of inquiry, thereby presenting themselves as 'real people.' Cognitive presence is the extent to which learners are able to construct and confirm meaning through sustained reflection and discourse (Garrison et al., 1999). The learning communities cluster (#9), featuring terms such as \u0026lsquo;technology-enhanced learning,\u0026rsquo; \u0026lsquo;undergraduate education,\u0026rsquo; and \u0026lsquo;reflective practice,\u0026rsquo; reflects the growing recognition of social learning theories in blended education. This cluster emphasizes the importance of creating supportive, interactive learning environments that extend beyond the traditional classroom (Wenger, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). The inclusion of \u0026lsquo;digital immigrants\u0026rsquo; and \u0026lsquo;digital natives\u0026rsquo; in this cluster suggests that researchers are considering generational differences in technology use and learning preferences when designing blended learning communities.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eImportant clusters of keywords in BLHE research.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" 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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ecluster ID\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003esize\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003esilhouette\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ecluster names (LLR)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLSI primary\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eLSI secondary\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eLLR\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.903\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eblended learning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eblended learning; collaborative learning;\u003c/p\u003e \u003cp\u003eteaching evaluations; instructional change; online education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eonline learning; student satisfaction; learning strategy; physical education; virtual learning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eblended learning (133.65, 1.0E-4); higher education (68.21, 1.0E-4); flipped classroom (38.68, 1.0E-4); online learning (35.66, 1.0E-4); student engagement (17.75, 1.0E-4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.789\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ecollaborative learning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eblended learning; collaborative learning; continuous assessment; adaptive tests; technology quality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eformative assessment; learning report; formative feedback; teaching bpm; distance learning education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ecollaborative learning (24.22, 1.0E-4); web 2.0 (23.61, 1.0E-4); English for academic purposes (23.36, 1.0E-4); English for specific purposes (18.68, 1.0E-4); bilingual education (18.68, 1.0E-4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.873\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003econtinuance intention\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eblended learning; mobile learning;\u003c/p\u003e \u003cp\u003etechnology adoption; mixed methods; new technologies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003econtinuance intention; academic self-efficacy; intrinsic motivation;\u003c/p\u003e \u003cp\u003emandatory environments; success model\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003econtinuance intention (21.51, 1.0E-4); grounded theory (16.25, 1.0E-4); technology acceptance (16.25, 1.0E-4); utaut (15.3, 1.0E-4); technology acceptance model (12.53, 0.001)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.759\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eself-regulated learning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eblended learning; online learning; social capital; learning strategies; education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eself-regulated learning; blended course designs: academic success; czech republic; self-reported measures\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eself-regulated learning (27.89, 1.0E-4); mixed methods (14.77, 0.001); learning strategies (13.85, 0.001); social network analysis (12.31, 0.001); critical thinking (10.37, 0.005)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.731\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ecurriculum design\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eblended learning: public health; educational modality; work-integrated learning; sustainability assessment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eonline learning; educational technology; hybrid learning; multi-criteria decision; decision making\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ecurriculum design (14.38, 0.001); continuing professional development (14.38, 0.001); online and blended learning (14.38, 0.001); communities of practice (14.37, 0.001); professional development (12.18, 0.001)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.854\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ework-integrated learning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ework-integrated learning; scoping review; learning design; self-directed learning;\u003c/p\u003e \u003cp\u003estudy behaviors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eblended learning; transparency assessment; research methods; descriptive review; work placements\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ework-integrated learning (100.14, 1.0E-4); blended learning (40, 1.0E-4); employability (30.82, 1.0E-4); online learning (17.18, 1.0E-4); work integrated learning (16.01, 1.0E-4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.866\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eteaching/learning strategies\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eblended learning; digital content; hybrid learning; management studies; student-generated media\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003elearning strategies; pedagogical issues; improving classroom teaching; adult learning; digital content\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eteaching learning strategies (37.5, 1.0E-4); pedagogical issues (25.6, 1.0E-4); improving classroom teaching (20.84, 1.0E-4); distributed learning environments (20.33, 1.0E-4); lifelong learning (19.58, 1.0E-4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ehybrid learning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eblended learning; online learning. social science; academic health; information technology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ehybrid learning; engineering education; computer-aided design; linear auto-regression; data mining\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ehybrid learning (30 35, 1.0E-4); digital competence (24.71, 1.0E-4); distance learning (24.49, 1.0E-4); learning design (15.34, 1.0E-4); learning technologies (15.12, 0.001)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.925\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003egame-based learning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBlended learning; game-based learning; advanced classroom technology; interactive tools; traditional learning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eOpen educational resources; advanced classroom applications; learning space design; serious games; didactical innovations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eGame-based learning (41.77, 1.0E-4); flipped learning (41.77, 1.0E-4); learning by-doing (36.33, 1.0E-4); serious games (36.53, 1.0E-4); learning space design (36.53, 1.0E-4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.834\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003elearning communities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eblended learning; reflective practice; digital immigrants; digital natives; digital storytelling\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003etechnology-enhanced learning; undergraduate education༛ gross anatomy education: medical education; task-based language\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003elearning communities (15.39, 1.0E-4); technology-enhanced learning (13.42, 0.001); undergraduate education (13.23, 0.001); community of practice (13.2, 0.001)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.871\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003ecommunity of inquiry\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eblended learning;learning style model༛ learning level; deep learning: synchronous\u003c/p\u003e \u003cp\u003eteaching model\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eteaching presence; social presence; cognitive presence; blended learning\u003c/p\u003e \u003cp\u003econtexts; inquiry framework\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ecommunity of inquiry (25.79, 1.0E-4); teaching presence (25.09, 1.0E-4); social presence (17.17, 1.0E-4); cognitive presence\u003c/p\u003e \u003cp\u003e(12.7, 0.001); adult education (9.84, 0.005)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eClusters related to technological aspects include \u0026lsquo;game-based learning\u0026rsquo; (#8) and elements of \u0026lsquo;continuance intention\u0026rsquo; (#2), which often deals with technology adoption. These clusters reflect the ongoing integration of innovative technologies in blended learning environments. Game-based learning's emergence as a distinct cluster (#8), with terms like \u0026lsquo;serious games,\u0026rsquo; \u0026lsquo;learning by-doing,\u0026rsquo; and \u0026lsquo;learning space design,\u0026rsquo; suggests a growing interest in leveraging gamification and interactive technologies to enhance engagement and learning outcomes in blended settings (Tsay et al., \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). This cluster highlights the potential of game-based approaches to create immersive, motivating learning experiences that complement traditional instructional methods. The integration of game-based learning in blended environments offers several potential benefits. Games could provide immediate feedback, allow for experimentation and failure in safe environments, and often incorporate elements of storytelling and problem-solving that can enhance engagement and knowledge retention, according to Tsay et al., (\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Moreover, the \u0026lsquo;learning by-doing\u0026rsquo; approach inherent in many games aligns well with constructivist learning theories that underpin much of blended learning design (Moreno-Ger et al., \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). The continuance intention cluster (#2), featuring terms such as \u0026lsquo;technology acceptance,\u0026rsquo; \u0026lsquo;UTAUT\u0026rsquo; (Unified Theory of Acceptance and Use of Technology), and \u0026lsquo;grounded theory,\u0026rsquo; indicates researchers' interest in understanding factors that influence the sustained use of blended learning technologies. They are crucial for ensuring the long-term success and adoption of blended learning approaches (Bhattacherjee, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). The presence of \u0026lsquo;grounded theory\u0026rsquo; in this cluster suggests that researchers are employing qualitative, inductive approaches to understand technology acceptance in blended learning contexts. This methodological choice allows for the development of context-specific theories that could capture the nuanced factors influencing technology adoption in diverse educational settings.\u003c/p\u003e \u003cp\u003eClusters focused on design aspects include \u0026lsquo;curriculum design\u0026rsquo; (#4), \u0026lsquo;work-integrated learning\u0026rsquo; (#5), and elements of \u0026lsquo;teaching/learning strategies\u0026rsquo; embedded in other clusters. These clusters highlight the importance of thoughtful design in blended learning implementations. The curriculum design cluster (#4), with terms like \u0026lsquo;continuing professional development,\u0026rsquo; \u0026lsquo;communities of practice,\u0026rsquo; and \u0026lsquo;multi-criteria decision,\u0026rsquo; underscores the need for intentional and pedagogically sound approaches to blended learning. This cluster suggests a focus on designing blended learning experiences that are aligned with professional development needs and foster ongoing learning communities. The inclusion of \u0026lsquo;multi-criteria decision\u0026rsquo; in this cluster is particularly interesting, as it suggests that researchers are exploring complex decision-making processes in curriculum design for blended learning. This could involve balancing various factors such as learning objectives, technological constraints, student preferences, and institutional resources when designing blended curricula. The work-integrated learning cluster (#5), featuring terms such as \u0026lsquo;employability,\u0026rsquo; \u0026lsquo;scoping review,\u0026rsquo; and \u0026lsquo;self-directed learning,\u0026rsquo; suggests a trend towards aligning blended learning with professional and vocational education (Wuxue, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). This cluster highlights the potential of blended approaches to bridge the gap between academic learning and workplace requirements, potentially enhancing students' employability and career readiness. The emphasis on \u0026lsquo;self-directed learning\u0026rsquo; within this cluster aligns well with the demands of many modern workplaces, where employees are often expected to take initiative in their own learning and professional development. Blended learning approaches, by offering flexibility and promoting self-regulation, may be particularly well-suited to preparing students for these workplace expectations.\u003c/p\u003e \u003cp\u003eWhile not appearing as a distinct cluster, assessment and evaluation themes are present within several clusters, particularly in \u0026lsquo;collaborative learning\u0026rsquo; (#1) and \u0026lsquo;curriculum design\u0026rsquo; (#4). Terms like \u0026lsquo;continuous assessment,\u0026rsquo; \u0026lsquo;formative feedback,\u0026rsquo; and \u0026lsquo;adaptive tests\u0026rsquo; within these clusters reflect the ongoing challenges and innovations in assessing student learning in blended environments (Gikandi et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). This cross-cutting theme suggests that researchers have been exploring ways to leverage both online and face-to-face components of blended learning for more effective and diverse assessment strategies. Continuous assessment and formative feedback, in particular, align well with the iterative and interactive nature of many blended learning approaches. These assessment strategies could provide ongoing insights into student progress, allowing for timely interventions and personalized support. The presence of \u0026lsquo;adaptive tests\u0026rsquo; in the curriculum design cluster points to an interest in using technology to create more personalized assessment experiences. Adaptive testing, which adjusts the difficulty or content of questions based on a student's performance, could be particularly powerful in blended learning environments (Barla et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) where data on student performance can be collected and analyzed in real-time.\u003c/p\u003e"},{"header":"4. Discussion and implications for future studies","content":"\u003cp\u003eDiscussion The bibliometric analysis of BLHE research from 2001 to 2024 revealed a field that has undergone significant evolution, characterized by the development of robust theoretical frameworks, methodological diversification, and an increasing focus on practical applications. This study addressed three key research questions, providing insights into the intellectual structure, global diffusion, and critical research features of BLHE.\u003c/p\u003e\n\u003cp\u003eThe document co-citation analysis revealed a clear progression in the intellectual structure of blended learning research of the past more than two decades. The field\u0026apos;s foundation was laid by Garrison and Kanuka\u0026apos;s (2004) seminal work, which introduced the Community of Inquiry (CoI) framework to blended learning contexts. This framework, emphasizing the interplay of cognitive, social, and teaching presence, has become a cornerstone in conceptualizing effective blended learning environments. The enduring influence of this work, evidenced by its high citation count (241), suggested that it successfully captured a fundamental conceptual need in the emerging field of blended learning. The CoI framework\u0026apos;s dominance in blended learning research aligned with broader trends in educational theory that emphasized the social nature of learning. As Garrison and Arbaugh (2007) noted, the CoI framework provided a valuable lens for understanding the complex interactions that occured in blended learning environments\u0026nbsp;(Garrison \u0026amp; Arbaugh, 2007). However, as Rourke and Kanuka (2009) pointed out, there was a need for more research on how the CoI framework translated into measurable learning outcomes, suggesting a potential area for future investigation\u0026nbsp;(Rourke \u0026amp; Kanuka, 2009). The progression of highly cited works demonstrated a clear evolution in the field\u0026apos;s focus. Graham\u0026apos;s (2006) \u0026lsquo;\u003cem\u003eThe Handbook of Blended Learning: Global Perspectives, Local Designs\u003c/em\u003e\u0026rsquo; marked a shift towards contextual considerations in blended learning design. This work bridged the gap between theoretical frameworks and practical implementation, a theme that became increasingly prominent in later works. The emphasis on global perspectives and local designs resonated with calls from researchers like Uzuner (2009) for more cross-cultural studies in online and blended learning environments. Subsequent highly cited works by Garrison and Vaughan (2007), L\u0026oacute;pez-P\u0026eacute;rez et al. (2011), and Graham et al. (2013) demonstrated a progression from theoretical foundations to empirical validation and institutional adoption strategies. This evolution mirrored the typical development pattern of maturing fields of study, as described by Kuhn (1962). in his work on the structure of scientific revolutions. The balanced citation counts across these later works suggested that the field valued theoretical development, practical implementation, and empirical research equally. This holistic approach recognized that effective implementation of blended learning required a combination of strong theoretical grounding, practical know-how, and evidence-based practice.\u003c/p\u003e\n\u003cp\u003eThis analysis examined the implications of the observed publication trends for the global diffusion and adoption of blended learning practices in higher education. This trend alignd with broader patterns of educational technology adoption and the increasing digitalization of higher education\u0026nbsp;(Zawacki-Richter \u0026amp; Latchem, 2018). The slight dip in publications in 2020, followed by a quick rebound in 2021, likely reflected the impact of the COVID-19 pandemic and subsequent renewed interest in blended learning strategies. This observation was consistent with findings from other educational technology research areas, where the pandemic acted as a catalyst for increased interest and adoption of online and blended learning approaches\u0026nbsp;(Ferdig et al., 2020).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe geographic diversity of top institutions, spanning countries such as Australia, Portugal, Spain, and China, indicated that blended learning research is indeed a global endeavor. This diversity was crucial for developing a comprehensive understanding of blended learning, as it allowed for the exploration of cultural and contextual factors that may influence the effectiveness of blended learning approaches\u0026nbsp;(Tarhini et al., 2015). However, the dominance of English-language publications from Western institutions also pointed to potential gaps in the literature, particularly regarding blended learning implementation in other cultural contexts. This observation aligned with concerns raised by Zawacki-Richter and Latchem (2018) about the need for more diverse perspectives in educational technology research. The prominence of conference proceedings among the most productive outlets suggested a field that valued rapid dissemination of ideas and practices. This was congruent with observations by Halverson et al. (2014), who noted the importance of conferences in disseminating emerging educational technology research. The preference for conference proceedings may be particularly beneficial in a fast-evolving area like blended learning, where practitioners and researchers alike benefited from timely access to new insights and best practices. This aligned with observations by Martin et al., (2018), who noted the importance of conferences in disseminating emerging educational technology research. The preference for conference proceedings may be particularly beneficial in a fast-evolving area like blended learning, where practitioners and researchers alike benefit from timely access to new insights and best practices.\u003c/p\u003e\n\u003cp\u003eThe cluster analysis revealed a rich tapestry of research areas within blended learning, providing a nuanced picture of the field\u0026apos;s current focus. The emergence of distinct clusters around foundational concepts, theoretical frameworks, technological integration, curriculum design, and assessment methods reflected the multifaceted nature of blended learning research. The largest cluster, labeled \u0026lsquo;blended learning,\u0026rsquo; encompassed core concepts such as \u0026lsquo;higher education,\u0026rsquo; \u0026lsquo;flipped classroom,\u0026rsquo; and \u0026lsquo;student engagement.\u0026rsquo; The prominence of the \u0026lsquo;flipped classroom\u0026rsquo; within this cluster reflected a growing interest in pedagogical models that leveraged technology to restructure traditional learning environments. As Bergmann and Sams (2012) argued, the flipped classroom model represented a specific implementation of blended learning that aimed to enhance face-to-face interactions by shifting content delivery to online platforms. However, the concentration of research on this particular model raised questions about whether other innovative blended learning approaches were being overlooked. The clusters focused on theoretical frameworks and learning processes, including \u0026lsquo;self-regulated learning,\u0026rsquo; \u0026lsquo;community of inquiry,\u0026rsquo; and \u0026lsquo;learning communities,\u0026rsquo; underscore the field\u0026apos;s strong theoretical grounding. The emergence of self-regulated learning as a distinct cluster resonated with findings from Broadbent and Poon (2015), who highlighted the importance of self-regulation skills in online and blended learning environments. This focus suggested that successful blended learning required students to develop skills in managing their own learning processes, a crucial competency in increasingly flexible and personalized learning environments\u0026nbsp;(Schunk \u0026amp; Zimmerman, 2011). However, the emphasis on self-regulated learning also raised important questions about equity and access in blended learning environments. Students with well-developed self-regulation skills may thrive in these settings, while those who struggled with self-regulation may be at a disadvantage. This concern echoed broader issues of educational equity in digital learning environments, as highlighted by Broadbent and Poon (2015). Future research could explore interventions to support the development of self-regulation skills in blended learning contexts, particularly for students from diverse educational backgrounds. The persistence of the Community of Inquiry (CoI) framework, nearly two decades after its introduction, speaks to its robustness and applicability in understanding the complex interactions that occur in blended learning environments. However, as Rourke and Kanuka (2009) pointed out, there was a need for more research on how the CoI framework translated into measurable learning outcomes. This gap suggests a potential area for future research that could bridge theoretical understanding with practical outcomes.\u003c/p\u003e\n\u003cp\u003eClusters related to technological integration and innovation, such as \u0026lsquo;game-based learning\u0026rsquo; and \u0026lsquo;continuance intention,\u0026rsquo; reflect the ongoing integration of innovative technologies in blended learning environments. The game-based learning cluster, with terms like \u0026lsquo;serious games\u0026rsquo; and \u0026lsquo;learning by-doing,\u0026rsquo; aligns with findings from Dicheva et al. (2015), who identified positive effects of gamification on student engagement and motivation in various educational contexts, including blended learning. However, the enthusiasm for game-based learning and other technological innovations in blended environments should be tempered with critical consideration of their long-term effectiveness and potential drawbacks, as it was stressed by Meoreno-Ger et al. (2008) in his study. The continuance intention cluster, featuring terms such as \u0026lsquo;technology acceptance\u0026rsquo; and \u0026lsquo;UTAUT\u0026rsquo; (Unified Theory of Acceptance and Use of Technology), indicates ongoing interest in understanding the factors that influence the adoption and sustained use of blended learning technologies. This research stream, building on the work of Venkatesh et al. (2003), is crucial for ensuring the long-term success and sustainability of blended learning initiatives. The focus on technology acceptance and continuance intention also highlights a potential blind spot in the field. While understanding the factors that influence adoption is important, there is a risk of technological determinism \u0026ndash; the assumption that technological innovation alone can drive educational improvement. Clusters focused on curriculum design and work-integrated learning highlight the importance of thoughtful design in blended learning implementations. The emergence of work-integrated learning as a distinct cluster suggests a trend towards aligning blended learning with professional and vocational education, reflecting broader trends in higher education towards more career-focused curricula\u0026nbsp;(Bonk \u0026amp; Graham, 2012). While this trend is promising, it also raises questions about the broader purpose of higher education. There is a risk that an overemphasis on vocational skills could come at the expense of critical thinking, creativity, and other transferable skills that are crucial for long-term career success and civic engagement.\u003c/p\u003e\n\u003cp\u003eThe cross-cutting theme of assessment, evident across multiple clusters, reflected the ongoing challenges and innovations in evaluating student learning in blended environments. Terms like \u0026lsquo;continuous assessment,\u0026rsquo; \u0026lsquo;formative feedback,\u0026rsquo; and \u0026lsquo;adaptive tests\u0026rsquo; suggested that researchers have been exploring ways to leverage both online and face-to-face components of blended learning for more effective and diverse assessment strategies. This aligns with the findings of Gikandi et al. (2011), who highlighted the potential of online formative assessment in blended and online learning contexts. However, the integration of these assessment strategies with traditional evaluation methods remains a challenge, particularly in institutional contexts where established assessment practices are deeply entrenched. Despite the rich insights provided by this analysis, several significant gaps and potential areas for future research emerge. The relatively low representation of studies from non-Western contexts suggests a pressing need for more diverse cultural perspectives on blended learning. This gap resonates with calls from researchers like Uzuner (2009) for more cross-cultural studies in online learning environments. Future research could explore how cultural factors influence the design, implementation, and effectiveness of blended learning approaches in different global contexts. Moreover, while the field has made significant progress in understanding the implementation of blended learning, there is still a critical need for more longitudinal studies that examine the long-term impacts on student outcomes and institutional transformation. Most of the highly cited works focus on short-term outcomes or implementation processes, leaving questions about the sustained effects of blended learning initiatives largely unanswered. This gap aligns with observations by Halverson and Graham (2019) about the need for more rigorous, long-term studies of blended learning effectiveness. The analysis also reveals potential methodological gaps in the field. While there is a mix of theoretical, quantitative, and qualitative approaches represented in the highly cited works, there appears to be a lack of large-scale, mixed-methods studies that combine the depth of qualitative insights with the breadth of quantitative data. Future research could benefit from more integrated methodological approaches, as suggested by Creswell and Plano Clark (2017), to provide a more comprehensive understanding of blended learning phenomena. As blended learning continues to evolve, the integration of emerging technologies such as artificial intelligence and virtual reality presents both opportunities and challenges. While these technologies have the potential to significantly reshape blended learning practices, their integration must be approached thoughtfully, with careful consideration of both pedagogical implications and ethical concerns.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eImplications for future studies.\u003c/strong\u003e Based on the discussion, two critical issues that deserve more consideration in future studies on BLHE. Future research should focus on exploring how cultural factors influence the design, implementation, and effectiveness of blended learning approaches in diverse global contexts. The current literature is dominated by Western perspectives, leaving a significant gap in our understanding of how blended learning can be effectively adapted and implemented in non-Western educational systems. This line of inquiry is crucial as higher education becomes increasingly globalized. As Shadiev et al. (2024) points out, there is a pressing need for more cross-cultural studies in online and blended learning environments. Such research could investigate how different cultural values, learning styles, and educational traditions impact the acceptance and effectiveness of blended learning models. For instance, studies could explore how the Community of Inquiry (CoI) framework, which has been primarily developed and tested in Western contexts, translates to educational settings in Asia, Africa, or the Middle East. This research could build on the work of Garrison and Arbaugh (2007) but extend it to diverse cultural contexts, potentially leading to refinements or adaptations of the framework. Moreover, as Nistor et al. (2013) demonstrated in their cross-cultural examination of educational technology acceptance, factors influencing technology adoption can vary significantly across cultures. Future studies could extend this work to blended learning specifically, examining how cultural factors impact not just technology acceptance, but also engagement with different aspects of blended learning, such as online discussions, collaborative projects, or flipped classroom approaches.\u003c/p\u003e\n\u003cp\u003eThere is a critical need for more longitudinal studies that examine the long-term impacts of blended learning on student outcomes, skill development, and institutional transformation. As Versteijlen et al. (2023) observed, much of the existing research focuses on short-term outcomes or implementation processes, leaving questions about the sustained effects of blended learning initiatives largely unanswered. Future research should aim to track cohorts of students through blended learning programs and into their early career stages, examining not only academic outcomes but also the development of lifelong learning skills, digital literacy, and career readiness. Such studies could build on the work of Ingkavara et al. (2022) on self-regulated learning in online environments, extending it to long-term outcomes in blended learning contexts. Additionally, research should investigate the institutional factors that contribute to the sustainability of blended learning initiatives over time. This could involve examining how institutions successfully embed blended learning into their long-term strategic plans, adapt to evolving technologies, and maintain faculty engagement and development. The framework for institutional adoption proposed by Graham et al. (2013) could serve as a starting point for such investigations, but with a focus on long-term sustainability rather than initial adoption(Graham et al., 2013). Furthermore, as the educational technology landscape continues to evolve rapidly, longitudinal studies could explore how institutions successfully integrate emerging technologies like artificial intelligence and virtual reality into their blended learning models over time. This research could build on the work of Zawacki-Richter et al. (2019) on AI in higher education(Zawacki-Richter et al., 2019), but with a specific focus on its long-term integration and impact in blended learning environments. By addressing these two critical areas, future research can contribute to a more comprehensive and nuanced understanding of BLHE, informing both policy and practice in an increasingly diverse and technology-driven educational landscape.\u003c/p\u003e"},{"header":"5. Conclusion ","content":"\u003cp\u003eBlended learning has emerged as a significant area of research in higher education over the past two decades. This study aimed to systematically review the literature on BLHE using bibliometric tools, specifically CiteSpace. Our analysis of 2,125 publications from the Web of Science Core Collection spanning from 2001 to 2024 provides a comprehensive overview of the field's evolution, intellectual structure, and emerging trends. The descriptive analysis revealed a substantial increase in publications from 2013 onwards, with peak productivity in 2018 and 2019, indicating growing academic interest in blended learning across various disciplines. The slight dip in 2020 followed by a rebound in 2021 reflects the impact of the COVID-19 pandemic and the subsequent renewed focus on blended learning strategies.\u0026nbsp;Our findings highlight the dominance of conference proceedings in disseminating blended learning research, with\u0026nbsp;Edulearn Proceedings, Inted Proceedings, and Iceri Proceedings leading in publication output. This trend underscores the field's dynamic nature and the need for rapid knowledge exchange, as noted by Martin et al. (2020) in their recent review of educational technology research dissemination. Garrison and Kanuka's (2004) Community of Inquiry framework emerges as particularly influential in shaping blended learning research. The evolution of highly cited works demonstrates a clear progression from theoretical foundations to practical implementation strategies and empirical validation, reflecting the field's maturation. The cluster analysis identified 11 distinct research areas, including blended learning foundations, self-regulated learning, game-based learning, and work-integrated learning. These clusters highlighted the multifaceted nature of blended learning research and its integration with various pedagogical approaches and technologies. The prominence of self-regulated learning and technology acceptance models in these clusters resonated with recent findings by Junaštíková (2024) on the importance of learner autonomy and technology integration in successful blended learning implementations.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOur analysis also revealed several gaps and potential areas for future research. Firstly, there is a pressing need for more diverse cultural perspectives on blended learning, particularly from non-Western contexts. As Serradell-Lopez et al. (2012) argued, understanding the cultural dimensions of blended learning is crucial for its effective global implementation(Serradell-Lopez et al., 2012). Secondly, longitudinal studies examining the long-term impacts of blended learning on student outcomes and institutional transformation are scarce(Ashraf et al., 2021). Future research should address this gap to provide insights into the sustained effects of blended learning initiatives. Furthermore, the integration of emerging technologies such as artificial intelligence and virtual reality in blended learning environments presents both opportunities and challenges that warrant further investigation(Zawacki-Richter et al., 2019). Additionally, as blended learning continues to evolve, research on innovative assessment strategies that leverage both online and face-to-face components will be crucial(Buhl-Wiggers et al., 2023). While this study aimed to provide a comprehensive review of blended learning research in higher education, it has some limitations. The analysis was limited to publications in the Web of Science Core Collection, potentially excluding relevant studies from other databases. Additionally, the rapid pace of technological advancements and the recent impact of the COVID-19 pandemic may not be fully reflected in the analyzed literature due to publication time lags.\u003c/p\u003e\n\u003cp\u003eDespite these limitations, this bibliometric analysis offers a valuable overview of global research on BLHE. It provides researchers, educators, and policymakers with insights into the field's intellectual structure, emerging trends, and future directions. As blended learning continues to play a crucial role in shaping the future of higher education, addressing the identified research gaps and embracing new challenges will be essential for developing more effective, inclusive, and transformative learning experiences. The findings of this review have significant implications for both theory and practice in blended learning. They highlight the need for more integrated theoretical frameworks that can account for the complex interplay of pedagogical, technological, and institutional factors in blended learning environments. Practically, they underscore the importance of thoughtful design, ongoing assessment, and institutional support in successful blended learning implementations. As higher education continues to navigate the challenges of the digital age, the insights from this study can guide the development of more robust and effective blended learning strategies.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eauthor A conceptualized the study, conducted the bibliometric analysis using CiteSpace, and wrote the main manuscript text. author B contributed to the methodology design, assisted with data interpretation, and reviewed the results. Both author A and author B conducted the literature review, discussed the findings, and critically revised the manuscript. All authors reviewed and approved the final version of the manuscript.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eData is provided within the manuscript or supplementary information files\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eAdebayo, O., Iwu-James, J., Olawoyin, O., Fagbohun, O., Esse, U., Yusuf, F., Segun-Adeniran, C., Izuagbe, R., \u0026amp; Owolabi, S. (2019). \u003cem\u003eBLENDED LEARNING IN HIGHER EDUCATION: IMPLICATION AND STRATEGIES FOR ACADEMIC LIBRARY SUPPORT\u003c/em\u003e. 7210\u0026ndash;7217. https://doi.org/10.21125/inted.2019.1746\u003c/li\u003e\n \u003cli\u003eAhmad, J. (2021). 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Bibliometric Methods in Management and Organization. \u003cem\u003eOrganizational Research Methods\u003c/em\u003e, \u003cem\u003e18\u003c/em\u003e(3), 429\u0026ndash;472. https://doi.org/10.1177/1094428114562629\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-5302006/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5302006/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study presents a comprehensive bibliometric analysis of blended learning in higher education (BLHE) research from 2001 to 2024. Using CiteSpace, we analyzed 2,125 publications from the Web of Science Core Collection to map the intellectual structure and evolution of the field. Our findings reveal a significant increase in BLHE research from 2013 onwards, with peak productivity in 2018 and 2019. Conference proceedings emerged as dominant publication venues, reflecting the field's dynamic nature. Document co-citation analysis identified influential works, with Garrison and Kanuka's (2004) Community of Inquiry framework emerging as particularly impactful. Cluster analysis revealed 11 distinct research areas, including blended learning foundations, self-regulated learning, game-based learning, and work-integrated learning. These clusters highlight the multifaceted nature of BLHE research and its integration with various pedagogical approaches and technologies. Our analysis also uncovered several research gaps, including a need for more diverse cultural perspectives, longitudinal studies examining long-term impacts, and research on innovative assessment strategies in blended environments. While the field has made significant progress in understanding BLHE implementation, challenges remain in addressing cultural diversity and long-term effectiveness. This study provides researchers, educators, and policymakers with insights into the field's intellectual structure, emerging trends, and future directions. As blended learning continues to shape higher education, addressing identified research gaps will be crucial for developing more effective, inclusive, and transformative learning experiences.\u003c/p\u003e","manuscriptTitle":"A Bibliometric Study of Blended Learning in Higher Education (2001- 2024)","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-11-04 05:09:09","doi":"10.21203/rs.3.rs-5302006/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"804e1f6d-e0a4-4317-9732-77c0f1d337f1","owner":[],"postedDate":"November 4th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":39195882,"name":"Social science/Education"},{"id":39195883,"name":"Social science/Science technology and society"}],"tags":[],"updatedAt":"2024-12-03T09:24:34+00:00","versionOfRecord":[],"versionCreatedAt":"2024-11-04 05:09:09","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5302006","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5302006","identity":"rs-5302006","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}