Clustering blended learning courses by online behavior data: A case study in a Korean higher education institute

Abstract Blended learning (BL) is recognized as one of the major trends in higher education today. To identify how BL has been actually adopted, this study employed a data-driven approach instead of model-driven methods. Latent Class Analysis method as a clustering approach of educational data mining was employed to extract common activity features of 612 courses in a large private university located in South Korea by using online behavior data tracked from Learning Management System and institution's course database. Four unique subtypes were identified. Approximately 50% of the courses manifested inactive utilization of LMS or immature stage of blended learning implementation, which is labeled as Type I. Other subtypes included Type C — Communication or Collaboration (24.3%), Type D — Delivery or Discussion (18.0%), and Type S — Sharing or Submission (7.2%). We discussed the implications of BL based on data-driven decisions to provide strategic institutional initiatives.

[1]  John P. Campbell,et al.  Academic Analytics: A New Tool for a New Era. , 2007 .

[2]  M. Patton,et al.  Qualitative evaluation and research methods , 1992 .

[3]  Mark Nichols,et al.  Institutional perspectives: The challenges of e-learning diffusion , 2008, Br. J. Educ. Technol..

[4]  Mimi Recker,et al.  Teaching Analytics: A Clustering and Triangulation Study of Digital Library User Data , 2012, J. Educ. Technol. Soc..

[5]  Tarsem Singh Cooner,et al.  Creating opportunities for students in large cohorts to reflect in and on practice: Lessons learnt from a formative evaluation of students' experiences of a technology-enhanced blended learning design , 2010, Br. J. Educ. Technol..

[6]  George Siemens,et al.  Penetrating the fog: analytics in learning and education , 2014 .

[7]  Ana Carvalho,et al.  Students' perceptions of Blackboard and Moodle in a Portuguese university , 2011, Br. J. Educ. Technol..

[8]  N. Vaughan.  A blended community of inquiry approach: Linking student engagement and course redesign , 2010, Internet High. Educ..

[9]  Charles R. Graham,et al.  A framework for institutional adoption and implementation of blended learning in higher education , 2013, Internet High. Educ..

[10]  Brian H. Cameron.  The effectiveness of simulation in a hybrid and online networking course , 2003 .

[11]  Françoise Blin,et al.  Why hasn't technology disrupted academics' teaching practices Understanding resistance to change through the lens of activity theory , 2008, Comput. Educ..

[12]  Agathe Merceron,et al.  A Data Model to Ease Analysis and Mining of Educational Data , 2010, EDM.

[13]  B. Muthén,et al.  Integrating person-centered and variable-centered analyses: growth mixture modeling with latent trajectory classes. , 2000, Alcoholism, clinical and experimental research.

[14]  Charles R. Graham,et al.  A thematic analysis of the most highly cited scholarship in the first decade of blended learning research , 2014, Internet High. Educ..

[15]  C. Dziuban,et al.  A time‐based blended learning model , 2011 .

[16]  Roisin Donnelly,et al.  Harmonizing technology with interaction in blended problem-based learning , 2010, Comput. Educ..

[17]  Bengt Muthén,et al.  Statistical and substantive checking in growth mixture modeling: comment on Bauer and Curran (2003). , 2003, Psychological methods.

[18]  D. Garrison,et al.  Institutional change and leadership associated with blended learning innovation: Two case studies , 2013, Internet High. Educ..

[19]  D. Garrison,et al.  Blended learning: Uncovering its transformative potential in higher education , 2004, Internet High. Educ..

[20]  Embry-Riddle Aeronautical,et al.  The Flipped Classroom: A Survey of the Research , 2013 .

[21]  Paul Baepler,et al.  Academic Analytics and Data Mining in Higher Education , 2010 .

[22]  Il-Hyun Jo,et al.  "Need Analysis for Learning Analytics Dashboard in LMS: Applying Activity Theory as an Analytic and design Tool" , 2014 .

[23]  Patti Shank.  The online learning idea book : 95 proven ways to enhance technology-based and blended learning , 2007 .

[24]  Kimberly E. Arnold.  Signals: Applying Academic Analytics. , 2010 .

[25]  Bruce W. Tuckman.  Evaluating ADAPT: a hybrid instructional model combining Web-based and classroom components , 2002, Comput. Educ..

[26]  Christian Geiser,et al.  Data Analysis with Mplus , 2012 .

[27]  Gail Salaway,et al.  The ECAR Study of Undergraduate Students and Information Technology, 2008 , 2007 .

[28]  Sally Beisser,et al.  Hybrid Online Coursework to Enhance Technology Competencies of School Principals , 2002 .

[29]  Joanna Poon,et al.  Blended Learning: An Institutional Approach for Enhancing Students' Learning Experiences , 2013 .

[30]  E. Rogers.  Diffusion of Innovations , 1962 .

[31]  Harvey Singh,et al.  Building Effective Blended Learning Programs , 2021, Challenges and Opportunities for the Global Implementation of E-Learning Frameworks.

[32]  Jon Young,et al.  Implementing Blended Learning: Policy Implications for Universities , 2010 .

[33]  Charles R. Graham,et al.  Blended learning in higher education: Institutional adoption and implementation , 2014, Comput. Educ..

[34]  D. W. Zimmerman.  A Note on the Influence of Outliers on Parametric and Nonparametric Tests , 1994 .