Incorporating student population differences for effective online education: A content-based review and integrative model. (September 2019)

• Record Type: Journal Article
• Authors: Money, William H.; Dean, Benjamin P.
• Is Part Of: Computers & education. Volume 138(2019)
• Page Start: 57
• Page End: 82
• Publication Date: 2019-09
• Subjects: Online learning -- Online education -- E-Learning -- Student population -- Content-based review; Education -- Data processing -- Periodicals; Education -- Periodicals; Computers -- Periodicals; Computer-Assisted Instruction -- Periodicals; Éducation -- Informatique -- Périodiques; Electronic journals; 370.285
• DOI: 10.1016/j.compedu.2019.03.013
• Languages: English
• ISSNs: 0360-1315

Abstract

Abstract: The present study reviews and analyzes recent literature relevant to learning online in higher education. This study applied a content-based method for collecting and evaluating recently published studies relating to populations of students engaged in formal online programs and courses. Based on our findings, we identified key descriptors and processes that prove essential for defining online student populations and understanding their differences. This study offers a new conceptual model that consolidates certain prior typologies and frameworks of online learning. The model integrates key components and major processes derived from our study's findings. Our model thus synthesizes and classifies the major categories of antecedents and processes, and suggests relationships that directly or indirectly influence outcomes. The model also provides an integrated framework by which educators and institutions may develop better strategies and approaches for designing, developing, and delivering online education. This study and its model thus advance theory and contribute to educational practice and research in online learning. The study encourages more research specifically on student populations engaged in online learning. Our framework orients future studies that can generate more consistent, coherent data on antecedents of student populations and how population differences interrelate with processes to impact online learning outcomes. Highlights: Differences among student populations can impact online delivery effectiveness and learning outcomes in higher education. Broad discontinuities of concepts and crucial gaps in data emerge from studies describing students in online learning. This study consolidates concepts and findings to suggest online approaches for enhancing educational practice and research. A new model categorizes and integrates key components, processes, and relationships that affect online learning outcomes. Student antecedents interact directly with internal processes and indirectly with external influences that impact outcomes.