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This study examines how e-learning course structure relates to learner autonomy, prior experience, background knowledge, and both student–student and student–instructor dialogue, and proposes solutions using transactional distance theory. 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Autonomy, and  \nDialogue  \nHassan Abuhassna  \nFaculty of Social Sciences & Humanities, School of Education, Universiti Teknologi Malaysia, 81310, UTM  \nSkudai, Johor, Malaysia  \nORCID: 0000-0002-5774-3652  \nAbdelsalam H. Busalim  \nIrish Institute of Digital Business, DCU Business School, Dublin City University, Dublin, Ireland  \nORCID: 0000-0001-5826-8593  \nBabakura Mamman  \nFaculty of Education, University of Maiduguri, P. M. B. 1069, Maiduguri, Borno State Nigeria  \nORCID: 0000-0001-9055-1006  \nNoraffandy Yahaya  \nFaculty of Social Sciences & Humanities, School of Education, Universiti Teknologi Malaysia, 81310, UTM  \nSkudai, Johor, Malaysia  \nORCID: 0000-0002-7952-5461  \nMegat Aman Zahiri Megat Zakaria  \nFaculty of Social Sciences & Humanities, School of Education, Universiti Teknologi Malaysia, 81310, UTM  \nSkudai, Johor, Malaysia  \nORCID: 0000-0001-8223-8124  \nQusay Al-Maatouk  \nSchool of Digital, Technologies and Arts, Staffordshire University, Stoke on Trent, United Kingdom  \nORCID: 0000-0003-4654-9464  \nFareed Awae  \nFaculty of Social Sciences & Humanities, School of Education, Universiti Teknologi Malaysia, 81310, UTM  \nSkudai, Johor, Malaysia  \nORCID: 0000-0001-9121-5020  \nReceived: 28 May 2021 Accepted: 11 Oct 2021  \nAbstract  \nBackground: E-learning is increasingly becoming a preference in higher education institutions worldwide;  \nthis is intended to assist educational institutions in achieving objectives to meet the proportion of individuals with their educational opportunities. Nevertheless, instructors and students frequently have concerns with their capacity to succeed in E-learning environments.  \nObjectives: This study aimed to presents common eLearning challenges in regard to e-learning courses structure and its relations to various factors, for instance; students’ autonomy, prior knowledge and experience, students- students dialogue, and students- instructor dialogue, and proposes solutions to these challenges based on the transactional distance theory. Moreover, this study presents evidence from  \nMalaysian higher institutions based on theoretical models for e-learning course structure and its relations to the factors mentioned above.  \nMethods: Data have been collected from 680 university learners all over Malaysia. Data were then examined using exploratory factor analysis, confirmatory factor analysis, and structural equation modelling employing Smart PLS 3.0 software.  \nResults and conclusion: Research findings indicated that e-learning course structure was affected by all dimensions of overall path analysis findings: student autonomy, students background, student-instructor dialogue, and student-student dialogue. However, the e-learning course structure showed insignificant with students’ prior experience.  \nImplications: Implications for universities are discussed accordingly. Such findings provide vital support to the integrative association among collaborative control (CC) and transactional distance theory (TDT) regarding e-learning environments experience, which might support universities administrators in the higher education industry to implement, plan and evaluate online learning platforms applications in their institutions.  \nKeywords: e-learning courses structure, e-learning student background, e-learning student autonomy, elearning dialogue  \nINTRODUCTION  \nE-learning offers access to higher education institutions to a wide variety of students. Including face-to-face learners on campus, students who are working; thus, looking for opportunities to pursue their degree or post-degree through their working experience to be able to switch their career path, individuals who are looking for a flexible time scheduling possibility, those who choose not to take part in face-to-face environments, and finally those who have abnormal circumstances, for instance, nowadays COVID-19 ou","cbCailBCKt9t53r4","https://ap.wps.com/l/cbCailBCKt9t53r4","pdf",563962,23,"English","# Abstract\n## Background\n## Objectives\n## Methods\n## Results and conclusion\n## Implications\n# Introduction\n## E-learning access and benefits\n## Collaboration tools and implementation challenges","[{\"question\":\"What factors does the study investigate regarding e-learning course structure?\",\"answer\":\"It examines relationships with students’ autonomy, prior knowledge/experience, student background, and dialogue both between students and between students and instructors.\"},{\"question\":\"How were the study data collected and analyzed?\",\"answer\":\"Data were collected from 680 university learners across Malaysia, then analyzed using exploratory factor analysis, confirmatory factor analysis, and structural equation modeling with Smart PLS 3.0.\"},{\"question\":\"What was the key finding about prior experience?\",\"answer\":\"E-learning course structure was influenced by autonomy, student background, and student–instructor and student–student dialogue, while the link with students’ prior experience was insignificant.\"}]","From Student’s Experience: Does E-learning Course Structure Influenced by learner’s Prior Experience, Background Knowledge, Autonomy, and Dialogue | PDF",1792090064,58]