Revealing Impact Factors on Student Engagement: Learning Analytics Adoption in Online and Blended Courses in Higher Education
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| Title: | Revealing Impact Factors on Student Engagement: Learning Analytics Adoption in Online and Blended Courses in Higher Education |
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| Authors: | Fan, Si (ORCID |
| Source: | Education Sciences. 2021 11. |
| Availability: | MDPI AG. Klybeckstrasse 64, 4057 Basel, Switzerland. e-mail: education@mdpi.com; e-mail: indexing@mdpi.com; Web site: https://www.mdpi.com/journal/education |
| Peer Reviewed: | Y |
| Page Count: | 17 |
| Publication Date: | 2021 |
| Document Type: | Journal Articles Reports - Research |
| Education Level: | Higher Education Postsecondary Education |
| Descriptors: | Learner Engagement, Learning Analytics, Integrated Learning Systems, Adoption (Ideas), Online Courses, Blended Learning, Discussion Groups, Course Content, Behavior Patterns, Teacher Participation, Foreign Countries, College Students |
| Geographic Terms: | Australia |
| ISSN: | 2227-7102 |
| Abstract: | This study aimed to identify factors influencing student engagement in online and blended courses at one Australian regional university. It applied a data science approach to learning and teaching data gathered from the learning management system used at this university. Data were collected and analysed from 23 subjects, spanning over 5500 student enrolments and 406 lecturer and tutor roles, over a five-year period. Based on a theoretical framework adapted from Community of Inquiry (CoI) framework by Garrison et al. (2000), the data were segregated into three groups for analysis: Student Engagement, Course Content and Teacher Input. The data analysis revealed a positive correlation between Student Engagement and Teacher Input, and interestingly, a negative correlation between Student Engagement and Course Content when a certain threshold was exceeded. The findings of the study offer useful suggestions for future course design, and pedagogical approaches teachers can adopt to foster student engagement. |
| Abstractor: | As Provided |
| Entry Date: | 2021 |
| Accession Number: | EJ1317965 |
| Database: | ERIC |
| Abstract: | This study aimed to identify factors influencing student engagement in online and blended courses at one Australian regional university. It applied a data science approach to learning and teaching data gathered from the learning management system used at this university. Data were collected and analysed from 23 subjects, spanning over 5500 student enrolments and 406 lecturer and tutor roles, over a five-year period. Based on a theoretical framework adapted from Community of Inquiry (CoI) framework by Garrison et al. (2000), the data were segregated into three groups for analysis: Student Engagement, Course Content and Teacher Input. The data analysis revealed a positive correlation between Student Engagement and Teacher Input, and interestingly, a negative correlation between Student Engagement and Course Content when a certain threshold was exceeded. The findings of the study offer useful suggestions for future course design, and pedagogical approaches teachers can adopt to foster student engagement. |
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| ISSN: | 2227-7102 |
