Using Learning Analytics and Student Perceptions to Explore Student Interactions in an Online Construction Management Course
| Autor: | Paige West, Frederick Paige, Walter Lee, Natasha Watts, Glenda Scales |
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| Rok vydání: | 2022 |
| Předmět: | |
| Zdroj: | Journal of Civil Engineering Education. 148 |
| ISSN: | 2643-9115 2643-9107 |
| DOI: | 10.1061/(asce)ei.2643-9115.0000066 |
| Popis: | The expansion of online learning in higher education has both contributed to researchers exploring innovative ways to develop learning environments and created challenges in identifying student interactions with course material. Learning analytics is an emerging field that can identify student interactions and help make data-informed course design decisions. In this case study, learning analytics were collected from 113 students in three course sections of an online construction management course in the Canvas learning management system (LMS). Surveys were used to collect students’ perceptions of the course design and materials to correlate with the students’ interactions with the course materials. The survey findings showed the students found watching the lecture videos and reading the lecture slides to be the most helpful aspects of the course materials in their learning. Findings from the learning analytics showed that students’ interactions with the course decreased after the midterm exam. Based on the results, online course instructors can leverage their learning analytics to understand student interactions and make data-informed course design changes to improve their online learning environments. Published version |
| Databáze: | OpenAIRE |
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