{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,8,29]],"date-time":"2024-08-29T00:29:59Z","timestamp":1724891399074},"reference-count":0,"publisher":"Asia-Pacific Society for Computers in Education","license":[{"start":{"date-parts":[[2024,8,28]],"date-time":"2024-08-28T00:00:00Z","timestamp":1724803200000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["RPTEL"],"abstract":"This study investigated the transitions in behavioral patterns of students participating in online learning throughout a semester. We analyzed the page view behavior of 283 students enrolled in a course designed to enhance online readiness at a Midwestern university. Utilizing K-means cluster analysis, we tracked page view frequency across various tasks, including assignments, overviews, and reading resources. Our findings indicate a decline in page view frequency for all tasks. Four distinct clusters were identified: active, passive, assignment-oriented, and overview-oriented groups. A notable shift was observed with the majority of students transitioning to the passive group in the second half of the semester. Examining the factors influencing this shift, we employed motivation constructs from Self-Determination Theory (SDT) and measures of cognitive engagement. The results revealed that deep learning strategies and identified motivation positively correlate with the maintenance of active and engaged behaviors. Conversely, shallow learning strategies are associated with decreased active engagement and a focus on specific tasks. External motivation served as a predicting factor for remaining passivity. These insights contribute to understanding the dynamics of student engagement in online learning environment.<\/jats:p>","DOI":"10.58459\/rptel.2025.20026","type":"journal-article","created":{"date-parts":[[2024,8,28]],"date-time":"2024-08-28T01:08:02Z","timestamp":1724807282000},"page":"026","source":"Crossref","is-referenced-by-count":0,"title":["The transition patterns of learners\u2019 behavior and the association with motivation and cognitive engagement in online learning"],"prefix":"10.58459","volume":"20","author":[{"given":"Jingwen","family":"He","sequence":"first","affiliation":[]},{"given":"Zilu","family":"Jiang","sequence":"additional","affiliation":[]},{"given":"Zilong","family":"Pan","sequence":"additional","affiliation":[]},{"given":"Qiwei","family":"Men","sequence":"additional","affiliation":[]},{"given":"Kui","family":"Xie","sequence":"additional","affiliation":[]}],"member":"37131","published-online":{"date-parts":[[2024,8,28]]},"container-title":["Research and Practice in Technology Enhanced Learning"],"original-title":[],"link":[{"URL":"https:\/\/rptel.apsce.net\/index.php\/RPTEL\/article\/download\/2025-20026\/2025-20026","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/rptel.apsce.net\/index.php\/RPTEL\/article\/download\/2025-20026\/2025-20026","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,28]],"date-time":"2024-08-28T01:08:03Z","timestamp":1724807283000},"score":1,"resource":{"primary":{"URL":"https:\/\/rptel.apsce.net\/index.php\/RPTEL\/article\/view\/2025-20026"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,8,28]]},"references-count":0,"URL":"https:\/\/doi.org\/10.58459\/rptel.2025.20026","relation":{},"ISSN":["1793-7078"],"issn-type":[{"value":"1793-7078","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,8,28]]}}}