Location
Hilton Hawaiian Village, Honolulu, Hawaii
Event Website
https://hicss.hawaii.edu/
Start Date
3-1-2024 12:00 AM
End Date
6-1-2024 12:00 AM
Description
The field of education has the potential to better facilitate student learning by employing educational recommender systems that adapt the learning process to the needs of individual learners. There is a lack of research that ties educational theory to the design and implementation of these systems. In this research, the design science methodology is employed to advocate for an educational recommender framework with a theoretical base in self-regulated learning. This paper focuses on the qualitative evaluation of this approach to gain insights on students’ perceptions of the resulting recommender when deployed to assist student studying for an upcoming exam. Student perceptions are analyzed to obtain design themes that serve to aid future researchers and practitioners in the design of these systems.
Recommended Citation
Mcnett, Alicia and Noteboom, Cherie, "Something for Every Kind of Learner: Students' Perceptions of an Educational Recommender Study Tool" (2024). Hawaii International Conference on System Sciences 2024 (HICSS-57). 2.
https://aisel.aisnet.org/hicss-57/da/learning_analytics/2
Something for Every Kind of Learner: Students' Perceptions of an Educational Recommender Study Tool
Hilton Hawaiian Village, Honolulu, Hawaii
The field of education has the potential to better facilitate student learning by employing educational recommender systems that adapt the learning process to the needs of individual learners. There is a lack of research that ties educational theory to the design and implementation of these systems. In this research, the design science methodology is employed to advocate for an educational recommender framework with a theoretical base in self-regulated learning. This paper focuses on the qualitative evaluation of this approach to gain insights on students’ perceptions of the resulting recommender when deployed to assist student studying for an upcoming exam. Student perceptions are analyzed to obtain design themes that serve to aid future researchers and practitioners in the design of these systems.
https://aisel.aisnet.org/hicss-57/da/learning_analytics/2