| How Learning Analytics Measures and Supports Students’ Self-Regulative Learning in Virtual Classes: A Qualitative Study |
| کد مقاله : 1101-CNF |
| نویسندگان |
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مکرمه بیات *1، محمد داودی2 1دانشکده زبانهای خارجی . دانشگاه حکیم سبزواری 2دانشیار و عضو هیات علمی گروه زبان انگلیسی- دانشگاه سبزوار |
| چکیده مقاله |
| Virtual learning is accompanied by different challenges and motives for EFL students. Learning analytics can measures the state of self-regulative learning by improving the learning experience. Thus, the present study tried to investigate this connection regarding the students’ academic performance with a socio-cognitive view of SRL in Iran. The data collection process was started with video-recording the virtual classes, using learners’ reflective journals, and administering stimulated recall interviews. We used transitory graphs and social network analysis for analyzing LA effectiveness as well. Based on the obtained results, learning analytics can foster students’ improved experienced of learning with further opportunities for searching, discovering and learning. It could also provide detailed analytics about the students’ progress for teachers and educational administrators. LA can suggest more recommendations for learners to regulate their learning process in a more effective and personalized way. Therefore, further open windows for learners’ progress and effective teaching experience can be obtained. |
| کلیدواژه ها |
| learning analytics, self-regulative learning, content analysis, virtual classes |
| وضعیت: چکیده برای ارائه به صورت پوستر پذیرفته شده است |