How learning analytics can early predict under-achieving students in a blended medical education course.

@article{Saqr2017HowLA,
  title={How learning analytics can early predict under-achieving students in a blended medical education course.},
  author={Mohammed Saqr and Uno G. H. Fors and Matti Tedre},
  journal={Medical teacher},
  year={2017},
  volume={39 7},
  pages={
          757-767
        }
}
AIM Learning analytics (LA) is an emerging discipline that aims at analyzing students' online data in order to improve the learning process and optimize learning environments. It has yet un-explored potential in the field of medical education, which can be particularly helpful in the early prediction and identification of under-achieving students. The aim of this study was to identify quantitative markers collected from students' online activities that may correlate with students' final… CONTINUE READING
Highly Cited
This paper has 19 citations. REVIEW CITATIONS

From This Paper

Topics from this paper.

Citations

Publications citing this paper.
Showing 1-9 of 9 extracted citations

Identifying at-risk students in online learning by analysing learning behaviour: A systematic review

2017 IEEE Conference on Big Data and Analytics (ICBDA) • 2017
View 3 Excerpts
Highly Influenced

Similar Papers

Loading similar papers…