The effects of applying learning analytics via decision trees to students’ performance in a physical science course

• In Event: RTD - Research Methods: Learning Analytics and Content Analysis [TC]

Short Description

With the abundance of electronic data available to educational researchers, new opportunities for research have emerged, combining data mining with traditional research methods. In our study we used a learning analytics tool called “decision trees” to explore students’ performance in a physical science course. The results showed that the identified classification model was 81% correct in predicting total grades of students based their scores of homework, tests, labs, and final exam.

Authors

• Aklilu Maasho, University of Memphis

• Trey Martindale, University of Memphis