Performance increases in mathematics during COVID-19 pandemic distance learning in Austria: Evidence from an intelligent tutoring system for mathematics

Student course grade prediction using the random forest algorithm: Analysis of predictors' importance

BACKGROUND

Universities need to find strategies for improving student retention rates. Predicting student academic performance enables institutions to identify underachievers and take appropriate actions to increase student completion and lower dropout rates.

METHOD

In this work, we proposed a model based on random forest methodology to predict students' course performance using seven input predictors and find their relative importance in determining the course grade. Seven predictors were derived from transcripts and recorded data from 650 undergraduate computing students.

RESULTS

Our findings indicate that grade point average and high school score were the two most significant predictors of a course grade. The course category and class attendance percentage have equal importance. Course delivery mode does not have a significant effect.

CONCLUSION

Our findings show that courses students at risk find challenging can be identified, and appropriate actions, procedures, and policies can be taken.

Undergraduate Skills Training in Pandemic Times: Where Is the Future of Medical Education?

BACKGROUND

The COVID-19 pandemic forced medical programs to rapidly switch to remote teaching from scratch, impacting hands-on skills training. This study compared the efficacy of a hybrid online format to a regular in-person session for a mandatory surgical skills class.

METHODS

Third-year undergraduate medical students attending the surgical skills class in the winter semester of 2020/21 at the Medical University of Graz were randomly assigned to either the hybrid or in-person class, depending on their course schedule and government regulations. The hybrid class involved online videos, one-on-one peer tutoring, and an Objective Structured Clinical Examination (OSCE). Pre- and post-class self-assessments were conducted to evaluate their theoretical and practical knowledge of a single interrupted suture.

RESULTS

The study included 85 students in the regular in-person class and 50 in the hybrid class. A pre-class assessment revealed higher self-assessments in the hybrid class for theoretical and practical knowledge, but a post-class assessment showed no significant difference. The advantages and disadvantages of both modalities were identified, providing valuable insights for future curriculum development.

CONCLUSIONS

Both teaching modes were effective for undergraduate surgical skills training. This study recommends implementing positive aspects of both the hybrid and in-person formats while recognizing their respective limitations.