Exploring language needs of college transfer students with learning analytics: Towards a more equitable experience

Exploring language needs of college transfer students with learning analytics: Towards a more equitable experience

• Foung, Dennis The University of British Columbia
• Chen, Julia The Hong Kong Polytechnic University
• Cheung, Kin The Hong Kong Polytechnic University

International Journal of Educational Technology in Higher Education, 20, 2023

Springer

2023

• N Students & Student Services
  • NA Allocation & Admission of Students

Learning Analytics College Transfer Students Transfer Shock Classification Tree Senior Year Admitted Students

• Hong Kong

• 1997.7 onwards

• Post-Secondary Education

• View Full Text 全文連結

College transfer students are those who follow a different trajectory in their higher education journeys than traditional students, completing a sub-degree before pursuing a bachelor's degree at a university. While the possibility of transferring makes higher education accessible to these students, previous studies have found that they face various challenges, from issues with course load to language challenges. This study aims to examine (1) the critical factors contributing to the success of transfer students in a language course; and (2) how transfer students perform better or worse than those who enter university directly. This study conducted learning analytics with 700 college transfer students in Hong Kong, retrieving their demographic and learning data from the learning management system and the university academic registry. The results suggest that English exam scores, current semester GPA, graduating GPA at community college and current course load are important predictors of transfer students' success in language courses. This study also finds that transfer students have lower levels of language proficiency than direct entrants. It concludes with specific recommendations to make higher education more accessible to transfer students and suggestions on how to use learning analytics to track students with different trajectories. Copyright © 2023 Springer.

• English

Journal Articles

• 23659440

• 10.1186/s41239-023-00429-y

https://bibliography.lib.eduhk.hk/en/bibs/e21a5b09

2024-04-09