Using Institutional data and messages on Social Media to Predict the Career decisions of University Students - A Data-Driven Approach
Author:
Funder
ministry of science and technology, taiwan
Publisher
Springer Science and Business Media LLC
Subject
Library and Information Sciences,Education
Link
https://link.springer.com/content/pdf/10.1007/s10639-022-11185-3.pdf
Reference85 articles.
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2. Alvarez, N. L., Callejas, Z., & Griol, D. (2020). Predicting Computer Engineering students’ dropout in Cuban Higher Education with pre-enrollment and early performance data. JOTSE, 10(2), 241–258
3. Alyahyan, E., & Düştegör, D. (2020). Predicting academic success in higher education: literature review and best practices. International Journal of Educational Technology in Higher Education, 17(1), 3. https://doi.org/10.1186/s41239-020-0177-7
4. Arnold, W. W. (2018). Strengthening college support services to improve student transitioning to careers. Journal of College Teaching & Learning (TLC), 15(1), 5–26
5. Atitsogbe, K. A., Mama, N. P., Sovet, L., Pari, P., & Rossier, J. (2019). Perceived employability and entrepreneurial intentions across university students and job seekers in Togo: The effect of career adaptability and self-efficacy. Frontiers in psychology, 10, 180. https://doi.org/10.3389/fpsyg.2019.00180
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