Predicting dropout at master level using educational data mining: A case of public health students in Saudi Arabia
Resumen
Student dropout and its economic and social consequences are significant issues in developing countries. Students who drop out experience reduced employment prospects and encounter social stigma. While early dropout prediction can assist in mitigating the consequences, it remains a considerable challenge. The present research employed a data mining approach to predict dropout of public health master-level students in Saudi Arabia, a developing nation that has invested considerable resources to promote higher education. The research model focused on three fundamental determinants of students’ dropout: individual, institutional, and academic. The study analysis on a dataset of 150 students revealed that all three determinants predicted student dropout. The results indicated that students with low academic performance who received an academic warning were likelier to drop out. Freshmen with poor academic achievement were particularly at risk of dropping out of college. Students between 31 and 36 years old who attended technical courses as a subject specialization could also dropout. The research contributes to the literature by suggesting that universities should consider these individual, institutional, and academic determinants to develop their dropout prevention strategies. This study has ramifications for university administrators in developing nations, such as Saudi Arabia, who can establish dropout prevention programs based on the determinants revealed in this study.
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Abdulghani, H. M., Alanazi, K., Alotaibi, R., Alsubeeh, N. A., Ahmad, T., & Haque, S. (2023). Prevalence of potential dropout thoughts and their influential factors among Saudi medical students. SAGE Open, 13(1), 215824402211469. https://doi.org/10.1177/21582440221146966
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Alam, F., Singh, H. P., & Singh, A. (2022). Economic Growth in Saudi Arabia through Sectoral Reallocation of Government Expenditures. SAGE Open, 12(4), 1-13. https://doi.org/10.1177/21582440221127158
Alazemi, N. F. S. A. (2023). The use of information technology applications by faculty members at the college of basic education in the public authority for applied education and training in the state of Kuwait. International Journal of Advanced and Applied Sciences, 10(3), 136-142. https://doi.org/10.21833/ijaas.2023.03.018
Alhamad, I. A., & Singh, H. P. (2021). Decoding Significant and Trivial Factors Influencing Online Hotel Ratings: The Case of Saudi Arabia's Makkah City. International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies, 12(7), 12A7H, 1-11. https://doi.org/10.14456/ITJEMAST.2021.134
Alhamuddin, A., Inten, D. N., Mulyani, D., Suganda, A. D., Juhji, J., Prachagool, V., & Nuangchalerm, P. (2023). Multiple intelligence-based differential learning on critical thinking skills of higher education students. International Journal of Advanced and Applied Sciences, 10(8), 132-139. https://doi.org/10.21833/ijaas.2023.08.015
Alhulail, H. N., & Singh, H. P. (2023). Impact of multimedia technology on university students learning agility and creativity. Amazonia Investiga, 12(70), 189-199. https://doi.org/10.34069/AI/2023.70.10.17
Alkhalil, A. (2021). Decision support model to adopt big data analytics in higher education systems. International Journal of Advanced and Applied Sciences, 8(6), 67-78. https://doi.org/10.21833/ijaas.2021.06.008
Al-Omar, B. (2023). About King Saud University. King Saud University Accessed December 12, 2023. from https://tinyurl.com/y5cek94f
Baalmann, T. (2023). Health-Related Quality of Life, Success Probability and Students’ Dropout Intentions: Evidence from a German Longitudinal Study. Research in Higher Education. 65. https://doi.org/10.1007/s11162-023-09738-7
Bharadwaj, B. K., & Pal, S. (2011). Mining educational data to analyze students performance. International Journal of Advanced Computer Science and Applications, 2(6). https://doi.org/10.14569/ijacsa.2011.020609
Bharadwaj, B. K., & Pal, S. (2012). Data Mining: A prediction for performance improvement using classification. International Journal of Computer Science and Information Security, 9(4), 1-5. https://tinyurl.com/mvzvun6v
Casanova, J. R., Cervero, A., Núñez, J. C., Almeida, L. S., & Bernardo, A. (2018). Factors that determine the persistence and dropout of university students. Psicothema, 30(4), 408-414. https://doi.org/10.7334/psicothema2018.155
CGIJ. (2023). List of universities and colleges in Saudi Arabia. Consulate General of India, Jeddah. Retrieved December 16, 2023, from http://www.cgijeddah.com/listofuniversity.pdf
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Cios, K. J., Teresinska, A., Konieczna, S., Potocka, J., & Sharma, S. (2000). A knowledge discovery approach to diagnosing myocardial perfusion. IEEE Engineering in Medicine and Biology Magazine, 19(4), 17-25. https://doi.org/10.1109/51.853478
Dlungwane, T., & Voce, A. (2020). Exploring student persistence to completion in a Master of Public Health programme in South Africa. African Journal of Health Professions Education, 12(1), 17. https://doi.org/10.7196/ajhpe.2020.v12i1.1183
Gentle, J. E., Härdle, W. K., & Mori, Y. (Eds.). (2012). Handbook of Computational Statistics: Concepts and Methods (2nd ed., Springer Handbooks of Computational Statistics). Heidelberg, Germany: Springer-Verlag. https://doi.org/10.1007/978-3-642-21551-3
Han, J., Kamber, M., & Pei, J. (2012). Data Mining: Concepts and Techniques (3rd ed.). Waltham, MA: Morgan Kaufmann. https://doi.org/10.1016/C2009-0-61819-5
Hashim, R. A., Lim, H. E., Jafar, M. F., Shanmugam, S. K. S., & Bukhari, N. (2024). Statistical identification of predictors of dropout in secondary education: evidence from Malaysia. Journal of the Asia Pacific Economy, 1-27. https://doi.org/10.1080/13547860.2024.2306673
Ibeaheem, H. A., Elawady, S., & Ragmoun, W. (2018). Saudi Universities and higher education skills on Saudi Arabia. International Journal of Higher Education Management, 04(02), 1-14. https://doi.org/10.24052/ijhem/v04n02/art05
Kumari, R., & Singh, H. P. (2022). Role of Incident Reporting System in Healthcare Management: A Case of Multispeciality Tertiary Hospital in India. International Journal of Information Movement, 6(IX), 12-18. https://tinyurl.com/38pejmwb
Liu, H., Hussain, F., Tan, C. L., & Dash, M. (2002). Discretization: An Enabling Technique. Data Mining and Knowledge Discovery, 6, 393-423. https://doi.org/10.1023/a:1016304305535
Márquez-Vera, C., Cano, A., Romero, C., Noaman, A. Y., Fardoun, H. M., & Ventura, S. (2015). Early Dropout Prediction using Data Mining: A Case Study with High School Students. Expert Systems, 33(1), 107-124. https://doi.org/10.1111/exsy.12135
Mubarak, A. A., Cao, H., & Zhang, W. (2020). Prediction of students’ early dropout based on their interaction logs in online learning environment. Interactive Learning Environments, 30(8), 1414-1433. https://doi.org/10.1080/10494820.2020.1727529
Pal, S. (2012). Mining Educational Data to Reduce Dropout Rates of Engineering Students. International Journal of Information Engineering and Electronic Business, 4(2), 1-7. https://doi.org/10.5815/ijieeb.2012.02.01
Refaeilzadeh, P., Tang, L., & Liu, H. (2009). Cross-Validation. In L. Liu & M. T. Özsu (Eds.), Encyclopedia of Database Systems (pp. 532–538). Springer, Boston, MA. https://doi.org/10.1007/978-0-387-39940-9_565
Robert, K. J. B. (2023). Faculty commitment and performance in Montfortian educational institutions: Basis for a faculty development program. International Journal of Advanced and Applied Sciences, 10(2), 113-127. https://doi.org/10.21833/ijaas.2023.02.015
Rodríguez-Muñiz, L. J., Bernardo, A. B., Esteban, M., & Díaz, I. (2019). Dropout and transfer paths: What are the risky profiles when analyzing university persistence with machine learning techniques? Plos One, 14(6), 1-20. https://doi.org/10.1371/journal.pone.0218796
Rotem, N., Yair, G., & Shustak, E. (2020). Dropping out of master’s degrees: objective predictors and subjective reasons. Higher Education Research and Development, 40(5), 1070-1084. https://doi.org/10.1080/07294360.2020.1799951
Saudi Gazette. (2020, May 20). Full text of Saudi Arabia’s Vision 2030 | Al Arabiya English. https://tinyurl.com/4nt5pxan
Singh, A., Singh, H. P., Alam, F., & Agrawal, V. (2022b). Role of Education, Training, and E-Learning in Sustainable Employment Generation and Social Empowerment in Saudi Arabia. Sustainability, 14(14), 8822. https://doi.org/10.3390/su14148822
Singh, H. P., & Alhamad, I. A. (2022a). Influence of National Culture on Perspectives and Factors Affecting Student Dropout: A Comparative Study of Australia, Saudi Arabia, and Ethiopia. Archives of Business Research, 10(11), 287-300. https://doi.org/10.14738/abr.1011.13508
Singh, H. P., & Alhamad, I. A. (2022b). A Data Mining Approach to Predict Key Factors Impacting University Students Dropout in a Least Developed Economy. Archives of Business Research, 10(12), 48-59. https://doi.org/10.14738/abr.1012.13556
Singh, H. P., & Alhulail, H. N. (2022). Predicting Student-Teachers Dropout Risk and Early Identification: A Four-Step Logistic Regression Approach. IEEE Access, 10, 6470-6482. https://doi.org/10.1109/access.2022.3141992
Singh, H. P., & Alodaynan, A. M. M. (2023). The role of educational technology in developing the cognitive and communicative skills of university students: A Saudi Arabian case. International Journal of Advanced and Applied Sciences, 10(7), 157-164. https://doi.org/10.21833/ijaas.2023.07.017
Singh, H. P., & Chand, P. (2012). ICT Education: Challenges and Opportunities. In D. Parimala (Ed.), Role of Teachers in Changing Context: Policy and Practice (1st ed., pp. 255–263). Kanishka Publishers, Distributors. https://tinyurl.com/3cvexykt
Singh, H. P., Agarwal, A., & Das, J. K. (2013). Implementation of E-Learning in Adult Education: A Roadmap. Mumukshu Journal of Humanities, 5(1), 229-232. https://tinyurl.com/yfcws7rw
Singh, H. P., Alshallaqi, M., & Altamimi, M. (2023). Predicting Critical Factors Impacting Hotel Online Ratings: A Comparison of Religious and Commercial Destinations in Saudi Arabia. Sustainability, 15(15), 11998. https://doi.org/10.3390/su151511998
Singh, H. P., Jindal, S., & Kaurav, R. P. S. (2011a). Adult Education and E-Learning. In Proceedings of the National Conference on Turbulent Business Environment: The Road Ahead. Rohini, Delhi, India; Gitarattan International Business School (giBS). https://tinyurl.com/ru9dhne7
Singh, H. P., Jindal, S., & Samim, S. A. (2011b). A Critical Study on Adoption of E-Learning for Development of Human Resources in Developing Countries. Mumukshu Journal of Humanities, 3(3), 116-120.
Singh, H. P., Jindal, S., & Samim, S. A. (2011c). Role of Human Resource Information System in Banking Industry of Developing Countries. Special Issue of the International Journal of the Computer, the Internet and Management, 19(SP1), 59.1-59.5. https://bit.ly/3coQmWw
Singh, H., & Alhulail, H. N. (2023). Information Technology Governance and Corporate Boards’ Relationship with Companies’ Performance and Earnings Management: A Longitudinal Approach. Sustainability, 15(8), 6492. https://doi.org/10.3390/su15086492
Singh, H., Singh, A., Alam, F., & Agrawal, V. (2022a). Impact of Sustainable Development Goals on Economic Growth in Saudi Arabia: Role of Education and Training. Sustainability, 14(21), 14119. https://doi.org/10.3390/su142114119
Singh, H.P., & Alhamad, I. A. (2021). Deciphering Key Factors Impacting Online Hotel Ratings Through the Lens of Two-Factor Theory: A Case of Hotels in Makkah City of Saudi Arabia. International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies, 12(8), 12A8M, 1-12. https://doi.org/10.14456/ITJEMAST.2021.160
Singh, H.P., & Alwaqaa, M. A. M. (2023). The educational technology's impact on youth creativity and innovation: A case of Ha’il region of Saudi Arabia. Amazonia Investiga, 12(66), 144-154. https://doi.org/10.34069/AI/2023.66.06.14
Yadav, S. K., Bharadwaj, B., & Pal, S. (2012). Mining Education Data to Predict Student's Retention: A Comparative Study. International Journal of Computer Science and Information Security, 10(2), 113-117. https://tinyurl.com/4jndx6dt
Ye, X., Zhai, M., Feng, L., Xie, A., Wang, W., & Wu, H. (2022). Still want to be a doctor? Medical student dropout in the era of COVID-19. Journal of Economic Behavior and Organization, 195, 122-139. https://doi.org/10.1016/j.jebo.2021.12.034
Zhang, Y., Oussena, S., Clark, T., & Kim, H. (2010). Use data mining to improve student retention in higher education - A case study. In ICEIS - 12th International Conference on Enterprise Information Systems. Retrieved December 27, 2023, from http://shura.shu.ac.uk/11970/
Ahmed, U., Umrani, W. A., Qureshi, M. A., & Samad, A. (2018). Examining the links between teachers support, academic efficacy, academic resilience, and student engagement in Bahrain. International Journal of Advanced and Applied Sciences, 5(9), 39-46. https://doi.org/10.21833/ijaas.2018.09.008
Alam, F., Singh, H. P., & Singh, A. (2022). Economic Growth in Saudi Arabia through Sectoral Reallocation of Government Expenditures. SAGE Open, 12(4), 1-13. https://doi.org/10.1177/21582440221127158
Alazemi, N. F. S. A. (2023). The use of information technology applications by faculty members at the college of basic education in the public authority for applied education and training in the state of Kuwait. International Journal of Advanced and Applied Sciences, 10(3), 136-142. https://doi.org/10.21833/ijaas.2023.03.018
Alhamad, I. A., & Singh, H. P. (2021). Decoding Significant and Trivial Factors Influencing Online Hotel Ratings: The Case of Saudi Arabia's Makkah City. International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies, 12(7), 12A7H, 1-11. https://doi.org/10.14456/ITJEMAST.2021.134
Alhamuddin, A., Inten, D. N., Mulyani, D., Suganda, A. D., Juhji, J., Prachagool, V., & Nuangchalerm, P. (2023). Multiple intelligence-based differential learning on critical thinking skills of higher education students. International Journal of Advanced and Applied Sciences, 10(8), 132-139. https://doi.org/10.21833/ijaas.2023.08.015
Alhulail, H. N., & Singh, H. P. (2023). Impact of multimedia technology on university students learning agility and creativity. Amazonia Investiga, 12(70), 189-199. https://doi.org/10.34069/AI/2023.70.10.17
Alkhalil, A. (2021). Decision support model to adopt big data analytics in higher education systems. International Journal of Advanced and Applied Sciences, 8(6), 67-78. https://doi.org/10.21833/ijaas.2021.06.008
Al-Omar, B. (2023). About King Saud University. King Saud University Accessed December 12, 2023. from https://tinyurl.com/y5cek94f
Baalmann, T. (2023). Health-Related Quality of Life, Success Probability and Students’ Dropout Intentions: Evidence from a German Longitudinal Study. Research in Higher Education. 65. https://doi.org/10.1007/s11162-023-09738-7
Bharadwaj, B. K., & Pal, S. (2011). Mining educational data to analyze students performance. International Journal of Advanced Computer Science and Applications, 2(6). https://doi.org/10.14569/ijacsa.2011.020609
Bharadwaj, B. K., & Pal, S. (2012). Data Mining: A prediction for performance improvement using classification. International Journal of Computer Science and Information Security, 9(4), 1-5. https://tinyurl.com/mvzvun6v
Casanova, J. R., Cervero, A., Núñez, J. C., Almeida, L. S., & Bernardo, A. (2018). Factors that determine the persistence and dropout of university students. Psicothema, 30(4), 408-414. https://doi.org/10.7334/psicothema2018.155
CGIJ. (2023). List of universities and colleges in Saudi Arabia. Consulate General of India, Jeddah. Retrieved December 16, 2023, from http://www.cgijeddah.com/listofuniversity.pdf
Cios, K. J., Pedrycz, W., Swiniarski, R. W., & Kurgan, L. A. (2007). Data Mining: A Knowledge Discovery Approach (1st ed.). New York, NY: Springer US. https://doi.org/10.1007/978-0-387-36795-8
Cios, K. J., Teresinska, A., Konieczna, S., Potocka, J., & Sharma, S. (2000). A knowledge discovery approach to diagnosing myocardial perfusion. IEEE Engineering in Medicine and Biology Magazine, 19(4), 17-25. https://doi.org/10.1109/51.853478
Dlungwane, T., & Voce, A. (2020). Exploring student persistence to completion in a Master of Public Health programme in South Africa. African Journal of Health Professions Education, 12(1), 17. https://doi.org/10.7196/ajhpe.2020.v12i1.1183
Gentle, J. E., Härdle, W. K., & Mori, Y. (Eds.). (2012). Handbook of Computational Statistics: Concepts and Methods (2nd ed., Springer Handbooks of Computational Statistics). Heidelberg, Germany: Springer-Verlag. https://doi.org/10.1007/978-3-642-21551-3
Han, J., Kamber, M., & Pei, J. (2012). Data Mining: Concepts and Techniques (3rd ed.). Waltham, MA: Morgan Kaufmann. https://doi.org/10.1016/C2009-0-61819-5
Hashim, R. A., Lim, H. E., Jafar, M. F., Shanmugam, S. K. S., & Bukhari, N. (2024). Statistical identification of predictors of dropout in secondary education: evidence from Malaysia. Journal of the Asia Pacific Economy, 1-27. https://doi.org/10.1080/13547860.2024.2306673
Ibeaheem, H. A., Elawady, S., & Ragmoun, W. (2018). Saudi Universities and higher education skills on Saudi Arabia. International Journal of Higher Education Management, 04(02), 1-14. https://doi.org/10.24052/ijhem/v04n02/art05
Kumari, R., & Singh, H. P. (2022). Role of Incident Reporting System in Healthcare Management: A Case of Multispeciality Tertiary Hospital in India. International Journal of Information Movement, 6(IX), 12-18. https://tinyurl.com/38pejmwb
Liu, H., Hussain, F., Tan, C. L., & Dash, M. (2002). Discretization: An Enabling Technique. Data Mining and Knowledge Discovery, 6, 393-423. https://doi.org/10.1023/a:1016304305535
Márquez-Vera, C., Cano, A., Romero, C., Noaman, A. Y., Fardoun, H. M., & Ventura, S. (2015). Early Dropout Prediction using Data Mining: A Case Study with High School Students. Expert Systems, 33(1), 107-124. https://doi.org/10.1111/exsy.12135
Mubarak, A. A., Cao, H., & Zhang, W. (2020). Prediction of students’ early dropout based on their interaction logs in online learning environment. Interactive Learning Environments, 30(8), 1414-1433. https://doi.org/10.1080/10494820.2020.1727529
Pal, S. (2012). Mining Educational Data to Reduce Dropout Rates of Engineering Students. International Journal of Information Engineering and Electronic Business, 4(2), 1-7. https://doi.org/10.5815/ijieeb.2012.02.01
Refaeilzadeh, P., Tang, L., & Liu, H. (2009). Cross-Validation. In L. Liu & M. T. Özsu (Eds.), Encyclopedia of Database Systems (pp. 532–538). Springer, Boston, MA. https://doi.org/10.1007/978-0-387-39940-9_565
Robert, K. J. B. (2023). Faculty commitment and performance in Montfortian educational institutions: Basis for a faculty development program. International Journal of Advanced and Applied Sciences, 10(2), 113-127. https://doi.org/10.21833/ijaas.2023.02.015
Rodríguez-Muñiz, L. J., Bernardo, A. B., Esteban, M., & Díaz, I. (2019). Dropout and transfer paths: What are the risky profiles when analyzing university persistence with machine learning techniques? Plos One, 14(6), 1-20. https://doi.org/10.1371/journal.pone.0218796
Rotem, N., Yair, G., & Shustak, E. (2020). Dropping out of master’s degrees: objective predictors and subjective reasons. Higher Education Research and Development, 40(5), 1070-1084. https://doi.org/10.1080/07294360.2020.1799951
Saudi Gazette. (2020, May 20). Full text of Saudi Arabia’s Vision 2030 | Al Arabiya English. https://tinyurl.com/4nt5pxan
Singh, A., Singh, H. P., Alam, F., & Agrawal, V. (2022b). Role of Education, Training, and E-Learning in Sustainable Employment Generation and Social Empowerment in Saudi Arabia. Sustainability, 14(14), 8822. https://doi.org/10.3390/su14148822
Singh, H. P., & Alhamad, I. A. (2022a). Influence of National Culture on Perspectives and Factors Affecting Student Dropout: A Comparative Study of Australia, Saudi Arabia, and Ethiopia. Archives of Business Research, 10(11), 287-300. https://doi.org/10.14738/abr.1011.13508
Singh, H. P., & Alhamad, I. A. (2022b). A Data Mining Approach to Predict Key Factors Impacting University Students Dropout in a Least Developed Economy. Archives of Business Research, 10(12), 48-59. https://doi.org/10.14738/abr.1012.13556
Singh, H. P., & Alhulail, H. N. (2022). Predicting Student-Teachers Dropout Risk and Early Identification: A Four-Step Logistic Regression Approach. IEEE Access, 10, 6470-6482. https://doi.org/10.1109/access.2022.3141992
Singh, H. P., & Alodaynan, A. M. M. (2023). The role of educational technology in developing the cognitive and communicative skills of university students: A Saudi Arabian case. International Journal of Advanced and Applied Sciences, 10(7), 157-164. https://doi.org/10.21833/ijaas.2023.07.017
Singh, H. P., & Chand, P. (2012). ICT Education: Challenges and Opportunities. In D. Parimala (Ed.), Role of Teachers in Changing Context: Policy and Practice (1st ed., pp. 255–263). Kanishka Publishers, Distributors. https://tinyurl.com/3cvexykt
Singh, H. P., Agarwal, A., & Das, J. K. (2013). Implementation of E-Learning in Adult Education: A Roadmap. Mumukshu Journal of Humanities, 5(1), 229-232. https://tinyurl.com/yfcws7rw
Singh, H. P., Alshallaqi, M., & Altamimi, M. (2023). Predicting Critical Factors Impacting Hotel Online Ratings: A Comparison of Religious and Commercial Destinations in Saudi Arabia. Sustainability, 15(15), 11998. https://doi.org/10.3390/su151511998
Singh, H. P., Jindal, S., & Kaurav, R. P. S. (2011a). Adult Education and E-Learning. In Proceedings of the National Conference on Turbulent Business Environment: The Road Ahead. Rohini, Delhi, India; Gitarattan International Business School (giBS). https://tinyurl.com/ru9dhne7
Singh, H. P., Jindal, S., & Samim, S. A. (2011b). A Critical Study on Adoption of E-Learning for Development of Human Resources in Developing Countries. Mumukshu Journal of Humanities, 3(3), 116-120.
Singh, H. P., Jindal, S., & Samim, S. A. (2011c). Role of Human Resource Information System in Banking Industry of Developing Countries. Special Issue of the International Journal of the Computer, the Internet and Management, 19(SP1), 59.1-59.5. https://bit.ly/3coQmWw
Singh, H., & Alhulail, H. N. (2023). Information Technology Governance and Corporate Boards’ Relationship with Companies’ Performance and Earnings Management: A Longitudinal Approach. Sustainability, 15(8), 6492. https://doi.org/10.3390/su15086492
Singh, H., Singh, A., Alam, F., & Agrawal, V. (2022a). Impact of Sustainable Development Goals on Economic Growth in Saudi Arabia: Role of Education and Training. Sustainability, 14(21), 14119. https://doi.org/10.3390/su142114119
Singh, H.P., & Alhamad, I. A. (2021). Deciphering Key Factors Impacting Online Hotel Ratings Through the Lens of Two-Factor Theory: A Case of Hotels in Makkah City of Saudi Arabia. International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies, 12(8), 12A8M, 1-12. https://doi.org/10.14456/ITJEMAST.2021.160
Singh, H.P., & Alwaqaa, M. A. M. (2023). The educational technology's impact on youth creativity and innovation: A case of Ha’il region of Saudi Arabia. Amazonia Investiga, 12(66), 144-154. https://doi.org/10.34069/AI/2023.66.06.14
Yadav, S. K., Bharadwaj, B., & Pal, S. (2012). Mining Education Data to Predict Student's Retention: A Comparative Study. International Journal of Computer Science and Information Security, 10(2), 113-117. https://tinyurl.com/4jndx6dt
Ye, X., Zhai, M., Feng, L., Xie, A., Wang, W., & Wu, H. (2022). Still want to be a doctor? Medical student dropout in the era of COVID-19. Journal of Economic Behavior and Organization, 195, 122-139. https://doi.org/10.1016/j.jebo.2021.12.034
Zhang, Y., Oussena, S., Clark, T., & Kim, H. (2010). Use data mining to improve student retention in higher education - A case study. In ICEIS - 12th International Conference on Enterprise Information Systems. Retrieved December 27, 2023, from http://shura.shu.ac.uk/11970/
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2024-02-29
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Alhamad, I. A., & Singh, H. P. (2024). Predicting dropout at master level using educational data mining: A case of public health students in Saudi Arabia. Amazonia Investiga, 13(74), 264-275. https://doi.org/10.34069/AI/2024.74.02.22
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