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Adaptation of the Undergraduate Learning Persistence Scale: A Validity and Reliability Study

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This study used a quantitative research method to administer a questionnaire to 719 undergraduate students from three Chinese universities based on Tinto's dropout theory. The study tested the reliability and validity of the Chinese version of the Learning Persistence Scale (LPS). The results demonstrated that the exploratory factor analysis extracted 5 main factors and retained 20 entries, explaining 65.453% of the variance cumulatively. Each index of the validating factor numerator reached the desired value and the model fit was good. The total scale's Cronbach's alpha coefficient was 0.903, and the folded reliability levels were found to be between 0.794 and 0.882. CONCLUSION: The Chinese version of the Learning Persistence Scale shows high levels of both reliability and validity, is suitable for evaluating and measuring learning persistence among Chinese undergraduate students, and can be used to understand Chinese undergraduate students' learning persistence behaviors to improve undergraduate students' learning persistence and academic achievement.
Bai, H., Yu, H., Bantsimba N., R.,& Luo, L. (2022). How college experiences impact student learning outcomes: Insights from Chinese undergraduate students. Frontiers in Psychology, 13. https://doi.org/10.3389/fpsyg.2022.1021591
Baker, B. A., Caison, A. L., & Meade, A. W. (2007). Assessing Gender-Related Differential Item Functioning and Predictive Validity With the Institutional Integration Scale. Educational and Psychological Measurement, 67(3), 545–559. https://doi.org/10.1177/0013164406292088
Baker, D. J., Arroyo, A. T., Braxton, J. M., Gasman, M., & Francis, C. H. (2018). Expanding the Student Persistence Puzzle to Minority Serving Institutions: The Residential Historically Black College and University Context. Journal of College Student Retention: Research, Theory & Practice, 22(4), 152102511878403. https://doi.org/10.1177/1521025118784030
Boyraz, G., Horne, S. G., Owens, A. C., & Armstrong, A. P. (2013). Academic achievement and college persistence of African American students with trauma exposure. Journal of Counseling Psychology, 60(4), 582–592. https://doi.org/10.1037/a0033672
Browne, M. W.,& Cudeck, R. (1993). Alternative Ways of Assessing Model Fit. Sociological Methods & Research, 21 (2), 230–258. https://doi.org/10.1177/0049124192021002005
Chen, X., Elliott, B. G., Kinney, S. K., Cooney, D., Pretlow, J., Bryan, M., Wu, J., Ramirez, N. A., & Campbell, T. (2019). Persistence, Retention, and Attainment of 2011-12 First-Time Beginning Postsecondary Students as of Spring 2017. First Look. NCES 2019-401. National Center for Education Statistics.
Duckworth, A. L., Peterson, C., Matthews, M. D.,& Kelly, D. R. (2007). Grit: Perseverance and passion for long-term goals. Journal of Personality and Social Psychology, 92 (6), 1087–1101. https://doi.org/10.1037/0022-3514.92.6.1087
Freedman, H. I., & Moson, P. (1990). Persistence definitions and their connections. Proceedings of the American Mathematical Society, 109(4), 1025–1033. https://doi.org/10.1090/s0002-9939-1990-1012928-6
French, B. F. (2009). Measurement invariance related to gender of the institutional integration scale. European Review of Applied Psychology, 59(2), 85–90. https://doi.org/10.1016/j.erap.2008.12.003
French, B. F., & Oakes, W. (2004). Reliability and Validity Evidence for the Institutional Integration Scale. Educational and Psychological Measurement, 64(1), 88–98. https://doi.org/10.1177/0013164403258458
Gloria, A. M., & Robinson Kurpius, S. E. (2001). Influences of self-beliefs, social support, and comfort in the university environment on the academic nonpersistence decisions of American Indian undergraduates. Cultural Diversity and Ethnic Minority Psychology, 7, 88 –102. doi: 10.1037/1099-9809.7.1.88
Gloria, A. M., Robinson Kurpius, S. E., Hamilton, K. D., & Willson, M. S. (1999). African American academic nonpersistence at a predominately White institution: Issues of social support, university comfort, and self-beliefs. Journal of College Student Development, 40, 257–268.
Hair, J. F., Black, W. C., Babin, B. J.,& Anderson, R. E. (2019). Multivariate Data Analysis (8th ed.). Cengage Learning Emea.
Hair, J. F., Anderson, R. E., Tatham, R. L., and Black, W. C. (1998), Multivariate Data Analysis(5th ed.). Prentice-Hall?Englewood Cliffs, NJ.
Henson, R. K., & Roberts, J. K. (2006). Use of Exploratory Factor Analysis in Published Research. Educational and Psychological Measurement, 66 (3), 393–416. https://doi.org/10.1177/0013164405282485
Huerta-Manzanilla, E., Ohland, M., & Long, R. (2020). The Impact of Social Integration on Engineering Students’ Persistence, Longitudinal, Interinstitutional Database Analysis. Papers on Engineering Education Repository (American Society for Engineering Education), 23.1211.1–23.1211.16. https://doi.org/10.18260/1-2--22596
Hurtado, E., Rosado, E., Aoiz, M., Quero, S.,& Luis, E. O. (2024). Factors associated with the permanence of doctoral students. A scoping review. Frontiers in Psychology, 15. https://doi.org/10.3389/fpsyg.2024.1390784
Jung, Y., & Lee, J. (2018). Learning Engagement and Persistence in Massive Open Online Courses (MOOCS). Computers & Education, 122, 9–22. https://doi.org/10.1016/j.compedu.2018.02.013
Kaiser, H. F. (1960). The Application of Electronic Computers to Factor Analysis. Educational and Psychological Measurement, 20 (1), 141–151. https://doi.org/10.1177/001316446002000116
Kaiser, H. F.,& Rice, J. (1974). Little Jiffy, Mark IV. Educational and Psychological Measurement, 34 (1), 111–117. https://doi.org/10.1177/001316447403400115
Kember, D. (1995). Open learning courses for adults: A model of student progress. Educational Technology Publications.
Nunnally, J. C., & Bernstein, I. H. (1994). Psychometric theory (3rd ed.). New York, NY: McGraw-Hill, Inc.
Pascarella, E. T.,& Terenzini, P. T. (1980). Predicting Freshman Persistence and Voluntary Dropout Decisions from a Theoretical Model. The Journal of Higher Education, 51(1), 60–75. https://doi.org/10.1080/00221546.1980.11780030
Pett, M., Lackey, N., & Sullivan, J. (2003). Making Sense of Factor Analysis. https://doi.org/10.4135/9781412984898
Pintrich, P. R. (1986). Motivation and learning strategies interactions with achievement. Developmental Review, 6?25–56.
Jing, S. (2015) An empirical study on the impact of social interpersonal interaction on learning outcomes of undergraduate students . Huazhong University of Science and Technology: China
Spady, W. G. (1970). Dropouts from higher education: An interdisciplinary review and synthesis. Interchange, 1(1), 64–85. https://doi.org/10.1007/bf02214313
Thompson, M. N., Johnson-Jennings, M., & Nitzarim, R. S. (2013). Native American undergraduate students’ persistence intentions: A psychosociocultural perspective. Cultural Diversity and Ethnic Minority Psychology, 19(2), 218–228. https://doi.org/10.1037/a0031546
Tinto, V. (1975). Dropout from Higher Education: A Theoretical Synthesis of Recent Research. Review of Educational Research, 45(1), 89–125. https://doi.org/10.3102/00346543045001089
Tinto, V. (1993). Leaving college: Rethinking the causes and cures of student attrition (2nd ed.). Chicago: University Of Chicago Press.
Zhai, Y., & Carney, J. V. (2024). The role of mental health and protective factors in student academic persistence and retention during a global crisis. Global Mental Health, 11. https://doi.org/10.1017/gmh.2024.12
Haiyan, L., & Ashari, Z. M. (2025). Adaptation of the Undergraduate Learning Persistence Scale: A Validity and Reliability Study. International Journal of Academic Research in Business and Social Sciences, 15(6), 110-119.