Home⇛The Trinitian Researcher⇛vol. 13 no. 1 (2025)

Differences in Learning Strategies Between Full-Time and Part-Time Students in HEBEI Province in China

Jingxuan Han

Discipline: Education

 

Abstract:

This study compares the learning strategies of fulltime and part-time students at a vocational college using the Chinese version of the Learning Strategy Questionnaire (MSLQ-CAL). Data were collected from 333 students through questionnaires and interviews. Results show that part-time students score slightly higher in elaboration strategy, indicating they more often connect new knowledge with practical work experience. Full-time students score significantly higher in metacognition, organization, management of the learning environment, critical thinking, and cooperative learning, demonstrating that school support and structure promote systematic learning. Both groups perform similarly in time and effort management, self-regulation, and rehearsal strategies, and face the same difficulties. Overall, the study finds that part-time students focus on empirical, application-oriented learning, while full-time students depend on systematic resources and guidance. These findings can deepen understanding of learning strategies in vocational education and offer a new perspective for further research on strategies in China. The results highlight the importance of aligning vocational education policies with the distinct needs and strategies of full-time and part-time students to create a more effective educational framework.



References:

  1. Abbasnejad, B., Soltani, S., & Wong, P. (2024). A systematic review of online learning and teaching strategies during the COVID-19 pandemic: Implications for the construction management sector. Smart and Sustainable Built Environment, 13(4), 934–959. https://doi.org/10.1108/SASBE-08-2022-0174
  2. Adel Elsayed, A., Caeiro-Rodríguez, M., Mikic-Fonte, F. A., Lugilde-López, A., & Llamas-Nistal, M. (2024). Measuring and promoting self-regulated learning using spaced questionnaires. IEEE Access, 12, 158837–158853. https://doi.org/10.1109/ACCESS.2024.3457238
  3. Almulhim, F. A., Alghamdi, M. S., Almetwally, E. M., & Al-Zahrani, S. I. (2024). An optimal estimation approach in stratified random sampling utilizing two auxiliary attributes with application in agricultural, demography, finance, and education sectors. Heliyon, 10(4), e37234. https://doi.org/10.1016/j.heliyon.2024.e37234
  4. Artino, A. R. (2005). Review of the Motivated Strategies for Learning Questionnaire. University of Connecticut. https://eric.ed.gov/?id=ED499083
  5. Carpenter, S.K., Pan, S.C. & Butler, A.C. The science of effective learning with spacing and retrieval practice. Nature Reviews Psychology 1, 496–511 (2022). https://doi.org/10.1038/s44159-022-00089-1
  6. Chua, C. S. K., Soo, J. L. M., & Raza, K. (2024). Work-integrated (adult) learning: Un-stigmatizing blue-collar adult learners in Singapore by embracing visibility. Journal of Adult and Continuing Education, 30(1), 112–130. https://doi.org/10.1177/14779714241228847
  7. Gardner, A. C., Maietta, H. N., Gardner, P. D., & Perkins, N. (2021). Postsecondary adult learner motivation: An analysis of credentialing patterns and decision-making within higher education programs. Adult Learning, 33(1), 15–31. https://doi.org/10.1177/1045159520988361
  8. Guo, H., Tong, F., Wang, Z., Tang, S., Yoon, M., Ying, M., & Yu, X. (2021). Examining self-regulated learning strategy model: A measurement invariance analysis of MSLQ-CAL among college students in China. Sustainability, 13(18), 10133. https://doi.org/10.3390/su131810133
  9. Guo, R., Jantharajit, N., & Thongpanit, P. (2024). Enhancing analytical and critical thinking skills through reflective and collaborative learning: A quasi-experimental study. Journal of Education and Educational Development, 11(2), 200–223. https://doi.org/10.22555/joeed.v11i2.1166
  10. Hsu, T. C., Chang, C., & Jen, T. H. (2023). Artificial intelligence image recognition using self-regulation learning strategies: Effects on vocabulary acquisition, learning anxiety, and learning behaviors of English language learners. Interactive Learning Environments, 32(6), 3060–3078. https://doi.org/10.1080/10494820.2023.2165508
  11. Li, R., Nasri, N. M., & Li, Z. (2024). Research of blended teaching strategies based on heutagogy, cybergogy and peeragogy: A systematic literature review. International Journal of Future Education and Advances, 1(1), 85–101. https://www.masree.info/wp-content/uploads/2024/03/IJFEA-Article-10-1.pdf
  12. Li, Y., Fang, Q., & Shao, J. (2025). Impact of video quality in online learning on anxiety and motivation: A randomized controlled trial among medical students. BMC Medical Education, 25, 257. https://doi.org/10.1186/s12909-025-06795-7
  13. Liu, I. F., Hung, H. C., & Liang, C. T. (2023). A study of programming learning perceptions and effectiveness under a blended learning model with live streaming: Comparisons between full-time and working students. Interactive Learning Environments, 32(8), 4396–4410. https://doi.org/10.1080/10494820.2023.2198586
  14. McKay, J., & Sridharan, B. (2024). Student perceptions of collaborative group work (CGW) in higher education. Studies in Higher Education, 49(2). https://doi.org/10.1080/03075079.2023.2227677
  15. Ministry of Education of the People’s Republic of China. (2024). 2023 National Education Development Statistics Bulletin. https://www.moe.gov.cn/jyb_sjzl/sjzl_fztjgb/202410/t20241024_1159002.html
  16. Moayeri, M., Nami, K., Rahmani, M., & Abedini, M. (2023). Structural modeling of the enhancement of the electronic professional learning environment for managers (case study: Bandar Abbas Oil Refinery). International Journal of Innovation Management and Organizational Behavior, 3(4), 28–35. https://doi.org/10.61838/kman.ijmob.3.4.4
  17. Mundia, L., Jawawi, R., Hamid, M. H. S. A., & Zakir, N. (2021). Comparison of the motivation and learning strategies of brunei secondary students in forms 1-5 (Years 7-11): Implications for teaching. Anatolian Journal of Education, 6(2), 173-192. https://doi.org/10.29333/aje.2021.6213a
  18. Pintrich, P. R. (1991). A manual for the use of the Motivated Strategies for Learning Questionnaire (MSLQ). University of Michigan.
  19. Pintrich, P. R., Smith, D. A. F., Garcia, T., & McKeachie, W. J. (1993). Predictive validity and reliability of the Motivated Strategies for Learning Questionnaire (MSLQ). Educational and Psychological Measurement, 53(3), 801–813. https://doi.org/10.1177/0013164493053003024
  20. Polrak, M., Kedcham, A., & Chansri, C. (2024). Metacognitive Learning Strategies and English Language Proficiency of EFL Undergraduate Science Students: The Mediating Role of Self-Efficacy. PASAA: Journal of Language Teaching and Learning in Thailand, 69, 195-231.
  21. State Council of the People’s Republic of China. (2025, July 18). State Council executive meeting reviews and adopts the “Opinions on Improving National Student Loan Work.” Central People’s Government of the People’s Republic of China. https://www.gov.cn/zhengce/202507/content_7032288.htm
  22. Stanton, J. D., Sebesta, A. J., & Dunlosky, J. (2021). Fostering metacognition to support student learning and performance. CBE—Life Sciences Education, 20(2), fe3. https://doi.org/10.1187/cbe.20-12-0289
  23. Smucker, A. D. and Nuss, S. M. (2022). Enhancing Collaborative Learning Through Design for Learning.  The William & Mary Educational Review, 8(1). https://scholarworks.wm.edu/wmer/vol8/iss1/1
  24. Tipton, E. (2013). Stratified sampling using cluster analysis: A sample selection strategy for improved generalizations from experiments. Evaluation Review, 37(2), 109–139. https://doi.org/10.1177/0193841X13516324
  25. Tong, F., Guo, H., Wang, Z., & Min, Y. (2017). A comparative empirical study on college students’ motivation and strategies in learning professional courses. Advances in Psychology, 7(12), 1462–1472. https://doi.org/10.12677/ap.2017.712180
  26. Wang, G., & Wang, Z. (2023). Vocational education: A poor second choice? A comparison of the labour market outcomes of academic and vocational graduates in China. Oxford Review of Education, 49(3), 408–427. https://doi.org/10.1080/03054985.2022.2096583
  27. Wang, S. (2023). Exploration of undergraduate vocational education in China: Process, experience and strategy. Journal of Education and Training Studies, 11(4), 83–98. https://EconPapers.repec.org/RePEc:rfa:jetsjl:v:11:y:2023:i:4:p:83-98
  28. Wang, X., Zhou, Z., & Wu, C. (2025). Enhancing vocational students’ identities through program-occupation-skill alignment and learning experiences: A mediation analysis based on learning experiences. Vocation, Technology & Education, 2(1). https://doi.org/10.54844/vte.2025.0888
  29. Wu, S., Duan, J., & Luo, M. (2024). Evaluating and analyzing student labor literacy in China’s higher vocational education: An assessment model approach. Frontiers in Education, 9, 1361224. https://doi.org/10.3389/feduc.2024.1361224
  30. Xue, E., & Li, J. (2021). Cultivating high-level innovative talents by integration of science and education in China: A strategic policy perspective. Educational Philosophy and Theory, 54(9), 1419–1430. https://doi.org/10.1080/00131857.2021.1918545
  31. Yan, J., Wen, K., & Li, L. (2019). Effects of Summer Transportation Institute on Minority High School Students’ Perception on STEM Learning. Journal of STEM Education: Innovations and Research, 20(2), 58-64.
  32. Yu, T., Yan, X., & Jin, Y. (2024). Vocational education in China. In Z. Feng, Q. Wang, N. Liu, Education in China and the World: National Development and Global Benchmarking (pp. 361–418). Springer. https://doi.org/10.1007/978-981-97-7415-9_8.
  33. Zimmerman, B. J. (2002). Becoming a self-regulated learner: An overview. Theory Into Practice, 41(2), 64–70. https://doi.org/10.1207/s15430421tip4102_2

Tools


Copyright © 2026  KITE Digital Educational Solutions |  Exclusively distributed by CE-Logic