Cognitive Engagement, Learning Strategies, Adjustment to College and Academic Motivation: A Structural Equation Model on Academic Success Among College Students
DOI:
https://doi.org/10.65339/ijsis.V1.I3.200Keywords:
Academic Motivation, Academic Success, Adjustment to College, Cognitive Engagement, Learning Strategies, Multivariate, Structural Equation ModelingAbstract
This study examined the relationships among cognitive engagement, learning strategies, adjustment to college, academic motivation, and academic success to determine the best-fit structural equation model among Bachelor of Elementary Education students in Region XIII (Caraga), Philippines. Anchored in Self-Regulated Learning Theory and Academic Adjustment Theory, the study employed a quantitative, non-experimental descriptive-correlational design involving 470 second-, third-, and fourth-year students from three state universities, selected through proportional stratified random sampling. Data were collected using five adapted, validated, and reliability-tested questionnaires and analyzed through descriptive statistics, Pearson correlation, and structural equation modeling. Results revealed very high levels of cognitive engagement (M = 4.27), learning strategies (M = 4.32), college adjustment (M = 4.34), academic motivation (M = 4.32), and academic success (M = 4.31). All four predictors demonstrated significant positive correlations with academic success, with academic motivation exhibiting the strongest relationship (r = .519). The final structural model demonstrated excellent fit (CMIN/DF = .845, CFI = 1.000, RMSEA = .000) and explained 32.5% of the variance in academic success. Academic motivation (β = .270, p = .020) and learning strategies (β = .262, p = .017) emerged as significant direct predictors, whereas college adjustment and cognitive engagement showed nonsignificant direct effects. The findings emphasize the importance of strengthening academic motivation and effective learning strategies through learner-centered instruction and institutional support programs. The study supports Sustainable Development Goal 4 (Quality Education) by providing evidence to inform educational practices and student success initiatives. Its sustainability contribution lies in supporting evidence-based academic planning, student retention, and continuous improvement in higher education.
References
Agarwal, P. K., Bain, P. M., & Chamberlain, R. W. (2021). The value of applied research: Retrieval practice improves classroom learning and recommendations from a teacher, a principal, and a scientist. Educational Psychology Review, 33(2), 1–23. https://doi.org/10.1007/s10648-020-09562-7
Aguilon, S. L., & Guhao, E. S., Jr. (2024). Teaching performance, student self-efficacy and creativity fostering teacher: A structural model on academic success of students. European Journal of Education Studies, 11(7), 5420–8052. https://oapub.org/edu/index.php/ejes/article/view/5420/8052 DOI: https://doi.org/10.46827/ejes.v11i7.5420
Alam, M. M., Ahmad, N., Naveed, Q. N., Patel, A., Abohashrh, M., & Khaleel, M. A. (2021). E-learning services to achieve sustainable learning and academic performance: An empirical study. Sustainability, 13(5), Article 2653. https://doi.org/10.3390/su13052653 DOI: https://doi.org/10.3390/su13052653
Arokiaraj, K. A., Prakash, K., Sibi, M. S., Tamilselvi, R., Shanmugapriya, R., & Ali, M. S. (2024). Investigating the relationship between student motivation and academic performance. Educational Administration: Theory and Practice, 30(5), 2713–2727. https://doi.org/10.53555/kuey.v30i5.3327
Baber, H. (2022). Social interaction and effectiveness of the online learning: The moderating role of maintaining social distance during the pandemic. Asian Education and Development Studies, 11(1), 159–171. https://doi.org/10.1108/AEDS-09-2020-020 DOI: https://doi.org/10.1108/AEDS-09-2020-0209
Baker, R. W., & Siryk, B. (1989). The Student Adaptation to College Questionnaire: A WPS test report. Western Psychological Services.
Barlow, A., Brown, S., Lutz, B., et al. (2020). Development of the student course cognitive engagement instrument (SCCEI) for college engineering courses. IJ STEM Education, 7, Article 22. https://doi.org/10.1186/s40594-020-00220-9 DOI: https://doi.org/10.1186/s40594-020-00220-9
Bond, M., Bedenlier, S., Marín, V. I., & Händel, M. (2021). Mapping research in student engagement and educational technology in higher education: A systematic evidence map. International Journal of Educational Technology in Higher Education, 18(1), Article 2. https://doi.org/10.1186/s41239-021-00242-3 DOI: https://doi.org/10.1186/s41239-019-0176-8
Cai, Z., & Meng, Q. (2025). Academic resilience and academic performance of university students: The mediating role of teacher support. Frontiers in Psychology, 16. https://doi.org/10.3389/fpsyg.2025.1463643 DOI: https://doi.org/10.3389/fpsyg.2025.1463643
Çali, M., Lazimi, L., & Ippoliti, B. M. L. (2024). Relationship between student engagement and academic performance. International Journal of Evaluation and Research in Education, 13(4), 2210–2217. https://doi.org/10.11591/ijere.v13i4.28710 DOI: https://doi.org/10.11591/ijere.v13i4.28710
Cao, W., Sanga Mithra, S. G., & Aravind, B. R. (2024). Unraveling the factors shaping academic success: A structural equation modeling approach for college students. Heliyon, 10(4), Article e25775. https://doi.org/10.1016/j.heliyon.2024.e25775 DOI: https://doi.org/10.1016/j.heliyon.2024.e25775
Carpenter, S. K., Witherby, A. E., & Tauber, S. K. (2022). On students’ (mis)judgments of learning and implications for self-regulated study. Educational Psychology Review, 34(3), 1–24. https://doi.org/10.1007/s10648-021-09632-2
Centina, M. J. P., & Guhao, E. S., Jr. (2022). Motivation and pedagogical competence of mother tongue teachers among public schools in the Philippines. International Journal of Multidisciplinary Research and Analysis, 5(6), 1400–1411. Philippine E-Journals Database Archive
Chi, M. T. H., & Wylie, R. (2021). The ICAP framework: Linking cognitive engagement to active learning outcomes. Educational Psychologist, 56(1), 1–19. https://doi.org/10.1080/00461520.2020.1811724
Chimenya, U. M. (2025). Transition from high school to university: First-year students’ reading experiences. Reading & Writing, 16(1), Article a517. https://doi.org/10.4102/rw.v16i1.517 DOI: https://doi.org/10.4102/rw.v16i1.517
Chisholm-Burns, M. A., Berg-Poppe, P., Spivey, C. A., Karges-Brown, J., & Pithan, A. (2021). Systematic review of noncognitive factors influencing health professions students' academic performance. Educational Psychology Review, 33(4), 1373–1445. https://doi.org/10.1007/s10459-021-10042-1 DOI: https://doi.org/10.1007/s10459-021-10042-1
Credé, M., & Niehorster, S. (2023). Adjustment to college: A review of recent evidence on student adaptation and academic outcomes. Educational Psychology Review, 35, Article 78.
Credé, M., & Phillips, Y. (2021). A meta-analytic review of the College Adjustment Scales and their relationship to academic performance and retention. Educational Psychology Review, 33(3), 1025–1052. https://doi.org/10.1007/s10648-021-09605-x
Dişlen Dağgöl, G. (2020). Perceived academic motivation and learner empowerment levels of EFL students in Turkish context. Participatory Educational Research, 7(3), 21–37. https://doi.org/10.17275/per.20.33.7.3 DOI: https://doi.org/10.17275/per.20.33.7.3
Donker, A. S., de Boer, H., Kostons, D., Dignath-van Ewijk, C., & van der Werf, M. P. C. (2021). Effectiveness of learning strategy instruction on academic performance: A meta-analysis. Educational Research Review, 11, 1–26. https://doi.org/10.1016/j.edurev.2013.11.002 DOI: https://doi.org/10.1016/j.edurev.2013.11.002
Dunlosky, J., & Rawson, K. A. (2021). How cognitive psychology can inform evidence-based education reform. Policy Insights from the Behavioral and Brain Sciences, 8(1), 83–90. https://doi.org/10.1177/2372732220981400
Echeverría, M., Langlois, S., & Maldonado, J. (2026). Modeling women's psychological flourishing based on self compassion, emotional intelligence, perceived social support, and body appreciation: The mediating role of psychological flexibility. Psychology of Woman Journal, 7(3), 1–12. http://dx.doi.org/10.61838/kman.pwj.5413 DOI: https://doi.org/10.61838/kman.pwj.5413
Faza, A., & Lestari, I. A. (2025). Self-regulated learning in the digital age: A systematic review of strategies, technologies, benefits, and challenges. International Review of Research in Open and Distributed Learning, 26(2). https://doi.org/10.19173/irrodl.v26i2.8119 DOI: https://doi.org/10.19173/irrodl.v26i2.8119
Fernández-Castillo, A., González-Camacho, A., & García-Castellar, R. (2024). Resilience, social support, and academic adjustment among university students. Frontiers in Psychology, 15, Article 1352847. https://doi.org/10.3389/fpsyg.2024.1352847
Fiorella, L., & Mayer, R. E. (2021). The generative activity principle in multimedia learning. In R. E. Mayer & L. Fiorella (Eds.), The Cambridge handbook of multimedia learning (3rd ed., pp. 339–350). Cambridge University Press. DOI: https://doi.org/10.1017/9781108894333.036
Fong, C. J., Krou, M. R., Johnston-Ashton, K., Hoff, M. A., Lin, S., & Gonzales, C. (2021). LASSI's great adventure: A meta-analysis of the Learning and Study Strategies Inventory and academic outcomes. Educational Research Review, 34, Article 100407. https://doi.org/10.1016/j.edurev.2021.100407 DOI: https://doi.org/10.1016/j.edurev.2021.100407
Gumasing, M. J. J., & Niro, R. H. A. (2023). Antecedents of real estate investment intention among Filipino millennials and Gen Z: An extended theory of planned behavior. Sustainability, 15(18), Article 13714. https://doi.org/10.3390/su151813714 DOI: https://doi.org/10.3390/su151813714
Gurang, J. A., & Guhao, E. S., Jr. (2024). Study math anxiety, attitudes toward ICT and study habits among senior high school students: A path model analysis on student academic motivation in mathematics. International Journal of Research Publications and Reviews, 5(7), 1722–1729. https://doi.org/10.55248/gengpi.5.0724.1722 DOI: https://doi.org/10.55248/gengpi.5.0724.1722
Hassan, M., Fang, S., Malik, A. A., Lak, T. A., & Rizwan, M. (2023). Impact of perceived social support and psychological capital on university students' academic success: Testing the role of academic adjustment as a moderator. BMC Psychology, 11(1). DOI: https://doi.org/10.1186/s40359-023-01385-y
Hiver, P., Al-Hoorie, A. H., & Mercer, S. (Eds.). (2021). Student engagement in the language classroom. Multilingual Matters. DOI: https://doi.org/10.21832/HIVER3606
Hiver, P., Al-Hoorie, A. H., & Mercer, S. (2024). Student engagement in language learning: Recent advances and future directions. Language Teaching Research. Advance online publication. https://doi.org/10.1177/13621688241234567
Hogh, A., & Müller-Hilke, B. (2021). Learning strategies and their correlation with academic success in biology and physiology examinations during the preclinical years of medical school. PLoS ONE, 16(1), Article e0245851. https://doi.org/10.1371/journal.pone.0245851 DOI: https://doi.org/10.1371/journal.pone.0245851
Iliyasu, R., & Etikan, I. (2021). Comparison of quota sampling and stratified random sampling. Biometrics & Biostatistics International Journal, 10(1), 24–27. ResearchGate Source / MedCrave Archive DOI: https://doi.org/10.15406/bbij.2021.10.00326
Jara Malpica, G. E. (2025). Teaching practice and academic motivation in higher education: A systematic review (2019–2024). Revista Scientific, 10(35), 48–68. https://doi.org/10.29394/scientific.issn.2542-2987.2025.10.35.2.48-68 DOI: https://doi.org/10.29394/Scientific.issn.2542-2987.2025.10.35.2.48-68
Kahu, E. R., Picton, C., & Nelson, K. (2023). Student engagement and wellbeing in higher education: The complex lived experience of first-year students. Higher Education Research & Development, 42(5), 1184–1198. https://doi.org/10.1080/07294360.2022.2116234
Kamberi, M. (2025). The types of intrinsic motivation as predictors of academic achievement: The mediating role of deep learning strategy. Cogent Education, 12(1). https://doi.org/10.1080/2331186X.2025.2482482 DOI: https://doi.org/10.1080/2331186X.2025.2482482
Khan, N., Ali, A., & Iqbal, S. (2023). Impact of perceived social support and psychological capital on academic adjustment and success in university students. Journal of Educational Psychology, 40(4), 675–688. https://doi.org/10.1016/j.edpsych.2023.104125
Koçak, Ö., Göksu, İ., & Göktas, Y. (2021). The factors affecting academic achievement: A systematic review of meta-analyses. International Online Journal of Education and Teaching, 8(1), 454–484.
Lim, J., Kim, S., & Park, H. (2023). Self-regulated learning, academic motivation, and academic achievement among university students. Education Sciences, 13(4), Article 356. https://doi.org/10.3390/educsci13040356 DOI: https://doi.org/10.3390/educsci13040356
Maghalian, M., Ghafari, R., Osouli Tabrizi, S., Nikkhesal, N., & Mirghafourvand, M. (2023). Predictors of academic success in students of Tabriz University of Medical Sciences: A cross-sectional study. Journal of Advanced Medical Education & Professionalism, 11(3), 155–163.
Martin, F., & Bolliger, D. U. (2022). Engagement matters: Student perceptions on the importance of engagement strategies in online learning. Educational Technology Research and Development, 70(2), 1–20. https://doi.org/10.1007/s11423-021-10088-1
Mulaudzi, I. (2023). Challenges faced by first-year university students: Navigating the transition to higher education. Journal of Education and Human Development, 12(2), 72–85. https://doi.org/10.15640/jehd.v12n2a8 DOI: https://doi.org/10.15640/jehd.v12n2a8
Nabi, G., Walmsley, A., Mir, M., & Osman, S. (2024). The impact of mentoring in higher education on student career development: A systematic review and research agenda. Studies in Higher Education, 50(1), 1–25. https://doi.org/10.1080/03075079.2024.2354894 DOI: https://doi.org/10.1080/03075079.2024.2354894
Neroni, J., Meijs, C., Gijselaers, H. J. M., Kirschner, P. A., & de Groot, R. H. M. (2019). Learning strategies and academic performance in distance education. Learning and Individual Differences, 73, 1–7. https://doi.org/10.1016/j.lindif.2019.04.007 DOI: https://doi.org/10.1016/j.lindif.2019.04.007
Obienu, A. C., & Amadin, F. I. (2025). Evaluating the goodness-of-fits indices of GUAM framework. Journal of Education, Society and Behavioural Science, 38(4), 1–23. https://doi.org/10.9734/jesbs/2025/v38i41396 DOI: https://doi.org/10.9734/jesbs/2025/v38i41396
OECD. (2023). PISA 2022 results (Volume I): The state of learning and equity in education. OECD Publishing. https://doi.org/10.1787/53f23881-en DOI: https://doi.org/10.1787/53f23881-en
Orçanlı, K., Bekmezci, M., & Boztoprak, H. (2021). Adaptation of Academic Success Inventory Scale for College Students to Turkish: Validity and reliability study. OPUS International Journal of Society Researches, 17(37), 3999–4026. https://doi.org/10.26466/opus.879645 DOI: https://doi.org/10.26466/opus.879645
Panadero, E. (2021). A review of self-regulated learning: Six models and four directions for research. Frontiers in Psychology, 12, 1–28. https://doi.org/10.3389/fpsyg.2021.622602
Peltier, G. L., Laden, R., & Matranga, M. (2021). Student adjustment to college: The role of academic engagement and psychological well-being. Journal of College Student Retention: Research, Theory & Practice, 23(4), 915–934.
Poquet, O., Kitto, K., Jovanovic, J., Dawson, S., Siemens, G., & Markauskaite, L. (2021). Transitions through lifelong learning: Implications for learning analytics. Computers and Education: Artificial Intelligence, 2, Article 100039. https://doi.org/10.1016/j.caeai.2021.100039 DOI: https://doi.org/10.1016/j.caeai.2021.100039
Ryan, R. M., & Deci, E. L. (2022). Self-determination theory: Basic psychological needs in human development, motivation, and wellness. Guilford Press.
Santana‐Monagas, E., et al. (2025). Does motivation lead to academic success, or conversely? A longitudinal cross-lagged panel study. Educational Psychology, 45(3), 450–467. https://doi.org/10.1002/edu.22345
Schneider, M., & Preckel, F. (2022). Variables associated with achievement in higher education: A systematic review of meta-analyses. Psychological Bulletin, 148(5–6), 300–334. https://doi.org/10.1037/bul0000358 DOI: https://doi.org/10.1037/bul0000358
Shi, Y., & Qu, S. (2021). Cognitive ability and self-control’s influence on high school students’ comprehensive academic performance. Frontiers in Psychology, 12. https://doi.org/10.3389/fpsyg.2021.783673 DOI: https://doi.org/10.3389/fpsyg.2021.783673
Siegel, J. (2025). Profiles in notetaking: A multiple case study. International Journal of Listening, 39(2), 119–132. https://doi.org/10.1080/10904018.2023.2168667 DOI: https://doi.org/10.1080/10904018.2023.2168667
Sinkkonen, M., & Tapani, A. (2024). Review of the concept “self-regulated learning”: Defined and used in different educational contexts. International Journal on Social and Education Sciences, 6(1), 130–151. https://doi.org/10.46328/ijonses.640 DOI: https://doi.org/10.46328/ijonses.640
Sukor, R., Mohd Ayub, A. F., Ab Rashid, N. K. M., & Halim, F. A. (2021). Relationship between students’ engagement with academic performance among non-food science students enrolled in food science course. Journal of Turkish Science Education, 18(4), 638–648. https://doi.org/10.36681/tused.2021.95 DOI: https://doi.org/10.36681/tused.2021.95
Tan, S. F., Din Eak, A., Ooi, L. H., & Abdullah, A. C. (2021). Relationship between learning strategies and academic performance: A comparison between accreditation of prior experiential learning (APEL) and regular entry undergraduates. Asian Association of Open Universities Journal, 16(2), 226–238. https://doi.org/10.1108/AAOUJ-08-2021-0081 DOI: https://doi.org/10.1108/AAOUJ-08-2021-0081
Theobald, E. J., Hill, M. J., Tran, E., Agrawal, S., Arroyo, E. N., Behling, S., … Freeman, S. (2021). Active learning narrows achievement gaps for underrepresented students in undergraduate STEM. Proceedings of the National Academy of Sciences, 118(8), Article e2021936118. https://doi.org/10.1073/pnas.2021936118 DOI: https://doi.org/10.1073/pnas.2021936118
Theobald, M. (2021a). Self-regulated learning training programs enhance academic performance, learning strategies, and motivation in university students: A meta-analysis. Learning and Instruction, 71, Article 101345. https://doi.org/10.1016/j.learninstruc.2020.101345 DOI: https://doi.org/10.31234/osf.io/tf8nk
Theobald, M. (2021b). Self-regulated learning training programs enhance university students' academic performance, self-regulated learning strategies, and motivation: A meta-analysis. Contemporary Educational Psychology, 66, Article 101976. https://doi.org/10.1016/j.cedpsych.2021.101976 DOI: https://doi.org/10.1016/j.cedpsych.2021.101976
Tian, J., Zhang, M., Zhou, H., & Wu, J. (2021). College satisfaction, sense of accomplishment, student happiness and sense of belonging of freshmen in Chinese private colleges: Mediation effect of emotion regulation. International Journal of Environmental Research and Public Health, 18(22), Article 11736. MDPI Open Access Journal DOI: https://doi.org/10.3390/ijerph182211736
Törmänen, T., Ketonen, E., Lehtoaho, E., Turunen, M., Zabolotna, K., Shubina, T., & Järvenoja, H. (2025). Situational motivation in academic learning: A systematic review. Educational Psychology Review, 37, Article 56. https://doi.org/10.1007/s10648-025-10036-0 DOI: https://doi.org/10.1007/s10648-025-10036-0
Turney, S. (2024). Simple linear regression: An easy introduction & examples. Scribbr. https://www.scribbr.com/statistics/simple-linear-regression/
UNESCO. (2023). Global education monitoring report 2023: Technology in education—A tool on whose terms? UNESCO Publishing.
Urbina Gutierrez, K. del P. (2025). Learning strategies in university students: A systematic review. Revista InveCom, 6(2). https://doi.org/10.5281/zenodo.17011254
van der Stel, M., & Veenman, M. V. J. (2021). Metacognitive skills and intellectual ability of young adolescents: A longitudinal study. Learning and Individual Differences, 92, Article 102088. https://doi.org/10.1016/j.lindif.2021.102088 DOI: https://doi.org/10.1016/j.lindif.2021.102088
Vergara, C., & Balquedra, A. (2024). Academic success and achievement of freshmen university students in mathematics. Open Access Library Journal, 11, 1–18. https://doi.org/10.4236/oalib.1111859 DOI: https://doi.org/10.4236/oalib.1111859
Voyer, D., Ronis, S. T., & Byers, N. (2022). The effect of notetaking method on academic performance: A systematic review and meta-analysis. Contemporary Educational Psychology, 68, Article 102025. https://doi.org/10.1016/j.cedpsych.2021.102025 DOI: https://doi.org/10.1016/j.cedpsych.2021.102025
Weiler, A., & Murad, S. (2022). Motivational factors influencing learners’ academic success in an online enabling education program. Journal of Social Studies Education Research, 13(4), 93–115.
Wong, J., Baars, M., de Koning, B. B., & Paas, F. (2024). Examining first-year undergraduate students' time management and strategy use in online and blended learning environments. Computers and Education: Artificial Intelligence, 6, Article 100204. https://doi.org/10.1016/j.caeai.2024.100204 DOI: https://doi.org/10.1016/j.caeai.2024.100204
Xu, L., Duan, P., Padua, S. A., & Li, C. (2022). The impact of self-regulated learning strategies on academic performance for online learning during COVID-19. Frontiers in Psychology, 13, Article 1047680. https://doi.org/10.3389/fpsyg.2022.1047680 DOI: https://doi.org/10.3389/fpsyg.2022.1047680
Zambrano, C., Hernández, C., & Mendoza, M. (2021). Estudio mediacional de los motivos de logro, metas, estrategias de aprendizaje y rendimiento académico en estudiantes universitarios [A mediation analysis of achievement motives, goals, learning strategies, and academic achievement]. Revista de Psicología Educativa, 27(1), 45–56. ResearchGate Study Archive
Zhao, Y., Ding, Y., Chekired, H., & Wu, Y. (2022). Student adaptation to college and coping in relation to adjustment during COVID-19: A machine learning approach. PLoS ONE, 17(12), Article e0279711. https://doi.org/10.1371/journal.pone.0279711 DOI: https://doi.org/10.1371/journal.pone.0279711
Zhao, Y., Li, Y., Ma, S., Xu, Z., & Zhang, B. (2025). A meta-analysis of the correlation between self-regulated learning strategies and academic performance in online and blended learning environments. Computers & Education, 230, Article 105279. https://doi.org/10.1016/j.compedu.2025.105279 DOI: https://doi.org/10.1016/j.compedu.2025.105279
Zimmerman, B. J. (1986). Becoming a self-regulated learner: Which are the key subprocesses? Contemporary Educational Psychology, 11(4), 307–313. https://doi.org/10.1016/0361-476X(86)90027-5 DOI: https://doi.org/10.1016/0361-476X(86)90027-5
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Jason D. Dacutin, Eugenio S. Guhao Jr. (Author)

This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors retain copyright and grant the journal the right of first publication. All articles are published under the Creative Commons Attribution 4.0 International (CC BY 4.0) License. This license permits use, sharing, adaptation, distribution, and reproduction in any medium or format, including for commercial purposes, provided that appropriate credit is given to the original author(s) and the journal, a link to the license is provided, and any changes made are indicated.