The Influence of Student Motivation and Learning Strategy on Learning Outcomes in Science
DOI:
https://doi.org/10.65339/ijsair.V2.I3.699Keywords:
Cognitive Strategies, Grade 10 Students, Learning Outcomes, Learning Strategies, Resource Management, Science Education, Student MotivationAbstract
This study examined the influence of student motivation and learning strategies on the science learning outcomes of Grade 10 students in selected public secondary schools in the Pantukan North District, Davao de Oro. Anchored on Zimmerman's Self-Regulated Learning Theory, Pintrich's Model of Motivated Learning, and Self-Determination Theory, the study employed a quantitative non-experimental descriptive-correlational design with regression analysis. Data were collected from 259 Grade 10 students selected through stratified random sampling using the adapted Motivation to Achieve Questionnaire (MAQ), the adapted Motivated Strategies for Learning Questionnaire (MSLQ), and students' official third-quarter science grades. Descriptive statistics, Pearson Product-Moment Correlation, and multiple regression analysis were used to analyze the data. The findings revealed that respondents demonstrated high levels of student motivation and learning strategy use and achieved very satisfactory science learning outcomes. Student motivation and learning strategies were both positively and significantly related to science learning outcomes. Regression analysis further showed that striving for excellence was the strongest predictor among the motivation domains, while resource management was the strongest predictor among the learning strategy domains. These findings indicate that motivated learners who effectively apply learning strategies are more likely to achieve higher academic performance in science. The study recommends strengthening students' motivation and strategic learning through learner-centered instructional practices, explicit instruction in effective study strategies, and professional development programs that enhance teachers' capacity to support student motivation and learning. The study supports Sustainable Development Goal (SDG) 4: Quality Education by providing evidence that can improve science instruction and learner achievement, and SDG 9: Industry, Innovation and Infrastructure by promoting scientific literacy, critical thinking, and problem-solving skills essential for innovation. Its findings contribute to educational, institutional, and socio-economic sustainability by informing evidence-based instructional practices that foster improved science learning outcomes.
References
Acosta-Gonzaga, E., & Ramirez-Arellano, A. (2021). The influence of motivation, emotions, cognition, and metacognition on students’ learning performance. SAGE Open, 11(2), 1–12. https://doi.org/10.1177/21582440211027561
Akpur, U. (2021). The predictive level of cognitive and metacognitive strategies on academic achievement. International Journal of Research in Education and Science, 7(3), 593–607. https://doi.org/10.46328/ijres.1444
Bernardo, A. B. I. (2020). Motivation and learning strategies in Philippine education: Implications for academic achievement. Philippine Journal of Psychology, 53(1), 23–45.
Department of Education. (2016). K to 12 curriculum guide: Science. https://www.deped.gov.ph
Department of Science and Technology–Science Education Institute. (2011). Science education in the Philippines: Challenges and opportunities.
Dent, A. L., & Koenka, A. C. (2016). The relation between self-regulated learning and academic achievement across childhood and adolescence: A meta-analysis. Educational Psychology Review, 28(3), 425–474. https://doi.org/10.1007/s10648-015-9320-8
Donoghue, G. M., & Hattie, J. (2021). A meta-analysis of ten learning techniques. Frontiers in Education, 6, 581216. https://doi.org/10.3389/feduc.2021.581216
Dudovskiy, J. (2018). Positivism—Research methodology. https://research-methodology.net
Foadi, N., Koop, C., Mikuteit, M., Paulmann, V., Steffens, S., & Behrends, M. (2021). Defining learning outcomes as a prerequisite of implementing a longitudinal and transdisciplinary curriculum. Journal of Medical Education and Curricular Development, 8, 1–9. https://doi.org/10.1177/23821205211028347
Gay, L. R., Mills, G. E., & Airasian, P. (2011). Educational research: Competencies for analysis and applications. Pearson.
Howard, J. L., Bureau, J. S., Guay, F., Chong, J. X. Y., & Ryan, R. M. (2021). Student motivation and associated outcomes: A meta-analysis from self-determination theory. Perspectives on Psychological Science, 16(6), 1300–1323. https://doi.org/10.1177/1745691620966789
Jamaluddin, N. S., Abd. Kadir, S., Alias, S. N., & Abdullah, A. (2021). A review of learning strategies towards learning outcome. International Journal of Social Science and Human Research, 4(12), 3647–3651. https://doi.org/10.47191/ijsshr/v4-i12-26
Koyuncuoğlu, Ö. (2021). An investigation of academic motivation and career decidedness. International Journal of Research in Education and Science, 7(1), 125–143. https://doi.org/10.46328/ijres.1694
Liem, G. A. D., & McInerney, D. M. (2021). Achievement and motivation. Educational Psychology, 41(4), 379–382. https://doi.org/10.1080/01443410.2021.1924475
Lisá, E., Sokolová, L., Jablonická, P., & Kardelisová, L. (2023). Motivation to succeed is not enough. Frontiers in Psychology, 14, 1119409. https://doi.org/10.3389/fpsyg.2023.1119409
Mendoza, W., Ramírez, G. M., González, C., & Moreira, F. (2022). Assessment of curriculum design by learning outcomes. Education Sciences, 12(8), 541. https://doi.org/10.3390/educsci12080541
Nauzeer, S., & Jaunky, V. C. (2021). A meta-analysis of motivation and academic performance. Pedagogical Research, 6(3), Article em0097. https://doi.org/10.29333/pr/10963
Organisation for Economic Co-operation and Development. (2019). PISA 2018 results (Volume I): What students know and can do. https://doi.org/10.1787/5f07c754-en
Öztürk, E., Kardaş, M., Sapmaz, A., Dönmez, U., Şahin, İ., & Çölkesen, A. (2022). The place of education in social development. Educational Research and Reviews, 17(8), 209–212.
Richardson, M., Abraham, C., & Bond, R. (2012). Psychological correlates of academic performance. Psychological Bulletin, 138(2), 353–387. https://doi.org/10.1037/a0026838
Robbins, S. B., Lauver, K., Le, H., Davis, D., Langley, R., & Carlstrom, A. (2004). Do psychosocial and study skill factors predict college outcomes? Psychological Bulletin, 130(2), 261–288. https://doi.org/10.1037/0033-2909.130.2.261
Rone, N., Guao, N., Medardo, M., Jr., A., N., B., K., & Saro, J. (2023). Students’ lack of interest, motivation in learning, and classroom participation: How to motivate them? Educational Psychology, 7, 636–645. https://doi.org/10.5281/zenodo.7749977
Ryan, R. M., & Deci, E. L. (2000). Intrinsic and extrinsic motivations. Psychological Inquiry, 11(4), 227–268. https://doi.org/10.1207/S15327965PLI1104_01
Sinay, H., Wenno, I. H., Pulu, S. R., Untajana, S. E., & Dulhasyim, A. B. (2023). Factors affecting science learning outcomes. International Journal of Education, Information Technology, and Others, 6(2), 245–260. https://doi.org/10.5281/zenodo.7901708
Stanton, J. D., Sebesta, A. J., & Dunlosky, J. (2021). Fostering metacognition. CBE—Life Sciences Education, 20(2), Article fe3. https://doi.org/10.1187/cbe.20-12-0289
Sulaiman, M. M. (2021). Education and social change. International Journal of Applied Research, 7(2), 85–88.
Tan, A. (2025). Association between anxiety disorders and English academic writing performance among college students: The chain mediating role of learning motivation and metacognitive strategies. Psoriasis: Targets and Therapy, 18, 1319–1332.
Tan, S. F., Din, A. E., Ooi, L. H., & Abdullah, A. C. (2021). Learning strategies and academic performance. Asian Association of Open Universities Journal, 16(2), 226–238. https://doi.org/10.1108/AAOUJ-08-2021-0081
Theobald, M. (2021). Self-regulated learning training programs. Contemporary Educational Psychology, 66, 101976. https://doi.org/10.1016/j.cedpsych.2021.101976
Urdanivia Alarcón, D. A., Talavera-Mendoza, F., Rucano Paucar, F. H., Cayani Cáceres, K. S., & Machaca Viza, R. M. (2023). Inquiry-based teaching and learning in science. Frontiers in Education, 8, 1170487. https://doi.org/10.3389/feduc.2023.1170487
UNESCO. (2023). Measuring and monitoring learning outcomes. https://www.uis.unesco.org
van der Steen, J., van Schilt-Mol, T., van der Vleuten, C., & Joosten-ten Brinke, D. (2022). Supporting teachers in formative assessment. Frontiers in Education, 7, 925352. https://doi.org/10.3389/feduc.2022.925352
Veneracion, E. V. (2023). Students’ motivation and learning strategies on academic performance in science. Psychology and Education: A Multidisciplinary Journal. https://doi.org/10.5281/zenodo.10171150
Wu, C., Jing, B., Gong, X., Mou, Y., & Li, J. (2021). Learning strategies and academic emotions. Frontiers in Psychology, 12, 717683. https://doi.org/10.3389/fpsyg.2021.717683
Zimmerman, B. J., & Schunk, D. H. (2011). Handbook of self-regulation of learning and performance. Routledge.
