Assessment of Students Academic Performance Using Metacognitive Skills, Learning Motivation, Learning Strategies, Scientific Literacy and Problem-Solving Skills as Indicators: An Evaluation
DOI:
https://doi.org/10.65339/ijsair.V2.I2.524Keywords:
Academic Achievement, Allied Medical Sciences, Learning Motivation, Learning Strategies, Metacognition, Problem-Solving Skills, Science Achievement, Scientific Literacy, Self-Regulated LearningAbstract
This study examined the relationships among metacognition, learning strategies, learning motivation, problem-solving skills, and scientific literacy among Allied Medical Sciences students in Cabanatuan City. Anchored on Flavell’s Theory of Metacognition, Eccles and Wigfield’s Expectancy-Value Theory, and the concept of scientific literacy discussed by Norris & Phillips (2003), Kuhn (2011), and Morling (2021), the study investigated how cognitive and motivational factors influence academic performance in science-related disciplines. A descriptive–correlational research design was employed involving 328 Allied Medical Sciences students enrolled in nursing, medical laboratory science, public health, psychology, and related programs. Data were collected using validated instruments, including the Metacognitive Skills Scale (MSS), Learning Strategy Questionnaire, Science Motivation Questionnaire II (SMQ-II), scientific literacy assessment, and Problem-Solving Skills Scale. Data analysis utilized descriptive statistics and Pearson correlation coefficients through SPSS and AMOS. Findings revealed that respondents demonstrated high levels of learning strategies, while learning motivation and problem-solving skills were at moderate levels. Metacognition showed moderate positive relationships with learning strategies (r = 0.41), learning motivation (r = 0.44), and problem-solving skills (r = 0.48), indicating that students with stronger metacognitive awareness tend to employ more effective learning behaviors and analytical skills. In contrast, scientific literacy exhibited very weak relationships with learning strategies, motivation, problem-solving skills, and metacognition. The study concluded that metacognition and learning motivation play important roles in enhancing science achievement and self-regulated learning among Allied Medical Sciences students. The study recommends strengthening reflective learning activities, inquiry-based instruction, motivational support, and learner-centered strategies to improve academic performance and professional preparedness. The study supports Sustainable Development Goal (SDG) 4: Quality Education by promoting effective learning processes and scientific literacy among Allied Medical Sciences students. It also aligns with SDG 3: Good Health and Well-Being through the development of competent future healthcare professionals capable of evidence-based decision-making. The sustainability impact of the study lies in its contribution to educational and public health sustainability by supporting curriculum improvement, learner development, and workforce preparedness in allied medical and health-related fields. Strengthening metacognitive and analytical competencies may contribute to long-term institutional effectiveness and improved healthcare practice.
References
Altindag, M., & Senemoglu, N. (2013). Metacognitive Skills Scale. Hacettepe Universitesi Egitim Fakultesi Dergisi [H.U. Journal of Education].
Calma, A. (2025). Students’ problem-solving skills in depth: Ready for “real life”? The International Journal of Management Education, 23(3). Elsevier. https://doi.org/10.1016/j.ijme.2025.101267
Eccles, J. S., & Wigfield, A. (2020). From expectancy-value theory to situated expectancy-value theory: A developmental, social cognitive, and sociocultural perspective on motivation. Contemporary Educational Psychology, 101859. https://doi.org/10.1016/j.cedpsych.2020.101859
Flavell, J. H. (1976). Metacognitive aspects of problem solving. In L. B. Resnick (Ed.), The nature of intelligence (pp. 231–236). Erlbaum.
Flavell, J. H. (1979). Metacognition and cognitive monitoring: A new area of cognitive developmental inquiry. American Psychologist, 34(10), 906–911.
Fleur, D. S., et al. (2025). Neural correlates of metacognition in education: A machine learning approach. Neuropsychologia, 219. Elsevier. https://doi.org/10.1016/j.neuropsychologia.2025.109265
Kuhn, D. (2011). What is scientific thinking and how does it develop? In U. Goswami (Ed.), The Wiley-Blackwell handbook of childhood cognitive development (2nd ed., pp. 497–523). Wiley-Blackwell.
Minh Ton, D. N., et al. (2025). Learning strategies of nursing students and correlation with study habit and academic performance. Teaching and Learning in Nursing, 20(4). Elsevier. https://doi.org/10.1016/j.teln.2025.04.013
Morling, B. (2021). Research methods in psychology (4th ed.). W.W. Norton & Company.
Norris, S. P., & Phillips, L. M. (2003). How literacy in its fundamental sense is central to scientific literacy. Science Education, 87(2), 224–240.
OECD. (2019). PISA 2018 assessment and analytical framework. OECD Publishing. https://doi.org/10.1787/b25efab8-en
Otermans, P. C. J., et al. (2025). Motivation is key: Exploring the role of motivation on learning approaches. Learning Research and Practice. https://doi.org/10.1080/23735082.2025.2536502
Sawyer, R. K. (2021). The Cambridge handbook of the learning sciences (3rd ed.). Cambridge University Press. https://doi.org/10.1017/9781108888295
Turiman, P., Omar, J., Daud, A. M., & Osman, K. (2012). Fostering the 21st century skills through scientific literacy and science process skills. Procedia - Social and Behavioral Sciences, 59, 110–116. https://doi.org/10.1016/j.sbspro.2012.09.253
