Causal Modeling of Cognitive Load, Teachers' Support-Services in Preparing For Test and Examination Malpractice on Achievement in Mathematics in Akwa Ibom State, Nigeria
Keywords:
Causal-modeling, cognitive load, teachers' support-services, test, examination malpractice, achievement in mathematicsAbstract
The study was aimed at developing a causal model of cognitive load, teachers' support services in preparing for test and examination malpractice on achievement in mathematics in Akwa Ibom State, Nigeria. The study was guided by two null hypotheses. A correlational survey research design was adopted for the study. The population of the study comprised 60,821 Junior Secondary Two (JS2) students in public secondary schools in Akwa Ibom State in the 2024/2025 academic year. A sample of 936 JS2 students in public secondary schools drawn using a multi-stage sampling procedure participated in the study. Four instruments: Mathematics Achievement Test (MAT), Students’ Cognitive Load questionnaire (SCLQ), Teachers’ Support Services in Test Preparation Questionnaire (TSTPQ), and Examination Malpractice Questionnaire (EMQ), developed by the researchers, were used for data collection. Three experts in relevant fields face-validated the instruments. The instruments were further subjected to construct validation through factor analysis. The reliability of the instruments was established using an estimate of internal consistency after trial-testing. Data obtained from the MAT was analysed using the Kuder-Richardson formula 20, which yielded a reliability coefficient of 0.83. The reliability for TCLQ, TSTPQ, and EMQ was determined using the Cronbach Alpha method, and the reliability coefficients obtained were 0.92, 0.86, and 0.85, respectively. Data collected from the actual study were analysed using a single-stage Partial Least Squares–Structural Equation Modeling (PLS-SEM) through Warp PLS, computer-based software. The findings of the study, among others, revealed that the most parsimonious causal model retained cognitive load dimensions (intrinsic, extraneous, and germane), teachers’ support services, and examination malpractice. Hence, it was recommended among others that schools should strengthen teachers-student interactions through structured mentorship, personalized instructional support, and guidance to improve students' mathematics achievement and reduce examination malpractice.
References
Agah, J. J., Utibe, U. J. & Fadip, A. N. (2022). Development and Standardization of Students’ Cognitive Load Rating Scale in Mathematics using Partial Credit Model Item Response Theory. African Journal of Science, Technology and Mathematics Education (AJSTME) Vol. 8(1), 467-473. http://www.ajstme.com.ng.
Al-Sarry, M. J., Majeed, B. & Kareem, S. K. (2022). Cognitive load of university students and its relationship to their academic achievement. European Journal of Humanities and Educational Advanced (EJHEA), 2(11), 62-68.
Altermatt, E. R. (2019). Academic support from peers as a predictor of academic self-efficacy among college students. Journal of College Student Retention: Research Theory & Practice, 21(1), 21–37.
Celik, H. E. & Yilmaz, V. (2013). Lisrel 9.1 SEM analysis. Ani Yayincilik.
Eugenia, C. (2020). Mathematician and Author. Albany: State University of New York Print.
Hair, J. F., Hult, G. T. M., Ringle, C. M. & Sarstedt, M. (2022). A primer on partial least squares structural equation modeling (PLS-SEM) (3rd ed.). SAGE Publications.
Henseler, J., Ringle, C M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modelling. Journal of the Academy of Marketing Science, 43(1), 115-135.
Johnson, P., Adekunle, O., & Musa, H. (2023). Cognitive-load and academic dishonesty: A multi-dimensional approach. Journal of Educational Psychology, 18(4), 123-141.
Kalyuga, S. (2019). Managing Cognitive Load in Adaptive Learning Systems. Journal of Educational Data Mining. 4(3), 206-212.
Knock, N. (2020). Wrap PLS User Manual: Version 7.0 Scriptwrapt System.
Marley, S. C., & Wilcox, M. J. (2021). Do family and peer academic social supports predict academic motivations and achievement of first-year college students? Journal of Applied Research in Higher Education, 14(3), 958–973.
Musa, K., & Aliyu, R. (2022). The role of cognitive-load in examination malpractice: A Nigerian perspective. Journal of African Educational Studies, 15(2), 35-49.
Nathan, N. A., Utibe, U. J., Agah, J. J. & Abasi, A. U. (2024). Causal Modeling of Cognitive-Load, Parents' Support-Services in Preparing for Test and Examination Malpractice on Achievement in Mathematics in Akwa Ibom State, Nigeria. Journal of Centre for Distance & e-Learning. 4(1), 120-137.
National Center for Education Statistics (2020). High school Longitudinal Study of 2009.
Nenty, H. J. & Umoinyang, I. E. (2004). Principles of Test Constructions. Calabar: University of Calabar Press.
Ogbu, S. & Anyaegbu, C. C. (2021). Content analysis of WAEC Chief Examiners reports on students’ weaknesses in May/June WASSCE Mathematics examination from 2008 to 2019. International Journal of Studies in Education, 17(1), 167-174.
Ojo, B., & Falade, A. (2023). Teacher-student relationships and academic integrity: Evidence from Nigerian secondary schools. International Journal of Educational Ethics, 12(2), 143-159.
Okafor, C., & Adekunle, T. (2022). Germane cognitive-load and student success in mathematics: A study of secondary school students. Journal of Cognitive Learning, 16(1), 52-69.
Olah, P. O. & Utibe, U. J. (2024). Guidance and Counselling Services, National Security Concern and Students’ Performance in Physics in Gwagwalada Area Council of FCT, Abuja, Nigeria. The Counsellor, Counselling Association of Nigeria (CASSON) 47(2), 230-243
Olatunji, E., & Ojo, F. (2023). The interplay of perseverance, test-taking strategies, and academic performance in mathematics. West African Journal of Educational Research, 18(3), 67-84.
Utibe, U. J., Nnaji, A. D. & Agah, J. J. (2024). Effectiveness of Technology-Based Classroom Testing on Students’ Academic Engagement in Geometry. Journal of Centre for Distance & e-Learning (JCDeL), 1(1), 26-41
Utibe, U. J., Nnaji, A. D., Adonu, I. I., Agah, J. J. & Nnaji, P. C. (2023). Online Formative Assessments and Undergraduates’ Psychomotor Skills. African Journal of Theory and Practice of Educational Assessment (AJTPEA). 12, 1-10
Wang, H., & Lin, J. (2023). The role of Teacher Support in Fostering Academic Success and Ethical behavior. Educational Leadership and Policy Studies, 9(4), 88-104.
Waters, L. E., Loton, D., & Jach, H. K. (2018). Does Strength-Based Parenting Predict Academic Achievement? The Mediating Effects of Persistence and Engagement. J Happiness Stud., 20, 1121-1140,
World Bank, Wold Development Report 2018
Yusuf, M., & Bello, R. (2023). The Interplay between Teacher Support and Student Self-Regulation in Mathematics Achievement. Nigerian Journal of Educational Development, 7(2), 31-49.
Zhang, L., Chen, X., & Li, J. (2023). Predicting Student Cheating Behavior using Cognitive-Load and Teacher Support: A PLS-SEM Analysis. Journal of Educational Psychology, 28(3), 301-318.
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