differences between alpha coefficients across Self-report Measurements and Cognitive Tasks of Cognitive Load Theory

  • Mahmoud Ali Moussa Lecturer of Assessment and Educational Evaluation, College of Education, Suez Canal university, Egypt. mahmod567@yahoo.com
Keywords: alpha coefficients, alpha coefficient for two different scales


The study depended on Feldt transformations (1969, 1980) in use of differences between two alpha coefficients across measurements associated with multiple measurements of the cognitive burden theory. The study aimed to compare the self-report and cognitive tasks measurements in Psychological and Educational research. The researcher adopted Peterson (1994) approach to select the optimal sample size, which reached 76 students from the 2nd year of the Psychology department at the Ismailia Faculty of Education. Structural validity had been used to test the common factor structure.

The results revealed that self-report scales were superior in their stability and in their ability to show variance among sample participants. The study recommended relying on self-report measures to judge cognitive traits. If cognitive tasks are used, it is necessary to rely on benchmarks that reflect the cognitive process in problem solving. The score on these benchmarks is given in the light of the Likert scale as a higher correlation in estimating the degree of performance.


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Brunken, R., Plass, J. L., & Leutner, D. (2003). Direct measurement of cognitive load in multimedia learning. Educational psychologist, 38(1), 53-61.‏

Chandler, P., & Sweller, J. (1996). Cognitive load while learning to use a computer program. Applied cognitive psychology, 10(2), 151-170.‏

Feldt, L. S. (1969). A test of the hypothesis that cronbach's alpha or kuder-richardson coefficent twenty is the same for two tests. Psychometrika, 34(3), 363-373.

Feldt, L. S. (1980). A test of the hypothesis that Cronbach's alpha reliability coefficient is the same for two tests administered to the same sample. Psychometrika, 45(1), 99-105.‏

Feldt, L. S., Woodruff, D. J., & Salih, F. A. (1987). Statistical inference for coefficient alpha. Applied psychological measurement, 11(1), 93-103.‏

Ginns, P., & Leppink, J. (2019, February). Special Issue on Cognitive Load Theory: Editorial. Springer: Educational Psychology Review.

Hale, J. L., Boster, F. J., & Mongeau, P. A. (1991). The validity of choice dilemma response scales. Journal of Communication Reports, 4, 1.

Hodge, D. R., & Gillespie, D. F. (2007). Phrase completion scales: a better measurement approach than Likert scales?. Journal of Social Service Research, 33(4), 1-12.

Hu, L., & Bentler, P. M. (1999). Cut off criterion for fit indexes in covariance structure: conventional criteria versus new alternatives. Structural Equation Modeling, 6, 1-55.

Ivanov, O. A., Ivanova, V. V., & Saltan, A. A. (2018). Likert-scale questionnaires as an educational tool in teaching discrete mathematics. International Journal of Mathematical Education in Science and Technology, 49(7), 1110-1118.

Knaus, K., Murphy, K., Blecking, A., & Holme, T. (2011). A valid and reliable instrument for cognitive complexity rating assignment of chemistry exam items. Journal of Chemical Education, 88(5), 554-560.

Kolfschoten, G., French, S., & Brazier, F. (2014). A discussion of the cognitive load in collaborative problem-solving. EURO Journal on Decision Processes, 2(3-4), 257-280.‏

Lam, T. C., & Stevens, J. J. (1994). Effects of content polarization, item wording, and rating scale width on rating response. Applied Measurement in Education, 7(2), 141-158.

Leppink, J. (2017). Cognitive load theory: Practical implications and an important challenge. Journal of Taibah University Medical Sciences, 12(5), 385-391.‏

Leung, S. O. (2011). A comparison of psychometric properties and normality in 4-, 5-, 6-, and 11-point Likert scales. Journal of Social Service Research, 37(4), 412-421.

Morrison, B. B., Dorn, B., & Guzdial, M. (2014, July). Measuring cognitive load in introductory CS: adaptation of an instrument. In Proceedings of the tenth annual conference on International computing education research (pp. 131-138). ACM.‏

Naismith, L. M., & Cavalcanti, R. B. (2015). Validity of cognitive load measures in simulation-based training: a systematic review. Academic Medicine, 90(11), S24-S35.

Naismith, L. M., Cheung, J. J., Ringsted, C., & Cavalcanti, R. B. (2015). Limitations of subjective cognitive load measures in simulation‐based procedural training. Medical education, 49(8), 805-814.

Peterson, R. A. (1994). A meta-analysis of Cronbach's coefficient alpha. Journal of consumer research, 21(2), 381-391.‏‏

Rhodes, R. E., Hunt-Matheson, D., & Mark, R. (2010). Evaluation of social cognitive scaling response options in the physical activity domain. Measurement in Physical Education and Exercise Science, 14(3), 137-150.

Schmeck, A., Opfermann, M., van Gog, T., Paas, F., & Leutner, D. (2015). Measuring cognitive load with subjective rating scales during problem solving: differences between immediate and delayed ratings. Instructional Science, 43(1), 93-114.‏

Sweller, J. (2011). Cognitive load theory. In Psychology of learning and motivation (Vol. 55, pp. 37-76). Academic Press.‏

Szulewski, A., Gegenfurtner, A., Howes, D. W., Sivilotti, M. L., & van Merriënboer, J. J. (2017). Measuring physician cognitive load: validity evidence for a physiologic and a psychometric tool. Advances in Health Sciences Education, 22(4), 951-968.

Van-Gerven, P. W., Paas, F., van Merriënboer, J. J., & Schmidt, H. G. (2006). Modality and variability as factors in training the elderly. Applied Cognitive Psychology: The Official Journal of the Society for Applied Research in Memory and Cognition, 20(3), 311-320.‏

Wainer, H., & Thissen, D. (1993). Combining multiple-choice and constructed-response test scores: Toward a Marxist theory of test construction. Applied Measurement in Education, 6(2), 103-118.

Woodruff, D. J., & Feldt, L. S. (1986). Tests for equality of several alpha coefficients when their sample estimates are dependent. Psychometrika, 51(3), 393-413.‏

Wu, H., & Leung, S. O. (2017). Can Likert scales be treated as interval scales?—A Simulation study. Journal of Social Service Research, 43(4), 527-532.

Yeigh, T. (2014). Cognitive inhibition and cognitive load: a moderation hypothesis. International Journal for Cross-Disciplinary Subjects in Education, 5(3), 1744.

How to Cite
Moussa, M. (2020). differences between alpha coefficients across Self-report Measurements and Cognitive Tasks of Cognitive Load Theory. International Journal of Research in Educational Sciences., 3(2), 563 - 605. Retrieved from https://iafh.net/index.php/IJRES/article/view/140

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