The Psychometric Properties of the Cognitive Load Inventory among Al-Azhar High School Students with Physics Learning Disabilities

Document Type : Original Article

Authors

1 قسم علم النفس التعليمي، کلية التربية، جامعة الأزهر بالقاهرة.

2 Educational Psychology Department, Faculty of Education, Al-Azhar University.

Abstract

 The current study aimed at developing a cognitive load inventory among Al-Azhar high school students with physics learning disabilities as well as testing its psychometric properties (validity - reliability). To achieve the aforementioned objective, forty three students with physics learning disabilities from the 2nd scientific high school grade were recruited. The researcher utilized the descriptive method. Utilizing the appropriate statistical methods in analyzing the psychometric properties of the prepared inventory, it has been applicable to similar groups to whom its psychometric properties were analyzed with high level of confidence. The arbitrators’ agreement on the inventory items ranged between (90.9% - 100%), being a high level of agreement and indicating the inventory validity. The correlation coefficients between the students’ scores on the cognitive load inventory and their scores on the criterion inventory were statistically significant (a= 0.01), indicating the inventory validity, as well. The correlation coefficients between the item and the dimension to which it belonged were statistically significant (a= 0.01). The correlation coefficients between the dimension and inventory total score were also statistically significant (a= 0.01), indicating a high level of internal consistency of the inventory. The reliability coefficients of the three dimensions of the inventory as well as its total score were (0.735 - 0.784 - 0.720 - 0.859), respectively. They represented high reliability coefficients which indicated the inventory had high reliability level.

Keywords


Abdel Alim,Z. (2014). Cognitive burden scale. Cairo: Modern Book House.
Abdelnour, A. (2019). Reciprocal thinking in a preschool child and its relationship to cognitive load. Journal of Scientific Research in Education, College of Girls, Ain Shams University, 14(2), 616-643.
Abu Riash,H. (2007). Cognitive learning. Amman, Jordan: Dar Al Masirah.
 
Ahmed,A. (2012). Cognitive burden and its relationship to learning style among a sample of university students. Education Journal for Educational, Psychological and Social Research, 151, (3), 695-741.
Al-Harthy,S. (2015). Cognitive burden and its relationship to cognition skills among a sample of sixth grade students with academic learning difficulties. Journal of Educational and Psychological Studies, Zagazig University, 1 (86), 11-48.
Al-Mursi,A. (2018). The effectiveness of the electronic mind mapping strategy in developing algebraic reasoning skills and reducing the cognitive load among middle school students. Journal of the Faculty of Education, Tanta University, 72(4), 208-364.
El Fil,H. (2015). Systemic intelligence in the theory of cognitive burden, Anglo-Egyptian Library, Cairo.
Ezzedine,S. (2017). The effectiveness of using graphic organizers in developing achievement and reducing the cognitive burden associated with solving algorithmic problems in analytical chemistry and the preferred learning methods of secondary school students in the Kingdom of Saudi Arabia. International Journal of Educational Research, Emirates, 41, (2), 77-144.
Fadel,N. (2014). Cognitive burden and its relationship to the ability of self-confrontation among university students (Unpublished Master's Thesis). College of Education, University of Diyala, Iraq.
Fathy,H. (2019). Cognitive burden among children with reading difficulties and normal children in primary education (Unpublished Master's Thesis). Childhood Institute, Psychological Studies for Children, Ain Shams University.
Habib,A. (2018). E-learning and the cognitive burden on students: an evaluation study and a future vision. Journal of Educational and Psychological Studies, Faculty of Education, Zagazig University, 2(101), 347-382.
Hassan, A.(2018). Achievement motivation and academic achievement as determinants of cognitive burden among adolescents of undergraduate students: a predictive study. Journal of Scientific Research in Arts, Girls' College of Arts, Sciences and Education, Ain Shams University, 10 (19), 603-628.
Jaber,Z. (2016). The effectiveness of educational scaffolding in developing engineering problem-solving skills and reducing the cognitive load of second year preparatory students. Journal of Mathematics Education, 19(8), 91-131.
 
 
Jaljal,N., Aladdin Al-Saeed,A., & Al-Saeed,F. (2019). The cognitive burden of people with learning difficulties in reading from fifth graders of primary school. Journal of the Faculty of Education, Kafr El-Sheikh University, 19(1), 389-422.
Juma,M. (2019). The effectiveness of using augmented reality in academic achievement, learning retention, and cognitive load among tenth grade students in social studies in the Sultanate of Oman (A magister message that is not published). College of Education, Sultan Qaboos University.
Khaled Zaki,K. (2019). The effect of a training program based on self-regulated learning strategies in reducing cognitive load (unpublished doctoral dissertation). College of Education, Yarmouk University.
Khalil,M., El Khouly,H., El-Sawy,R.,& Antar,A. (2019). The effectiveness of a training program in the light of the theory of cognitive burden on the academic achievement of primary school students with difficulties learning mathematics. Journal of the Faculty of Education, Faculty of Education, Benha University, 30 (118), 336-378.
Mahmoud,A. (2016). An educational design based on the theory of cognitive burden and its effectiveness in the achievement of mathematics and visual spatial intelligence among middle school students in Iraq. The Arab Journal of Science and Research Publishing, 2 (6), 25-55.
Milad,M. (2014). The effect of using virtual flow maps on developing visual thinking skills and reducing the cognitive load of professional diploma students specializing in educational technology. Journal of the College of Education, 30(4), 649-698.
Salem,M. (2014). Cognitive styles and academic self-efficacy as predictors of cognitive load among secondary school students in Mafraq Kasbah (A magister message that is not published). Deanship of Scientific Research and Graduate Studies, The Hashemite University.
Tawfik,A. (2019). The relative contribution of cognitive load, social support, self-efficacy, and anxiety in predicting student-teacher satisfaction. Egyptian Psychological Association, 29(2), 309-398.
Thabet, A., Saeed, A.(2016). The effectiveness of a training program based on brain-based learning in developing systemic thinking skills and reducing the cognitive load among students of the College of Education. Journal of the Faculty of Education, Tanta University, 64(4), 1-82.
 
Yusuf,M. (2009). The effect of the presentation, organization and time of presentation of the educational material in multimedia environments on the cognitive load of a sample of first-year scientific secondary school students in the Ramtha district schools (unpublished doctoral dissertation). College of Education, Yarmouk University.
ثانياً: المراجع الأجنبية
Antonenko, p. (2007). The effect of leads on cognitive load and learning in a conceptually rich hypertext environment. (Doctoral dissertation), low state university.
Antonenko, P. D., & Niederhauser, D. S. (2010). The influence of leads on cognitive load and learning in a hypertext environment. Computers in Human Behavior, 26(2), 140-150.‏
Chong,T. (2005). Recent Advances in Cognitive Load Theory Research: Implication for Instructional Designers. Malaysian  Online Journal of instructional Technology (MOJIT), 2 (3), 106-117.
Cooper, G., Tindall-Ford, S., Chandler, P., & Sweller, J. (2001). Learning by imagining. Journal of Experimental Psychology: Applied, 7(1), 68-82.
De Jong, T. (2010). Cognitive load theory, educational research, and instructional design: some food for thought. Instructional science, 38(2), 105-134.
Elliott, S; Kurz, A; Peddow, P & Fray, J . (2009). Cognitive Load Theory: Instruction-based Research with Application for Designing Tasts. Paper Presented at the National Association of School Psychologist Annual Convention. Boston, MA, February, 24, 1-22.
Gerjest , P. & Schiter , K. (2003). Goal configuration and processing strategies as moderators between in structional design and cognitive load. Evidence from hypertext , basea instruction Educational psychohogist , 389, 33-41 .
Hu, M. L. M., & Wu, M. H. (2012). The effect of concept mapping on students’ cognitive load. World transactions on engineering and technology education, 10(2), 134-137.
Karampiperis, P., Lin, T., Sampson, D. G., & Kinshuk. (2006). Adaptive cognitive‐based selection of learning objects. Innovations in Education and Teaching International, 43(2),    121-135.
Kernek, C. R. (2007). The principles of multimedia learning: Reducing cognitive load to construct meaningful learning in online courses. Texas A&M University-Commerce, 1-125.‏
Lin, x. (2001). Designing metacognitive activities. Educational Technology Research and Development , 313, 1049 -1050.
Mendel, J. (2010). The effect of interface consistency and cognitive load on user performance in an information search task (Master’s thesis), Clemson University.
Mousavi , Seyed & Low , Renae & Sweller , John .( 1995 ): Reducing cognitive load by mixing anditory and visal presentation modes , Joumal of Eductional psychohogy . American psychological Association , USA , 87, 319-334 .
Paas, F., & Sweller, J. (2012). An evolutionary upgrade of cognitive Load theory: using the human motor system and collaboration to support the learning of complex cognitive tasks. Educational psychology Review, 24 (1), 27-45.
Paas, F., Renkl, A., & Sweller, J. (2004). Cognitive load theory: Instructional implications of the interaction between information structures and cognitive architecture. Instructional science, 32(1/2), 1-8.‏
Paas, F., Van Gog, T., & Sweller, J. (2010). Cognitive Load Theory: New Conceptualizations, Specifications, and Integrated Research Perspectives. Educational psychology Review, 22, 115-121.
Pass, F; Tuovinen, J; Tabbers, H&Van Gerven, P. (2003). Cognitive Load Measurement as a Means to Advance Cognitive Load Theory. Educational Psychologist, 38(1), 63-71.
Price , H. E. ( 2000 ) . Interval matching by under graduatenon music majors. Journal of Research in masic Education, 329-360 .
Schnotz, W; Kurschner, C. (2007). A Recosideration of Cognitive Load Theory. Journal of Educational Psychology Review, (19), 469-508.
Sharp, D. C. , Knowlton, D. S. & Weiss , R. E. (2005). Applications of generative learning for the survey of international econamis course. Journal of  Economic Education, 6 , 409-434 .
Shehab, H. (2011). Cognitive load of critical thinking. (Doctoral dissertation), College of Education, University of Nevada, Las Vegas.
Smith, M. (2007).  Factors in the measurement of Cognitive Load of Multimedia Learning. (Master Dissertation), Faculty of Education, University of Pretoria.
Sweller J. ; Ayres, P.; & Kalyuga, S. (2011). Cognitive Load Theory. New York, NY: Springer.
 
Sweller, J. (2002). Visualisation and Instructional Design. In Proceedings of the International Workshop on Dynamic Visualizations and Learning. Knowledge Media Research Center,Tübingen, Germany, 1501-1510.
Sweller, J. (2010), Cognitive Load Theory: Recent Theoretical Advances. In Plass, J; Moreno, R & Brunken, R. (Eds). Cognitive Load Theory. New York: Cambridge University Press,  29-47.
Yao, Y. (2006). The effect of different presentation formats of hypertext annotations on cognitive load, learning and learner control. University of Central Florida.‏