STRUCTURAL EQUATION MODELLING OF COGNITIVE LOADING IN THE CDIO PEDAGOGICAL APPROACH

STRUCTURAL EQUATION MODELLING OF COGNITIVE LOADING IN THE CDIO PEDAGOGICAL APPROACH

E. Zulu, T. Haupt (2018).  STRUCTURAL EQUATION MODELLING OF COGNITIVE LOADING IN THE CDIO PEDAGOGICAL APPROACH. 15.

CDIO programs have tenets of self-directed learning and often use either problem or project based learning. The assessment questions usually model real world engineering scenarios using fairly complex questions which are located in the ‘zone of proximal development’ (ZPD) of the students. The efficacy of the CDIO approach is reported in many studies and the approach is emerging as an accepted best practice in the field of engineering education. However, the consequence of the CDIO pedagogical approach on the cognitive load induced in students is not understood. This study therefore aimed to ascertain the amount of cognitive load induced due to the central tenets of the CDIO approach namely, complex questions, zone of proximal development and self-directed learning. The study follows a quantitative research design and a positivist philosophy using a deductive research approach using a cross sectional questionnaire survey and non-probability sampling. Structural equation modelling was performed using IBM SPSS AMOS v25 while descriptive and reliability analysis were done using SPSS v25. The findings show that the use of complex questions yields significant levels of cognitive load and locating the questions in the zone of proximal development of students also induces some amount of cognitive load. Self-directed learning on the other hand does not subject students to significant levels of cognitive load. Several studies have established the detrimental impact of high levels of cognitive loading on learning. The findings therefore suggest that it is necessary and important to monitor and manage the levels of cognitive loading induced by the CDIO approach so that it does not begin to interfere with the learning process. Specifically, the complexity of the assessment problems used should be carefully planned to be appropriate to the knowledge level of the students and not located outside the zone of proximal development of the students.

Authors (New): 
Ephraim Zulu
Theodore Haupt
Pages: 
15
Affiliations: 
Mangosuthu University of Technology, South Africa
University of KwaZulu-Natal, South Africa
Keywords: 
Structural Equation Modelling
Cognitive Loading
Complex Questions
Zone of Proximal Development
Self-directed Learning
Year: 
2018
Reference: 
Alharbi, H. A. (2017). Readiness for Self-Directed Learning: How Bridging and Traditional nursing students differs? Nurse Education Today. : 
https://doi.org/10.1016/j.nedt.2017.12.002
Alotaibi, K. N. (2016). The learning environment as a mediating variable between self-directed learning readiness and academic performance of a sample of saudi nursing and medical emergency students. Nurse Education Today, 36, 249-254. : 
https://doi.org/10.1016/j.nedt.2015.11.003
Amadieu, F., van Gog, T., Paas, F., Tricot, A., & Mariné, C. (2009). Effects of prior knowledge and concept-map structure on disorientation, cognitive load, and learning. Learning and Instruction, 19(5), 376-386. : 
http://dx.doi.org/10.1016/j.learninstruc.2009.02.005
Anderson, J. C. & Gerbing, D. W. (1988). Structural Equation Modeling in Practice: A Review and Recommended Two-Step Approach, Psychological Bulletin, 103, 411–423: 
Ayres, P. (2006). Using subjective measures to detect variations of intrinsic cognitive load within problems. Learning and Instruction, 16(5), 389-400. : 
http://dx.doi.org/10.1016/j.learninstruc.2006.09.001
Bannert, M. (2002). Managing cognitive load—recent trends in cognitive load theory. Learning and Instruction, 12(1), 139-146. : 
http://dx.doi.org/10.1016/S0959-4752(01)00021-4
Bekiryazici, M. (2015). Teaching Mixed-Level Classes with a Vygotskian Perspective. Procedia - Social and Behavioral Sciences, 186, 913-917. : 
https://doi.org/10.1016/j.sbspro.2015.04.163
Bentler, P. M. (1990). Comparative Fit Indexes in Structural Models, Psychological Bulletin, 107(2), 238-246: 
Browne, M. W. & Cudeck, R. (1993). Alternative Ways of Assessing Model Fit. In Bollen, K. A & Long, J. S. (eds.). Testing Structural Equation Models, 136–61. Newbury Park, CA: Sage Publications: 
Byrne, B. M. (2006). Structural Equation Modeling with EQS: Basic Concepts, Applications, and Programming (2nd ed.). Mahwah, NJ: Lawrence Erlbaum Associates: 
Chali, Y., Hasan, S. A., & Mojahid, M. (2015). A reinforcement learning formulation to the complex question answering problem. Information Processing & Management, 51(3), 252-272. : 
https://doi.org/10.1016/j.ipm.2015.01.002
CDIO (2004). The CDIO™ Standards. PDF available at http://www.cdio.org/files/standards/cdio_standards_1.0.pdf, accessed on 23/01/2018: 
CDIO (2017). The CDIO™ initiative is an innovative educational framework for producing the next generation of engineers. URL available at http://www.cdio.org/about, accessed 23/01/2018: 
Çolak, E. & Kaya D. (2014). Learning Approaches of Vocational High School Students: Grade Level and School Type Influences. Procedia - Social and Behavioral Sciences, 2014. 116: p. 1556- 1561.: 
Din, N., Haron, S., & Rashid, R. M. (2016). Can Self-directed Learning Environment Improve Quality of Life? Procedia - Social and Behavioral Sciences, 222, 219-227. : 
https://doi.org/10.1016/j.sbspro.2016.05.150
Fornell, C. & Larcker, D. F. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error, Journal of Marketing Research 18 (1), 39-50: 
Hadie, S.N.H. & Yusoff, M.S.B. (2016). Assessing the validity of the cognitive load scale in a problembased learning setting. Journal of Taibah University Medical Sciences, 11(3): p. 194-202.: 
Hulland, J. (1999). Use of Partial Least Squares (PLS) in Strategic Management Research: A Review of Four Recent Studies, Strategic Management Journal, 20(2), 195–204: 
Kirschner, P. A. (2002). Cognitive load theory: implications of cognitive load theory on the design of learning. Learning and Instruction, 12(1), 1-10. : 
http://dx.doi.org/10.1016/S0959- 4752(01)00014-7
Kirschner, P. A., Sweller, J., & Clark, R. E. (2006). Why Minimal Guidance During Instruction Does Not Work: An Analysis of the Failure of Constructivist, Discovery, Problem-Based, Experiential, and Inquiry-Based Teaching. Educational Psychologist, 41(2), 78-86. : 
10.1207/s15326985ep4102_1
Kirschner, P.A., (2002). Cognitive load theory: implications of cognitive load theory on the design of learning. Learning and Instruction, 12(1): p. 1-10.: 
Lee, C., Yeung, A. S., & Ip, T. (2017). University english language learners' readiness to use computer technology for self-directed learning. System, 67, 99-110. : 
https://doi.org/10.1016/j.system.2017.05.001
Leppink, J., Paas, F., van Gog, T., van der Vleuten, C.P.M., & van Merriënboer, J.J.G. (2014). Effects of pairs of problems and examples on task performance and different types of cognitive load. Learning and Instruction, 30: p. 32-42.: 
Louws, M. L., Meirink, J. A., van Veen, K., & van Driel, J. H. (2017). Teachers' self-directed learning and teaching experience: What, how, and why teachers want to learn. Teaching and Teacher Education, 66, 171-183. : 
https://doi.org/10.1016/j.tate.2017.04.004
Marsh, H. W., Balla, J. R. & Hau, K. T. (1996). An Evaluation of Incremental Fit Indices: A Clarification of Mathematical and Empirical Properties, In Marcoulides, G. A. & R. E. Schumacker (eds.). Advanced Structural Equation Modeling, Issues and Techniques. Mahwah, NJ: Lawrence Erlbaum Associates Publishers: 
Naeini, J. (2014). On the Study of DA and SLA: Feuerstein's MLE and EFL Learners’ Reading Comprehension. Procedia - Social and Behavioral Sciences, 98, 1297-1306. : 
https://doi.org/10.1016/j.sbspro.2014.03.546
Nasri, N. M. (2017). Self-directed learning through the eyes of teacher educators. Kasetsart Journal of Social Sciences. : 
https://doi.org/10.1016/j.kjss.2017.08.006
Paas, F., & van Gog, T. (2006). Optimising worked example instruction: Different ways to increase germane cognitive load. Learning and Instruction, 16(2), 87-91. : 
http://dx.doi.org/10.1016/j.learninstruc.2006.02.004
Pollock, E., Chandler, P. & Sweller, J. (2002). Assimilating complex information. Learning and Instruction, 12(1): p. 61-86.: 
Rashid, T., & Asghar, H. M. (2016). Technology use, self-directed learning, student engagement and academic performance: Examining the interrelations. Computers in Human Behavior, 63, 604- 612. : 
https://doi.org/10.1016/j.chb.2016.05.084
Rouvrais, S. & Landrac, G. (2012) Resistance to Change in Institutionalizing The CDIO Standards: From a Cascade to an Agile Improvement Model. Proceedings of the 8th International CDIO Conference, Queensland University of Technology, Brisbane, July 1 - 4, 2012: 
Scheiter, K., Gerjets, P., Vollmann, B., & Catrambone, R. (2009). The impact of learner characteristics on information utilization strategies, cognitive load experienced, and performance in hypermedia learning. Learning and Instruction, 19(5): p. 387-401.: 
Shooshtari, Z. G., & Mir, F. (2014). ZPD, Tutor; Peer Scaffolding: Sociocultural Theory in Writing Strategies Application. Procedia - Social and Behavioral Sciences, 98, 1771-1776. : 
https://doi.org/10.1016/j.sbspro.2014.03.605
Slater, C. E., & Cusick, A. (2017). Factors related to self-directed learning readiness of students in health professional programs: A scoping review. Nurse Education Today, 52, 28-33. : 
https://doi.org/10.1016/j.nedt.2017.02.011
Sweller, J. (1994). Cognitive Load Theory, Learning Difficulty and Instructional Design. Learning and Instruction, 4.: 
Sweller, J., van Merriënboer, J.J.G., & Paas, F. G. W. C. (1998). Cognitive Architecture and Instructional Design. Educational Psychology Review, 10(3). : 
Tasir, Z. & Pin, O.C. (2012). Trainee teachers’ mental effort in learning spreadsheet through selfinstructional module based on Cognitive Load Theory. Computers & Education, 59(2): p. 449- 465: 
Van Gerven, P.W.M., Paas, F.G.W.C., van Merriënboer, J.J.G., & Schmidt, H.G. (2002). Cognitive load theory and aging: effects of worked examples on training efficiency. Learning and Instruction, 12(1): p. 87-105.: 
Zeng Qiangyu, Jiang Juanping & Wang Lijuan (2015). Construction of Engineering Education Teaching Mode based on CDIO-Taking Principles of Atmospheric Detection as an Example. Proceedings of the 11th International CDIO Conference, Chengdu University of Information Technology, Chengdu, Sichuan, P.R. China, June 8-11, 2015.: 
Zhoc, K. C. H., & Chen, G. (2016). Reliability and validity evidence for the Self-Directed Learning Scale (SDLS). Learning and Individual Differences, 49, 245-250. : 
https://doi.org/10.1016/j.lindif.2016.06.013
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