The Predicted Factors of Cognitive and Affective Learning at the Level 1 Sports Science Course by the Malaysian National Sports Council

Pertinent to Sports Science Course’s role as a coach learning program, it is important to look at factors that influence learning acquired of the participants. According to Kraiger, Ford and Salas (1993), learning acquired by the participants of training program consists of cognitive, affective a...

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Bibliographic Details
Main Author: Ayub, Hanafiah
Format: Thesis
Language:English
English
Published: 2009
Online Access:http://psasir.upm.edu.my/id/eprint/5704/1/FPP_2009_17.pdf
http://psasir.upm.edu.my/id/eprint/5704/
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Summary:Pertinent to Sports Science Course’s role as a coach learning program, it is important to look at factors that influence learning acquired of the participants. According to Kraiger, Ford and Salas (1993), learning acquired by the participants of training program consists of cognitive, affective and skill. Based on the theoretical approach of Sports Science Course, participants for this program are predicted to obtain cognitive and affective learning domains. This study employed the “Learning Transfer System Inventory (LTSI)” by Holton and Bates (1998) which was previously used in the Human Resource Development context (Holton, Naquin and Holton, 2003; Yaghi, Goodman, Holton and Bates, 2008) but has never been tested in the sports context. LTSI model has indicated that learning is influenced by individual, motivation, ability and environment factors. The objective of this study was to identify the predicting factors which are individual, motivation, ability and environment towards cognitive and affective learning among participants of Sports Science Courses conducted by the National Sports Council. This study is descriptive in design and researcher does not have control over the variables. A total of 204 participants who attended the Level 1 of Sports Science Course involved in this study. Analyses used in this study are percentage, frequency, mean, standard deviation, Confirmatory Factor Analysis, Pearson Moment Correlation, Stepwise Regression and Structural Equation Modelling. Findings showed that there are three factors at high level which are individual (mean = 4.01), motivation (mean = 4.13), ability (mean = 3.74) and one factor at moderate level which is environment (mean = 3.58). Cognitive learning was found as moderate (mean = 49.80) while affective learning as high (mean = 3.95) levels. Correlation analysis found significant relationship between environment factor (r = -.14, p < 0.05) with cognitive learning, while affective learning was found to have significant relationship with individual (r = .49, p < 0.05), motivation (r = .36, p < 0.05), environment (r =.32, p < 0.05) and ability (r = .28, p < 0.05) factors. Regression analysis showed significant influences of motivation and environment factors on cognitive learning, while individual factor was found to significantly influenced affective learning. The application of Structural Equation Modelling on all variables indicated individual factor to has direct effect (.49) on affective learning, while motivation (.26) and environment factors (.11) were found to have indirect effects towards affective learning. This study concludes that: 1) the identified model proposes learning in sports context to be geared toward more of affective learning, and 2) roles of individual, motivation and environment factors must be considered for learning program in sports context due to their effects on affective learning. Further research can be explored to examine the identified model using various areas related to adult education program.