Modeling relationships of matriculation students' affective and cognitive factors and achievement in organic chemistry
Modeling the learning of organic chemistry among matriculation students requires the integration of cognitive and affective factors and students’ performance. The cognitive factors include spatial ability and prior conceptual knowledge, whereas affective factors involve student attitude and self-eff...
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| Main Author: | |
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| Format: | Thesis |
| Language: | English |
| Published: |
2016
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| Subjects: | |
| Online Access: | http://psasir.upm.edu.my/id/eprint/70836/1/FPP%202017%2037%20IR.pdf |
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| Summary: | Modeling the learning of organic chemistry among matriculation students requires the integration of cognitive and affective factors and students’ performance. The cognitive factors include spatial ability and prior conceptual knowledge, whereas affective factors involve student attitude and self-efficacy. This study reviews Novak’s Model of Education that is relevant to the need for learning in organic chemistry. The literature reviews the importance of cognitive and affective factors that influence students’ achievement in organic chemistry. This study explores the integration of cognitive and affective factors using Structural Equation Modeling (SEM) analysis. Models was developed and validated through the correlational relationships among factors using student responses regarding Attitude towards Organic Chemistry Questionnaire (ATOCQ), The Purdue Visualization of Rotations Test (ROT), Chemistry Conceptual Inventory (CCI), and Organic Chemistry Achievement Test (OCAT).
SEM, involving Confirmatory Factor Analysis, was used to analyse the data. Four types of fitness indexes, RMSEA, GFI, CFI, and Chisq/df, were used to evaluate the fit of all models. Analysis of data started with confirming the fit of the first-order measurement model of Affective Factors, containing the student’s self-efficacy and attitudes construct. The analysis showed that all models fit the empirical data well, as indicated by the RMSEA value of less than 0.08, GFI and CFI values above 0.90 and Chisq/df value less than 5.0. This implies that the tools have validity in measuring each of the latent variables. The three models, namely the Proposed Model (Model 1) and Competing Models (Model 2 and Model 3), all achieved the fit indexes, with Model 3 being the best representative model to show the relationship between these achievement-relevant variables.
The models were also tested on empirical data and described the direction and magnitude of the relationship between cognitive and affective factors on students’ achievement well. Overall, the direct effect for model 3 (13.4%) was greater than for model 1 (12.2%) and model 2 (12.8%). Prior conceptual knowledge (8.4%) was the most important predictor for students’ achievement in this study, followed by student’s self-efficacy (4.5%) and spatial ability (0.7%). With regard to students’ attitudes toward organic chemistry, there was no direct effect on their achievement. Indirect effects for cognitive factor and affective factor on students’ achievement existed for model 2 and 3 only. For model 2, the indirect effects exist for the relationship between self-efficacy with student achievement where the attitude act as a mediator while for model 3, the indirect effects exist to the relationship between prior knowledge with student achievement where self-efficacy acts as a mediator. In conclusion, the findings of this study highlight the role of cognitive and affective factors on students’ achievement in learning organic chemistry. |
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