Abstract
This correlational study examines the relationship between pre-service teachers’ affective dispositions towards genetics and their academic performance in genetics courses. The unit of analysis consists of 101 undergraduate pre-service science teachers enrolled in a public university. A descriptive correlational research design was employed to quantify the nature and strength of the association between variables. Data were collected through standardized assessments of genetic content knowledge and a 5-point Likert-scale questionnaire measuring perceptions and attitudes towards genetics. The reliability of the instruments was confirmed using Cronbach’s alpha, with perception and attitude scales achieving coefficients of 0.87 and 0.85, respectively. Data analysis involved the use of Pearson’s correlation coefficient to determine the strength and direction of relationships, complemented by multiple Linear regression analysis to identify the predictive power of affective dispositions on academic outcomes. The results indicated that only 5% of students’ perception and attitude was able to predict their performance with a p-value of 0.087 depicting the model’s insignificance at 0.05 significance level, despite the positive attitude (mean [M] = 3.95) and perception (M = 4.09). This highlight’s the gap between students’ affective dispositions and their academic performance as what one might perceive may not entirely reflect within the shortest possible time. The study’s findings further suggest that tailored instructional strategies focusing on affective factors can enhance genetics comprehension and teaching efficacy among pre-service teachers.
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Article Type: Research Article
European Journal of Health and Biology Education, Volume 13, Issue 1, 2026, Article No: e2603
https://doi.org/10.29333/ejhbe/18120
Publication date: 14 Mar 2026
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