Expectancy-value-cost motivational profiles in biology and physics: Their relations with gender, self-reported satisfaction of needs, and learning behavior

• Published in: Learning and individual differences Vol. 115; p. 102520
• Main Authors: Kikas, Eve, Puusepp, Ita, Aus, Kati
• Format: Journal Article
• Language: English
• Published: Elsevier Inc 01.10.2024
• Subjects: Basic need satisfaction; Biology; Motivational profiles; Physics; Task-persistent learning behavior; Biology; Motivational profiles; Task-persistent learning behavior; Physics; Basic need satisfaction
• ISSN: 1041-6080
• DOI: 10.1016/j.lindif.2024.102520

This study aimed to 1) identify groups of students with different expectancy, intrinsic and utility value, and cost profiles in biology and physics, and 2) to examine group differences in sources of beliefs (gender, students' perceptions of their biology and physics teachers' need-supportive and need-thwarting behavior) and students' learning behavior (reported persistence and use of learning strategies). In total, 1502 eighth and ninth grade students from Estonia filled in questionnaires. With latent profile analysis, four general (Indifferent, Maladaptive, Moderate, and Adaptive) and two subject-specific (Biology-Adaptive and Physics-Adaptive) motivational profiles were identified. These groups differed in gender composition, students' perceptions of their teachers' need-supportive and need-thwarting behavior, task-persistent learning behavior, and reported use of deep learning strategies. The findings suggest that motivation may develop differently within each subject. Examining motivation across two or more subjects adds valuable information about individual differences and has practical implications for supporting motivation in various subjects. •Profiles with general and biology- and physics-specific motivation were identified.•Subject-specific and Indifferent motivational profiles differed in gender composition.•Profiles differed in perceived need supportive and thwarting behavior from teachers.•Profiles differed in task persistence and application of deep learning strategies.•Maladaptive and Indifferent profiles demonstrated the least adaptive characteristics.