Abstract

AbstractScience learning takes place not only in the context of science class but also after class. Students' internal forms of motivation, such as curiosity and interest, affect the entire science learning process in both in‐class and after‐class contexts. In addition, both stable existing learner characteristics, such as science curiosity and interest in a specific natural phenomenon (phenomenon interest), and temporary emotional states, such as state curiosity, are considered essential factors in improving learning. Given the importance of understanding how learners' two aspects of motivational variables influence their science learning in different learning contexts, this study aimed to examine the extent to which existing learner characteristics, such as science curiosity and phenomenon interest, and temporary emotional states, such as state curiosity, predict science learning both during and following class and how these variables are related to exploration after class. To achieve this goal, an explanatory sequential mixed‐method approach was employed, based on a correlational design, with a total of 706 cases from fifth‐grade and sixth‐grade students (45.5% female). In the context of science class, relatively stable existing learner characteristics, such as science curiosity and phenomenon interest, and temporary emotional states, such as state curiosity, were positively associated with learning, and temporary states were more predictive of learning than existing characteristics. In addition, state curiosity was directly related to learning, whereas science curiosity and phenomenon interest were only indirectly related to learning, mediated by state curiosity. In the context of the after‐class, however, only phenomenon interest significantly predicted spontaneous follow‐up learning and was positively associated with students' continued learning. An interpretation of these results was discussed, as well as their implications for science education and future research. Our findings will enable more fine‐grained analyses regarding how curiosity and interest can predict learning in science.

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