The primary purpose of this study was to create a questionnaire based on the assumed causal model that “cross-curriculum learning in subject of science and mathematics” mediates “awareness of the relevance between science and mathematics”, “learning strategies” and “self-efficacy”, and affects “usefulness of science and mathematics learning” and, further, to clarify the causal model of the factors that constitute “the significance of cross-curriculum learning in science and mathematics.” The secondary purpose of the study was to clarify the relevance of likes and dislikes of science and mathematics to each factor. After conducting a questionnaire survey, regarding the first purpose, six factors were extracted as factors that constitute the significance of cross-curriculum learning in science and mathematics: “awareness of problem solving,” “functional viewpoints / ways of thinking”, “usefulness of science and mathematics learning”, “learning strategies in science”, “necessity of mathematics in science learning”, and “awareness of formulation / quantification”. In addition, as a result of multiple regression analysis and path analysis, it was clarified that the “functional viewpoints / ways of thinking” indirectly influences the “usefulness of science and mathematics learning” via the four factors (“awareness of problem solving,” “learning strategies in science,” “necessity of mathematics in science learning,” and “awareness of formulation / quantification”). Furthermore, with regard to second purpose of the study, comparison between the likes and dislikes of science and mathematics and the scores on each factor, in the “awareness of formulation / quantification,” revealed ra significant difference between Group II (likes math and dislikes science) and Group III (likes science and dislikes science). In science learning, in order to raise “awareness of formulation/quantification,” the results of this study suggest a need for activities to quantitatively analyze and interpret while utilizing mathematical knowledge and skills, such as creating graphs to render natural things / phenomena and experimental results, as well as to derive formulas and patterns.
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