Predicting High School Students’ Situated Expectancy-Value Motivation Regarding Food System STEM Projects
DOI:
https://doi.org/10.5032/jae.v67i3.3213Keywords:
Food system education, Integrated STEM education, Situated expectancy-value motivation, High school studentsAbstract
The study predicted high school students’ self-efficacy (as confirmed by Exploratory Factor Analysis, EFA) based on Situated Expectancy-Value Theory (SEVT) variables. A convenience sample of 160 students from four Indiana high schools who had participated in food system science, technology, engineering, and mathematics (STEM) projects was used. Quantitative data were collected through the Food System Motivation Questionnaire to measure two self-efficacy variables and five SEVT variables. The data obtained were analyzed using Principal Components Analysis, descriptive statistics, simple linear correlations, and multiple regression. Qualitative data were collected via focus group interviews and analyzed through thematic (deductive) and pattern coding. Triangulation was used to analyze both data types. The findings showed that students’ motivation to solve complex food system problems through integrated STEM learning was reflected in their learning experiences and helped teachers make relevant connections. There were four conclusions: (1) the questionnaire accurately measured five variables aligned with SEVT; (2) students were motivated by the project’s usefulness in their local contexts and reported increased cultural project self-efficacy; (3) over 70% of cultural project self-efficacy to complete a food system STEM project can be predicted based on the students’ local context utility value, personal importance and usefulness, intrinsic value, and cost value, with local context utility value contributing the most unique variance; and (4) after completing the projects, urban high school students shared they made connections to their family/culture, communities, and future careers. Implications on how teachers can better engage high school students in solving complex food system problems were discussed.
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