Examining the Cross-Cultural Validity of the MUSIC Model of Academic Motivation Inventory in English Language Courses

Jones, Brett D.; Khajavy, Gholam Hassan; Li, Ming; Mohamed, Hanaa Ezzat; Reilly, Peter

doi:10.1177/21582440231156583

SAGE Open

2023

DOI: 10.1177/21582440231156583

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Examining the Cross-Cultural Validity of the MUSIC Model of Academic Motivation Inventory in English Language Courses

Brett D. Jones

Gholam Hassan Khajavy

Ming Li

et al.

Abstract: This study examined whether the five scales of the MUSIC Model of Academic Motivation Inventory produced valid scores when used in university English language courses across four different countries. We surveyed 1,147 students in English language courses in Iran, Mexico, China, and Egypt and analyzed their responses by performing measurement invariance testing using multiple group confirmatory factor analysis. The internal consistency reliability of the five MUSIC Inventory scales was acceptable. The configura… Show more

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Motivational climate predicts effort and achievement in a large computer science course: examining differences across sexes, races/ethnicities, and academic majors

Jones,

Ellis,

et al. 2023

IJ STEM Ed

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Background The motivational climate within a course has been shown to be an important predictor of students’ engagement and course ratings. Because little is known about how students’ perceptions of the motivational climate in a computer science (CS) course vary by sex, race/ethnicity, and academic major, we investigated these questions: (1) To what extent do students’ achievement and perceptions of motivational climate, cost, ease, and effort vary by sex, race/ethnicity, or major? and (2) To what extent do the relationships between students’ achievement and perceptions of motivational climate, cost, and effort vary by sex, race/ethnicity, and major? Participants were enrolled in a large CS course at a large public university in the southeastern U.S. A survey was administered to 981 students in the course over three years. Path analyses and one-way MANOVAs and ANOVAs were conducted to examine differences between groups. Results Students’ perceptions of empowerment, usefulness, interest, and caring were similar across sexes and races/ethnicities. However, women and Asian students reported lower success expectancies. Students in the same academic major as the course topic (i.e., CS) generally reported higher perceptions of the motivational climate than students who did not major or minor in the course topic. Final grades in the course did not vary by sex or race/ethnicity, except that the White and Asian students obtained higher grades than the Black students. Across sex, race/ethnicity, and major, students’ perceptions of the motivational climate were positively related to effort, which was positively related to achievement. Conclusions One implication is that females, Asian students, and non-CS students may need more support, or different types of support, to help them believe that they can succeed in computer science courses. On average, these students were less confident in their abilities to succeed in the course and were more likely to report that they did not have the time needed to do well in the course. A second implication for instructors is that it may be possible to increase students’ effort and achievement by increasing students’ perceptions of the five key constructs in the MUSIC Model of Motivation: eMpowerment, Usefulness, Success, Interest, and Caring.

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Motivational climate predicts effort and achievement in a large computer science course: examining differences across sexes, races/ethnicities, and academic majors

Jones,

Ellis,

et al. 2023

IJ STEM Ed

View full text Add to dashboard Cite

show abstract

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Examining the Cross-Cultural Validity of the MUSIC Model of Academic Motivation Inventory in English Language Courses

Cited by 1 publication

References 59 publications

Motivational climate predicts effort and achievement in a large computer science course: examining differences across sexes, races/ethnicities, and academic majors

Motivational climate predicts effort and achievement in a large computer science course: examining differences across sexes, races/ethnicities, and academic majors

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