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ERIC Number: EJ1047622
Record Type: Journal
Publication Date: 2015
Pages: 16
Abstractor: As Provided
Reference Count: 35
ISSN: ISSN-0020-739X
Predicting Performance in a First Engineering Calculus Course: Implications for Interventions
Hieb, Jeffrey L.; Lyle, Keith B.; Ralston, Patricia A. S.; Chariker, Julia
International Journal of Mathematical Education in Science and Technology, v46 n1 p40-55 2015
At the University of Louisville, a large, urban institution in the south-east United States, undergraduate engineering students take their mathematics courses from the school of engineering. In the fall of their freshman year, engineering students take "Engineering Analysis I," a calculus-based engineering analysis course. After the first two weeks of the semester, many students end up leaving "Engineering Analysis I" and moving to a mathematics intervention course. In an effort to retain more students in "Engineering Analysis I," the department collaborated with university academic support services to create a summer intervention programme. Students were targeted for the summer programme based on their score on an algebra readiness exam (ARE). In a previous study, the ARE scores were found to be a significant predictor of retention and performance in "Engineering Analysis I." This study continues that work, analysing data from students who entered the engineering school in the fall of 2012. The predictive validity of the ARE was verified, and a hierarchical linear regression model was created using math American College Testing (ACT) scores, ARE scores, summer intervention participation, and several metacognitive and motivational factors as measured by subscales of the Motivated Strategies for Learning Questionnaire. In the regression model, ARE score explained an additional 5.1% of the variation in exam performance in "Engineering Analysis I" beyond math ACT score. Students took the ARE before and after the summer interventions and scores were significantly higher following the intervention. However, intervention participants nonetheless had lower exam scores in "Engineering Analysis I." The following factors related to motivation and learning strategies were found to significantly predict exam scores in "Engineering Analysis I": "time and study environment management," "internal goal orientation," and "test anxiety." The adjusted R2 for the full model was 0.42, meaning that the model could explain 42% of the variation in "Engineering Analysis I" exam scores.
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Publication Type: Journal Articles; Reports - Research
Education Level: Higher Education; Postsecondary Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Identifiers - Location: Kentucky
Identifiers - Assessments and Surveys: ACT Assessment; Motivated Strategies for Learning Questionnaire