Identifying and Removing a Calculus Prerequisite as a Bottleneck in Clemson's General Engineering Curriculum

Ohland, Matthew W.; Yuhasz, Amy G.; Sill, Ben L.

doi:10.1002/j.2168-9830.2004.tb00812.x

Cited by 63 publications

(50 citation statements)

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“…Budny et al concluded that an algebra placement exam should be used to identify students for placement in a remediation course. Seeming to confirm these results is a study by Ohland, Yuhasz, and Sill [17] that showed an improvement in engineering retention by recognizing that many students were not ready to take calculus in their first semester.…”

Section: Relationship Between Engineering Retention and First Mathemasupporting

confidence: 67%

Predicting performance in a first engineering calculus course: implications for interventions

Hieb

Lyle

Ralston

et al. 2014

International Journal of Mathematical Education in Science and

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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 R 2 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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Section: Relationship Between Engineering Retention and First Mathemasupporting

confidence: 67%

Predicting performance in a first engineering calculus course: implications for interventions

Hieb

Lyle

Ralston

et al. 2014

International Journal of Mathematical Education in Science and

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“…Previous studies have already shown that grades students earn in their first mathematics course influences their retention in engineering 10,11 . How do the grades students earn influence their progress through the mathematics sequence?…”

Section: How Much Difference Does the Grade In The First Mathematics mentioning

confidence: 97%

Patterns of Students’ Success: How Engineering Students Progress Through a Course Sequence

Froyd¹,

Shryock²,

Tripathy³

et al.

2015 ASEE Annual Conference and Exposition Proceedings

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six institutions systematically renewed, assessed, and institutionalized innovative undergraduate engineering curricula. He has authored over 70 papers and offered over 30 workshops on faculty development, curricular change processes, curriculum redesign, and assessment. He has served as a program co-chair for three Frontiers Miss Manisha Tripathy, Texas A & M UniversityManisha Tripathy is a Masters student in Computer Science and Engineering Department at Texas A&M University.Currently she is working as a Student Worker with Engineering Academic and Student Affairs at Texas A&M University.She did her B Tech in Electronics and Telecommunication Engineering from KIIT University,India . Prior to joining as a master's student,she worked as an Assistant System Analyst at Tata Consultancy Services Ltd.Her work primarily included java development and application management activities. Her research interests include data analysis,information retrieval and application software development. Prof. arun r srinivasa, Texas A&M UniversityDr Arun Srinivasa is the Holdredge/Paul Professor and associate department head of Mechanical Engineering at Texas A&M University and has been with TAMU since 1997. Prior to that he was a faclty at University of Pittsburgh. He recieved his undergraduate in mechanical Engineering from the Indian Institute of Technology, Madras, India in 1986 and subsequently his PhD from University of California, Berkeley. He research interests include continuum mechanics and thermodynamics, simulations of materials processing, and smart materials modeling and design. He teaching interests include the use of technology for education, especially in the area of engineering mechanics and in effective teaching methodologies and their impact on student progress in mechanical engineering. Rebecca C Simon, Texas A&M University Rebecca Simon is a Program Specialist for Undergraduate Retention in the Dwight Patterns of Students' Success: How Engineering Students Progress through a Course Sequence AbstractIncreasing the number and diversity of graduates with undergraduate degrees in engineering continues to be highlighted in national reports. Improving the number of engineering graduates is not only a matter of recruitment but also a critical matter of retention. Currently, less than half of the students entering engineering persist and ultimately attain an engineering degree. Retention studies, in general, have evaluated cohorts related to specific lengths of time, such as first or second year retention. The studies have provided less information on patterns of student performance in courses in the engineering curricula and instead many times focus on success in a first course. The authors in this study examine how patterns of progression through course sequences might be used to improve retention in engineering.This approach visualizes how engineering students are progressing through course sequences. Engineering curricula are complex with multiple required courses, many of which have one or more prerequisites. S...

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“…For instance, [Ohland et al 2004] found that removing a gateway course for their engineering major improved graduation rates for the major as a whole, suggesting that the course was not a true prerequisite. Every curriculum is subject to time constraints, and knowing which units can be safely omitted if necessary is important.…”

Section: Discussionmentioning

confidence: 99%

Educational Data Mining

Peña-Ayala¹

2014

Studies in Computational Intelligence

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Identifying and Removing a Calculus Prerequisite as a Bottleneck in Clemson's General Engineering Curriculum

Cited by 63 publications

References 3 publications

Predicting performance in a first engineering calculus course: implications for interventions

Predicting performance in a first engineering calculus course: implications for interventions

Patterns of Students’ Success: How Engineering Students Progress Through a Course Sequence

Educational Data Mining

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