Active learning methodologies (ALM) are associated with student success, but little research on this topic has been pursued at the community college level. At a local community college, students in science, technology, engineering, and math (STEM) courses exhibited lower than average grades. The purpose of this study was to examine whether the use of ALM predicted STEM course grades while controlling for academic discipline, course level, and class size. The theoretical framework was Vygotsky's social constructivism. Descriptive statistics and multinomial logistic regression were performed on data collected through an anonymous survey of 74 instructors of 272 courses during the 2016 fall semester. Results indicated that students were more likely to achieve passing grades when instructors employed in-class, highly structured activities, and writing-based ALM, and were less likely to achieve passing grades when instructors employed project-based or online ALM. The odds ratios indicated strong positive effects (greater likelihoods of receiving As, Bs, or Cs in comparison to the grade of F) for writing-based ALM (39.1-43.3%, 95% CI [10.7-80.3%]), highly structured activities (16.4-22.2%, 95% CI [1.8-33.7%]), and in-class ALM (5.0-9.0%, 95% CI [0.6-13.8%]). Project-based and online ALM showed negative effects (lower likelihoods of receiving As, Bs, or Cs in comparison to the grade of F) with odds ratios of 15.7-20.9%, 95% CI [9.7-30.6%] and 16.1-20.4%, 95% CI [5.9-25.2%] respectively. A white paper was developed with recommendations for faculty development, computer skills assessment and training, and active research on writing-based ALM. Improving student grades and STEM course completion rates could lead to higher graduation rates and lower college costs for at-risk students by reducing course repetition and time to degree completion.
| Identifer | oai:union.ndltd.org:waldenu.edu/oai:scholarworks.waldenu.edu:dissertations-5256 |
| Date | 01 January 2017 |
| Creators | Lesko, Cherish Christina |
| Publisher | ScholarWorks |
| Source Sets | Walden University |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Walden Dissertations and Doctoral Studies |
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