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Determining persistence of community college students in introductory geology classes

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Science, Technology, Engineering & Mathematics (STEM) careers have been touted as critical to the success of our nation and also provide important opportunities for access and equity of underrepresented minorities (URM's). Community colleges serve a diverse population and a large

Science, Technology, Engineering & Mathematics (STEM) careers have been touted as critical to the success of our nation and also provide important opportunities for access and equity of underrepresented minorities (URM's). Community colleges serve a diverse population and a large number of undergraduates currently enrolled in college, they are well situated to help address the increasing STEM workforce demands. Geoscience is a discipline that draws great interest, but has very low representation of URM's as majors. What factors influence a student's decision to major in the geosciences and are community college students different from research universities in what factors influence these decisions? Through a survey-design mixed with classroom observations, structural equation model was employed to predict a student's intent to persist in introductory geology based on student expectancy for success in their geology class, math self-concept, and interest in the content. A measure of classroom pedagogy was also used to determine if instructor played a role in predicting student intent to persist. The targeted population was introductory geology students participating in the Geoscience Affective Research NETwork (GARNET) project, a national sampling of students in enrolled in introductory geology courses. Results from SEM analysis indicated that interest was the primary predictor in a students intent to persist in the geosciences for both community college and research university students. In addition, self-efficacy appeared to be mediated by interest within these models. Classroom pedagogy impacted how much interest was needed to predict intent to persist, in which as classrooms became more student centered, less interest was required to predict intent to persist. Lastly, math self-concept did not predict student intent to persist in the geosciences, however, it did share variance with self-efficacy and control of learning beliefs, indicating it may play a moderating effect on student interest and self-efficacy. Implications of this work are that while community college students and research university students are different in demographics and content preparation, student-centered instruction continues to be the best way to support student's interest in the sciences. Future work includes examining how math self-concept may play a role in longitudinal persistence in the geosciences.

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2014

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Relationships among personal characteristics, self-efficacy, and conceptual knowledge of circuit analysis of community college engineering students

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Conceptual knowledge and self-efficacy are two research topics that are well-established at universities, however very little has been investigated about these at the community college. A sample of thirty-seven students enrolled in three introductory circuit analysis classes at a large

Conceptual knowledge and self-efficacy are two research topics that are well-established at universities, however very little has been investigated about these at the community college. A sample of thirty-seven students enrolled in three introductory circuit analysis classes at a large southwestern community college was used to answer questions about conceptual knowledge and self-efficacy of community college engineering students. Measures included a demographic survey and a pre/post three-tiered concept inventory to evaluate student conceptual knowledge of basic DC circuit analysis and self-efficacy for circuit analysis. A group effect was present in the data, so descriptive statistics were used to investigate the relationships among students' personal and academic characteristics and conceptual knowledge of circuit analysis. The a priori attribute approach was used to qualitatively investigate misconceptions students have for circuit analysis. The results suggest that students who take more credit hours score higher on a test of conceptual knowledge of circuit analysis, however additional research is required to confirm this, due to the group effect. No new misconceptions were identified. In addition to these, one group of students received more time to practice using the concepts. Consequently, that group scored higher on the concept inventory, possibly indicating that students who have extra practice time may score higher on a test of conceptual knowledge of circuit analysis. Correlation analysis was used to identify relationships among students' personal and academic characteristics and self-efficacy for circuit analysis, as well as to investigate the relationship between self-efficacy for circuit analysis and conceptual knowledge of circuit analysis. Subject's father's education level was found to be inversely correlated with self-efficacy for circuit analysis, and subject's age was found to be directly correlated with self-efficacy for circuit analysis. Finally, self-efficacy for circuit analysis was found to be positively correlated with conceptual knowledge of circuit analysis.

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2014