This study explored the relationship of Deep Approaches to Learning (DAL) with overall students' satisfaction and perceived employability skills in the field of Science, Technology, Engineering and Mathematics (STEM) for the undergraduate seniors in the U.S. The study also aimed to investigate whether there is a difference between students in STEM and non-STEM fields on the relationship of DAL to overall student satisfaction and students' perceived employability skills. The data for the analysis was taken from the National Study of Student Engagement (NSSE) data. The Structural Equation Modeling (SEM) analysis was applied to explore the relationship between students' Deep Approaches to Learning (DAL), overall students' satisfaction and their perceived employability skills. The measurement invariance testing explored whether estimated factors are measuring the same constructs for STEM and non-STEM groups.
The findings of the study show that HO and RI construct was found to have statistically significant positive total (direct and indirect) effect on overall student satisfaction. Further, the results show that HO and RI learning activities were identified as the statistically significant factors in predicting students' perceived employability skills for STEM students.
The HO and RI have a statistically significant positive effect on perceived employability skills for STEM and the non-STEM students. The STEM students have a higher effect of HO learning activities on perceived employability skills than the non-STEM students. Further, the direct effect of perceived employability skill on overall student satisfaction is also positive for both the groups. The findings of the study confirmed the indirect effect of employability on overall students' satisfaction for both STEM and non-STEM students.
This study has created strong groundwork for future researchers to use the measurement models and the hypothesized full structure model for invariance testing among the groups of STEM and non-STEM in higher education in the U.S. Thus, this measurement model has a strong generalizability to both STEM and non-STEM groups. The implications and limitations of study are further discussed. / Doctor of Philosophy / There is an increasing consensus that for a society to solve complex problems that are related to climate, health, general economic development, and security, study in Science, Technology, Engineering, and Math (STEM) fields is critical to develop the skills that are needed to tackle those issues. However, there are reports on STEM education in the U.S. that have revealed that there is a general concern among policymakers and industrial leaders about the shortage of workers who are trained in STEM fields. To enhance the students' academic achievement, cognitive development, personal and social development, and to encourage them to be life-long learners, postsecondary institutions need to build a learning atmosphere that supports their deep learning approaches. This study explored the relationship of Deep Approaches to Learning (DAL) with overall students' satisfaction and perceived employability skills in the field of Science, Technology, Engineering and Mathematics (STEM) for the undergraduate seniors in the U.S. The study also investigated whether there is a difference between students in STEM and non-STEM fields on the relationship of DAL to overall student satisfaction and students' perceived employability skills at higher education. It has further shed a light on why the difference in patterns exist and can give direction on how teaching and learning can be improved in STEM and non-STEM fields.
The findings of the study suggests that Higher order (HO) and Reflective/Integrative (RI) have a positive effect on overall students' satisfaction for STEM students. The HO has a statistically significant higher effect on perceived employability skills for STEM students the for the non-STEM students. The effect of perceived employability skills on overall students' satisfaction on STEM and non-STEM students is positively high for both the groups. In order to enhance students' overall satisfaction with their university experience, the universities need to continuously develop new strategies and programs to make sure students are well-equipped with perceived employability skills.
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/115324 |
| Date | 05 June 2023 |
| Creators | Kapania, Madhu Bala |
| Contributors | Educational Research and Evaluation, Skaggs, Gary E., Savla, Jyoti Shital, Kniola, David John, Miyazaki, Yasuo |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Language | English |
| Detected Language | English |
| Type | Dissertation |
| Format | ETD, application/pdf |
| Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
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