Design and Development of Survey Instrument to Measure Engineering Doctoral Students’ Perceptions of Their Teaching Preparedness

Omar Jose Garcia; Javeed Kittur

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Conference: 2024 ASEE Annual Conference & Exposition
Location: Portland, Oregon
Publication Date: June 23, 2024
Start Date: June 23, 2024
End Date: June 26, 2024
Conference Session: Educational Research and Methods Division (ERM) Technical Session 16
Tagged Division: Educational Research and Methods Division (ERM)
Page Count: 14
DOI: 10.18260/1-2--47119
Permanent URL: https://peer.asee.org/47119
Download Count: 169

Paper Authors

biography

Omar Jose Garcia University of Oklahoma

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Omar Garcia is an undergraduate Aerospace Engineering student at The University of Oklahoma

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biography

Javeed Kittur University of Oklahoma orcid.org/0000-0001-6132-7304

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Dr. Kittur is an Assistant Professor in the Gallogly College of Engineering at The University of Oklahoma. He completed his Ph.D. in Engineering Education Systems and Design program from Arizona State University, 2022. He received a bachelor’s degree in Electrical and Electronics Engineering and a Master’s in Power Systems from India in 2011 and 2014, respectively. He has worked with Tata Consultancy Services as an Assistant Systems Engineer from 2011–2012 in India. He has worked as an Assistant Professor (2014–2018) in the department of Electrical and Electronics Engineering, KLE Technological University, India. He is a certified IUCEE International Engineering Educator. He was awarded the ’Ing.Paed.IGIP’ title at ICTIEE, 2018. He is serving as an Associate Editor of the Journal of Engineering Education Transformations (JEET).

He is interested in conducting engineering education research, and his interests include student retention in online and in-person engineering courses/programs, data mining and learning analytics in engineering education, broadening student participation in engineering, faculty preparedness in cognitive, affective, and psychomotor domains of learning, and faculty experiences in teaching online courses. He has published papers at several engineering education research conferences and journals. Particularly, his work is published in the International Conference on Transformations in Engineering Education (ICTIEE), American Society for Engineering Education (ASEE), Computer Applications in Engineering Education (CAEE), International Journal of Engineering Education (IJEE), Journal of Engineering Education Transformations (JEET), and IEEE Transactions on Education. He is also serving as a reviewer for a number of conferences and journals focused on engineering education research.

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Abstract

Doctoral students who choose an academic career path will essentially be required to teach courses. However, literature says most doctoral students have more research experience than teaching experience. Additionally, the teaching experience they have is through their graduate teaching assistantships, which may or may not have associated training on how to teach. Teaching can be difficult if you are not fully aware of the different aspects associated with it. This research project aims at understanding engineering doctoral students’ perceptions on their readiness to teach courses once they begin their academic careers. To understand engineering doctoral students’ perceptions on their preparedness to teach courses, a survey instrument was designed and deployed.

The survey instrument included three parts: Likert scale questions, free response questions, and demographic information. The Likert scale questions evaluate the participants’ confidence/preparedness in areas of teaching such as the teaching and learning process (9 items); course design and delivery (8 items); creating a dynamic classroom (9 items); harnessing the power of technology (6 items); collaborative learning (6 items); and effective assessment (8 items). To collect the content and face validity evidence, the survey was sent to three content experts with expertise in survey design and three potential participants – engineering doctoral students from three different institutions. This study was approved by the Institutional Review Board and the survey instrument was administered in fall 2023. The survey was distributed to approximately 3500 engineering doctoral students from 20 different R1 universities, and 285 responses were included in the analysis post data cleaning and data pre-processing. Exploratory factor analysis (EFA) was conducted to validate the factor structure. EFA revealed six factors, five factors were same as hypothesized (the teaching and learning process, course design and delivery, creating a dynamic classroom, collaborative learning, and effective assessment) and one new factor (ethical practices). The factor loadings for the final factors ranged from 0.42 to 0.99, and the internal consistency reliability (Cronbach’s α) for the six factors ranged from 0.77 to 0.86, indicating high reliability.

Citation
Format

Garcia, O. J., & Kittur, J. (2024, June), Design and Development of Survey Instrument to Measure Engineering Doctoral Students’ Perceptions of Their Teaching Preparedness Paper presented at 2024 ASEE Annual Conference & Exposition, Portland, Oregon. 10.18260/1-2--47119

TY  - CPAPER
AB  - Doctoral students who choose an academic career path will essentially be required to teach courses. However, literature says most doctoral students have more research experience than teaching experience. Additionally, the teaching experience they have is through their graduate teaching assistantships, which may or may not have associated training on how to teach. Teaching can be difficult if you are not fully aware of the different aspects associated with it. This research project aims at understanding engineering doctoral students’ perceptions on their readiness to teach courses once they begin their academic careers. To understand engineering doctoral students’ perceptions on their preparedness to teach courses, a survey instrument was designed and deployed.  

The survey instrument included three parts: Likert scale questions, free response questions, and demographic information. The Likert scale questions evaluate the participants’ confidence/preparedness in areas of teaching such as the teaching and learning process (9 items); course design and delivery (8 items); creating a dynamic classroom (9 items); harnessing the power of technology (6 items); collaborative learning (6 items); and effective assessment (8 items). To collect the content and face validity evidence, the survey was sent to three content experts with expertise in survey design and three potential participants – engineering doctoral students from three different institutions. This study was approved by the Institutional Review Board and the survey instrument was administered in fall 2023. The survey was distributed to approximately 3500 engineering doctoral students from 20 different R1 universities, and 285 responses were included in the analysis post data cleaning and data pre-processing. Exploratory factor analysis (EFA) was conducted to validate the factor structure. EFA revealed six factors, five factors were same as hypothesized (the teaching and learning process, course design and delivery, creating a dynamic classroom, collaborative learning, and effective assessment) and one new factor (ethical practices). The factor loadings for the final factors ranged from 0.42 to 0.99, and the internal consistency reliability (Cronbach’s α) for the six factors ranged from 0.77 to 0.86, indicating high reliability. 
AU  - Omar Jose Garcia
AU  - Javeed Kittur
CY  - Portland, Oregon
DA  - 2024/06/23
PB  - ASEE Conferences
TI  - Design and Development of Survey Instrument to Measure Engineering Doctoral Students’ Perceptions of Their Teaching Preparedness
UR  - https://peer.asee.org/47119
DO  - 10.18260/1-2--47119
ER  -