Understanding the Current Mentorship Capabilities of Teaching Assistants for Engineering Courses

<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Contribution:</i> This article describes and interprets the quantitative results from a survey meant to evaluate the mentorship capabilities of engineering teaassistants. <p xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><i>Background:</i> TA are a common facet at several higher learning institutions. In this position, they perform multiple duties to improve their students’ learning experiences, refining their own teaching abilities in the process. Given both their prevalence and impact, various researchers have been interested in studying these assistants’ capabilities and factors affecting their efficacy. Some of the most prominent lenses utilized for these investigations include self-efficacy, pedagogical behavior, and classroom structure. <p xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><i>Research Questions:</i> Building upon that previous literature, this article aims to answer the following questions: 1) How prepared is the current group of engineering teaching assistants (TAs) in the United States to facilitate improved student comprehension in class? 2) What potential avenues of growth can colleges in the United States follow to increase the overall efficacy of engineering TAs? <p xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><i>Methodology:</i> A survey with thirty-five 5-point Likert-based items was distributed to engineering program chairs at several universities across the United States. There was a total of 400 respondents for this survey once incomplete or insincere entries were excluded. Afterwards, exploratory factor analysis (EFA) was utilized to determine both the factorability of this data and its reliability. Regression analysis was also used to study the impact of certain factors across the survey’s scales. <p xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><i>Findings</i>: Three of the four initial questionnaire scales—self-efficacy, pedagogical practice, and content knowledge—emerged from EFA with high internal consistency reliability scores. Regression analysis found significance in student interaction, training, gender, and native language.