This work in progress paper describes the development of an instrument to assess graduate student motivation towards doctoral degree completion. Doctoral attrition rates in the United States have been estimated to be around 40% over a 10 year completion period [8]. King [8] also found that less than 20% of students complete their doctoral programs in the expected timeframe of between 3 and 4 years. These results indicate the need to better understand factors that affect graduate students' experience during their doctoral program, particularly their choice to persist, so we can ensure equal opportunities for Ph.D completion. Spaulding and Rockinson-Szapkiw [12] talk about personal factors that contribute to doctoral students’ persistence. These factors include motivation, strategies for writing the dissertation, time management, and attributes such as credibility, commitment, and increased monetary compensation. As part of this research study, we have selected to focus upon student motivation as motivation theories have been found to provide explanations for factors that influence individuals choices and actions [3]. Specifically, we have selected the Expectancy-Value Theory (EVT) of motivation because it considers social, cultural, and psychological factors [1], making it beneficial for elements that could be relevant in a graduate studies program.
This work seeks to create a motivational instrument specific to an engineering graduate studies program setting. Our instrument development process began with the Engineering Motivation Survey, developed by Brown & Matusovich [2]. This survey instrument was designed to measure motivation of undergraduate engineering students towards engineering education and career choices. Ultimately, the purpose was to measure motivational factors that contribute toward choices to pursue and complete engineering degrees. The 35 likert scale questions were rephrased to focus on a graduate student setting. After the rephrasing, the draft survey was used in a Think-aloud protocol with six engineering graduate students to determine what changes may be needed to better support its new area of implementation. Upon finalization of the graduate student engineering motivation survey we will apply it to measure civil and environmental engineering graduate students’ motivation towards their doctoral degree completion as part of their participation in a Graduate Assistance in Areas of National Need (GAANN) program.
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This content will become publicly available on June 23, 2025
Board 362: Reimagining Civil Engineering Graduate Programs: A Research-to-Practice Approach for Shaping Future Transportation Engineers
The existing curriculum and models for civil engineering graduate programs assume that graduating Ph.D. students will primarily pursue career opportunities in research or academia. However, the number of civil engineering Ph.D. graduate students continues to increase, while the number of opportunities in academia for civil engineers remains stagnant. As a result, it is becoming increasingly apparent that the civil engineering graduate programs must be reevaluated to assist students entering industry after graduation. As part of a larger research study funded through the NSF Innovations in Graduate Education (IGE), we aim to answer the following research questions: 1) How can a research-to-practice model assist students in preparing for a transportation engineering career outside of academia?, 2) What impacts does the research-to-practice graduate model have on the development of transportation engineering doctoral students’ professional identity?, 3) How does the cognitive apprenticeship framework prepare doctoral students for professional practice in transportation engineering?, and 4) What influences does the research-to-practice model have on doctoral students’ motivation toward degree completion?
As part of the first phase for the project, two surveys were developed: a graduate engineering student motivation survey based on Expectancy-Value-Theory, and an instrument based on the Cognitive Apprenticeship framework. The motivation survey was based on an instrument designed and validated by Brown & Matusovich (2013) which aimed to measure undergraduate engineering students' motivation towards obtaining an engineering degree. The survey prompts were reviewed and rewritten to reflect the change in context from undergraduate to graduate school. Revised survey prompts were reviewed with a group of graduate engineering students through a think aloud protocol and changes to the instrument were made to ensure consistency in interpretation of the prompts (Rodriguez-Mejia and Bodnar, 2023). The cognitive apprenticeship instrument was derived from the Maastricht Clinical Teaching Questionnaire (MCTQ), originally designed to offer clinical educators feedback on their teaching abilities, as provided by medical students during their clerkship rotations (Stalmeijer et al., 2010). To tailor it to the context of engineering graduate students, the MCTQ's 24 items were carefully examined and rephrased. A think aloud was conducted with three civil engineering graduate students to determine the effectiveness and clarity of the cognitive apprenticeship instrument. Preliminary results show that minimal clarification is needed for some items, and suggestions to include items which address support from their mentors. The other part of the project assessment involves students completing monthly reflections to obtain their opinions on specific events such as seminars or classes, and identify their perceptions of their identity as professionals, scientists, or researchers. Preliminary results suggest that the students involved place an emphasis on developing critical thinking and planning skills to become an engineering professional, but de-emphasize passion and enjoyment. This paper will report on initial findings obtained through this first phase of the IGE project.
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- Award ID(s):
- 2224724
- PAR ID:
- 10529036
- Publisher / Repository:
- ASEE Conferences
- Date Published:
- Format(s):
- Medium: X
- Location:
- Portland, Oregon
- Sponsoring Org:
- National Science Foundation
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