Board # 9 : Characterizing Student Identities in Engineering: Attitudinal Profiles of Engineering Majors

Abstract

Lisa Benson is a Professor of Engineering and Science Education at Clemson University, with a joint appointment in Bioengineering. Her research focuses on the interactions between student motivation and their learning experiences. Her projects involve the study of student perceptions, beliefs and attitudes towards becoming engineers and scientists, and their problem solving processes. Other projects in the Benson group include effects of student-centered active learning, self-regulated learning, and incorporating engineering into secondary science and mathematics classrooms.

Engineering Women’s Attitudes and Goals in Choosing Disciplines with Above and Below Average Female Representation

“…This study was part of a larger mixed methods project (Kirn et al 2016;Benson et al 2017). The target population was first-year engineering students, who were invited to complete a survey during the first two weeks of classes.…”

“…FTP consists of three dimensions (1) time orientation, orientation towards the past or future, (2) instrumentality, perceptions of the usefulness of a task in relation to their desired future or goals, and (3) perception of time, an individuals' view that time can help improve or make things better (Husman and Lens 1999;Husman and Shell 2008;Kirn and Benson 2018). A study of engineering students found that those who had a more positive outlook on their long-term goals were more likely to persist in engineering and problem-solving tasks (Benson et al 2017;Kirn and Benson 2018). Husman and Lens (1999) found that students whose time orientation is placed more towards the future are more likely to continue working on tasks than students who are more oriented towards the present.…”

Engineering students' noncognitive and affective factors: Group differences from cluster analysis

“…Based on prior literature (Benson et al, 2017), we expect that several clusters of students exist as well as a disperse unclustered set with potentially substantial membership. Benson et al (2017) largely focused on affective constructs and revealed a large "normative" group, seven smaller groups, and a disparate group of unclustered observations where each observation is the complete survey response of one student. We had no a priori knowledge that all observations in our data would fit cleanly into a finite number of clusters, so using GMM (a probabilistic method that allows for an unclustered group) was an important part of the research design.…”

Development and Testing of an Instrument to Understand Engineering Doctoral Students’ Identities and Motivations

“…In previous research, these factors were examined via a series of questions that asked participants to rate, on a seven-point Likert scale, how much they agreed with statements such as the following: "I understand concepts I have studied in engineering"; "I am interested in learning more about engineering"; and "My peers see me as an engineer". To explore the intersections between math, physics, and engineering identities, participants were also asked identical questions rephrased to explore math and physics domains [15].…”