Longitudinal Analysis of Co-Curricular Involvement Among Engineering Undergraduates: Exploring Timing, Type, and Self-Reported Skills Development

The purpose of this study is to explore the self-reported professional competencies gained by engineering students involved at different rates and types of co/extra-curricular activities (CECAs) between their grade 12 and junior years of undergraduate engineering education. The contribution of this work is in using longitudinal data to understand how student engagement and learning outcomes might evolve to inform potential co-curricular programming changes. We analyzed data from an annual professional development survey from 970 students from 2016-2019. Findings show that higher engagement may not necessarily lead to higher skill acquisition for all students per unit of time, particularly in engineering-focused facets of professional skills. Co-curricular spaces are prone to be dominated by certain demographic profiles, and students are likely to engage in nontechnical work and clubs, as compared to co-curricular projects and research experiences. We conclude that future work should attempt to specify the “goldilocks” level of involvement, understand barriers to participation, and robustly characterize the nature of learning and students’ recognition of their learning through CECAs

Cyber-Empathic Design: A data-driven framework for product design

One of the critical tasks in product design is to map information from the consumer space to the design space. Currently, this process is largely dependent on the designer to identify and map how psychological and consumer level factors relate to engineered product attributes. In this way current methodologies lack provision to test a designer’s cognitive reasoning and could therefore introduce bias while mapping from consumer to design space. Also, current dominant frameworks do not include user-product interaction data in design decision making and neither do they assist designers in understanding why a consumer has a particular perception about a product. This paper proposes a new framework — Cyber-Empathic Design — where user-product interaction data is acquired via embedded sensors in the products. To understand the motivations behind consumer perceptions, a network of latent constructs is used which forms a causal model framework. Structural Equation Modeling is used as the parameter estimation and hypothesis testing technique making the framework falsifiable in nature. To demonstrate the framework and demonstrate its effectiveness a case study of sensor integrated shoes is presented in this work, where two models are compared — one survey based and using the Cyber-Empathic framework model. It is shown that the Cyber-Empathic framework results in improved fit. The case study also demonstrates the technique to test a designers’ cognitive hypothesis.</jats:p

Co-curricular engagement among engineering undergrads: do they have the time and motivation?

Abstract Background Co-curricular activities are often touted as valuable STEM learning opportunities in higher education settings. Particularly in engineering, industry encourage and seek students with co-curricular experiences. However, many engineering undergraduates do not regularly participate in those experiences. Some researchers have suggested that the rigors of the curriculum leave little time for co-curriculars. Yet, little research has empirically examined the reality of the undergraduate students’ involvement in co-curriculars. Thus, as an initial study, we situated our study in a large public university to explore students’ motivations for co-curriculars. In this paper we report on our efforts to understand student perceptions about the value and costs of that involvement. We considered how undergraduate engineering students used their time and what motivated them to engage (or not) in co-curriculars using Expectancy-Value Theory (EVT). Students’ motivation was investigated with a quantitative research methodology and complemented by interview data. Results Results of our motivation survey show that students who participated in co-curriculars perceived less cost than those who never participated. We also found that the achievement values of co-curriculars does not necessarily motivate student involvement. Interview data were used to further interpret quantitative data results. Conclusions In the context of study findings and existent literature, we discuss several implications for future research and practice. First, we argue for a more granular investigation of student time use and its impact on co-curricular participation. Second, despite the potential for high impact outcomes, students who have never participated perceived high cost for co-curricular engagement. Those perceptions may aggravate inequitable engagement of student populations, including historically marginalized populations in the STEM field. Third, students do not necessarily associate co-curricular experiences with the types of achievement values and learning that institutions, alumni, and industry might consider most important. Thus, to build and support co-curricular programs that provide the holistic educational experiences and learning that are anticipated, research that supports design of co-curricular programs and policies to improve engagement and persistence in those programs for all students is necessary

Defining Open-Ended Problem Solving Through Problem Typology Framework

Problem solving is central to engineering education. Yet, there little agreement regarding what constitutes an exemplary design problem or case analysis problem for modeling undergraduate instruction after. There is even less agreement in engineering education literature regarding the best way to measure students ability or progress in learning to be better problem solvers in these discrete problem categories. We describe the development of a research method toward accessing how students think about design is described, what constitutes a measurable response, and how to compare through qualitative research methods pre and post student performance. The discussion draws from Jonassen’s (2000) framework for problem typology, as well as cognitive learning frameworks of design thinking, and metacognition as a theoretical basis that informs the problem formulation and planned approach for analysis