Portland, Oregon
June 23, 2024
June 23, 2024
June 26, 2024
Educational Research and Methods Division (ERM) Technical Session 9
Educational Research and Methods Division (ERM)
6
10.18260/1-2--48209
https://peer.asee.org/48209
48
Isabel Hilliger is Assistant Professor of Practice and Associate Director for Assessment and Evaluation at the Engineering Education Unit in Pontificia Universidad Católica de Chile (PUC-Chile). Isabel received a BEng and PhD in Engineering Sciences from PUC-Chile, and an MA in Policy Organizations and Leadership Studies from Stanford Graduate School of Education.
Marietta holds a Master in Technological Innovation from Federico Santa Maria University (Santiago, Chile) and a BA in Design from Diego Portales University (Santiago, Chile). She is the Course Director of the Design and Digital Animation programmes at the School of Design and Creative Industries, San Sebastian University (Santiago, Chile)
Psychologist, Gestora Unidad de Innovación Docentes de las Ingenierías (UIDIN)
Erick is a project manager at the Engineer Education Unit and the Research and Innovation Unit at the School of Engineering, Pontificia Universidad Católica de Chile. He is also an Adjunct Faculty member at the School of Digital Design and Creative Industries, San Sebastian University. Erick received his Master's Degree in Engineering Science with a focus on Computer Vision from PUC-Chile.
He is an associate professor in the Computer Science Department and Associate Dean for Engineering Education at the Engineering School in Pontificia Universidad Católica de Chile. Jorge holds a PhD in Computer Science from the University of Toronto in Ca
This is a work-in-progress about student workload. Over the past two decades, practitioners and researchers have shown concern for student workload within engineering programs. Since the late 1990s, engineering curricula have been overloaded with content and outcome assessments, with the objective that students are able to demonstrate both technical and professional skills. Different types of course assignments are often concentrated in specific weeks, what amplifies learners' levels of anxiety and academic stress. During the pandemic, some students perceived that they have spent more time on academic tasks, without necessarily obtaining better learning results. Considering the continuous curriculum changes, engineering faculty should support students who struggle with their ability to self-regulate their learning. So far, different theoretical models have tried to define student workload without reaching consensus. In the context of self-regulated learning, it represents the time students invest in various tasks to achieve their learning goals. According to rational choice, the time students spend on tasks is relative to the perceived benefits, like deeper learning or better grades. Cognitive load theory further breaks it down into intrinsic, extraneous, and germane cognitive loads based on students' prior knowledge and mental demands. Researchers have also differentiated between objective and subjective workload. Objective workload represents the desire to quantify the actual hours students spend inside and outside the classroom, whereas subjective workload relates to students' perceived time and effort, what can be further categorized into a quantitative variable (number of hours) and a qualitative variable (the difficulty of academic tasks). Elicitation techniques could be useful when discussing abstract or sensitive topics such as student workload, as they encourage participants to share more meaningful insights by reducing power imbalances between interviewers and participants. One set of these techniques involves construction tasks, such as free listing, where participants list words related to a given topic, shedding light on cultural interpretations and priorities. According to researchers from different fields, this method is adaptable, easy-to use, and suitable for various cultural contexts, and can yield both qualitative and quantitative data, making them valuable for group-level comparisons. This study is part of a large research project, and it aims to explore the perspectives of engineering faculty and students on workload. To meet this research objective, a free-listing activity was included at the beginning of five group interviews held in three different types of engineering schools in Chile. In total, 28 faculty and 32 students participated in this group interviews, which were conducted with faculty and students separately. These participants were required to write what they understand by student workload. Most participants listed the time allocated for subjects (37 out of the 60 participants), and for many of them, this implied both class time and independent study hours to achieve a good performance. However, most faculty mainly listed academic elements such as homework, study plan, and syllabus, while students listed social-emotional aspects of learning such as academic stress and responsibility. This reflects the need to generate consensus to reconcile both types of workload elements in engineering education programs.
Hilliger, I., & Castro, M., & Torres, E. H., & Svec, E. V., & Baier, J. (2024, June), Unpacking Student Workload through Elicitation Techniques: Perspectives from Engineering Faculty and Students Paper presented at 2024 ASEE Annual Conference & Exposition, Portland, Oregon. 10.18260/1-2--48209
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