Virtual On line
June 22, 2020
June 22, 2020
June 26, 2021
Educational Research and Methods
6
10.18260/1-2--35704
https://peer.asee.org/35704
354
Isabel Hilliger is the Associate Director for Assessment and Evaluation at the Engineering Education Division in Pontificia Universidad Católica de Chile (UC). Isabel received a BEng from UC and an MA in Education Policy from Stanford University. She is currently a PhD Candidate in Computer Science at UC-Engineering. Her research theme is the use of methodologies and analytical tools for continuous curriculum improvement in Higher Education. She has created qualitative and quantitative instruments for outcome assessment in enginering education. She has also evaluated policy efforts towards engineering diversity and undergraduate research.
Sociologist.
Assessment and Evaluation Coordinator, Division of Engineering Education (Pontificia Universidad Católica de Chile).
Javiera Meza has a Bachelor of Engineering Science in Pontificia Universidad Católica de Chile. She is a research assistant of the Engineering Education Division, responsible for supporting research tasks and collaborating in data collection and analysis. Javiera developed a project about STEM education focused on primary school. Her research theme is about gender gap and motivation of students in undergraduate computer science programs. Currently she is researching about student motivation in online lessons due to the influence of COVID-19.
Gonzalo Cortés is an undergraduate student at the engineering school in Pontificia Universidad Católica de Chile. His Major is Electrical Engineering and his Minor is Energy. Currently, he is a research assistant of the Engineering Education Division, responsible for supporting research tasks and collaborating in data collection and analysis. Gonzalo managed a pre-engineering program to encourage high school students to study careers in engineering and science. He also volunteered as a teacher in communication skills and personal development, aimed at training high school students in vulnerable backgrounds.
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 Canada and a Master's Degree in Engineering Sciences from Pontificia Universidad Católica de Chile. His research focuses on areas of automated reasoning in Artificial Intelligence; specifically, automated planning, search and knowledge representation. Currently his research focuses on understanding how machine learning techniques can be applied to the intelligent decision-making process, on the applicability of reasoning techniques and learning to databases. He is also an assistant researcher at the Millennium Institute for Foundational Research on Data.
Due to external influences, such as internationalization and technological changes, engineering curricula have incorporated an increasing number of contents and competencies. Future engineers have to demonstrate attainment of a broad range of abilities, such as complex problem-solving and entrepreneurial skills, and acquire a wide range of knowledge, such as scientific and mathematical principles. To achieve mastery of both abilities and knowledge, students are exposed to an increasing number of courses that they perceive as more demanding and rigorous when compared to previous versions.
For understanding what students define as a demanding course, several researchers have explored the concept of academic workload. By workload, researchers have typically referred to the time students dedicate to a course both inside and outside the classroom. So far, there is a growing body of knowledge regarding factors that affect how students distribute time between course face-to-face activities and independent study, such as the type and schedule of course evaluations. However, little is known about the students' perception of the level of course difficulty and learning benefits in relation to the coverage of a wide range of knowledge and skills. In order to ensure that a wider number of content and skills translates into a greater learning experience, more studies are needed to understand not only the hours dedicated to particular courses, but also the difficulty and the level of learning attained as a consequence of the work done across the curriculum.
This paper presents a Work-In-Progress (WIP) that is part of a large project to understand students’ perceptions on academic rigor at a large and selective school in Latin America. The research question addressed in this paper is: What factors affect students’ perceptions on demanding courses in terms of difficulty and learning? For answering this research question, we plan to combine the use of mixed methods with grounded theory research. This combination has already been used to generate theories about concepts that have not defined by the existing literature. In this study, mixed methods were used to collect qualitative and quantitative data from engineering students from different cohorts and disciplines. Qualitative data was collected from two focus groups with 13 students (26 students total), and quantitative data was collected from an online anonymous questionnaire applied to 1.154 students. Findings obtained from triangulation of quantitative and qualitative information show that the quantity and complexity of the content affects students’ perception of a greater difficulty, while students’ and teachers’ motivation for the course contents affects students’ perception of greater learning. Future work will focus on defining a theory to explain why students’ perceive engineering courses as more demanding.
Hilliger, I., & Melian, C., & Meza, J., & Cortés, G., & Baier, J. A. (2020, June), Work in Progress: What Makes Courses Demanding in Engineering Education? A Combination of Mixed Methods and Grounded Theory Research Paper presented at 2020 ASEE Virtual Annual Conference Content Access, Virtual On line . 10.18260/1-2--35704
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