Asee peer logo

From rote learning to deep learning: Filling the gap by enhancing engineering students' reasoning skills through explanatory learning activities

Download Paper |

Conference

2023 ASEE Annual Conference & Exposition

Location

Baltimore , Maryland

Publication Date

June 25, 2023

Start Date

June 25, 2023

End Date

June 28, 2023

Conference Session

Student Performance and Learning & Open-ended problems

Tagged Division

Educational Research and Methods Division (ERM)

Page Count

17

DOI

10.18260/1-2--43756

Permanent URL

https://strategy.asee.org/43756

Download Count

106

Request a correction

Paper Authors

biography

Huihui Qi University of California San Diego

visit author page

Dr.Huihui Qi is an Associate Teaching Professor in the department of Mechanical and Aerospace Engineering, at the University of California San Diego.

visit author page

biography

Minju Kim University of California San Diego Orcid 16x16 orcid.org/0000-0001-5878-7350

visit author page

Minju Kim is a postdoctoral scholar at the Engaged Teaching Hub at the UCSD Teaching+Learning Commons. Minju received her Ph.D in Experimental Psychology at UC San Diego. With Engaged Teaching Hub, Minju has designed TA training materials for oral exams and have conducted quantitative analysis on the value of oral exams as early diagnostic tool (Kim et al., ASEE 2022). Minju is interested in designing assessments that can capture and motivate students' deep conceptual learning, such as oral exams and the usage of visual representations (e.g., diagrams and manual gestures).

visit author page

biography

Yu Li University of California San Diego

visit author page

Brian has received his Master of Science degree in material science. He is currently continuing his education as a Material Science Ph.D. student. As a graduate student, Brian has spent the past three years as a teaching assistant in a variety of undergraduate courses. His research background focuses on medical devices and soft composite development.

visit author page

biography

Carolyn L. Sandoval University of California, San Diego

visit author page

Dr. Sandoval is the Associate Director of the Teaching + Learning Commons at the University of California, San Diego. She earned a PhD in Adult Education-Human Resource Development. Her research interests include adult learning and development, faculty de

visit author page

biography

Curt Schurgers University of California San Diego

visit author page

Curt Schurgers is a Teaching Professor in the UCSD Electrical and Computer Engineering Department. His research and teaching are focused on course redesign, active learning, and project-based learning. He also co-directs a hands-on undergraduate research program called Engineers for Exploration, in which students apply their engineering knowledge to problems in exploration and conservation.

visit author page

biography

Marko V. Lubarda University of California San Diego Orcid 16x16 orcid.org/0000-0002-3755-271X

visit author page

Marko V. Lubarda is an Assistant Teaching Professor in the Department of Mechanical and Aerospace Engineering at the University of California, San Diego. He teaches mechanics, materials science, design, computational analysis, and engineering mathematics courses, and has co-authored the undergraduate textbook Intermediate Solid Mechanics (Cambridge University Press, 2020). He is dedicated to engineering pedagogy and enriching students' learning experiences through teaching innovations, curriculum design, and support of undergraduate student research.

visit author page

author page

Xuan Emily Gedney

biography

Saharnaz Baghdadchi University of California San Diego

visit author page

Saharnaz Baghdadchi is an Associate Teaching Professor at UC San Diego. She is interested in scholarly teaching and employs active learning techniques to empower students to attain an expert level of critical thinking. Her expertise facilitates students' journey towards connecting facts with practical knowledge to tackle intricate engineering challenges. She excels in crafting innovative assessments and explores their impact on enhancing students' learning outcomes and fostering an inclusive educational environment.

visit author page

biography

Alex Phan University of California San Diego Orcid 16x16 orcid.org/0000-0003-2489-2886

visit author page

Dr. Phan received his Ph.D. in Mechanical Engineering from the University of California San Diego with a specialization in medical devices. He is currently an instructor for the Department of Electrical and Computer Engineering focusing on hands-on education.

visit author page

Download Paper |

Abstract

Rote learning refers to the superficial learning of concepts and procedures, typically by brute memorization and with little integration into existing cognitive schemas, resulting in poor knowledge retention and inability to apply the knowledge in new and evolving contexts. With rote learning, students usually learn declarative and procedural knowledge but usually do not pay attention to conditional knowledge (when to use what knowledge). As a result, they usually can replicate the problem-solving process in a familiar context but are unable to transfer the knowledge and use the concept for a new application.

This paper explores the use of explanatory learning activities to promote students’ deep learning. Cognitive psychology literature shows that students do not necessarily learn concepts deeply by solving problems, unless they monitor their thinking and decision-making process before and during problem solving, and reflect on the process after will help to conditionalize their knowledge, i.e., when to use what knowledge to solve the problem.

In this paper, we present a study on a multidimensional approach to enhancing students' reasoning skills by integrating a variety of explanatory learning activities, namely oral exams, written guidance prompts for homework which asks students to justify their problem-solving process, and video assignment in which students perform group-explanation on homework assignments. Oral exams, due to their adaptive diagnostic nature, provide an opportunity to probe students’ thought process behind their decision-making. In contrast, written exams are limited in this capacity: when students write down an equation, it is difficult to tell whether they understand the concept well or if they are trying to recall similar procedures from class examples and homework assignments. Oral exams also allow students to receive feedback from a content expert who can clear up misconceptions. Group explanation activities offer the benefits of feedback exchange and social learning among students. The paper will present the details of these learning activities as well as the outcomes. Mixed research methods were used to study the impact of verbal explanations of learning activities. Students' learning outcomes are mainly measured by exam performance. Students' perceptions were studied through both quantitative Likert-scale questions and free-response to open-ended questions.

Qi, H., & Kim, M., & Li, Y., & Sandoval, C. L., & Schurgers, C., & Lubarda, M. V., & Gedney, X. E., & Baghdadchi, S., & Phan, A. (2023, June), From rote learning to deep learning: Filling the gap by enhancing engineering students' reasoning skills through explanatory learning activities Paper presented at 2023 ASEE Annual Conference & Exposition, Baltimore , Maryland. 10.18260/1-2--43756

ASEE holds the copyright on this document. It may be read by the public free of charge. Authors may archive their work on personal websites or in institutional repositories with the following citation: © 2023 American Society for Engineering Education. Other scholars may excerpt or quote from these materials with the same citation. When excerpting or quoting from Conference Proceedings, authors should, in addition to noting the ASEE copyright, list all the original authors and their institutions and name the host city of the conference. - Last updated April 1, 2015