2023 ASEE Annual Conference & Exposition

A Study Report in the Web Technologies Course: What Makes Feedback Effective for Project-based Learning?

Presented at Problem- and Project-Based Learning

In this paper, we report our experience of applying project-based learning (PjBL) in a web technology course, with a focus on how different feedback tactics affect students’ learning outcomes. Giving high-quality feedback can have an immediate impact on students' learning progress. Although process-level feedback is considered more effective than task-level feedback in traditional pedagogies, it is still unclear whether this conclusion can be exacerbated or mitigated when applied to PjBL, as PjBL emphasizes students’ ownership and authenticity. We divided students into two groups and applied different feedback strategies. We report findings and insights to help instructors develop feedback policies and practices that are effective and likely to benefit students. Our results suggest that giving low-level feedback still improves students’ learning outcomes in the context of PjBL, especially for technical tasks.

Authors

Alaa Jaber [biography]

Alaa Jaber is currently pursuing her Master's degree in Computer Science from the University of Michigan Dearborn. She has always been passionate about technology and its potential to transform the world. She is excited about the possibility of continuing her studies by pursuing a Ph.D. in Computer Science.
Dr. Kimberly Lechasseur Worcester Polytechnic Institute [biography]

Dr. Kimberly LeChasseur is a researcher and evaluator with the Worcester Polytechnic Institute. She holds a dual appointment with the Center for Project-Based Learning and the Morgan Teaching and Learning Center. She holds a PhD in Educational Leadership
Khairul Mottakin [biography]

Khairul Mottakin is a PhD Candidate from CIS department of University of Michigan-Dearborn, USA. He received his Masters by Research (MRes) degree from Bournemouth University, UK and B.Sc. in CSE from United International University(UIU), Bangladesh. His research interests include indoor localization, WiFi sensing and machine learning.
Prof. Zheng Song UMDearborn [biography]

Dr. Song received his second PhD in Computer Science (with a focus on distributed systems and software engineering) from Virginia Tech USA in 2020, and the first PhD (with a focus on wireless networking and mobile computing) from Beijing University of Posts and Telecommunications China in 2015. He worked as a software engineer at Sina for one year after he graduated as a master from China Agriculture University in 2009. He received the Best Paper Award from IEEE Edge in 2019.

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