Supporting collaborative learning in engineering design

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Abstract

In team-based project courses, collaborative learning is the dominant learning mode. Collaborative learning has been shown to increase individual learning through co-construction and personal reflection. Rapid adoption of web-based communication and mobile computing by students provide opportunities to take advantage of computer-supported collaboration for engineering education. We present preliminary findings on a computer environment, the Kiva Web, that supports the activities of group collaboration for interdisciplinary engineering design teams. We have employed methods from human–computer interaction (HCI) to iterate on the design in the context of use. In this paper, we discuss the evolution of the Kiva Web and the implications for both student design teams and professional design teams.

Introduction

For both student and professional design teams, the design and development process requires that collaborators build and retain knowledge through discussions, sharing artifacts, and creating documents. The team design process also requires coordination of schedules, artifacts, documents, deadlines, and deliverables. Teams need to develop a shared language in order to communicate well. However, collaborators often have pressures that undermine coordination. Team members come and go, even in academic settings. Team members deal with competing priorities from work, school, and personal demands. Finally, for both student and professional collaborators, dedicated project space is at a premium. Meeting spaces need to be cleared at the end of a meeting, and team members leave a meeting with pieces of a puzzle that needs to be reconstructed at the beginning of the next meeting. Often critical pieces are missing so the team is either unable to proceed or revisits decisions they have already made.

The differences between engineering design teams in universities and those in industry are numerous. Students are novices both in their domain knowledge and in their knowledge of the design process. Students work in unstructured teams of peers, even if roles such as team leader have been assigned. They often judge their success by the grade they earn or by the artifacts they produce. The client, whether it is a professor or a company, rarely plans to use the team’s design directly. Rather, the goal is for the students to learn about the design process and to master new domain knowledge. On the other hand, professionals are expected to be domain experts, assigned to projects based on their skills, producing a product that the company can profit from. Learning, and the accumulation of shared knowledge, is rarely an explicit goal for industrial teams. For all these reasons, collaboration tools designed for teams in industry seldom work well for student teams. In response, design faculty on many campuses have begun to work on collaboration tools for student design teams, particularly for teams that are not co-located. Those working in this area include Ion et al., 1999, Kirschman and Greenstein, 2002, Lahti et al., 2004, Milne and Winograd, 2003, Subrahmanian et al., 2001.

Using an iterative, user-centered design process, we have designed and built tools to support students learning through collaboration. We have been conducting empirical studies to evaluate their usability and their contribution to learning for student design teams. We have designed the tools to facilitate learning through co-construction and reflection. Co-construction is the successful activity of knowledge building and problem solving between individuals (Miyake & Shirouzu, 2002). Reflection, discussion, and disagreement promote critical thinking (Li, 2003). This paper reviews the iterative design and development process of these tools. The environment is called the Kiva, which is a Native American gathering place.

Section snippets

Design motivation

Typical academic environments can undermine the learning goals of collaborative design projects. Scheduling and attending meetings are often difficult for students from different majors with different schedules and priorities. Because not all team members can attend all meetings, some team members miss key information and activities. They may be unaware that certain decisions have been made or that critical information has been presented and discussed.

In addition, students do not usually have

Rapid prototyping class

The Rapid Prototyping of Computer Systems course at Carnegie Mellon draws undergraduate and graduate students from electrical and computer engineering, computer science, human–computer interaction, industrial design, and mechanical engineering. In this class, which has been offered every spring for over 10 years, students work in project groups and collaborate on a single deliverable, employing a user-centered design methodology (Amon, Finger, Siewiorek, & Smailagic, 1996). The course is divided

The Kiva Web

The Kiva Web supports group organization and process as well as content organization and construction. The Kiva Web is designed to extend students’ ability to share information. Members contribute to the content, centralizing the discussion that surrounds the various artifacts or information. The Kiva Web provides a place to capture all group artifacts and discussions. It allows team members to build on each other’s work and to draw relevant relationships between information according to time

Concluding remarks

Although corporate tools have not been successful in the educational environment, perhaps corporations could take advantage of collaborative learning tools to meet organization goals. Building individual and corporate knowledge through developing constructive skills and reflective practice has value. This proposal requires further study.

Effective pedagogical tools aid students in building their own knowledge and reflecting on what they have learned. Our strategy has been to refine the tools in

Acknowledgments

This material is based upon work supported by the National Science Foundation under Grant EEC-0203448. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation. The Institute for Complex Engineered Systems at Carnegie Mellon has also supported this work. We would like to thank our colleagues Erica Cheng, Adam Fass, John Kembel, Jonathan Brodsky, Peter Scupelli, and

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