Journal ArticleDOI
Supporting collaborative learning and problem-solving in a constraint-based CSCL environment for UML class diagrams
Nilufar Baghaei,Antonija Mitrovic,Warwick Irwin +2 more
- Vol. 2, Iss: 2, pp 159-190
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TLDR
The architecture, interface and support for collaboration in the new, multi-user system described is described, which is the first system to also represent a higher-level skill such as collaboration using the same formalism.Abstract:
We present COLLECT-UML, a constraint-based intelligent tutoring system (ITS) that teaches object-oriented analysis and design using Unified Modelling Language (UML). UML is easily the most popular object-oriented modelling technology in current practice. While teaching how to design UML class diagrams, COLLECT-UML also provides feedback on collaboration. Being one of constraint-based tutors, COLLECT-UML represents the domain knowledge as a set of constraints. However, it is the first system to also represent a higher-level skill such as collaboration using the same formalism. We started by developing a single-user ITS that supported students in learning UML class diagrams. The system was evaluated in a real classroom, and the results showed that students’ performance increased significantly. In this paper, we present our experiences in extending the system to provide support for collaboration as well as domain-level support. We describe the architecture, interface and support for collaboration in the new, multi-user system. The effectiveness of the system has been evaluated in two studies. In addition to improved problem-solving skills, the participants both acquired declarative knowledge about effective collaboration and did collaborate more effectively. The participants have enjoyed working with the system and found it a valuable asset to their learning.read more
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Journal ArticleDOI
Computer-Supported Argumentation: A Review of the State of the Art
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Seven Affordances of Computer-Supported Collaborative Learning: How to Support Collaborative Learning? How Can Technologies Help?
TL;DR: This article proposes 7 core affordances of technology for collaborative learning based on theories of collaborative learning and CSCL (Computer-Supported Collaborative Learning) practices and explores in-depth explorations of how technologies are actually used to support collaborative learning in CSCL research.
Journal ArticleDOI
From Cognitive Load Theory to Collaborative Cognitive Load Theory
TL;DR: It is illustrated how and why cognitive load theory, by adding these concepts, can throw light on collaborative learning and generate principles specific to the design and study of collaborative learning.
Journal ArticleDOI
Adaptive and Intelligent Systems for Collaborative Learning Support: A Review of the Field
TL;DR: The reviewed articles indicate that AICLS systems increasingly introduce Artificial Intelligence and Web 2.0 techniques to support pretask interventions, in-task peer interactions, and learning domain-specific activities.
References
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Book
Usability Engineering
TL;DR: This guide to the methods of usability engineering provides cost-effective methods that will help developers improve their user interfaces immediately and shows you how to avoid the four most frequently listed reasons for delay in software projects.
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Protocol Analysis: Verbal Reports as Data.
TL;DR: This article reviewed major advances in verbal reports over the past decade, including new evidence on how giving verbal reports affects subjects' cognitive processes, and on the validity and completeness of such reports.
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The Unified Modeling Language User Guide
TL;DR: In The Unified Modeling Language User Guide, the original developers of the UML provide a tutorial to the core aspects of the language in a two-color format designed to facilitate learning.
Book
Protocol Analysis: Verbal Reports as Data
TL;DR: In this article, the authors reviewed major advances in verbal reports over the past decade, including new evidence on how giving verbal reports affects subjects' cognitive processes, and on the validity and completeness of such reports.
Journal Article
The Search for Methods of Group Instruction as Effective as One-to-One Tutoring.
TL;DR: In this article, the authors compared student learning under three conditions of instruction: 1. Conventional, 2. Mastery Learning, and 3. Tutoring, and concluded that the need for corrective work under tutoring is very small.
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