Please use this identifier to cite or link to this item:
https://hdl.handle.net/2440/108293
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Type: | Journal article |
Title: | A method to analyse computer science students’ teamwork in online collaborative learning environments |
Author: | Vivian, R. Falkner, K. Falkner, N. Tarmazdi, H. |
Citation: | ACM Transactions on Computing Education, 2016; 16(2):7-1-7-28 |
Publisher: | ACM Digital Library |
Issue Date: | 2016 |
ISSN: | 1531-4278 1946-6226 |
Statement of Responsibility: | Rebecca Vivian, Katrina Falkner, Nickolas Falkner and Hamid Tarmazdi |
Abstract: | Although teamwork has been identified as an essential skill for Computer Science (CS) graduates, these skills are identified as lacking by industry employers, which suggests a need for more proactive measures to teach and assess teamwork. In one CS course, students worked in teams to create a wiki solution to problem-based questions. Through a case-study approach, we test a developed teamwork framework, using manual content analysis and sentiment analysis, to determine if the framework can provide insight into students’ teamwork behavior and to determine if the wiki task encouraged students to collaborate, share knowledge, and selfadopt teamwork roles. Analysis revealed the identification of both active and cohesive teams, disengaged students, and particular roles and behaviors that were lacking. Furthermore, sentiment analysis revealed that teamsmoved through positive and negative emotions over the course of developing their solution, toward satisfaction. The findings demonstrate the value of the detailed analysis of online teamwork. However, we propose the need for automated measures that provide real-time feedback to assist educators in the fair and efficient assessment of teamwork. We present a prototype system and recommendations, based on our analysis, for automated teamwork analysis tools. |
Rights: | © 2016 ACM |
DOI: | 10.1145/2793507 |
Published version: | http://dl.acm.org/citation.cfm?doid=2894200.2793507 |
Appears in Collections: | Aurora harvest 8 Computer Science publications |
Files in This Item:
File | Description | Size | Format | |
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RA_hdl_108293.pdf Restricted Access | Restricted Access | 1.59 MB | Adobe PDF | View/Open |
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