Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/107908
Citations
Scopus Web of Science® Altmetric
?
?
Type: Conference paper
Title: Using learning analytics to visualise computer science teamwork
Author: Tarmazdi, H.
Vivian, R.
Szabo, C.
Falkner, K.
Falkner, N.
Citation: Proceedings of the 2015 ACM Conference on Innovation and Technology in Computer Science Education, 2015 / Dagiene, V., Schulte, C., Jevsikova, T. (ed./s), vol.2015-June, pp.165-170
Publisher: ACM
Issue Date: 2015
ISBN: 9781450334402
ISSN: 1942-647X
Conference Name: Innovation and Technology in Computer Science Education (ITiCSE) (06 Jul 2015 - 08 Jul 2015 : Vilnius, Lithuania)
Statement of
Responsibility: 
Harmid Tarmazdi, Rebecca Vivian, Claudia Szabo, Katrina Falkner and Nickolas Falkner
Abstract: Industry has called upon academia to better prepare Computer Science graduates for teamwork, especially in developing the soft skills necessary for collaborative work. However, the teaching and assessment of teamwork is not easy, with instructors being pressed for time and a lack of tools available to efficiently analyse student teamwork, where large cohorts are involved. We have developed a teamwork dashboard, founded on learning analytics, learning theory and teamwork models that analyses students’ online teamwork discussion data and visualises the team mood, role distribution and emotional climate. This tool allows educators to easily monitor teams in real-time. Educators may use the tool to provide students with feedback about team interactions as well as to identify problematic teams. We present a case study, trialing the dashboard on one university Computer Science course and include reflections from the course lecturer to determine its utility in monitoring online student teamwork.
Keywords: Learning analytics; Computer Science Education; Collaboration
Rights: ACM © 2015
RMID: 0030041201
DOI: 10.1145/2729094.2742613
Published version: http://dl.acm.org/citation.cfm?id=2729094
Appears in Collections:Computer Science publications

Files in This Item:
File Description SizeFormat 
RA_hdl_107908.pdfRestricted Access16.35 MBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.