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Investigating a shared co-located digital collaborative space for learning entity-relationship modelling

thesis
posted on 16.02.2017, 03:29 by Wong, Anthony Kee Ling
This research investigates aspects of collaborative learning in a shared co-located digital learning space. It concerns the approaches to Computer-Supported Collaborative Learning, more precisely it examines the instructional, interaction and interface mechanisms required to enhance learning in a shared co-located collaborative learning environment. Various approaches to collaborative learning are discussed with a view to identify an appropriate theoretical framework to design the collaborative learning activities in the context of this research. The role of computer technology in facilitating collaborative tasks is reviewed in order to design a digital learning space. Strategies to facilitate and control collaborative learning activities are investigated in order to establish methods to enhance the collaborative learning experience. Multi-touch technology is justified and incorporated to create a shared learning space. In this research, the collaborative learning domain is set as the Entity-Relationship (ER) modelling tasks for database design. This research adapted the design-science research methodology to scope, design, develop and evaluate the digital learning space. This research methodology was suitable for this type of research, where an artefact was design and developed as a proposed solution. There were three main phases in the research process, namely identifying issues, design and implementation, and evaluation. In the identifying issues phase, data was collected from students and academic staff to verify the specific nature of the conceptual problems students’ experience. The outcomes from the analysed data consolidated the conceptual learning issues of ER modelling into three tasks, namely; 1) analysing a scenario to identify entities, 2) establish relationships among entities, and 3) verify the Entity-Relationship Diagram (ERD) produced. These learning issues were used to inform the design of the proposed learning space. The literature review on collaborative learning provided insights into the productive interactions among learners that were predictive of learning outcomes. These interactions were synthesised as collaborative behaviours, consisting of sharing, explaining, justifying, criticising, and motivating. The proposed system, named CLEARER (collaborative learning environment for ER modelling), aimed to facilitate and encourage these interactions. To achieve these goals, CLEARER incorporated various collaborative mechanisms to provide an interface and interaction strategies to facilitate and guide the collaboration process. These strategies, e.g. turn-taking, role-paying, were incorporated into the learning tasks of ER modelling, while utilising the multi-touch technology. CLEARER was evaluated to examine its effectiveness, primarily through its collaborative strategies in the context of ERD modelling. Evaluation was conducted through qualitative feedback from participants and a detailed observational study of the participants’ collaborative interactions, system data, and learning outcomes. Participant feedback indicated that the learning activities were worth doing and the system was appreciated by the participants overall. Observational results indicated that these strategies have facilitated participants when contributing to group learning and guided productive interactions among group members. These results provide insights into the relationship between the collaborative strategies designed into the system and the collaborative behaviours carried out by participants. This research’s contribution is to synthesise collaborative strategies for the design of computer-supported co-located learning spaces that are facilitated with a multi-touch surface to promote collaborative behaviours in learning ER modelling.

History

Campus location

Australia

Principal supervisor

Michael Morgan

Year of Award

2014

Department, School or Centre

Clayton School of IT

Course

Doctor of Philosophy

Degree Type

DOCTORATE

Faculty

Faculty of Information Technology