Process Mining and Learners' Behavior Analytics in a Collaborative and Web-Based Multi-Tabletop Environment

Process Mining and Learners' Behavior Analytics in a Collaborative and Web-Based Multi-Tabletop Environment

Parham Porouhan (Siam University, Graduate School of Information Technology, Bangkok, Thailand) and Wichian Premchaiswadi (Siam University, Graduate School of Information Technology, Bangkok, Thailand)
Copyright: © 2017 |Pages: 25
DOI: 10.4018/IJOPCD.2017070103

Abstract

Interactive tabletops alone cannot automatically analyze and interpret students' digital footprints (event logs). Moreover, the final artifacts created by groups provide imperfect information about each individual's contribution to the group task. This research is divided into two main parts. In the first part of the study, a quantitative survey was conducted in order to identify the most significant indicators affecting the collaboration process in an online and networked context-aware multi-tabletop environment. In the second part of the study, several process mining techniques such as social network mining, basic performance analysis, role hierarchy mining, and dotted chart analysis were used with the purpose of increasing the instructor's awareness/knowledge about the collaborative dynamics in each group. The empirical findings showed that the levels of symmetry of actions (or similarity of tasks) and symmetry of roles (or low division of labor) were much higher in the high-performance groups compared with the low performance groups. Consequently, high performance groups showed increased tendencies to work on the same range of actions ‘together'. Quite the opposite, low performance groups showed increased tendencies to work on a dissimilar range of actions ‘individually'.
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Introduction

According to Dillenbourg (1998) in the definition of Computer-Supported Collaborative Learning (CSCL), a pedagogical situation is called collaborative when a group of students —who are more or less at the same level of status, skills, knowledge, expertise, development, and so on can work together and perform the same range of actions toward a common or shared goal (i.e., not by competing with each other toward a conflicting goal). Dillenbourg (1998) explains that although the terms ‘Collaboration’ and ‘Cooperation’ are often mistaken and misunderstood as two synonyms, there is a huge difference between them considering the degree of division of labor among peer group members. In cooperative learning situations, students divide the main task into sub-tasks, each group member tries to accomplish a sub-task individually, and finally these sub-tasks are assembled and presented in the form of a final output. However, in collaborative learning situations, students try to accomplish the main task together in a completely collective and spontaneous manner. As a result, five main features that distinguish the term Collaboration from Cooperation are based on the following factors:

  • 1.

    Symmetry of participants’ status with regard to their community;

  • 2.

    Participants are allowed to perform a similar range of actions;

  • 3.

    Symmetry of participants’ prior knowledge, expertise, skills, development, etc.;

  • 4.

    Participants attempt to reach a common/shared goal but not through competition;

  • 5.

    Low and spontaneous division of labor.

Table 1 indicates the main differences between cooperation and collaboration in the definition of Computer-Supported Collaborative Learning (CSCL).

Table 1.
Differences between cooperation and collaboration in CSCL (Chiu, 2004; Dillenbourg, 1998; Harding-Smith, 1993; Hinze-Hoare, 2006)
CooperationCollaboration
Cooperation may occur between participants with or without a similar status.
Examples: between ‘a boss and an employee’, between ‘a teacher and a student’, between ‘a student and a student’, or between ‘a teacher and a teacher’
Collaboration is more likely to occur between participants with a similar status.
Examples: between ‘a student and a student’, or between ‘a teacher and a teacher’
Participants normally perform specific types of actionsParticipants are allowed to perform similar ranges of actions
Participants may have (or may not have) a similar level of knowledge or degree of expertiseParticipants have a similar level of knowledge or degree of expertise
Participants systematically divide the main task into some sub-tasks among themselves
Each participant individually works on a specific sub-task
Finally, the completed sub-tasks are assembled and presented in form of a final output/artifact
Degree of division of labor is very high
Participants do not divide the main task into sub-tasks
All of participants spontaneously work on the main task together in a collective manner
Some low degree of division of labor may occur accidentally and spontaneously
Participants attempt to reach a common and shared goalParticipants attempt to reach a common and shared goal

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