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Visualizing Collaborative Processes in a Knowledge Community and Inquiry Curriculum for Grade 12 Biology

Fri, April 5, 12:00 to 1:30pm, Metro Toronto Convention Centre, Floor: 800 Level, Room 801B

Abstract

Theoretical Framework
To be successful, collaborative learning depends on effective interactions among learners. However, merely assigning students a collaborative task and providing them with communication tools is not sufficient to ensure that their interactions will be productive (Weinberger et al., 2009). In learning communities (Bielaczyc & Collins, 1999), the inclusion of Learning Analytics (LA) can assist students and teachers in monitoring the learning process to improve their collaborative experiences. LA draws upon the research, methods, and techniques from a variety of different disciplines including business analytics, data mining, information visualization, psychology, and the learning sciences (Ferguson, 2012).

Objectives
The purpose of this study was to develop a series of visualizations to represent the collaborative processes of small groups of students (i.e. 3-7 each) who were engaged in a KCI curriculum as part of a Grade 12 Biology course. The goal of this work was to allow visual comparisons to be made both within and between groups, and to inform the design of student- and teacher-facing LA to support small group collaborations.

Methods & Data Sources
Participants for this study included a high school biology teacher and two class sections of Grade 12 Biology students (n=29). Over the course of each curricular unit, students co-constructed a community knowledge base that was later used as a resource for collaborative "review challenge" activities. The data for this study includes audio/video footage for seven small groups that was captured during these "review challenge" activities. To analyze the collaborative processes of each group, the audio/video footage was coded using two different coding schemes: One for quality of collaboration and another for group member contributions. The quality of collaboration coding scheme was adapted from Smith et al (2016). For each audio/video clip, codes were applied to 10-second segments of footage at 1 minute intervals. The group member contributions coding scheme was adapted from multiple sources, including Hmelo-Silver and Barrows (2008), Weinberger and Fischer (2006), and Chuy et al (2011). Here, codes were applied to every utterance contained in an audio/video clip (i.e. a full or partial sentence containing a single idea or question).

Results
Based on these coding schemes, two types of visualizations were developed to represent the collaborative processes of a group. The first was a temporal representation of groups' quality of collaboration, which included information such as session length, time spent on each question, and collaboration quality over time (see Figure 6). The second type of visualization was a sunburst representation depicting the contributions of various group members (see Figure 7). This visualization included information such as the proportion of contributions made by each member (i.e. balance of participation), levels of off-task behaviour, as well as the nature of questions and statements made (e.g. cognitive, metacognitive, social, task-oriented). The poster for this session will elaborate on how to interpret each type of visualization, and will discuss comparisons between groups.

Scholarly Significance
This work represents a first step towards developing group process analytics for KCI.

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