Allan Jeong

The Sequential Analysis of Group Interaction and Critical Thinking in Online Threaded Discussions

The purpose of this study was to examine group interaction and critical thinking in online threaded discussions. The Discussion Analysis Tool (DAT) was used to identify patterns in interactions and determine which interactions promoted critical thinking. With DAT, discussion transcripts were coded across twelve critical thinking events, and transitional probabilities between events were computed using the method of sequential analysis (Bakeman and Quera 1995). By computing the transitional probabilities, DAT generated useful quantitative descriptions of interaction patterns and critical thinking events that followed. The findings show that interactions involving conflicting viewpoints promoted more discussion and critical thinking, and that evaluation of arguments was more likely to occur as conclusions were being drawn-not as arguments were being presented. Tools such as DAT will be useful for empirically testing interactions and structures that enhance online discussions, providing the basis for more systematic testing of instructional interventions and computer-conferencing technologies.

Scaffolding collaborative argumentation in asynchronous discussions with message constraints and message labels

This study examined the effects of message constraints and labels on collaborative argumentation in asynchronous online discussions. Thirty-eight undergraduate students in an introductory educational technology course were assigned to one of three groups. In one group, students posted specific types of messages using a prescribed set of message categories such as argument, evidence, critique, and explanation. Using the same message categories, another group inserted message labels directly into the subject headings to identify each message by category and increase the visibility of the arguments and challenges presented in debates. A control group received none of the above instructions and constraints. Students in the constraints-with-labels group were significantly less likely to (a) challenge other students, and (b) respond to challenges from other students. The label used to identify critiques might have discouraged students from posting critiques and shifted attention to posting more arguments, following up explanations with more explanations, and evidence with more evidence.

A Guide to Analyzing Message-Response Sequences and Group Interaction Patterns in Computer-Mediated Communication

This paper proposes a set of methods and a framework for evaluating, modeling, and predicting group interactions in computer‐mediated communication. The method of sequential analysis is described along with specific software tools and techniques to facilitate the analysis of message–response sequences. In addition, the Dialogic Theory and its assumptions are presented to establish a theoretical framework and guide to using sequential analysis in computer‐mediated communication research. Step‐by‐step instructions are presented to illustrate how sequential analysis can be used to measure the way latent variables (e.g., message function, response latency, communication style) and exogenous variables (e.g., gender, discourse rules, context) affect how likely a message is to elicit a response, the types of responses elicited by the message, and whether or not the elicited sequence of responses (e.g., claim → challenge → explain) mirror the processes that support group decision‐making, problem‐solving, and learning.

How Day of Posting Affects Level of Critical Discourse in Asynchronous Discussions and Computer-Supported Collaborative Argumentation.

In asynchronous threaded discussions, messages posted near the end of the week provide less time for students to critically examine and respond to ideas presented in the messages than messages posted early in the week. This study examined how the day in which messages are posted (early, midweek and weekend) in computer-supported collaborative argumentation affect the number of responses elicited by arguments and challenges, and how its effects differ across the four types of exchanges (argument–challenge, challenge–counterchallenge, challenge–explain, challenge–evidence) that serve as indicators of critical discourse. This study found that the day of posting had a significant effect on the number of responses elicited per message, with the greatest to smallest effect on argument–challenge, challenge–counterchallenge, challenge–explain and challenge–evidence exchanges respectively. These findings highlight some of the limitations of asynchronous discussions, and suggest alternative ways to implement and design discussion environments to promote higher levels of critical discourse. [ABSTRACT FROM AUTHOR]

Effects of Pre-Structuring Discussion Threads on Group Interaction and Group Performance in Computer-Supported Collaborative Argumentation

This study examined the effects of pre‐structuring discussion threads on group performance in computer‐supported collaborative argumentation where students labeled their messages as arguments, challenges, supporting evidence, and explanations on a threaded discussion board. In the pre‐structured group students were required to post supporting and opposing arguments to designated and separate discussion threads. In the control group no discussion threads were designated for posting supporting and opposing arguments. The mean number of challenges elicited per argument was 64% greater with pre‐structured threads (ES = +.47). No significant differences were found in the mean number of counter‐challenges, supporting evidence, and explanations posted in reply to challenges. The findings suggest that prestructured discussion threads can increase the frequency of argument→challenge exchanges needed to initiate critical discourse.

Intrateam Communication and Performance in Doubles Tennis

Verbal and nonverbal communication is a critical mediator of performance in team sports and yet there is little extant research in sports that involves direct measures of communication. Our study explored communication within NCAA Division I female tennis doubles teams. Video and audio recordings of players during doubles tennis matches captured the communications that took place between and during points. These recordings were coded and sequential analysis computed using the Discussion Analysis Tool software (Jeong, 2003). Results indicated that most communications were emotional (i.e., > 50%) or action statements (i.e., > 25%). Winning teams exhibited significantly different communication sequences than losing teams. In particular, winning teams had a more homogeneous model of communication, which perhaps makes message interpretation more reliable. Finally, winning teams exchanged twice as many messages as losing teams.

Model-Based Methods for Assessment, Learning, and Instruction: Innovative Educational Technology at Florida State University

In this chapter, we describe our research and development efforts relating to eliciting, representing, and analyzing how individuals and small groups conceptualize complex problems. The methods described herein have all been developed and are in various states of being validated. In addition, the methods we describe have been automated and most have been integrated in an online model-based set of tools called HIMATT (Highly Interactive Model-based Assessment Tools and Technologies; available for research purposes at http://himatt.ezw.uni-freiburg.de/cgi-bin/hrun/himatt.pl and soon to be available on a server at Florida State University). HIMATT continues to expand in terms of the tools and technologies included. Our methods and tools represent an approach to learning and instruction that is now embedded in many of the graduate courses at Florida State University and also at the University of Freiburg. We call our approach model-based because it integrates representations of mental models and internal cognitive processes with tools that are used to (a) assess progress of learning, and (b) provide the basis for informative and reflective feedback during instruction.

Modeling, Assessing, and Supporting Key Competencies Within Game Environments

The first challenge of accomplishing the goals of any successful instructional system depends on accurately identifying characteristics of a particular learner or group of learners – such as the type and level of specific knowledge, skills, and other attributes. The second challenge is then leveraging the information to improve learning. This chapter is intended to extend current thinking about (a) educationally valuable skills and (b) instructional system design by describing an approach for analyzing key competencies and developing valid assessments embedded within an immersive game. Specifically, we will describe theoretically based research relating to stealth assessment, diagnosis, and instructional decisions, operational within an immersive game environment. Stealth assessment and diagnosis occur during the learning (playing) process, and instructional decisions are based on inferences of learners’ current and projected competency states. Inferences – both diagnostic and predictive – will be handled by Bayesian networks and used directly in student models to handle uncertainty via probabilistic inference to update and improve belief values on learner competencies. Resulting probabilities inform decision making, as needed in, for instance, the selection of instructional support based on the learner’s current state.

The effects of active versus reflective learning style on the processes of critical discourse in computer‐supported collaborative argumentation

This study examined how message-response exchanges produced in the interactions between active learners only, reflective learners only, active-reflective learners and reflective-active learners affected how often active versus reflective learners posted rebuttals to arguments and challenges across four types of exchanges that believed to promote critical discourse (argument–challenge, challenge–counterchallenge, challenge–explain, challenge–evidence) in computer-supported collaborative argumentation (CSCA). This study found that the exchanges between reflective learners produced 44% more responses than in the exchanges between active learners ( ES = +0.17). The reflective–reflective exchanges produced 47% more responses than the active–reflective exchanges ( ES = +0.18). These results suggest that groups with reflective learners only are likely to produce more critical discourse than groups with active learners only, and the ratio of active–reflective learners within a group can potentially influence overall group performance. These findings illustrate how specific traits of the learner can affect discourse processes in CSCA and provide insights into process-oriented strategies and tools for structuring dialogue and promoting critical inquiry in online discussions.

Gender Interaction Patterns and Gender Participation in Computer-Supported Collaborative Argumentation

This case study examined interaction patterns between men and women and the effects of the patterns on gender participation in online debates. Students labeled messages to identify each message as an argument, challenge, evidence, or explanation when posting messages to the debates. The results revealed no differences in the number of male and female challenges elicited by male versus female messages, number of male and female rebuttals (e.g., explanations and counterchallenges) elicited by male versus female challenges, and the frequency of challenges and explanations posted by men versus women. These findings suggest that gender differences in communication styles do not necessarily produce gender differences in response patterns and participation. Other factors such as male–female ratio and task structures can affect gender interaction patterns and gender participation. Nevertheless, this study demonstrated how interaction patterns can provide causal explanations for observed differences and similarities in male and female performance in computer-mediated environments.