How could I apply computer-mediated discourse analysis (CMDA) in my research interests?

In researching cognitive influences that gamification can have on learning, CMDA can be used to identify how participant comfort level influences performance.  In fact, this approach would be effective for researching serious games in education as well.  Research participants that otherwise fit the requirements could skew findings because of their comfort level interacting with game-like features.  

In learning, students have varying degrees of comfort with technology, which can make learning with technology a hinderance in some situations.  Game-like learning activities are designed to motivate and excite students to keep them engaged with the content.  If the student is not comfortable with the game-like features they will struggle and not benefit from the actual content.  Jong et al. (2016) implemented a virtual mentor into a serious game.  The purpose was to assist nonplayer participants with game interaction.  Interviews with select control group participants noted their lack of game play experience hindered their ability to learn.  The findings indicated that nonplayer participants that had the mentor to help them interact with the game, showed significant improvements in learning achievement.

To implement in research message boards could be added to the gamification module, with some threads addressing technical challenges.  This application of CMDA would apply both quantitative and qualitative methodologies.  Overall assessment of scores can be analyzed, message board interaction can be analyzed and then associated with scores generated in the learning assessments.  This will add the context of technology comfort level with score leveling.

The integration of CMDA with gamification research can be used in two ways.  First, it is a means to validate quantitative scores since additional meaning will be added to why these scores were achieved.  For example, did the participant struggle with the actual content or did they struggle with the gamification interaction.  Second, if it is found that lower scores correlate to discomfort with the game-like features, then interviews could be done to identify potential design improvements.  For example, offer more detailed directions, create example modules to practice interaction before entering the actual module, or simplify interactions.

Jong M.S.Y., Shang J., Tam V.W.L. (2016) Using Non-player Characters to Scaffold Non-gamer Students in Serious Gaming. In: Spector M., Lockee B., Childress M. (eds) Learning, Design, and Technology. Springer, Cham

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