Dickey- Engaging By Design: How Engagement Strategies in Popular Computer and Video Games Can Inform Instructional Design

Dickey points out how computer and video games excel at engaging players, and that there are a number of strategies that seem to be employed to keep players engaged in the gameplay. In the field of education, there is a growing movement now to try to bring gameplay strategies into educational applications, to motivate and engage students in learning to the same degree that they are engaged in playing video/computer games. Dickey identifies then several strategies and methods that foster engagement in games and discusses how such strategies and methods can inform instructional design. The key strategies are: Player positioning, or point of view; the use of narratives; and methods employed to make interactions interesting such as action and time hooks.

Obviously in the design of our Microarray learning modules, we are interested in making the learning interactive and game-like. It has been hard though to take the fairly abstract scientific concepts which Microarrays deal with and import game strategies into their presentation. The use of narrative doesn’t really make sense given that this is a pretty specialized laboratory procedure and any kind of lab-based narrative seemed both artificial and cartoonish. So we could only think about some of the kind of “hooks” that might be employed in playing more visually abstract games like Tetris- which actually can look a lot like a microarray sometimes. Still we have been constrained by needing the game- even the microarray rearranging type game to adhere to scientific accuracy so a row of squares has to retain its meaning as a microarry, and so we can only allow a certain amount of manipulation of the variables… We haven’t quite figured this out.

Schwann & Riemp-The cognitive benefits of interactive videos: learning to tie nautical knots

Pretty straightforward study that establishes the benefit of interactive dynamic visualisations over non-interactive forms in that the interactivity allows persons great control over their learning- the pace, and process.  With the caveat that the interactive features shouldn’t increase cognitive load.  In this study, participants learned to tie nautical knots (of increasing degrees of difficulty) by watching videos. With the interactive videos, participants were able to pause, replay, slow down and so on, which was essential when the knots became more complex.  The participants that had access only to non-interactive videos took much longer than their counterparts to learn the knots.

Rieber- Discovery learning, Referential processing, Multimedia explanations, Simulations

Rieber et al. look at computer-based simulations, and how to promote referential processing through supplementing the simulations with brief multimedia explanations. Their findings support the usefulness of brief multimedia explanations coupled with appropriate representational feedback in the simulation to facilitate more referential processing and deeper learning. I find the following concepts from this article to be especially important to keep in mind for the design of any simulation-based educational media:

1) The cognitive processing called for through computer-based simulations, especially when they are “video game-like”, is primarily VISUAL (see Dual Coding Theory)

2) The necessity for timely feedback to facilitate reflective thinking.

3) The affordances of computer-based simulations to engage the learner in experiential, discovery-oriented, “interactive” learning.

4) The importance of the form of representation (in the design of the interface) for promoting engagement and or reflection.

The notion of referential processing comes from Pavio’s “Dual Coding Theory” (DCT). DCT proposes two processing systems in the brain for visual and verbal information. Within and between both systems, or “channels”, there are different levels of processing- representational, associational, and referential. Representational processing takes place in each respective channel depending on the representational nature of the information (visual or verbal), and associational processing also takes place in each channel (again in relation to the representation of information), but referential processing moves between both channels and functions to relate coding between the two channels. When information is processed in this way within and between both channels, there is a greater chance for retrieval and usage of the information.

An implication of DCT is thus that the way information is represented then will greatly affect the processing of that information; and for this reason, the representation of information becomes an important issue in the design of educational materials. Computer-based simulations can be used in education, and their interactive affordances can provide ways for students to learn more difficult conceptual material through experiential learning scenarios, they enable the student to engage in “discovery learning.” Computer-based simulations may be especially effective for learing complex systems like physics by letting a student focus first on conceptual understanding and approach the material through experiences rather than explanations. However, simulations that are purely exploratory may not provide enough support for referential processing as the representational nature of simulations is overwhelmingly VISUAL. Thus, this is where Rieber et al. write that “the “video game-like” quality of the simulation may have interfered with referential processing by only promoting processing in the visual system and discouraging processing in the verbal system” (309). Being immersed in the overwhelmingly visual realm of the simulation seems to disallow students from the kind of reflection needed for referential processing.

Also, another important concept is the importance of FEEDBACK:

“One of the most important considerations in a simulation’s interface design is how to provide meaningful feedback to the user… Given the way computers can represent feedback in a simulation, research is needed to ensure that design decisions are made based on the psychological needs of the individual user and not simply on what the computer is capable of doing” (308).

Rieber’s study proposed to supplement a simulation (on physics concepts) with five short and embedded explanations. The explanations themselves were then provided to the student either as graphical feedback or textual feedback. The feedback (whether graphical or textual) was provided as brief explanations of the scientific principle being modeled after the student had an oppportunity to interact with the simulation, but before they mastered the content. Findings indicated that students had the best scores for explicit learning (which implies better referential processing) when using the simulations embedded with graphical feedback.