Matching Items (2)
Description
This dissertation describes Space Vector 1 and Space Vector 2, two video games that introduce Newtonian mechanics concepts. Space Vector 1 is a side-scrolling game, in which players choose to drop bombs or supplies. Players had to identify if the physics was correct during a mission, or they had to plot the trajectory of a falling object, which was then simulated. In Space Vector 2, players were given velocity and acceleration values and had to plot the trajectory of a spaceship across a grid, or players were given a trajectory of a spaceship on a grid and had to program the velocity and acceleration values to produce the trajectory. Space Vector 1 was evaluated with 65 college undergraduates. Space Vector 2 was evaluated with 18 high school students. All participants were given a subset of the Force Concept Inventory, a standard assessment tool in physics education, as a pretest and posttest. Space Vector 1 was evaluated with a single group pretest-posttest design. Space Vector 2 was evaluated with a 2 x 2 ANOVA, where the factors were game mechanic (prediction mechanic or programming mechanic) and bonus questions (bonus question after a mission or no bonus question). Bayesian statistical methods were used for the data analysis. The best estimate for the average change in test scores for Space Vector 1 was a score gain of 1.042 (95% Highest Density Interval (HDI) [0.613, 1.487]) with an effect size of 0.611 (95% HDI [0.327, 0.937]). The best estimate for the grand mean of change scores in Space Vector 2 was an increase of 0.78 (95% HDI [-0.3, 1.85]) with an effect size of 0.379 (95% HDI [-0.112, 0.905]). The prediction
o bonus question version produced the largest change in score, where the best estimate for the mean change score was an increase of 1.2. The estimation intervals for the Space Vector 2 results were wide, and all included zero as a credible value.
o bonus question version produced the largest change in score, where the best estimate for the mean change score was an increase of 1.2. The estimation intervals for the Space Vector 2 results were wide, and all included zero as a credible value.
ContributorsKeylor, Eric Karl (Author) / Gee, James P. (Thesis advisor) / Stevens, Scott M. (Committee member) / Nelson, Brian C. (Committee member) / Atkinson, Robert K. (Committee member) / Arizona State University (Publisher)
Created2014
Description
Serious or educational games have been a subject of research for a long time. They usually have game mechanics, game content, and content assessment all tied together to make a specialized game intended to impart learning of the associated content to its players. While this approach is good for developing games for teaching highly specific topics, it consumes a lot of time and money. Being able to re-use the same mechanics and assessment for creating games that teach different contents would lead to a lot of savings in terms of time and money. The Content Agnostic Game Engineering (CAGE) Architecture mitigates the problem by disengaging the content from game mechanics. Moreover, the content assessment in games is often quite explicit in the way that it disturbs the flow of the players and thus hampers the learning process, as it is not integrated into the game flow. Stealth assessment helps to alleviate this problem by keeping the player engagement intact while assessing them at the same time. Integrating stealth assessment into the CAGE framework in a content-agnostic way will increase its usability and further decrease in game and assessment development time and cost. This research presents an evaluation of the learning outcomes in content-agnostic game-based assessment developed using the CAGE framework.
ContributorsVerma, Vipin (Author) / Craig, Scotty D (Thesis advisor) / Bansal, Ajay (Thesis advisor) / Amresh, Ashish (Committee member) / Baron, Tyler (Committee member) / Levy, Roy (Committee member) / Arizona State University (Publisher)
Created2021