ERIC Number: ED560876
Record Type: Non-Journal
Publication Date: 2015-Jun
Pages: 4
Abstractor: As Provided
ISBN: N/A
ISSN: N/A
EISSN: N/A
Measuring Problem Solving Skills in Plants vs. Zombies 2
Shute, Valerie J.; Moore, Gregory R.; Wang, Lubin
International Educational Data Mining Society, Paper presented at the International Conference on Educational Data Mining (EDM) (8th, Madrid, Spain, Jun 26-29, 2015)
We are using stealth assessment, embedded in "Plants vs. Zombies 2," to measure middle-school students' problem solving skills. This project started by developing a problem solving competency model based on a thorough review of the literature. Next, we identified relevant in-game indicators that would provide evidence about students' levels on the various problem-solving facets. Our problem solving model was implemented in the game via Bayesian networks. To validate the stealth assessment, we ran a small pilot study to collect data from students who played our game-based assessment and completed an external problem solving measure ("MicroDYN"). Preliminary results indicate that problem solving estimates derived from the game significantly correlate with the external measure, suggesting that our stealth assessment is valid. Our next steps include running a larger validation study (in progress) and developing tools to help educators interpret the results of the assessment. [For complete proceedings, see ED560503.]
Descriptors: Middle School Students, Problem Solving, Educational Games, Bayesian Statistics, Student Evaluation, Evaluation Methods, Validity, Models, Educational Indicators, Pilot Projects, Data Collection, Correlation, Measures (Individuals)
International Educational Data Mining Society. e-mail: admin@educationaldatamining.org; Web site: http://www.educationaldatamining.org
Publication Type: Speeches/Meeting Papers; Reports - Research
Education Level: Middle Schools; Secondary Education; Junior High Schools
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: International Educational Data Mining Society
Grant or Contract Numbers: N/A