Learning Gains for Core Concepts in a Serious Game on Scientific Reasoning
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| Title: | Learning Gains for Core Concepts in a Serious Game on Scientific Reasoning |
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| Language: | English |
| Authors: | Forsyth, Carol, Pavlik, Philip, Graesser, Arthur C., Cai, Zhiqiang, Germany, Mae-lynn, Millis, Keith, Dolan, Robert P., Butler, Heather, Halpern, Diane, International Educational Data Mining Society |
| Source: | International Educational Data Mining Society. 2012. |
| Availability: | International Educational Data Mining Society. e-mail: admin@educationaldatamining.org; Web site: http://www.educationaldatamining.org |
| Peer Reviewed: | N |
| Page Count: | 4 |
| Publication Date: | 2012 |
| Sponsoring Agency: | Institute of Education Sciences (ED) National Science Foundation |
| Contract Number: | R305B070349 |
| Document Type: | Reports - Research Speeches/Meeting Papers |
| Education Level: | Higher Education Postsecondary Education |
| Descriptors: | Learning, Cognitive Processes, Logical Thinking, Scientific Methodology, Inquiry, Fundamental Concepts, Intelligent Tutoring Systems, Educational Games, Pretests Posttests, College Students, Regression (Statistics), Validity |
| Geographic Terms: | California |
| Abstract: | "OperationARIES!" is an Intelligent Tutoring System that teaches scientific inquiry skills in a game-like atmosphere. Students complete three different training modules, each with natural language conversations, in order to acquire deep-level knowledge of 21 core concepts of research methodology (e.g., correlation does not mean causation). The student first acquires basic declarative knowledge and then applies the knowledge by critiquing case studies on scientific methodology and finally generating questions that reflect the core topics. A study using a pretest-training-posttest design was conducted in which 46 college students interacted with the modules of "OperationARIES!", resulting in thousands of logged measures. The goal of this investigation was to discover the different trajectories of learning within 11 of these core concepts by evaluating 3 main constructs (e.g., discrimination, generation, and time on task) represented by key logged measures. Different constructs showed relationships with specific core concepts. Three core concepts were analyzed with stepwise regression and 5-fold cross-validation in order to discover contributing factors to learning gains for these core concepts. [For the complete proceedings, "Proceedings of the International Conference on Educational Data Mining (EDM) (5th, Chania, Greece, June 19-21, 2012)," see ED537074.] |
| Abstractor: | As Provided |
| Number of References: | 15 |
| IES Funded: | Yes |
| Entry Date: | 2012 |
| Accession Number: | ED537227 |
| Database: | ERIC |
| Abstract: | "OperationARIES!" is an Intelligent Tutoring System that teaches scientific inquiry skills in a game-like atmosphere. Students complete three different training modules, each with natural language conversations, in order to acquire deep-level knowledge of 21 core concepts of research methodology (e.g., correlation does not mean causation). The student first acquires basic declarative knowledge and then applies the knowledge by critiquing case studies on scientific methodology and finally generating questions that reflect the core topics. A study using a pretest-training-posttest design was conducted in which 46 college students interacted with the modules of "OperationARIES!", resulting in thousands of logged measures. The goal of this investigation was to discover the different trajectories of learning within 11 of these core concepts by evaluating 3 main constructs (e.g., discrimination, generation, and time on task) represented by key logged measures. Different constructs showed relationships with specific core concepts. Three core concepts were analyzed with stepwise regression and 5-fold cross-validation in order to discover contributing factors to learning gains for these core concepts. [For the complete proceedings, "Proceedings of the International Conference on Educational Data Mining (EDM) (5th, Chania, Greece, June 19-21, 2012)," see ED537074.] |
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