Data Analytic and Psychometric Methods for Innovative Educational Systems Data Analytic and Psychometric Methods for Innovative Educational Systems STATEMENT OF WORK Introduction& Purpose: Pearson is developing a multipronged research agenda move to instruction with invisible assessment that is done in an unobtrusive, ubiquitous way. This kind of assessment is what will be able to provide information to teachers that can inform daily instructional decisions. That means we have to be able to extract information from open, rich environments and use it to make inferences about students knowledge, skills, and attributes. We need to be able to build models using new and different kinds of information (durations, counts of events, sequences of action). Games are one example of this type of environment. It is good to use them as a starting place because we know students are engaged (97% of US kids 12-17 play) and they help kids learn (as seen in recent meta-analyses). The purpose of this contract is to draw on Dr. Roy Levys extensive research background in statistical methodology and educational inference to help develop and evaluate models of student characteristics based on data from rich digital environments. In the game literature, there has been an accepted definition of player motivations as: reaching achievements, social interaction, exploration of environments, and interference with play of others. In the learning literature there is a long history of goal/ motivation theory and research (approach and avoidance, etc.) that is related to achievement. Recently, gamification advocates assigning points as positive reinforcement for a wide array of behaviors, but this only impacts one type of motivation. We expect that we can use game behavior to better detect student motivation types or personas. This will lead us to be able to make both recommendations to teachers and to build adaptivity/ personalization around best motivation techniques, not just skill level. This project addresses assessment needs of Pearson, modeling the use of ubiquitous, unobtrusive assessment, as well as learning analytics and efficacy for open-ended environments.
|Effective start/end date||9/1/13 → 2/28/16|
- INDUSTRY: Domestic Company: $124,247.00
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