2 research outputs found
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Assessing Science Inquiry using MDP Goal Detectors
Complex cognitive tasks, such as science inquiry, often involve a sequence of goals, each of which is pursuedthrough a sequence of actions. Effective assessment of inquiry performance requires identification of these student goals.Markov decision processes (MDPs) have been used to infer goals and beliefs over a single directed sequence of actions (Bakeret al., 2009), but multi-goal complex systems are computationally prohibitive to model. This research investigates the useof targeted MDPs as goal detectors, embedded within a larger hidden Markov model (HMM) that accounts for the transitionbetween goals. This multi-layer approach allows the MDP state spaces to remain small while modeling complex cognition.Because canonical HMM estimation is complicated by the dynamic nature of MDPs, in which action probabilities depend oncontext, we explore several different estimation methods. The approach is applied to log-file data of test-taker interactions witha simulation-based science inquiry assessment
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Modifying Cognitive Load Component Survey for K-12 STEM Testing
Test-taker’s capability to answer questions is influenced by available cognitive resources for problem solving. Due tothe limited working memory capacity, excessive cognitive load for interpreting instruction would impact test-taker’s construct-relevant process and test validity. Especially in STEM assessment where multimedia and interactive design are widely used,test-takers can easily get overwhelmed by a large amount of visual or audio information. Testing materials should be designed tominimize the unnecessary cognitive load in order to increase cognitive resources for problem solving in the task. The CognitiveLoad Component Survey is one of the first self-report measurements distinguishing different types of cognitive load: intrinsiccognitive load, extraneous cognitive load, and germane cognitive load. We report modifications of this survey to fit into K-12educational assessment, results of measuring cognitive loads in a simulation-rich science assessment, and implications to usethis survey for future assessment development