Optimization of Learning Performance on Multimedia Items using Machine-learning Methods

Castle Rock Research provides quality curriculum-based educational resources to students, parents and educators, both online and in print. Reinforcement has been well-studied in psychology and proven to be an efficient learning technique. However, learning behavior varies from one individual to another. It is important to understand one’s learning capabilities and response pattern so as to customize the reinforcement process and to optimize the performance of individual learners.

A Statistical Model to Assess Cognitive Skills

Castle Rock Research provides quality curriculum-based educational resources to students, parents and educators, both online and in print. Assessment of learned knowledge needs to focus on two distinct aspects: knowledge retention and associated cognitive skills. Knowledge retention not only refers to the ability to recall learned facts but also the ability to understand the relationship between these facts (ie to understand the structure of the learned domain knowledge).

A Parameter-based Statistical Algorithm for Math Items in Multimedia Education

Castle Rock Research provides quality curriculum-based educational resources to students, parents and educators, both online and in print. This project involves the design of a parameter-based statistical algorithm to automatically generate math questions for multimedia education applications. Rather than relying on a curriculum designer to create questions one by one, multiple questions can be generated by the algorithm. By varying the parameter values, the model is able to control the difficulty level of the questions.

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