Abstract: The present invention relates to an apparatus and method for providing personalized adaptive e-learning, and more specifically, to an apparatus and method for estimating a learner's proficiency to each attribute and providing adaptive e-learning by taking into consideration an item answering result of an individual learner in a personalized learning environment.

Abstract: Provided are an apparatus and method for learner diagnosis using reliability of a cognitive diagnostic model, which estimates the reliability of the cognitive diagnostic model that estimates a concept vector (?) of a learner through a Q-matrix regarding a question and an R-matrix regarding a response to a question, the method including assuming a probability (P(X|?)) of a learner response (X) when a concept vector (?) of a learner is given; obtaining a concept pattern-specific probability (P(?|X)) of the learner from the assumed concept vector and learner response of the learner; obtaining an information entropy (H) value of the learner from the concept pattern-specific probability (P(?|X)) of the learner; and obtaining reliability (?) of an estimated result of a learner-specific concept understanding using the information entropy value of the learner and a number of concepts.

Abstract: The present invention relates to an apparatus and method for providing personalized adaptive e-learning, and more specifically, to an apparatus and method for estimating a learner's proficiency to each attribute and providing adaptive e-learning by taking into consideration an item answering result of an individual learner in a personalized learning environment.

Abstract: The present invention relates to a learning diagnosis apparatus, a method of diagnosing a learner's learning ability, and an adaptive learning system for providing adaptive learning using the diagnosis result. The learning diagnosis apparatus includes a database (DB) configured to store and manage adaptive learning data and store a program for estimating a learner's proficiency to each attribute and recommending learning content and a processor configured to execute the program, wherein the processor calculates a attribute proficiency vector estimation result of a specific learner using information about a solution to a personalized item together with group test solution information.