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Adaptabilidade de Objetos de Aprendizagem usando Calibragem e Sequenciamento Adaptativo de Exercícios
Author(s) -
Rômulo César Silva,
Alexandre Ibrahim Direne,
Diego Marczal,
Ana Carla Borille,
Paulo Ricardo Bittencourt Guimarães,
Angelo da Silva Cabral,
Bruno Filla Camargo
Publication year - 2018
Publication title -
revista brasileira de informática na educação
Language(s) - English
Resource type - Journals
eISSN - 2317-6121
pISSN - 1414-5685
DOI - 10.5753/rbie.2018.26.01.70
Subject(s) - computer science , matching (statistics) , domain (mathematical analysis) , logarithm , artificial intelligence , mathematics , statistics , mathematical analysis
The work approaches theoretical and implementation issues of a framework for creating and executing Learning Objects (LOs) where problem-solving tasks are ordered according to the matching of two parameters, both calculated automatically: (1) student skill level and (2) problem solution difficulty. They are formally defined as algebraic expressions. The definition of skill level is achieved through a rating-based measure that resembles the ones of game mastery scales, while the solution difficulty is based on mistakes and successes of learners to deal with the problem. An empirical study based on existing students data demonstrated the suitability of the formulas. Besides, the motivational aspects of learning are considered in depth. In this sense, it is importante to propose activitites accordign to the student’s level of expertise, which is achieved through presenting students with exercises that are compatible with the difficulty degree of their cognitive skills. Also, the results of an experiment conducted with four highschool classes using the framework for the domain of logarithmic properties are presented.

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