II. ASPIREXS-LO: A PROPOSAL OF ALGORITHM FOR THE INTEGRATION OF ADAPTIVE DIDACTIC SEQUENCES
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Abstract
Within the field of adaptive learning, some proposals have opted for the
use of fuzzy inference systems as a method to obtain the amount and type of resources
or learning objects necessary for better student performance. However,
These proposals do not establish a method for the integration of didactic sequences from
of these learning resources. This research aimed to present a
algorithm for the production of adaptive didactic sequences based on the values
generated by fuzzy inference systems used in learning systems
adaptive. The methodology used was cascade development, which allowed generating
the Sequential, Prioritized, Interleaved and Recursive Depletion algorithm for the
Assignment of Learning Objects (ASPIRED). For testing purposes, this
algorithm was translated into the Python programming language where three
didactic sequences from different fuzzy values corresponding to four types of
learning objects (text, audio, video and infographics). As a result, it was observed that the
didactic sequences were generated with low execution times and with a low use of
processing resources and memory. It was concluded by mentioning that the algorithm has
as characteristics to be effective, modular, flexible, adaptable and understandable; Similarly,
the benefits and possible applications of the algorithm in future research were exposed
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Algorithm, Sequence, Didactics, Learning, Adaptive
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