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Evolution of an adaptive mathematics learning game for lower primary students

Authors: Siti Afiqah Ismail and Jason Teo Tze Wi

Abstract:

The newly coined term “courseware” was actually derived from the words “course” and “software”. The courseware that is available nowadays has been added with the
adaptiveness values. These adaptive elements have been implemented by researchers in various ways. Some are using fuzzy, neural-network or even metaheuristics to
implement the adaptive elements in to their courseware systems. By using these approaches, they apply the adaptiveness by optimizing the learning path. In this
research, the learning path will be optimized based on the learners’ understanding level of the concept being learnt. This approach is commonly known as personalization. In
this project, the Evolutionary Algorithm approach is selected as the optimization method. The EA used in this project is Genetic Programming. Instead of evolving the
separate representations to the solution, Genetic Programming evolves the solution itself. Genetic Programming usually evolves computer programs instead of evolving the
solution representations found in Genetic Algorithms. Nonetheless, the process of Genetic Programming is still similar to Genetic Algorithms. Apart from implementing
GP into the learning system, this research utilizes the basic user interface design for designing an interface of the mathematics learning game. Since the main audience of
the game is young children, some interface design elements especially suited for young children have to be taken into account. In this research, 4 experiments had been
conducted to test the algorithms implemented. In comparison, experiment 2 yielded better results compared to other experiments. In experiment 2, the level was set to be
fixed, while in the other experiments, the level changing parameter is set to be random. In experiments 1, 3 and 4, the findings show that the random changing level is
unpredictable. Some level jumps are too high and some level jumps are too low. In general, the overall outcomes of this research demonstrate that EAs can be a viable
approach in terms of implementing adaptive courseware at least in the realms of teaching mathematics to young children. 

 

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