Mobile-Learning (M-learning) makes many learners get the advantages of both traditional learning and E-learning.
Currently, Web-based Mobile-Learning Systems have created many new ways and defined new relationships between
educators and learners. Association rule mining is one of the most important fields in data mining and knowledge
discovery in databases. Rules explosion is a serious problem which causes great concerns, as conventional mining
algorithms often produce too many rules for decision makers to digest. Since Web-based Mobile-Learning System
collects vast amounts of student profile data, data mining and knowledge discovery techniques can be applied to find
interesting relationships between attributes of learners, assessments, the solution strategies adopted by learners and so
on. Therefore ,this paper focus on a new data-mining algorithm, combined with the advantages of genetic algorithm and
simulated annealing algorithm , called ARGSA(Association rules based on an improved Genetic Simulated Annealing
Algorithm), to mine the association rules. This paper first takes advantage of the Parallel Genetic Algorithm and
Simulated Algorithm designed specifically for discovering association rules. Moreover, the analysis and experiment are
also made to show the proposed method is superior to the Apriori algorithm in this Mobile-Learning system.