Adapting instruction in search of 'a significant difference'
Journal of Network and Computer Applications
An intelligent distributed environment for active learning
Journal on Educational Resources in Computing (JERIC)
Automatic Construction of Decision Trees from Data: A Multi-Disciplinary Survey
Data Mining and Knowledge Discovery
Knowledge Discovery with Genetic Programming for Providing Feedback to Courseware Authors
User Modeling and User-Adapted Interaction
Personalized links recommendation based on data mining in adaptive educational hypermedia systems
EC-TEL'07 Proceedings of the Second European conference on Technology Enhanced Learning: creating new learning experiences on a global scale
Educational data mining: a review of the state of the art
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Data mining for adaptive learning in a TESL-based e-learning system
Expert Systems with Applications: An International Journal
Using data mining technique to enhance tax evasion detection performance
Expert Systems with Applications: An International Journal
Artificial Intelligence Review
Identifying patterns in learner's behavior Using Markov chains and n-gram models
CSCC'11 Proceedings of the 2nd international conference on Circuits, Systems, Communications & Computers
Constructing concept maps for adaptive learning systems based on data mining techniques
Expert Systems with Applications: An International Journal
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The purpose of this paper is to propose an adaptive system analysis for optimizing learning sequences. The analysis employs a decision tree algorithm, based on students' profiles, to discover the most adaptive learning sequences for a particular teaching content. The profiles were created on the basis of pretesting and posttesting, and from a set of five student characteristics: gender, personality type, cognitive style, learning style, and the students' grades from the previous semester. This paper address the problem of adhering to a fixed learning sequence in the traditional method of teaching English, and recommend a rule for setting up an optimal learning sequence for facilitating students' learning processes and for maximizing their learning outcome. By using the technique proposed in this paper, teachers will be able both to lower the cost of teaching and to achieve an optimally adaptive learning sequence for students. The results show that the power of the adaptive learning sequence lies in the way it takes into account students' personal characteristics and performance; for this reason, it constitutes an important innovation in the field of Teaching English as a Second Language (TESL).