Abstract
This chapter describes ELaCv2, which is the 2nd improved version of ELaC that is described in a previous work [1]. ELaCv2 is a novel integrated adaptive educational environment that provides e-training in programming and the language ‘C’. It adapts the learning material and process to the learner’s background, knowledge level, needs and ability. The adaptivity is achieved due to the incorporation of a 4-parameter student model that was developed taking into consideration the data and results that have been gathered by the student model of ELaC. The particular student model is responsible for identifying and updating the student’s knowledge level and needs each time from the beginning to the end of the learning process, allowing the learner to complete the e-training course at her/his own pace and according to her/his ability. The system can identify, each time and for each individual learner, which domain concepts are partially or completely known, which domain concepts are unknown, which domain concepts have been assimilated and which domain concepts need revision. Thus, the system schedules dynamically the learning material for each individual learner on the fly, minimizing the time that is required for her/his to complete the e-training course, and improving, simultaneously, the learning results.
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Chrysafiadi, K., Virvou, M., Sakkopoulos, E. (2020). Optimizing Programming Language Learning Through Student Modeling in an Adaptive Web-Based Educational Environment. In: Virvou, M., Alepis, E., Tsihrintzis, G., Jain, L. (eds) Machine Learning Paradigms. Intelligent Systems Reference Library, vol 158. Springer, Cham. https://doi.org/10.1007/978-3-030-13743-4_11
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