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Direct linkXuanyan Zhong; Zehui Zhan – Interactive Technology and Smart Education, 2025
Purpose: The purpose of this study is to develop an intelligent tutoring system (ITS) for programming learning based on information tutoring feedback (ITF) to provide real-time guidance and feedback to self-directed learners during programming problem-solving and to improve learners' computational thinking. Design/methodology/approach: By…
Descriptors: Intelligent Tutoring Systems, Computer Science Education, Programming, Independent Study
Download full textXu, Jia; Wei, Tingting; Lv, Pin – International Educational Data Mining Society, 2022
In an Intelligent Tutoring System (ITS), problem (or question) difficulty is one of the most critical parameters, directly impacting problem design, test paper organization, result analysis, and even the fairness guarantee. However, it is very difficult to evaluate the problem difficulty by organized pre-tests or by expertise, because these…
Descriptors: Prediction, Programming, Natural Language Processing, Databases
Wang, Tiantian; Su, Xiaohong; Ma, Peijun; Wang, Yuying; Wang, Kuanquan – Computers & Education, 2011
Learning to program is a difficult process for novice programmers. AutoLEP, an automated learning and assessment system, was developed by us, to aid novice programmers to obtain programming skills. AutoLEP is ability-training-oriented. It adopts a novel assessment mechanism, which combines static analysis with dynamic testing to analyze student…
Descriptors: Foreign Countries, Feedback (Response), Program Effectiveness, Learning Experience
Shuqun, Yang; Shuliang, Ding; Zhiqiang, Yao – International Journal of Distance Education Technologies, 2009
Cognitive diagnosis (CD) plays an important role in intelligent tutoring system. Computerized adaptive testing (CAT) is adaptive, fair, and efficient, which is suitable to large-scale examination. Traditional cognitive diagnostic test needs quite large number of items, the efficient and tailored CAT could be a remedy for it, so the CAT with…
Descriptors: Monte Carlo Methods, Distance Education, Adaptive Testing, Intelligent Tutoring Systems
Hu, Xiangen, Ed.; Barnes, Tiffany, Ed.; Hershkovitz, Arnon, Ed.; Paquette, Luc, Ed. – International Educational Data Mining Society, 2017
The 10th International Conference on Educational Data Mining (EDM 2017) is held under the auspices of the International Educational Data Mining Society at the Optics Velley Kingdom Plaza Hotel, Wuhan, Hubei Province, in China. This years conference features two invited talks by: Dr. Jie Tang, Associate Professor with the Department of Computer…
Descriptors: Data Analysis, Data Collection, Graphs, Data Use
