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Xu, 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
Shi, Yang; Chi, Min; Barnes, Tiffany; Price, Thomas W. – International Educational Data Mining Society, 2022
Knowledge tracing (KT) models are a popular approach for predicting students' future performance at practice problems using their prior attempts. Though many innovations have been made in KT, most models including the state-of-the-art Deep KT (DKT) mainly leverage each student's response either as correct or incorrect, ignoring its content. In…
Descriptors: Programming, Knowledge Level, Prediction, Instructional Innovation
Bohorquez, Carlos; Marquet, Pascal – International Association for Development of the Information Society, 2019
This paper describes the first stages on the development of a design method of digital trainings using the collaborative authoring tool "ALO". Based on the theory of instrumental conflict (Marquet, 2005), this method highlights the necessity of the design digital trainings under the optimal harmonization for users/learners in didactic,…
Descriptors: Instructional Design, Programming, Conflict, Teaching Methods
Mao, Ye; Shi, Yang; Marwan, Samiha; Price, Thomas W.; Barnes, Tiffany; Chi, Min – International Educational Data Mining Society, 2021
As students learn how to program, both their programming code and their understanding of it evolves over time. In this work, we present a general data-driven approach, named "Temporal-ASTNN" for modeling student learning progression in open-ended programming domains. Temporal-ASTNN combines a novel neural network model based on abstract…
Descriptors: Programming, Computer Science Education, Learning Processes, Learning Analytics
Reis, Rosa; Marques, Bertil P. – International Association for Development of the Information Society, 2021
In this paper we present a model for designing professional courses in a blended learning context as a tool to help the interaction between students, teachers and learning resources. This model aims to promote new concepts, new approaches and new strategies that have been changing the paradigm of teaching and learning. To develop a course based on…
Descriptors: Programming, Instructional Design, Computer Science Education, Case Studies
An, Truong-Sinh; Krauss, Christopher; Merceron, Agathe – International Educational Data Mining Society, 2017
The emergence of Massive Open Online Courses (MOOCs) has enabled new research to analyze typical behaviors of learners. In this paper, we investigate whether this research is generalizable to other courses that are backed by a learning management system (LMS) as MOOCs are. Building on methods developed by others, we characterize individual…
Descriptors: Large Group Instruction, Online Courses, Student Behavior, College Students
Goldenson, Dennis – 1996
The assertion that "higher order" thinking skills can be improved by learning to program computers is not a new one. The idea endures even though the empirical evidence over the years has been mixed at best. In fact, there is no reason to expect that all programming courses will have identical, or even similar, effects. Such courses typically…
Descriptors: Academic Achievement, Authoring Aids (Programming), Computer Software, Computers

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