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Bhagya Munasinghe; Tim Bell; Anthony Robins – ACM Transactions on Computing Education, 2023
In learning to program and understanding how a programming language controls a computer, learners develop both insights and misconceptions whilst their mental models are gradually refined. It is important that the learner is able to distinguish the different elements and roles of a computer (compiler, interpreter, memory, etc.), which novice…
Descriptors: Computation, Thinking Skills, Programming, Programming Languages
Toukiloglou, Pavlos; Xinogalos, Stelios – Journal of Educational Computing Research, 2023
Serious games are a growing field in academic research and they are considered an effective tool for education. Game-based learning invokes motivation and engagement in students resulting in effective instructional outcomes. An essential aspect of a serious game is the method of support for presenting the teaching material and providing feedback.…
Descriptors: Educational Games, Programming, Sequential Learning, Cognitive Processes
Michelle Pauley Murphy; Woei Hung – TechTrends: Linking Research and Practice to Improve Learning, 2024
Constructing a consensus problem space from extensive qualitative data for an ill-structured real-life problem and expressing the result to a broader audience is challenging. To effectively communicate a complex problem space, visualization of that problem space must elucidate inter-causal relationships among the problem variables. In this…
Descriptors: Information Retrieval, Data Analysis, Pattern Recognition, Artificial Intelligence
Zhang, Yingbin; Pinto, Juan D.; Fan, Aysa Xuemo; Paquette, Luc – Journal of Educational Data Mining, 2023
The second CSEDM data challenge aimed at finding innovative methods to use students' programming traces to model their learning. The main challenge of this task is how to decide which past problems are relevant for predicting performance on a future problem. This paper proposes a set of weighting schemes to address this challenge. Specifically,…
Descriptors: Problem Solving, Introductory Courses, Computer Science Education, Programming
Guozhu Ding; Xiangyi Shi; Shan Li – Education and Information Technologies, 2024
In this study, we developed a classification system of programming errors based on the historical data of 680,540 programming records collected on the Online Judge platform. The classification system described six types of programming errors (i.e., syntax, logical, type, writing, misunderstanding, and runtime errors) and their connections with…
Descriptors: Programming, Computer Science Education, Classification, Graphs
Aslina Saad; Suhaila Zainudin – Interactive Learning Environments, 2024
This study delves into the integration of Project-Based Learning (PBL) and Computational Thinking (CT) to enhance 21st century learning. Through a Narrative Literature Review (NLR), pivotal strategies for effective implementation are identified. These include fostering collaborative pedagogy, employing visualization tools, embracing diverse…
Descriptors: Active Learning, Student Projects, Teaching Methods, Computation
Liu, Fang; Zhao, Liang; Zhao, Jiayi; Dai, Qin; Fan, Chunlong; Shen, Jun – IEEE Transactions on Learning Technologies, 2022
Educational process mining is now a promising method to provide decision-support information for the teaching-learning process via finding useful educational guidance from the event logs recorded in the learning management system. Existing studies mainly focus on mining students' problem-solving skills or behavior patterns and intervening in…
Descriptors: Data Use, Learning Management Systems, Problem Solving, Learning Processes
Flores, Rejeenald M.; Rodrigo, Ma. Mercedes T. – Journal of Educational Computing Research, 2020
Wheel-spinning refers to the failure to master a skill in a timely manner or after a considerable number of practice opportunities. Several past studies have developed wheel-spinning models in the areas of Mathematics and Physics. However, no models have been made for the context of novice programming. The purpose of this study was to develop…
Descriptors: Mastery Learning, Novices, Programming, Computer Science Education
Szlávi,Péter; Zsakó, László – Acta Didactica Napocensia, 2017
As a programmer when solving a problem, a number of conscious and unconscious cognitive operations are being performed. Problem-solving is a gradual and cyclic activity; as the mind is adjusting the problem to its schemas formed by its previous experiences, the programmer gets closer and closer to understanding and defining the problem. The…
Descriptors: Problem Solving, Programming, Mathematics, Programming Languages
Kuroki, Masanori – Journal of Economic Education, 2023
As vast amounts of data have become available in business in recent years, the demand for data scientists has been rising. The author of this article provides a tutorial on how one entry-level machine learning competition from Kaggle, an online community for data scientists, can be integrated into an undergraduate econometrics course as an…
Descriptors: Statistics Education, Teaching Methods, Competition, Prediction
Marwan, Samiha; Shi, Yang; Menezes, Ian; Chi, Min; Barnes, Tiffany; Price, Thomas W. – International Educational Data Mining Society, 2021
Feedback on how students progress through completing subgoals can improve students' learning and motivation in programming. Detecting subgoal completion is a challenging task, and most learning environments do so either with "expert-authored" models or with "data-driven" models. Both models have advantages that are…
Descriptors: Expertise, Models, Feedback (Response), Identification
Zebel-Al Tareq; Raja Jamilah Raja Yusof – IEEE Transactions on Education, 2024
Contribution: A problem-solving approach (PSA) model derived from major computational thinking (CT) concepts. This model can be utilized to formulate solutions for different algorithmic problems and translate them into effective active learning methods. Background: Different teaching approaches for programming are widely available; however, being…
Descriptors: Models, Problem Solving, Computation, Thinking Skills
Jiang, Bo; Wu, Simin; Yin, Chengjiu; Zhang, Haifeng – IEEE Transactions on Learning Technologies, 2020
Accurately tracing the state of learner knowledge contributes to providing high-quality intelligent support for computer-supported programming learning. However, knowledge tracing is difficult when learners have only had a few practice opportunities, which is often common in block-based programming. This article proposed two knowledge tracing…
Descriptors: Programming, Computer Assisted Instruction, Problem Solving, Task Analysis
Phillips, A. M.; Gouvea, E. J.; Gravel, B. E.; Beachemin, P. -H.; Atherton, T. J. – Physical Review Physics Education Research, 2023
Computation is intertwined with essentially all aspects of physics research and is invaluable for physicists' careers. Despite its disciplinary importance, integration of computation into physics education remains a challenge and, moreover, has tended to be constructed narrowly as a route to solving physics problems. Here, we broaden Physics…
Descriptors: Physics, Science Instruction, Teaching Methods, Models
Güney, Zafer – International Journal of Progressive Education, 2019
The need for methods, techniques and approaches that we can develop high-level thinking skills in important activities increases day by day in order to achieve effective use of technology and change in information and communication technologies. In particular, the diversity, complexity of technical skills and to gain technical skills required to…
Descriptors: Instructional Design, Models, Programming, Thinking Skills