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Showing 1 to 15 of 99 results Save | Export
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Leah Bidlake; Eric Aubanel; Daniel Voyer – ACM Transactions on Computing Education, 2025
Research on mental model representations developed by programmers during parallel program comprehension is important for informing and advancing teaching methods including model-based learning and visualizations. The goals of the research presented here were to determine: how the mental models of programmers change and develop as they learn…
Descriptors: Schemata (Cognition), Programming, Computer Science Education, Coding
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Erkki Kaila; Kjell Lemström – Informatics in Education, 2023
Massive Open Online Courses (MOOCs) have become hugely popular recently. MOOCs can offer high-quality education for anyone interested and equalize the whole education field. Still, there are different methodologies for running MOOCs. Coming up with the most suitable methodology benefits both students and teachers. In this study, we have limited…
Descriptors: MOOCs, Scheduling, Programming Languages, Programming
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Michael E. Ellis; K. Mike Casey; Geoffrey Hill – Decision Sciences Journal of Innovative Education, 2024
Large Language Model (LLM) artificial intelligence tools present a unique challenge for educators who teach programming languages. While LLMs like ChatGPT have been well documented for their ability to complete exams and create prose, there is a noticeable lack of research into their ability to solve problems using high-level programming…
Descriptors: Artificial Intelligence, Programming Languages, Programming, Homework
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Melina Verger; Chunyang Fan; Sébastien Lallé; François Bouchet; Vanda Luengo – Journal of Educational Data Mining, 2024
Predictive student models are increasingly used in learning environments due to their ability to enhance educational outcomes and support stakeholders in making informed decisions. However, predictive models can be biased and produce unfair outcomes, leading to potential discrimination against certain individuals and harmful long-term…
Descriptors: Algorithms, Prediction, Bias, Classification
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Sayginer, Senol; Tüzün, Hakan – Journal of Computer Assisted Learning, 2023
Background: Studies on the effectiveness of block-based environments continue to produce inconsistent results. A strong reason for this is that most studies compare environments that are not equivalent to each other or to the level of learners. Moreover, studies that present evidence of the effectiveness of block-based environments by comparing…
Descriptors: Programming, Academic Achievement, Logical Thinking, Thinking Skills
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Miedema, Daphne; Fletcher, George; Aivaloglou, Efthimia – ACM Transactions on Computing Education, 2023
Prior studies in the Computer Science education literature have illustrated that novices make many mistakes in composing SQL queries. Query formulation proves to be difficult for students. Only recently, some headway was made towards understanding why SQL leads to so many mistakes, by uncovering student misconceptions. In this article, we shed new…
Descriptors: Computer Science Education, Novices, Misconceptions, Programming Languages
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James A. Parejko – Journal of Microbiology & Biology Education, 2024
The current and ongoing challenges brought on by climate change will require future scientists who have hands-on experience using advanced molecular techniques, can work with large data sets, and can make correlations between metadata and microbial diversity. A course-embedded research project can prepare students to answer complex research…
Descriptors: Plants (Botany), Microbiology, Science Instruction, Teaching Methods
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Sa Li; Jingjing Dong – International Journal of Web-Based Learning and Teaching Technologies, 2024
In order to deeply analyze and evaluate the changes in the comprehensive quality of college students' sports dance, the overall idea of systematically evaluating the changes in the comprehensive quality of college students' sports dance was established. Firstly, this article uses the triangular fuzzy number method to measure the evaluation…
Descriptors: Dance Education, Teaching Methods, Evaluation Methods, Programming Languages
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Taspolat, Ata; Özdamli, Fezile; Soykan, Emrah – SAGE Open, 2021
The flipped classroom method, which could be considered as one of the crucial new generation teaching approaches, is a permutation of the educational activities that are carried out inside and outside of the classroom environment. The main purpose of the present study is to determine the impact of the flipped classroom approach on students'…
Descriptors: Programming Languages, Computer Science Education, Flipped Classroom, Instructional Effectiveness
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Vance, Eric A. – Journal of Statistics and Data Science Education, 2021
Data science is collaborative and its students should learn teamwork and collaboration. Yet it can be a challenge to fit the teaching of such skills into the data science curriculum. Team-Based Learning (TBL) is a pedagogical strategy that can help educators teach data science better by flipping the classroom to employ small-group collaborative…
Descriptors: Cooperative Learning, Data Analysis, Statistics Education, Flipped Classroom
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Lasser, Jana; Manik, Debsankha; Silbersdorff, Alexander; Säfken, Benjamin; Kneib, Thomas – Teaching Statistics: An International Journal for Teachers, 2021
Data and its applications are increasingly ubiquitous in the rapidly digitizing world and consequently, students across different disciplines face increasing demand to develop skills to answer both academia's and businesses' increasing need to collect, manage, evaluate, apply and extract knowledge from data and critically reflect upon the derived…
Descriptors: Introductory Courses, Data, Interdisciplinary Approach, Programming Languages
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Sunday, Kissinger; Wong, Seng Yue; Samson, Balogun Oluwafemi; Sanusi, Ismaila Temitayo – Education and Information Technologies, 2022
Learning object oriented programming (OOP) has been a daunting and challenging task for students across tertiary institutions in Nigeria. Various literatures have suggested the use of technology as a way to improve students' understanding of the subject. In this study, the overall aim is to investigate the effect of Imikode- a virtual reality (VR)…
Descriptors: Foreign Countries, College Students, Computer Simulation, Programming
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Strömbäck, Filip; Mannila, Linda; Kamkar, Mariam – Informatics in Education, 2021
Concurrency is often perceived as difficult by students. One reason for this may be due to the fact that abstractions used in concurrent programs leave more situations undefined compared to sequential programs (e.g., in what order statements are executed), which makes it harder to create a proper mental model of the execution environment. Students…
Descriptors: College Students, Programming, Programming Languages, Concept Formation
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Asmaa Bengueddach; Djamila Hamdadou – International Society for Technology, Education, and Science, 2024
The COVID-19 pandemic, an unprecedented global health crisis, has not only significantly impacted public health but has also caused substantial disruptions to conventional education systems. In response to these challenges, our institution has undertaken innovative measures within the realm of education. A pivotal aspect of our response involves…
Descriptors: Personal Autonomy, Online Courses, Educational Change, Coding
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Cuervo-Cely, Karen D.; Restrepo-Calle, Felipe; Ramírez-Echeverry, Jhon J. – Journal of Information Technology Education: Research, 2022
Aim/Purpose: The purpose of this research is to examine the effect of computer-assisted gamification on the learning motivation of computer programming students. Background: The teaching-learning of computer programming involves challenges that imply using learning environments in which the student is actively involved. Gamification is an…
Descriptors: Game Based Learning, Student Motivation, Computer Science Education, Programming
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