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Showing 1 to 15 of 21 results Save | Export
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Tetsuo Tanaka; Ryo Horiuchi; Mari Ueda – International Association for Development of the Information Society, 2024
We evaluate the effectiveness of reading aloud a program code in learning programming from a neuroscientific perspective by measuring brain activity using a near-infrared spectroscopy device. The results show that when reading aloud and then reading silently, brain activity increases during reading aloud; a similar trend is observed when the…
Descriptors: Oral Reading, Programming, Coding, Neurosciences
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Gao, Zhikai; Erickson, Bradley; Xu, Yiqiao; Lynch, Collin; Heckman, Sarah; Barnes, Tiffany – International Educational Data Mining Society, 2022
In computer science education timely help seeking during large programming projects is essential for student success. Help-seeking in typical courses happens in office hours and through online forums. In this research, we analyze students coding activities and help requests to understand the interaction between these activities. We collected…
Descriptors: Computer Science Education, College Students, Programming, Coding
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Jahnke, Maximilian; Höppner, Frank – International Educational Data Mining Society, 2022
The value of an instructor is that she exactly recognizes what the learner is struggling with and provides constructive feedback straight to the point. This work aims at a step towards this type of feedback in the context of an introductory programming course, where students perform program execution tracing to align their understanding of Java…
Descriptors: Programming, Coding, Computer Science Education, Error Patterns
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Höppner, Frank – International Educational Data Mining Society, 2021
Various similarity measures for source code have been proposed, many rely on edit- or tree-distance. To support a lecturer in quickly assessing live or online exercises with respect to "approaches taken by the students," we compare source code on a more abstract, semantic level. Even if novice student's solutions follow the same idea,…
Descriptors: Coding, Classification, Programming, Computer Science Education
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Abigail Erskine; Laura Bofferding; Sezai Kocabos; Haoran Tang – North American Chapter of the International Group for the Psychology of Mathematics Education, 2023
As elementary students begin to program using tangible blocks, they must coordinate their use of counting with the movements, directions, and numbers they use to move a character. In our study, we analyzed 13 first graders' first attempts at coordinating these elements when playing a programming game on the iPad that used tangible programming…
Descriptors: Elementary School Students, Elementary School Mathematics, Grade 1, Computation
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Andrea Domínguez-Lara; Wulfrano Arturo Luna-Ramírez – International Association for Development of the Information Society, 2022
The automatic code generation is the process of generating source code snippets from a program, i.e., code for generating code. Its importance lies in facilitating software development, particularly important is helping in the implementation of software designs such as engineering diagrams, in such a case, automatic code generation copes with the…
Descriptors: Programming, Coding, Computer Software, Programming Languages
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Tsabari, Stav; Segal, Avi; Gal, Kobi – International Educational Data Mining Society, 2023
Automatically identifying struggling students learning to program can assist teachers in providing timely and focused help. This work presents a new deep-learning language model for predicting "bug-fix-time", the expected duration between when a software bug occurs and the time it will be fixed by the student. Such information can guide…
Descriptors: College Students, Computer Science Education, Programming, Error Patterns
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Krish Pillai; Marcia Lovas – International Society for Technology, Education, and Science, 2023
A typical first computer science course (CS1) introduces the student to coding conventions, variables, methods, control structures, conditionals, and the semantics of classes and objects. Advanced concepts of inheritance, polymorphism, abstract classes, interfaces, and their use in the design process, are covered in a second-level course (CS2).…
Descriptors: Computer Games, Educational Games, Teaching Methods, Technology Uses in Education
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Shi, Yang; Schmucker, Robin; Chi, Min; Barnes, Tiffany; Price, Thomas – International Educational Data Mining Society, 2023
Knowledge components (KCs) have many applications. In computing education, knowing the demonstration of specific KCs has been challenging. This paper introduces an entirely data-driven approach for: (1) discovering KCs; and (2) demonstrating KCs, using students' actual code submissions. Our system is based on two expected properties of KCs: (1)…
Descriptors: Computer Science Education, Data Analysis, Programming, Coding
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Ruiz-Arias, Perla Marysol; Sacristán, Ana Isabel – North American Chapter of the International Group for the Psychology of Mathematics Education, 2020
This paper presents a case study that is part of a research studying how university statistics teachers integrate digital tools in their practice. The case study is of a teacher who claims to follow constructionist ideas for her teaching of statistics, using the R programming language. The teacher developed a series of activities with R, aiming to…
Descriptors: College Faculty, Statistics Education, College Mathematics, Data Analysis
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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
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Ma, Yingbo; Katuka, Gloria Ashiya; Celepkolu, Mehmet; Boyer, Kristy Elizabeth – International Educational Data Mining Society, 2022
Collaborative learning is a complex process during which two or more learners exchange opinions, construct shared knowledge, and solve problems together. While engaging in this interactive process, learners' satisfaction toward their partners plays a crucial role in defining the success of the collaboration. If intelligent systems could predict…
Descriptors: Middle School Students, Cooperative Learning, Prediction, Peer Relationship
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Paaßen, Benjamin; Jensen, Joris; Hammer, Barbara – International Educational Data Mining Society, 2016
The first intelligent tutoring systems for computer programming have been proposed more than 30 years ago, mostly focusing on well defined programming tasks e.g. in the context of logic programming. Recent systems also teach complex programs, where explicit modelling of every possible program and mistake is no longer possible. Such systems are…
Descriptors: Intelligent Tutoring Systems, Programming, Computer Science Education, Data
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Emerson, Andrew; Rodríguez, Fernando J.; Mott, Bradford; Smith, Andy; Min, Wookhee; Boyer, Kristy Elizabeth; Smith, Cody; Wiebe, Eric; Lester, James – International Educational Data Mining Society, 2019
Recent years have seen a growing interest in block-based programming environments for computer science education. While these environments hold significant potential for novice programmers, they lack the adaptive support necessary to accommodate students exhibiting a wide range of initial capabilities and dispositions toward computing. A promising…
Descriptors: Programming, Computer Science Education, Feedback (Response), Prediction
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Rossano, Veronica; Roselli, Teresa; Quercia, Gaetano – International Association for Development of the Information Society, 2018
The Computational Thinking recently has been recognised as one of the basic knowledge to be developed since childhood. Coding and computers are not just programming, but tools that help students to develop problem solving skills and more deep understand of the way things work. For these reasons, great attention has been focused on this topic both…
Descriptors: Coding, Computation, Problem Solving, Computer Software
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