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Showing 1 to 15 of 38 results Save | Export
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Brown, Neil C. C.; Weill-Tessier, Pierre; Sekula, Maksymilian; Costache, Alexandra-Lucia; Kölling, Michael – ACM Transactions on Computing Education, 2023
Objectives: Java is a popular programming language for use in computing education, but it is difficult to get a wide picture of the issues that it presents for novices; most studies look only at the types or frequency of errors. In this observational study, we aim to learn how novices use different features of the Java language. Participants:…
Descriptors: Novices, Programming, Programming Languages, Data
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Feijoo-Garcia, Pedro G.; Kapoor, Amanpreet; Gardner-McCune, Christina; Ragan, Eric – IEEE Transactions on Education, 2022
Contribution: In this article, the authors present findings and insights on the efficacy of using an educational block-based programming (BBP) environment--Blocks4DS, to teach the binary search tree (BST). Background: For a decade, BBP environments have been a hot topic in the computer science education (CSEd) community to promote interactive…
Descriptors: Computer Science Education, Programming, Programming Languages, Mathematics
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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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Omer, Uzma; Tehseen, Rabia; Farooq, Muhammad Shoaib; Abid, Adnan – Education and Information Technologies, 2023
Learning analytics (LA) is a significant field of study to examine and identify difficulties the novice programmers face while learning how to program. Despite producing notable research by the community in the specified area, rare work is observed to synthesize these research efforts and discover the dimensions that guide the future research of…
Descriptors: Programming, Learning Analytics, Educational Research, Data
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Bende, Imre – Acta Didactica Napocensia, 2022
Understanding data structures is fundamental for mastering algorithms. In order to solve problems and tasks, students must be able to choose the most appropriate data structure in which the data is stored and that helps in the process of the solution. Of course, there is no single correct solution, but in many cases, it is an important step to…
Descriptors: Programming, Computer Science Education, Data, Visual Aids
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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
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Fergusson, Anna; Wild, Chris J. – Teaching Statistics: An International Journal for Teachers, 2021
The explosion in availability and variety of data requires learning experiences that reveal more of the data world faster and develop practical skills with digital technologies. Key high-level goals of the International Data Science in Schools Project (IDSSP) include having students continually immersed in the cycle of learning from data, and data…
Descriptors: Data, Data Analysis, Skill Development, Discovery Learning
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Demetrios G. Sampson, Editor; Dirk Ifenthaler, Editor; Pedro Isaías, Editor – Cognition and Exploratory Learning in the Digital Age, 2024
This edited volume presents the latest research focussing on current challenges on the deployment of smart technologies and pedagogies for supporting teaching and learning in the post-covid19 era. This is at the core of studying the evolution of the learning process, the role of technology-supported pedagogical approaches, and the progress of…
Descriptors: Teaching Methods, Influence of Technology, Educational Technology, Professional Development
Qian, Yizhou – ProQuest LLC, 2018
With the expansion of computer science (CS) education, CS teachers in K-12 schools should be cognizant of student misconceptions and be prepared to help students establish accurate understanding of computer science and programming. This exploratory design-based research (DBR) study implemented a data-driven approach to identify secondary school…
Descriptors: Misconceptions, Data, Decision Making, Computer Science Education
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Rivers, Kelly; Koedinger, Kenneth R. – International Journal of Artificial Intelligence in Education, 2017
To provide personalized help to students who are working on code-writing problems, we introduce a data-driven tutoring system, ITAP (Intelligent Teaching Assistant for Programming). ITAP uses state abstraction, path construction, and state reification to automatically generate personalized hints for students, even when given states that have not…
Descriptors: Programming, Coding, Computers, Data
Hicks, Andrew Gregory – ProQuest LLC, 2017
Games-Based Learning systems, particularly those that use advances from Intelligent Tutoring Systems (ITS) to provide adaptive feedback and support, have proven potential as learning tools. Taking their lead from commercial games such as Little Big Planet and SuperMarioMaker, these systems are increasingly turning to content creation as a learning…
Descriptors: Data, Decision Making, Intelligent Tutoring Systems, Educational Games
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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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Price, Thomas W.; Dong, Yihuan; Barnes, Tiffany – International Educational Data Mining Society, 2016
Intelligent Tutoring Systems (ITSs) have shown success in the domain of programming, in part by providing customized hints and feedback to students. However, many popular novice programming environments still lack these intelligent features. This is due in part to their use of open-ended programming assignments, which are difficult to support with…
Descriptors: Intelligent Tutoring Systems, Programming, Data, Computer Science Education
Liu, Zhongxiu – International Educational Data Mining Society, 2015
Data-driven methods have been a successful approach to generating hints for programming problems. However, the majority of previous studies are focused on procedural hints that aim at moving students to the next closest state to the solution. In this paper, I propose a data-driven method to generate remedy hints for BOTS, a game that teaches…
Descriptors: Programming, Educational Games, Puzzles, Problem Solving
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Werner, Linda; McDowell, Charlie; Denner, Jill – Journal of Educational Data Mining, 2013
Educational data mining can miss or misidentify key findings about student learning without a transparent process of analyzing the data. This paper describes the first steps in the process of using low-level logging data to understand how middle school students used Alice, an initial programming environment. We describe the steps that were…
Descriptors: Electronic Learning, Learning Processes, Educational Research, Data Collection
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