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Showing 1 to 15 of 37 results Save | Export
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Xiaoheng Yan; Gila Hanna – International Journal of Mathematical Education in Science and Technology, 2025
As new technological developments continue to change the educational landscape, it is not an exception in the area of proof and proving. This classroom note introduces the use of one of the trending proofs assistants -- the Lean theorem prover. We first provide a technical account of Lean, then exemplify Lean proofs in propositional logic, number…
Descriptors: Mathematics Instruction, Undergraduate Students, Mathematical Logic, Validity
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Yang Shi; Robin Schmucker; Keith Tran; John Bacher; Kenneth Koedinger; Thomas Price; Min Chi; Tiffany Barnes – Journal of Educational Data Mining, 2024
Understanding students' learning of knowledge components (KCs) is an important educational data mining task and enables many educational applications. However, in the domain of computing education, where program exercises require students to practice many KCs simultaneously, it is a challenge to attribute their errors to specific KCs and,…
Descriptors: Programming Languages, Undergraduate Students, Learning Processes, Teaching Models
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Paola Iannone; Athina Thoma – International Journal of Mathematical Education in Science and Technology, 2024
Programming is becoming increasingly common in mathematics degrees as it is a desirable skill for new graduates. However, research shows that its use is mostly restricted to computational or modelling tasks. This paper reports a study on students' perceptions of and difficulties with Lean, an interactive theorem prover introduced as part of a…
Descriptors: Programming, Mathematics Instruction, Computer Science Education, Student Attitudes
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Felienne Hermans – Informatics in Education, 2024
This autoethnographic paper is part of a special issue trying to answer the question "How to design or choose languages for programming novices?" I will describe how my programming language Hedy was created, how the initial design goals were formed, how my perspectives on learning and teaching changed along the way, and how Hedy changed…
Descriptors: Decision Making, Programming Languages, Novices, Computer Science Education
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Arjan J. F. Kok; Lex Bijlsma; Cornelis Huizing; Ruurd Kuiper; Harrie Passier – Informatics in Education, 2024
This paper presents the first experiences of the use of an online open-source repository with programming exercises. The repository is independent of any specific teaching approach. Students can search for and select an exercise that trains the programming concepts that they want to train and that only uses the programming concepts they already…
Descriptors: Programming Languages, Computer Science Education, Open Source Technology, Teaching Methods
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Lokkila, Erno; Christopoulos, Athanasios; Laakso, Mikko-Jussi – Informatics in Education, 2023
Prior programming knowledge of students has a major impact on introductory programming courses. Those with prior experience often seem to breeze through the course. Those without prior experience see others breeze through the course and disengage from the material or drop out. The purpose of this study is to demonstrate that novice student…
Descriptors: Prior Learning, Programming, Computer Science Education, Markov Processes
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Yun Huang; Christian Dieter Schunn; Julio Guerra; Peter L. Brusilovsky – ACM Transactions on Computing Education, 2024
Programming skills are increasingly important to the current digital economy, yet these skills have long been regarded as challenging to acquire. A central challenge in learning programming skills involves the simultaneous use of multiple component skills. This article investigates why students struggle with integrating component skills--a…
Descriptors: Programming, Computer Science Education, Error Patterns, Classification
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Justin Gambrell; Eric Brewe – Physical Review Physics Education Research, 2024
Computational thinking in physics has many different forms, definitions, and implementations depending on the level of physics or the institution it is presented in. To better integrate computational thinking in introductory physics, we need to understand what physicists find important about computational thinking in introductory physics. We…
Descriptors: Physics, Introductory Courses, Science Instruction, Thinking Skills
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Johnson, Marina E.; Misra, Ram; Berenson, Mark – Decision Sciences Journal of Innovative Education, 2022
In the era of artificial intelligence (AI), big data (BD), and digital transformation (DT), analytics students should gain the ability to solve business problems by integrating various methods. This teaching brief illustrates how two such methods--Bayesian analysis and Markov chains--can be combined to enhance student learning using the Analytics…
Descriptors: Bayesian Statistics, Programming Languages, Artificial Intelligence, Data Analysis
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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
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Buteau, Chantal; Gueudet, Ghislaine; Muller, Eric; Mgombelo, Joyce; Sacristán, Ana Isabel – International Journal of Mathematical Education in Science and Technology, 2020
The instrumental approach is a useful theoretical lens for understanding students' learning processes with a main focus on the transformation of an artefact (a human design for a goal-directed activity) into a meaningful instrument (i.e. an artefact and schemes developed by the student). In this paper, we articulate the instrumental approach for…
Descriptors: Undergraduate Students, College Mathematics, Programming Languages, Active Learning
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Mashood, K. K.; Khosla, Kamakshi; Prasad, Arjun; V., Sasidevan; Ashefas CH, Muhammed; Jose, Charles; Chandrasekharan, Sanjay – Physical Review Physics Education Research, 2022
Recent educational policies advocate a radical revision of science curricula and pedagogy, to support interdisciplinary practices, a distinguishing feature of contemporary science. Computational modeling (CM) is a core methodology of interdisciplinary science, as such models allow intertwining of data and theoretical perspectives from multiple…
Descriptors: Teaching Methods, Undergraduate Students, Science Instruction, Science Curriculum
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Sbaraglia, Marco; Lodi, Michael; Martini, Simone – Informatics in Education, 2021
Introductory programming courses (CS1) are difficult for novices. Inspired by "Problem solving followed by instruction" and "Productive Failure" approaches, we define an original "necessity-driven" learning design. Students are put in an apparently well-known situation, but this time they miss an essential ingredient…
Descriptors: Programming, Introductory Courses, Computer Science Education, Programming Languages
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Scheller, Daniel S. – Journal of Public Affairs Education, 2022
The general growth in public affairs programs offering hybrid and online courses to reach a wide variety of students, along with the necessity of doing so during a global health pandemic, calls for an investigation of best practices in teaching public affairs statistics and research-oriented courses. These courses often require the use of a…
Descriptors: Case Studies, Programming Languages, Statistics Education, Teaching Methods
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Wang, Hai; Wang, Shouhong – Journal of Information Systems Education, 2022
No-code/low-code app development is transforming traditional information system development paradigms. This teaching tip uses an example of course unit of decision support systems (DSS) to demonstrate that introducing no-code system implementation assignments into a course as a replacement for computer programming language exercises can improve…
Descriptors: Information Systems, Information Science Education, Programming Languages, Teaching Methods
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