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Showing 1 to 15 of 16 results Save | Export
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Barbosa Rocha, Hemilis Joyse; Cabral De Azevedo Restelli Tedesco, Patrícia; De Barros Costa, Evandro – Informatics in Education, 2023
In programming problem solving activities, sometimes, students need feedback to progress in the course, being positively affected by the received feedback. This paper presents an overview of the state of the art and practice of the feedback approaches on introductory programming. To this end, we have carried out a systematic literature mapping to…
Descriptors: Classification, Computer Science Education, Feedback (Response), Problem Solving
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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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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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Fonseca, Samuel C.; Pereira, Filipe Dwan; Oliveira, Elaine H. T.; Oliveira, David B. F.; Carvalho, Leandro S. G.; Cristea, Alexandra I. – International Educational Data Mining Society, 2020
As programming must be learned by doing, introductory programming course learners need to solve many problems, e.g., on systems such as 'Online Judges'. However, as such courses are often compulsory for non-Computer Science (nonCS) undergraduates, this may cause difficulties to learners that do not have the typical intrinsic motivation for…
Descriptors: Programming, Introductory Courses, Computer Science Education, Automation
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Broisin, Julien; Hérouard, Clément – International Educational Data Mining Society, 2019
How to support students in programming learning has been a great research challenge in the last years. To address this challenge, prior works have mainly focused on proposing solutions based on syntactic analysis to provide students with personalized feedback about their grammatical programming errors and misconceptions. However, syntactic…
Descriptors: Semantics, Programming, Syntax, Feedback (Response)
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Karnalim, Oscar – Themes in Science and Technology Education, 2017
This paper empirically enlists Python plagiarism attacks that have been found on Introductory Programming course assignments for undergraduate students. According to our observation toward 400 plagiarism-suspected cases, there are 35 plagiarism attacks that have been conducted by students. It starts with comment & whitespace modification as…
Descriptors: Plagiarism, Introductory Courses, Programming Languages, Taxonomy
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Kanika; Chakraverty, Shampa; Chakraborty, Pinaki – Journal of Educational Technology Systems, 2020
Courses on computer programming are included in the curricula of almost all engineering disciplines. We surveyed the research literature and identified the techniques that are commonly used by instructors for teaching these courses. We observed that visual programming and game-based learning can enhance computational thinking and problem-solving…
Descriptors: Teaching Methods, Programming, Computer Science Education, Robotics
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Taniguchi, Tadanari; Maruyama, Yukiko; Kurita, Daisaku; Tanaka, Makoto – International Association for Development of the Information Society, 2018
We propose developing a method to set key educational skills which students need to achieve for each class using a student self-assessment questionnaire in analytical approach. It is difficult to set key academic skills for class since there are little systematic methods to set them. The questionnaire survey with 25 educational skills was…
Descriptors: Student Attitudes, Computer Science Education, Self Evaluation (Individuals), Information Technology
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Maaliw, Renato R. III; Ballera, Melvin A. – International Association for Development of the Information Society, 2017
The usage of data mining has dramatically increased over the past few years and the education sector is leveraging this field in order to analyze and gain intuitive knowledge in terms of the vast accumulated data within its confines. The primary objective of this study is to compare the results of different classification techniques such as Naïve…
Descriptors: Classification, Cognitive Style, Electronic Learning, Decision Making
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Taherkhani, Ahmad; Malmi, Lauri – Journal of Educational Data Mining, 2013
In this paper, we present a method for recognizing algorithms from students programming submissions coded in Java. The method is based on the concept of "programming schemas" and "beacons". Schemas are high-level programming knowledge with detailed knowledge abstracted out, and beacons are statements that imply specific…
Descriptors: Programming, Mathematics, Computer Science Education, Methods
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Larraza-Mendiluze, Edurne; Garay-Vitoria, Nestor – IEEE Transactions on Education, 2015
This paper surveys how the computer input/output (I/O) subsystem is taught in introductory undergraduate courses. It is important to study the educational process of the computer I/O subsystem because, in the curricula recommendations, it is considered a core topic in the area of knowledge of computer architecture and organization (CAO). It is…
Descriptors: Computer Science Education, Engineering Education, Introductory Courses, Undergraduate Study
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Lang, Guido; O'Connell, Stephen D. – Information Systems Education Journal, 2015
We investigate the relationship between learning styles, online content usage and exam performance in an undergraduate introductory Computer Information Systems class comprised of both online video tutorials and in-person classes. Our findings suggest that, across students, (1) traditional learning style classification methodologies do not predict…
Descriptors: Introductory Courses, Correlation, Cognitive Style, Undergraduate Students
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Ezen-Can, Aysu; Boyer, Kristy Elizabeth – Journal of Educational Data Mining, 2015
Within the landscape of educational data, textual natural language is an increasingly vast source of learning-centered interactions. In natural language dialogue, student contributions hold important information about knowledge and goals. Automatically modeling the dialogue act of these student utterances is crucial for scaling natural language…
Descriptors: Classification, Dialogs (Language), Computational Linguistics, Information Retrieval
Heiner, Cecily; Zachary, Joseph L. – International Working Group on Educational Data Mining, 2009
Students in introductory programming classes often articulate their questions and information needs incompletely. Consequently, the automatic classification of student questions to provide automated tutorial responses is a challenging problem. This paper analyzes 411 questions from an introductory Java programming course by reducing the natural…
Descriptors: Classification, Questioning Techniques, Introductory Courses, Computer Science Education
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Gaspar, Alessio; Langevin, Sarah; Boyer, Naomi; Armitage, William – Informatics in Education, 2010
This qualitative study explores how using Peer Learning Forums (PLF) in an online asynchronous computer programming course can be analyzed to derive information about Student Activity Focus (SAF) for adult Information Technology students. Three instruments are proposed to assist instructors classify questions posted by students on these forums,…
Descriptors: Asynchronous Communication, Qualitative Research, Learning Activities, Classification
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