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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
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
Guozhu Ding; Xiangyi Shi; Shan Li – Education and Information Technologies, 2024
In this study, we developed a classification system of programming errors based on the historical data of 680,540 programming records collected on the Online Judge platform. The classification system described six types of programming errors (i.e., syntax, logical, type, writing, misunderstanding, and runtime errors) and their connections with…
Descriptors: Programming, Computer Science Education, Classification, Graphs
Charalampos-S Charitsis – ProQuest LLC, 2023
The employment rate of software developers has risen significantly over the last 30 years. As a result, more students are considering computer science as a potential career path. Over the last 15 years, introductory programming course (CS1) enrollment has been increasing at a much faster rate than the increase in the number of CS faculty, with no…
Descriptors: Computer Science Education, Programming, Natural Language Processing, Computer Software
Ragonis, Noa; Shmallo, Ronit – Informatics in Education, 2022
Object-oriented programming distinguishes between instance attributes and methods and class attributes and methods, annotated by the "static" modifier. Novices encounter difficulty understanding the means and implications of "static" attributes and methods. The paper has two outcomes: (a) a detailed classification of aspects of…
Descriptors: Programming, Computer Science Education, Concept Formation, Thinking Skills
Wanxue Zhang; Lingling Meng; Bilan Liang – Interactive Learning Environments, 2023
With the continuous development of education, personalized learning has attracted great attention. How to evaluate students' learning effects has become increasingly important. In information technology courses, the traditional academic evaluation focuses on the student's learning outcomes, such as "scores" or "right/wrong,"…
Descriptors: Information Technology, Computer Science Education, High School Students, Scoring
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)
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
Saito, Tomohiro; Watanobe, Yutaka – International Journal of Distance Education Technologies, 2020
Programming education has recently received increased attention due to growing demand for programming and information technology skills. However, a lack of teaching materials and human resources presents a major challenge to meeting this demand. One way to compensate for a shortage of trained teachers is to use machine learning techniques to…
Descriptors: Programming, Computer Science Education, Electronic Learning, Instructional Materials
Srba, Ivan; Bielikova, Maria – IEEE Transactions on Learning Technologies, 2015
In the current time of globalization, collaboration among people in virtual environments is becoming an important precondition of success. This trend is reflected also in the educational domain where students collaborate in various short-term groups created repetitively but changing in each round (e.g. in MOOCs). Students in these kind of dynamic…
Descriptors: Cooperative Learning, Online Courses, Group Dynamics, Feedback (Response)
Rashkovits, Rami; Lavy, Ilana – Journal of Information Technology Education, 2011
This study discusses and presents various strategies employed by novice programmers concerning exception handling. The main contributions of this paper are as follows: we provide an analysis tool to measure the level of assimilation of exception handling mechanism; we present and analyse strategies to handle exceptions; we present and analyse…
Descriptors: Foreign Countries, Programming Languages, Computer Software, Computer Software Evaluation
Zendler, A.; Spannagel, C.; Klaudt, D. – Computer Science Education, 2008
Computer science education should not be based on short-term developments but on content that is observable in multiple domains of computer science, may be taught at every intellectual level, will be relevant in the longer term, and is related to everyday language and/or thinking. Recently, a catalogue of "central concepts" for computer…
Descriptors: Computer Science Education, Multivariate Analysis, Computer Science, Problem Solving

Kolata, Gina – Science, 1985
To determine how hard it is for computers to solve problems, researchers have classified groups of problems (polynomial hierarchy) according to how much time they seem to require for their solutions. A difficult and complex proof is offered which shows that a combinatorial approach (using Boolean circuits) may resolve the problem. (JN)
Descriptors: Classification, Computer Science, Difficulty Level, Mathematical Logic
Clancey, William J. – 1984
In an attempt to specify in some canonical terms what many heuristic programs known as "expert systems" do, an analysis was made of ten rule-based systems. It was found that these programs proceed through easily identifiable phases of data abstraction, heuristic mapping onto a hierarchy of pre-enumerated solutions, and refinement within this…
Descriptors: Classification, Computer Science, Computer Software, Heuristics
Allenbrand, Bob, Ed.; And Others – 1979
Designed to be used in conjunction with a school district's educational goals and focusing on what is to be learned rather than the methodology to be used, the program and course goals presented here are intended as guidelines for planning and evaluating elementary and secondary school curricula in computer education. Of four possible levels of…
Descriptors: Calculators, Career Education, Classification, Computer Programs
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