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Showing 1 to 15 of 94 results Save | Export
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Henrique Mohallem Paiva; Flávia Maria Santoro; Victor Takashi Hayashi; Bianca Cassemiro Lima – IEEE Transactions on Education, 2025
Contribution: This article analyzes student assessment within a computing faculty employing a full project-based learning (PBL) approach. Examining 2078 final grades across 60 classes and periods, the study reveals a significant correlation between graded self-studies, exams, and projects. This result contributes to understanding the reliability…
Descriptors: Student Evaluation, Computer Science Education, College Faculty, Correlation
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Noelle Brown; Benjamin Xie; Ella Sarder; Casey Fiesler; Eliane S. Wiese – ACM Transactions on Computing Education, 2024
The computing education research community now has at least 40 years of published research on teaching ethics in higher education. To examine the state of our field, we present a systematic literature review of papers in the "Association for Computing Machinery" computing education venues that describe teaching ethics in higher-education…
Descriptors: Ethics, Computer Science Education, Higher Education, Teaching Methods
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Marjahan Begum; Pontus Haglund; Ari Korhonen; Violetta Lonati; Mattia Monga; Filip Strömbäck; Artturi Tilanterä – Informatics in Education, 2024
There can be many reasons why students fail to answer correctly to summative tests in advanced computer science courses: often the cause is a lack of prerequisites or misconceptions about topics presented in previous courses. One of the ITiCSE 2020 working groups investigated the possibility of designing assessments suitable for differentiating…
Descriptors: Foreign Countries, College Students, Prerequisites, Computer Science Education
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Divasón, Jose; Martinez-de-Pison, Francisco Javier; Romero, Ana; Saenz-de-Cabezon, Eduardo – IEEE Transactions on Learning Technologies, 2023
The evaluation of student projects is a difficult task, especially when they involve both a technical and a creative component. We propose an artificial intelligence (AI)-based methodology to help in the evaluation of complex projects in engineering and computer science courses. This methodology is intended to evaluate the assessment process…
Descriptors: Student Projects, Student Evaluation, Artificial Intelligence, Models
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Sam Maesschalck – Journal of Information Technology Education: Innovations in Practice, 2024
Aim/Purpose: This paper explores the potential value of critical thinking in computer science education and discusses strategies for its integration across the curriculum. Background: As technology rapidly evolves and becomes increasingly integrated into society, there is a growing need for computer science graduates who can think critically about…
Descriptors: Computer Science Education, Critical Thinking, Integrated Curriculum, Curriculum Development
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Grethe Sandstrak; Bjorn Klefstad; Arne Styve; Kiran Raja – IEEE Transactions on Education, 2024
Teaching programming efficiently to students in the first year of computer science education is challenging. It is especially cumbersome to retain the interest of both groups, when the student group consists of novice (i.e., those who have never programmed before) and expert programmers in the same crowd. Thus, individualized teaching cannot be…
Descriptors: Computer Science Education, Programming, Teaching Methods, College Freshmen
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Sarika Tomar; Arundhathi Arundhathi; Shikha Gupta; Mansi Sharma – Journal of Education and Learning (EduLearn), 2024
As universities shifted to online education with the onset of the Coronavirus Disease 2019 (COVID-19) pandemic, both pedagogy and assessment patterns across disciplines underwent a change, with a shift towards collaborative digital assessments. In this context, using qualitative and quantitative methods for data collection from an assessment…
Descriptors: Student Evaluation, Cooperative Learning, Video Technology, Web Sites
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Paschoal, Leo Natan; Melo, Silvana Morita; Neves, Vânia de Oliveira; Conte, Tayana Uchôa; Souza, Simone do Rocio Senger de – Informatics in Education, 2023
Nowadays, few professionals understand the techniques and testing criteria to systematize the software testing activity in the software industry. Towards shedding some light on such problems and promoting software testing, professors in the area have established Massive Open Online Courses as educational initiatives. However, the main limitation…
Descriptors: Computer Science Education, Computer Software, College Faculty, MOOCs
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Asmaa Bengueddach; Djamila Hamdadou – International Society for Technology, Education, and Science, 2024
The COVID-19 pandemic, an unprecedented global health crisis, has not only significantly impacted public health but has also caused substantial disruptions to conventional education systems. In response to these challenges, our institution has undertaken innovative measures within the realm of education. A pivotal aspect of our response involves…
Descriptors: Personal Autonomy, Online Courses, Educational Change, Coding
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Pejic, Marko; Savic, Goran; Segedinac, Milan – Journal of Educational Computing Research, 2021
This study proposes a software system for determining gaze patterns in on-screen testing. The system applies machine learning techniques to eye-movement data obtained from an eye-tracking device to categorize students according to their gaze behavior pattern while solving an on-screen test. These patterns are determined by converting eye movement…
Descriptors: Eye Movements, Computer Assisted Testing, Computer Software, Evaluation Methods
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Ramon Lawrence; Sarah Foss; Tatiana Urazova – ACM Transactions on Computing Education, 2023
Objectives: Automatic assessment systems are widely used to provide rapid feedback for students and reduce grading time. Despite the benefits of increased efficiency and improved pedagogical outcomes, an ongoing challenge is mitigating poor student behaviors when interacting with automatic assessment systems including numerous submissions,…
Descriptors: Student Behavior, Evaluation Methods, Technology Uses in Education, Educational Technology
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Rico-Juan, Juan Ramón; Cachero, Cristina; Macià, Hermenegilda – Assessment & Evaluation in Higher Education, 2022
Maximising the accuracy and learning of self and peer assessment activities in higher education requires instructors to make several design decisions, including whether the assessment process should be individual or collaborative, and, if collaborative, determining the number of members of each peer assessment team. In order to support this…
Descriptors: Self Evaluation (Individuals), Peer Evaluation, Evaluation Methods, College Freshmen
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Mei Yuan Law – Journal of Applied Research in Higher Education, 2024
Purpose: This research aims to investigate the leadership strategies employed by two higher education institutions in Malaysia as they navigated the shift to online delivery of their computer science programs in response to the demands of Education 4.0. Design/methodology/approach: A phenomenological, comparative case study approach was used to…
Descriptors: Instructional Leadership, Educational Change, Higher Education, Online Courses
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Lu, Chang; Macdonald, Rob; Odell, Bryce; Kokhan, Vasyl; Demmans Epp, Carrie; Cutumisu, Maria – Journal of Computing in Higher Education, 2022
The field of computational thinking (CT) is developing rapidly, reflecting its importance in the global economy. However, most empirical studies have targeted CT in K-12, thus, little attention has been paid to CT in higher education. The present scoping review identifies and summarizes existing empirical studies on CT assessments in…
Descriptors: Computation, Thinking Skills, Higher Education, Educational Trends
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Mike Richards; Kevin Waugh; Mark A Slaymaker; Marian Petre; John Woodthorpe; Daniel Gooch – ACM Transactions on Computing Education, 2024
Cheating has been a long-standing issue in university assessments. However, the release of ChatGPT and other free-to-use generative AI tools has provided a new and distinct method for cheating. Students can run many assessment questions through the tool and generate a superficially compelling answer, which may or may not be accurate. We ran a…
Descriptors: Computer Science Education, Artificial Intelligence, Cheating, Student Evaluation
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