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Angeles Lopez; M. Asunción Castaño; M. Victoria Ibáñez; Ismael Sanz; Lledó Museros; Reyes Grangel – ACM Transactions on Computing Education, 2025
The Bachelor's Degree in Computer Engineering at University Jaume I has a capstone project in which the student develops, during a 300-hour internship in an enterprise, a real-world project. We collected data for five academic years to analyze the assessment process to propose a new hybrid model, which combines analytic and holistic assessment and…
Descriptors: Capstone Experiences, Internship Programs, Student Projects, Undergraduate Students
Tavares, Paula Correia; Gomes, Elsa Ferreira; Henriques, Pedro Rangel; Vieira, Diogo Manuel – Open Education Studies, 2022
Computer Programming Learners usually fail to get approved in introductory courses because solving problems using computers is a complex task. The most important reason for that failure is concerned with motivation; motivation strongly impacts on the learning process. In this paper we discuss how techniques like program animation, and automatic…
Descriptors: Learner Engagement, Programming, Computer Science Education, Problem Solving
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
Berriri, Mehdi; Djema, Sofiane; Rey, Gaëtan; Dartigues-Pallez, Christel – Education Sciences, 2021
Today, many students are moving towards higher education courses that do not suit them and end up failing. The purpose of this study is to help provide counselors with better knowledge so that they can offer future students courses corresponding to their profile. The second objective is to allow the teaching staff to propose training courses…
Descriptors: Student Evaluation, Artificial Intelligence, Classification, Foreign Countries
Bocharov, Mikhail I.; Simonova, Irina V.; Bocharov?, Tatyana I.; Zaika, Anna Y. – International Association for Development of the Information Society, 2020
The analysis of the results of scientific research has revealed the necessity to track the level of anxiety of a student while studying aspects of information security in a particular subject area. And in accordance with the results, it was necessary to justify the choice of methods for management and content of information security training in…
Descriptors: Information Security, Computer Science Education, Anxiety, Middle School Students
Liénardy, Simon; Donnet, Benoit; Leduc, Laurent – Student Success, 2021
This practice report discusses the evolution of a CS1 Course taught at the University of Liège, Belgium. Over the last seven years several teaching activities have been thought to complement traditional theoretical courses and exercise sessions in order to promote students' engagement. The result is aligned with (i) the principles of assessment…
Descriptors: Learner Engagement, Computer Science Education, Introductory Courses, Student Evaluation
Jui-Hung Chang; Chi-Jane Wang; Hua-Xu Zhong; Hsiu-Chen Weng; Yu-Kai Zhou; Hoe-Yuan Ong; Chin-Feng Lai – Educational Technology Research and Development, 2024
Amidst the rapid advancement in the application of artificial intelligence learning, questions regarding the evaluation of students' learning status and how students without relevant learning foundation on this subject can be trained to familiarize themselves in the field of artificial intelligence are important research topics. This study…
Descriptors: Artificial Intelligence, Technological Advancement, Student Evaluation, Models
Mukasheva, Manargul; Omirzakova, Aisara – World Journal on Educational Technology: Current Issues, 2021
The study was carried out from 2018 to 2020 with the challenge - how to assess the level of computational thinking. The research design is mixed since the disclosure of mutual influence of the components of the chain 'learning programming -- computational thinking -- evaluating computational thinking' requires the use of both qualitative and…
Descriptors: Computation, Thinking Skills, Student Evaluation, Cognitive Measurement
Zhizezhang Gao; Haochen Yan; Jiaqi Liu; Xiao Zhang; Yuxiang Lin; Yingzhi Zhang; Xia Sun; Jun Feng – International Journal of STEM Education, 2025
Background: With the increasing interdisciplinarity between computer science (CS) and other fields, a growing number of non-CS students are embracing programming. However, there is a gap in research concerning differences in programming learning between CS and non-CS students. Previous studies predominantly relied on outcome-based assessments,…
Descriptors: Computer Science Education, Mathematics Education, Novices, Programming
Yogi, Jonathan Kimei – ProQuest LLC, 2023
Jung and Won's (2018) review of elementary school ER found a lack of understanding of instructional practices for ER with young children. Other researchers have called for further studies into what effective classroom orchestration and interaction look like within ER classrooms (Ioannou & Makridou, 2018; Xia & Zhong, 2019). This study was…
Descriptors: Computer Science Education, Robotics, Group Dynamics, Gender Differences
Chengliang Wang; Xiaojiao Chen; Yifei Li; Pengju Wang; Haoming Wang; Yuanyuan Li – Journal of Educational Computing Research, 2025
This study explored the impact of MetaClassroom, a virtual immersive programming learning environment designed based on the three-dimensional learning progression (3DLP) concept, on students' multidimensional development. Utilizing a quasi-experimental research design, this study compared students' programming learning achievements (PLA),…
Descriptors: Programming, Computer Science Education, Metacognition, Computer Simulation
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
Yasemin Allsop; Filiz Kalelioglu; Melike Aslan Unlu – International Journal of Computer Science Education in Schools, 2024
This study investigated the effectiveness of the 'Match it' card sorting activity for evaluating the student teachers' knowledge and understanding of computational thinking (CT) concepts. One hundred forty-six primary student teachers were asked to sort 26 scenarios and words alongside nine images under five main computational concepts:…
Descriptors: Preservice Teachers, Teacher Education Programs, Thinking Skills, Generalization
European Education and Culture Executive Agency, European Commission, 2023
This report presents the results of the 2023 data collection on the structural indicators for monitoring education and training systems in the area of digital competence. The report contains six indicators on key policies in the following areas: 1. curriculum, 2. teachers, 3. assessment, 4. the digital education ecosystem. The paper contains…
Descriptors: Foreign Countries, Technological Literacy, Educational Policy, Curriculum
Lertyosbordin, Chacharin; Maneewan, Sorakrich; Yampinij, Sakesun; Thamwipat, Kuntida – International Education Studies, 2019
Office of basic education commission of Thailand firstly declared the indicator for computing science of the students in primary education and secondary education in 2018. The important of computing science is to develop the learners to solve the questions of computing science by using technology correctly. To gain the effective learning…
Descriptors: Scoring Rubrics, Problem Solving, Computer Science Education, Student Evaluation