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Van Petegem, Charlotte; Deconinck, Louise; Mourisse, Dieter; Maertens, Rien; Strijbol, Niko; Dhoedt, Bart; De Wever, Bram; Dawyndt, Peter; Mesuere, Bart – Journal of Educational Computing Research, 2023
We present a privacy-friendly early-detection framework to identify students at risk of failing in introductory programming courses at university. The framework was validated for two different courses with annual editions taken by higher education students (N = 2 080) and was found to be highly accurate and robust against variation in course…
Descriptors: Pass Fail Grading, At Risk Students, Introductory Courses, Programming
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Edwards, John; Hart, Kaden; Shrestha, Raj – Journal of Educational Data Mining, 2023
Analysis of programming process data has become popular in computing education research and educational data mining in the last decade. This type of data is quantitative, often of high temporal resolution, and it can be collected non-intrusively while the student is in a natural setting. Many levels of granularity can be obtained, such as…
Descriptors: Data Analysis, Computer Science Education, Learning Analytics, Research Methodology
Luz, Bruno N.; Santos, Rafael; Alves, Bruno; Areão, Andreza S.; Yokoyama, Marcos H.; Guimarães, Marcelo P. – International Association for Development of the Information Society, 2015
The main purpose of this paper is to present the importance of Interactive Learning Objects (ILO) to improve the teaching-learning process by assuring a constant interaction among teachers and students, which in turn, allows students to be constantly supported by the teacher. The paper describes the ontology that defines the ILO available on the…
Descriptors: Resource Units, Metadata, Interaction, Learning Processes
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Knauf, Rainer; Sakurai, Yoshitaka; Tsuruta, Setsuo; Jantke, Klaus P. – Journal of Educational Computing Research, 2010
University education often suffers from a lack of an explicit and adaptable didactic design. Students complain about the insufficient adaptability to the learners' needs. Learning content and services need to reach their audience according to their different prerequisites, needs, and different learning styles and conditions. A way to overcome such…
Descriptors: Prerequisites, College Instruction, Educational Experiments, Cognitive Style
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Miller, L. D.; Soh, Leen-Kiat; Samal, Ashok; Nugent, Gwen – International Journal of Artificial Intelligence in Education, 2012
Learning objects (LOs) are digital or non-digital entities used for learning, education or training commonly stored in repositories searchable by their associated metadata. Unfortunately, based on the current standards, such metadata is often missing or incorrectly entered making search difficult or impossible. In this paper, we investigate…
Descriptors: Computer Science Education, Metadata, Internet, Artificial Intelligence
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Reiners, Torsten; Dreher, Heinz – Journal of Information Technology Education, 2009
In modern learning environments, the lecturer or educational designer is often confronted with multi-national student cohorts, requiring special consideration regarding language, cultural norms and taboos, religion, and ethics. Through a somewhat provocative example we demonstrate that taking such factors into account can be essential to avoid…
Descriptors: Student Diversity, Culturally Relevant Education, Profiles, Cultural Differences
Amin, Rohan Mahesh – ProQuest LLC, 2010
Targeted email attacks to enable computer network exploitation have become more prevalent, more insidious, and more widely documented in recent years. Beyond nuisance spam or phishing designed to trick users into revealing personal information, targeted malicious email (TME) facilitates computer network exploitation and the gathering of sensitive…
Descriptors: Electronic Mail, Program Effectiveness, Classification, Statistical Analysis
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Holmboe, Christian – Computer Science Education, 2005
Constructing a data model for a problem area requires identifying and formulating some symbolic representation of the concepts involved, their characteristics, and the relationships between them. Taking a socio-cultural perspective on learning, analysis of classroom dialog is used to identify cognitive challenges met by novice students of data…
Descriptors: Concept Formation, Concept Teaching, Psycholinguistics, Metalinguistics
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Derntl, Michael; Botturi, Luca – Computer Science Education, 2006
Coming from architecture, through computer science, pattern-based design spread into other disciplines and is nowadays recognized as a powerful way of capturing and reusing effective design practice. However, current pedagogical pattern approaches lack widespread adoption, both by users and authors, and are still limited to individual initiatives.…
Descriptors: Computer System Design, Computer Science Education, Design Requirements, Scientific Concepts
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Abel, Marie-Helene; Benayache, Ahcene; Lenne, Dominique; Moulin, Claude; Barry, Catherine; Chaput, Brigitte – Educational Technology & Society, 2004
E-learning leads to evolutions in the way of designing a course. Diffused through the web, the course content cannot be the direct transcription of a face to face course content. A course can be seen as an organization in which different actors are involved. These actors produce documents, information and knowledge that they often share. We…
Descriptors: Course Content, Internet, College Instruction, Models
International Association for Development of the Information Society, 2012
The IADIS CELDA 2012 Conference intention was to address the main issues concerned with evolving learning processes and supporting pedagogies and applications in the digital age. There had been advances in both cognitive psychology and computing that have affected the educational arena. The convergence of these two disciplines is increasing at a…
Descriptors: Academic Achievement, Academic Persistence, Academic Support Services, Access to Computers