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Meng, Huijuan; Ma, Ye – Educational Measurement: Issues and Practice, 2023
In recent years, machine learning (ML) techniques have received more attention in detecting aberrant test-taking behaviors due to advantages when compared to traditional data forensics methods. However, defining "True Test Cheaters" is challenging--different than other fraud detection tasks such as flagging forged bank checks or credit…
Descriptors: Artificial Intelligence, Cheating, Testing, Information Technology
Langerbein, Janine; Massing, Till; Klenke, Jens; Striewe, Michael; Goedicke, Michael; Hanck, Christoph – International Educational Data Mining Society, 2023
Due to the precautionary measures during the COVID-19 pandemic many universities offered unproctored take-home exams. We propose methods to detect potential collusion between students and apply our approach on event log data from take-home exams during the pandemic. We find groups of students with suspiciously similar exams. In addition, we…
Descriptors: Information Retrieval, Pattern Recognition, Data Analysis, Information Technology
Zhang, Wei; Zeng, Xinyao; Wang, Jihan; Ming, Daoyang; Li, Panpan – Education and Information Technologies, 2022
Programming skills (PS) are indispensable abilities in the information age, but the current research on PS cultivation mainly focuses on the teaching methods and lacks the analysis of program features to explore the differences in learners' PS and guide programming learning. Therefore, the purpose of this study aims to explore horizontal…
Descriptors: Programming, Skill Development, Information Retrieval, Data Processing
Cohausz, Lea; Tschalzev, Andrej; Bartelt, Christian; Stuckenschmidt, Heiner – International Educational Data Mining Society, 2023
Demographic features are commonly used in Educational Data Mining (EDM) research to predict at-risk students. Yet, the practice of using demographic features has to be considered extremely problematic due to the data's sensitive nature, but also because (historic and representation) biases likely exist in the training data, which leads to strong…
Descriptors: Information Retrieval, Data Processing, Pattern Recognition, Information Technology
Ustaog?lu, Mehmet Ali; Kukul, Volkan – Open Praxis, 2022
MOOCs can be considered as a powerful alternative in extraordinary situations where people cannot reach formal education. In recent years, the widespread use of the internet worldwide and especially the COVID-19 has increased the need of people for MOOCs. However, in order to increase the effectiveness of MOOCs, and to provide a better learning…
Descriptors: Students, MOOCs, Student Satisfaction, Electronic Publishing
Roslan, Muhammad Haziq Bin; Chen, Chwen Jen – Education and Information Technologies, 2023
This study attempts to predict secondary school students' performance in English and Mathematics subjects using data mining (DM) techniques. It aims to provide insights into predictors of students' performance in English and Mathematics, characteristics of students with different levels of performance, the most effective DM technique for students'…
Descriptors: Foreign Countries, Secondary School Students, Academic Achievement, English Instruction
Trakunphutthirak, Ruangsak; Lee, Vincent C. S. – Journal of Educational Computing Research, 2022
Educators in higher education institutes often use statistical results obtained from their online Learning Management System (LMS) dataset, which has limitations, to evaluate student academic performance. This study differs from the current body of literature by including an additional dataset that advances the knowledge about factors affecting…
Descriptors: Information Retrieval, Pattern Recognition, Data Analysis, Information Technology
Dun, Yijie; Wang, Na; Wang, Min; Hao, Tianyong – International Journal of Distance Education Technologies, 2017
In a question-answering system, learner generated content including asked and answered questions is a meaningful resource to capture learning interests. This paper proposes an approach based on question topic mining for revealing learners' concerned topics in real community question-answering systems. The authors' approach firstly preprocesses all…
Descriptors: Natural Language Processing, Information Retrieval, Data Processing, Pattern Recognition
Niemi, David; Gitin, Elena – International Association for Development of the Information Society, 2012
An underlying theme of this paper is that it can be easier and more efficient to conduct valid and effective research studies in online environments than in traditional classrooms. Taking advantage of the "big data" available in an online university, we conducted a study in which a massive online database was used to predict student…
Descriptors: Higher Education, Online Courses, Academic Persistence, Identification
Nguyen, Bao-An; Yang, Don-Lin – International Review of Research in Open and Distance Learning, 2012
An ontology is an effective formal representation of knowledge used commonly in artificial intelligence, semantic web, software engineering, and information retrieval. In open and distance learning, ontologies are used as knowledge bases for e-learning supplements, educational recommenders, and question answering systems that support students with…
Descriptors: Language Processing, Information Retrieval, Instructional Materials, Semantics
Mislevy, Robert J.; Behrens, John T.; Dicerbo, Kristen E.; Levy, Roy – Journal of Educational Data Mining, 2012
"Evidence-centered design" (ECD) is a comprehensive framework for describing the conceptual, computational and inferential elements of educational assessment. It emphasizes the importance of articulating inferences one wants to make and the evidence needed to support those inferences. At first blush, ECD and "educational data…
Descriptors: Educational Assessment, Psychometrics, Evidence, Computer Games
Cohen, Sandra; Kaimenakis, Nikolaos – Learning Organization, 2007
Purpose: In recent years a significant number of intellectual capital (IC) metrics has been developed and applied in many organizations. However, there is still a strong need to specify the relations among the different categories of intellectual assets that exist in the context of small to medium-sized enterprises (SME), and to determine the way…
Descriptors: Foreign Countries, Social Networks, Human Capital, Intellectual Property