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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
Poitras, Eric; Butcher, Kirsten R.; Orr, Matthew; Hudson, Michelle A.; Larson, Madlyn – Interactive Learning Environments, 2022
This study mined student interactions with visual representations as a means to automate assessment of learning in a complex, inquiry-based learning environment. Log trace data of 143 middle school students' interactions with an interactive map in Research Quest (an inquiry-based, online learning environment) were analyzed. Students used the…
Descriptors: Middle School Students, Electronic Learning, Maps, Science 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
Ming, Norma C.; Ming, Vivienne L. – Technology, Instruction, Cognition and Learning, 2015
We present a method to help faculty assess and visualize conceptual knowledge by applying topic modeling to unstructured student writing from online class discussion forums. To validate the technique against conventional assessment metrics, we evaluated its accuracy in predicting final grades in introductory undergraduate biology and graduate…
Descriptors: Knowledge Level, Student Evaluation, Writing (Composition), Online Courses
Valsamidis, Stavros; Kontogiannis, Sotirios; Kazanidis, Ioannis; Theodosiou, Theodosios; Karakos, Alexandros – Educational Technology & Society, 2012
Learning Management Systems (LMS) collect large amounts of data. Data mining techniques can be applied to analyse their web data log files. The instructors may use this data for assessing and measuring their courses. In this respect, we have proposed a methodology for analysing LMS courses and students' activity. This methodology uses a Markov…
Descriptors: Foreign Countries, Electronic Learning, College Mathematics, Integrated Learning Systems
Hung, Jui-long – British Journal of Educational Technology, 2012
This study investigated the longitudinal trends of e-learning research using text mining techniques. Six hundred and eighty-nine (689) refereed journal articles and proceedings were retrieved from the Science Citation Index/Social Science Citation Index database in the period from 2000 to 2008. All e-learning publications were grouped into two…
Descriptors: Electronic Learning, Medical Education, Social Sciences, Journal Articles
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
Sharma, Richa – International Journal on E-Learning, 2011
Building intelligent course designing systems adaptable to the learners' needs is one of the key goals of research in e-learning. This goal is all the more crucial as gaining knowledge in an e-learning environment depends solely on computer mediated interaction within the learner group and among the learners and instructors. The patterns generated…
Descriptors: Electronic Learning, Educational Environment, Instructional Design, Student Needs
Jones, Kenneth D., II. – ProQuest LLC, 2010
The primary purpose of this study is to determine how students are impacted by the use of Classroom Response System (CRS) technology. This research explores the nature of the outcomes experienced by students and their perceptions on the leading pedagogy and practices for using CRS technology in the classroom. The research is both quantitative and…
Descriptors: Quasiexperimental Design, Personality, Information Systems, Educational Technology
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