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Giora Alexandron; Aviram Berg; Jose A. Ruiperez-Valiente – IEEE Transactions on Learning Technologies, 2024
This article presents a general-purpose method for detecting cheating in online courses, which combines anomaly detection and supervised machine learning. Using features that are rooted in psychometrics and learning analytics literature, and capture anomalies in learner behavior and response patterns, we demonstrate that a classifier that is…
Descriptors: Cheating, Identification, Online Courses, Artificial Intelligence
Jessica K. Holien; Lachlan Coff; Andrew J. Guy; Jennifer C. Boer – Journal of Chemical Education, 2023
During COVID-19 lockdowns, online learning activities had to be developed for the Undergraduate and Masters by Coursework Bioinformatics students at RMIT University. Therefore, we designed an integrative, industry-based research assignment, which guided the students through a drug discovery project from target identification to lead optimization.…
Descriptors: Chemistry, Drug Therapy, Science Instruction, Undergraduate Students
Pillutla, Venkata Sai; Tawfik, Andrew A.; Giabbanelli, Philippe J. – Technology, Knowledge and Learning, 2020
In massive open online courses (MOOCs), learners can interact with each other using discussion boards. Automatically inferring the states or needs of learners from their posts is of interest to instructors, who are faced with a high attrition in MOOCs. Machine learning has previously been successfully used to identify states such as confusion or…
Descriptors: Learning Processes, Online Courses, Data Collection, Data Analysis
Mbouzao, Boniface; Desmarais, Michel C.; Shrier, Ian – International Educational Data Mining Society, 2020
Massive online Open Courses (MOOCs) make extensive use of videos. Students interact with them by pausing, seeking forward or backward, replaying segments, etc. We can reasonably assume that students have different patterns of video interactions, but it remains hard to compare student video interactions. Some methods were developed, such as Markov…
Descriptors: Comparative Analysis, Video Technology, Interaction, Measurement Techniques
Victor Ong; Stanley Yamashiro – Biomedical Engineering Education, 2022
Teaching labs at the undergraduate level poses unique challenges to a school system forced online by COVID-19. We adapted physiology laboratories typically taught in-person to an online-only format, allowing students to measure personal health data alone. Students used available technology and low-cost devices for measuring respiratory and…
Descriptors: COVID-19, Physiology, Human Body, Laboratory Experiments
Haarman, Susan – Philosophical Studies in Education, 2021
In this article, Susan Haarman discusses the ways in which datafication technologies such as Big Data and algorithms have the potential to either challenge or exacerbate what Miranda Fricker calls epistemic injustice. She briefly defines epistemic injustice using Fricker's subsets of testimonial and hermeneutical injustice before moving to the…
Descriptors: Data Analysis, Hermeneutics, Activism, Story Telling
Buser, Peter; Semmler, Klaus-Dieter – Journal of Learning Analytics, 2017
These pages aim to explain and interpret why the late Mika Seppälä, a conformal geometer, proposed to model student study behaviour using concepts from conformal geometry, such as Riemann surfaces and Strebel differentials. Over many years Mika Seppälä taught online calculus courses to students at Florida State University in the United States, as…
Descriptors: Geometry, Student Behavior, Mathematical Models, Graphs
Fesler, Lily; Dee, Thomas; Baker, Rachel; Evans, Brent – Journal of Research on Educational Effectiveness, 2019
Recent advances in computational linguistics and the social sciences have created new opportunities for the education research community to analyze relevant large-scale text data. However, the take-up of these advances in education research is still nascent. In this article, we review the recent automated text methods relevant to educational…
Descriptors: Educational Research, Content Analysis, Research Methodology, Data Analysis
Fesler, Lily; Dee, Thomas; Baker, Rachel; Evans, Brent – Grantee Submission, 2019
Recent advances in computational linguistics and the social sciences have created new opportunities for the education research community to analyze relevant large-scale text data. However, the take-up of these advances in education research is still nascent. In this article, we review the recent automated text methods relevant to educational…
Descriptors: Educational Research, Content Analysis, Research Methodology, Data Analysis
Pratsri, Sajeewan; Nilsook, Prachyanun – Higher Education Studies, 2020
According to a continuously increasing amount of information in all aspects whether the sources are retrieved from an internal or external organization, a platform should be provided for the automation of whole processes in the collection, storage, and processing of Big Data. The tool for creating Big Data is a Big Data challenge. Furthermore, the…
Descriptors: Data Analysis, Higher Education, Information Systems, Data Collection
Prior-Grosch, Ariadne; Woodruff, Karen – Science Teacher, 2022
Fall 2020 presented myriad challenges for teachers trying to plan curricula to meet students' social-emotional and learning needs following an unprecedented spring and summer of isolation and loss due to the pandemic caused by SARS-CoV-2 (Rivera and Wallace 2020). The result of creative planning and adjusting of curricula for remote instruction…
Descriptors: COVID-19, Pandemics, School Closing, Distance Education
Liang, Dong; Chen, Guanbo; Tian, Hailin; Lu, Qi – Advances in Engineering Education, 2020
This article describes how the Sichuan University - Pittsburgh Institute has embraced new methods and new technologies to ensure high-quality laboratory teaching during the COVID-19 pandemic. Taking Mechanical Measurements 1 course as an example, this paper introduces two lab projects that were successfully transferred into online experiments…
Descriptors: Foreign Countries, Educational Technology, Technology Uses in Education, COVID-19
Chen, Zhongzhou; Lee, Sunbok; Garrido, Geoffrey – International Educational Data Mining Society, 2018
The amount of information contained in any educational data set is fundamentally constrained by the instructional conditions under which the data are collected. In this study, we show that by redesigning the structure of traditional online courses, we can improve the ability of educational data mining to provide useful information for instructors.…
Descriptors: Online Courses, Course Organization, Data Analysis, Instructional Design
Chatti, Mohamed Amine; Muslim, Arham – International Review of Research in Open and Distributed Learning, 2019
Personalization is crucial for achieving smart learning environments in different lifelong learning contexts. There is a need to shift from one-size-fits-all systems to personalized learning environments that give control to the learners. Recently, learning analytics (LA) is opening up new opportunities for promoting personalization by providing…
Descriptors: Guidelines, Data Analysis, Learning Experience, Metacognition
Marcella, Vanessa; Samofalova, Yuliya – Language Learning in Higher Education, 2022
This work is a contribution to the usefulness of climate-related authentic material for pedagogical purposes in Higher Education. The two case studies had the aim of raising environmental awareness of a sustainable future among university students, while encouraging them to explore language use and draw their own conclusions and considerations…
Descriptors: Environmental Education, Cross Cultural Studies, Foreign Countries, Climate