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Schneider, Johannes; Bernstein, Abraham; Brocke, Jan vom; Damevski, Kostadin; Shepherd, David C. – IEEE Transactions on Learning Technologies, 2018
All methodologies for detecting plagiarism to date have focused on the final digital "outcome", such as a document or source code. Our novel approach takes the creation process into account using logged events collected by special software or by the macro recorders found in most office applications. We look at an author's interaction…
Descriptors: Plagiarism, Assignments, Programming, Computer Software
Wan, Han; Liu, Kangxu; Yu, Qiaoye; Gao, Xiaopeng – IEEE Transactions on Learning Technologies, 2019
Most educational institutions adopted the hybrid teaching mode through learning management systems. The logging data/clickstream could describe learners' online behavior. Many researchers have used them to predict students' performance, which has led to a diverse set of findings, but how to use insights from captured data to enhance learning…
Descriptors: Educational Practices, Learner Engagement, Identification, Study Habits
Charlton, Patricia; Avramides, Katerina – IEEE Transactions on Learning Technologies, 2016
This paper focuses on a design based research study about STEM (Science, Technology, Engineering and Maths) learning by making through collaboration and production. This study examines learning by making by students to explore STEM using a constructionist approach with a particular focus on computer science and engineering. The use of IoT as a…
Descriptors: Computer Science Education, Engineering Education, STEM Education, Constructivism (Learning)