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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
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
Chung, Cheng-Yu; Hsiao, I-Han – International Educational Data Mining Society, 2021
The distributed practice effect suggests that students retain learning content better when they pace their practice over time. The key factors are practice dosage (intensity) and timing (when to practice and how in between). Inspired by the thriving development of image recognition, this study adopts one of the successful techniques,…
Descriptors: Models, Drills (Practice), Pacing, Computer Uses in Education
Karimov, Ayaz; Saarela, Mirka; Kärkkäinen, Tommi – International Educational Data Mining Society, 2023
Within the last decade, different educational data mining techniques, particularly quantitative methods such as clustering, and regression analysis are widely used to analyze the data from educational games. In this research, we implemented a quantitative data mining technique (clustering) to further investigate students' feedback. Students played…
Descriptors: Student Attitudes, Feedback (Response), Educational Games, Information Retrieval
Say What? Automatic Modeling of Collaborative Problem Solving Skills from Student Speech in the Wild
Pugh, Samuel L.; Subburaj, Shree Krishna; Rao, Arjun Ramesh; Stewart, Angela E. B.; Andrews-Todd, Jessica; D'Mello, Sidney K. – International Educational Data Mining Society, 2021
We investigated the feasibility of using automatic speech recognition (ASR) and natural language processing (NLP) to classify collaborative problem solving (CPS) skills from recorded speech in noisy environments. We analyzed data from 44 dyads of middle and high school students who used videoconferencing to collaboratively solve physics and math…
Descriptors: Problem Solving, Cooperation, Middle School Students, High School Students
Sharma, Arjun; Biswas, Arijit; Gandhi, Ankit; Patil, Sonal; Deshmukh, Om – International Educational Data Mining Society, 2016
Online educational videos have emerged as one of the most popular modes of learning in the recent years. Studies have shown that liveliness is highly correlated to engagement in educational videos. While previous work has focused on feature engineering to estimate liveliness and that too using only the acoustic information, in this paper we…
Descriptors: Video Technology, Audiovisual Aids, Artificial Intelligence, Prediction
Mi, Fei; Faltings, Boi – International Educational Data Mining Society, 2017
Massive open online courses (MOOCs) have demonstrated growing popularity and rapid development in recent years. Discussion forums have become crucial components for students and instructors to widely exchange ideas and propagate knowledge. It is important to recommend helpful information from forums to students for the benefit of the learning…
Descriptors: Online Courses, Sequential Approach, Discussion Groups, Student Interests
Blanchard, Nathaniel; Donnelly, Patrick J.; Olney, Andrew M.; Samei, Borhan; Ward, Brooke; Sun, Xiaoyi; Kelly, Sean; Nystrand, Martin; D'Mello, Sidney K. – International Educational Data Mining Society, 2016
We investigate automatic detection of teacher questions from automatically segmented human-transcripts of teacher audio recordings collected in live classrooms. Using a dataset of audio recordings from 11 teachers across 37 class sessions, we automatically segment teacher speech into individual teacher utterances and code each as containing a…
Descriptors: Transcripts (Written Records), Nonprint Media, Automation, Classroom Communication
International Educational Data Mining Society, 2012
The 5th International Conference on Educational Data Mining (EDM 2012) is held in picturesque Chania on the beautiful Crete island in Greece, under the auspices of the International Educational Data Mining Society (IEDMS). The EDM 2012 conference is a leading international forum for high quality research that mines large data sets of educational…
Descriptors: Information Retrieval, Data, Data Analysis, Pattern Recognition