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John Stamper; Steven Moore; Carolyn P. Rosé; Philip I. Pavlik Jr.; Kenneth Koedinger – Journal of Educational Data Mining, 2024
LearnSphere is a web-based data infrastructure designed to transform scientific discovery and innovation in education. It supports learning researchers in addressing a broad range of issues including cognitive, social, and motivational factors in learning, educational content analysis, and educational technology innovation. LearnSphere integrates…
Descriptors: Learning Analytics, Web Sites, Data Use, Educational Technology
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Zehner, Fabian; Eichmann, Beate; Deribo, Tobias; Harrison, Scott; Bengs, Daniel; Andersen, Nico; Hahnel, Carolin – Journal of Educational Data Mining, 2021
The NAEP EDM Competition required participants to predict efficient test-taking behavior based on log data. This paper describes our top-down approach for engineering features by means of psychometric modeling, aiming at machine learning for the predictive classification task. For feature engineering, we employed, among others, the Log-Normal…
Descriptors: National Competency Tests, Engineering Education, Data Collection, Data Analysis
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Jacob Whitehill; Jennifer LoCasale-Crouch – Journal of Educational Data Mining, 2024
With the aim to provide teachers with more specific, frequent, and actionable feedback about their teaching, we explore how Large Language Models (LLMs) can be used to estimate "Instructional Support" domain scores of the CLassroom Assessment Scoring System (CLASS), a widely used observation protocol. We design a machine learning…
Descriptors: Artificial Intelligence, Teacher Evaluation, Models, Transcripts (Written Records)
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Winne, Philip H.; Baker, Ryan S. J. D. – Journal of Educational Data Mining, 2013
Our article introduces the "Journal of Educational Data Mining's" Special Issue on Educational Data Mining on Motivation, Metacognition, and Self-Regulated Learning. We outline general research challenges for data mining researchers who conduct investigations in these areas, the potential of EDM to advance research in this area, and…
Descriptors: Data Analysis, Metacognition, Motivation, Learning Strategies
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Rupp, André A.; Nugent, Rebecca; Nelson, Brian – Journal of Educational Data Mining, 2012
In recent years the educational community has increasingly embraced digital technologies for the purposes of developing alternative learning environments, providing diagnostic feedback, and fostering the development of so-called 21st-century skills. This special issue is dedicated to bridging recent work from the disciplines of educational and…
Descriptors: Electronic Learning, Psychometrics, Educational Environment, Educational Technology
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Ezen-Can, Aysu; Boyer, Kristy Elizabeth – Journal of Educational Data Mining, 2015
Within the landscape of educational data, textual natural language is an increasingly vast source of learning-centered interactions. In natural language dialogue, student contributions hold important information about knowledge and goals. Automatically modeling the dialogue act of these student utterances is crucial for scaling natural language…
Descriptors: Classification, Dialogs (Language), Computational Linguistics, Information Retrieval
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Nelson, Brian; Nugent, Rebecca; Rupp, Andre A. – Journal of Educational Data Mining, 2012
This special issue of "JEDM" was dedicated to bridging work done in the disciplines of "educational and psychological assessment" and "educational data mining" (EDM) via the assessment design and implementation framework of "evidence-centered design" (ECD). It consisted of a series of five papers: one…
Descriptors: Statistical Analysis, Value Added Models, Educational Assessment, Program Design
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Xu, Beijie; Recker, Mimi – Journal of Educational Data Mining, 2011
This article describes the Knowledge Discovery and Data Mining (KDD) process and its application in the field of educational data mining (EDM) in the context of a digital library service called the Instructional Architect (IA.usu.edu). In particular, the study reported in this article investigated a certain type of data mining problem, clustering,…
Descriptors: Electronic Libraries, Library Services, Multivariate Analysis, Electronic Learning
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Amershi, Saleema; Conati, Cristina – Journal of Educational Data Mining, 2009
In this paper, we present a data-based user modeling framework that uses both unsupervised and supervised classification to build student models for exploratory learning environments. We apply the framework to build student models for two different learning environments and using two different data sources (logged interface and eye-tracking data).…
Descriptors: Supervision, Classification, Models, Educational Environment