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Chen, Lujie Karen; Ramsey, Joseph; Dubrawski, Artur – Journal of Educational Data Mining, 2021
Human one-on-one coaching involves complex multimodal interactions. Successful coaching requires teachers to closely monitor students' cognitive-affective states and provide support of optimal type, timing, and amount. However, most of the existing human tutoring studies focus primarily on verbal interactions and have yet to incorporate the rich…
Descriptors: Causal Models, Coaching (Performance), Statistical Analysis, Correlation
Kai, Shimin; Almeda, Ma. Victoria; Baker, Ryan S.; Heffernan, Cristina; Heffernan, Neil – Journal of Educational Data Mining, 2018
Research on non-cognitive factors has shown that persistence in the face of challenges plays an important role in learning. However, recent work on wheel-spinning, a type of unproductive persistence where students spend too much time struggling without achieving mastery of skills, show that not all persistence is uniformly beneficial for learning.…
Descriptors: Decision Making, Models, Intervention, Computer Assisted Instruction
Knowles, Jared E. – Journal of Educational Data Mining, 2015
The state of Wisconsin has one of the highest four year graduation rates in the nation, but deep disparities among student subgroups remain. To address this the state has created the Wisconsin Dropout Early Warning System (DEWS), a predictive model of student dropout risk for students in grades six through nine. The Wisconsin DEWS is in use…
Descriptors: Dropouts, Models, Prediction, Risk
Zimmermann, Judith; Brodersen, Kay H.; Heinimann, Hans R.; Buhmann, Joachim M. – Journal of Educational Data Mining, 2015
The graduate admissions process is crucial for controlling the quality of higher education, yet, rules-of-thumb and domain-specific experiences often dominate evidence-based approaches. The goal of the present study is to dissect the predictive power of undergraduate performance indicators and their aggregates. We analyze 81 variables in 171…
Descriptors: Undergraduate Students, Graduate Students, Academic Achievement, Prediction
Liu, Ran; Koedinger, Kenneth R. – Journal of Educational Data Mining, 2017
As the use of educational technology becomes more ubiquitous, an enormous amount of learning process data is being produced. Educational data mining seeks to analyze and model these data, with the ultimate goal of improving learning outcomes. The most firmly grounded and rigorous evaluation of an educational data mining discovery is whether it…
Descriptors: Educational Technology, Technology Uses in Education, Data Collection, Data Analysis
Kowalski, John; Zhang, Yanhui; Gordon, Geoffrey J. – Journal of Educational Data Mining, 2014
The Pinyin Tutor has been used the past few years at over thirty institutions around the world to teach students to transcribe spoken Chinese phrases into Pinyin. Large amounts of data have been collected from this program on the types of errors students make on this task. We analyze these data to discover what makes this task difficult and use…
Descriptors: Intelligent Tutoring Systems, Chinese, Verbal Communication, Statistical Analysis
Waters, Andrew; Studer, Christoph; Baraniuk, Richard – Journal of Educational Data Mining, 2014
Identifying collaboration between learners in a course is an important challenge in education for two reasons: First, depending on the courses rules, collaboration can be considered a form of cheating. Second, it helps one to more accurately evaluate each learners competence. While such collaboration identification is already challenging in…
Descriptors: Cooperation, Large Group Instruction, Online Courses, Probability
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
Cetintas, Suleyman; Si, Luo; Xin, Yan Ping; Zhang, Dake; Park, Joo Young; Tzur, Ron – Journal of Educational Data Mining, 2010
Estimating the difficulty level of math word problems is an important task for many educational applications. Identification of relevant and irrelevant sentences in math word problems is an important step for calculating the difficulty levels of such problems. This paper addresses a novel application of text categorization to identify two types of…
Descriptors: Probability, Word Problems (Mathematics), Classification, Difficulty Level
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