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PaaBen, Benjamin; Dywel, Malwina; Fleckenstein, Melanie; Pinkwart, Niels – International Educational Data Mining Society, 2022
Item response theory (IRT) is a popular method to infer student abilities and item difficulties from observed test responses. However, IRT struggles with two challenges: How to map items to skills if multiple skills are present? And how to infer the ability of new students that have not been part of the training data? Inspired by recent advances…
Descriptors: Item Response Theory, Test Items, Item Analysis, Inferences
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Tempelaar, Dirk – International Association for Development of the Information Society, 2022
E-tutorial learning aids as worked examples and hints have been established as effective instructional formats in problem-solving practices. However, less is known about variations in the use of learning aids across individuals at different stages in their learning process in student-centred learning contexts. This study investigates different…
Descriptors: Learning Analytics, Student Centered Learning, Learning Processes, Student Behavior
Yikai Lu; Teresa M. Ober; Cheng Liu; Ying Cheng – Grantee Submission, 2022
Machine learning methods for predictive analytics have great potential for uncovering trends in educational data. However, simple linear models still appear to be most widely used, in part, because of their interpretability. This study aims to address the issues of interpretability of complex machine learning classifiers by conducting feature…
Descriptors: Prediction, Statistics Education, Data Analysis, Learning Analytics
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Barollet, Théo; Bouchez Tichadou, Florent; Rastello, Fabrice – International Educational Data Mining Society, 2021
In Intelligent Tutoring Systems (ITS), methods to choose the next exercise for a student are inspired from generic recommender systems, used, for instance, in online shopping or multimedia recommendation. As such, collaborative filtering, especially matrix factorization, is often included as a part of recommendation algorithms in ITS. One notable…
Descriptors: Intelligent Tutoring Systems, Prediction, Internet, Purchasing
Ji-Eun Lee; Amisha Jindal; Sanika Nitin Patki; Ashish Gurung; Reilly Norum; Erin Ottmar – Grantee Submission, 2022
This paper demonstrates how to apply Machine Learning (ML) techniques to analyze student interaction data collected in an online mathematics game. We examined: (1) how different ML algorithms influenced the precision of middle-school students' (N = 359) performance prediction; and (2) what types of in-game features were associated with student…
Descriptors: Teaching Methods, Algorithms, Mathematics Tests, Computer Games
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Ojeda-Hernández, Manuel; Pérez-Gámez, Francisco; Bonilla, Ángel Mora; López-Rodríguez, Domingo – International Association for Development of the Information Society, 2021
Due to the COVID-19 restrictions, high-schools in Spain are having both online and in-class lectures. As a result, the students can use not only the information provided by the teachers in class, but they can also use several other methods such as videos and online examples that allow the students to have materials from different places. In this…
Descriptors: Logical Thinking, Mathematics Education, Foreign Countries, High School Students
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Grimaldi, Phillip; Weatherholtz, Kodi; Hill, Kelli Millwood – International Educational Data Mining Society, 2022
As educational technology platforms become more and more commonplace in education, it is critical that these systems work well across a diverse range of student sub-groups. In this study, we estimated the effectiveness of MAP Accelerator; a large-scale, personalized, web-based, mathematics mastery learning platform. Our analysis placed a…
Descriptors: Educational Technology, Mastery Learning, Learning Management Systems, Middle School Students
Adjei, Seth A.; Botelho, Anthony F.; Heffernan, Neil T. – Grantee Submission, 2016
Prerequisite skill structures have been closely studied in past years leading to many data-intensive methods aimed at refining such structures. While many of these proposed methods have yielded success, defining and refining hierarchies of skill relationships are often difficult tasks. The relationship between skills in a graph could either be…
Descriptors: Prediction, Learning Analytics, Attribution Theory, Prerequisites