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Christhilf, Katerina; Newton, Natalie; Butterfuss, Reese; McCarthy, Kathryn S.; Allen, Laura K.; Magliano, Joseph P.; McNamara, Danielle S. – International Educational Data Mining Society, 2022
Prompting students to generate constructed responses as they read provides a window into the processes and strategies that they use to make sense of complex text. In this study, Markov models examined the extent to which: (1) patterns of strategies; and (2) strategy combinations could be used to inform computational models of students' text…
Descriptors: Markov Processes, Reading Strategies, Reading Comprehension, Models
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Ramesh, Arti; Goldwasser, Dan; Huang, Bert; Daume, Hal; Getoor, Lise – IEEE Transactions on Learning Technologies, 2020
Maintaining and cultivating student engagement is critical for learning. Understanding factors affecting student engagement can help in designing better courses and improving student retention. The large number of participants in massive open online courses (MOOCs) and data collected from their interactions on the MOOC open up avenues for studying…
Descriptors: Online Courses, Learner Engagement, Student Behavior, Success
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Caprotti, Olga – Journal of Learning Analytics, 2017
This paper describes investigations in visualizing logpaths of students in an online calculus course held at Florida State University in 2014. The clickstreams making up the logpaths can be used to visualize student progress in the information space of a course as a graph. We consider the graded activities as nodes of the graph, while information…
Descriptors: Online Courses, Calculus, Markov Processes, Graphs
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Tenison, Caitlin; Anderson, John R. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2016
A focus of early mathematics education is to build fluency through practice. Several models of skill acquisition have sought to explain the increase in fluency because of practice by modeling both the learning mechanisms driving this speedup and the changes in cognitive processes involved in executing the skill (such as transitioning from…
Descriptors: Skill Development, Mathematics Skills, Learning Processes, Markov Processes
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Hlavatý, Robert; Dömeová, Ludmila – International Education Studies, 2014
The paper is focused on students of Mathematical methods in economics at the Czech university of life sciences (CULS) in Prague. The idea is to create a model of students' progress throughout the whole course using the Markov chain approach. Each student has to go through various stages of the course requirements where his success depends on the…
Descriptors: Foreign Countries, Markov Processes, Mathematical Models, Progress Monitoring
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Li, Hongli; Suen, Hoi K. – Educational Assessment, 2013
Cognitive diagnostic analyses have been advocated as methods that allow an assessment to function as a formative assessment to inform instruction. To use this approach, it is necessary to first identify the skills required for each item in the test, known as a Q-matrix. However, because the construct being tested and the underlying cognitive…
Descriptors: Reading Tests, Reading Comprehension, Cognitive Processes, Models
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Feng, Mingyu, Ed.; Käser, Tanja, Ed.; Talukdar, Partha, Ed. – International Educational Data Mining Society, 2023
The Indian Institute of Science is proud to host the fully in-person sixteenth iteration of the International Conference on Educational Data Mining (EDM) during July 11-14, 2023. EDM is the annual flagship conference of the International Educational Data Mining Society. The theme of this year's conference is "Educational data mining for…
Descriptors: Information Retrieval, Data Analysis, Computer Assisted Testing, Cheating
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Huang, Hung-Yu; Wang, Wen-Chung; Chen, Po-Hsi; Su, Chi-Ming – Applied Psychological Measurement, 2013
Many latent traits in the human sciences have a hierarchical structure. This study aimed to develop a new class of higher order item response theory models for hierarchical latent traits that are flexible in accommodating both dichotomous and polytomous items, to estimate both item and person parameters jointly, to allow users to specify…
Descriptors: Item Response Theory, Models, Vertical Organization, Bayesian Statistics
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Huang, Hung-Yu; Wang, Wen-Chung – Educational and Psychological Measurement, 2014
In the social sciences, latent traits often have a hierarchical structure, and data can be sampled from multiple levels. Both hierarchical latent traits and multilevel data can occur simultaneously. In this study, we developed a general class of item response theory models to accommodate both hierarchical latent traits and multilevel data. The…
Descriptors: Item Response Theory, Hierarchical Linear Modeling, Computation, Test Reliability
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Fox, J.-P.; Wyrick, Cheryl – Journal of Educational and Behavioral Statistics, 2008
The randomized response technique ensures that individual item responses, denoted as true item responses, are randomized before observing them and so-called randomized item responses are observed. A relationship is specified between randomized item response data and true item response data. True item response data are modeled with a (non)linear…
Descriptors: Item Response Theory, Models, Markov Processes, Monte Carlo Methods
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Huang, Yueh-Min; Huang, Tien-Chi; Wang, Kun-Te; Hwang, Wu-Yuin – Educational Technology & Society, 2009
The ability to apply existing knowledge in new situations and settings is clearly a vital skill that all students need to develop. Nowhere is this truer than in the rapidly developing world of Web-based learning, which is characterized by non-sequential courses and the absence of an effective cross-subject guidance system. As a result, questions…
Descriptors: Markov Processes, Transfer of Training, Probability, Internet
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Fox, Jean-Paul – Journal of Educational and Behavioral Statistics, 2005
The randomized response (RR) technique is often used to obtain answers on sensitive questions. A new method is developed to measure latent variables using the RR technique because direct questioning leads to biased results. Within the RR technique is the probability of the true response modeled by an item response theory (IRT) model. The RR…
Descriptors: Item Response Theory, Models, Probability, Markov Processes
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Barnes, Tiffany, Ed.; Chi, Min, Ed.; Feng, Mingyu, Ed. – International Educational Data Mining Society, 2016
The 9th International Conference on Educational Data Mining (EDM 2016) is held under the auspices of the International Educational Data Mining Society at the Sheraton Raleigh Hotel, in downtown Raleigh, North Carolina, in the USA. The conference, held June 29-July 2, 2016, follows the eight previous editions (Madrid 2015, London 2014, Memphis…
Descriptors: Data Analysis, Evidence Based Practice, Inquiry, Science Instruction
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Lynch, Collin F., Ed.; Merceron, Agathe, Ed.; Desmarais, Michel, Ed.; Nkambou, Roger, Ed. – International Educational Data Mining Society, 2019
The 12th iteration of the International Conference on Educational Data Mining (EDM 2019) is organized under the auspices of the International Educational Data Mining Society in Montreal, Canada. The theme of this year's conference is EDM in Open-Ended Domains. As EDM has matured it has increasingly been applied to open-ended and ill-defined tasks…
Descriptors: Data Collection, Data Analysis, Information Retrieval, Content Analysis
Borden, Victor M. H.; Dalphin, John F. – 1998
This study used Markov chain matrices to simulate the effect of varying degrees of change in student characteristics on retention and graduation rates. Data were applied to a 1-year enrollment transition matrix that tracks how students of each class level progress into the same or higher class levels, to a completed degree, or to non-returning…
Descriptors: Academic Persistence, College Students, Credits, Enrollment
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