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Timothy Gallagher; Bert Slof; Marieke van der Schaaf; Ryo Toyoda; Yusra Tehreem; Sofia Garcia Fracaro; Liesbeth Kester – Journal of Computer Assisted Learning, 2024
Background: The potential of learning analytics dashboards in virtual reality simulation-based training environments to influence occupational self-efficacy via self-reflection phase processes in the Chemical industry is still not fully understood. Learning analytics dashboards provide feedback on learner performance and offer points of comparison…
Descriptors: Learning Analytics, Self Efficacy, Reflection, Chemistry
Du, Han; Enders, Craig; Keller, Brian; Bradbury, Thomas N.; Karney, Benjamin R. – Grantee Submission, 2022
Missing data are exceedingly common across a variety of disciplines, such as educational, social, and behavioral science areas. Missing not at random (MNAR) mechanism where missingness is related to unobserved data is widespread in real data and has detrimental consequence. However, the existing MNAR-based methods have potential problems such as…
Descriptors: Bayesian Statistics, Data Analysis, Computer Simulation, Sample Size
Jiang, Shiyan; Huang, Xudong; Sung, Shannon H.; Xie, Charles – Research in Science Education, 2023
Learning analytics, referring to the measurement, collection, analysis, and reporting of data about learners and their contexts in order to optimize learning and the environments in which it occurs, is proving to be a powerful approach for understanding and improving science learning. However, few studies focused on leveraging learning analytics…
Descriptors: Learning Analytics, Hands on Science, Science Education, Laboratory Safety
Zhang, Qiao; Maclellan, Christopher J. – International Educational Data Mining Society, 2021
Knowledge tracing algorithms are embedded in Intelligent Tutoring Systems (ITS) to keep track of students' learning process. While knowledge tracing models have been extensively studied in offline settings, very little work has explored their use in online settings. This is primarily because conducting experiments to evaluate and select knowledge…
Descriptors: Electronic Learning, Mastery Learning, Computer Simulation, Intelligent Tutoring Systems
The AI Teacher Test: Measuring the Pedagogical Ability of Blender and GPT-3 in Educational Dialogues
Tack, Anaïs; Piech, Chris – International Educational Data Mining Society, 2022
How can we test whether state-of-the-art generative models, such as Blender and GPT-3, are good AI teachers, capable of replying to a student in an educational dialogue? Designing an AI teacher test is challenging: although evaluation methods are much-needed, there is no off-the-shelf solution to measuring pedagogical ability. This paper reports…
Descriptors: Artificial Intelligence, Dialogs (Language), Bayesian Statistics, Decision Making
Bárcena, M. J.; Garín, M. A.; Martín, A.; Tusell, F.; Unzueta, A. – Journal of Statistics Education, 2019
Teaching some concepts in statistics greatly benefits from individual practice with immediate feedback. In order to provide such practice to a large number of students we have written a simulator based on an historical event: the loss in May 22, 1968, and subsequent search for the nuclear submarine USS Scorpion. Students work on a simplified…
Descriptors: Computer Simulation, Computer Assisted Instruction, Teaching Methods, Bayesian Statistics
Andrade, Alejandro; Danish, Joshua A.; Maltese, Adam V. – Journal of Learning Analytics, 2017
Interactive learning environments with body-centric technologies lie at the intersection of the design of embodied learning activities and multimodal learning analytics. Sensing technologies can generate large amounts of fine-grained data automatically captured from student movements. Researchers can use these fine-grained data to create a…
Descriptors: Measurement, Interaction, Models, Educational Environment
Ruggeri, Azzurra; Lombrozo, Tania; Griffiths, Thomas L.; Xu, Fei – Developmental Psychology, 2016
Children are active learners: they learn not only from the information people offer and the evidence they happen to observe, but by actively seeking information. However, children's information search strategies are typically less efficient than those of adults. In two studies, we isolate potential sources of developmental change in how children…
Descriptors: Information Seeking, Search Strategies, Cognitive Style, Cognitive Structures
Jin, Kuan-Yu; Wang, Wen-Chung – Educational and Psychological Measurement, 2014
Extreme response style (ERS) is a systematic tendency for a person to endorse extreme options (e.g., strongly disagree, strongly agree) on Likert-type or rating-scale items. In this study, we develop a new class of item response theory (IRT) models to account for ERS so that the target latent trait is free from the response style and the tendency…
Descriptors: Item Response Theory, Research Methodology, Bayesian Statistics, Response Style (Tests)
Koenig, Alan D.; Lee, John J.; Iseli, Markus; Wainess, Richard – National Center for Research on Evaluation, Standards, and Student Testing (CRESST), 2010
The military's need for high-fidelity games and simulations is substantial, as these environments can be valuable for demonstration of essential knowledge, skills, and abilities required in complex tasks. However assessing performance in these settings can be difficult--particularly in non-linear simulations where more than one pathway to success…
Descriptors: Military Training, Fire Protection, Computers, Games
Hershkovitz, Arnon; Baker, Ryan S. J. d.; Gobert, Janice; Wixon, Michael; Sao Pedro, Michael – Grantee Submission, 2013
In recent years, an increasing number of analyses in Learning Analytics and Educational Data Mining (EDM) have adopted a "Discovery with Models" approach, where an existing model is used as a key component in a new EDM/analytics analysis. This article presents a theoretical discussion on the emergence of discovery with models, its…
Descriptors: Learning Analytics, Models, Learning Processes, Case Studies
Iseli, Markus R.; Koenig, Alan D.; Lee, John J.; Wainess, Richard – National Center for Research on Evaluation, Standards, and Student Testing (CRESST), 2010
Assessment of complex task performance is crucial to evaluating personnel in critical job functions such as Navy damage control operations aboard ships. Games and simulations can be instrumental in this process, as they can present a broad range of complex scenarios without involving harm to people or property. However, "automatic"…
Descriptors: Performance Tests, Performance Based Assessment, Decision Making Skills, Military Training
Fidalgo, Angel M.; Hashimoto, Kanako; Bartram, Dave; Muniz, Jose – Journal of Experimental Education, 2007
In this study, the authors assess several strategies created on the basis of the Mantel-Haenszel (MH) procedure for conducting differential item functioning (DIF) analysis with small samples. One of the analytical strategies is a loss function (LF) that uses empirical Bayes Mantel-Haenszel estimators, whereas the other strategies use the classical…
Descriptors: Bayesian Statistics, Test Bias, Statistical Analysis, Sample Size
PDF pending restorationGreen, Bert F. – 2002
Maximum likelihood and Bayesian estimates of proficiency, typically used in adaptive testing, use item weights that depend on test taker proficiency to estimate test taker proficiency. In this study, several methods were explored through computer simulation using fixed item weights, which depend mainly on the items difficulty. The simpler scores…
Descriptors: Adaptive Testing, Bayesian Statistics, Computer Assisted Testing, Computer Simulation
Shute, Valerie J.; Ventura, Matthew; Bauer, Malcolm; Zapata-Rivera, Diego – ETS Research Report Series, 2008
To reveal what is being learned during the gaming experience, this report proposes an approach for embedding assessments in immersive games, drawing on recent advances in assessment design. Key to this approach are formative assessment to guide instructional experiences and evidence-centered design to systematically analyze the assessment argument…
Descriptors: Educational Games, Formative Evaluation, Instructional Design, Evidence Based Practice
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