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Bosch, Nigel; Paquette, Luc – Journal of Learning Analytics, 2018
Metrics including Cohen's kappa, precision, recall, and F[subscript 1] are common measures of performance for models of discrete student states, such as a student's affect or behaviour. This study examined discrete model metrics for previously published student model examples to identify situations where metrics provided differing perspectives on…
Descriptors: Models, Comparative Analysis, Prediction, Probability
Cohausz, Lea – Journal of Educational Data Mining, 2022
Student success and drop-out predictions have gained increased attention in recent years, connected to the hope that by identifying struggling students, it is possible to intervene and provide early help and design programs based on patterns discovered by the models. Though by now many models exist achieving remarkable accuracy-values, models…
Descriptors: Guidelines, Academic Achievement, Dropouts, Prediction
How, Meng-Leong; Hung, Wei Loong David – Education Sciences, 2019
Artificial intelligence-enabled adaptive learning systems (AI-ALS) are increasingly being deployed in education to enhance the learning needs of students. However, educational stakeholders are required by policy-makers to conduct an independent evaluation of the AI-ALS using a small sample size in a pilot study, before that AI-ALS can be approved…
Descriptors: Stakeholders, Artificial Intelligence, Bayesian Statistics, Probability
Kovalchik, Stephanie A.; Martino, Steven C.; Collins, Rebecca L.; Shadel, William G.; D'Amico, Elizabeth J.; Becker, Kirsten – Journal of Educational and Behavioral Statistics, 2018
Ecological momentary assessment (EMA) is a popular assessment method in psychology that aims to capture events, emotions, and cognitions in real time, usually repeatedly throughout the day. Because EMA typically involves more intensive monitoring than traditional assessment methods, missing data are commonly an issue and this missingness may bias…
Descriptors: Probability, Statistical Bias, Holistic Approach, Evaluation Methods
Briggs, Derek C.; Circi, Ruhan – International Journal of Testing, 2017
Artificial Neural Networks (ANNs) have been proposed as a promising approach for the classification of students into different levels of a psychological attribute hierarchy. Unfortunately, because such classifications typically rely upon internally produced item response patterns that have not been externally validated, the instability of ANN…
Descriptors: Artificial Intelligence, Classification, Student Evaluation, Tests
Ueno, Maomi; Miyazawa, Yoshimitsu – IEEE Transactions on Learning Technologies, 2018
Over the past few decades, many studies conducted in the field of learning science have described that scaffolding plays an important role in human learning. To scaffold a learner efficiently, a teacher should predict how much support a learner must have to complete tasks and then decide the optimal degree of assistance to support the learner's…
Descriptors: Scaffolding (Teaching Technique), Prediction, Probability, Comparative Analysis
Huang, Yun; González-Brenes, José P.; Kumar, Rohit; Brusilovsky, Peter – International Educational Data Mining Society, 2015
Latent variable models, such as the popular Knowledge Tracing method, are often used to enable adaptive tutoring systems to personalize education. However, finding optimal model parameters is usually a difficult non-convex optimization problem when considering latent variable models. Prior work has reported that latent variable models obtained…
Descriptors: Guidelines, Models, Prediction, Evaluation Methods
Porter, Kristin E.; Balu, Rekha – MDRC, 2016
Education systems are increasingly creating rich, longitudinal data sets with frequent, and even real-time, data updates of many student measures, including daily attendance, homework submissions, and exam scores. These data sets provide an opportunity for district and school staff members to move beyond an indicators-based approach and instead…
Descriptors: Models, Prediction, Statistical Analysis, Elementary Secondary Education
van der Ven, Sanne H. G.; Boom, Jan; Kroesbergen, Evelyn H.; Leseman, Paul P. M. – Journal of Experimental Child Psychology, 2012
Variability in strategy selection is an important characteristic of learning new skills such as mathematical skills. Strategies gradually come and go during this development. In 1996, Siegler described this phenomenon as ''overlapping waves.'' In the current microgenetic study, we attempted to model these overlapping waves statistically. In…
Descriptors: Short Term Memory, Probability, Learning Strategies, Investigations
Hsu, Anne S.; Chater, Nick; Vitanyi, Paul M. B. – Cognition, 2011
There is much debate over the degree to which language learning is governed by innate language-specific biases, or acquired through cognition-general principles. Here we examine the probabilistic language acquisition hypothesis on three levels: We outline a novel theoretical result showing that it is possible to learn the exact "generative model"…
Descriptors: Linguistics, Prediction, Natural Language Processing, Language Acquisition
Woolstenhulme, Jared Lynn – ProQuest LLC, 2013
Academic couples make up a significant portion of the academic labor market. Unlike other dual-career households, academic couples must not only find employment in the same region, but often in the same institution. Previous work has not considered how outcomes may be different when dual career households work for the same employer. In the first…
Descriptors: College Faculty, Spouses, Employed Parents, Teacher Selection
Denison, Stephanie; Xu, Fei – Developmental Science, 2010
Previous research has revealed that infants can reason correctly about single-event probabilities with small but not large set sizes (Bonatti, 2008; Teglas "et al.", 2007). The current study asks whether infants can make predictions regarding single-event probability with large set sizes using a novel procedure. Infants completed two trials: A…
Descriptors: Prediction, Infants, Probability, Preschool Children
Jaeger, T. Florian – Cognitive Psychology, 2010
A principle of efficient language production based on information theoretic considerations is proposed: Uniform Information Density predicts that language production is affected by a preference to distribute information uniformly across the linguistic signal. This prediction is tested against data from syntactic reduction. A single multilevel…
Descriptors: Speech, Syntax, Figurative Language, Probability
VanDerHeyden, Amanda M. – Exceptional Children, 2011
Perhaps the greatest value of response to intervention (RTI) as a decision framework is that it brings attention to variables (e.g., mastery of prerequisite skills, frequency of instructional corrective feedback, reinforcement schedules for correct responding) that if changed might make a meaningful difference for students (e.g., child rate of…
Descriptors: Feedback (Response), Intervention, Classification, Response to Intervention
Krishnamurthy, Janaki – ProQuest LLC, 2010
Given the increasing competition in the software industry and the critical consequences of software errors, it has become important for companies to achieve high levels of software quality. While cost reduction and timeliness of projects continue to be important measures, software companies are placing increasing attention on identifying the user…
Descriptors: Program Evaluation, Opinions, Privacy, Prediction
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