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Tian Li; Gaomin Sun; Xinlin Zhou; Tengfei Wang – Educational Psychology, 2023
The close relationship between working memory and maths problem solving is generally accepted, but the specifics of how working memory and its subcomponents contribute to maths problem solving remain poorly understood. Tests of working memory, maths problem problem solving, calculation, and intelligence were administered to 246 university…
Descriptors: Mathematics, Short Term Memory, Problem Solving, Computation
Korchi, Adil; Dardor, Mohamed; Mabrouk, El Houssine – Education and Information Technologies, 2020
Learning techniques have proven their capacity to treat large amount of data. Most statistical learning approaches use specific size learning sets and create static models. Withal, in certain some situations such as incremental or active learning the learning process can work with only a smal amount of data. In this case, the search for algorithms…
Descriptors: Learning Analytics, Data, Computation, Mathematics
Tadayon, Manie; Pottie, Gregory J. – IEEE Transactions on Education, 2020
Contributions: Prior studies on education have mostly followed the model of the cross-sectional study, namely, examining the pretest and the posttest scores. This article shows that students' knowledge throughout the intervention can be estimated by time-series analysis using a hidden Markov model (HMM). Background: Analyzing time series and the…
Descriptors: Prediction, Performance, Educational Games, Markov Processes
Suciawati, Vici; Jatisunda, Mohamad Gilar; Kania, Nia – Malikussaleh Journal of Mathematics Learning, 2021
Intuition is the first way humans get knowledge. A worker in making a traditional West Java house works using his experience to be able to determine how many building materials are needed to become a house. The roof of the house is one part that is quite complicated to determine the amount of wood needed. Workers using intuition based on…
Descriptors: Mathematical Concepts, Construction (Process), Construction Materials, Foreign Countries
Çakit, Erman; Dagdeviren, Metin – Education and Information Technologies, 2022
In recent years, there has been an increase in the demand for higher education in Turkey, where the demand, as in most other countries, exceeds what is available. The main purpose of this research is to develop machine learning algorithms for predicting the percentage of student placement based on the data related to the university's academic…
Descriptors: Student Placement, Foreign Countries, Artificial Intelligence, Mathematics
Young, Nicholas T.; Caballero, Marcos D. – Journal of Educational Data Mining, 2021
We encounter variables with little variation often in educational data mining (EDM) due to the demographics of higher education and the questions we ask. Yet, little work has examined how to analyze such data. Therefore, we conducted a simulation study using logistic regression, penalized regression, and random forest. We systematically varied the…
Descriptors: Prediction, Models, Learning Analytics, Mathematics
Ezz, Mohamed; Elshenawy, Ayman – Education and Information Technologies, 2020
Some of the educational organizations have multi-education paths such as engineering and medicine collages. In such colleges, the behavior of the student in the preparatory year determines which education path the student will join in the future. In this paper, an adaptive recommendation system is proposed for predicting a suitable education…
Descriptors: Educational Technology, Artificial Intelligence, Computation, Mathematics
Levin, Nathan A. – Journal of Educational Data Mining, 2021
The Big Data for Education Spoke of the NSF Northeast Big Data Innovation Hub and ETS co-sponsored an educational data mining competition in which contestants were asked to predict efficient time use on the NAEP 8th grade mathematics computer-based assessment, based on the log file of a student's actions on a prior portion of the assessment. In…
Descriptors: Learning Analytics, Data Collection, Competition, Prediction
Zhou, Jianing; Bhat, Suma – Grantee Submission, 2021
Consistency of learning behaviors is known to play an important role in learners' engagement in a course and impact their learning outcomes. Despite significant advances in the area of learning analytics (LA) in measuring various self-regulated learning behaviors, using LA to measure consistency of online course engagement patterns remains largely…
Descriptors: Models, Online Courses, Learner Engagement, Learning Processes
Mbaye, Baba – International Association for Development of the Information Society, 2018
The significant amount of information available on the web has led to difficulties for the learner to find useful information and relevant resources to carry out their training. The recommender systems have achieved significant success in the area of e-commerce, they still have difficulties in formulating relevant recommendations on e-learning…
Descriptors: Information Systems, Electronic Learning, Referral, Information Sources
Gardner, Josh; Brooks, Christopher – Journal of Learning Analytics, 2018
Model evaluation -- the process of making inferences about the performance of predictive models -- is a critical component of predictive modelling research in learning analytics. We survey the state of the practice with respect to model evaluation in learning analytics, which overwhelmingly uses only naïve methods for model evaluation or…
Descriptors: Prediction, Models, Evaluation, Evaluation Methods
Martori, Francesc; Cuadros, Jordi; González-Sabaté, Lucinio – International Educational Data Mining Society, 2015
Student modeling can help guide the behavior of a cognitive tutor system and provide insight to researchers on understanding how students learn. In this context, Bayesian Knowledge Tracing (BKT) is one of the most popular knowledge inference models due to its predictive accuracy, interpretability and ability to infer student knowledge. However,…
Descriptors: Bayesian Statistics, Inferences, Prediction, Accuracy
Abu-Hamour, Bashir – International Journal of Inclusive Education, 2018
The Cattell-Horn-Carroll (CHC) factors of the Woodcock-Johnson (WJ) Arabic Tests of Cognitive Abilities were studied with a group of students at risk of Math Disability (MD) (n50) and average students (n50) between second and fourth grades. Specifically, several statistical analyses were conducted using the seven CHC factors identified by the WJ…
Descriptors: Foreign Countries, Culture Fair Tests, Intelligence Tests, Cognitive Ability
Lan, Liang – ProQuest LLC, 2012
In my dissertation, I will present my research which contributes to solve the following three open problems from biomedical informatics: (1) Multi-task approaches for microarray classification; (2) Multi-label classification of gene and protein prediction from multi-source biological data; (3) Spatial scan for movement data. In microarray…
Descriptors: Data Collection, Mathematics, Computation, Classification
Stanton, Roger D.; Nosofsky, Robert M. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2013
Researchers have proposed that an explicit reasoning system is responsible for learning rule-based category structures and that a separate implicit, procedural-learning system is responsible for learning information-integration category structures. As evidence for this multiple-system hypothesis, researchers report a dissociation based on…
Descriptors: Classification, Psychological Studies, Learning Strategies, Cognitive Processes
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