NotesFAQContact Us
Collection
Advanced
Search Tips
Audience
Laws, Policies, & Programs
Assessments and Surveys
Wechsler Intelligence Scale…1
What Works Clearinghouse Rating
Showing all 10 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Kok, Ellen; Hormann, Olle; Rou, Jeroen; Saase, Evi; der Schaaf, Marieke; Kester, Liesbeth; Gog, Tamara – Journal of Computer Assisted Learning, 2022
Background: Performance monitoring plays a key role in self-regulated learning, but is difficult, especially for complex visual tasks such as navigational map reading. Gaze displays (i.e. visualizations of participants' eye movements during a task) might serve as feedback to improve students' performance monitoring. Objectives: We hypothesized…
Descriptors: Metacognition, Eye Movements, Task Analysis, Visualization
Peer reviewed Peer reviewed
Direct linkDirect link
Warren, Aaron R. – Physical Review Physics Education Research, 2020
The evaluation of hypotheses, and the ability to learn from critical reflection on experimental and theoretical tests of those hypotheses, is central to an authentic practice of physics. A large part of physics education therefore seeks to help students understand the significance of this kind of reflective practice and to develop the strategies…
Descriptors: Epistemology, Bayesian Statistics, Physics, Science Instruction
Peer reviewed Peer reviewed
Direct linkDirect link
Foster, Colin – Educational Studies in Mathematics, 2018
Achieving fluency in important mathematical procedures is fundamental to students' mathematical development. The usual way to develop procedural fluency is to practise repetitive exercises, but is this the only effective way? This paper reports three quasi-experimental studies carried out in a total of 11 secondary schools involving altogether 528…
Descriptors: Mathematics Achievement, Mathematics Instruction, Comparative Analysis, Quasiexperimental Design
Peer reviewed Peer reviewed
PDF on ERIC Download full text
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
Peer reviewed Peer reviewed
Direct linkDirect link
Zhang, Dake; Stecker, Pamela; Huckabee, Sloan; Miller, Rhonda – Journal of Learning Disabilities, 2016
Research has suggested that different strategies used when solving fraction problems are highly correlated with students' problem-solving accuracy. This study (a) utilized latent profile modeling to classify students into three different strategic developmental levels in solving fraction comparison problems and (b) accordingly provided…
Descriptors: Middle School Students, Fractions, Mathematics Achievement, Low Achievement
Peer reviewed Peer reviewed
Direct linkDirect link
van Viersen, Sietske; de Bree, Elise H.; Kalee, Lilian; Kroesbergen, Evelyn H.; de Jong, Peter F. – Reading and Writing: An Interdisciplinary Journal, 2017
A few studies suggest that gifted children with dyslexia have better literacy skills than averagely intelligent children with dyslexia. This finding aligns with the hypothesis that giftedness-related factors provide compensation for poor reading. The present study investigated whether, as in the native language (NL), the level of foreign language…
Descriptors: Foreign Countries, Second Language Learning, Reading Instruction, Spelling Instruction
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Liu, Ran; Koedinger, Kenneth R. K – International Educational Data Mining Society, 2017
Research in Educational Data Mining could benefit from greater efforts to ensure that models yield reliable, valid, and interpretable parameter estimates. These efforts have especially been lacking for individualized student-parameter models. We collected two datasets from a sizable student population with excellent "depth" -- that is,…
Descriptors: Data Analysis, Intelligent Tutoring Systems, Bayesian Statistics, Pretests Posttests
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Aslan, Burak Galip; Öztürk, Özlem; Inceoglu, Mustafa Murat – Educational Sciences: Theory and Practice, 2014
Considering the increasing importance of adaptive approaches in CALL systems, this study implemented a machine learning based student modeling middleware with Bayesian networks. The profiling approach of the student modeling system is based on Felder and Silverman's Learning Styles Model and Felder and Soloman's Index of Learning Styles…
Descriptors: Foreign Countries, Undergraduate Students, Graduate Students, Cognitive Style
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Kosek, Michal; Lison, Pierre – Research-publishing.net, 2014
We present an intelligent tutoring system that lets students of Chinese learn words and grammatical constructions. It relies on a Bayesian, linguistically motivated cognitive model that represents the learner's knowledge. This model is dynamically updated given observations about the learner's behaviour in the exercises, and employed at runtime to…
Descriptors: Intelligent Tutoring Systems, Grammar, Bayesian Statistics, Second Language Learning
Peer reviewed Peer reviewed
Direct linkDirect link
Pardos, Zachary A.; Dailey, Matthew D.; Heffernan, Neil T. – International Journal of Artificial Intelligence in Education, 2011
The well established, gold standard approach to finding out what works in education research is to run a randomized controlled trial (RCT) using a standard pre-test and post-test design. RCTs have been used in the intelligent tutoring community for decades to determine which questions and tutorial feedback work best. Practically speaking, however,…
Descriptors: Feedback (Response), Intelligent Tutoring Systems, Pretests Posttests, Educational Research