NotesFAQContact Us
Collection
Advanced
Search Tips
Showing all 4 results Save | Export
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Akalin, Tevfik Cem; Gümüs, Mustafa – African Educational Research Journal, 2020
The purpose of this study is to investigate whether the time spent on viewing television and using computer is associated with overweight and obesity among 11- to 14-y-old Turkish secondary school students'. This study was carried out in 5th, 6th and 7th grades of two secondary schools in Zonguldak province in 2016. A total of 476 students, 52.3%…
Descriptors: Obesity, Body Weight, Secondary School Students, Predictor Variables
Peer reviewed Peer reviewed
Direct linkDirect link
Hughes, Joan E.; Read, Michelle F.; Jones, Sara; Mahometa, Michael – Journal of Research on Technology in Education, 2015
This study used multiple regression to identify predictors of middle school students' Web 2.0 activities out of school, a construct composed of 15 technology activities. Three middle schools participated, where sixth- and seventh-grade students completed a questionnaire. Independent predictor variables included three demographic and five computer…
Descriptors: Multiple Regression Analysis, Predictor Variables, Middle School Students, Web 2.0 Technologies
Peer reviewed Peer reviewed
Direct linkDirect link
Su, Addison Y. S.; Huang, Chester S. J.; Yang, Stephen J. H.; Ding, T. J.; Hsieh, Y. Z. – Educational Technology & Society, 2015
In Taiwan elementary schools, Scratch programming has been taught for more than four years. Previous studies have shown that personal annotations is a useful learning method that improve learning performance. An annotation-based Scratch programming (ASP) system provides for the creation, share, and review of annotations and homework solutions in…
Descriptors: Foreign Countries, Elementary School Students, Grade 6, Programming
Peer reviewed Peer reviewed
Direct linkDirect link
Baker, Ryan S. J. D.; Goldstein, Adam B.; Heffernan, Neil T. – International Journal of Artificial Intelligence in Education, 2011
Intelligent tutors have become increasingly accurate at detecting whether a student knows a skill, or knowledge component (KC), at a given time. However, current student models do not tell us exactly at which point a KC is learned. In this paper, we present a machine-learned model that assesses the probability that a student learned a KC at a…
Descriptors: Intelligent Tutoring Systems, Mastery Learning, Probability, Knowledge Level