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Heo, Gyun – Computers & Education, 2013
The purpose of the present study was to identify latent classes resting on early adolescents' change trajectory patterns in using computers and the Internet for learning and to test the effects of gender, self-control, self-esteem, and game use in South Korea. Latent growth mixture modeling (LGMM) was used to identify subpopulations in the Korea…
Descriptors: Early Adolescents, Computer Use, Internet, Learning
Greene, Jeffrey A.; Moos, Daniel C.; Azevedo, Roger – New Directions for Teaching and Learning, 2011
Self-regulated learning (SRL) skills are enacted dynamically over the course of learning tasks, and the frequency and quality of their use can fluctuate dramatically. Further, students' SRL skills can vary from one academic domain to another and even from one task to another within a single domain. Thus, while SRL skills are essential for…
Descriptors: Computer Assisted Instruction, Self Control, Self Efficacy, Learning
Vidal-Abarca, Eduardo; Mana, Amelia; Gil, Laura – Journal of Educational Psychology, 2010
The goal of this study is to analyze the self-regulation processes present in task-oriented reading activities. In the 1st experiment, we examined the following self-regulation processes in the context of answering questions about an available text: (a) monitoring the comprehension of the question, (b) self-regulating the search process, and (c)…
Descriptors: Comprehension, Metacognition, Grade 8, Task Analysis
Calero, Maria Dolores; Garcia-Martin, Maria Belen; Jimenez, Maria Isabel; Kazen, Miguel; Araque, Arsenio – Learning and Individual Differences, 2007
Current approaches in intelligence research indicate the need for a more extensive determination of characteristics of children with possible giftedness, not only at an intellectual level, but also at the level of self-regulation and motivation. The present study compares self-regulation efficiency between high-IQ and average-ability children aged…
Descriptors: Gifted, Intelligence Quotient, Motivation, Memory
Moseley, David; Baumfield, Viv; Higgins, Steve; Lin, Mei; Miller, Jen; Newton, Doug; Robson, Sue; Elliott, Joe; Gregson, Maggie – Learning and Skills Development Agency (NJ1), 2004
In this report, the authors aim to review and advance knowledge of systematic ways of classifying thinking skills. They concentrate on taxonomies and theory-based frameworks, in the belief that studying and using them will promote better understanding of how people think and learn at the age of 16 or above. Their overarching interest is in how…
Descriptors: Thinking Skills, Learning, Classification, Postsecondary Education