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Guinibert, Matthew – Australasian Journal of Educational Technology, 2020
Based on the presupposition that visual literacy skills are not usually learned unaided by osmosis, but require targeted learning support, this article explores how everyday encounters with visuals can be leveraged as contingent learning opportunities. The author proposes that a learner's environment can become a visual learning space if…
Descriptors: Visual Literacy, Telecommunications, Handheld Devices, Informal Education
Milan, Lara; Reis, Sally M.; Zanetti, Maria Assunta; Renzulli, Joseph S. – International Journal for Talent Development and Creativity, 2019
This article describes current attempts and steps to expand both services and research about gifted education and talent development programs and educational opportunities for academically talented students in Italy. The laws, procedures, and policies that have been essential to this process are described, as is the outcome, which is the…
Descriptors: Foreign Countries, Comparative Education, Gifted Education, Academically Gifted
Long, Lye Chan; Erwin, Adrienne – Gifted Education International, 2020
IGNITE, a high school-based programme, was developed for high ability underachievers using the Achievement Orientation Model (AOM), Maker Model, and Bibliotherapy in a mainstream setting. This paper reports on the effects discovered while implementing the programme over the course of 2 years. Year 7 (13 year olds) and Year 9 (15 year olds)…
Descriptors: Underachievement, Academically Gifted, High School Students, Program Effectiveness
Jevsikova, Tatjana; Berniukevicius, Andrius; Kurilovas, Eugenijus – Informatics in Education, 2017
The paper is aimed to present a methodology of learning personalisation based on applying Resource Description Framework (RDF) standard model. Research results are two-fold: first, the results of systematic literature review on Linked Data, RDF "subject-predicate-object" triples, and Web Ontology Language (OWL) application in education…
Descriptors: Metadata, Individualized Instruction, Models, Cognitive Style
Mao, Ye; Marwan, Samiha; Price, Thomas W.; Barnes, Tiffany; Chi, Min – International Educational Data Mining Society, 2020
Modeling student learning processes is highly complex since it is influenced by many factors such as motivation and learning habits. The high volume of features and tools provided by computer-based learning environments confounds the task of tracking student knowledge even further. Deep Learning models such as Long-Short Term Memory (LSTMs) and…
Descriptors: Time, Models, Artificial Intelligence, Bayesian Statistics
Li, Fengying; He, Yifeng; Xue, Qingshui – Educational Technology & Society, 2021
With the deep application of artificial intelligence and big data in education, adaptive learning has become a new research hotspot in online education. Based on the systematic review of the connotation and research progress of adaptive learning, a new definition of adaptive learning is given. By literature analysis, this paper points out the…
Descriptors: Educational Technology, Artificial Intelligence, Student Needs, Individualized Instruction
Black, Alison; Lawson, Hazel; Norwich, Brahm – Journal of Research in Special Educational Needs, 2019
This study investigates how three secondary subject teachers think about and take account of learner diversity in their lesson planning, enactment and reviewing, with a specific focus on pupils designated as having special educational needs (SEN). The study is significant in the context of international moves in contemporary school teaching…
Descriptors: Secondary School Teachers, Teacher Attitudes, Lesson Plans, Student Diversity
Jennifer L. Kassimer – ProQuest LLC, 2022
Using a learning management system (LMS) to deliver robust content for K-12 students became an essential part of the discussion of technology's place in K-12 education when teachers were forced to teach online at the start of the COVID-19 pandemic. Teachers used an LMS to deliver content in various ways and as part of different instructional…
Descriptors: Coaching (Performance), Models, Active Learning, Educational Environment
Buch, Bettina; Christiansen, Rene B.; Hansen, Dorrit; Petersen, Anne Kristine; Sørensen, Randi Skovbjerg – Universal Journal of Educational Research, 2018
Designing teaching in an era of educational technology calls for new models for designing learning opportunities. The 7Cs framework developed by Professor Gráinne Conole and her colleagues provides a tool for discussing learning designs for online learning environments. In this paper, we introduce the 7Cs framework put forward by Conole and…
Descriptors: Online Courses, Blended Learning, Educational Technology, Individualized Instruction
Pieniazkiewicz, Amy A. – ProQuest LLC, 2018
This Appreciative Inquiry (AI) study was conducted to create the framework for the Differentiated Support Model (DSM). The DSM is a framework of individualized support for first year teachers that can be applied in any school district alongside a mentoring program or without a mentoring program. The DSM was designed to be implemented by an…
Descriptors: Individualized Instruction, Beginning Teachers, Elementary School Teachers, Models
Pardo, Abelardo; Bartimote-Aufflick, Kathryn; Shum, Simon Buckingham; Dawson, Shane; Gao, Jing; Gaševic, Dragan; Leichtweis, Steve; Liu, Danny; Martínez-Maldonado, Roberto; Mirriahi, Negin; Moskal, Adon Christian Michael; Schulte, Jurgen; Siemens, George; Vigentini, Lorenzo – Journal of Learning Analytics, 2018
The learning analytics community has matured significantly over the past few years as a middle space where technology and pedagogy combine to support learning experiences. To continue to grow and connect these perspectives, research needs to move beyond the level of basic support actions. This means exploring the use of data to prove richer forms…
Descriptors: Individualized Instruction, Data Analysis, Learning, Feedback (Response)
Hook, Pam – set: Research Information for Teachers, 2018
In Q&A Pam Hook reflects on what drew her to SOLO taxonomy and why she is so motivated to develop its classroom-based use to enhance student learning. She explains what SOLO is and how it can help students to articulate their learning outcomes, understand the learning process, and set new learning goals over time. I also asked her to highlight…
Descriptors: Foreign Countries, Taxonomy, Outcomes of Education, Student Evaluation
Balwant, Paul Tristen; Doon, Roshnie – International Journal of Educational Technology in Higher Education, 2021
In higher education, one commonly used teaching approach that is intended to develop deep learning is that of the 'Oxford' tutorial--a personalized Socratic approach in which an instructor discusses course-related issues with a handful of students. Even though this conventional tutorial model is well supported in the literature, it may be…
Descriptors: Tutoring, Tutors, Teaching Methods, Questioning Techniques
Ottenbreit-Leftwich, Anne; Liao, Yin-Chan; Karlin, Michael; Lu, Ya-Huei; Ding, Ai-Chu Elisha; Guo, Meize – Journal of Digital Learning in Teacher Education, 2020
This multiple case study describes a year-long implementation of a research-based coaching model designed to support changes in elementary teachers' technology integration practices. We examined coaches' perceptions of the model through the use of coaches' questionnaires, reflection notes, and meeting notes. Teachers' coaching experiences were…
Descriptors: Coaching (Performance), Faculty Development, Elementary School Teachers, Evidence Based Practice
Wang, Jack Z.; Lan, Andrew S.; Grimaldi, Phillip J.; Baraniuk, Richard G. – International Educational Data Mining Society, 2017
Existing personalized learning systems (PLSs) have primarily focused on providing learning analytics using data from learners. In this paper, we extend the capability of current PLSs by incorporating data from instructors. We propose a latent factor model that analyzes instructors' preferences in explicitly "excluding" particular…
Descriptors: Item Response Theory, Individualized Instruction, Prediction, Models

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