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Seongyune Choi; Hyeoncheol Kim – Education and Information Technologies, 2025
Attention to programming education from K-12 to higher education has been growing with the aim of fostering students' programming ability. This ability involves employing appropriate algorithms and computer codes to solve problems and can be enhanced through practical learning. However, in a formal educational setting, it is challenging to provide…
Descriptors: Foreign Countries, High School Freshmen, Programming, Artificial Intelligence
Zayet, Tasnim M. A.; Ismail, Maizatul Akmar; Almadi, Sara H. S.; Zawia, Jamallah Mohammed Hussein; Mohamad Nor, Azmawaty – Education and Information Technologies, 2023
Online learning has significantly expanded along with the spread of the coronavirus disease (COVID-19). Personalization becomes an essential component of learning systems due to students' different learning styles and abilities. Recommending materials that meet the needs and are tailored to learners' styles and abilities is necessary to ensure a…
Descriptors: Electronic Learning, Individualized Instruction, Artificial Intelligence, Cognitive Style
Shelby L. Short – ProQuest LLC, 2024
This action research investigates the perceptions of teachers regarding the supports provided by instructional coaches within the context of Dan Alko Middle School. Recognizing that effective instructional coaching is crucial for teacher development, the study explores the challenges coaches face, including teacher resistance to change, scheduling…
Descriptors: Middle School Teachers, Teacher Attitudes, Coaching (Performance), Barriers
Li, Xiaoyu; Xia, Jianping – Science Insights Education Frontiers, 2020
The rise of big data technology provides direction and support for the reform and development of education. Big data technology can realize the inventory management and effective dynamic monitoring of schools, students, and teachers. It is conducive to comprehensively and accurately controlling the development of teaching activities, injecting new…
Descriptors: Foreign Countries, Middle School Students, Data Analysis, Data Collection
Michele Haiken – National Council of Teachers of English, 2024
Unlock the power of personalized reading with practical strategies and easy-to-use ideas to engage students in the digital age. In the first edition of this book, the authors identified ways for working with four different types of readers--struggling readers, reluctant readers, English learners, and advanced readers--using technology to…
Descriptors: Reading Instruction, Individualized Instruction, Electronic Learning, Teaching Methods
Hariyanto, Didik; Triyono, Moch. Bruri; Köhler, Thomas – Knowledge Management & E-Learning, 2020
One of the advanced technologies in e-learning deals with the systems' ability to fit the students' preferences. It emerged based upon the common conception that every person has different learning style. However, despite the many options of learning style models toward using personalized elearning, there are considerable challenges to assess the…
Descriptors: Usability, Electronic Learning, Individualized Instruction, Computer Assisted Instruction
Wouters, Pieter; van der Meulen, Esmee S. – International Journal of Game-Based Learning, 2020
Adapting learning to the level and preferences of learners and game-based learning have increasingly received much attention. The current study examined whether learning styles based on the Felder-Silverman classification (perception, input, processing and organization of information) influence learning in GBL. Only the input and processing scales…
Descriptors: Cognitive Style, Educational Games, Preferences, Mathematics Education
Zulfiani Zulfiani; Iwan Permana Suwarna; Sujiyo Miranto – Journal of Baltic Science Education, 2018
Students with their different learning styles also have their own different learning approaches, and teachers cannot simultaneously facilitate them all. Teachers' limitation in serving all students' learning styles can be anticipated by the use of computer-based instructions. This research aims to develop ScEd-Adaptive Learning System (ScEd-ASL)…
Descriptors: Science Instruction, Cognitive Style, Intelligent Tutoring Systems, Teaching Methods
Smith, Kasee L.; Rayfield, John – Journal of Agricultural Education, 2019
Career and technical education (CTE) courses, including agricultural education courses, are home to a disproportionately large number of students with learning disabilities. Agricultural education has been sought as a potential solution to teaching abstract STEM concepts through experiential learning methods. Abstract concepts are noted in the…
Descriptors: STEM Education, Learning Disabilities, Experiential Learning, Learning Strategies
Kearney, Randi; Patterson, Katelyn; Wyner, Tressa – Childhood Education, 2019
Some of the most effective innovations in education have allowed fundamental changes to how individual students are being taught and assessed. Personalized learning models tailor learning to individual needs, accommodating students with diverse learning styles.
Descriptors: Self Efficacy, Educational Innovation, Emotional Development, Social Development
Mudrák, Marián – ICTE Journal, 2018
The paper deals with the issue of e-courses personalization in selected LMS. Even though this topic has been the subject of research for a longer time, more effective concepts of learning through e-courses are still being sought. Part of the contribution is a brief explanation of the terms personalization and adaptivity, which are often mistaken…
Descriptors: Individualized Instruction, Online Courses, Electronic Learning, Curriculum Implementation
Doubet, Kristina J.; Hockett, Jessica A. – ASCD, 2015
In this one-stop resource for middle and high school teachers, Kristina J. Doubet and Jessica A. Hockett explore how to use differentiated instruction to help students be more successful learners--regardless of background, native language, learning style, motivation, or school savvy. They explain how to: (1) create a healthy classroom community in…
Descriptors: Individualized Instruction, Cognitive Style, Secondary Education, Sense of Community
Siddique, Ansar; Durrani, Qaiser S.; Naqvi, Husnain A. – Journal of Educational Computing Research, 2019
The falling learning outcome is one of the major challenges faced by most of the educational systems. Adaptive educational systems (AESs) are viewed as catalyst to reinforce learning. Several AESs have been developed considering only single aspect of learners, for example, learning styles. The impact of learning style-based AESs in terms of…
Descriptors: Electronic Learning, Individualized Instruction, Cognitive Style, Prior Learning
Maeng, Jennifer L. – Research in Science Education, 2017
This qualitative investigation explored the beliefs and practices of one secondary science teacher, Diane, who differentiated instruction and studied how technology facilitated her differentiation. Diane was selected based on the results of a previous study, in which data indicated that Diane understood how to design and implement proactively…
Descriptors: Technology Uses in Education, Individualized Instruction, Science Instruction, Secondary School Science
Drinkwine, Timothy – ProQuest LLC, 2013
This research study considers the status of middle school students in the 21st century in terms of their tendency to multitask in their daily lives and the overall influence this multitasking has on teaching and learning environments. Student engagement in the learning environment and students' various learning styles are discussed as primary…
Descriptors: Middle School Students, Time Management, Cognitive Style, Learner Engagement
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