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Michael Agyemang Adarkwah; Samuel Anokye Badu; Evans Appiah Osei; Enoch Adu-Gyamfi; Jonathan Odame; Käthe Schneider – Discover Education, 2025
The advancement of artificial intelligence (AI) tools has revolutionized teaching and learning, particularly in healthcare education, where they enhance pedagogy, foster immersive learning, and support healthcare provision. However, their use in healthcare education is contentious, warranting careful examination, especially regarding Generative AI…
Descriptors: Artificial Intelligence, Health Services, Medical Education, Technological Advancement
Sérgio Gaitas; T. Sarabando; C. Alves; M. Alves Martins; G. Leite; R. Laranjeira – European Journal of Special Needs Education, 2025
This study investigates how regular teachers support the inclusion of students with special educational needs in heterogeneous classrooms, focusing on instructional arrangements for fostering both social and academic inclusion. Conducted as two descriptive case studies in primary school classrooms, the research involved classroom observations and…
Descriptors: Inclusion, Students with Disabilities, Student Needs, Regular and Special Education Relationship
Shantanu Tilak; Mindy Gumpert; Taryn A. Myers – Education and Information Technologies, 2025
This mixed methods study investigates whether technology mediated collaborative practices during a professional development (PD) session led to growth in the collective efficacy of 21 special education teachers at an independent 1-12 school in Southeastern Virginia. This school specializes in individualized instruction for students with learning…
Descriptors: Cooperative Learning, Faculty Development, Computer Mediated Communication, Educational Technology
Paul W. Cascella – Teaching and Learning in Communication Sciences & Disorders, 2025
This paper highlights the utility of personalized learning (PL) embedded into an on-campus graduate seminar focused on pediatric speech sound disorders (PSSD). The example showcases six key PL features described from an autoethnographic lens. These include: (a) context-specific positionality viewpoints (i.e., instructor, student, discipline, and…
Descriptors: Individualized Instruction, Graduate Study, Seminars, Allied Health Occupations Education
Sheejamol P. T.; Anu Mary Chacko; S. D. Madhu Kumar – Electronic Journal of e-Learning, 2025
Traditional education, characterized by rigid curricula and inflexible teaching methods, often fails to accommodate the diverse cognitive profiles of neurodivergent learners, including those with Autism Spectrum Disorder (ASD), Attention Deficit Hyperactivity Disorder (ADHD), and dyslexia. Although e-Learning has introduced greater flexibility and…
Descriptors: Individualized Instruction, Gamification, Electronic Learning, Students with Disabilities
Youssef Baba Khouya, Editor; Abderrahmane Ismaili Alaoui, Editor – IGI Global, 2025
The application of artificial intelligence (AI) in the teaching and learning of English as a Foreign Language (EFL) transforms traditional educational practices by offering more personalized, efficient, and interactive learning experiences. AI-powered tools enable learners to receive instant feedback, engage in conversational practice, and tailor…
Descriptors: Artificial Intelligence, Educational Technology, Technology Uses in Education, English (Second Language)
Yolanda Muñoz Martínez; Ignacio Figueroa Céspedes; Susana Domínguez Santos – Education, Citizenship and Social Justice, 2025
The article explores the essential attributes required for primary education teachers to promote inclusion and social justice. This study aims to identify and analyze the teaching attributes perceived as essential by student teachers in primary education. Employing a qualitative approach grounded in Participatory Action Learning and Action…
Descriptors: Elementary Education, Student Teachers, Teacher Characteristics, Student Teacher Attitudes
Li Wang; Jianchun Dai – European Journal of Education, 2025
As artificial intelligence (AI) technologies become increasingly embedded in language education, it is essential to move beyond perception-based research and examine teachers' actual experiences with AI integration. Drawing on Expectancy Value Theory (EVT), this qualitative study explores how Chinese EFL teachers have engaged with AI tools in…
Descriptors: Foreign Countries, Language Teachers, Second Language Instruction, English (Second Language)
Papamitsiou, Zacharoula; Pappas, Ilias O.; Sharma, Kshitij; Giannakos, Michail N. – IEEE Transactions on Learning Technologies, 2020
Investigating and explaining the patterns of learners' engagement in adaptive learning conditions is a core issue towards improving the quality of personalized learning services. This article collects learner data from multiple sources during an adaptive learning activity, and employs a fuzzy set qualitative comparative analysis (fsQCA) approach…
Descriptors: Undergraduate Students, Individualized Instruction, Learner Engagement, Reaction Time
Martinetti, Alberto – Education Sciences, 2020
Our ever-changing and developing society constantly requires professions that did not exist 20 years ago. Students have to become professionals capable of steering their own career development and controlling their own learning process, at university and in their future profession. In order to reach these goals, lecturers have to understand the…
Descriptors: Individualized Instruction, Masters Programs, Graduate Students, Foreign Countries
Karaoglan Yilmaz, Fatma Gizem; Yilmaz, Ramazan – Technology, Knowledge and Learning, 2020
There is a growing interest in the use of learning analytics in higher education institutions. Learning analytics also appear to have the potential to be used to provide personalized feedback and support in online learning. However, when the literature is examined, the use of learning analytics for this purpose appears as a gap to be investigated.…
Descriptors: Student Attitudes, Individualized Instruction, Electronic Learning, Feedback (Response)
Ghallabi, Sameh; Essalmi, Fathi; Jemni, Mohamed; Kinshuk – Education and Information Technologies, 2020
With the emergence of technology, the personalization of e-learning systems is enhanced. These systems use a set of parameters for personalizing courses. However, in literature, these parameters are not based on classification and optimization algorithms to implement them in the cloud. Cloud computing is a new model of computing where standard and…
Descriptors: Electronic Learning, Internet, Information Storage, Models
Slanda, Dena D.; Little, Mary E. – SRATE Journal, 2020
The Every Student Succeeds Act (2015) requires teachers to address students' diverse learning needs to master increasingly rigorous state standards within a Multi-Tier System of Supports (MTSS). To actualize equitable learning opportunities, it is critical teachers be equipped with the knowledge and skills to provide individualized, specially…
Descriptors: Teacher Education Programs, Inclusion, Equal Education, Teacher Competencies
Stevens-Smith, Deborah A. – Journal of Physical Education, Recreation & Dance, 2020
The purpose of this article is to examine the brain-based differentiations between the genders and the impact they may have on teaching and learning. The term gender will be used throughout the article to highlight the characteristics that distinguish males and females. The article will first examine if these differences do exist and how they…
Descriptors: Gender Differences, Brain, Physical Education, Individualized Instruction
Dennis, Minyi Shih; Gratton-Fisher, Emma – Learning Disabilities Research & Practice, 2020
Secondary students with persistent mathematics difficulties need the most intensive intervention in order to improve their mathematics outcomes. One approach to intensifying and individualizing intervention is through data-based individualization (DBI). The present study used a single-subject, multiple-baseline-across-participants,…
Descriptors: High School Students, Mathematics Skills, Computation, Mathematical Concepts

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