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Tom Porta; Nicole Todd; Lorraine Gaunt – British Educational Research Journal, 2024
Differentiated instruction (DI) is an educational praxis that is built on the premise that all students can be engaged in learning and achieve positive academic outcomes. Previous research in secondary schools has shown promise in the success of DI practices and outlines the importance of sustained professional development (PD) for teachers. There…
Descriptors: Foreign Countries, Individualized Instruction, Educational Policy, Teacher Attitudes
Guoqian Luo; Hengnian Gu; Xiaoxiao Dong; Dongdai Zhou – Education and Information Technologies, 2025
In the realm of e-learning, supporting personalized learning effectively necessitates recommending sequences of learning items that maximize learning efficiency while minimizing cognitive load, all tailored to the learner's goals. These recommendations must account for the prerequisite relationships among learning items and the learner's…
Descriptors: Electronic Learning, Individualized Instruction, Sequential Learning, Learning Processes
Ni Luh Vidary Wiakta Putri; Frieda Maryam Mangunsong – Elementary School Forum (Mimbar Sekolah Dasar), 2024
Differentiated Instruction (DI) is recognized as an effective method for addressing varied student learning needs within a single classroom. However, integrating DI into teaching practices remains a challenge for many teachers. This non-experimental study employs a quantitative comparative design to examine the understanding and implementation of…
Descriptors: Foreign Countries, Individualized Instruction, Elementary School Teachers, Teacher Competencies
Fariani, Rida Indah; Junus, Kasiyah; Santoso, Harry Budi – Technology, Knowledge and Learning, 2023
Personalised learning (PL) is learning in which the stage of learning and the instructional approach are optimised for the needs of each learner. The concept of PL allows e-learning design to shift from a 'one size fits all' approach to an adaptive and student-centred approach. This paper aims to provide a literature review of PL based on: the PL…
Descriptors: Literature Reviews, Individualized Instruction, College Students, Electronic Learning
Pedro Luis Saraiva Barbosa; Rafael Augusto Ferreira do Carmo; João P. P. Gomes; Windson Viana – Education and Information Technologies, 2024
Adaptive learning is a teaching approach aiming to personalize the learning experience for each student. In Computer Science Education (CSE), Adaptive Learning Systems (ALS) can provide students with customized lessons, exercises, and assessments based on their previous knowledge, strengths, and weaknesses. Some literature reviews focus on…
Descriptors: Teaching Methods, Individualized Instruction, Educational Technology, Technology Uses in Education
Yessingeldinov, Baurzhan T.; Ashirbayev, Nurgali K.; Zhumykbayeva, Akmaral K.; Sarsekenov, Rauan M.; Ismailova, Guldana M.; Bibekov, Kanysh ?. – Cypriot Journal of Educational Sciences, 2022
This article describes research on the use of a differentiated approach in assessing students' academic achievements during mathematics lessons. The study used theoretical and empirical research methods. In particular, normative documents and scholarly literature were reviewed, and in 2021, the study conducted a survey of online mathematics…
Descriptors: Knowledge Level, Individualized Instruction, Mathematics Instruction, Academic Achievement
Examining Teachers' Needs, Competencies, and Knowledge in Gifted Education for Professional Learning
Gülendam Akgül; Cemre Erten Tatli; Nazli B. Akçabozan Kayabol – Journal of Advanced Academics, 2025
The current knowledge and competence level of teachers concerning gifted education in Türkiye is not well-studied that may hinder the development of need-based planning of teacher training programs. The aim of this study is to explore teachers' needs, competencies, and level of perceived knowledge in gifted education. In a mixed methods study,…
Descriptors: Foreign Countries, Gifted Education, Teacher Competencies, Educational Needs
Lixiang Xu; Zhanlong Wang; Suojuan Zhang; Xin Yuan; Minjuan Wang; Enhong Chen – IEEE Transactions on Learning Technologies, 2024
Knowledge tracing (KT) is an intelligent educational technology used to model students' learning progress and mastery in adaptive learning environments for personalized education. Despite utilizing deep learning models in KT, current approaches often oversimplify students' exercise records into knowledge sequences, which fail to explore the rich…
Descriptors: Knowledge Level, Educational Technology, Intelligent Tutoring Systems, Individualized Instruction
Landon Kubicek – ProQuest LLC, 2024
Teachers are the backbone of our education system and are often overlooked sources of information within the education system itself. It's critical to find the most up-to-date teaching practices and combine those practices by gaining insight from these teachers to ensure student success. Today, in the modern United States education system,…
Descriptors: Student Diversity, Individualized Instruction, Student Needs, Course Content
Mohammed Estaiteyeh; Isha DeCoito – Teacher Educator, 2025
To promote inclusive practices in science, technology, engineering, and mathematics (STEM) classrooms, this research explores teacher candidates' (TCs') views and understandings of differentiated instruction (DI). The article addresses the following research questions: (1) What are intermediate-senior STEM TCs' initial views and understandings of…
Descriptors: STEM Education, Preservice Teachers, Student Attitudes, Individualized Instruction
Hao Zhou; Wenge Rong; Jianfei Zhang; Qing Sun; Yuanxin Ouyang; Zhang Xiong – IEEE Transactions on Learning Technologies, 2025
Knowledge tracing (KT) aims to predict students' future performances based on their former exercises and additional information in educational settings. KT has received significant attention since it facilitates personalized experiences in educational situations. Simultaneously, the autoregressive (AR) modeling on the sequence of former exercises…
Descriptors: Learning Experience, Academic Achievement, Data, Artificial Intelligence
Ma, Hua; Huang, Zhuoxuan; Tang, Wensheng; Zhu, Haibin; Zhang, Hongyu; Li, Jingze – IEEE Transactions on Learning Technologies, 2023
To provide intelligent learning guidance for students in e-learning systems, it is necessary to accurately predict their performance in future exams by analyzing score data in past exams. However, existing research has not addressed the uncertain and dynamic features of students' cognitive status, whereas these features are essential for improving…
Descriptors: Prediction, Student Evaluation, Performance, Tests
Anne Kultti – Early Child Development and Care, 2024
In this study, the notion of 'multilingual children' is differentiated by problematizing overgeneralizations or homogenizing of children with potentially different experiences of language(s). The aim is to generate knowledge of how minority language-speaking children use their language(s) outside the education system through teacher-parent…
Descriptors: Native Language, Multilingualism, Early Childhood Education, Individualized Instruction
Wisani Hlangwani; Zwelithini Bongani Dhlamini – International Journal of Learning and Change, 2024
This qualitative exploratory case study delves into learners' understanding of differentiation through the first principle and power rule. The study adopted the action, process, object, and schema (APOS) theory as a lens to track learners' understanding of these concepts using the activities, classroom discussion, and exercise (ACE) teaching…
Descriptors: High School Seniors, Grade 12, Student Attitudes, Knowledge Level
Doll, William J. – ProQuest LLC, 2022
The purpose of this study was to determine current kindergarten teacher understandings of early phonics instruction and how teachers are meeting readers' early phonics needs during guided reading instruction. Using Vygotsky's (1979) social constructivist theory and Ehri's (1995) connectionist theory and by focusing on age-appropriate instruction,…
Descriptors: Preschool Teachers, Kindergarten, Teacher Attitudes, Knowledge Level