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Rodríguez-Martínez, José Antonio; González-Calero, José Antonio; Olmo-Muñoz, Javier; Arnau, David; Tirado-Olivares, Sergio – British Journal of Educational Technology, 2023
This study analyses the potential of a learning analytics (LA) based formative assessment to construct personalised teaching sequences in Mathematics for 5th-grade primary school students. A total of 127 students from Spanish public schools participated in the study. The quasi-experimental study was conducted over the course of six sessions, in…
Descriptors: Foreign Countries, Elementary School Students, Grade 5, Mathematics Instruction
Kunwar, Rajendra; Sapkota, Hari Prasad – Online Submission, 2022
Dyslexia is a specific learning disability caused by a neurological problem. It is a worldwide problem with a prevalence of 5-10% of the population. It is described mainly by difficulties in reading, spelling, accuracy, fluency, and decoding abilities. This article is chiefly concerned to provide an overview of dyslexia, some key issues based on…
Descriptors: Dyslexia, Intervention, Mathematics Instruction, Learning Processes
Kleinman, Erica; Shergadwala, Murtuza N.; Teng, Zhaoqing; Villareale, Jennifer; Bryant, Andy; Zhu, Jichen; Seif El-Nasr, Magy – Journal of Learning Analytics, 2022
Educational technology is shifting toward facilitating personalized learning. Such personalization, however, requires a detailed understanding of students' problem-solving processes. Sequence analysis (SA) is a promising approach to gaining granular insights into student problem solving; however, existing techniques are difficult to interpret…
Descriptors: Problem Solving, Learning Analytics, Decision Making, Educational Technology
Shen, Shitian; Chi, Min – International Educational Data Mining Society, 2017
One of the most challenging tasks in the field of Educational Data Mining (EDM) is to cluster students directly based on system-student sequential moment-to-moment interactive trajectories. The objective of this study is to build a general temporal clustering framework that captures the distinct characteristics of students' sequential behaviors…
Descriptors: Sequential Approach, Cluster Grouping, Interaction, Student Behavior
Rasheed, Fareeha; Wahid, Abdul – International Journal of Information and Learning Technology, 2019
Purpose: The purpose of this paper is to identify the different sequence generation techniques for learning, which are applied to a broad category of personalized learning experiences. The papers have been classified using different attributes, such as the techniques used for sequence generation, attributes used for sequence generation; whether…
Descriptors: Sequential Approach, Electronic Learning, Futures (of Society), Student Characteristics
Morret, Tanya H.; Machado, Crystal H. – AASA Journal of Scholarship & Practice, 2017
Given the wide range of ability (academic, linguistic and cultural) in classrooms differentiated instruction is often difficult to manage. District and building level leadership can play an important role by providing the vision and support needed to implement Whole School Cluster Grouping (WSCG), the innovative scheduling approach described in…
Descriptors: Elementary School Students, Cluster Grouping, Individualized Instruction, Scheduling
Perna, Laura W.; Ruby, Alan; Boruch, Robert F.; Wang, Nicole; Scull, Janie; Ahmad, Seher; Evans, Chad – Educational Researcher, 2014
This paper reports on the progress of users through 16 Coursera courses taught by University of Pennsylvania faculty for the first time between June 2012 and July 2013. Using descriptive analyses, this study advances knowledge by considering two definitions of massive open online course (MOOC) users (registrants and starters), comparing two…
Descriptors: Online Courses, College Students, Sequential Approach, Learner Controlled Instruction
Bonnici, Laurie J.; Maatta, Stephanie L.; Klose, M. Katherine; Julien, Heidi; Bajjaly, Stephen – Studies in Higher Education, 2016
This case study examined student preference for delivery mode of online courses in two graduate degree programs in Library and Information Science. Within-group and between-groups comparisons indicated a distinct preference across the institutions. Findings from focus groups conducted with two cohorts of students enrolled in a federally funded…
Descriptors: Case Studies, Graduate Students, Comparative Analysis, Focus Groups
Bradley, Karen Sue; Bradley, Jack – Texas Journal of Literacy Education, 2014
In recent years, the popularity of alphabet books has spread into older grades, as they address a variety of themes and can be used across disciplines. Their complexity can stimulate thinking and offer a world of possibilities in the area of research. Students of all ages are motivated to create an alphabet book on a self-selected topic. The…
Descriptors: Alphabets, Books, Childrens Literature, Teaching Methods
Simonson, Michael, Ed.; Seepersaud, Deborah, Ed. – Association for Educational Communications and Technology, 2021
For the forty-fourth time, the Association for Educational Communications and Technology (AECT) is sponsoring the publication of these Proceedings. Papers published in this volume were presented online and onsite during the annual AECT Convention. Volume 1 contains papers dealing primarily with research and development topics. Papers dealing with…
Descriptors: Educational Technology, Technology Uses in Education, Computer Mediated Communication, Video Technology
Center for Mental Health in Schools at UCLA, 2011
Response to intervention is meant to be broad-based and preventative. However, as formulated and practiced the approach often is too limited in how it frames what needs to go on to enable learning, engage students, and keep them engaged. In particular, it pays too little attention to the need to strengthen the classroom and schoolwide context in…
Descriptors: Response to Intervention, Teaching Methods, Barriers, Program Implementation
Bicard, Sara; Casey, Laura Baylot; Nichols, Kathryn; Plank, Esther; Finley, Samantha – Journal on School Educational Technology, 2009
Differentiated instruction denotes varying instruction in terms of content, product, and process to meet the needs of all learners. One way to differentiate the instructional process is to provide multi-tiered instruction. Examples of systematic approaches to multi-tiered instruction are response to intervention (RTI) and school-wide positive…
Descriptors: Intervention, Individualized Instruction, Technology Uses in Education, Screening Tests
Cagiltay, Nergiz Ercil; Yildirim, Soner; Aksu, Meral – Educational Technology & Society, 2006
This paper reports the findings of a study conducted on a foreign language course at a large mid-west university in the USA. In the study a web-based tool which supports both linear and non-linear learning environments was designed and developed for this course. The aim of this study was to find out students' preferences pertaining to the learning…
Descriptors: Higher Education, Student Attitudes, Web Based Instruction, Internet
Su, Jun-Ming; Tseng, Shian-Shyong; Wang, Wei; Weng, Jui-Feng; Yang, Jin Tan David; Tsai, Wen-Nung – Educational Technology & Society, 2006
With vigorous development of the Internet, e-learning system has become more and more popular. Sharable Content Object Reference Model (SCORM) 2004 provides the Sequencing and Navigation (SN) Specification to define the course sequencing behavior, control the sequencing, selecting and delivering of course, and organize the content into a…
Descriptors: Portfolios (Background Materials), Teaching Methods, Sequential Approach, Computer System Design
Stamper, John, Ed.; Pardos, Zachary, Ed.; Mavrikis, Manolis, Ed.; McLaren, Bruce M., Ed. – International Educational Data Mining Society, 2014
The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…
Descriptors: Information Retrieval, Data Processing, Data Analysis, Data Collection