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Brown, Alice; Lawrence, Jill; Basson, Marita; Axelsen, Megan; Redmond, Petrea; Turner, Joanna; Maloney, Suzanne; Galligan, Linda – Active Learning in Higher Education, 2023
Combining nudge theory with learning analytics, 'nudge analytics', is a relatively recent phenomenon in the educational context. Used, for example, to address such issues as concerns with student (dis)engagement, nudging students to take certain action or to change a behaviour towards active learning, can make a difference. However, knowing who to…
Descriptors: Online Courses, Learner Engagement, Learning Analytics, Intervention
Hatice Yildiz Durak – Education and Information Technologies, 2025
Feedback is critical in providing personalized information about educational processes and supporting their performance in online collaborative learning environments. However, giving effective feedback and monitoring its effects, which is especially important in online environments, is a complex issue. Although providing feedback by analyzing…
Descriptors: Feedback (Response), Online Systems, Electronic Learning, Learning Analytics
Chia-Yu Hsu; Izumi Horikoshi; Rwitajit Majumdar; Hiroaki Ogata – Educational Technology & Society, 2024
This study focuses on the problem that the process of building learning habits has not been clearly described. Therefore, we aim to extract the stages of learning habits from log data. We propose a data model to extract stages of learning habits based on the transtheoretical model and apply the model to the learning logs of self-directed extensive…
Descriptors: Habit Formation, Behavior Change, Learning Analytics, Data Interpretation
Susnjak, Teo; Ramaswami, Gomathy Suganya; Mathrani, Anuradha – International Journal of Educational Technology in Higher Education, 2022
This study investigates current approaches to learning analytics (LA) dashboarding while highlighting challenges faced by education providers in their operationalization. We analyze recent dashboards for their ability to provide actionable insights which promote informed responses by learners in making adjustments to their learning habits. Our…
Descriptors: Learning Analytics, Computer Interfaces, Artificial Intelligence, Prediction
Esnaashari, Shadi; Gardner, Lesley A.; Arthanari, Tiru S.; Rehm, Michael – Journal of Computer Assisted Learning, 2023
Background: It is vital to understand students' Self-Regulatory Learning (SRL) processes, especially in Blended Learning (BL), when students need to be more autonomous in their learning process. In studying SRL, most researchers have followed a variable-oriented approach. Moreover, little has been known about the unfolding process of students' SRL…
Descriptors: Metacognition, Student Attitudes, Learning Strategies, Questionnaires
Congning Ni; Bhashithe Abeysinghe; Juanita Hicks – International Electronic Journal of Elementary Education, 2025
The National Assessment of Educational Progress (NAEP), often referred to as The Nation's Report Card, offers a window into the state of U.S. K-12 education system. Since 2017, NAEP has transitioned to digital assessments, opening new research opportunities that were previously impossible. Process data tracks students' interactions with the…
Descriptors: Reaction Time, Multiple Choice Tests, Behavior Change, National Competency Tests
Park, Yeonjeong; Jo, Il-Hyun – Educational Technology Research and Development, 2019
A learning analytics dashboard enables teachers and students to monitor and reflect on their online teaching and learning patterns. This study was a review of prior studies on learning analytics dashboards to show the need to develop an instrument for measuring dashboard success. An early version of the instrument based on the framework of…
Descriptors: Learning Analytics, Test Validity, Factor Analysis, Aesthetics
Chen, Li; Lu, Min; Goda, Yoshiko; Shimada, Atsushi; Yamada, Masanori – International Association for Development of the Information Society, 2020
In this study, we used a learning analytics dashboard (LAD) in a higher education course to support students' metacognition and evaluated the effects of its use. The LAD displays students' reading path and specific behaviors when viewing digital learning materials. The study was conducted on 53 university students to identify the factors that…
Descriptors: College Students, Learning Analytics, Metacognition, Educational Technology
Acosta, Alejandra – New America, 2020
Predictive analytics has taken higher education by storm, with its promise of closing equity gaps, raising student retention rates, and increasing tuition revenue by keeping students enrolled. Many colleges and universities have made an investment in predictive analytics for student success initiatives, and even more are looking into implementing,…
Descriptors: Prediction, Learning Analytics, Higher Education, Information Dissemination
Letitia Hewlett Roman – ProQuest LLC, 2021
Leadership strategies for school turnaround and how to prioritize improvement efforts seem to lack a clear pattern for leaders of failing schools. The purpose of this study was to determine successful leadership strategies and methods for school turnaround and how best to prioritize the efforts by surveying a panel of experts through a Delphi…
Descriptors: School Turnaround, Delphi Technique, Intervention, Leadership Role
Mazgutova, Diana – International Journal of Educational Methodology, 2020
Revision constitutes an important component of the writing process that integrates text interpretation, reflection, and production. Although previous studies have offered useful insights into the revision behaviour of L2 writers at different levels of proficiency using off-line measures, little is known about the online processes of revision. In…
Descriptors: Revision (Written Composition), Behavior Change, English for Academic Purposes, Intensive Language Courses
Sánchez, Inmaculada Arnedillo, Ed.; Isaias, Pedro, Ed.; Ravesteijn, Pascal, Ed.; Ongena, Guido, Ed. – International Association for Development of the Information Society, 2019
These proceedings contain the papers and posters of the 15th International Conference on Mobile Learning 2019, which was organised by the International Association for Development of the Information Society and co-organised by the University of Applied Sciences, in Utrecht, The Netherlands, April 11-13, 2019. The Mobile Learning 2019 Conference…
Descriptors: Electronic Learning, Educational Research, Learning Analytics, Internet