NotesFAQContact Us
Collection
Advanced
Search Tips
Laws, Policies, & Programs
What Works Clearinghouse Rating
Showing 1 to 15 of 43 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Teemu Valtonen; Teija Paavilainen; Sonsoles López-Pernas; Mohamed Saqr; Laura Hirsto – Technology, Knowledge and Learning, 2025
This study focuses on learning analytics from the perspective of elementary and secondary classroom teachers (grades one to nine). The aim is to explore teachers' perceptions about the use of learning analytics, the challenges and opportunities associated with the tools, and the future of the analytics. The research is based on qualitative data:…
Descriptors: Elementary School Teachers, Secondary School Teachers, Learning Analytics, Teacher Attitudes
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Anni Silvola; Amanda Sjöblom; Piia Näykki; Egle Gedrimiene; Hanni Muukkonen – Frontline Learning Research, 2023
An in-depth understanding of student experiences and evaluations of learning analytics dashboards (LADs) is needed to develop supportive learning analytics tools. This study investigates how students (N = 140) evaluated two student-facing LADs as a support for academic path-level self-regulated learning (SRL) through the concrete processes of…
Descriptors: Learning Analytics, Student Evaluation, Student Experience, Student Attitudes
Peer reviewed Peer reviewed
Direct linkDirect link
Xiaona Xia; Wanxue Qi – European Journal of Education, 2025
Massive Open Online Courses (MOOCs) effectively support online learning behaviour; while constructing a sustainable learning process, MOOCs have also formed the social network. In addition, learners' burnout state has become a serious obstacle to the development and promotion of MOOCs. This study analyzes the potential social behaviour associated…
Descriptors: MOOCs, Burnout, Social Behavior, Feedback (Response)
Peer reviewed Peer reviewed
Direct linkDirect link
Alzahrani, Asma Shannan; Tsai, Yi-Shan; Iqbal, Sehrish; Marcos, Pedro Manuel Moreno; Scheffel, Maren; Drachsler, Hendrik; Kloos, Carlos Delgado; Aljohani, Naif; Gasevic, Dragan – Education and Information Technologies, 2023
Potential benefits of learning analytics (LA) for improving students' performance, predicting students' success, and enhancing teaching and learning practice have increasingly been recognized in higher education. However, the adoption of LA in higher education institutions (HEIs) to date remains sporadic and predominantly small in scale due to…
Descriptors: Learning Analytics, Higher Education, Adoption (Ideas), Epistemology
Peer reviewed Peer reviewed
Direct linkDirect link
Park, Eunsung; Ifenthaler, Dirk; Clariana, Roy B. – British Journal of Educational Technology, 2023
The real-time and granularized learning information and recommendations available from adaptive learning technology can provide learners with feedback that is personalized. However, at an individual level, learners often experience technological and pedagogical conflicts. Learners have more freedom to accept, ignore or reject the feedback while…
Descriptors: Metacognition, Learning Analytics, Learning Management Systems, Learning Strategies
Peer reviewed Peer reviewed
Direct linkDirect link
Yamauchi, Taisei; Flanagan, Brendan; Nakamoto, Ryosuke; Dai, Yiling; Takami, Kyosuke; Ogata, Hiroaki – Smart Learning Environments, 2023
In recent years, smart learning environments have become central to modern education and support students and instructors through tools based on prediction and recommendation models. These methods often use learning material metadata, such as the knowledge contained in an exercise which is usually labeled by domain experts and is costly and…
Descriptors: Mathematics Instruction, Classification, Algorithms, Barriers
Peer reviewed Peer reviewed
Direct linkDirect link
Gyeonggeon Lee; Xiaoming Zhai – TechTrends: Linking Research and Practice to Improve Learning, 2025
Educators and researchers have analyzed various image data acquired from teaching and learning, such as images of learning materials, classroom dynamics, students' drawings, etc. However, this approach is labour-intensive and time-consuming, limiting its scalability and efficiency. The recent development in the Visual Question Answering (VQA)…
Descriptors: Artificial Intelligence, Computer Software, Teaching Methods, Learning Processes
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Lee, Hakeoung Hannah; Gargroetzi, Emma C. – Journal of Learning Analytics, 2023
Data-driven learning analytics (LA) exploits artificial intelligence, data-mining, and emerging technologies, rapidly expanding the collection and uses of learner data. Considerations of potential harm and ethical implications have not kept pace, raising concerns about ethical and privacy issues (Holstein & Doroudi, 2019; Prinsloo & Slade,…
Descriptors: Learning Analytics, Mentors, Ethics, Responsibility
Peer reviewed Peer reviewed
Direct linkDirect link
Stewart, Bonnie; Miklas, Erica; Szcyrek, Samantha; Le, Thu – International Journal of Educational Technology in Higher Education, 2023
In recent decades, higher education institutions around the world have come to depend on complex digital infrastructures. In addition to registration, financial, and other operations platforms, digital classroom tools with built-in learning analytics capacities underpin many course delivery options. Taken together, these intersecting digital…
Descriptors: Learning Analytics, Higher Education, College Faculty, Teacher Attitudes
Peer reviewed Peer reviewed
Direct linkDirect link
Alkhalil, Adel; Abdallah, Magdy Abd Elrahman; Alogali, Azizah; Aljaloud, Abdulaziz – International Journal of Information and Communication Technology Education, 2021
Higher education systems (HES) have become increasingly absorbed in applying big data analytics due to competition as well as economic pressures. Many studies have been conducted that applied big data analytics in HES; however, a systematic review (SR) of the research is scarce. In this paper, the authors conducted a systematic mapping study to…
Descriptors: Learning Analytics, Higher Education, Educational Research, Publications
Peer reviewed Peer reviewed
Direct linkDirect link
Ana Stojanov; Ben Kei Daniel – Education and Information Technologies, 2024
The need for data-driven decision-making primarily motivates interest in analysing Big Data in higher education. Although there has been considerable research on the value of Big Data in higher education, its application to address critical issues within the sector is still limited. This systematic review, conducted in December 2021 and…
Descriptors: Higher Education, Learning Analytics, Well Being, Decision Making
Peer reviewed Peer reviewed
Devika Venugopalan; Ziwen Yan; Conrad Borchers; Jionghao Lin; Vincent Aleven – Grantee Submission, 2025
Caregivers (i.e., parents and members of a child's caring community) are underappreciated stakeholders in learning analytics. Although caregiver involvement can enhance student academic outcomes, many obstacles hinder involvement, most notably knowledge gaps with respect to modern school curricula. An emerging topic of interest in learning…
Descriptors: Homework, Computational Linguistics, Teaching Methods, Learning Analytics
Peer reviewed Peer reviewed
Direct linkDirect link
Frances Edwards; Bronwen Cowie; Suzanne Trask – Professional Development in Education, 2025
This paper reports on teachers developing their own data literacy and then acting as data coaches for colleagues in their schools. The 13 teachers from 7 schools in the study analysed standardised data using a data conversation protocol to identify students with significant mathematical misconceptions. They then took data-informed action with…
Descriptors: Coaching (Performance), Peer Teaching, Statistics Education, Knowledge Level
Peer reviewed Peer reviewed
Direct linkDirect link
Liu, Kai; Tatinati, Sivanagaraja; Khong, Andy W. H. – IEEE Transactions on Learning Technologies, 2020
Activity-centric data gather feedback on students' learning to enhance learning effectiveness. The heterogeneity and multigranularity of such data require existing data models to perform complex on-the-fly computation when responding to queries of specific granularity. This, in turn, results in latency. In addition, existing data models are…
Descriptors: Context Effect, Models, Learning Analytics, Data Use
Peer reviewed Peer reviewed
Direct linkDirect link
Li, Yanyan; Zhang, Muhua; Su, You; Bao, Haogang; Xing, Shuang – Educational Technology Research and Development, 2022
Learning analytics dashboards have been developed to facilitate teacher guidance in computer-supported collaborative learning (CSCL). As yet, little is known about how teachers interpret dashboard information to facilitate guidance in their teaching practice. This study examined teachers' behavior patterns in interpreting information from…
Descriptors: Teacher Behavior, Teacher Attitudes, Educational Technology, Guidance
Previous Page | Next Page »
Pages: 1  |  2  |  3