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Mengke Wang; Taotao Long; Na Li; Yawen Shi; Zengzhao Chen – Education and Information Technologies, 2025
Feedback plays an indispensable role in pre-service teachers' microteaching practice. It provides essential information about their microteaching performance, which is of great significance in their reflection and improvement. As AI and teaching analytics advance, feedback is no longer exclusively human-generated. AI technologies are increasingly…
Descriptors: Feedback (Response), Preservice Teachers, Microteaching, Reflection
Khalid Alalawi; Rukshan Athauda; Raymond Chiong; Ian Renner – Education and Information Technologies, 2025
Learning analytics intervention (LAI) studies aim to identify at-risk students early during an academic term using predictive models and facilitate educators to provide effective interventions to improve educational outcomes. A major impediment to the uptake of LAI is the lack of access to LAI infrastructure by educators to pilot LAI, which…
Descriptors: Intervention, Learning Analytics, Guidelines, Prediction
Patterson, Chris R.; York, Emily; Maxham, Danielle; Molina, Rudy; Mabrey, Paul, III – Journal of Learning Analytics, 2023
The anticipation, inclusion, responsiveness, and reflexivity (AIRR) framework (Stilgoe et al., 2013) is a novel framework that has helped those in science and technology fields shift their focus from products to the processes used to create those products. However, the framework has not been known to be applied to the development and…
Descriptors: Learning Analytics, Innovation, School Holding Power, At Risk Students
Chen, Si; Ouyang, Fan; Jiao, Pengcheng – Journal of Computer Assisted Learning, 2022
Background: Online Collaborative Writing (OCW) has been reported to be useful to improve writing quality in higher education. However, challenges emerge during the collaborative processes, mainly centering on how to sustain active interactions and communications in order to complete a high quality of writing. Objectives: Using the design-based…
Descriptors: Learner Engagement, Computer Mediated Communication, Collaborative Writing, Cooperative Learning
Sunday Olaleye; Richard Agjei; Biliaminu Jimoh; Prince Adoma – International Journal of Education and Development using Information and Communication Technology, 2023
The Modular Object-Oriented Dynamic Learning Environment (Moodle), a type of Learning Management System (LMS), is growing globally. Across the world, the student population keeps growing, making it challenging for the existing physical infrastructure to accommodate all the students. Despite the enormous potential significance of Analytics Graphs,…
Descriptors: Foreign Countries, Learning Management Systems, Usability, Technology
Iouri Kotorov; Yuliya Krasylnykova; Mar Pérez-Sanagustín; Fernanda Mansilla; Julien Broisin – Journal of Learning Analytics, 2024
The quality of the data and the amount of correct information available is key to informed decision-making. Higher education institutions (HEIs) often employ various decision support systems (DSSs) to make better choices. However, there is a lack of systems to assist with decision-making to promote innovation in teaching and learning. In this…
Descriptors: Decision Making, Case Studies, Instructional Innovation, Teaching Methods
Mitra, Reshmi; Schwieger, Dana; Lowe, Robert – Information Systems Education Journal, 2023
Many universities have, or are facing, the task of providing high quality essential customer services with fewer financial and human resources. The growing diversity of students, their needs and proficiencies, along with the increasing variety of university program offerings, make providing customized, ondemand, automated solutions crucial to…
Descriptors: Universities, Academic Advising, Artificial Intelligence, Faculty Workload
Flora Ji-Yoon Jin; Bhagya Maheshi; Roberto Martinez-Maldonado; Dragan Gasevic; Yi-Shan Tsai – Journal of Learning Analytics, 2024
Feedback is essential in learning. The emerging concept of feedback literacy underscores the skills students require for effective use of feedback. This highlights students' responsibilities in the feedback process. Yet, there is currently a lack of mechanisms to understand how students make sense of feedback and whether they act on it. This gap…
Descriptors: Scaffolding (Teaching Technique), Feedback (Response), Learning Analytics, Literacy
Lars de Vreugd; Anouschka van Leeuwen; Renée Jansen; Marieke van der Schaaf – Journal of Learning Analytics, 2024
For university students, self-regulation of study behaviour is important. However, students are not always capable of effective self-regulation. Providing study behaviour information via a learning analytics dashboard (LAD) may support phases within self-regulated learning (SRL). However, it is unclear what information a LAD should provide, how to…
Descriptors: Learning Management Systems, Learning Analytics, Student Behavior, Behavior Patterns
Aaron Bere; Patrick Chirilele; Rugare Chitiga – International Association for Development of the Information Society, 2022
The purpose of this paper is to present an empirical investigation of the critical determinants for the adoption of learning analytics in higher education. A conceptual model was proposed to understand better the adoption of learning analytics in higher education by teaching staff. Structural equation modelling is used for testing and validating…
Descriptors: Learning Analytics, Validity, Research Methodology, Higher Education
Rets, Irina; Herodotou, Christothea; Bayer, Vaclav; Hlosta, Martin; Rienties, Bart – International Journal of Educational Technology in Higher Education, 2021
Learning analytics dashboards (LADs) can provide learners with insights about their study progress through visualisations of the learner and learning data. Despite their potential usefulness to support learning, very few studies on LADs have considered learners' needs and have engaged learners in the process of design and evaluation. Aligning with…
Descriptors: Learning Analytics, Educational Technology, Usability, College Students
Chavan, Pankaj; Mitra, Ritayan – Journal of Learning Analytics, 2022
The use of online video lectures in universities, primarily for content delivery and learning, is on the rise. Instructors' ability to recognize and understand student learning experiences with online video lectures, identify particularly difficult or disengaging content and thereby assess overall lecture quality can inform their instructional…
Descriptors: Learning Analytics, Video Technology, Lecture Method, Online Courses
Silvia García-Méndez; Francisco de Arriba-Pérez; Francisco J. González-Castaño – International Association for Development of the Information Society, 2023
Mobile learning or mLearning has become an essential tool in many fields in this digital era, among the ones educational training deserves special attention, that is, applied to both basic and higher education towards active, flexible, effective high-quality and continuous learning. However, despite the advances in Natural Language Processing…
Descriptors: Higher Education, Artificial Intelligence, Computer Software, Usability
PLS Model Performance for Factors Influencing Student Acceptance of E-Learning Analytics Recommender
Sandhu, Kamaljeet – International Journal of Virtual and Personal Learning Environments, 2020
The aim of this article is to present the multivariate analyses results of the factors that influence students' acceptance and the continuance usage intention of e-learning analytics recommender systems in higher education institutions in Saudi Arabia. Data was collected from 353 Saudi Arabian university students via an online survey…
Descriptors: Electronic Learning, Learning Analytics, Foreign Countries, College Students
van Leeuwen, Anouschka – Educational Technology Research and Development, 2019
The flipped classroom model is a form of blended learning in which delivery of content occurs with online materials, and face-to-face meetings are used for teacher-guided practice. It is important that teachers stay up to date with the activities students engage in, which may be accomplished with the help of learning analytics (LA). This study…
Descriptors: Teacher Attitudes, Usability, Learning Analytics, Blended Learning
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