Publication Date
In 2025 | 0 |
Since 2024 | 1 |
Since 2021 (last 5 years) | 6 |
Since 2016 (last 10 years) | 12 |
Since 2006 (last 20 years) | 13 |
Descriptor
Learning Analytics | 13 |
Predictor Variables | 13 |
Student Behavior | 13 |
Academic Achievement | 6 |
Online Courses | 5 |
Artificial Intelligence | 4 |
Foreign Countries | 4 |
Undergraduate Students | 4 |
Blended Learning | 3 |
Computer Science Education | 3 |
Electronic Learning | 3 |
More ▼ |
Source
Author
Acar, Umut | 1 |
Akpinar, Nil-Jana | 1 |
Aom Perkash | 1 |
Bouchet, François | 1 |
Cerratto-Pargman, Teresa | 1 |
Chan, Ada Pui-Ling | 1 |
Chan, Henry C. B. | 1 |
Chen, Julia | 1 |
Cohen, Anat | 1 |
Dougiamas, Martin | 1 |
Eduardo Silva Alvarado | 1 |
More ▼ |
Publication Type
Reports - Research | 12 |
Journal Articles | 11 |
Dissertations/Theses -… | 1 |
Speeches/Meeting Papers | 1 |
Education Level
Higher Education | 9 |
Postsecondary Education | 9 |
Junior High Schools | 1 |
Middle Schools | 1 |
Secondary Education | 1 |
Audience
Location
Hong Kong | 1 |
Israel | 1 |
Pennsylvania (Pittsburgh) | 1 |
Sweden | 1 |
Turkey | 1 |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
So, Joseph Chi-Ho; Ho, Yik Him; Wong, Adam Ka-Lok; Chan, Henry C. B.; Tsang, Kia Ho-Yin; Chan, Ada Pui-Ling; Wong, Simon Chi-Wang – IEEE Transactions on Learning Technologies, 2023
Generic competence (GC) development is an integral part of higher education to provide holistic education and enhance student career development. It also plays a critical role in complementing the curriculum. Many tertiary institutions provide various GC development activities (GCDA). Moreover, institutions strongly need to further understand…
Descriptors: Predictor Variables, Higher Education, Online Courses, Correlation
Aom Perkash; Qaisar Shaheen; Robina Saleem; Furqan Rustam; Monica Gracia Villar; Eduardo Silva Alvarado; Isabel de la Torre Diez; Imran Ashraf – Education and Information Technologies, 2024
Developing tools to support students, educators, intuitions, and government in the educational environment has become an important task to improve the quality of education and learning outcomes. Information and communication technology (ICT) is adopted by educational institutions; one such instance is video interaction in flipped teaching.…
Descriptors: Academic Achievement, Colleges, Artificial Intelligence, Predictor Variables
Mutimukwe, Chantal; Viberg, Olga; Oberg, Lena-Maria; Cerratto-Pargman, Teresa – British Journal of Educational Technology, 2022
Understanding students' privacy concerns is an essential first step toward effective privacy-enhancing practices in learning analytics (LA). In this study, we develop and validate a model to explore the students' privacy concerns (SPICE) regarding LA practice in higher education. The SPICE model considers "privacy concerns" as a central…
Descriptors: Privacy, Learning Analytics, Student Attitudes, College Students
Pei, Bo; Xing, Wanli – Journal of Educational Computing Research, 2022
This paper introduces a novel approach to identify at-risk students with a focus on output interpretability through analyzing learning activities at a finer granularity on a weekly basis. Specifically, this approach converts the predicted output from the former weeks into meaningful probabilities to infer the predictions in the current week for…
Descriptors: At Risk Students, Learning Analytics, Information Retrieval, Models
Mohammed Alzaid – ProQuest LLC, 2022
Distributed self-assessments and reflections empower learners to take the lead on their knowledge gaining evaluation. Both provide essential elements for practice and self-regulation in learning settings. Nowadays, many sources for practice opportunities are made available to the learners, especially in the Computer Science (CS) and programming…
Descriptors: Learning Analytics, Self Evaluation (Individuals), Programming, Problem Solving
Kokoç, Mehmet; Kara, Mehmet – Educational Technology & Society, 2021
The purposes of the two studies reported in this research are to adapt and validate the instrument of the Evaluation Framework for Learning Analytics (EFLA) for learners into the Turkish context, and to examine how metacognitive and behavioral factors predict learner performance. Study 1 was conducted with 83 online learners enrolled in a 16-week…
Descriptors: Learning Analytics, Electronic Learning, Measures (Individuals), Test Validity
Makhlouf, Jihed; Mine, Tsunenori – Journal of Educational Data Mining, 2020
In recent years, we have seen the continuous and rapid increase of job openings in Science, Technology, Engineering and Math (STEM)-related fields. Unfortunately, these positions are not met with an equal number of workers ready to fill them. Efforts are being made to find durable solutions for this phenomena, and they start by encouraging young…
Descriptors: Learning Analytics, STEM Education, Science Careers, Career Choice
Harrak, Fatima; Bouchet, François; Luengo, Vanda – Journal of Learning Analytics, 2019
The analysis of student questions can be used to improve the learning experience for both students and teachers. We investigated questions (N = 6457) asked before the class by first-year medicine/pharmacy students on an online platform, used by professors to prepare for Q&A sessions. Our long-term objectives are to help professors in…
Descriptors: Medical Students, Pharmaceutical Education, Classroom Communication, Questioning Techniques
Akpinar, Nil-Jana; Ramdas, Aaditya; Acar, Umut – International Educational Data Mining Society, 2020
Educational software data promises unique insights into students' study behaviors and drivers of success. While much work has been dedicated to performance prediction in massive open online courses, it is unclear if the same methods can be applied to blended courses and a deeper understanding of student strategies is often missing. We use pattern…
Descriptors: Learning Strategies, Blended Learning, Learning Analytics, Student Behavior
Olive, David Monllao; Huynh, Du Q.; Reynolds, Mark; Dougiamas, Martin; Wiese, Damyon – IEEE Transactions on Learning Technologies, 2019
A significant amount of research effort has been put into finding variables that can identify students at risk based on activity records available in learning management systems (LMS). These variables often depend on the context, for example, the course structure, how the activities are assessed or whether the course is entirely online or a…
Descriptors: Prediction, Identification, At Risk Students, Online Courses
Foung, Dennis; Chen, Julia – Electronic Journal of e-Learning, 2019
In recent years, research using learning analytics to predict learning outcomes has begun to increase. This emerging field of research advocates the use of readily-available data to inform teaching and learning. The current case study adopts a learning analytics approach to evaluate the online learning package of an academic English course in a…
Descriptors: Foreign Countries, Blended Learning, Electronic Learning, English for Academic Purposes
Moore, Robert L.; Oliver, Kevin M.; Wang, Chuang – Interactive Learning Environments, 2019
Learning analytics focuses on extracting meaning from large amounts of data. One of the largest datasets in education comes from Massive Open Online Courses (MOOCs) that typically feature enrollments in the tens of thousands. Analyzing MOOC discussion forums presents logistical issues, resulting chiefly from the size of the dataset, which can…
Descriptors: Cognitive Processes, Online Courses, Discussion Groups, Learning Analytics
Levi-Gamlieli, Hadas; Cohen, Anat; Nachmias, Rafi – Technology, Instruction, Cognition and Learning, 2015
The aim of this study is to identify online learning behavior that is excessively intense as reflected in a student's overly frequent interaction with the instructor through various communication channels. Then, this study aims to use learning analytics methodologies to discover whether a student with the identified behavior also displays the same…
Descriptors: Student Behavior, Online Courses, Web Sites, Teacher Student Relationship