NotesFAQContact Us
Collection
Advanced
Search Tips
Laws, Policies, & Programs
What Works Clearinghouse Rating
Showing 1 to 15 of 49 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Swai, Carina Titus; Mangowi, Steven Edward – International Journal of Information and Learning Technology, 2022
Purpose: The general goal of this paper is to help educators understand the importance of MOOC training to school teachers and their hypothetical value for predicting the use of teaching strategies in the face-to face-classroom teaching. With this purpose, the study is guided by two research questions: (1) Are there different patterns of…
Descriptors: Teacher Attitudes, Preferences, Teaching Methods, Conventional Instruction
Peer reviewed Peer reviewed
Direct linkDirect link
Michos, Konstantinos; Schmitz, Maria-Luisa; Petko, Dominik – Education and Information Technologies, 2023
Since schools increasingly use digital platforms that provide educational data in digital formats, teacher data use, and data literacy have become a focus of educational research. One main challenge is whether teachers use digital data for pedagogical purposes, such as informing their teaching. We conducted a survey study with N = 1059 teachers in…
Descriptors: Secondary School Teachers, Prediction, Data Use, Data Analysis
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Bozkurt, Aras; Sharma, Ramesh C. – Asian Journal of Distance Education, 2022
Humans have always been lured by the idea that they can use data to understand a phenomenon and make predictions about it. Learning analytics, in this sense, promise to understand and optimize learning and the environments in which it occurs by collecting data from learners and learning contexts. In this regard, this study systematically examines…
Descriptors: Learning Analytics, Teaching Methods, Learning Processes, Prediction
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Doroudi, Shayan – AERA Open, 2020
In addition to providing a set of techniques to analyze educational data, I claim that data science as a field can provide broader insights to education research. In particular, I show how the bias-variance tradeoff from machine learning can be formally generalized to be applicable to several prominent educational debates, including debates around…
Descriptors: Data Analysis, Learning Theories, Teaching Methods, Educational Research
Peer reviewed Peer reviewed
Direct linkDirect link
Perrotta, Carlo; Selwyn, Neil – Learning, Media and Technology, 2020
In Applied AI, or 'machine learning', methods such as neural networks are used to train computers to perform tasks without human intervention. In this article, we question the applicability of these methods to education. In particular, we consider a case of recent attempts from data scientists to add AI elements to a handful of online learning…
Descriptors: Artificial Intelligence, Intelligent Tutoring Systems, Teaching Methods, Online Courses
Peer reviewed Peer reviewed
Direct linkDirect link
Prieto, Luis P.; Magnuson, Paul; Dillenbourg, Pierre; Saar, Merike – Technology, Pedagogy and Education, 2020
Improving educational practice through reflection is one important focus of teacher professional development approaches. However, such teacher reflection operates under practical classroom constraints that make it happen infrequently, including the reliance on disruptive peer/supervisor observations or recordings. This article describes three…
Descriptors: Faculty Development, Reflection, Secondary School Teachers, Educational Technology
Peer reviewed Peer reviewed
Direct linkDirect link
Seufert, Sabine; Meier, Christoph; Soellner, Matthias; Rietsche, Roman – Technology, Knowledge and Learning, 2019
The increasing prevalence of learner-centred forms of learning as well as an increase in the number of learners actively participating on a wide range of digital platforms and devices give rise to an ever-increasing stream of learning data. Learning analytics (LA) can enable learners, teachers, and their institutions to better understand and…
Descriptors: Incidence, Student Centered Learning, Data Analysis, Prediction
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Saqr, Mohammed; López-Pernas, Sonsoles – Journal of Learning Analytics, 2022
There has been extensive research using centrality measures in educational settings. One of the most common lines of such research has tested network centrality measures as indicators of success. The increasing interest in centrality measures has been kindled by the proliferation of learning analytics. Previous works have been dominated by…
Descriptors: Measurement Techniques, Learning Analytics, Data Analysis, Academic Achievement
Peer reviewed Peer reviewed
Direct linkDirect link
Thontirawong, Pipat; Chinchanachokchai, Sydney – Marketing Education Review, 2021
In the age of big data and analytics, it is important that students learn about artificial intelligence (AI) and machine learning (ML). Machine learning is a discipline that focuses on building a computer system that can improve itself using experience. ML models can be used to detect patterns from data and recommend strategic marketing actions.…
Descriptors: Marketing, Artificial Languages, Career Development, Time Management
Peer reviewed Peer reviewed
Direct linkDirect link
Aydogdu, Seyhmus – Education and Information Technologies, 2020
Prediction of student performance is one of the most important subjects of educational data mining. Artificial neural networks are seen to be an effective tool in predicting student performance in e-learning environments. In the studies carried out with artificial neural networks, performance predictions based on student scores are generally made,…
Descriptors: Prediction, Academic Achievement, Electronic Learning, Artificial Intelligence
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Bulathwela, Sahan; Pérez-Ortiz, María; Lipani, Aldo; Yilmaz, Emine; Shawe-Taylor, John – International Educational Data Mining Society, 2020
The explosion of Open Educational Resources (OERs) in the recent years creates the demand for scalable, automatic approaches to process and evaluate OERs, with the end goal of identifying and recommending the most suitable educational materials for learners. We focus on building models to find the characteristics and features involved in…
Descriptors: Prediction, Open Educational Resources, Learner Engagement, Video Technology
Peer reviewed Peer reviewed
Direct linkDirect link
Alonso-Fernández, Cristina; Martínez-Ortiz, Iván; Caballero, Rafael; Freire, Manuel; Fernández-Manjón, Baltasar – Journal of Computer Assisted Learning, 2020
Serious games have proven to be a powerful tool in education to engage, motivate, and help students learn. However, the change in student knowledge after playing games is usually measured with traditional (paper) prequestionnaires-postquestionnaires. We propose a combination of game learning analytics and data mining techniques to predict…
Descriptors: Case Studies, Teaching Methods, Game Based Learning, Student Motivation
Peer reviewed Peer reviewed
Direct linkDirect link
Raj, Gaurav; Mahajan, Manish; Singh, Dheerendra – International Journal of Web-Based Learning and Teaching Technologies, 2020
In secure web application development, the role of web services will not continue if it is not trustworthy. Retaining customers with applications is one of the major challenges if the services are not reliable and trustworthy. This article proposes a trust evaluation and decision model where the authors have defined indirect attribute, trust,…
Descriptors: Trust (Psychology), Models, Decision Making, Computer Software
Peer reviewed Peer reviewed
Direct linkDirect link
Hlioui, Fedia; Aloui, Nadia; Gargouri, Faiez – International Journal of Web-Based Learning and Teaching Technologies, 2021
Nowadays, the virtual learning environment has become an ideal tool for professional self-development and bringing courses for various learner audiences across the world. There is currently an increasing interest in researching the topic of learner dropout and low completion in distance learning, with one of the main concerns being elevated rates…
Descriptors: At Risk Students, Withdrawal (Education), Dropouts, Distance Education
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Karimi, Hamid; Derr, Tyler; Huang, Jiangtao; Tang, Jiliang – International Educational Data Mining Society, 2020
Online learning has attracted a large number of participants and is increasingly becoming very popular. However, the completion rates for online learning are notoriously low. Further, unlike traditional education systems, teachers, if any, are unable to comprehensively evaluate the learning gain of each student through the online learning…
Descriptors: Online Courses, Academic Achievement, Prediction, Teaching Methods
Previous Page | Next Page »
Pages: 1  |  2  |  3  |  4