Publication Date
| In 2025 | 7 |
| Since 2024 | 23 |
| Since 2021 (last 5 years) | 68 |
| Since 2016 (last 10 years) | 91 |
| Since 2006 (last 20 years) | 141 |
Descriptor
Source
Author
Publication Type
Education Level
Audience
| Practitioners | 18 |
| Researchers | 13 |
| Administrators | 7 |
| Policymakers | 6 |
| Community | 1 |
Location
| California | 5 |
| Australia | 3 |
| Canada | 2 |
| Florida | 2 |
| Hong Kong | 2 |
| Louisiana | 2 |
| Missouri | 2 |
| Pakistan | 2 |
| Solomon Islands | 2 |
| Sweden | 2 |
| Texas | 2 |
| More ▼ | |
Laws, Policies, & Programs
| Every Student Succeeds Act… | 3 |
| American Recovery and… | 2 |
| No Child Left Behind Act 2001 | 2 |
| Education Consolidation and… | 1 |
| Elementary and Secondary… | 1 |
| Proposition 13 (California… | 1 |
Assessments and Surveys
What Works Clearinghouse Rating
Peer reviewed
Download full textFabricio Trujillo; Marcelo Pozo; Gabriela Suntaxi – Journal of Technology and Science Education, 2025
This paper presents a systematic literature review of using Machine Learning (ML) techniques in higher education career recommendation. Despite the growing interest in leveraging Artificial Intelligence (AI) for personalized academic guidance, no previous reviews have synthesized the diverse methodologies in this field. Following the Kitchenham…
Descriptors: Artificial Intelligence, Higher Education, Career Guidance, Models
Direct linkAndrea Zanellati; Daniele Di Mitri; Maurizio Gabbrielli; Olivia Levrini – IEEE Transactions on Learning Technologies, 2024
Knowledge tracing is a well-known problem in AI for education, consisting of monitoring how the knowledge state of students changes during the learning process and accurately predicting their performance in future exercises. In recent years, many advances have been made thanks to various machine learning and deep learning techniques. Despite their…
Descriptors: Artificial Intelligence, Prior Learning, Knowledge Management, Models
Or Dagan; Carlo Schuengel; Marije L. Verhage; Sheri Madigan; Glenn I. Roisman; Kristin Bernard; Robbie Duschinsky; Marian Bakermans-Kranenburg; Jean-François Bureau; Abraham Sagi-Schwartz; Rina D. Eiden; Maria S. Wong; Geoffrey L. Brown; Isabel Soares; Mirjam Oosterman; R. M. Pasco Fearon; Howard Steele; Carla Martins; Ora Aviezer – Child Development, 2024
An individual participant data meta-analysis was conducted to test pre-registered hypotheses about how the configuration of attachment relationships to mothers and fathers predicts children's language competence. Data from seven studies (published between 1985 and 2014) including 719 children (M[subscript age]: 19.84 months; 51% female; 87% White)…
Descriptors: Parent Child Relationship, Attachment Behavior, Fathers, Mothers
Tapio Rasa – European Journal of Education, 2025
Education is inherently entangled with the future. This argumentative review examines this entanglement and proposes a framework differentiating between four educational orientations towards the future. The orientation 'Futures of education' examines how education changes in the future: From rhetorical to visionary, these futures are concerned…
Descriptors: Educational Trends, Trend Analysis, Educational Change, Futures (of Society)
Rachel Horst; Derek Gladwin – Journal of Curriculum and Pedagogy, 2024
It is no surprise that concern for the future is on the rise. Several catastrophes obscure our future(s) imaginary, such as climate change, a global pandemic, racial inequality, and political polarization. Students are feeling a disconnect between what they learn in classrooms and the futures that populate their media platforms. Futures literacies…
Descriptors: Futures (of Society), Multiple Literacies, Interdisciplinary Approach, Inquiry
Samah AlKhuzaey; Floriana Grasso; Terry R. Payne; Valentina Tamma – International Journal of Artificial Intelligence in Education, 2024
Designing and constructing pedagogical tests that contain items (i.e. questions) which measure various types of skills for different levels of students equitably is a challenging task. Teachers and item writers alike need to ensure that the quality of assessment materials is consistent, if student evaluations are to be objective and effective.…
Descriptors: Test Items, Test Construction, Difficulty Level, Prediction
Jutta Kray; Linda Sommerfeld; Arielle Borovsky; Katja Häuser – Child Development Perspectives, 2024
Prediction error plays a pivotal role in theories of learning, including theories of language acquisition and use. Researchers have investigated whether and under which conditions children, like adults, use prediction to facilitate language comprehension at different levels of linguistic representation. However, many aspects of the reciprocal…
Descriptors: Prediction, Child Development, Language Acquisition, Error Analysis (Language)
Verschuere, Bruno; Bogaard, Glynis; Meijer, Ewout – Applied Cognitive Psychology, 2021
The Verifiability Approach predicts that truth tellers will include details that can be verified by the interviewer, whereas liars will refrain from providing such details. A meta-analysis revealed that truth tellers indeed provided more verifiable details (k = 28, d = 0.49, 95% CI [0.25; 0.74], BF[subscript 10] = 93.28), and a higher proportion…
Descriptors: Deception, Ethics, Credibility, Incentives
M. Nazir; A. Noraziah; M. Rahmah – International Journal of Virtual and Personal Learning Environments, 2023
An effective educational program warrants the inclusion of an innovative construction that enhances the higher education efficacy in such a way that accelerates the achievement of desired results and reduces the risk of failures. Educational decision support system has currently been a hot topic in educational systems, facilitating the pupil…
Descriptors: Data Analysis, Academic Achievement, Artificial Intelligence, Prediction
Ke Ting Chong; Noraini Ibrahim; Sharin Hazlin Huspi; Wan Mohd Nasir Wan Kadir; Mohd Adham Isa – Journal of Information Technology Education: Research, 2025
Aim/Purpose: The purpose of this study is to review and categorize current trends in student engagement and performance prediction using machine learning techniques during online learning in higher education. The goal is to gain a better understanding of student engagement prediction research that is important for current educational planning and…
Descriptors: Literature Reviews, Meta Analysis, Artificial Intelligence, Higher Education
Damla Mustu Yaldiz; Saniye Kuleli; Ozlem Soydan Oktay; Nedime Selin Copgeven; Elif Akyol Emmungil; Yusuf Yildirim; Firat Sosuncu; Mehmet Firat – Turkish Online Journal of Distance Education, 2024
The e-learning domain has witnessed a shift from the traditional behavioral approach to an individual centered learning approach based on learning analytics, with the aim of creating personalized and learner sensitive designs. A systematic literature review of 284 articles published between 2011 and 2022 in 133 different journals was conducted to…
Descriptors: Learning Analytics, Personal Autonomy, Independent Study, Learning Processes
Seo, Michael; Furukawa, Toshi A.; Karyotaki, Eirini; Efthimiou, Orestis – Research Synthesis Methods, 2023
Clinical prediction models are widely used in modern clinical practice. Such models are often developed using individual patient data (IPD) from a single study, but often there are IPD available from multiple studies. This allows using meta-analytical methods for developing prediction models, increasing power and precision. Different studies,…
Descriptors: Prediction, Models, Patients, Data Analysis
Migliavaca, Celina Borges; Stein, Cinara; Colpani, Verônica; Barker, Timothy Hugh; Ziegelmann, Patricia Klarmann; Munn, Zachary; Falavigna, Maicon – Research Synthesis Methods, 2022
Over the last decade, there has been a 10-fold increase in the number of published systematic reviews of prevalence. In meta-analyses of prevalence, the summary estimate represents an average prevalence from included studies. This estimate is truly informative only if there is no substantial heterogeneity among the different contexts being pooled.…
Descriptors: Incidence, Meta Analysis, Statistics, Statistical Distributions
Batool, Saba; Rashid, Junaid; Nisar, Muhammad Wasif; Kim, Jungeun; Kwon, Hyuk-Yoon; Hussain, Amir – Education and Information Technologies, 2023
Educational data mining is an emerging interdisciplinary research area involving both education and informatics. It has become an imperative research area due to many advantages that educational institutions can achieve. Along these lines, various data mining techniques have been used to improve learning outcomes by exploring large-scale data that…
Descriptors: Academic Achievement, Prediction, Data Use, Information Retrieval
Ramaswami, Gomathy; Susnjak, Teo; Mathrani, Anuradha; Umer, Rahila – Technology, Knowledge and Learning, 2023
Learning analytics dashboards (LADs) provide educators and students with a comprehensive snapshot of the learning domain. Visualizations showcasing student learning behavioral patterns can help students gain greater self-awareness of their learning progression, and at the same time assist educators in identifying those students who may be facing…
Descriptors: Prediction, Learning Analytics, Learning Management Systems, Identification
