Publication Date
In 2025 | 71 |
Since 2024 | 384 |
Since 2021 (last 5 years) | 759 |
Since 2016 (last 10 years) | 785 |
Since 2006 (last 20 years) | 788 |
Descriptor
Source
Author
van der Linden, Wim J. | 17 |
Kiers, Henk A. L. | 13 |
ten Berge, Jos M. F. | 10 |
Gongjun Xu | 9 |
Gerlach, Vernon S. | 8 |
Willett, Peter | 8 |
Chun Wang | 7 |
Stocking, Martha L. | 7 |
Charp, Sylvia | 6 |
Chen, Hsinchun | 6 |
Craven, Timothy C. | 6 |
More ▼ |
Publication Type
Education Level
Audience
Practitioners | 255 |
Teachers | 126 |
Researchers | 114 |
Policymakers | 6 |
Administrators | 5 |
Students | 4 |
Counselors | 1 |
Media Staff | 1 |
Support Staff | 1 |
Location
China | 17 |
Australia | 15 |
Netherlands | 14 |
Turkey | 12 |
USSR | 10 |
United States | 9 |
California | 8 |
United Kingdom (England) | 7 |
Brazil | 6 |
Europe | 6 |
Germany | 6 |
More ▼ |
Laws, Policies, & Programs
Elementary and Secondary… | 2 |
Coronavirus Aid Relief and… | 1 |
Family Educational Rights and… | 1 |
Privacy Act 1974 | 1 |
Assessments and Surveys
What Works Clearinghouse Rating
Gabriella Colajanni; Alessandro Gobbi; Marinella Picchi; Alice Raffaele; Eugenia Taranto – INFORMS Transactions on Education, 2024
In this paper, we continue describing the project and the experimentation of "Ricerca Operativa Applicazioni Reali" (ROAR; in English, Real Applications of Operations Research), a three-year project for higher secondary schools, introduced. ROAR is composed of three teaching units, addressed to Grades 10, 11, and 12, respectively, having…
Descriptors: Foreign Countries, Grade 11, Operations Research, High School Students
Jordan M. Wheeler; Allan S. Cohen; Shiyu Wang – Journal of Educational and Behavioral Statistics, 2024
Topic models are mathematical and statistical models used to analyze textual data. The objective of topic models is to gain information about the latent semantic space of a set of related textual data. The semantic space of a set of textual data contains the relationship between documents and words and how they are used. Topic models are becoming…
Descriptors: Semantics, Educational Assessment, Evaluators, Reliability
En Xie; Shaw-chiang Wong; Ying Bai – Journal of Autism and Developmental Disorders, 2024
Psychology originally defined parent-child conflict in terms of interpersonal relationships, where parent-child conflict is a process of inconsistent attitudes between parents and children that occurs in a family setting. For this end, we aims to investigate the influence of parental awareness on preschoolers' perception of parent-child conflict…
Descriptors: Computer Software, Computer Simulation, Parent Child Relationship, Cooperation
Slavko Žitnik; Glenn Gordon Smith – Interactive Learning Environments, 2024
In the recent, and ongoing, COVID-19 pandemic, remote or online K-12 schooling became the norm. Even if the pandemic tails off somewhat, remote K-12 schooling will likely remain more frequent than it was before the pandemic. A mainstay technique of online learning, at least at the college and graduate level, has been the online discussion. Since…
Descriptors: Grade 4, Elementary School Students, Discussion, Automation
WenHua Cui; Yiming Fang; Yan Ma – International Journal of Web-Based Learning and Teaching Technologies, 2024
A framework was proposed to identify the at-risk factors of college courses in blended mode, offering suggestions for continuous improvement. An indicator system concerning teaching quality characteristics was constructed based on context, input, process, and product (CIPP) model. Subsequently, the group Analytic Hierarchy Process (AHP) algorithm…
Descriptors: Higher Education, Blended Learning, Risk Assessment, Risk
Tanjea Ane; Tabatshum Nepa – Research on Education and Media, 2024
Precision education derives teaching and learning opportunities by customizing predictive rules in educational methods. Innovative educational research faces new challenges and affords state-of-the-art methods to trace knowledge between the teaching and learning ecosystem. Individual intelligence can only be captured through knowledge level…
Descriptors: Artificial Intelligence, Prediction, Models, Teaching Methods
Nesra Yannier; Scott E. Hudson; Henry Chang; Kenneth R. Koedinger – International Journal of Artificial Intelligence in Education, 2024
Adaptivity in advanced learning technologies offer the possibility to adapt to different student backgrounds, which is difficult to do in a traditional classroom setting. However, there are mixed results on the effectiveness of adaptivity based on different implementations and contexts. In this paper, we introduce AI adaptivity in the context of a…
Descriptors: Artificial Intelligence, Computer Software, Feedback (Response), Outcomes of Education
Camille Lund – Mathematics Teacher: Learning and Teaching PK-12, 2024
Every educator knows the sinking feeling of a lesson gone wrong. As teachers look around the room and realize that many of their students are just not getting it, they often feel like failures. However, the struggle students experience as they persevere through high-quality challenging tasks is not a sign of failure, but rather a key aspect of…
Descriptors: Mathematics Instruction, Difficulty Level, Mathematics Skills, Teaching Methods
Hongyu Xie; He Xiao; Yu Hao – International Journal of Web-Based Learning and Teaching Technologies, 2024
Modern e-learning system is a representative service form in innovative service industry. This paper designs a personalized service domain system, optimizes various parameters and can be applied to different education quality evaluation, and proposes a decision tree recommendation algorithm. Information gain is carried out through many existing…
Descriptors: Artificial Intelligence, Electronic Learning, Individualized Instruction, Models
Kerstin Wagner; Agathe Merceron; Petra Sauer; Niels Pinkwart – Journal of Educational Data Mining, 2024
In this paper, we present an extended evaluation of a course recommender system designed to support students who struggle in the first semesters of their studies and are at risk of dropping out. The system, which was developed in earlier work using a student-centered design, is based on the explainable k-nearest neighbor algorithm and recommends a…
Descriptors: At Risk Students, Algorithms, Foreign Countries, Course Selection (Students)
Laurel Raffington – npj Science of Learning, 2024
Recently, biological aging has been quantified in DNA-methylation samples of older adults and applied as so-called "methylation profile scores" (MPSs) in separate target samples, including samples of children. This nascent research indicates that (1) biological aging can be quantified early in the life course, decades before the onset of…
Descriptors: Genetics, Aging (Individuals), Older Adults, Scores
Liou, Gloria; Bonner, Cavan V.; Tay, Louis – International Journal of Testing, 2022
With the advent of big data and advances in technology, psychological assessments have become increasingly sophisticated and complex. Nevertheless, traditional psychometric issues concerning the validity, reliability, and measurement bias of such assessments remain fundamental in determining whether score inferences of human attributes are…
Descriptors: Psychometrics, Computer Assisted Testing, Adaptive Testing, Data
Taylor, Kevin – Education and Culture, 2022
For Dewey, growth in the educative process means education that enriches and expands one's experience as it prepares students for not only a vocation but also entry into and transaction with the world. In few places can we see growth, generally understood, to be occurring as fast as in big data technology. This essay begins with an overview of…
Descriptors: Educational Philosophy, Educational Development, Technology Uses in Education, Learning Analytics
Arastoopour Irgens, Golnaz; Adisa, Ibrahim; Bailey, Cinamon; Vega Quesada, Hazel – Educational Technology & Society, 2022
As big data algorithm usage becomes more ubiquitous, it will become critical for all young people, particularly those from historically marginalized populations, to have a deep understanding of data science that empowers them to enact change in their local communities and globally. In this study, we explore the concept of critical machine…
Descriptors: Artificial Intelligence, Children, Algorithms, After School Programs
Yao, Yuling; Vehtari, Aki; Gelman, Andrew – Grantee Submission, 2022
When working with multimodal Bayesian posterior distributions, Markov chain Monte Carlo (MCMC) algorithms have difficulty moving between modes, and default variational or mode-based approximate inferences will understate posterior uncertainty. And, even if the most important modes can be found, it is difficult to evaluate their relative weights in…
Descriptors: Bayesian Statistics, Computation, Markov Processes, Monte Carlo Methods