Publication Date
In 2025 | 2 |
Since 2024 | 9 |
Since 2021 (last 5 years) | 48 |
Since 2016 (last 10 years) | 137 |
Since 2006 (last 20 years) | 324 |
Descriptor
Models | 476 |
Prior Learning | 476 |
Foreign Countries | 110 |
Teaching Methods | 99 |
Higher Education | 83 |
Cognitive Processes | 67 |
Knowledge Level | 57 |
Learning Processes | 51 |
Science Instruction | 48 |
Problem Solving | 47 |
College Students | 46 |
More ▼ |
Source
Author
Publication Type
Education Level
Location
Australia | 13 |
Germany | 7 |
Netherlands | 7 |
United Kingdom | 7 |
Pennsylvania | 6 |
Texas | 6 |
Illinois | 5 |
Norway | 5 |
Turkey | 5 |
United States | 5 |
Wisconsin | 5 |
More ▼ |
Laws, Policies, & Programs
No Child Left Behind Act 2001 | 1 |
Assessments and Surveys
What Works Clearinghouse Rating
Meets WWC Standards without Reservations | 1 |
Meets WWC Standards with or without Reservations | 1 |
Does not meet standards | 1 |
Alicia M. Chen; Andrew Palacci; Natalia Vélez; Robert D. Hawkins; Samuel J. Gershman – Cognitive Science, 2024
How do teachers learn about what learners already know? How do learners aid teachers by providing them with information about their background knowledge and what they find confusing? We formalize this collaborative reasoning process using a hierarchical Bayesian model of pedagogy. We then evaluate this model in two online behavioral experiments (N…
Descriptors: Bayesian Statistics, Models, Teaching Methods, Evaluation
Andrea 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
de Jong, Bastian; Jansen in de Wal, Joost; Cornelissen, Frank; van der Lans, Rikkert; Peetsma, Thea – International Journal of Training and Development, 2023
Transfer motivation is an important factor influencing transfer of training. However, earlier research often did not investigate transfer motivation as a multidimensional construct. The unified model of task-specific motivation (UMTM) takes into account that (transfer) motivation is multidimensional by including both affective and cognitive…
Descriptors: Informed Consent, Transfer of Training, Prediction, Models
Gorney, Kylie; Wollack, James A. – Journal of Educational Measurement, 2022
Detection methods for item preknowledge are often evaluated in simulation studies where models are used to generate the data. To ensure the reliability of such methods, it is crucial that these models are able to accurately represent situations that are encountered in practice. The purpose of this article is to provide a critical analysis of…
Descriptors: Prior Learning, Simulation, Models, Reaction Time
Gleiman, Ashley – Journal of Continuing Higher Education, 2023
Prior Learning Assessment (PLA) programs are unique to the institution and the students they serve. While a variety of best practices persist, the need for academically rigorous and credible programs is ever-present as institutions evolve to keep up with the growing needs of adult learners today. This article provides a case study overview of…
Descriptors: Prior Learning, Portfolio Assessment, Best Practices, Adult Learning
Roee Peretz; Natali Levi-Soskin; Dov Dori; Yehudit Judy Dori – IEEE Transactions on Education, 2024
Contribution: Model-based learning improves systems thinking (ST) based on students' prior knowledge and gender. Relations were found between textual, visual, and mixed question types and student achievements. Background: ST is essential to judicious decision-making and problem-solving. Undergraduate students can be taught to apply better ST, and…
Descriptors: Models, Engineering Education, Thinking Skills, Systems Approach
Zhang, Qian; Fiorella, Logan – Educational Psychologist, 2023
Errors are inevitable in most learning contexts, but under the right conditions, they can be beneficial for learning. Prior research indicates that generating and learning from errors can promote retention of knowledge, higher-level learning, and self-regulation. The present review proposes an integrated theoretical model to explain two major…
Descriptors: Models, Error Correction, Learning Processes, Feedback (Response)
Mao, Shun; Zhan, Jieyu; Wang, Yizhao; Jiang, Yuncheng – IEEE Transactions on Learning Technologies, 2023
For offering adaptive learning to learners in intelligent tutoring systems, one of the fundamental tasks is knowledge tracing (KT), which aims to assess learners' learning states and make prediction for future performance. However, there are two crucial issues in deep learning-based KT models. First, the knowledge concepts are used to predict…
Descriptors: Intelligent Tutoring Systems, Learning Processes, Prediction, Prior Learning
Durak, Benzegul; Topçu, Mustafa Sami – Science Activities: Projects and Curriculum Ideas in STEM Classrooms, 2023
Recent research suggests that integrating model-based learning and socioscientific issue based instruction helps students construct meaningful learning in science classrooms. Thus, this paper presents a unit plan that integrates model-based learning and socioscientific issues. The focus of the unit is the white butterfly which is a local pest. A…
Descriptors: Science and Society, Models, Science Instruction, Middle School Students
Ghudkam, Supachai; Chatwattana, Pinanta; Piriyasurawong, Pallop – Higher Education Studies, 2023
An imagineering learning model using advance organizers with the internet of things was developed to promote creative innovation for learners in the 21st century. It is an innovation initiated by integrating classroom learning and technology that connects with the internet of things. The objectives of this research were (1) to study and synthesize…
Descriptors: Advance Organizers, Models, Imagination, Problem Solving
Löhr, Guido; Michel, Christian – Cognitive Science, 2022
We propose a cognitive-psychological model of linguistic intuitions about copredication statements. In copredication statements, like "The book is heavy and informative," the nominal denotes two ontologically distinct entities at the same time. This has been considered a problem for standard truth-conditional semantics. In this paper, we…
Descriptors: Cognitive Processes, Intuition, Decision Making, Ethics
Dragos Corlatescu; Micah Watanabe; Stefan Ruseti; Mihai Dascalu; Danielle S. McNamara – Grantee Submission, 2023
Reading comprehension is essential for both knowledge acquisition and memory reinforcement. Automated modeling of the comprehension process provides insights into the efficacy of specific texts as learning tools. This paper introduces an improved version of the Automated Model of Comprehension, version 3.0 (AMoC v3.0). AMoC v3.0 is based on two…
Descriptors: Reading Comprehension, Models, Concept Mapping, Graphs
D. R. E. Cotton; S. Bloxham; S. Cooper; J. Downey; M. Fornasiero – Journal of Further and Higher Education, 2024
Knowledge exchange (KE) is increasingly important in higher education internationally, yet relatively little attention has been paid to it as a pedagogic opportunity for students. This paper draws on 26 interviews with stakeholders within and outside HE to develop a model of student-led knowledge exchange as a guide for learning through KE. The…
Descriptors: Higher Education, Stakeholders, Attitudes, Models
Butterfuss, Reese; Kendeou, Panayiota – Educational Psychology Review, 2021
The aim of this paper is two-fold. The first aim is to review the core representational and processing aspects of influential accounts of single-document and multiple-document comprehension with a particular emphasis on how readers negotiate conflicting information during reading. This review provides the groundwork for the second aim--to expand…
Descriptors: Reading Comprehension, Cognitive Processes, Conflict, Misconceptions
Butterfuss, Reese; Kendeou, Panayiota – Grantee Submission, 2021
The aim of this paper is two-fold. The first aim is to review the core representational and processing aspects of influential accounts of single-document and multiple-document comprehension with a particular emphasis on how readers negotiate conflicting information during reading. This review provides the groundwork for the second aim--to expand…
Descriptors: Reading Comprehension, Cognitive Processes, Conflict, Misconceptions