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Alex Quigley – Routledge, Taylor & Francis Group, 2024
It is a truth universally acknowledged that pupils do not learn all that they are taught. They may learn something, they may even learn a lot, but it may not be a lot of what we think we have taught them or they may struggle to apply knowledge successfully. In this book, bestselling author Alex Quigley characterises how the long and winding road…
Descriptors: Learning, Success, Failure, Memory
Panayiota Kendeou – Educational Psychology Review, 2024
In this paper, I discuss the inspiration, development, and further refinement of the Knowledge Revision Components framework (KReC; Kendeou & O'Brien, 2014). In KReC, we theorize about the conditions that facilitate knowledge revision during reading, and thus successful learning in the presence of prior, often incorrect knowledge. I discuss…
Descriptors: Knowledge Level, Reading, Prior Learning, Information Literacy
Tina Seufert; Verena Hamm; Andrea Vogt; Valentin Riemer – Educational Psychology Review, 2024
Self-regulated learning depends on task difficulty and on learners' resources and cognitive load, as described by an inverted U-shaped relationship in Seufert's (2018) model: for easy tasks, resources are high and load is low, so there is no need to regulate, whereas for difficult tasks, load is too high and resources are too low to regulate. Only…
Descriptors: Cognitive Processes, Difficulty Level, Resources, Self Management
Xiao, Yiqi; Jiang, Chenhan – International Journal of Technology and Design Education, 2023
Social design produces strategic, systematic solutions or new cultures as a response to the complexity of social changes and, in consequence, designers who are used to the traditional way of ideation may not be well prepared for the requirements of social design. This paper identified the characteristics of the concept generation of industrial…
Descriptors: Industrial Arts, Design, Concept Formation, Prior Learning
Yasuhiro Yamamoto; Yasuo Miyazaki – Journal of Experimental Education, 2025
Bayesian methods have been said to solve small sample problems in frequentist methods by reflecting prior knowledge in the prior distribution. However, there are dangers in strongly reflecting prior knowledge or situations where much prior knowledge cannot be used. In order to address the issue, in this article, we considered to apply two Bayesian…
Descriptors: Sample Size, Hierarchical Linear Modeling, Bayesian Statistics, Prior Learning
Joyce B. Main; Christina Pantoja; Susan M. Lord; Catherine Mobley; Catherine Brawner – Journal of Engineering Education, 2025
Background: In the United States, there is increased demand to expand the engineering workforce. Many military veterans have received technical training that can be leveraged in engineering. Their pursuit of engineering degrees has great potential to expand and diversify the engineering workforce. Purpose: This study examines the pathways of US…
Descriptors: Engineering Education, Veterans, Prior Learning, High School Graduates
Adrienne Mueller; Johannes Konert; René Röpke; Ömer Genc; Henrik Bellhäuser – Journal of Computing in Higher Education, 2025
The study investigates how the 2×2 configuration of homogeneous and heterogeneous distributions of extraversion and prior knowledge influences group outcomes, including satisfaction, performance, and stability. Based on the standard deviation of extraversion and prior knowledge, groups were established to test experimentally, what form of grouping…
Descriptors: Extraversion Introversion, Prior Learning, Online Courses, Heterogeneous Grouping
Sheridan Reilly; Lynn Sheridan; Elise van der Jagt – International Journal of Lifelong Education, 2025
Pre-university mathematics enabling courses can potentially change adult learners' perceptions and beliefs around mathematics, enhance self-efficacy, personal confidence, motivation, and enable achievements that support future study and career goals. Enabling courses, however, often require highly individualised curricula and approaches that can…
Descriptors: Adult Students, Mathematics Instruction, Adult Learning, Self Esteem
Tulay Senel Coruhlu; Muammer Calik; Sibel Er Nas; Salih Cepni; Cevriye Ergul; Seyma Kurt Almali – Asia Pacific Education Review, 2025
This study aimed to investigate the effects of the prediction-observation-explanation (POE) strategy using worksheets designed for the "living things and life" topic on conceptual understanding and science process skills (SPS) of students with mild intellectual disabilities (SMIDs). The sample consisted of 12 SMIDs (eight students for…
Descriptors: Students with Disabilities, Intellectual Disability, Scientific Concepts, Science Education
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
Federick Ngo – Education Economics, 2024
As a result of systemic barriers, undocumented immigrants are more likely to enroll in community colleges and to enter these institutions with higher prior academic achievement than their peers. I explore the potential spillover benefits of this hyperselection on other students using data from a large community college system and two…
Descriptors: Undocumented Immigrants, Community Colleges, Barriers, College Enrollment
Johan Lind; Eva Davidsson; Mats Lundström – International Journal of Technology and Design Education, 2024
Research on students' perceptions and understanding of technology has shown that students have a narrow view of technology: for example, technology is often manifested in students' descriptions as artefacts or objects. This study investigates the ways in which students' understanding of how technology is manifested expands during a series of…
Descriptors: Elementary School Students, Knowledge Level, Technology, Photography
Brittany N. Kester – ProQuest LLC, 2024
With over 1 million international students enrolling in US colleges and universities every year and the continued expansion of available information, including the spread of mis- and dis-information, it is essential that students be information literate and know how to effectively search for, critically evaluate, and produce information.…
Descriptors: Graduate Students, Foreign Students, Asians, Student Experience
Daniela Kocanova; Anna Horváth – European Education and Culture Executive Agency, European Commission, 2024
This report investigates whether higher education systems across Europe recognise and validate learning outcomes from non-formal and informal learning. Specifically, the report looks at whether non-formal and informal learning can enable alternative access to higher education; the extent to which non-formal and informal learning can contribute to…
Descriptors: Foreign Countries, Higher Education, Prior Learning, Nonformal Education
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

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