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Limeng Wu; Tong Li – SAGE Open, 2025
While the significant impact of faculty feedback on student learning is well recognized, the intricate link between the quality of faculty feedback and students' deep approaches to learning, especially in the context of general education, has yet to be clarified. Employing a mixed-methods approach, this study examined the relationship between…
Descriptors: College Faculty, Feedback (Response), Educational Quality, General Education
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Maurizio Costabile; Connie Caruso; Chris Della Vedova; Sheree Bailey; Layla Mahdi – Advances in Physiology Education, 2025
Science, technology, engineering, and mathematics (STEM) students are typically taught content delivered didactically and closely aligned with the laboratory demonstration of concepts, which facilitates the development of experimental skills. Because of the volume of content delivered across multiple courses, student cognitive abilities can be…
Descriptors: Computer Simulation, Computer Software, Learning Processes, Laboratory Training
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Robin Samuelsson – British Journal of Educational Technology, 2025
Programming is becoming a key subject in early education globally, with surging problems of how computer science can become a subject for children of all ages and backgrounds. Problems of implementing new technologies in the old curricula have long been noted, and lately, concern over computer science education goals is often too narrow and…
Descriptors: Computer Science Education, Play, Early Childhood Education, Technology Integration
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Ronnel B. King; Faming Wang – British Journal of Educational Psychology, 2025
Background: Past studies on mindsets have mostly examined them as an individual difference variable. However, the mindset-by-context framework argues that mindsets do not occur within a vacuum, and their successful implementation depends on the social context. One of the most important social contexts for students is the socioeconomic conditions…
Descriptors: Socioeconomic Status, Advantaged, Student Development, Student Attitudes
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Liangliang Xia; Kexin Shen; Herui Sun; Xin An; Yan Dong – Education and Information Technologies, 2025
While generative artificial intelligence (AI) empowers students in their learning, it may also have the potential to undermine their learning agency. Understanding student learning agency in the generative AI-supported contexts (SLA-GAI) has become critical for educators. However, student learning agency is a domain-specific construct, current…
Descriptors: Artificial Intelligence, Technology Uses in Education, Test Construction, Test Validity
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Guoqian Luo; Hengnian Gu; Xiaoxiao Dong; Dongdai Zhou – Education and Information Technologies, 2025
In the realm of e-learning, supporting personalized learning effectively necessitates recommending sequences of learning items that maximize learning efficiency while minimizing cognitive load, all tailored to the learner's goals. These recommendations must account for the prerequisite relationships among learning items and the learner's…
Descriptors: Electronic Learning, Individualized Instruction, Sequential Learning, Learning Processes
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Yuchen Pan; Wenbin Xu; Yunxian Chen; Nana Huang; Yang Wang – Psychology in the Schools, 2025
At the beginning of the 21st century, "number sense" was listed as one of the core words in the mathematics curriculum of compulsory education in China, and it has now become one of the core competencies of primary school mathematics. It is necessary to determine the development of number sense of first-grade primary school students (6-7…
Descriptors: Grade 1, Numeracy, Elementary School Students, Mathematics Curriculum
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Ying-Lien Lin; Wei-Tsong Wang; Zhi-Lun Lai – Education and Information Technologies, 2025
Although some studies have examined the effects of self-regulated learning (SRL) strategies on learning effectiveness, inconsistent results have been reported. Additionally, studies that adopt the perspective of SRL to evaluate the effect of metacognitive skills on students' actual learning effectiveness in digital game-based learning (DGBL)…
Descriptors: Prior Learning, Metacognition, Game Based Learning, Learning Strategies
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Stephen Ferrigno; Samuel J. Cheyette; Susan Carey – Cognitive Science, 2025
Complex sequences are ubiquitous in human mental life, structuring representations within many different cognitive domains--natural language, music, mathematics, and logic, to name a few. However, the representational and computational machinery used to learn abstract grammars and process complex sequences is unknown. Here, we used an artificial…
Descriptors: Sequential Learning, Cognitive Processes, Knowledge Representation, Training
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Sonja Dieterich; Stefan Rumann; Marc Rodemer – Educational Psychology Review, 2025
Example-based learning is a well-known instructional method for effective cognitive skill acquisition in complex domains. "(Contrasting) erroneous examples" are a promising extension that embed errors in instructional material, potentially fostering not only positive but negative knowledge. However, the mechanisms and conditions for…
Descriptors: Learning Processes, Teaching Methods, Instructional Effectiveness, Models
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Ching-Huei Chen; Victor Law – Educational Technology Research and Development, 2025
This study explores the roles of students' help-seeking profiles when seeking help from AI chatbots, specifically ChatGPT, in a digital game-based learning environment, "Summon of Magicrystal." The study involved 102 middle school students who played an online game with the provision of ChatGPT and sought help from ChatGPT while solving…
Descriptors: Help Seeking, Game Based Learning, Artificial Intelligence, Computer Software
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Robert A. Ellis; Feifei Han; David Kember; Si Fan – Review of Education, 2025
There has been ongoing research into qualitative differentiation of university student learning outcomes but limited attempts to explain the extent to which material elements such as learning technologies contribute to these differences. A theory of materiality for the university student experience is essential if teachers are to design and teach…
Descriptors: Universities, College Administration, Instructional Leadership, Educational Technology
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Andreas Lachner; Heike Russ; Nicolas Hübner; Leonie Sibley; Katharina Scheiter – Educational Psychology Review, 2025
Non-interactive teaching, in which students explain previously learned content to a non-present peer, is a generative learning activity that has gained increasing attention in recent years. While meta-analyses indicate small-to-moderate benefits, findings have been inconsistent, suggesting that its effectiveness depends on contextual factors.…
Descriptors: Learning Processes, Student Characteristics, Teaching Methods, Learning Activities
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Suparti Suparti; Milawati Milawati; Abdul Kholiq – Educational Process: International Journal, 2025
Background/purpose: This study aims to analyze the application and impact of dynamic assessment as an enhancement of deep learning in writing narratives for elementary school students. The main focus is DA can improve the quality of the learning process and outcomes through intervention, feedback, and reflective revision. Materials/methods: This…
Descriptors: Elementary School Students, Grade 6, Alternative Assessment, Writing Instruction
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Adrienne Kitchin; Nancy Taber – Canadian Journal for the Study of Adult Education, 2025
In this article, we discuss the learning processes of our feminist fiction-based research, which makes visible the often forgotten and essentialized stories of Toronto-based women World War II workers. We describe this gendered war work through the lenses of intersectional feminism and feminist antimilitarism. We detail the power of fiction-based…
Descriptors: Educational Research, Adult Education, Feminism, Learning Processes
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