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Kangkang Li; Chengyang Qian; Xianmin Yang – Education and Information Technologies, 2025
In learnersourcing, automatic evaluation of student-generated content (SGC) is significant as it streamlines the evaluation process, provides timely feedback, and enhances the objectivity of grading, ultimately supporting more effective and efficient learning outcomes. However, the methods of aggregating students' evaluations of SGC face the…
Descriptors: Student Developed Materials, Educational Quality, Automation, Artificial Intelligence
Robin Junker; Jennifer Janeczko; Alena Lehmkuhl; Verena Zucker; Manfred Holodynski; Nicola Meschede – Education and Information Technologies, 2025
The adoption of virtual learning environments (VLEs) in education has grown significantly due to their potential to enhance learning. Effective learning in VLEs depends on managing cognitive load and sustaining motivation, particularly for complex tasks like developing teachers' professional vision -- the ability to notice and interpret classroom…
Descriptors: Models, Prompting, Electronic Learning, Computer Simulation
Michelle Cheong – Journal of Computer Assisted Learning, 2025
Background: Increasingly, students are using ChatGPT to assist them in learning and even completing their assessments, raising concerns of academic integrity and loss of critical thinking skills. Many articles suggested educators redesign assessments that are more 'Generative-AI-resistant' and to focus on assessing students on higher order…
Descriptors: Artificial Intelligence, Performance Based Assessment, Spreadsheets, Models
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
Julius Meier; Peter Hesse; Stephan Abele; Alexander Renkl; Inga Glogger-Frey – Instructional Science: An International Journal of the Learning Sciences, 2024
Self-explanation prompts in example-based learning are usually directed backwards: Learners are required to self-explain problem-solving steps just presented ("retrospective" prompts). However, it might also help to self-explain upcoming steps ("anticipatory" prompts). The effects of the prompt type may differ for learners with…
Descriptors: Problem Based Learning, Problem Solving, Prompting, Models
Shin, Jinnie; Gierl, Mark J. – Journal of Applied Testing Technology, 2022
Automated Essay Scoring (AES) technologies provide innovative solutions to score the written essays with a much shorter time span and at a fraction of the current cost. Traditionally, AES emphasized the importance of capturing the "coherence" of writing because abundant evidence indicated the connection between coherence and the overall…
Descriptors: Computer Assisted Testing, Scoring, Essays, Automation
Hardy, Jessica K.; Hemmeter, Mary Louise – Topics in Early Childhood Special Education, 2023
Early math skills predict later academic achievement and are of critical importance in preschool. There also are discrepancies in early math skills of preschoolers with disabilities compared with their typically developing peers. We used an experimental single-case research design, multiple probe across skills, to investigate the effectiveness of…
Descriptors: Preschool Children, Disabilities, Mathematics Skills, Developmental Delays
Deliang Wang; Gaowei Chen – British Journal of Educational Technology, 2025
Classroom dialogue is crucial for effective teaching and learning, prompting many professional development (PD) programs to focus on dialogic pedagogy. Traditionally, these programs rely on manual analysis of classroom practices, which limits timely feedback to teachers. To address this, artificial intelligence (AI) has been employed for rapid…
Descriptors: Classroom Communication, Artificial Intelligence, Technology Uses in Education, Models
Davis, Dennis S.; Jones, Jill S.; Samuelson, Courtney – Reading & Writing Quarterly, 2021
Recent media reports suggest that teachers and teacher educators are using the three-cueing system model to justify an overemphasis on context to help students read unfamiliar words. In this conceptual article, the authors argue that although these critiques are exaggerated, the current climate provides an opportunity for teacher educators to…
Descriptors: Prompting, Word Recognition, Teacher Education, Reading Instruction
Chun-Ying Chen – ACM Transactions on Computing Education, 2025
This study examined the effects of worked examples with different explanation types and novices' motivation on cognitive load, and how this subsequently influenced their programming problem-solving performance. Given the study's emphasis on both instructional approaches and learner motivation, the Cognitive Theory of Multimedia Learning served as…
Descriptors: Models, Learning Motivation, Cognitive Processes, Difficulty Level
Morrison, Ryan – Online Submission, 2022
Large Language Models (LLM) -- powerful algorithms that can generate and transform text -- are set to disrupt language learning education and text-based assessments as they allow for automation of text that can meet certain outcomes of many traditional assessments such as essays. While there is no way to definitively identify text created by this…
Descriptors: Models, Mathematics, Automation, Natural Language Processing
Peter Organisciak; Selcuk Acar; Denis Dumas; Kelly Berthiaume – Grantee Submission, 2023
Automated scoring for divergent thinking (DT) seeks to overcome a key obstacle to creativity measurement: the effort, cost, and reliability of scoring open-ended tests. For a common test of DT, the Alternate Uses Task (AUT), the primary automated approach casts the problem as a semantic distance between a prompt and the resulting idea in a text…
Descriptors: Automation, Computer Assisted Testing, Scoring, Creative Thinking
Brown, Alice; Lawrence, Jill; Basson, Marita; Redmond, Petrea – Higher Education Research and Development, 2022
Student engagement is consistently identified as a key predictor of learner outcomes within the online learning environment. However, there is limited guidance about using proactive strategies to improve engagement for low and non-engaged students: for example by specifically employing course learning analytics (CLA) and nudging strategies in…
Descriptors: Electronic Learning, Learner Engagement, Instructional Improvement, College Instruction
Michelle Pauley Murphy; Woei Hung – Advances in Physiology Education, 2023
A well-developed mental model is crucial for effectively studying physiology core concepts. However, mental models can be difficult for students to represent and for instructors to evaluate and correct. Systems modeling as a visualization cognitive tool may facilitate mental model development. On the other hand, evidence of mental model…
Descriptors: Schemata (Cognition), Scientific Concepts, Physiology, Allied Health Occupations Education
Razvan Paroiu; Stefan Ruseti; Mihai Dascalu; Stefan Trausan-Matu; Danielle S. McNamara – Grantee Submission, 2023
The exponential growth of scientific publications increases the effort required to identify relevant articles. Moreover, the scale of studies is a frequent barrier to research as the majority of studies are low or medium-scaled and do not generalize well while lacking statistical power. As such, we introduce an automated method that supports the…
Descriptors: Science Education, Educational Research, Scientific and Technical Information, Journal Articles

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