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Gregorcic, Bor; Pendrill, Ann-Marie – Physics Education, 2023
We present a case study of a conversation between ourselves and an artificial intelligence-based chatbot ChatGPT. We asked the chatbot to respond to a basic physics question that will be familiar to most physics teachers: 'A teddy bear is thrown into the air. What is its acceleration in the highest point?' The chatbot's responses, while…
Descriptors: Artificial Intelligence, Physics, Science Instruction, Scientific Concepts
Fisher, Isabelle; Costa, Patrícia – Learning Organization, 2023
Purpose: This study aims to explore how individual personal growth initiative (PGI) mediates the relationship between a positive error orientation and job crafting. Furthermore, it explores the moderating role of the feedback from the leader in this relationship. Design/methodology/approach: Data was collected through a survey conducted on 209…
Descriptors: Job Development, Feedback (Response), Leadership, Error Patterns
Gilbert Kereng Pule; Khensane Mkhabela; Amokelo Given Maweya – Journal of Inquiry Based Activities, 2025
This qualitative case study, grounded within the interpretive paradigm, analyzed the errors and misconceptions made by 11th-grade learners when tackling the tangent-chord theorem task in Euclidean geometry. Studying Euclidean geometry helps learners develop critical thinking skills, such as constructing arguments and applying logical reasoning.…
Descriptors: Error Patterns, Misconceptions, Grade 11, High School Students
Pham Sy Nam; Ngoc-Giang Nguyen; Hoa Anh Tuong; Ben Haas; Zsolt Lavicza; Yves Kreis – International Journal for Technology in Mathematics Education, 2023
Problem-based learning puts students in situations that suggest problems without providing instructions and available knowledge. Therefore, when using problem-based learning, students need to be flexible, self-disciplined, active and self-occupied with knowledge and turn the knowledge the teacher intends to impart into their knowledge. For locus…
Descriptors: Computer Software, Mathematics Instruction, Teaching Methods, Problem Based Learning
Eva Viviani; Michael Ramscar; Elizabeth Wonnacott – Cognitive Science, 2024
Ramscar, Yarlett, Dye, Denny, and Thorpe (2010) showed how, consistent with the predictions of error-driven learning models, the order in which stimuli are presented in training can affect category learning. Specifically, learners exposed to artificial language input where objects preceded their labels learned the discriminating features of…
Descriptors: Symbolic Learning, Learning Processes, Artificial Intelligence, Prediction
Yuling Zhuang; AnnaMarie Conner – Mathematical Thinking and Learning: An International Journal, 2024
This study illustrates how two secondary mathematics teachers used students' incorrect answers as they supported students' engagement in collective argumentation. Three ways of supporting argumentation when students contributed incorrect answers are exemplified, and the structures of these arguments are investigated. Then, by focusing on the…
Descriptors: Secondary School Mathematics, Mathematics Teachers, Mathematics Instruction, Teaching Methods
Sideridis, Georgios D.; Jaffari, Fathima – Measurement and Evaluation in Counseling and Development, 2022
The present study describes an R function that implements six corrective procedures developed by Bartlett, Swain, and Yuan in the correction of 21 statistics associated with the omnibus Chi-square test, the residuals, or fit indices in confirmatory factor analysis (CFA) and structural equation modeling (SEM).
Descriptors: Statistical Analysis, Goodness of Fit, Factor Analysis, Structural Equation Models
Olaperi Okuboyejo; Sigrid Ewert; Ian Sanders – ACM Transactions on Computing Education, 2025
Regular expressions (REs) are often taught to undergraduate computer science majors in the Formal Languages and Automata (FLA) course; they are widely used to implement different software functionalities such as search mechanisms and data validation in diverse fields. Despite their importance, the difficulty of REs has been asserted many times in…
Descriptors: Automation, Feedback (Response), Error Patterns, Error Correction
Stanley, T. D.; Doucouliagos, Hristos – Research Synthesis Methods, 2023
Partial correlation coefficients are often used as effect sizes in the meta-analysis and systematic review of multiple regression analysis research results. There are two well-known formulas for the variance and thereby for the standard error (SE) of partial correlation coefficients (PCC). One is considered the "correct" variance in the…
Descriptors: Correlation, Statistical Bias, Error Patterns, Error Correction
Yasar C. Kakdas; Sinan Kockara; Tansel Halic; Doga Demirel – IEEE Transactions on Learning Technologies, 2024
This article presents a 3-D medical simulation that employs reinforcement learning (RL) and interactive RL (IRL) to teach and assess the procedure of donning and doffing personal protective equipment (PPE). The simulation is motivated by the need for effective, safe, and remote training techniques in medicine, particularly in light of the COVID-19…
Descriptors: Medical Education, Error Patterns, Error Correction, Reinforcement
Mehmet Gürbüz; Murat Basar – Reading Psychology, 2025
The purpose of this study is to examine the effect of using the wrongly read and written words in sentences on correcting the reading and writing errors of students with learning disabilities. The study group of this research, which was designed according to the qualitative action research, consisted of 13 second grade students and 7 primary…
Descriptors: Reading Skills, Writing Skills, Error Patterns, Students with Disabilities
Rahel Schmid; Robbert Smit; Nicolas Robin; Alexander Strahl – British Journal of Educational Psychology, 2025
Background: Students make many errors in visual programming. In order to learn from these, it is important that students regulate their emotions and view errors as learning opportunities. Aims: This study aimed to explore to what extent momentary emotions, specifically enjoyment, anxiety and boredom, as well as the error learning orientation of…
Descriptors: Psychological Patterns, Emotional Response, Learning Processes, Error Patterns
Weisberg, Steven M.; Schinazi, Victor R.; Ferrario, Andrea; Newcombe, Nora S. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2023
Relying on shared tasks and stimuli to conduct research can enhance the replicability of findings and allow a community of researchers to collect large data sets across multiple experiments. This approach is particularly relevant for experiments in spatial navigation, which often require the development of unfamiliar large-scale virtual…
Descriptors: Programming, Error Patterns, Computer Simulation, Spatial Ability
Tšhegofatšo P. Makgakga – Pythagoras, 2023
Error analysis is an instructional strategy that can assist teachers to identify learners' areas of weakness in mathematics and that can point to remediation of those errors. This article explores the errors learners exhibit when solving quadratic equations by completing the square using Newman's Error Analysis Model. A research study explored the…
Descriptors: Error Patterns, Mathematics Instruction, Error Correction, Problem Solving
Bei Cai; Ziyu He; Hong Fu; Yang Zheng; Yanjie Song – IEEE Transactions on Learning Technologies, 2025
Much research has applied automated writing evaluation (AWE) systems to English writing instruction; however, understanding how students internalize and apply this feedback to reduce writing errors is difficult, largely due to the personal and private nature of this process. Therefore, this research utilized eye-tracking technology to explore the…
Descriptors: Undergraduate Students, Majors (Students), Writing (Composition), Writing Evaluation

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