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Juliann Sergi McBrayer; Regina Rahimi – School Leadership Review, 2023
This research proposes a new model for Educational Leadership and Teacher Preparation Programs through a "Practitioner-Based Mentor-Teacher Candidate Model", which is intended to be beneficial to both the aspiring school leader as the evaluator and mentor and the preservice teacher as the recipient of the feedback. With the shift to…
Descriptors: Preservice Teachers, Electronic Learning, Online Courses, Observation
Jennie Akerstrom Zumbusch – ProQuest LLC, 2023
This study investigated teacher-driven change efforts. A review of existing literature posits that the current education system is largely driven by top-down mandates, such as the implementation of evidence-based practices generated by large scale and randomized controlled trials. While these approaches provide the field with important knowledge,…
Descriptors: Educational Change, Feedback (Response), Teacher Student Relationship, Accountability
Littman, Erica – ProQuest LLC, 2023
The purpose of this mixed-method study is to examine if teachers are receiving effective feedback from their administrators and what school leaders can do to improve the feedback and coaching they provide. The conceptual framework that supports this study is based upon the research by Romano (2014), Ficke (2020), Tuma et al. (2018), and Nasatir…
Descriptors: Teacher Attitudes, Observation, Feedback (Response), Coaching (Performance)
Abbas, Mohsin; van Rosmalen, Peter; Kalz, Marco – IEEE Transactions on Learning Technologies, 2023
For predicting and improving the quality of essays, text analytic metrics (surface, syntactic, morphological, and semantic features) can be used to provide formative feedback to the students in higher education. In this study, the goal was to identify a sufficient number of features that exhibit a fair proxy of the scores given by the human raters…
Descriptors: Feedback (Response), Automation, Essays, Scoring
Rico-Juan, Juan Ramon; Sanchez-Cartagena, Victor M.; Valero-Mas, Jose J.; Gallego, Antonio Javier – IEEE Transactions on Learning Technologies, 2023
Online Judge (OJ) systems are typically considered within programming-related courses as they yield fast and objective assessments of the code developed by the students. Such an evaluation generally provides a single decision based on a rubric, most commonly whether the submission successfully accomplished the assignment. Nevertheless, since in an…
Descriptors: Artificial Intelligence, Models, Student Behavior, Feedback (Response)
Kylie Gorney; Sandip Sinharay – Educational and Psychological Measurement, 2025
Test-takers, policymakers, teachers, and institutions are increasingly demanding that testing programs provide more detailed feedback regarding test performance. As a result, there has been a growing interest in the reporting of subscores that potentially provide such detailed feedback. Haberman developed a method based on classical test theory…
Descriptors: Scores, Test Theory, Test Items, Testing
Jill Brown; Craig M. McGill – School Leadership & Management, 2025
This study developed a grounded theory model describing how principals manage feedback on their leadership. Our research was conducted through interviews with 12 principals and led to the identification of three distinct phases. In Phase I, 'Feedback Collection', principals choose between formal and informal feedback methods, decide the scope of…
Descriptors: Principals, Feedback (Response), Leadership Qualities, Administrator Effectiveness
Janea J. Thibodeaux; Pierce M. Taylor; Janelle K. Bacotti; Samuel L. Morris – Journal of Applied Behavior Analysis, 2025
Many researchers have evaluated how characteristics of feedback may influence trainee performance, but relatively little attention has been allocated to directly assessing trainee preference for feedback characteristics and its relation to performance. Thus, the primary purpose of this study was to use a within-subject experimental design to…
Descriptors: Undergraduate Students, Feedback (Response), Difficulty Level, Learning Strategies
Emmanuel Fokides; Eirini Peristeraki – Education and Information Technologies, 2025
This research analyzed the efficacy of ChatGPT as a tool for the correction and provision of feedback on primary school students' short essays written in both the English and Greek languages. The accuracy and qualitative aspects of ChatGPT-generated corrections and feedback were compared to that of educators. For the essays written in English, it…
Descriptors: Artificial Intelligence, Error Correction, Feedback (Response), Elementary School Students
Jinglei Yu; Shengquan Yu; Ling Chen – British Journal of Educational Technology, 2025
Video-based teacher online learning enables teachers to engage in reflective practice by watching others' classroom videos, providing peer feedback (PF) and reviewing others' work. However, the quality and reliability of PF often suffer due to variations in teaching proficiency among providers, which limits its usefulness for reviewers. To improve…
Descriptors: Artificial Intelligence, Peer Evaluation, Feedback (Response), Reflection
Mengke Wang; Taotao Long; Na Li; Yawen Shi; Zengzhao Chen – Education and Information Technologies, 2025
Feedback plays an indispensable role in pre-service teachers' microteaching practice. It provides essential information about their microteaching performance, which is of great significance in their reflection and improvement. As AI and teaching analytics advance, feedback is no longer exclusively human-generated. AI technologies are increasingly…
Descriptors: Feedback (Response), Preservice Teachers, Microteaching, Reflection
Suping Yi; Wayan Sintawati; Yibing Zhang – Journal of Computer Assisted Learning, 2025
Background: Natural language processing (NLP) and machine learning technologies offer significant advantages, such as facilitating the delivery of reflective feedback in collaborative learning environments while minimising technical constraints for educators related to time and location. Recently, scholars' interest in reflective feedback has…
Descriptors: Reflection, Feedback (Response), Cooperative Learning, Natural Language Processing
Christoph Bamberg; Sarah Weigelt; Klara Hagelweide – npj Science of Learning, 2025
Learning behavioural responses and adapting them based on feedback is crucial from a young age, continuing to develop into young adulthood. This study examines the development trajectory and contributing factors from childhood to adulthood using a reversal learning paradigm. We tested 202 participants aged 10 to 22 in an online study, where they…
Descriptors: Early Adolescents, Individual Development, Learning, Age Differences
Bell, Sanée – Educational Leadership, 2021
Learning to process feedback wisely is essential to school improvement--and personal growth, writes school principal Sanée Bell. Here, Bell shares hard-won tips for soliciting authentic feedback from staff and, even more important, for organizing, acting on, and reflecting on that feedback.
Descriptors: Empowerment, Leaders, Feedback (Response), Principals
Brent Duckor; Carrie Holmberg – Phi Delta Kappan, 2024
Learning is iterative. It takes time and effort. Real progress in any subject requires we engage, motivate, and support learners as they take next steps to improve their work. Brent Duckor and Carrie Holmberg show how teachers can use progress guides as a formative feedback tool to re-engage and support students where they are, while keeping the…
Descriptors: Learner Engagement, Student Motivation, Feedback (Response), Evaluation