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Christina Glasauer; Martin K. Yeh; Lois Anne DeLong; Yu Yan; Yanyan Zhuang – Computer Science Education, 2025
Background and Context: Feedback on one's progress is essential to new programming language learners, particularly in out-of-classroom settings. Though many study materials offer assessment mechanisms, most do not examine the accuracy of the feedback they deliver, nor give evidence on its validity. Objective: We investigate the potential use of a…
Descriptors: Novices, Computer Science Education, Programming, Accuracy
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Matthew J. Madison; Stefanie Wind; Lientje Maas; Kazuhiro Yamaguchi; Sergio Haab – Grantee Submission, 2024
Diagnostic classification models (DCMs) are psychometric models designed to classify examinees according to their proficiency or nonproficiency of specified latent characteristics. These models are well suited for providing diagnostic and actionable feedback to support intermediate and formative assessment efforts. Several DCMs have been developed…
Descriptors: Diagnostic Tests, Classification, Models, Psychometrics
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Matthew J. Madison; Stefanie A. Wind; Lientje Maas; Kazuhiro Yamaguchi; Sergio Haab – Journal of Educational Measurement, 2024
Diagnostic classification models (DCMs) are psychometric models designed to classify examinees according to their proficiency or nonproficiency of specified latent characteristics. These models are well suited for providing diagnostic and actionable feedback to support intermediate and formative assessment efforts. Several DCMs have been developed…
Descriptors: Diagnostic Tests, Classification, Models, Psychometrics
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Jiaxian Ye; Lawrence Jun Zhang; Helen Dixon – Assessment in Education: Principles, Policy & Practice, 2025
Student agency is a key feature in feedback practices. Student feedback agency is generally defined as students' active engagement in the feedback process. Its conceptualisation has evolved from individualistic views, through unidirectional structure-agency perspectives, to more socially oriented approaches. However, this commentary argues that…
Descriptors: Personal Autonomy, Feedback (Response), Social Cognition, Students
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Jesús Pérez; Eladio Dapena; Jose Aguilar – Education and Information Technologies, 2024
In tutoring systems, a pedagogical policy, which decides the next action for the tutor to take, is important because it determines how well students will learn. An effective pedagogical policy must adapt its actions according to the student's features, such as knowledge, error patterns, and emotions. For adapting difficulty, it is common to…
Descriptors: Feedback (Response), Intelligent Tutoring Systems, Reinforcement, Difficulty Level
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Vikki Pollard; Christine Armatas – Online Learning, 2025
The Interactive, Constructive, Active, Passive (ICAP) Framework (Chi & Wylie, 2014) is used to review and develop active learning in higher education. It is a hierarchical model based on overt behaviours seen by the teacher in the classroom. This principle is acknowledged as a limitation, especially in the case of online modes of study. In…
Descriptors: Active Learning, Online Courses, Asynchronous Communication, Feedback (Response)
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Youn Seon Lim; Catherine Bangeranye – International Journal of Testing, 2024
Feedback is a powerful instructional tool for motivating learning. But effective feedback, requires that instructors have accurate information about their students' current knowledge status and their learning progress. In modern educational measurement, two major theoretical perspectives on student ability and proficiency can be distinguished.…
Descriptors: Cognitive Measurement, Diagnostic Tests, Item Response Theory, Case Studies
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Nina Vandermeulen; Elke Van Steendam; Sven De Maeyer; Marije Lesterhuis; Gert Rijlaarsdam – Reading and Writing: An Interdisciplinary Journal, 2024
Writing a synthesis text involves interacting reading and writing processes, serving the comprehension of source information, and its integration into a reader-friendly and accurate synthesis text. Mastering these processes requires insight into process' orchestrations. A way of achieving this is via process feedback in which students compare…
Descriptors: Feedback (Response), Observation, Writing Processes, Models
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Carranza Rogerio, Brenda; Yan, Yu; Cooper, Eric Wallace – International Journal of Technology in Education, 2023
The growing integration of technology into education, particularly in the STEM fields, has tended to focus on its objective advantages, ignoring its affective potential. To explore this potential, based on some principles of "Kansei/Affective Engineering," an initial analysis was conducted considering 501 interventions in a conversation…
Descriptors: Affective Behavior, Feedback (Response), STEM Education, Electronic Learning
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
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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)
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Juliette Woodrow; Sanmi Koyejo; Chris Piech – International Educational Data Mining Society, 2025
High-quality feedback requires understanding of a student's work, insights into what concepts would help them improve, and language that matches the preferences of the specific teaching team. While Large Language Models (LLMs) can generate coherent feedback, adapting these responses to align with specific teacher preferences remains an open…
Descriptors: Feedback (Response), Artificial Intelligence, Teacher Attitudes, Preferences
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Lindsay Maffei-Almodovar; Peter Sturmey; Joshua Jessel – Journal of Behavioral Education, 2025
Pyramidal training is an effective model for disseminating behavior analytic skills. However, pyramidal training in research is often conducted in controlled university settings. Further, research that has evaluated the effectiveness of pyramidal training in classroom settings (see Pence et al. 2014) often focuses on improving the use of one…
Descriptors: Functional Behavioral Assessment, Training Methods, Training, Program Effectiveness
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Austin M. Shin; Ayaan M. Kazerouni – ACM Transactions on Computing Education, 2024
Background and Context: Students' programming projects are often assessed on the basis of their tests as well as their implementations, most commonly using test adequacy criteria like branch coverage, or, in some cases, mutation analysis. As a result, students are implicitly encouraged to use these tools during their development process (i.e., so…
Descriptors: Feedback (Response), Programming, Student Projects, Computer Software
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Panadero, Ernesto – Educational Psychologist, 2023
As the articles in this special issue on "Psychological Perspectives on the Effects and Effectiveness of Assessment Feedback" have shown, feedback is a key factor in education. Although there exists a substantial body of research on the topic, it is imperative to continue advancing the field. My aim is to outline five steps to solidify…
Descriptors: Educational Change, Feedback (Response), Educational Research, Models
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