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The Documentational Approach To Didactics (DAD) aims to study teachers' professional development through their interactions with their resources for/from teaching. It has been introduced in the French community of didactics of mathematics…

History and Overview · Mathematics 2021-01-01 Luc Trouche

Motivation: How immature teams can become agile is a question that puzzles practitioners and researchers alike. Scrum is one method that supports agile working. Empirical research on the Scrum Master role remains scarce and reveals…

Software Engineering · Computer Science 2021-02-10 Simone V. Spiegler , Christoph Heinecke , Stefan Wagner

One fundamental goal of learning is preparation for future learning (PFL) and being able to extend acquired skills and problem-solving strategies to different domains and environments. While substantial research has shown that PFL can be…

Human-Computer Interaction · Computer Science 2023-03-28 Mark Abdelshiheed , Mehak Maniktala , Tiffany Barnes , Min Chi

The digital age is changing the role of educators and pushing for a paradigm shift in the education system as a whole. Growing demand for general and specialized education inside and outside classrooms is at the heart of this rising trend.…

Computers and Society · Computer Science 2023-10-12 Tommaso Martorella , Antonio Bucchiarone

We describe theoretical bounds and a practical algorithm for teaching a model by demonstration in a sequential decision making environment. Unlike previous efforts that have optimized learners that watch a teacher demonstrate a static…

Machine Learning · Computer Science 2012-10-19 Thomas J. Walsh , Sergiu Goschin

Background: Pair programming is a well-established and versatile agile practice. Previous research has found it to involve far more different roles than the well-known Driver and Observer/Navigator roles. Pair programming often involves…

Software Engineering · Computer Science 2025-10-30 Linus Ververs , Trang Linh Lam , Lutz Prechelt

Policy advice is a transfer learning method where a student agent is able to learn faster via advice from a teacher. However, both this and other reinforcement learning transfer methods have little theoretical analysis. This paper formally…

Machine Learning · Computer Science 2016-04-15 Yusen Zhan , Haitham Bou Ammar , Matthew E. taylor

Neurodiversity, the paradigm shift away from a pathologization of cognitive difference and towards a celebration of cognitive diversity, in an educational context has important implications on how educators structure their classes and on…

Physics Education · Physics 2025-07-18 Daniel P. Oleynik , Kiley Fridley , Liam G. McDermott

This study examines the impact of a remote laboratory experiment on Physics learning, using a case study approach. Societal advancements over the past century have spurred discussions regarding restructuring the current educational system,…

Physics Education · Physics 2025-01-17 Carlos Antonio da Rocha , Matheus Santos Nogueira

This resource letter intends to provide physics instructors - particularly graduate student teaching assistants - at the introductory university level with a small but representative collection of resources to acquire a familiarity with…

Physics Education · Physics 2025-05-29 Zosia A. C. Krusberg

Through a case study, we demonstrate that teachers can tacitly notice student epistemic framing, and that this noticing can prompt instructor action which tips student framing. Our study is based on video data taken during tutorial sections…

Physics Education · Physics 2020-03-02 Christopher A. F. Hass , Qing X. Ryan , Eleanor C Sayre

Autonomous driving faces challenges in navigating complex real-world traffic, requiring safe handling of both common and critical scenarios. Reinforcement learning (RL), a prominent method in end-to-end driving, enables agents to learn…

Robotics · Computer Science 2026-03-09 Ahmed Abouelazm , Johannes Ratz , Philip Schörner , J. Marius Zöllner

Peer learning is a novel high-level reinforcement learning framework for agents learning in groups. While standard reinforcement learning trains an individual agent in trial-and-error fashion, all on its own, peer learning addresses a…

Machine Learning · Computer Science 2024-05-07 Cedric Derstroff , Mattia Cerrato , Jannis Brugger , Jan Peters , Stefan Kramer

Research on nontraditional laboratory (lab) activities in physics shows that students often expect to verify predetermined results, as takes place in traditional activities. This understanding of what is taking place, or epistemic framing,…

In this paper we explore the theory of communities of practice in the context of a physics college course and in particular the classroom environment of an advanced laboratory. We introduce the idea of elements of a classroom community…

Physics Education · Physics 2015-06-18 Paul W. Irving , Eleanor C. Sayre

Recent advances in natural language processing (NLP) have the ability to transform how classroom learning takes place. Combined with the increasing integration of technology in today's classrooms, NLP systems leveraging question answering…

Computation and Language · Computer Science 2021-06-10 Ananya Ganesh , Martha Palmer , Katharina Kann

Too often, physics students are beset by feelings of failure and isolation rather than experiencing the creative joys of discovery that physics has to offer. This dissertation research was founded on the desire of a teacher to make physics…

Physics Education · Physics 2015-02-17 Ben Van Dusen

The rapid development of artificial intelligence technologies, particularly Large Language Models (LLMs), has revolutionized the landscape of lifelong learning. This paper introduces a conceptual framework for a self-constructed lifelong…

Computers and Society · Computer Science 2024-09-25 Kirill Krinkin , Tatiana Berlenko

There are diverse teaching methodologies to promote both collaborative and individual work in undergraduate physics courses. However, few educational studies seek to understand how students learn and apply new knowledge through open-ended…

Identity teacher forcing (ITF) enables stable training of deterministic recurrent surrogates for chaotic dynamical systems and has been highly effective for dynamical systems reconstruction (DSR) with recurrent neural networks (RNNs),…

Machine Learning · Computer Science 2026-04-29 Andre Herz , Daniel Durstewitz , Georgia Koppe