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Step Tutor: Supporting Students through Step-by-Step Example-Based Feedback

Annual Conference on Innovation and Technology in Computer Science Education, 2020
Students often get stuck when programming independently, and need help to progress. Existing, automated feedback can help students progress, but it is unclear whether it ultimately leads to learning. We present Step Tutor, which helps struggling students
Wengran Wang   +5 more
semanticscholar   +1 more source

To Tutor or Not to Tutor: That is the Question

2009
Intelligent tutoring systems often rely on interactive tutored problem solving to help students learn math, which requires students to work through problems step-by-step while the system provides help and feedback. This approach has been shown to be effective in improving student performance in numerous studies. However, tutored problem solving may not
Leena M. Razzaq, Neil T. Heffernan
openaire   +1 more source

Peer‐tutoring: what’s in it for the tutor?

Educational Studies, 2010
Drawing on role theory and socio‐constructivist ideas about learning, this study explores how peer‐tutoring can support tutors’ learning. The sample comprised ten 16–17‐year‐old biology tutors, working with twenty‐one 14–15‐year‐old students from a science class over eight weeks.
Jonathan Galbraith, Mark Winterbottom
openaire   +1 more source

Tutor CoPilot: A Human-AI Approach for Scaling Real-Time Expertise

arXiv.org
Generative AI, particularly Language Models (LMs), has the potential to transform real-world domains with societal impact, particularly where access to experts is limited.
Rose E. Wang   +4 more
semanticscholar   +1 more source

Write Tutor

2011 IEEE International Conference on Technology for Education, 2011
The article addresses the technical principles of a new interactive Robotic device, called Write Tutor, and gives an overview of its application. In spite of the various measures and efforts taken in terms of improving literacy rate we still have a major section of the population who are not able to read and write.
Chembian Parthiban, Rishikesan Parthiban
openaire   +1 more source

Unifying AI Tutor Evaluation: An Evaluation Taxonomy for Pedagogical Ability Assessment of LLM-Powered AI Tutors

North American Chapter of the Association for Computational Linguistics
In this paper, we investigate whether current state-of-the-art large language models (LLMs) are effective as AI tutors and whether they demonstrate pedagogical abilities necessary for good AI tutoring in educational dialogues.
Kaushal Kumar Maurya   +3 more
semanticscholar   +1 more source

Peer tutoring and tutor training

Educational Research, 1991
Summary Tutor training is crucial to the effectiveness of peer tutoring programmes, but little research has been undertaken in comparing different types of training. Two studies are reported which explore the relative impact of ‘non‐elaborated’ training in the procedures necessary for carrying out the task, and ‘elaborated’ training in which the ...
Anne‐Marie Barron, Hugh Foot
openaire   +1 more source

Tutoring the tutors: Supporting effective personal tutoring

Active Learning in Higher Education, 2016
The research into personal tutoring in higher education from a tutor’s perspective suggests that tutors lack training in tutoring and may lack clarity as to the purpose and boundaries of the role. This article explores personal tutors’ perceptions of their confidence and competence in relation to personal tutoring and identifies strategies that might ...
openaire   +1 more source

AutoTutor meets Large Language Models: A Language Model Tutor with Rich Pedagogy and Guardrails

ACM Conference on Learning @ Scale
Large Language Models (LLMs) have found several use cases in education, ranging from automatic question generation to essay evaluation. In this paper, we explore the potential of using LLMs to author Intelligent Tutoring Systems.
Sankalan Pal Chowdhury   +2 more
semanticscholar   +1 more source

Tutoring Process in Emotionally Intelligent Tutoring Systems

International Journal of Technology and Educational Marketing, 2014
Research has shown that emotions can influence learning in situations when students have to analyze, reason, make conclusions, apply acquired knowledge, answer questions, solve tasks, and provide explanations. A number of research groups inspired by the close relationship between emotions and learning have been working to develop emotionally ...
openaire   +1 more source

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