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Automata Tutor v3

Computer science class enrollments have rapidly risen in the past decade. With current class sizes, standard approaches to grading and providing personalized feedback are no longer possible and new techniques become both feasible and necessary. In this paper, we present the third version of Automata...

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Autores principales: D’Antoni, Loris, Helfrich, Martin, Kretinsky, Jan, Ramneantu, Emanuel, Weininger, Maximilian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7363205/
http://dx.doi.org/10.1007/978-3-030-53291-8_1
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author D’Antoni, Loris
Helfrich, Martin
Kretinsky, Jan
Ramneantu, Emanuel
Weininger, Maximilian
author_facet D’Antoni, Loris
Helfrich, Martin
Kretinsky, Jan
Ramneantu, Emanuel
Weininger, Maximilian
author_sort D’Antoni, Loris
collection PubMed
description Computer science class enrollments have rapidly risen in the past decade. With current class sizes, standard approaches to grading and providing personalized feedback are no longer possible and new techniques become both feasible and necessary. In this paper, we present the third version of Automata Tutor, a tool for helping teachers and students in large courses on automata and formal languages. The second version of Automata Tutor supported automatic grading and feedback for finite-automata constructions and has already been used by thousands of users in dozens of countries. This new version of Automata Tutor supports automated grading and feedback generation for a greatly extended variety of new problems, including problems that ask students to create regular expressions, context-free grammars, pushdown automata and Turing machines corresponding to a given description, and problems about converting between equivalent models - e.g., from regular expressions to nondeterministic finite automata. Moreover, for several problems, this new version also enables teachers and students to automatically generate new problem instances. We also present the results of a survey run on a class of 950 students, which shows very positive results about the usability and usefulness of the tool.
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spelling pubmed-73632052020-07-16 Automata Tutor v3 D’Antoni, Loris Helfrich, Martin Kretinsky, Jan Ramneantu, Emanuel Weininger, Maximilian Computer Aided Verification Article Computer science class enrollments have rapidly risen in the past decade. With current class sizes, standard approaches to grading and providing personalized feedback are no longer possible and new techniques become both feasible and necessary. In this paper, we present the third version of Automata Tutor, a tool for helping teachers and students in large courses on automata and formal languages. The second version of Automata Tutor supported automatic grading and feedback for finite-automata constructions and has already been used by thousands of users in dozens of countries. This new version of Automata Tutor supports automated grading and feedback generation for a greatly extended variety of new problems, including problems that ask students to create regular expressions, context-free grammars, pushdown automata and Turing machines corresponding to a given description, and problems about converting between equivalent models - e.g., from regular expressions to nondeterministic finite automata. Moreover, for several problems, this new version also enables teachers and students to automatically generate new problem instances. We also present the results of a survey run on a class of 950 students, which shows very positive results about the usability and usefulness of the tool. 2020-06-16 /pmc/articles/PMC7363205/ http://dx.doi.org/10.1007/978-3-030-53291-8_1 Text en © The Author(s) 2020 Open Access This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made. The images or other third party material in this chapter are included in the chapter's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.
spellingShingle Article
D’Antoni, Loris
Helfrich, Martin
Kretinsky, Jan
Ramneantu, Emanuel
Weininger, Maximilian
Automata Tutor v3
title Automata Tutor v3
title_full Automata Tutor v3
title_fullStr Automata Tutor v3
title_full_unstemmed Automata Tutor v3
title_short Automata Tutor v3
title_sort automata tutor v3
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7363205/
http://dx.doi.org/10.1007/978-3-030-53291-8_1
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