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DOI: 10.4230/OASIcs.ICPEC.2026.2

Exploiting Generative AI to Scale up Intelligent Tutoring Systems

Authors: Miguel Ferreira and José Paulo Leal

Published in: OASIcs, Volume 145, 7th International Computer Programming Education Conference (ICPEC 2026)

Abstract

The research described in this paper explores the integration of Generative Artificial Intelligence (GenAI) into Intelligent Tutoring Systems (ITS) with the aim of improving programming education. Specifically, it extends Agni, a web-based programming learning platform, by automating the construction of key ITS components that are traditionally built manually. The methodology leverages Large Language Models (LLMs) to extract programming concepts from educational materials, map their relationships via concept graphs and diagnose specific student knowledge gaps. Additionally, GenAI provides real-time, contextual feedback during programming exercises, mimicking the personalized support typically offered by a human tutor. The work evaluates whether GenAI can effectively replace or augment the manual creation of domain models while preserving the pedagogical benefits of ITS. The obtained results suggest the potential of combining AI with ITS to improve scalability and reduce manual workload.

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Miguel Ferreira and José Paulo Leal. Exploiting Generative AI to Scale up Intelligent Tutoring Systems. In 7th International Computer Programming Education Conference (ICPEC 2026). Open Access Series in Informatics (OASIcs), Volume 145, pp. 2:1-2:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026)

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@InProceedings{ferreira_et_al:OASIcs.ICPEC.2026.2,
  author =	{Ferreira, Miguel and Leal, Jos\'{e} Paulo},
  title =	{{Exploiting Generative AI to Scale up Intelligent Tutoring Systems}},
  booktitle =	{7th International Computer Programming Education Conference (ICPEC 2026)},
  pages =	{2:1--2:14},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-443-7},
  ISSN =	{2190-6807},
  year =	{2026},
  volume =	{145},
  editor =	{Portela, Filipe and Matos, Lu{\'\i}s and Guimar\~{a}es, Tiago},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ICPEC.2026.2},
  URN =		{urn:nbn:de:0030-drops-267390},
  doi =		{10.4230/OASIcs.ICPEC.2026.2},
  annote =	{Keywords: Intelligent Tutoring Systems, Large language Models}
}

Document

DOI: 10.4230/OASIcs.SLATE.2016.15

Automata Serialization for Manipulation and Drawing

Authors: Miguel Ferreira, Nelma Moreira, and Rogério Reis

Published in: OASIcs, Volume 51, 5th Symposium on Languages, Applications and Technologies (SLATE'16) (2016)

Abstract

GUItar is a GPL-licensed, cross-platform, graphical user interface for automata drawing and manipulation, written in C++ and Qt5. This tool offers support for styling, automatic layouts, several format exports and interface with any foreign finite automata manipulation library that can parse the serialized XML or JSON produced. In this paper we describe a new redesign of the GUItar framework and specially the method used to interface GUItar with automata manipulation libraries.

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Miguel Ferreira, Nelma Moreira, and Rogério Reis. Automata Serialization for Manipulation and Drawing. In 5th Symposium on Languages, Applications and Technologies (SLATE'16). Open Access Series in Informatics (OASIcs), Volume 51, pp. 15:1-15:7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)

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@InProceedings{ferreira_et_al:OASIcs.SLATE.2016.15,
  author =	{Ferreira, Miguel and Moreira, Nelma and Reis, Rog\'{e}rio},
  title =	{{Automata Serialization for Manipulation and Drawing}},
  booktitle =	{5th Symposium on Languages, Applications and Technologies (SLATE'16)},
  pages =	{15:1--15:7},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-006-4},
  ISSN =	{2190-6807},
  year =	{2016},
  volume =	{51},
  editor =	{Mernik, Marjan and Leal, Jos\'{e} Paulo and Gon\c{c}alo Oliveira, Hugo},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.SLATE.2016.15},
  URN =		{urn:nbn:de:0030-drops-60209},
  doi =		{10.4230/OASIcs.SLATE.2016.15},
  annote =	{Keywords: automata, serialization, visualization}
}

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Documents authored by Ferreira, Miguel

Exploiting Generative AI to Scale up Intelligent Tutoring Systems

Abstract

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Automata Serialization for Manipulation and Drawing

Abstract

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