GaTO: An Ontological Model to Apply Gamification in Intelligent Tutoring Systems

Dermeval, Diego; Albuquerque, Josmário; Bittencourt, Ig Ibert; Isotani, Seiji; Silva, Alan Pedro da; Vassileva, Julita

doi:10.3389/frai.2019.00013

Cited by 23 publications

(9 citation statements)

References 48 publications

(99 reference statements)

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“…An ontology-driven method for an ITS was developed by Dermeval et al [14]. The goal was to develop a gamification module in an ITS by connecting concepts in a standard and formalized manner.…”

Section: Intelligent Tutoring Systems and Psychomotor Trainingmentioning

confidence: 99%

OntoStrength: An Ontology for Psychomotor Strength Development

Neagu¹,

Rigaud²,

Guarnieri³

et al. 2022

IxD&A

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An ontology is a formal, explicit description of concepts and relations from a domain while considering underlying properties, restrictions, and instances.With the advancement of the Semantic Web, the rise of the Educational Semantic Web, and the lack of uniformity between approaches for knowledge representation, ontologies are becoming more and more popular, including adaptive learning environments such as the Intelligent Tutoring Systems (ITSs). OntoStrength is an ontology developed to support the Selfit ITS, a platform that aims to improve the fundamental human psychomotor skills and, more specifically, bio-motor strength abilities. The goal of Selfit is to prevent the negative consequences of a sedentary lifestyle and accidents involving inadequate strength skills. Most ontologies in the sports domain support the development of digital solutions for sports performance and data collected during competitions. In contrast, OntoStrength’s goal is to contribute to the development of digital solutions dedicated to bio-motor strength ability analysis. OntoStrength considers other bio-motor skills like speed, endurance, or flexibility, as well as other activities like muscle analysis, movement patterns, or training load management, to support sport, professional and daily-life activities. OntoStrength enables the personalization of strength development programs in the Selfit ITS by providing a comprehensive data layer for its student, domain, and tutoring models.

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Section: Intelligent Tutoring Systems and Psychomotor Trainingmentioning

confidence: 99%

OntoStrength: An Ontology for Psychomotor Strength Development

Neagu¹,

Rigaud²,

Guarnieri³

et al. 2022

IxD&A

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“…Concerning ontologies in gamification domain, we can mention three recent works, namely the OntoGamif (Bouzidi et al, 2018), OntoGaCLeS (Chalco & Isotani, 2019) and GaTO (Dermeval, Albuquerque, et al, 2019) ontologies. The first work deals with a modular ontology for the gamification domain, covering the users, organizational structures, ethical issues, and psychological factors.…”

Section: Ontologies and Gamificationmentioning

confidence: 99%

“…The second ontology formalizes the representation of gamification concepts and explains how they affect motivation in collaborative learning contexts (Chalco & Isotani, 2019). The third ontology connects concepts of gamification with concepts of intelligent tutoring systems (ITS), allowing automated reasoning to enable interoperability and the creation of awareness about theories and good practices for the designers of gamified ITS (Dermeval, Albuquerque, et al, 2019).…”

Section: Ontologies and Gamificationmentioning

confidence: 99%

An ontology for modelling user’ profiles and activities in gamified education

Palomino¹,

Toda²,

Rodrigues³

et al. 2022

RPTEL

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Gamification studies in the educational domain usually focus on motivating students to increase their learning performance by enhancing their motivation. Classifications of behavioural profiles are often used for this (referred to as “gamer” or “user types”), which support the personalization of students’ experiences. These classifications consider these profiles from gamers’ or non-gamers’ points of view. However, within education research, it is necessary to broadly inspect these behavioural profiles to create an instructional design based on learners’ intrinsic drivers and motivations. The relationship between these concepts is subjective, complex, and difficult to categorize, demanding research to bridge this gap. Therefore, in this article we present the design and evaluation of an application ontology that seeks to represent relationships between Jung’s archetypes (e.g., the Hero, the Outlaw and others) adapted for educational purposes, creating a new approach for modelling user profiles, a taxonomy of game elements specific for use in educational contexts, and Bloom’s revised taxonomy to classify learning activities types. This ontology enables personalized and instructional designs directly related to the learning activity type for students. We demonstrate that the proposed ontology can help create better gamification designs to support learning, and we envision it to be used both to create unplugged gamification strategies and personalized gamified educational systems.

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“…Rani et al [41] proposed an ontology-driven adaptive tutoring system based on the Felder-Silverman learning style model. Dermeval et al [42] proposed an ontological model to connect gamification and ITS concepts. The ontology has been manually developed following the Methontology methodology [43].…”

Section: Related Workmentioning

confidence: 99%

Building Ontology-Driven Tutoring Models for Intelligent Tutoring Systems Using Data Mining

et al. 2020

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Pedagogical (Tutor or Tutoring) Models are an important element of Intelligent Tutoring Systems (ITS) and they can be described by sets of (tutoring) rules. The implementation of a Tutoring Model includes both the formal representation of the aforementioned rules and a mechanism able to interpret such representation and execute the rules. One of the most suitable approaches to formally represent pedagogical rules is to construct semantic web ontologies that are highly interoperable and can be integrated with other models in an ITS like the subject domain and the student model. However, the main drawback of semantic web-based approaches is that they require a considerable human effort to prepare and build relevant ontologies. This paper proposes a novel approach to maintain the benefits of the semantic web-based approach in representing pedagogical rules for an ITS, while overcoming its main drawback by employing a data mining technique to automatically extract rules from real-world tutoring sessions and represent them by means of Web Ontology Language (OWL). INDEX TERMS Classification rule mining, intelligent tutoring systems, ontologies, pedagogical rules, semantic web, web ontology language (OWL).

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GaTO: An Ontological Model to Apply Gamification in Intelligent Tutoring Systems

Cited by 23 publications

References 48 publications

OntoStrength: An Ontology for Psychomotor Strength Development

OntoStrength: An Ontology for Psychomotor Strength Development

An ontology for modelling user’ profiles and activities in gamified education

Building Ontology-Driven Tutoring Models for Intelligent Tutoring Systems Using Data Mining

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