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Open AccessArticle

A Granularity-Based Intelligent Tutoring System for Zooarchaeology

1
Eurecat, Centre Tecnològic de Catalunya, C/Bilbao, 72, 08005 Barcelona, Spain
2
Faculty of Computer Science, Multimedia and Telecommunications, Universitat Oberta de Catalunya, Rambla del Poblenou, 156, 08018 Barcelona, Spain
3
IPHES, Institut Català de Paleoecologia Humana i Evolució Social, Zona Educacional 4, Campus Sescelades URV (Edifici W3), 43007 Tarragona, Spain
4
Àrea de Prehistoria, Universitat Rovira i Virgili (URV), Avinguda de Catalunya, 35, 43002 Tarragona, Spain
5
Departamento de Geografía e Historia, Área de Prehistoria (Facultad de Humanidades), Universidad de La Laguna, Campus de Guajara, La Laguna, 38071 Tenerife, Spain
6
Universidad Autónoma de Madrid, Ciudad Universitaria de Cantoblanco, 28049 Madrid, Spain
*
Author to whom correspondence should be addressed.
Appl. Sci. 2019, 9(22), 4960; https://doi.org/10.3390/app9224960
Received: 30 September 2019 / Revised: 9 November 2019 / Accepted: 11 November 2019 / Published: 18 November 2019
(This article belongs to the Special Issue Smart Learning)
This paper presents a tutoring system which uses three different granularities for helping students to classify animals from bone fragments in zooarchaeology. The 3406 bone remains, which have 64 attributes, were obtained from the excavation of the Middle Palaeolithic site of El Salt (Alicante, Spain). The coarse granularity performs a five-class prediction, the medium a twelve-class prediction, and the fine a fifteen-class prediction. In the coarse granularity, the results show that the first 10 most relevant attributes for classification are width, bone, thickness, length, bone fragment, anatomical group, long bone circumference, X, Y, and Z. Based on those results, a user-friendly interface of the tutor has been built in order to train archaeology students to classify new remains using the coarse granularity. A pilot has been performed in the 2019 excavation season in Abric del Pastor (Alicante, Spain), where the automatic tutoring system was used by students to classify 51 new remains. The pilot experience demonstrated the usefulness of the tutoring system both for students when facing their first classification activities and also for seniors since the tutoring system gives them valuable clues for helping in difficult classification problems. View Full-Text
Keywords: supervised learning; zooarchaeology; intelligent tutoring system supervised learning; zooarchaeology; intelligent tutoring system
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MDPI and ACS Style

Subirats, L.; Pérez, L.; Hernández, C.; Fort, S.; Sacha, G.-M. A Granularity-Based Intelligent Tutoring System for Zooarchaeology. Appl. Sci. 2019, 9, 4960. https://doi.org/10.3390/app9224960

AMA Style

Subirats L, Pérez L, Hernández C, Fort S, Sacha G-M. A Granularity-Based Intelligent Tutoring System for Zooarchaeology. Applied Sciences. 2019; 9(22):4960. https://doi.org/10.3390/app9224960

Chicago/Turabian Style

Subirats, Laia; Pérez, Leopoldo; Hernández, Cristo; Fort, Santiago; Sacha, Gomez-Monivas. 2019. "A Granularity-Based Intelligent Tutoring System for Zooarchaeology" Appl. Sci. 9, no. 22: 4960. https://doi.org/10.3390/app9224960

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