Intelligent Tutoring System in Archaeology

ID: 54875 Type: Virtual Paper
  1. Laia Subirats and Santiago Fort, Eurecat - Centre Tecnològic de Catalunya, Spain
  2. Cristo Hernández, Universidad de La Laguna, Spain
  3. Leopoldo Pérez, IPHES - Institut Català de Paleoecologia Humana i Evolució Social and Universitat Rovira i Virgili, Spain
  4. Mikko Vesisenaho, Tuula Nousiainen, Marika Peltonen, and Iryna Miakush, University of Jyväskylä, Finland
  5. G M Sacha, Universidad Autónoma de Madrid, Spain

Abstract: A method that uses artificial intelligence for the taxonomical characterization of bone remains in archaeological sites is shown. The main goal of this method is to help students and archaeologists in the classification of samples in order to improve the efficiency of their tasks during the campaigns at archaeological sites. The development of the system implies several steps: training of classification algorithms, development of a user-friendly interface and implementation of gamification techniques to improve learning motivation and the efficiency of the system in the learning process. This system will help archaeology students to classify new samples. In this prototype, by introducing characteristics of a sample, the system answers with a possible animal “Family” related to the sample. This answer can be used by archaeologists as a first clue to determine the species recovered, or by students as additional information to help them in their learning process and self-regulation learning phase.

Topics

Conference attendees are able to comment on papers, view the full text and slides, and attend live presentations. If you are an attendee, please login to get full access.