Sound of Reason: Using AI to build a Digital Twin after the Kanon of Pythagoras in school settings
This paper presents ongoing work on kanON, an AI-driven EdTech tool designed to foster interactive learning and support Digital Cultural Heritage (DCH) preservation. kanON facilitates the digital reconstruction of the infamous Pythagorean monochord, by allowing users to seamlessly manipulate parameters such as origin (location and epoch), materials, and shape/dimensions. Through the integration of Machine Learning (ML) algorithms, the tool predicts missing archaeological data and generates real-time 3D renderings based on user input, accompanied by corresponding confidence metrics. A mixed-methods (pilot) study was conducted in classroom environments to evaluate its educational impact via quantitative Likert scale assessments and qualitative content analysis of educator feedback. Preliminary results demonstrate high levels of student engagement and reflect positive educator responses, highlighting its potential to enhance the in-class accessibility and understanding of complex historical concepts, as well as to enable the preservation and exploration of cultural artifacts through digital means. Future work will focus on refining kanON and expanding its applicability within both educational and DCH contexts, by introducing the capability of outputting a fully operational digital twin, that integrates mixed reality functionalities. The idea is to enable users to later engage with their (personalized) model dynamically (e.g., readjusting string length and tension), thus allowing them to produce different soundscapes in real-time. This advancement aims to deepen the pedagogical impact by merging tactile interaction with visual and auditory feedback, further enhancing the educational experience via immersive, experiential learning.
Authors
- Alexandros Basiakoulis
- Marianna Efstathiou (ORCID: https://orcid.org/0000-0001-9291-0383)
- Kyriakos Efstathiou (ORCID: https://orcid.org/0009-0002-4562-4725)
- Zach Anthis (ORCID: https://orcid.org/0000-0001-5359-4111)
Institutions
- Cyprus University of Technology (CY)
- Aristotle University of Thessaloniki (GR)
- University College London (GB)
Publication Details
- Published
- 2024-12-02
- DOI
- https://doi.org/10.1109/swc62898.2024.00329
- Citations
- 1
- Primary Topic
- Digital Transformation in Industry
- Type
- article
- Field-Weighted Citation Impact
- 0.35