Guerreiro-Santalla, SaraDuraes, Dalila ACrompton, HelenNovais, PauloBellas, Francisco2024-01-172023-12-15Guerreiro-Santalla, S., Duraes, D., Crompton, H., Novais, P., Bellas, F. (2023). Simulation-Based Adaptive Interface for Personalized Learning of AI Fundamentals in Secondary School. In: Moniz, N., Vale, Z., Cascalho, J., Silva, C., Sebastião, R. (eds) Progress in Artificial Intelligence. EPIA 2023. Lecture Notes in Computer Science(), vol 14115. Springer, Cham. https://doi.org/10.1007/978-3-031-49008-8_1978-3-031-49007-1http://hdl.handle.net/2183/34954This version of the conference paper has been accepted for publication, and is subject to Springer Nature’s AM terms of use, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: http:// dx.doi.org/10.1007/978-3-031-49008-8_1[Abstract]: This paper presents the first results on the validation of a new Adaptive E-learning System, focused on providing personalized learning to secondary school students in the field of education about AI by means of an adaptive interface based on a 3D robotic simulator. The prototype tool presented here has been tested at schools in USA, Spain, and Portugal, obtaining very valuable insights regarding the high engagement level of students in programming tasks when dealing with the simulated interface. In addition, it has been shown the system reliability in terms of adjusting the students’ learning paths according to their skills and competences in an autonomous fashion.engSpringer Nature’s AM terms of use https://www.springernature.com/gp/open-research/policies/accepted-manuscript-termsAdaptive e-learningIntelligent tutoring systemPersonalized learningAdaptive interfacesAI educationRobot simulationconference outputopen accesshttps://doi.org/10.1007/978-3-031-49008-8_1