ע 229 אורית בן שושן ספר הכנס העשרים ואחד לחקר חדשנות וטכנולוגיות למידה ע"ש צ'ייס: האדם הלומד בעידן הדיגיטלי א' בלאו, ד' אולניק - שמש, נ' גרי, א' כספי, י' סידי, י' עשת - אלקלעי, י' קלמן ו נ' ברנדל )עורכים(, רעננה: האוניברסיטה הפתוחה "נוסעים ברצף ברכבת קלה" כלי דיגיטלי מבוסס כלי AI להנגשת רצף הנסיעה ברכבת קלה לצעירים על הרצף האוטיסטי ) פוסטר ( אורית בן שושן מכללת תלפיות Orit957@gmail.com "Light Rail Sequence Travel" a Digital Tool Based on Artificial intelligence Making the Light Rail Sequence Accessible to Young People on the Autism Spectrum (Poster) Orit ben shusan Talpiot College of Education Orit957@gmail.com Abstract Rationale: ndependent travel using public transportation is a crucial skill for autonomy and social integration of young adults transitioning to adulthood. For individuals on the autism spectrum with high functioning levels, light rail travel presents a significant challenge due to difficulties in sequential action planning, spatial orientation, cognitive flexibility, and sensory information processing. Nevertheless, for these young adults, acquiring this skill is not merely a mobility tool, but also a decisive factor in developing independence, expanding employment opportunities, and enabling full social participation (Ravnsborg et al., 2025). Research demonstrates that structured and adapted instruction in action sequences can significantly improve the ability to perform complex daily tasks among individuals on the autism spectrum. Therefore, there is a substantial need to develop accessible digital tools tailored to their unique needs, enabling them to learn and independently execute the light rail travel sequence. The use of artificial intelligence (AI) tools for developing adapted educational content represents an innovative and accessible solution to this challenge, allowing for the creation of personalized learning materials and continuous support throughout the learning process (Valencia et al., 2019). Research goals: To examine the effectiveness of an AI-based digital tool for making light rail service sequences accessible to young adults on the autism spectrum with high functioning levels, to identify effective learning strategies, and to develop a model for integrating AI technologies in interventions aimed at enhancing independence in public transportation. Population and methods: The study included 15 therapists working with young adults on the autism spectrum across various therapeutic settings, and 25 young adults on the autism spectrum with high functioning levels aged 15-25 who face challenges with independent light rail travel. Instruments: Initial data collection was conducted using a semi-structured questionnaire developed for this study and designed for therapists working with young adults on the autism spectrum. The
RkJQdWJsaXNoZXIy Mjk0MjAwOQ==