246 ע בּוֹטְסָלֶה: צ’אטבוט מבוסס GenAI להכוון אקדמי עבור צעירים מהחברה הערבית בישראל )פוסטר( 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 בּוֹטְסָלֶה: צ' אטבוט מבוסס GenAI להכוון אקדמי עבור צעירים מהחברה הערבית בישראל )פוסטר( מאיה אושר HIT מכון טכנולוגי חולון mayau@hit.ac.il מיטל אמזלג HIT מכון טכנולוגי חולון meitalam@hit.ac.il דוניא זועבי - סלימאן HIT מכון טכנולוגי חולון Donia.slieman@gmail.com Botsale: A GenAI Chatbot for Academic Guidance among Arab Youth in Israel (Poster) Donia Zoabie-Slieman HIT Holon Institute of Technology Donia.slieman@gmail.com Meital Amzalag HIT Holon Institute of Technology meitalam@hit.ac.il Maya Usher HIT Holon Institute of Technology mayau@hit.ac.il Abstract Young adults from the Arab society in Israel face challenges in choosing an academic study path, including language barriers, limited access to information, and limited culturally responsive guidance services (Khoury-Kassabri & Ajzenstadt, 2023; Smooha, 2019). Although GenAI-based chatbots show potential for supporting educational decision-making (Adamopoulou & Moussiades, 2020; Luo et al., 2022), AI-based academic guidance tools in Arabic are largely unexplored. To address this gap, Botsale–a GenAI-based Arabic-language chatbot–was developed to offer personalized, reflective support in choosing an academic field. A quantitative study with 128 eighteen-year-old participants from the Arab society in a gap-year program examined Botsale's contribution to perceived knowledge, trust, and future use intention. Participants conversed with Botsale and completed an online questionnaire based on prior research (Li et al., 2023; Subramaniam, 2024; Yu et al., 2024; Zhao et al., 2025). Findings showed medium-tohigh levels: trust (M = 3.96, SD = .72), perceived knowledge (M = 3.77, SD = .90), and future use intention (M = 3.68, SD = .95). Strong positive correlations emerged among all variables (p < .001): perceived knowledge with future use intention (r = .85), with trust (r = .77), and trust with future use intention (r = .69). A low-scoring item–preferring Botsale over consulting a knowledgeable person (M = 3.17, SD = 1.25)–suggested ongoing preference for complementary human support. Overall, the findings suggest that culturally adapted, language-matched chatbots can enhance perceived knowledge, trust, and future use intentions, while emphasizing the importance of hybrid models integrating digital and human guidance. Keywords: Arab youth, Chatbots, Future use intention, GenAI, Perceived knowledge, Trust.
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