RIASEC GPT Chatbot and Eye Tracking: Conscious vs. Subconscious Vocational Interest Inventory
摘要
Vocational Interest Inventories (VIIs) are career assessments that recommend suitable career categories based on stated interest in various work activities. Utilizing advanced chatbot software and modern eye-tracking technology may glean additional conscious and subconscious data from users to improve VII’s. Through the application of the RIASEC (Holland’s Codes) model of VII’s to Generative Pre-trained Transformer (GPT) multimodal multi-bot chatbots and image-based comparison programs incorporating background eye-tracking in three related experiments, alternative methodologies of VII career category and career recommendation prediction are conducted, compared, and proposed for future vocational research studies. This is the first VII project that explores GPT-4 applications, eye-tracking technology, and diametrically opposite RIASEC career category comparison to efficiently predict user interest in RIASEC’s career categories.