{'fraction_non_alphanumeric': 0.023005032350826744, 'fraction_numerical': 0.0, 'mean_word_length': 5.925373134328358, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Digital Transformation (DX) for Skill Learners: The Design Methodology and Implementation of Educational Chatbot using Knowledge Connection and Emotional Expression

With the continuous evolution of online education, online educational chatbots have become an indispensable help between teachers and learners. Due to the unified answers, it is hard for the educational chatbots to replace part of the teacher’s work, which should be more efficient than textbooks when retrieving knowledge and establishing emotional connections. In this paper, we propose an AI-based educational chatbot paradigm that introduces context recognition, learning experience, and emotion management to improve learners’ emotional confidence through the dialogue template while strengthening the chatbots’ ability to guide materials to inspire learners. We utilize long-term attention mechanisms to establish emotional connections with learners and strengthen skill learners’ self-efficacy. We investigate two types of up-to-date AI chatbots and conduct a mathematical analysis of the learners’ dialogue trust and self-efficacy by DNN (deep learning neural network). Referring to the analysis results, the introduction of mechanism rationale knowledge sharing and emotional connection has a significant effect on dialogue trust when chatting, and the learners’ self-efficacy is satisfied for future skill learning.