{'fraction_non_alphanumeric': 0.0169061707523246, 'fraction_numerical': 0.0, 'mean_word_length': 5.4, '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': 1, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Human Factor Modeling for Development of Learning Support Systems Facilitating Meta-Cognition

In the cognitive science field, many researchers have proposed a concept whereby meta-cognition plays an important role to acquire expertise and transfer it. Our research goal is to develop a methodology for building sophisticated learning systems which can effectively facilitate learners' meta-cognition. The intelligent novice is good at observing knowledge objectively and producing an efficient plan of learning processes. On the other hand, it is not so easy for an ordinary novice to perform meta-cognitive activities. We must model these two types of learners for building learning systems that can support ordinary novices effectively. In this paper, we build cognitive models that capture human factors to perform meta-cognitive activities as a basis of learning systems development for facilitating meta-cognition based on the knowledge in cognitive system engineering and cognitive psychology fields. Then, we build an intelligent novice model that can explain the characteristics of them. Lastly, we clarify design rationales of our system called Kassist based on the models.