{'fraction_non_alphanumeric': 0.02142051860202931, 'fraction_numerical': 0.004509582863585118, 'mean_word_length': 5.626865671641791, '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}}
Causal Association Analysis Algorithm for MOOC Learning Behavior and Learning Effect

From 2012, Massive Open Online Course (MOOC), which combines the advantages of traditional teaching mode and the common network teaching, develops rapidly and has set off an education revolution. In the process of MOOC learning, a great deal of data related to the learning behavior are generated, but the data hasn't got efficient use. Embarking from the definition of learners' learning behaviors in MOOC learning environment, we analyzed the components of learning behavior, and proposed a formalized representation of learning behavior. By improving Apriori algorithm, we proposed a causal association analysis (CAA) algorithm to analyze the association between learning behavior and effect, and an application direction of daily inspection system based on the learning behaviors is also provided.