{'fraction_non_alphanumeric': 0.01945945945945946, 'fraction_numerical': 0.0, 'mean_word_length': 5.614285714285714, '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}}
Evaluating Expertise in Collaborative Educational Environments

This paper aims to conceive a system capable of assessing the understanding an individual possesses on an arbitrary subject. A hard, essential question regarding a collaborative environment is how to evaluate the knowledge an individual maintains about a specific domain. Such evaluation is usually accomplished with collective works or examinations applied individually. However, techniques such as those are subjected to idiosyncratic factors related to both the tutor (level of experience, mood, affinity, etc.) and the team member. In this paper, we used some techniques from the field of natural language understanding based on concepts like dynamic memory, case-based reasoning and semantic parser. We discuss experiments, carried out within one such educational environment, which turned out to be coherent according to the opinion of the tutors involved