{'fraction_non_alphanumeric': 0.018409425625920472, 'fraction_numerical': 0.0, 'mean_word_length': 5.380281690140845, '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}}
Big Data Assessment Methods for Students’ Online Laboratory Work Based on NCSLab

Traditional laboratory provides students with physical places and equipment to conduct experiments. Under this circumstance, the record and analysis of experimental data lack convenience and completeness to a certain extent. Compared to the former laboratory, online laboratory is able to record and store more data during the process of experiment. Online laboratory has changed the way of assessing students’ laboratory work. Based on these online recorded data, judging criteria of laboratory work can be extended to a richer dimension like behavior, attendance, and online experimental reports. Meanwhile, modern large-scale data storage and analysis technologies can be used to carry out the assessment. In this paper, big data assessment methods for students’ laboratory work are proposed. The data generated by users’ experiments is stored by the method of big data through distributed storage system. The assessment emphasis on laboratory work lies in behavior data which is generated during experiments and the assessment is carried out based on fuzzy inference. This paper takes Wuhan University as a case study, where students major in automation are using Networked Control System Laboratory (NCSLab) as a tool to conduct experiments for their laboratory sessions.