The Study on Problems and Their Answer in Elementary Education Quality Monitoring

Elementary education quality (BEQ) monitoring plays the key role in BEQ improvement. Since BEQ monitoring employs traditional educational measurement methodology (including test, questionnaires, interview, observation, literature and so on) for information collection, today’s BEQ shows its disadvantages on high human cost, small sample, poor timeliness, much more steady-state and secondary data, unable to dynamically monitor all the samples in the whole education process, paying more attentions on qualitative evaluation and less on quantitative evaluation. As the result, BEQ’s credibility and public trust are harmed. Recently, education big data is limited to BEQ of online education and however, cannot be used to monitor the classroom teaching effect (CTE). Based on the latest information technology including affective computing, this work proposes a novel CTE auto-monitoring model and develops an initial prototype system named as CAISBNU. Initial studies draw the exciting conclusion. This system leads to much more advantages on high automation and efficiency, perfect timeliness, easy integration, low operation cost, generating education big data for deep researches on basic education, which can make some contribution for education of China.