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

Dongxing Li; Zuying Luo; Wenquan Chang

doi:doi:10.11648/j.si.20170504.15

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

Dongxing Li, Zuying Luo, Wenquan Chang

Published in Science Innovation (Volume 5, Issue 4)

Received: 10 May 2017 Published: 11 May 2017

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Abstract

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.

Published in	Science Innovation (Volume 5, Issue 4)
DOI	10.11648/j.si.20170504.15
Page(s)	220-226
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2017. Published by Science Publishing Group

Keywords

Educational Measurement, Education Monitoring, Classroom Teaching, Instruction Evaluation, Education Big Data, Educational Technology, Affective Computing

References

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APA Style

Dongxing Li, Zuying Luo, Wenquan Chang. (2017). The Study on Problems and Their Answer in Elementary Education Quality Monitoring. Science Innovation, 5(4), 220-226. https://doi.org/10.11648/j.si.20170504.15

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ACS Style

Dongxing Li; Zuying Luo; Wenquan Chang. The Study on Problems and Their Answer in Elementary Education Quality Monitoring. Sci. Innov. 2017, 5(4), 220-226. doi: 10.11648/j.si.20170504.15

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AMA Style

Dongxing Li, Zuying Luo, Wenquan Chang. The Study on Problems and Their Answer in Elementary Education Quality Monitoring. Sci Innov. 2017;5(4):220-226. doi: 10.11648/j.si.20170504.15

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@article{10.11648/j.si.20170504.15,
  author = {Dongxing Li and Zuying Luo and Wenquan Chang},
  title = {The Study on Problems and Their Answer in Elementary Education Quality Monitoring},
  journal = {Science Innovation},
  volume = {5},
  number = {4},
  pages = {220-226},
  doi = {10.11648/j.si.20170504.15},
  url = {https://doi.org/10.11648/j.si.20170504.15},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.si.20170504.15},
  abstract = {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.},
 year = {2017}
}

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TY  - JOUR
T1  - The Study on Problems and Their Answer in Elementary Education Quality Monitoring
AU  - Dongxing Li
AU  - Zuying Luo
AU  - Wenquan Chang
Y1  - 2017/05/11
PY  - 2017
N1  - https://doi.org/10.11648/j.si.20170504.15
DO  - 10.11648/j.si.20170504.15
T2  - Science Innovation
JF  - Science Innovation
JO  - Science Innovation
SP  - 220
EP  - 226
PB  - Science Publishing Group
SN  - 2328-787X
UR  - https://doi.org/10.11648/j.si.20170504.15
AB  - 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.
VL  - 5
IS  - 4
ER  -

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Author Information

Dongxing Li

College of Information Science and Technology, Beijing Normal University, Beijing, P. R. China
Zuying Luo

College of Information Science and Technology, Beijing Normal University, Beijing, P. R. China
Wenquan Chang

College of Information Science and Technology, Beijing Normal University, Beijing, P. R. China

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Plain Text BibTeX RIS

APA Style

Dongxing Li, Zuying Luo, Wenquan Chang. (2017). The Study on Problems and Their Answer in Elementary Education Quality Monitoring. Science Innovation, 5(4), 220-226. https://doi.org/10.11648/j.si.20170504.15

Copy | Download

ACS Style

Dongxing Li; Zuying Luo; Wenquan Chang. The Study on Problems and Their Answer in Elementary Education Quality Monitoring. Sci. Innov. 2017, 5(4), 220-226. doi: 10.11648/j.si.20170504.15

Copy | Download

AMA Style

Dongxing Li, Zuying Luo, Wenquan Chang. The Study on Problems and Their Answer in Elementary Education Quality Monitoring. Sci Innov. 2017;5(4):220-226. doi: 10.11648/j.si.20170504.15

Copy | Download

@article{10.11648/j.si.20170504.15,
  author = {Dongxing Li and Zuying Luo and Wenquan Chang},
  title = {The Study on Problems and Their Answer in Elementary Education Quality Monitoring},
  journal = {Science Innovation},
  volume = {5},
  number = {4},
  pages = {220-226},
  doi = {10.11648/j.si.20170504.15},
  url = {https://doi.org/10.11648/j.si.20170504.15},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.si.20170504.15},
  abstract = {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.},
 year = {2017}
}

Copy | Download

TY  - JOUR
T1  - The Study on Problems and Their Answer in Elementary Education Quality Monitoring
AU  - Dongxing Li
AU  - Zuying Luo
AU  - Wenquan Chang
Y1  - 2017/05/11
PY  - 2017
N1  - https://doi.org/10.11648/j.si.20170504.15
DO  - 10.11648/j.si.20170504.15
T2  - Science Innovation
JF  - Science Innovation
JO  - Science Innovation
SP  - 220
EP  - 226
PB  - Science Publishing Group
SN  - 2328-787X
UR  - https://doi.org/10.11648/j.si.20170504.15
AB  - 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.
VL  - 5
IS  - 4
ER  -

Copy | Download