2017DEStech Transactions on Social Science Education and Human ScienceRequires access

Relationship Between Big Data and Teaching Evaluation

Qing-hui Dai, Yu-Zhao CHEN, Guan-Ru HUA

Open publisher page 5 citations

Abstract

The current teaching quality evaluation system has been difficult to adapt to the class in era of big data. Due to the limited amount of information, the limited data sources, the current teaching evaluation is more of the result-based evaluation and empirical evaluation. Teaching evaluation of supervision is not only to distinguish the different teaching levels of teachers, more important is to understand the situation of teaching and learning, so as to develop personalized program to better achieve the training objectives. This requires that teaching evaluation is a formative evaluation. Network teaching will be the substitute for modern classroom teaching. Through the reflection on the teaching quality evaluation system, it points out the problems of the teaching quality evaluation system, analyzes the reasons and puts forward the suggestions to solve the problems. Construction of teaching quality data monitoring platform and improving the teaching supervision of data literacy is an effective way to make the teaching supervision from the "experience" to "data type". It can be predicted that Web school will be a substitute for classroom teaching.

About this research paper

What this paper is about

The current teaching quality evaluation system has been difficult to adapt to the class in era of big data. Due to the limited amount of information, the limited data sources, the current teaching evaluation is more of the result-based evaluation and empirical evaluation. Teaching evaluation of supervision is not only to distinguish the different teaching levels of teachers, more important is to understand the situation of teaching and learning, so as to develop personalized program to better achieve the training objectives. This requires that teaching evaluation is a formative evaluation. Network teaching will be the substitute for modern classroom teaching. Through the reflection on the teaching quality evaluation system, it points out the problems of the teaching quality evaluation system, analyzes the reasons and puts forward the suggestions to solve the problems. Construction of teaching quality data monitoring platform and improving the teaching supervision of data literacy is an effective way to make the teaching supervision from the "experience" to "data type". It can be predicted that Web school will be a substitute for classroom teaching.

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OpenAlex reports 5 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

The current teaching quality evaluation system has been difficult to adapt to the class in era of big data. Due to the limited amount of information, the limited data sources, the current teaching evaluation is more of the result-based evaluation and empirical evaluation. Teaching evaluation of supervision is not only to distinguish the different teaching levels of teachers, more important is to understand the situation of teaching and learning, so as to develop personalized program to better achieve the training objectives. This requires that teaching evaluation is a formative evaluation. Network teaching will be the substitute for modern classroom teaching. Through the reflection on the teaching quality evaluation system, it points out the problems of the teaching quality evaluation system, analyzes the reasons and puts forward the suggestions to solve the problems. Construction of teaching quality data monitoring platform and improving the teaching supervision of data literacy is an effective way to make the teaching supervision from the "experience" to "data type". It can be predicted that Web school will be a substitute for classroom teaching.

Key concepts: Formative assessment, Quality (philosophy), Computer science, Class (philosophy), Teaching method, Reflection (computer programming), Teaching and learning center, Big data

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