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Article
Peer-Review Record

Research on Recognition and Analysis of Teacher–Student Behavior Based on a Blended Synchronous Classroom

Appl. Sci. 2023, 13(6), 3432; https://doi.org/10.3390/app13063432
by Taojie Xu, Wei Deng *, Si Zhang, Yantao Wei and Qingtang Liu
Reviewer 1: Anonymous
Reviewer 2: Anonymous
Reviewer 3: Anonymous
Reviewer 4: Anonymous
Appl. Sci. 2023, 13(6), 3432; https://doi.org/10.3390/app13063432
Submission received: 13 January 2023 / Revised: 2 March 2023 / Accepted: 5 March 2023 / Published: 8 March 2023
(This article belongs to the Special Issue Artificial Intelligence in Online Higher Educational Data Mining)

Round 1

Reviewer 1 Report

It is recommended to add the aim of the article in the abstract, as it is not clarified in the current version, so the readers can to get an idea of the content of the paper.

Abbreviations should not be used in the abstract.

It is good to add section Conclusion where to summarize the achieved results and to systematize the main conclusions of the study.

Author Response

Please see the attachment.

Author Response File: Author Response.docx

Reviewer 2 Report

The work is certainly original and shows broad future perspectives on a particularly topical subject. The structure of the paper is clear and precise, and the references presented provide excellent support for what is discussed in the theoretical framework. The results are clear, precisely presented and also supported by graphs and tables.

Author Response

We are grateful for your effort in reviewing our paper and your positive feedback.

Reviewer 3 Report

This paper presents student-teacher behavior analysis in the classroom. This kind of behavior analysis is applicable in both face-to-face and online/virtual classroom environments. Although some design approaches and predicated results need much more improvement, the research approach has significance. 

Following are my suggestions for improvement before considering it for publication. 

1. There are some English Typo errors and grammatical errors. Therefore they need to be checked carefully and fixed. 

2. The references are not sufficient. The introduction part seems good. But in the background section, more references need to be cited to review the research attempts in this classroom behavior analysis via computer vision and machine learning techniques. 

3. There is no Conclusion section. It is better to add a Conclusion section and outline the findings of this research supported by experimental results. 

4. I think it is not necessary to provide a link for the VOC2007 dataset in Data Availability Sentence as it is a well-known dataset and publically available. You can point it out in reference though. 

Everingham, M., Van Gool, L., Williams, C. K., Winn, J., & Zisserman, A. (2009). The pascal visual object classes (voc) challenge. International journal of computer vision88, 303-308.

Author Response

Please see the attachment.

Author Response File: Author Response.docx

Reviewer 4 Report

 

The paper is written in an organized manner and worth publishing in this journal, however, there are major issues need to be fixed:

 

1.   The problem statement and study objective should be clearly stated in the 'Introduction' section.

2. The main contributions should be clearly stated.

3- What are the potential advantages of using the VGG16 model to identify teacher actions?

4- Add an appropriate description of the data set and its suitability for the task at hand.5- What are limitations of the study?

 

 

Author Response

Please see the attachment.

Author Response File: Author Response.docx

Round 2

Reviewer 4 Report

The paper has been improved

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