A Dataset of Vietnamese Junior High School Students’ Reading Preferences and Habits
, Anh-Vinh Le 3, Viet-Phuong La 1,2, Thu-Trang Vuong 4, Thu-Hang Do 5, Ha-My Vuong 6, Duc-Lan Do 3, Phuong-Hanh Hoang 3, Thi-Hanh Vu 7, Manh-Tung Ho 1,2 and Manh-Toan Ho 1,2,*Round 1
Reviewer 1 Report
GENERAL OVERVIEW AND MAIN CONTRIBUTIONS:
The authors of this paper present a dataset of 1676 responses to the survey “Studying reading habits and preferences” of junior high school students in Vietnam. Result analysis facilitates evaluation of reading habits and their affecting factors, thus holding implications on education measures policy.
The motivation for this work is, despite the ample literature on reading habits, there still exists a lack of holistic approach with empirical results concerning the reciprocal interactions of reading and its relevant affecting factors.
WEAK POINTS:
The ideas presented in the paper are very interesting and the paper is well written. However, there are some open questions:
- It would be interesting to have the structure of the paper described at the end of the Summary section.
- The authors ask students about their source of book supply (‘Source’). And the students only have three options:
1) access books by borrowing from friends or libraries (‘borrow’).
2) buying books using their own or their parents’ money (‘buy’)
3) receiving books as gifts or rewards (‘gift’).
In our opinion, the first option should be divided in two:
i) borrowing from friends
ii) libraries
Because it would be interesting to find out if the students usually use the libraries.
- Which are the main conclusions of this study? We suggest to add a new section “Conclusions and Future work” to include explicitly the main conclusions of this work.
ADDITIONAL COMMENTS AND TYPOS:
- Line 36: “1. Summary (required)” should be “1. Summary”
- Line 53: “2. Data Description (required)” should be “2. Data Description”
- Line 192: “3. Methods (required)” should be “3. Methods”
- Lines 241-242: “young female students value reading than males [17].” Please modify this sentence.
Line 255: “Examples of the used code on R to come up with the results as in Table 3 is.” Please modify this sentence.
- Table 1 is split in two pages. Therefore the header should be included in the second page.
- The captions of all Tables in the paper should be positioned on the top and not below the data.
In conclusion, the paper can be improved provided that the authors answer the above-mentioned questions and modify the paper according to the suggestions.
Author Response
Dear Sir/Madam,
Thank you very much for reviewing our paper. We greatly appreciate that your detailed comments and suggestions for our paper have significantly improved the quality of our paper. We have addressed your points in our revised version. Please notice that in the revised paper, the parts that are highlighted in yellow is for corrections on the old text, the parts highlighted in green is written anew. Below are our answers (in bold text) to your comments (in italic). Also, the line numbers in the bold text refer to the revised paper.
WEAK POINTS:
The ideas presented in the paper are very interesting and the paper is well written. However, there are some open questions:
- It would be interesting to have the structure of the paper described at the end of the Summary section.
We have included a new paragraph to explain the structure of the paper at the end of Summary section (line 57-60)
In the next section, we will explain in detail all the coded variables of the dataset. Then, in the Methods section, the design of questionnaire, the survey process, the data analysis method, and examples of results are presented. Finally, the Conclusion will discuss the limitation and potential of the dataset.
- The authors ask students about their source of book supply (‘Source’). And the students only have three options:
1) access books by borrowing from friends or libraries (‘borrow’).
2) buying books using their own or their parents’ money (‘buy’)
3) receiving books as gifts or rewards (‘gift’).
In our opinion, the first option should be divided in two:
i) borrowing from friends
ii) libraries
Because it would be interesting to find out if the students usually use the libraries.
Thank you for your suggestion. During questionnaire design however, our main purpose concerning this question was to examine the economic aspect of book access – that is, whether students are willing to spend either money or efforts on books, or only passively receive books as gifts; in other words, whether students are actively seeking to read more. Whether the borrowing comes from friends or libraries did not concern this aspect.
However, we do recognize that it would give interesting insights and we will consider including this change in the next national-scale survey. For this dataset, the survey period is finished. We have included this the shortcoming in the limitation section of the article (Line 320-325):
Moreover, there are values of the categorical variables that can be divided into two values. For instance, the categorical variable ‘Source’ now contains three values: borrowing from friends or libraries (‘borrow’), using their own or their parents’ money (‘buy’), and receiving books as gifts or rewards (‘gift’). The ‘borrow’ value can be divided into borrowing from friends and borrowing for libraries. Such an amendment in the categorization of data will provide a better insight into the usage of libraries. However, we can only address this in the future survey.
- Which are the main conclusions of this study? We suggest to add a new section “Conclusions and Future work” to include explicitly the main conclusions of this work.
We have included a conclusion section for the article (Line 294-325):
The dataset provide a comprehensive view on the reading practices, habits and preferences of students in Vietnam, which is a subject that to this day lacks systematic research despite being acknowledged as a crucial aspect of education. The inclusion of both self-reported personal preferences and objective data regarding school performance under the form of notes allows for multifaceted analyses. In addition to data regarding the activity of book reading, we have also collected demographic data and recorded the socio-economic background of the respondents, including estimated household income and parents’ profession. We believe this dataset has one of the most complete set of variables out of all datasets in the same field in Vietnam, which would be especially beneficial in future models that require extensive control variables.
In terms of content, our dataset promises fertile grounds for future research on reading practices in adolescents both as a response variable – to demographic factors, family background, or personal preferences, for example – and a predictor variable – to, among others, academic performance or professional orientation. The insights gained into the reading habits and preferences in Vietnamese pupils would serve as grounded suggestions for future policies and informed decisions [22], namely education but also social policies geared towards families in rural areas and low-income households. Policy implications should concern not also Vietnam but perhaps also other emerging countries similar in economic development, or other East Asian/Southeast Asian countries with similar cultural attributes and family structures.
We acknowledge however that the dataset faces some limitations. First, the geographical area where the survey was conducted is limited to one province in the North of Vietnam. In the future, we hope to expand the dataset by broadening the surveyed geographical area to allow for more comparative perspectives between different regions, for example urban versus rural. Second, the school grade range in the dataset could also be expanded to include primary school for a more panoramic view of reading habits among the youth, and potential investigations into differing habits between generations.
Moreover, there are values of the categorical variables that can be divided into two values. For instance, the categorical variable ‘Source’ now contains three values: borrowing from friends or libraries (‘borrow’), using their own or their parents’ money (‘buy’), and receiving books as gifts or rewards (‘gift’). The ‘borrow’ value can be divided into borrowing from friends and borrowing for libraries. Such an amendment in the categorization of data will provide a better insight into the usage of libraries. However, we can only address this in the future survey.
ADDITIONAL COMMENTS AND TYPOS:
- Line 36: “1. Summary (required)” should be “1. Summary”
- Line 53: “2. Data Description (required)” should be “2. Data Description”
- Line 192: “3. Methods (required)” should be “3. Methods”
We have removed the redundant “(required)” part in the section titles.
- Lines 241-242: “young female students value reading than males [17].” Please modify this sentence.
The sentence have been modified (Line 207-208): young female student value reading more than the male counterpart
Line 255: “Examples of the used code on R to come up with the results as in Table 3 is.” Please modify this sentence.
The sentence have been modified (Line 274): Examples of code on R that were used to come up with the results in Table 3 is as follows:
- Table 1 is split in two pages. Therefore the header should be included in the second page.
Table 1 have been modified accordingly with header and caption in each pages.
- The captions of all Tables in the paper should be positioned on the top and not below the data.
The captions of all Tables have been moved to the top.
In conclusion, the paper can be improved provided that the authors answer the above-mentioned questions and modify the paper according to the suggestions.
Once again, we greatly appreciate the hard work and time that you have spent on this manuscript. Your comments and suggestions have helped us improve the quality of our paper. We hope that the revised paper has met your requirements.
Please accept our sincere thanks for your great contributions to data science and the overall advancement of sciences in the world.
Shall you have further comments, we look forward to hearing from you.
Best regards,
Author Response File: 
Author Response.docx
Reviewer 2 Report
the section titles should have the "(required)" text removed: that is just guidance from the template.
Suggest review structure to put research question nearer the front (at least paraphrase section 3.2 earlier)
The paper does need a greater explanation/justification of the use of the logistic model and the implcations of the Logit values .
It also needs a discussion and conclusions section to bring together the research question and how far the evidence has answered that,
Author Response
Dear Sir/Madam,
Thank you very much for reviewing our paper. We greatly appreciate that your detailed comments and suggestions for our paper have significantly improved the quality of our paper. We have addressed your points in our revised version. Please notice that in the revised paper, the parts that are highlighted in yellow are for corrections on the old text, the parts highlighted in green are written anew. Below are our answers (in bold text) to your comments (in italic). Also, the line numbers in the bold text refer to the revised paper.
The section titles should have the "(required)" text removed: that is just guidance from the template.
We have removed the “(required)” from the section titles.
Suggest review structure to put research question nearer the front (at least paraphrase section 3.2 earlier)
Research questions have been moved to section 2.3., right after the description of data. We also changed the name of this section to ‘Potential research questions’, which is a better fit for a Data Descriptor article (Line 203-215).
The paper does need a greater explanation/justification of the use of the logistic model and the implications of the Logit values.
We have explained in detail our decision to choose logistic model and the implications of the Logit values in the articles (Line 247-255):
The majority of the dataset is discrete data, which received their value from categories that were built according to the design of the survey. Thus, the most suitable method of analysis for this kind of data is categorical regression, in which, log-linear and logistic models can be equivalent [20]. However, logistic regression model is more efficient in explaining the relationship, either independence or associations, among variables. Moreover, logistic regression analysis also provides coefficients to estimate the probabilistic trends for each value of the dependent variables according to the conditions of the independent variables. Logistic regression analysis is more flexible for analyzing mixed sets of nominal/ordinal and interval variables [21]. For more detailed discussion on the comparative advantages of the two methods of analysis, please see [19-21].
It also needs a discussion and conclusions section to bring together the research question and how far the evidence has answered that.
We have included a conclusion section for the article (Line 294-325):
The dataset provide a comprehensive view on the reading practices, habits and preferences of students in Vietnam, which is a subject that to this day lacks systematic research despite being acknowledged as a crucial aspect of education. The inclusion of both self-reported personal preferences and objective data regarding school performance under the form of notes allows for multifaceted analyses. In addition to data regarding the activity of book reading, we have also collected demographic data and recorded the socio-economic background of the respondents, including estimated household income and parents’ profession. We believe this dataset has one of the most complete set of variables out of all datasets in the same field in Vietnam, which would be especially beneficial in future models that require extensive control variables.
In terms of content, our dataset promises fertile grounds for future research on reading practices in adolescents both as a response variable – to demographic factors, family background, or personal preferences, for example – and a predictor variable – to, among others, academic performance or professional orientation. The insights gained into the reading habits and preferences in Vietnamese pupils would serve as grounded suggestions for future policies and informed decisions [22], namely education but also social policies geared towards families in rural areas and low-income households. Policy implications should concern not also Vietnam but perhaps also other emerging countries similar in economic development, or other East Asian/Southeast Asian countries with similar cultural attributes and family structures.
We acknowledge however that the dataset faces some limitations. First, the geographical area where the survey was conducted is limited to one province in the North of Vietnam. In the future, we hope to expand the dataset by broadening the surveyed geographical area to allow for more comparative perspectives between different regions, for example urban versus rural. Second, the school grade range in the dataset could also be expanded to include primary school for a more panoramic view of reading habits among the youth, and potential investigations into differing habits between generations.
Moreover, there are values of the categorical variables that can be divided into two values. For instance, the categorical variable ‘Source’ now contains three values: borrowing from friends or libraries (‘borrow’), using their own or their parents’ money (‘buy’), and receiving books as gifts or rewards (‘gift’). The ‘borrow’ value can be divided into borrowing from friends and borrowing for libraries. Such an amendment in the categorization of data will provide a better insight into the usage of libraries. However, we can only address this in the future survey.
Once again, we greatly appreciate the hard work and time that you have spent on this manuscript. Your comments and suggestions have helped us improve the quality of our paper. We hope that the revised paper has met your requirements.
Please accept our sincere thanks for your great contributions to data science and the overall advancement of sciences in the world.
Shall you have further comments, we look forward to hearing from you.
Best regards,
Author Response File: Author Response.docx
