Factors Affecting the Happiness of Learners in Higher Education: Attitude, Grade Point Average, and Time Management
Round 1
Reviewer 1 Report (Previous Reviewer 2)
Comments and Suggestions for Authors1) the study lacks a proper theoretical background.
It seminal to enrich the intro discussing more current research
2) It is surprising that in today’s society the authors do not mention the digital world and how digital interaction affect happiness.
This topic MUST be analyzed.
Author Response
Please follow the revision note in the attached file.
Author Response File: 
Author Response.pdf
Reviewer 2 Report (Previous Reviewer 3)
Comments and Suggestions for AuthorsIt is grateful to see that the authors has revised the manuscripts according to part of my comments. Still, there are some unaddressed concerns as follows:
Purpose of clustering: “This differentiation enables more precise and meaningful interpretations of the data, highlighting specific needs or characteristics that might influence policy or educational interventions. The clusters established through k-means serve as a foundation for subsequent analyses. For example, ANOVA is used to test if the differences between these groups are statistically significant concerning their reported levels of happiness.” >> Cannot see any suggestions based on different cluster. Technically ANOVA is not a subsequent analysis, it is to prove cluster differences.
For the hypothesis, “It is right to use ‘affect’ in our hypothesis” >> Perhaps the authors can check how hypothesis are written up for multiple regression in other articles in the same journal.
Line 195-206, the formula for multiple regression is correct but not specific for this research.
Elbow method is an acceptable yet rather intuitive method is determining the number of K. Perhaps the authors can check the other valid methods https://towardsdatascience.com/how-many-clusters-6b3f220f0ef5
Another way is to examine the potential interpretation of different cluster solutions.
Standardization of key terms: Changed throughout the article to use "university environment" consistently.>> this is not the reviewer responsibility to check every term used, but it is clear that the authors did not really take it serious to the use of term , or maybe they are not holding specific concepts for the variables in multiple regression
>>for university (table 3), university factors (line 285)
>>The other terms should be standardized as well.
Also, for figure 5, there are no more histograms, some of name of the related factors are not shown.
The authors did not truly response to my last comment on the scale.>> “Cannot determine if it is related. Only suggesting perspectives from the research on how to enhance student happiness.” What is the inventory used? What are the questions adopted?
Should the “participatory teaching methods and engaging learning activities, such as interactive games and activities. (Line 419)” be more of the university factor instead of attitude? Line 428 directly touch on workload instead of time management.
>>>>>“no response or amendments to the discussion is found”
if the factors are interrelated (stated in abstract), will it break the very fundamental rules of multiple regression?
"no response or amendments to the discussion is found”
Author Response
Please follow the revision note in the attached file.
Author Response File: Author Response.pdf
Reviewer 3 Report (Previous Reviewer 1)
Comments and Suggestions for AuthorsI thank the authors for resubmiting the paper.
As in the first round of review I have made some minor recommendations and the authors considered them in the new submitted version, I have no further comments. Thank you!
Author Response
Please follow the revision note in the attached file.
Author Response File: Author Response.pdf
Round 2
Reviewer 2 Report (Previous Reviewer 3)
Comments and Suggestions for AuthorsThe authors have truly responded to much of my concerns this time. Still my last big concern is about the how the authors wrote the hypothesis.
The author proposed hypothesis are as follows:
H1: GPA influences students' happiness. 177
H2: Workload influences students' happiness. 178
Where I do not think these hypothesis meet the norms of writing up hypothesis of any previous work from Sustainability as cited in the reply of the authors.
1) Zhang, S.; Yang, J.; Shen, Y.; Li, Z. How Do Digital Capabilities Impact the Sustained Growth of Entrepreneurial Income: Evidence from Chinese Farmer Entrepreneurs. Sustainability 2024, 16, 7522
H1. Digital capabilities have a positive effect on the sustained increase in entrepreneurial income
H2. Entrepreneurial alertness mediates the impact of digital competence on the sustained increase in entrepreneurial income.
2) Pham, V.K.; Vu, T.N.Q.; Phan, T.T.; Nguyen, N.A. The Impact of Organizational Culture on Employee Performance: A Case Study at Foreign-Invested Logistics Service Enterprises Approaching Sustainability Development. Sustainability 2024, 16, 6366. https://doi.org/10.3390/su16156366
Hypothesis 1. Artifact factors positively influence employee performance in enterprises.
Hypothesis 2. Espoused values positively influence employee performance in enterprises.
3) Lei, M.; Alam, G.M.; Bashir, K. The Relationships between Job Performance, Job Burnout, and Psychological Counselling: A Perspective on Sustainable Development Goals (SDGs). Sustainability 2024, 16, 7569. https://doi.org/10.3390/su16177569
Ha1: Academics’ “job performance” has a substantially detrimental impact on “job burnout” when all predictor variables are considered.
Ha2: “Psychological counseling” has different moderating effects on academic performance and burnout when all predictor variables are considered.
4) Monteiro, S.; Roque, V.; Faria, M. Does Sustainability Reporting Impact Financial Performance? Evidence from the Largest Portuguese Companies. Sustainability 2024, 16, 6448. https://doi.org/10.3390/su16156448
H: the financial performance of Portuguese companies that publish SRs differs from the financial performance of companies that do not publish SRs.
I also do not see why the authors did not provide sample questions / scale. There is no way for readers to understand / replicate the research work.
Author Response
Please see the attachment.
Author Response File: Author Response.pdf
This manuscript is a resubmission of an earlier submission. The following is a list of the peer review reports and author responses from that submission.
Round 1
Reviewer 1 Report
Comments and Suggestions for AuthorsI found the paper to be interesting.
Both the abstract and introduction provides the needed information to support this research. Please add a brief roadmap at the end of the introduction.
Also, please include in the paper the questions associated with each of the 8 independent variables in figure 1 and with the dependent variable. The authors might choose to add it as an annex to the paper.
Section 2 is comprehensive and ensures the reproducibility of the study.
The results in section 3 are supported by the data. I highly appreciated the elements presented in figure 5.
The discussions section is more than welcomed.
Please expand upon concluding remarks as this section is brief. Please discuss how the proposed approach can be used to other similar studies and how it is expected that the results will/will not change when another population is considered.
Please add limitations.
Reviewer 2 Report
Comments and Suggestions for AuthorsThe paper deals with student well-being, understood as essential for academic achievement and personal growth. This study aimed to identify key determinants of stu-9 dent happiness in higher education. Eight factors, including GPA, workload, family support, university environment, attitude, motivation, time management, and social relationships, were examined among 388 Thai students using an online survey. Students were categorized into distinct groups based on these factors using k-means clustering. ANOVA was employed to assess whether these factors significantly differentiated the groups, and significant factors were further analyzed using regression analysis to confirm their impact on student happiness. Neural network analysis was also utilized to evaluate the relative importance of each factor. The results revealed that attitude, GPA, and time management significantly affected student happiness. A positive attitude fosters a sense of opportunity and achievement, a high GPA reflects academic success and enhances self-confidence, and effective time management reduces stress while allowing more time for enjoyable activities. These factors are interrelated and collectively impact overall student happiness.
The paper is well organized and methodologically sound.
Accordingly the results have the potential to contribute to this field of literature.
However,
1) the study lacks a proper theoretical background.
It seminal to enrich the intro discussing more current research
2) It is surprising that in today’s society the authors do not mention the digital world and how digital interaction affect happiness.
This classic book might help.
Cartelli, A. (2012). Current trends and future practices for digital literacy and competence. Hershey, PH: IGI Global.
Reviewer 3 Report
Comments and Suggestions for AuthorsThis study investigates the relationship of 8 factors to students’ perceived happiness in higher education in Thailand. Some suggestions are as follows:
The authors could consider to improve the introduction by introducing the context. Why study happiness is important at this time? Is this important to Thailand?
>>“Research related to studying the factors affecting learners' happiness has been widely conducted. (Line 48)” > what is the significance of this research?
>>> Just wonder if the clustering analysis is necessary? It seems that the results of different clusters are not very distinct to each other. The discussion is rather weak as well.
In the first paragraph, I would like to know what is the standpoint of the authors, whether it is better results lead to better happiness or the other way round?
Sentences introducing the previous literatures is awkward. “Research by [1] found that happy learners 30 tend to achieve better academic results”
It is understood that excessive workload in school could cause unhappiness. But it is a strictly linear relationship?
For H1-H8, it is technically not right use “affect”. The results just prove there is a linear relationship or not. Also, as an academic paper, it is expected to report whether this Hypothesis are rejected or not.
Figure 1 is not really presentable. Should the author consider to indicate the related Hypothesis. Could further improve the resolution as well.
Is the formula provided in Line 186 accurate for multiple regression and specific for this study?
Is the Neural Network techniques primarily for validating the results? (line 191)
Not all the methods are clearly described in section 2. (Chi square, stepwise method, RMSE)
What are the scales for all factors?
>>shall we assume emotional / financial support/ relationship/ stability (line 49-51) are all included in the scale?
>>>shouldn’t the scale indicate the meaning of the score of different factors? What is the use of line 216-224? >>>>perhaps if the authors use the numbers instead of the interpretation, chi square is not necessary.
>>>>lacking of a description of scale, it is hard to make consistent understanding. Should the “participatory teaching methods and engaging learning activities, such as interactive games and activities. (Line 419)” be more of the university factor instead of attitude? Line 428 directly touch on workload instead of time management. >>>>>if the factors are interrelated (also stated in abstract), will it break the very fundamental rules of multiple regression?
Perhaps the naming of clusters should be starting from 1 instead of 0.
The determining of K is purely by elbow method. Would the authors provide more considerations? Also, the within group difference of cluster 2 is quite high compared to other clusters. Would there be 2 latent groups within this cluster?
Is the description for line 232-234 correct?
In Section 3.2, instead of looking at difference across 3 clusters, perhaps the authors could also investigate some more detailed relationships. Could there be no statistical difference between cluster 0 and cluster 1 in terms of GPA? And for workload between cluster 0 and cluster 1?
Why family support and attitudes in Line 344? They are not the three factors identified in line 307. They also have quite different interpretations in table3. Shouldn’t be the university, motivation also influential?
Self efficacy cannot be proved by this work. Line 388-391
As an academic paper, it is very important to standardise the naming of factors. Use of different terms E.g. university environment in abstract, university factors (line 54), university (line 207) could be very confusing.
Other minor suggestions:
It is strange to tell there are “three independent groups” in Line 174 at that point.
Wonder if 1.00 is the lowest GPA is among 388 students?
Some reference might be needed on the methods.
Is there a need to give 3 citations in line 288?
