Mitigating Student Cynicism for Sustainable Academic Performance: University Identification and Academic Self-Efficacy

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

Thank you for the opportunity, the manuscript entitled “Mitigating Student Cynicism to Enhance Sustainable Academic Performance in Higher Education: The Interplay of University Identification and Academic Self-Efficacy”. This manuscript investigates the interplay between student cynicism, university identification, and academic self-efficacy in predicting academic performance among college students. The manuscript addresses a relevant and timely issue in higher education, linking student cynicism, university identification, and academic self-efficacy to sustainable academic performance. The study is well-structured, and the theoretical framework is clearly articulated. However, several areas require some revisions before the manuscript can be considered for the Sustainability journal. You can see my comments below:

1. The topic is significant, aligning with the Sustainable Development Goals (SDGs) and addressing psychological well-being in higher education. However, the study's originality could be strengthened by emphasizing how it differs from existing research on student cynicism and academic self-efficacy. More elaboration on its contribution to sustainability literature is needed, including the cultural background of Turkiye on this issue.
2. The introduction provides a clear overview of the research problem and the study's objectives. However, the authors could strengthen the introduction by providing more specific examples of how cynicism, university identification, and academic self-efficacy manifest in the higher education context.
3. The rationale behind selecting policy, academic, social, and institutional cynicism should be justified with stronger theoretical grounding.
4. The study needs a clear differentiation between student cynicism and other constructs, such as academic disengagement or burnout. Consider integrating more recent studies on the study variables.
5. The methodology section lacks details on sampling. Why was a single university selected, and how does this impact generalizability? More specifically, the authors should discuss the generalizability of the findings to other institutions, cultural settings, or educational levels. Moreover, the authors could consider including more information about the university where the data were collected, such as its size, type, and student demographics.
6. The reliance on self-reported measures may introduce potential biases, such as social desirability. Self-reported GPA as an academic performance measure is a concern. The study would benefit from objective academic records or triangulation with instructor evaluations. The authors should acknowledge and/or discuss these limitations in more detail, also including the remedies they have taken for mitigating the common method variance.
7. The CFA results indicate acceptable fit, but a comparison with alternative /nested models (i.e. four-factor structure vs three-factor structure, two-factor structure, etc) could strengthen the measurement model.
8. Figures and tables are well-organized, but Figure 2 (moderation effects) requires a clearer interpretation in the text.
9. The moderation effect of academic self-efficacy is interesting, but interaction plots should be provided to clarify the nature of the moderation.
10. The discussion section provides a thoughtful interpretation of the findings. The authors effectively connect the results to the existing literature and discuss the theoretical and practical implications of the study. However, they could consider expanding the discussion of the non-significant findings related to social cynicism. (For instance, the authors suggest that student cynicism negatively affects performance, but the social dimension of cynicism did not show significant effects. This should be explored in more depth.

11. The discussion should address alternative explanations, such as external stressors or socioeconomic status, that might confound the relationships.

12. The discussion does not sufficiently address practical implications for educational policymakers and university administrators. More concrete recommendations should be included.

13. Several grammatical errors and awkward phrasings are present. A thorough proofreading is recommended.

The manuscript presents a valuable contribution but requires substantial improvements in methodology, analysis, and discussion. Addressing the concerns raised above will significantly enhance the quality of the study and its suitability for publication.

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

In their article, the authors investigated mitigating student cynicism to enhance sustainable academic performance in higher education. They analyzed the interplay of university identification and academic self-efficacy. Main comments that can contribute to improving the quality of the article:

1. The title of the article is too long. I suggest shortening it.
2. In which year was the study conducted?
3. The description of the regression model is very weak and requires a lot of explanation. What is the analytical form of the model? Is it a linear model? Is it a simple regression or multiple regression? The form of this model should be provided. Table 3 provides the results of estimating the model parameters. On the one hand, it seems that this is a multiple regression model. On the other hand, each independent variable has an R-sq value (i.e. R2). This is a measure of the model fit. It is determined for the entire model. Such a notation indicates that this is a single regression model. In addition, the R-sq values ​​are so small that such a model should not be considered at all. Unless the authors considered a different model – nonlinear. But the problem of one or many variables still remains. The authors should explain and justify this very well.
4. In tables and in the text of the manuscript, fractions of the form .200 should be written in the form 0.200. The number 0 should be entered before the decimal separator.
5. The section 7. Limitations is unnecessarily separated. I suggest combining the Limitations section with the Discussion or Conclusion section.
6. The text of the article should be carefully checked for language errors. For example, there are many incorrect words: "identificatin", "skepticism", "siclusion", "intitutional".

Comments on the Quality of English Language

The article contains numerous language errors, e.g. "identificatin", "skepticism", "siclusion", "intitutional".

Author Response

Please see the attachment.

Author Response File: Author Response.pdf

Round 2

Reviewer 2 Report

Comments and Suggestions for Authors

The authors did not make any corrections in accordance with my suggestions. This is especially true for the empirical part of the article. The principles of using linear regression are the same for every field of science. There are no exceptions. The R2 measure informs about the fit of the model to the data. In the case of this study, it is too small. This indicates that the study should be conducted using nonlinear models. It is unacceptable to draw conclusions based on a model with R2 equal to, for example, 0.015. This indicates that the model is correct for only 1.5% of the data. This is definitely too little. In addition, the authors write about certain changes that are not visible in the table with results (Table 3). In this table, only the notation of numbers has been corrected. However, this is an editorial change, not a substantive one. In addition, the R2 measure is still determined for individual variables. As I indicated in the review, it is given for the entire model. In response to the review, the authors wrote that the model had many variables. This is contrary to the results in Table 3. The description of variables in the given model is still imprecise (lines 452-458). In the linear model, variables are defined as numbers. What number is e.g. university identification? The described model does not correspond to the analyzed model.

Author Response

Response to Reviewer 2

Dear Reviewer,

Thank you once again for your detailed and thoughtful feedback. We truly value your input and appreciate the opportunity to revise our manuscript in line with your observations. In this revised version, we have taken your critique seriously and have fundamentally revised the empirical part of the study, far beyond cosmetic or editorial changes.

The revisions made in response to Revision 1 are highlighted in yellow in the manuscript, while the revisions addressing Revision 2 are highlighted in blue.

We respectfully address your points below and highlight how they have been incorporated into the revised manuscript:

1. Concern about the use of linear regression models:

We fully acknowledge your concern regarding the limitations of using linear models. In response, we have thoroughly revised the empirical strategy and now employ both linear and non-linear (quadratic) analyses to better capture the complexity of the relationships among the variables. This dual approach allows us to examine not only straightforward linear effects but also potential curvilinear patterns that may reveal more nuanced dynamics.

Importantly, this shift led to a theoretically meaningful and statistically significant U-shaped relationship between academic cynicism and academic performance, which would have remained undetected using only linear methods. This curvilinear finding contributes novel insight to the literature and opens new directions for further qualitative and longitudinal exploration, as noted in the revised discussion.

Additionally, model fit has been more appropriately addressed: We have used two most popular measures of Akaike information criterion (AIC) and Bayesian information criterion (BIC) for the new models. We believe this revised analytical strategy responds directly to your methodological critique and significantly strengthens the manuscript.

2. Clarification of the analytical model and R² values:

We agree that the original model's structure and reporting were ambiguous. To resolve this, we have now:

• Clearly defined the analytical models used and clarified in both the method and results sections which variables were entered at models
• These corrections are both substantive and structural in nature, and the table format has been updated accordingly.

3. Description and operationalization of variables:

We appreciate your request for clearer variable definitions. In response, we have updated the manuscript to provide:

• Explicit definitions of all variables, including how they are measured and coded.
• A brief rationale for treating these composite scores as interval data suitable for regression analysis, as supported by prior empirical literature and scale validation studies.

This revised explanation appears in the Measures and Data Analysis sections and should now resolve the lack of clarity in lines 452–458 noted in your review.

4. Substantive changes beyond table editing:

While you rightly pointed out that our previous submission appeared to include only editorial changes to Table 3, the current revision includes a complete re-analysis of the data. This includes:

• New linear and nonlinear models,
• Updated abstract and introduction,
• Updated justifications for hypotheses,
• Revised hypotheses,
• Rewritten and clarified tables,
• Updated interpretations in the results and discussion,
• A revised conclusion that reflect the new findings,
• And a new paragraph discussing the implications of the U-shaped relationship, as you rightly noted such a pattern warranted further inquiry.

We are grateful for your detailed critique, which has led to a much stronger, clearer, and more rigorous manuscript. We hope these extensive changes demonstrate our commitment to addressing your concerns in full and that the revised manuscript now meets your expectations regarding methodological robustness and clarity.

Thank you again for your constructive feedback.

Sincerely,

Author Response File: Author Response.pdf

Round 3

Reviewer 2 Report

Comments and Suggestions for Authors

In the new version of the article, the authors included most of the changes suggested in the review.