Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

• * Do you have any other ethical concerns about this study?

• It’s unclear whether explicit consent was obtained from students whose data were used.

• The paper does not mention whether institutional review board (IRB) or ethics committee approval was obtained—this is typically required for studies involving human data.

Comments on the Quality of English Language

The paper contains several issues related to grammar, sentence structure, and stylistic clarity. Common problems include inconsistent verb tenses, overly long and complex sentences, occasional awkward phrasing, and misuse of articles and prepositions. Additionally, some technical and academic expressions could be improved for greater precision and conciseness.

To enhance readability and professionalism, it is recommended that the manuscript undergo comprehensive language editing by a native English speaker or professional academic editor. This will improve grammatical accuracy, clarity of expression, and overall fluency.

Author Response

Comment 1 and 2: The English could be improved to more clearly express the research.

Response: We agree that the manuscript should be improved to more clearly express our research. Therefore, we have revised our manuscript to improve the quality of the paper.

Firstly, we change it to ACS format then rewrite some sentences for more clarification.

For example, in abstract section the original sentence "Artificial Intelligence has fundamentally reshaped college curricula by promoting a data-driven personalisation approach that improves student outcomes and aligns educational programs with workforce needs." has been modified as "Artificial Intelligence is fundamentally transforming college curricula by enabling data-driven personalization, which enhances student outcomes and better aligns educational programs with evolving workforce demands." 

We have improved some sentences in Introduction, Methodology, Results, Discussion, Ethical Considerations and Conclusion.

Author Response File: Author Response.pdf

Reviewer 2 Report

Comments and Suggestions for Authors

Review Report

- Paper titled "Artificial Intelligence in Curriculum Design: A Data-Driven Approach to Higher Education Innovation".

 

The paper is well-structured and relevant. However, it needs proofreading to enhance its readability. Also, following the report recommendations may improve its quality.

Suggestions for Improvement: 

1. Title

- I may suggest updating the title to a more readable and attractive to readers: "Revolutionizing Higher Education: AI-Driven Curriculum Design for Personalized Learning and Industry Alignment"

 

2. Abstract 

- The abstract lacks a clear statement of the research gap or originality. Therefore, state clearly the research gap (e.g., limitations of traditional curriculum design).

- Explain the comparison group (traditional curricula) earlier in the abstract.

 

3. Introduction 

- The section on study objectives needs to be edited and proofread so that it is easier to read. 

- Make the change to research objectives go more smoothly by giving a short summary of what makes the study unique or important.

-  To make the case stronger, focus on the specific issue (for example, the fact that curriculum doesn't always match up with business needs).

 

4. Research Problem

The problem statement lacks precision, as it encompasses various issues (personalization, industry relevance, student outcomes) without establishing a clear priority among them. The study's scope, including specific disciplines or institutions, remains ambiguous. Consequently:

- Refine the problem statement to emphasize a primary focus, such as the lack of personalization in curriculum design, while recognizing secondary issues.

- Clarify the scope by specifying particular types of institutions or disciplines to improve focus.

- Clearly outline the repercussions of failing to address the issue, such as reduced employability, lower student engagement

5. Literature Review

- Add a literature review section to your manuscript.

- Group studies by theme (e.g., AI for customization, AI for industry alignment) and critically assess their shortcomings.

- State how this study expands on or differs from previous studies.

- Add 2024 and 2025 studies to your literature to reflect the rapid evolution of AI in education.

 

6. Research Gaps:

The introduction and literature review do not specify what knowledge or methodological gaps this work addresses. It is unknown whether these gaps is in AI technique application, implementation size, or ethical considerations. So:

- Identify one or two gaps, such as insufficient attention on ethical AI implementation or absence of scalable AI models for curriculum customisation.

-  Justify the study's contribution by linking gaps to its objectives.

- Explain how the mixed-methods study solves these gaps.

 

7. Theoretical Background

The absence of a dedicated theoretical background section diminishes the academic rigor of the paper.  The text mentions predictive analytics and adaptive learning but fails to anchor these concepts within a theoretical framework, such as learning theories or technology acceptance models.  This omission restricts the study's capacity to theoretically contextualize the role of AI in education.  Consequently:

 - Include a succinct theoretical background section that addresses pertinent frameworks, such as constructivism in relation to personalized learning and human-computer interaction concerning AI adoption.

 - Connect the theoretical framework with the methodology and results of the study.

 

8. Methodology

- Provide details on sample size, participant demographics (e.g., students, faculty), and AI model configurations (e.g., hyperparameters, training datasets).

- Elucidate the time frame of data collection and the institutions included.

- Clarify on bias mitigation techniques (e.g., fairness metrics, diverse training data) to reinforce ethical rigor.

 

9. Results Presentation

- There are clear measurements and statistically strong outcomes with well-presented results. While quantitative data is useful, authors should supplement it with qualitative findings (such as interviews with educators or industry experts) to enhance the results narrative and provide a more complete picture.

 

10. Discussion

- Discuss unexpected findings (e.g., lower constructive feedback in AI curricula) or potential alternative explanations.

- Clarify on practical implications for institutions (e.g., implementation costs, faculty training) and policy guidelines (e.g., AI governance in education).

- Reinforce the connection to the theoretical framework (if added) to enhance academic rigor.

- Add a separate section of study limitations with future research directions.

 

9. References

- Include more 2024–2025 studies on AI in education to reflect the latest trends. I suggest you add:

Soliman, M., Ali, R.A., Khalid, J. et al. (2024). Modelling continuous intention to use generative artificial intelligence as an educational tool among university students: findings from PLS-SEM and ANN. J. Comput. Educ. 12(1), 1-32. https://doi.org/10.1007/s40692-024-00333-y

Soliman, M., Ali, R.A., Noipom, T. (2025). Unlocking AI-Powered Tools Adoption among University Students: A Fuzzy-Set Approach. Journal of Information and Communication Technology. 24(1). https://doi.org/10.1186/s40561-024-00357-y

 

 

 

Comments for author File: Comments.pdf

Author Response

The review 2 has same comments with the review 1.  The manuscript has been already improved.

Author Response File: Author Response.pdf

Reviewer 3 Report

Comments and Suggestions for Authors

The author is not consistent in writing the reference list, the references in the article are written in a different style than the references.

The reference style of the article seems to use APA style and the reference list seems to use Vancouver or Chicago references. Please check the instructions in the journal again.

Author Response

The review 3 did not require to improve English writing.

Round 2

Reviewer 2 Report

Comments and Suggestions for Authors

- Add a literature review section to include a critical synthesis of prior studies, addressing contradictions and research gaps.  

 

 - Add a succinct theoretical background section that addresses pertinent frameworks, such as constructivism in relation to personalized learning and human-computer interaction concerning AI adoption.

 

- Clarify on practical implications for institutions (e.g., implementation costs, faculty training) and policy guidelines (e.g., AI governance in education).

 

- Add a separate section on study limitations with future research directions.

 

- Include more 2024–2025 studies on AI in education to reflect the latest trends. I suggest you add:

Soliman, M., Ali, R.A., Khalid, J. et al. (2024). Modelling continuous intention to use generative artificial intelligence as an educational tool among university students: findings from PLS-SEM and ANN. J. Comput. Educ. 12(1), 1-32. https://doi.org/10.1007/s40692-024-00333-y

Soliman, M., Ali, R.A., Noipom, T. (2025). Unlocking AI-Powered Tools Adoption among University Students: A Fuzzy-Set Approach. Journal of Information and Communication Technology. 24(1). https://doi.org/10.1186/s40561-024-00357-y

Author Response

Comment 1: Add a literature review section to include a critical synthesis of prior studies, addressing contradictions and research gaps.  

Response 1: Thank you for pointing out. We agree with this comment. Therefore, we have added literature review section from page 3.

 

Comment 2: Add a succinct theoretical background section that addresses pertinent frameworks, such as constructivism in relation to personalized learning and human-computer interaction concerning AI adoption.

Response 2: Agree, we have added section 3 Theoretical Background to emphasize this point from page 5.

 

Comment 3: Clarify on practical implications for institutions (e.g., implementation costs, faculty training) and policy guidelines (e.g., AI governance in education).

Response 3: We agree and have added section 7 Practical Implications from page 12.

 

Comment 4: Add a separate section on study limitations with future research directions.

Response 4: We agree and have added section 8 Study Limitation and Future Research from page 14.

 

Comment 5: Include more 2024–2025 studies on AI in education to reflect the latest trends. I suggest you add:

Soliman, M., Ali, R.A., Khalid, J. et al. (2024). Modelling continuous intention to use generative artificial intelligence as an educational tool among university students: findings from PLS-SEM and ANN. J. Comput. Educ. 12(1), 1-32. https://doi.org/10.1007/s40692-024-00333-y

Soliman, M., Ali, R.A., Noipom, T. (2025). Unlocking AI-Powered Tools Adoption among University Students: A Fuzzy-Set Approach. Journal of Information and Communication Technology. 24(1). https://doi.org/10.1186/s40561-024-00357-y

Response 5: We have included these 2 papers to the paper.

Author Response File: Author Response.pdf