The Role of Automated Diagnostics in the Identification of Learning Disabilities: Bayesian Probability Models in the Diagnostic Assessment

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The manuscript presents a novel topic of special interest in the assessment and diagnosis of specific learning disabilities, based on Bayesian probability models. To do so, they review documentation from a sample of students with this disorder and apply Bayes' probability theorem to each variable to predict the diagnosis based on that information. Their conclusions are very interesting.

 

Strengths

- Topic

- Introduction

- Conclusions

 

Limitations

- Abstract

- Method

- Results

 

Areas for improvement:

Title and abstract:

1. The title indicating automated diagnostics deviates from the content of the article; a reference should be made to a probabilistic or Bayesian model.
2. The abstract should NOT include citations. Furthermore, it is inappropriate to cite self-citations, especially at the beginning of the document.
3. The abstract should include: a brief theoretical introduction (two lines), objectives (yes), method (sample, variables, and design), results, and conclusions.
4. The authors have not briefly included some theoretical introduction or contextualization ideas, and the other sections are vague.
5. The objectives of the work are not explicitly stated.

Theoretical Introduction

1. The DSM-5 and ICD-11 do not have the corresponding citations (authors).
2. Acronyms should be preceded by their meaning, as is the case with QCA, but those referring to fsQCA are missing (line 41).
3. Lines 92-95 should be deleted or rewritten, as they are conclusions of this work. The bases of the work should be stated here, not its consequences.
4. The authors highlight diagnostic beliefs in a subsection, but then this variable is not measured. This should be clear: why is this section included?
5. In contrast, the "predictor" variables included in the model are not even mentioned in the introduction. A brief explanation should be provided of the variables that may frequently appear in the reports and are related to the diagnosis of LD.
6. This section should end with a clear and explicit presentation of the objectives of the study and, if applicable, hypotheses.

Materials and Method

7. This section detracts from the work and is unclear. It should be completely rewritten.
8. This information would possibly be useful in the theoretical introduction as a justification for the statistical procedures to be used.
9. This section should be reorganized, presenting the participants, procedure, design, and data analysis first.
10. Some of the information is in the results section (lines 202-245) and should be included in the following sections.

Participants

11. The research participants should be described, not only their age, sex, and number, but also their sociocultural status, participating school, family information, etc.

Variables or Measures

12. The variables taken into account must be presented.

Procedure

13. A description of the evaluation process or the extraction of variable categories.
14. Ethical permission is not included, nor are ethical issues, such as requesting participation from the school administration and legal guardians.

Design and Data Analysis

15. The design could be included here and explained in greater detail.
16. The statistical tests used should be included according to the study objectives.

Results

17. The results should be divided according to the study objectives and presented in subsections.
18. Abbreviations or colors in tables or figures should be explained with brief footnotes.
19. Figure 1 is not visible, which is a shame given the valuable information it contains. It should be enlarged or divided into two.
20. Each equation should be named with a number (1), equation, etc.
21. Conclusions do not contain figures; they must be included in the results.

Discussion

22. Here, authors should begin by stating the objective of the study explicitly, not implicitly.

Conclusions

23. Contains all necessary ideas.
24. It is recommended that limitations and future lines be included in this section.

Citations and References

25. Citations and references are in APA format.
26. Some citations do not comply with the format and have quotation marks (line 557) and do not have the journal in italics (line 560). This aspect detracts from the article's merit.

 

 

 

Author Response

Dear Reviewer,

I would like to sincerely thank you for the time and effort devoted to reviewing my manuscript. Your detailed comments and constructive suggestions were extremely valuable and helped me improve the quality and clarity of the paper significantly.

I have carefully revised the manuscript in accordance with your recommendations, addressing each point raised. I am confident that these changes have strengthened the work, both methodologically and conceptually.

Once again, I greatly appreciate your contribution and support in this process.

With kind regards

Reviewer 2 Report

Comments and Suggestions for Authors

This is an interesting and original paper that explores the role of abductive reasoning, Bayesian networks, and fuzzy set analysis in the identification of learning disabilities. The combination of qualitative comparative analysis and Bayesian modeling is both innovative and valuable, offering new perspectives on diagnostic pathways in special education.

Strengths:

• Clear methodological design and appropriate application of statistical and probabilistic tools.

• Results are presented in a structured way with supportive tables and visualizations.

• The paper is well referenced, drawing on both classical and recent scholarship.

• Practical implications for pre-screening and decision-support in inclusive education are significant.

Areas for improvement:

• The English expression could be polished to improve readability and accessibility for an international audience.

• The discussion of unexpected or counterintuitive correlations (e.g., vocabulary vs. verbal comprehension index) should be expanded and contextualized more clearly.

• The limitations section should more explicitly acknowledge issues such as the absence of a control group and reliance on SNI cases only.

• While the outlook on automation is promising, the discussion could benefit from a more concrete reflection on how abductive reasoning might be integrated into software-based AI or decision-support systems in practice.

Overall, this is a strong and valuable contribution to the field. With minor revisions, the paper will be well suited for publication.

Comments on the Quality of English Language

The paper is original, methodologically sound, and offers a significant contribution to scholarship on learning disability diagnostics. No ethical concerns or plagiarism detected. Minor revisions regarding language clarity and elaboration of limitations are recommended.

Author Response

Dear Reviewer,

I would like to sincerely thank you for the time and effort devoted to reviewing my manuscript. Your detailed comments and constructive suggestions were extremely valuable and helped me improve the quality and clarity of the paper significantly.

I have carefully revised the manuscript in accordance with your recommendations, addressing each point raised. I am confident that these changes have strengthened the work, both methodologically and conceptually.

Once again, I greatly appreciate your contribution and support in this process.

With kind regards,

Author Response File: Author Response.docx