Career Profiles of University Students: How STEM Students Distinguish Regarding Interests, Prestige and Sextype
Round 1
Reviewer 1 Report
Presentation of research results and also explanation of data analysis is explained very well, a little input to the author in order to add references to the relevance of research results. especially references that refer to the discussion of career, gender and interests
Author Response
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Author Response File: 
Author Response.pdf
Reviewer 2 Report
Review Report
Manuscript ID: education-2239332
Title: Career profiles of university students: How STEM students distinguish regarding interests, prestige and sextype
Authors have used Gottfredson’s dimensions to create latent profiles in the focus of this study regarding career profiles of university freshmen. Results are presented to show eleven latent profiles. Of these, five were considered by prestige levels and two by their sextype. Some of these profiles were related to study outcomes and study satisfaction, allowing at-risk profile identification. This study successfully shows that Gottfredson’s framework can be used for the recognition of at-risk students
I strongly recommend that the Editorial office consider this manuscript for publication in its present form.
Author Response
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Author Response File: Author Response.pdf
Reviewer 3 Report
I read the paper with interest and find the topic particularly important to unhinging gender biases in people's education and careers.
I found, however, no minor difficulty due partly to the length of the paper and the wealth of information provided and partly because of the way the results were presented, starting with the graphs that are difficult to read.
The reader has difficulties getting an immediate idea of the characteristics of the clusters because of their number and behavior concerning the validation variables given. A summary table of the main issues may help.
I doubt the interpretation and commentary of the results concerning the percentages of males and females: since, in the total sample, these are more than males (61% vs. 39%), it does not seem to me that this is taken into account when describing and interpreting the clusters. For example, in P3, defined as "somewhat sex balanced," if we consider that in the total sample, they are 61% and here 58%, we should define it as "balanced," while P11, in which they are 50%, as "somewhat balanced" because the percentage is lower than in the total sample. In other words, the percentages should be calculated within the sex, not within the cluster, and then compared between males and females.
A second technical issue concerns using the RIASEC model: several studies have shown how this model is weaker outside the U.S., to the point of being untraceable if we move culturally away from Western nations. In this research, no verification is indicated to the consistency of the hexagonal model, especially about the order of the dimensions, but also the similarity to a model that considers the dimensions as equidistant.
Author Response
Please see the attachment.
Author Response File: Author Response.pdf
Round 2
Reviewer 3 Report
While I remain doubtful about the excess of results presented, I think this version is more understandable than the previous one, and the summary table helps a lot to get an overall idea of the different profiles.
