Quantitative and qualitative evaluation of a learning model based on workstation activities

Judit Sánchez; Cristina Andreu-Vázquez; Marta Lesmes; Marta García-Lecea; Iván Rodríguez-Martín; Antonio S. Tutor; Beatriz Gal

doi:10.1371/journal.pone.0236940

Peer Review History

Original SubmissionFebruary 9, 2020
25 Jun 2020 Decision Letter - Andrew R. Dalby, Editor PONE-D-20-03757 Quantitative and qualitative evaluation of a learning model based on workstation activities PLOS ONE Dear Dr. Gal, Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. Currently the paper does not meet even the lowest level of criteria for publication in PLoS One. Most specifically there is no clear question that is addressed by the research. This means that the paper needs a very extensive rewrite before it will be suitable for publication. To start with there needs to be a clear explanation of the expected differences that you think will occur because of the use of the work-station based methods. The introduction needs to be strengthened with a deeper look at theory and in particular current methods of teaching and extrinsic and intrinsic motivation theory as well as Bloom and extensions from Bloom. If you are not able to meet the publication criteria in a revised manuscript then it may be rejected at that stage. I have attached a copy of the manuscript with some more detailed comments. Please submit your revised manuscript by Aug 09 2020 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file. Please include the following items when submitting your revised manuscript: A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'. A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'. An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'. If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter. If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols We look forward to receiving your revised manuscript. Kind regards, Andrew R. Dalby, PhD Academic Editor PLOS ONE Journal Requirements: When submitting your revision, we need you to address these additional requirements. 1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf 2. PLOS ONE will consider submissions that present new methods, software, or databases as the primary focus of the manuscript if they meet the criteria of utility, validation, and availability described here: http://journals.plos.org/plosone/s/submission-guidelines#loc-methods-software-databases-and-tools. To meet these criteria, please provide supporting materials enabling other teachers and researchers to replicate your teaching intervention such as sample worksheets, a detailed lesson plan or curriculum or other educational materials. If you include supporting materials, they should not be under a copyright more restrictive than CC-BY. 3. Thank you for stating the following in the Funding Section of your manuscript: "This work was funded by the 2017-2018 Wilson Award and the 2018/UEM20" We note that you have provided funding information that is not currently declared in your Funding Statement. However, funding information should not appear in the Acknowledgments section or other areas of your manuscript. We will only publish funding information present in the Funding Statement section of the online submission form. Please remove any funding-related text from the manuscript and let us know how you would like to update your Funding Statement. Currently, your Funding Statement reads as follows: "The author(s) received no specific funding for this work" 4. We note that you have indicated that data from this study are available upon request. PLOS only allows data to be available upon request if there are legal or ethical restrictions on sharing data publicly. For information on unacceptable data access restrictions, please see http://journals.plos.org/plosone/s/data-availability#loc-unacceptable-data-access-restrictions. In your revised cover letter, please address the following prompts: a) If there are ethical or legal restrictions on sharing a de-identified data set, please explain them in detail (e.g., data contain potentially identifying or sensitive patient information) and who has imposed them (e.g., an ethics committee). Please also provide contact information for a data access committee, ethics committee, or other institutional body to which data requests may be sent. b) If there are no restrictions, please upload the minimal anonymized data set necessary to replicate your study findings as either Supporting Information files or to a stable, public repository and provide us with the relevant URLs, DOIs, or accession numbers. Please see http://www.bmj.com/content/340/bmj.c181.long for guidelines on how to de-identify and prepare clinical data for publication. For a list of acceptable repositories, please see http://journals.plos.org/plosone/s/data-availability#loc-recommended-repositories. We will update your Data Availability statement on your behalf to reflect the information you provide. 5. Your ethics statement must appear in the Methods section of your manuscript. If your ethics statement is written in any section besides the Methods, please move it to the Methods section and delete it from any other section. Please also ensure that your ethics statement is included in your manuscript, as the ethics section of your online submission will not be published alongside your manuscript. [Note: HTML markup is below. Please do not edit.] Reviewers' comments: Reviewer's Responses to Questions Comments to the Author 1. Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: No ******** 2. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: Yes ****** 3. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified. Reviewer #1: Yes ****** 4. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #1: Yes ****** 5. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: The authors describe a learning model that by modern educational research standards would be obviously better than pure lecture and the benefit would show up to a greater extent on more conceptually difficult to answer questions, unless technical details were poorly done. There is not an open research question to answer here. This is a quality assurance project (were these materials well designed at the details level). While Bloom's Taxonomy remains popular in applied contexts, it is terribly outdated. The full taxonomy has many levels beyond just higher and lower as a binary. There never was a clear empirical basis for the original taxonomy, nor has there been a systematic validation of it or the revised one. "Apply" is a hopelessly broad category. Webb's Domains of Knowledge could be used, since it actually has some empirical support. If one wants to use a general framework from this century, I would suggest Chi and colleagues' ICAP framework. Easy and clear in how to use it in research; strong empirical validation. As an empirical study, there were also many problems. The two cohorts were not checked for equivalence on incoming standards. Focusing on just one model is thin from a generalizability standpoint. Using one multiple choice question is terrible from a measurement perspective. The interview analysis had a clear bias of interpretation: when the students asserted that the combination of lecture and workstation was important, the authors assumed (ironically!) that the students were wrong and their answers reflected cultural bias. ****** 6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review?** For information about this choice, including consent withdrawal, please see our Privacy Policy. Reviewer #1: No [NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.] While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step. https://doi.org/10.1371/journal.pone.0236940.r001
Revision 1
15 Jul 2020 Author Response Reviewer #1: The authors describe a learning model that by modern educational research standards would be obviously better than pure lecture and the benefit would show up to a greater extent on more conceptually difficult to answer questions, unless technical details were poorly done. There is not an open research question to answer here. This is a quality assurance project (were these materials well designed at the details level). We apologize our research question was not clearly posed in the previous version. Please note we introduced the WSLA in 2016, as a flexible learning instrument in our university. Up to that moment, most teaching followed classical methodology and basic and clinical sciences were poorly integrated. Thus, our main motivation with this work was to evaluate quantitative and qualitatively whether and how WSLA affects academic performance and to understand student´s experience with the methodology. We found WSLA useful to integrate learning at the higher cognitive level while promoting student engagement. We have revised the manuscript to make our question clearer. See Abstract (first paragraph) and Introduction (last paragraph). While Bloom's Taxonomy remains popular in applied contexts, it is terribly outdated. The full taxonomy has many levels beyond just higher and lower as a binary. There never was a clear empirical basis for the original taxonomy, nor has there been a systematic validation of it or the revised one. "Apply" is a hopelessly broad category. Webb's Domains of Knowledge could be used, since it actually has some empirical support. If one wants to use a general framework from this century, I would suggest Chi and colleagues' ICAP framework. Easy and clear in how to use it in research; strong empirical validation. We thank the reviewer for bringing our attention to this very important point. We feel that in the context of our study, Bloom’s and Webb’s definitions apply in relation to learning goals and assessment. The empirical character of the learning framework is another aspect to consider. We appreciate the reviewer suggestions to rely on the ICAP framework, but because our practice was focused on learning objectives, our study adopted Bloom´s taxonomy. Notably, we don’t see Bloom´s taxonomy as binary. The fact that we identified difference at low and high levels rather reflects the effect in the continuum of the cognitive spectrum. However, we feel that incorporating the reviewer´s perspectives benefits the analysis of our work. Indeed, the WSLA as a flexible learning instrument allows combining multiple perspectives. Thus, we have substantially edited the Introduction to connect the evolution from Bloom’s and Webb’s considerations into more constructive and empirically demonstrated frameworks, such as ICAP. Later, at the Discussion, we revolve around these ideas to extend the reach of our conclusion further and we suggest indeed that adopting ICAP is desirable for a future work. We feel the manuscript has gained a wider view. See Introduction and Discussion. As an empirical study, there were also many problems. The two cohorts were not checked for equivalence on incoming standards. We appreciate this comment. We have added information on incoming standards in the revised version. See page 5. Focusing on just one model is thin from a generalizability standpoint. We understand the reviewer meant the WSLA model. Please, note that our motivation was to assess this model versus the traditional. Of course, we are running different programs and models in our everyday health science education. Those are now under review in other journals. We feel it is important for clarity sake to address them one by one. Using one multiple choice question is terrible from a measurement perspective. Indeed, we had many multiple choice questions to measure each learning objective. However, we included only those questions meeting statistical criteria regarding similar difficulty and discrimination index and quality of questions in the two cohorts to avoid confounding factors. While this was specified in Materials and Methods of the previous version, we have revised the current version to make even clearer. See page 6. The interview analysis had a clear bias of interpretation: when the students asserted that the combination of lecture and workstation was important, the authors assumed (ironically!) that the students were wrong and their answers reflected cultural bias. We fully agree. Thank you for highlighting this. This was removed in the masnucript accordingly. Attachments Attachment Submitted filename: Rebuttal Letter-PlosOne.docx https://doi.org/10.1371/journal.pone.0236940.r002
17 Jul 2020 Decision Letter - Andrew R. Dalby, Editor Quantitative and qualitative evaluation of a learning model based on workstation activities PONE-D-20-03757R1 Dear Dr. Gal, We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements. Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication. An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org. If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org. Kind regards, Andrew R. Dalby, PhD Academic Editor PLOS ONE Additional Editor Comments (optional): Reviewers' comments: https://doi.org/10.1371/journal.pone.0236940.r003
Formally Accepted
23 Jul 2020 Acceptance Letter - Andrew R. Dalby, Editor PONE-D-20-03757R1 Quantitative and qualitative evaluation of a learning model based on workstation activities Dear Dr. Gal: I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department. If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org. If we can help with anything else, please email us at plosone@plos.org. Thank you for submitting your work to PLOS ONE and supporting open access. Kind regards, PLOS ONE Editorial Office Staff on behalf of Dr. Andrew R. Dalby Academic Editor PLOS ONE https://doi.org/10.1371/journal.pone.0236940.r004

Open letter on the publication of peer review reports

PLOS recognizes the benefits of transparency in the peer review process. Therefore, we enable the publication of all of the content of peer review and author responses alongside final, published articles. Reviewers remain anonymous, unless they choose to reveal their names.

We encourage other journals to join us in this initiative. We hope that our action inspires the community, including researchers, research funders, and research institutions, to recognize the benefits of published peer review reports for all parts of the research system.

Learn more at ASAPbio .