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The paper can be accepted without further revisions.
[# PeerJ Staff Note - this decision was reviewed and approved by Bob Patton, a PeerJ Section Editor covering this Section #]
All responses are addressed in the revised version of the manuscript.
Investigation is carried and method described are sufficient w.r.t revised version of manuscript.
Findings are validated with proper data.
All review comments are answered and incorporated appropriately.
manuscript is well organized and explored on important point required in current context
methodology given well and implemented too to obtain specific outcomes
findings obtained from the proposed method are valid may be improved in the performance on various datasets/various data sizes
manuscript will be so worthy if mentioned Limitations are reduced and future directions are implemented further
Yes, the revision version is fine.
The results enclosed in revision are fine
Supporting data is provided for validation.
The revision version is acceptable.
The paper needs further major revisions - the authors should clarify more about the dataset used and its features. Also the training ad testing model should be explained in a systematic way.
The authors should follow the comments from the reviewers precisely and clearly.
[# PeerJ Staff Note: Please ensure that all review comments are addressed in a rebuttal letter and any edits or clarifications mentioned in the letter are also inserted into the revised manuscript where appropriate. It is a common mistake to address reviewer questions in the rebuttal letter but not in the revised manuscript. If a reviewer raised a question then your readers will probably have the same question so you should ensure that the manuscript can stand alone without the rebuttal letter. Directions on how to prepare a rebuttal letter can be found at: https://peerj.com/benefits/academic-rebuttal-letters/ #]
The paper aims at addressing role of metacognition in promoting deep learning via MOOCs. The work targets to answer two research questions. The work reported though not novel is acceptable contribution as the attempt is considerable.
Three aspects Critical thinking, Connecting concepts and Creating new concepts are considered as evaluation strategy. The questionnaire enclosed along with manuscript is considered for review.
In my view, A detailed analysis w.r.t Anova would have been better instead of just stating the outcome. Some more w.r.t analysis and key findings would add value. Authors can address these in revision.
Computation enclosed in excel file support for validation. Conclusion is relatable to discussion done in the paper. The approach though not novel is acceptable attempt.
A more comparative evaluation is preferred as present version is limited.
Usually, analysis is expected but analysis part is very limited
These two points may be considered
its an attempt to explore the Role of Metacognition in Promoting Deep Learning in MOOCs during COVID-19 Pandemic. deep learning is not elevated in detail. data set taken for experimentation is not mentioned in detail.
needs more explanation about dataset taken and its features. how they have trained the model and how they tested. utilization of deep learning model to be discussed. Results generated from the proposed idea are limited
somewhat okay but dataset size and features to be enhanced. model should be more scalable with more variety of data and with higher dimensions are able to process in dynamic platform.
more investigation to be done on idea(methodology), dataset taken and projecting the role of deep learning in MOOCs
As per my observation, the studies were done on covid -19 and are related to the title given. Participants were students at the department of home economics who were all at the seventh academic level. Based on their scores on the metacognition awareness inventory, they were divided into two experimental
groups, i.e high metacognition students and low metacognition students done with a small sample.
if it is taken for a large sample will the same results will be appeared?
As per the Author's view 203 out of 260 quantitative MAI points, metacognition was graded into two groups, high 204 metacognition (HM ≥ 65 percent) and low metacognition (LM < 65 percent) in line with Aydın205 and Coşkun (2011); Redondo and López (2018).
In other words, based on their scores on the 206 MAI instrument, participants were divided into two experimental groups.
There is a scope for comparative study. is it possible to incorporate?
is it justifiable that the authors noted that all participants have studied and passed the course's prerequisite 14 courses, mainly Research Methodology, Teaching & Statistics Principles, and Principles of
215 statistics. Performance can be upgraded
Check the Grammar again
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