Computational Thinking (CT) towards Creative Action: Developing a Project-Based Instructional Taxonomy (PBIT) in AI Education

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

I highly comment you on this publication, it is near and dear to my heart and during our research we came to some very similar conclusions. CT is incredibly helpful to develop future skills in curious students and your extension of Blooms Taxonomy is a smart addition to the current knowledge space. I would like to know more about the data you have collected during the last two years, I imagine there may be some differences between Chinese students and Austrian students were I am situated. I would be interested to compare and contrast your findings and generally have a look at the underlying data. So if I may make one recommendation it is to publish your data and inquire the community to use your framework in a variety of countries.
It truly is seldom to review research that is so close to my own interests and I was pleased to see the level of understanding you clearly developed.

One last remark, as I am sure you stumbled upon the staggering differences in definitions of CT as a skillset, I would appreciate to know the definition you are working with and the school of thought you are following.

Thank you for your work, I am looking forward to reading and working with your published article.

Author Response

Dear reviewer, 

Many thanks for your efforts of peer-review of our submission, and we have been very glad to hear our article is close to your research interests especially in the context in Austria. We summarise two main points from your comments: 

One is about the definition of CT, we have followed the basic meaning from Wing, and particularly regard CT as one of terms of problem-solving skills. This  point has been added in  section 2.1 in the revised version. 

The other suggestion is to include more data during past two years. Accordingly some new findings during 2023-2024 have been added in Discussion. We also added one more section 4.1 Method: A Case of An Example, which also helps to explicitly strengthen how we apply theoretical model into real teaching practice. 

Hopefully the above responses will move on our publication, and we are looking forwards to hearing more suggestions and a great collaboration with you in the future. 

Best regards

Authors 

Reviewer 2 Report

Comments and Suggestions for Authors

This paper shows a model of Project-Based Instructional Taxonomy (PBIT) with the intention that it can be used in the classroom and contribute to the improvement of computational thinking. Subsequently, it presents a case in which the model has been used successfully.

Although it is an interesting paper, there are some aspects that should be improved for its publication.

It would be advisable to modify the title and avoid mentioning Artificial Intelligence. From reading the article, nothing can be deduced regarding AI Education.

Some aspects about Applying PBIT in Education Practice must be explained. Authors should specify the methodology, such as the number of participants, the procedure followed during the experimentation, the timing or the way of selection of the evidence.

In relation to the above, it would also be convenient to include an example that follows the six stages of the project workflow and that can clarify how to progress in it. This could accompany Figure 4 as part of it, or be included as part of the text. Also, Figure 3 must be changed to Figure 4 (line 288).

The discussion includes aspects that would correspond to results and that would be convenient to relocate. In addition, some statements are made without justification or argument, such as ”For example, students provided solutions to solve problems like ‘Simulating AND, OR, 416 and NAND Gates with Perceptron’ or ‘Simulating Loss Function in High-Level Program-417 ming Language’. This indicated that students mastered comprehensive understanding of binary CT, decimal CT, and programming skills.” But, why? or how?

However, the same section does not include discussion in relation to previous studies, which could be included.

 

Author Response

Dear reviewer, 

Many thanks for your efforts of peer-review of our submission, and we have been very grateful for your comments and suggestions. We summarise two main points from your comments: 

The first comment is about whether this paper includes AI education. We regard CT as one of basic skills in relation to learning AI and AI literacy in both a narrow sense of discipline-based education and a broad sense of AI-related learning contexts, especially in the contexts of solving problems using computer thinking and competencies. This can be identified by our definition regarding CT as one of everyone's daily life skills, as a part of problem-solving skills and a part of creativity. In particular, the case also reflects how we use the new developed model in the bachelor AI education program in one of Chinese universities. 

The second suggestion is to include more data and methodology in the paper.  Accordingly some new findings during 2023-2024 have been added in Discussion. We also added one more section 4.1 Method: A Case of An Example, which also helps to explicitly strengthen how we apply theoretical model into real teaching practice. The method is also in line with research question in our article. 

The third comment is about how to address more on the six stages of project workflow. We have to state that the workflow is designed as one of tools to facilitate student project process. This has been explained already in the current lines, and we also have numbered the figures in correct way. 

The last point is about how to improve the Discussion. We have added the findings from 2022-2023. We also would like to explain that the discussion is following the case and involve more reflective discussion.Our study is very innovative that leads to a conclusion with both advantages and limitations, and implications for the future. 

Hopefully the above responses will move on our publication, and we are looking forwards to hearing more suggestions and a great collaboration with you in the future. 

Best regards

Authors 

Reviewer 3 Report

Comments and Suggestions for Authors

The paper introduces a novel model called Project-Based Instructional Taxonomy (PBIT) to aid course design to enhance Computational Thinking (CT) development for creative problem-solving.

It presents in a very extensive way the framework behind the course design and describes in detail how it is implemented, for example, the workflow and the students' grading system.

 

However, it fails to outline the research methodology employed, detailing how the PBIT model was developed and how its application was studied. It mentions the case study method, focusing on a specific course within a bachelor program at Northeastern University (NEU) in China, but there is no evidence of a research method application. Therefore, the section related to the discussion of the results is weak, not including data, analyses, and relevant statistics achieved during the experimentation.

Author Response

Dear reviewer, 

Many thanks for your efforts of peer-review of our submission, and we have been very grateful for your comments and suggestions. We summarise the main point is to improve the method of this article. 

Accordingly some new findings during 2023-2024 have been added in Discussion. We also added one more section 4.1 Method: A Case of An Example, which also helps to explicitly strengthen how we apply theoretical model into real teaching practice. 

Hopefully the above response will move on our publication, and we are looking forwards to hearing more suggestions and a great collaboration with you in the future. 

Best regards

Authors 

Round 2

Reviewer 3 Report

Comments and Suggestions for Authors

The paper has been improved with respect to the previous one.