Enhance College AI Course Learning Experience with Constructivism-Based Blog Assignments

Round 1

Reviewer 1 Report (Previous Reviewer 1)

Comments and Suggestions for Authors

• Incorporate recent studies in AI education and digital learning to make the research feel more up-to-date and relevant.
• Clarify how the qualitative and quantitative findings were combined to provide a more cohesive understanding of the results.
• Expand on how the findings could be applied to other AI-related subjects or broader educational settings.
• Simplify some of the more complex sentences to ensure the content is easy to read and understand.
• Provide ideas on how the blog-based approach can be adapted for use in other STEM courses or online learning environments.
• Double-check that all in-text citations match the reference list and follow a consistent format.

Comments on the Quality of English Language

• The language in the manuscript is clear and professional overall, making the content easy to follow.
• Some sentences are a bit too complex and could be simplified to make them more reader-friendly.
• A few minor grammatical issues can be corrected to improve the flow of the text.
• Consistent use of technical terms throughout the manuscript would help avoid any confusion.
• While the quality of English is good and does not affect comprehension, refining it further would make the paper even more polished and engaging.

Author Response

Comments 1: Incorporate recent studies in AI education and digital learning to make the research feel more up-to-date and relevant.  
Response 1: Thank you for your suggestion. We have added additional references to recent studies on AI and digital learning to the manuscript. Indeed, there are only a few works that focus on blogs in teaching, and we noticed that very few of them specifically address AI courses. The added references are:  
[1] Winkler, R., Hobert, S., Salovaara, A., Söllner, M., & Leimeister, J. M. (2020). Sara, the lecturer: Improving learning in online education with a scaffolding-based conversational agent. In *Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems* (pp. 1-14).  
[2] Meirbekov, A., Nyshanova, S., Meiirbekov, A., Kazykhankyzy, L., Burayeva, Z., & Abzhekenova, B. (2024). Digitisation of English language education: Instagram and TikTok online educational blogs and courses vs. traditional academic education. How to increase student motivation?. Education and Information technologies, 29(11), 13635-13662. 
[3] Brott, P. E. (2023). Vlogging and reflexive applications. Open Learning: The Journal of Open, Distance and e-Learning, 38(3), 281-293.

 

Comments 2: Clarify how the qualitative and quantitative findings were combined to provide a more cohesive understanding of the results.  
Response 2: Thank you for your comments. Quantitatively, we analyzed data collected through structured questionnaires, which allowed us to identify statistical relationships. Additionally, we conducted interviews to gather nuanced insights and contextual explanations that complemented the quantitative data. The integration of these two methods was achieved by using the qualitative findings to interpret and elaborate on the quantitative results. For instance, while the survey data provided measurable outcomes, the interview responses helped explain the underlying reasons behind those outcomes, offering a deeper and more comprehensive understanding of the research findings. This combination ensured that the results were not only statistically robust but also contextually rich and meaningful. We have elaborated on this in line 54 of the revised manuscript and updated the corresponding expressions in the abstract section.  

 

Comments 3: Expand on how the findings could be applied to other AI-related subjects or broader educational settings.  
Response 3: We have added additional discussion on the application of the findings to other subjects (see line 425). Specifically, in computer vision courses, students could use the blog-based platform to document their progress on projects, such as image classification or object detection. They could share their code, discuss challenges, and receive feedback from peers and instructors. This continuous interaction would help deepen their understanding of complex algorithms and improve their problem-solving skills. For machine learning courses, students could blog about their experiences with different algorithms, datasets, and model tuning techniques. They could also discuss the ethical implications of their models, fostering a more holistic understanding of the subject. The strategy could serve as a space for collaborative learning, where students share insights and troubleshoot issues together. Therefore, the teaching strategies and solutions proposed are broadly applicable across various AI domains.  

 

Comments 4: Simplify some of the more complex sentences to ensure the content is easy to read and understand.  
Response 4: Thank you for your comments. We have reviewed all the complex sentences and revised them into simpler, more accessible language.  

 

Comments 5: Provide ideas on how the blog-based approach can be adapted for use in other STEM courses or online learning environments.  
Response 5: Thank you for your comments. We have added additional discussion on the application of the findings to other subjects (see line 425). Please refer to our response to Comment 3 for details.  

 

Comments 6: Double-check that all in-text citations match the reference list and follow a consistent format.  
Response 6: We have carefully reviewed all the references to ensure consistency and accuracy.  

 

Comments 7 on English: The language in the manuscript is clear and professional overall, making the content easy to follow. Some sentences are a bit too complex and could be simplified to make them more reader-friendly. A few minor grammatical issues can be corrected to improve the flow of the text. Consistent use of technical terms throughout the manuscript would help avoid any confusion. While the quality of English is good and does not affect comprehension, refining it further would make the paper even more polished and engaging.  
Response 7: Thank you for your positive feedback. We have revised the manuscript per the suggestions of native speakers to improve clarity, grammar, and flow.  

 

Reviewer 2 Report (New Reviewer)

Comments and Suggestions for Authors

The paper, Enhance College AI Course Learning Experience with Constructivism-based Blog Assignments, delves into an important atopic that resonates with the evolving landscape of education. By integrating constructivist principles with blog assignments, the study offers a novel approach to enhancing student learning outcomes in college-level AI courses in China. I thoroughly enjoyed reading this paper, as it provides valuable insights  that educators can adopt to foster deeper understanding and meaningful learning experiences in the field of artificial intelligence and in any educational filed. However, I have the following comments that should enhance the quality of the paper.

·       The title needs revision. It does not fit with the aim of the study. Since the study primarily measures students' perceptions of the AI course design, learning abilities, experiences, outcomes, and satisfaction, all in the context of constructivism-based blog assignments. That is not reflected in the title.

·       The abstract need revision as it does not explicitly state that the study focuses on students' perceptions, which is a key aspect of the research.

·       The abstract needs to mention the data collection tools, the qualitative and quantitative tools (e.g., surveys, interviews).

·       The abstract should provide main recommendations.  

·       "The text in line 117 requires a language revision to use lowercase for consistency. Suggested revision: 'Autonomous learning and collaborative exploration. Constructivism emphasizes combining...'

·       "Line 193 requires revision to expand the paragraph into three or more sentences for better clarity and depth.

·       In table 3 there is need to add number of items in each dimension and I suggest combining table 1 and table 3 since they show the same variable (Cronbach’s Alpha)

·       Line 559 “7.2. Uniqueness of the Study” should be presented after the literature review in the context of previous studies

·       The main issue in the current format is that there is a problem of alignment among the hypotheses, research questions, results and discussion.  There is a need to work on such alignment.

·       I am not sure about the need for the Definitions section at the end of the paper.

 

Author Response

Comments 1:
The title needs revision. It does not align with the aim of the study. Since the study primarily measures students' perceptions of the AI course design, learning abilities, experiences, outcomes, and satisfaction—all in the context of constructivism-based blog assignments—this is not reflected in the title.

Response 1:
Thank you so much for your suggestion. Actually, our focus is on the use of blogs in AI course design to enhance the learning experience. The measures of students' perceptions of the AI course design, learning abilities, experiences, outcomes, and satisfaction are part of the methodology we use to verify and validate the effectiveness of incorporating blogs into the course framework. Therefore, we believe that the current title is suitable for the context of our study.

Comments 2:
The abstract needs revision as it does not explicitly state that the study focuses on students' perceptions, which is a key aspect of the research. The abstract should mention the data collection tools, such as qualitative and quantitative tools (e.g., surveys, interviews). Additionally, the abstract should provide the main recommendations.

Response 2:
Thank you for your suggestions. We have incorporated revisions into the abstract to better reflect the measurement of students' perceptions. The revised abstract is as follows:

This study, grounded in constructivist theory, presents an innovative artificial intelligence (AI) course framework for undergraduate students from the School of Artificial Intelligence at Anhui University. The research focuses on students' perceptions and explores the impact of blogs as a platform for assignment submission in an AI course. Data were collected using structured questionnaires and analyzed quantitatively using the partial least squares structural equation model. Additionally, interviews were conducted to provide nuanced insights and contextual explanations, supplementing the quantitative findings. The study explores the specific impacts of blogs on students’ learning abilities, learning experiences, academic outcomes, and overall satisfaction within the AI course. By leveraging blogs as a pedagogical tool, this study highlights their potential to transform traditional teaching methods, promoting active learning and knowledge sharing in higher education. The proposed curriculum framework also offers a scalable model that can be adapted for other science and engineering disciplines in colleges and universities.

Comments 3:

1. The text in line 117 requires a language revision to use lowercase for consistency. Suggested revision: "Autonomous learning and collaborative exploration. Constructivism emphasizes combining..."

2. Line 193 requires revision to expand the paragraph into three or more sentences for better clarity and depth.

3. In Table 3, there is a need to add the number of items in each dimension.

4. I suggest combining Table 1 and Table 3 since they show the same variable (Cronbach’s Alpha).

5. Line 559, “7.2. Uniqueness of the Study,” should be presented after the literature review in the context of previous studies.

Response 3:
We have updated the manuscript accordingly based on your suggestions.

Comments 4:
The main issue in the current format is that there is a problem of alignment among the hypotheses, research questions, results, and discussion. There is a need to work on such alignment.

Response 4:
Thank you so much for your helpful suggestions. We noticed that the fourth research question is not well aligned with Hypothesis 4 and Results 4. We have revised the research question to: What is the impact of using blogs on students' learning outcomes in an AI course? A summary of the research questions, hypotheses, and results is tabulated below:

Research questions	Hypotheses	Results
How do blogs influence students' learning abilities and experiences in an AI course?	LA: The AI course design based on a blog platform enhances students' learning abilities, including 1)faster mastery of cutting-edge technologies and knowledge, 2)improvement in autonomous learning capabilities,and 3)enhancement of programming skills.	supported as valid
What impact do blogs have on students' learning outcomes in an AI course?	LE: The AI course design based on a blog platform provides students with a positive learning experience, including, including 1) increased interest in the course, 2) better understanding of the material, and 3) a sense of achievement.	supported as valid
How satisfied are students with using blogs as a platform for assignment submission?	LS: The AI course design based on a blog platform leads to high student satisfaction, including 1) Satisfaction with course resources, 2) Satisfaction with course programming source code, 3) Satisfaction with course assignments, 4) Satisfaction with course outcomes, and 5) Satisfaction with the course difficulty.	supported as valid
What is the impact of using blogs on students' learning outcomes in an AI course?	LO: The AI course design based on a blog platform positively impacts learning outcomes, including 1) Students' self-reported effectiveness of the course, 2) Performance in theoretical course assessments, and 3) Performance in practical course assessments.	H4 is supported as a valid ypothesis due to the mediating factors

Comments 5: I am not sure about the need for the Definitions section at the end of the paper.

Response 5: We added this section per the requirements of other reviewers. We keep it as there is no space limit.

 

Reviewer 3 Report (New Reviewer)

Comments and Suggestions for Authors

The article discusses the integration of blogs into an AI course at Anhui University and examines their impact on student learning. The authors draw on constructivist approaches and argue that blogs can promote self-directed learning and practical skills. The study provides valuable insights into innovative teaching methods in the field of AI and shows great potential to improve teaching in technically demanding courses. Particularly noteworthy is the methodological approach based on the combination of technology and constructivist pedagogy.

 

content design of the article

While the article describes interesting approaches, it lacks a clear focus on the AI course and its specific content. The chosen approach could in principle be applied in any course, as the authors do not elaborate on specific characteristics of the AI course. It is necessary to describe the course in more detail, including the content and specific examples of how blogs were integrated into the learning process. This would help to better illustrate the unique connection between course content and the use of blogs.

 

study design:

Although a mixed-method approach is announced in the abstract, the article remains limited to the quantitative analysis of questionnaire data. The interviews that were supposed to be part of the design were not reported. It is important to integrate this qualitative data into the article in order to provide a complete picture and to substantiate the statements made.

 

comparison with groups that do not work with blogs:

The authors assume that the positive effects are due to the use of blogs without considering alternative explanations (e.g. the AI course itself). A comparison group without the use of blogs would be necessary to ensure that the results are indeed due to the blogs.

 

Use of the term "learning ability":

The discussion of "learning ability" is based solely on student self-assessments, which limits its validity. It would be helpful to make it clearer that the assessment of such abilities should go beyond mere self-assessments and to mention possible more objective methods of measurement.

 

examples of blog entries:

The article remains theoretical and does not provide concrete examples of student blog entries. These should be included and discussed by the authors to better illustrate the role of blogs in the learning process.

 

Discussion and limitations:

The discussion is brief and does not take sufficient account of the limitations of the study. There is a lack of comparison with the existing literature, especially with similar studies in the field of learning with blogs or AI education. A more detailed discussion would improve the scientific depth of the article.

 

literature used:

The article refers mostly to older literature and contains only a few recent studies on AI in education. Given the rapid development in this area, more up-to-date sources should be used to strengthen the relevance of the argument. In addition, more international literature should be used. 

 

 

Conclusion

The article offers interesting approaches, but has significant gaps in its conception, presentation and discussion. The proposed changes aim to sharpen the focus, better substantiate the findings and increase the scientific depth. A major revision is necessary to raise the quality of the article to the required level.

Author Response

Comments 1: Content Design of the Article
While the article describes interesting approaches, it lacks a clear focus on the AI course and its specific content. The chosen approach could, in principle, be applied to any course, as the authors do not elaborate on the specific characteristics of the AI course. It is necessary to describe the course in more detail, including its content and specific examples of how blogs were integrated into the learning process. This would help to better illustrate the unique connection between the course content and the use of blogs.

Response 1:
We have added relevant discussions in Sections 4.1 and 6.2, "Uniqueness of the Study."
For example, within the course, students delve into algorithms for tasks such as sentiment analysis. During the sentiment analysis module, students were tasked with crafting blog posts that synthesized the various algorithms they had studied. In these posts, they compared the algorithms' performance in terms of accuracy and computational efficiency. Additionally, they shared real-world examples of sentiment analysis applications, such as their use in social media monitoring or customer feedback evaluation. Another instance occurred when students explored neural network-based language generation models. They utilized blogs to document their experiments with different model architectures, discussing challenges like overfitting and the solutions they attempted.

Comments 2: Study Design
Although a mixed-method approach is announced in the abstract, the article remains limited to the quantitative analysis of questionnaire data. The interviews that were supposed to be part of the design were not reported. It is important to integrate this qualitative data into the article to provide a complete picture and substantiate the statements made.

Response 2:
We appreciate the feedback regarding the study design and the integration of qualitative data. In response to the concern about the mixed-method approach, we would like to clarify that our study primarily relies on quantitative data collected through questionnaires, with qualitative insights gathered from open-ended questions embedded within the questionnaire. These open-ended questions were designed to complement the quantitative data and provide additional context to the findings. While we initially considered a mixed-method approach involving separate interviews, we ultimately focused on the questionnaire as the main data collection tool, with the qualitative responses serving a supplementary role.

To address this, we have revised the methodology section to clearly state that the study is primarily quantitative, with qualitative data derived from open-ended questions in the questionnaire. This adjustment ensures transparency about our approach and avoids any confusion regarding the use of a mixed-method design.

In Section 4.3, we added the following content:
"At the end of the survey, we invited students to respond to the open-ended question as a text-based interview: 'Do you have any feedback on the course?' A total of 41 students responded. The comments collected focused on students' feedback on learning experiences, feelings, and interaction patterns on the blog platform."

By incorporating these open-ended questions, we aimed to capture qualitative insights that would enrich the quantitative findings and provide a more comprehensive understanding of the course's impact on students. We believe this approach strikes a balance between the depth of qualitative data and the breadth of quantitative analysis, ensuring a robust and nuanced exploration of the research questions.

We hope this clarification addresses the concerns raised and demonstrates our commitment to a rigorous and transparent research methodology. Thank you for your valuable feedback.

Comments 3: Comparison with Groups That Do Not Use Blogs
The authors assume that the positive effects are due to the use of blogs without considering alternative explanations (e.g., the AI course itself). A comparison group without the use of blogs would be necessary to ensure that the results are indeed due to the blogs.

Response 3:
Thank you for your comments. As a single-case study, our research is exploratory in nature and focuses on an in-depth analysis of the use of blogs in this AI course. Single-case studies are particularly useful for generating hypotheses, understanding unique phenomena, and providing rich, contextual insights into a particular situation.

As this study employs a single-case study methodology, we acknowledge the limitations of this approach. The findings from a single case study may have limited generalizability and applicability, particularly in different academic contexts and course structures. Therefore, we plan to expand the scope of future research by incorporating more cases for comparison to validate and broaden the conclusions of the current study.

Reviewer 4 Report (New Reviewer)

Comments and Suggestions for Authors

My rating is not really consistent with the opinion that I am going to explain. The interest, the approach of this research are original. Using Blogs as a teaching tool, as was noted in the literature study, has already been done. Whether on mammal breeding or on Artificial Intelligence, should the interest be the same or not? We cannot know, because the survey focuses on the students' opinions, with ultimately quite few crossovers. If the attempts to use structural equations to prioritize influences and interests, this remains very declarative. The big absentee from this work is the study of Blogs to detect their interest and relevance with regard to the objectives. The questionnaire survey can come to re-examine the experience from another point of view, but it seems to me that the work on the corpus must be the basis of the work. I would add that it is now possible to use artificial intelligence instruments to try to detect indicators, for example on learning, and even on satisfaction, on the momentum that the blog offers, or any other indicators to be determined from a constructivist perspective.

Author Response

Comments 1: Using Blogs as a teaching tool, as was noted in the literature study, has already been done. Whether on mammal breeding or on Artificial Intelligence, should the interest be the same or not? We cannot know, because the survey focuses on the students' opinions, with ultimately quite few crossovers. If the attempts to use structural equations to prioritize influences and interests, this remains very declarative. The big absentee from this work is the study of Blogs to detect their interest and relevance with regard to the objectives. The questionnaire survey can come to re-examine the experience from another point of view, but it seems to me that the work on the corpus must be the basis of the work. I would add that it is now possible to use artificial intelligence instruments to try to detect indicators, for example on learning, and even on satisfaction, on the momentum that the blog offers, or any other indicators to be determined from a constructivist perspective.

Response: 

Interest in Blogs:
We agree that the interest in using blogs as a teaching tool may vary depending on the subject matter. While the literature suggests that blogs have been used successfully in various contexts (e.g., English courses), the level of student engagement and interest may indeed differ based on the topic. This is an area that could benefit from further exploration, perhaps through comparative studies across disciplines. We have added this point to the discussion in Section 6.2.

Study of Blogs as a Corpus:
We agree with the importance of analyzing blog content to assess its relevance and alignment with learning objectives. A textual or content analysis of the blogs could reveal valuable insights into their educational value, engagement strategies, and potential for fostering constructivist learning. This could serve as a strong foundation for further research.

In the current study, we would like to clarify that we have evaluated the content of each blog post as part of the assessment process. Specifically, students were required to complete hands-on NLP tasks and document their implementation process, results, and reflections in their blogs. These blogs were then scored by instructors based on criteria such as the completeness of the documentation, the effectiveness of the task implementation, and the application of relevant knowledge. This scoring process allows us to validate our hypotheses about the effectiveness of blogs as a teaching tool.

While we have not yet used AI tools in this study for blog content evaluation, we have discussed the potential of AI as a next step in our research. For instance, AI could be employed to automate the analysis of blog content, providing additional insights into student learning patterns, engagement levels, and the overall effectiveness of the blogging activity. This could include detecting indicators such as the depth of technical understanding, the clarity of explanations, or even the emotional tone of student reflections. We plan to investigate and incorporate AI tools in future studies.

We have added the following discussion in Section 7.3:

A textual or content analysis of the blogs could yield valuable insights into their educational value, engagement strategies, and potential to foster constructivist learning. However, it is important to note that such an analysis has not yet been conducted, representing a limitation of the current study. In future research, we plan to address this gap by leveraging AI tools to evaluate blog content. For instance, AI could be utilized to automate the analysis of blog posts, uncovering deeper insights into student learning patterns, engagement levels, and the overall effectiveness of the blogging activity. This could involve identifying indicators such as the depth of technical understanding, the clarity of explanations, or even the emotional tone of student reflections. By incorporating AI tools in future studies, we aim to enhance the rigor and depth of our analysis.

 

Round 2

Reviewer 3 Report (New Reviewer)

Comments and Suggestions for Authors

Thanks to the authors for adding and correcting the suggested points. 

This manuscript is a resubmission of an earlier submission. The following is a list of the peer review reports and author responses from that submission.

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

1. Adding more up-to-date studies on how blogs are used in STEM education would be great. Expanding on constructivist theory and explaining how it applies to your course would also help strengthen the background.

2. Some readers might not be familiar with terms like "constructivism" or "blog assignments." It could be helpful to break these down in simpler terms so everyone can follow along.

3. Adding more detail about the practical side of using blogs in AI education would be useful. For example, how are the blog assignments evaluated, and what blogging platforms would you recommend?

4. Some statistics might seem technical to some readers. Simplifying and explaining those terms more straightforwardly would make the data easier to grasp.

5. Since students post content online, discussing how you handle data privacy and security to protect their information might be worth discussing.

6. It could be useful to expand the section on limitations. You could touch on how your findings could apply to other courses or schools and any potential challenges others might face in using blogs.

Reviewer 2 Report

Comments and Suggestions for Authors

Summary

The article underscores the imperative for the development of novel course curricula in the field artificial intelligence. It is argued that students in Chinese universities lack practical skills and face challenges in self-regulated learning and self-management skills. Therefore, the authors suggest the use of blogs as a learning tool for students to increase knowledge sharing and try to explore with their study if the use of blogs has a positive impact on student learning. With their results, the authors try to draw conclusions for the design of AI courses and teaching practice. The authors used a mixed methods design within a single case study to explore a new teaching approach for an AI course to answer this research question. The article is therefore within the scope of the journal and of potential interest to readers. The strengths of the article lie in the potentially large empirical data set for qualitative analysis and the single case study design, which could provide valuable insights into design aspects of course curricula.

 

General concept comments

GC1.      While I think the topic is highly relevant and the authors made some good points in the introduction (e.g., dynamic and fast technological development). I think the motivation for research and the importance of research could be strengthened. For example, what are the unique challenges of teaching artificial intelligence? How is it different from other technology education? Examples could also help readers outside the field to better understand the practical relevance. You could also use this ex-ante setting to explain later what your approach changed. Especially since it later appears that the research was conducted for an NLP course, I wonder if the results would also apply to other AI courses, or if there might be other unique differences. Second, I would recommend including the current lack of knowledge about the teaching approach. Since it is later stated in the paper that student-centered course design and other included teaching strategies has improved the quality of student learning, I would be interested in reading about the current challenges of student-centered course design and especially the approach of using blogs for knowledge sharing to address these challenges.

GC2.      When I looked at the literature on how to use blogs, I realized that most of it was older than ten years. I could only find one reference from 2019. This would make me wonder if the topic has been neglected for some reason and now gets a new aspect that would justify researching it, or if maybe relevant literature has been overlooked. This may be an opportunity to enhance the motivation of your research by demonstrating how you can offer a novel contribution to this subject matter.

GC3.      While the article employs a mixed-methods approach, the specifics of the qualitative methodology are lacking sufficient detail. For example, in line 44 it is stated that survey and interviews were conducted. In line 209, the authors indicate that they have received 146 responses from the 245 students enrolled in the course. However, I could not find any indication of how many interviews were conducted or whether the student text comments were taken from the survey responses. In this case, you still have qualitative data, but this is a different data collection than conducting interviews, and should be reported accordingly. If interviews were conducted, include the number of interviews, length, setting, and interview technique used.

GC4.      Similar to the qualitative data collection, it also remains unclear how the qualitative data was analyzed. A qualitative approach can use various methods such as qualitative content analysis, theme analysis, template analysis, and others. 

GC5.      Line 33 mentions that the study was conducted as a case study. Focusing more on the case study aspects of the methodology could be an excellent way to show the limitations and unique strengths of the research design, and thus giving more validity to the research findings. I would assume that this is a single case study design. In a single case study, it is important to describe the uniqueness of the case as best as possible, and a deep understanding of the uniqueness of the case could be gained through the research method [1], [2], [3], maybe you could elaborate more on this aspect. You might also want to note if the design of the AI course differs from the design of other technology courses or other subjects.

GC6.      In response to GC3-GC5, the limitations sections could be improved by stating the limitations of the research design and not just the limitations on how the results can be further used or interpreted.

 

Specific comments

SC1.       In line 1 and 33 it is state that an innovation AI course framework is presented. While the term innovation is often used to describe something novel it has a slightly different meaning in the academic discussion and especially innovation literature e.g., [4]. I would recommend changing it to "novel" or something similar, and also explicitly emphasizing the novel aspect. This will also help you better understand the limitations and contributions of your research.

SC2.       In line 35 you introduce the main research question "Can blog assignments be beneficial to AI course learning?". Starting at line 43, you specify these questions with four subsequent questions. Both are referred to as "questions". It may be more straightforward to distinguish between these two categories as research questions and research objectives, or a similar delineation. 

SC3.       The title "Study Design" for section two is somewhat misleading, as I would expect the methodology to be discussed in a section with this headline. Perhaps "Theoretical Background" or a similar designation would be more appropriate to indicate that this section describes the theoretical concepts employed.

SC4.       In line 130, "BLOG" is capitalized, but it is not clear why or if it refers to a specific "blog community".

SC5.       The text contains a number of spelling errors. Please ensure that you review and edit it thoroughly to correct these mistakes. (e.g., caption of figure 2: "Designn"; missing space before the reference in line 316 and 317).

SC6.       The abbreviation "AI" has been introduced, but the full version is occasionally used in the text. For example, see lines 37, 55, and 57. Please check the other abbreviations as well. Also, line 208 uses the full name "School of Artificial Intelligence, Anhui University", but an abbreviation has been introduced in line 33.

 

I hope my comments are helpful to the authors and wish them all the best in their future research.

 

References

[1]  K. M. Eisenhardt, “Building Theories from Case Study Research,” The Academy of Management Review, vol. 14, no. 4, pp. 532–550, Oct. 1989.

[2]  K. M. Eisenhardt and M. E. Graebner, “Theory Building From Cases: Opportunities And Challenges,” AMJ, vol. 50, no. 1, pp. 25–32, Feb. 2007, doi: 10.5465/amj.2007.24160888.

[3]  R. K. Yin, Case Study Research and Applications: Design and Methods, Sixth Edit. Thousand Oaks, California: SAGE Publications, Inc, 2018.

[4]  T. Kastelle and J. Steen, “Ideas are not innovations,” Prometheus, vol. 29, no. 2, Jun. 2011, doi: 10.1080/08109028.2011.608554.

Reviewer 3 Report

Comments and Suggestions for Authors

 

In the introduction of the paper the authors discuss the Natural Language Processing (NLP) Course at Anhui School of Artificial Intelligence and formulate the aim of the paper from a series of research questions how Can blog assignments be beneficial for learning in AI courses; How do blogs impact students' learning skills and learning experiences in an AI course; What influence do blogs have on learning outcomes in an AI course How satisfied are students with the use of blogs as a platform for assignment delivery; What is the impact of blogs on learning outcomes in an AI course; How satisfied are students with the use of blogs as a platform for assignment delivery? Or What mechanisms underlie the impact of blogs on student learning in science and engineering (lines 46-52).

After the introduction, they pose a section called “research design” where, on the one hand, they describe the NLP course, on the other side talking about blogging as a motivational tool for student learning outcomes (line 68) and, on the other hand, they mention the constructivist curriculum, as a working tool that applies to the NLP course described in the text. After this section, the methodology of the work, the analysis and discussion of the results, and, finally, the conclusions are presented.

The main limitations of the work are identified from its structure, which is very confusing and could be improved by replacing, for example, the “study design” section with a section called a literature review, where the authors present previous studies and research on the concepts of the constructivist curriculum, the description of the NLP course and the blog. Although they provide a fairly exhaustive basis for these sections, their inclusion in the study design creates some confusion when it comes to understanding the theoretical basis of the work. In addition, it would be convenient to include the research questions after the literature review, allowing the reader to understand much better the elements that the authors investigate from the analysis of the work.

The questionnaire is mentioned in the methodological part of the manuscript, although neither the structure nor the type of questions that have been carried out are raised. It is recommended, in this section, that some examples of questions be provided to establish, for example, categories of analysis to understand better the type of sample used in the study. Only the number of students is mentioned (lines 160-163) but we do not know the percentage of women, men, or the average age of the students, among other data that would be interesting to consider for the study. A table could even be designed with this information about the sample.

Only the number of responses obtained (59.6%) and that a Likert scale was used are mentioned, but no sample questions are included.

Although the data analysis and the results help to understand the reliability of the study in statistical terms, in the section on discussion of the results only fragments of the students' interviews are included, not taking up any concept from either the theoretical framework or the design of the work. There is also no mention of any author and/or previous study in the conceptual part. There is talk of improvements thanks to the blog for the development of competencies such as autonomy or reflection thanks to the use of elements analyzed from the statistical point of view in the survey such as repeated self-assessments, continuous access learning files, and multi-layered feedback mechanisms have allowed (line 392). However, none of the research questions raised in the introduction are taken up again, nor are the hypotheses of the paper mentioned in a structured way in the conclusions. Although the limitations and contributions of the study are clear, the article lacks a clear structure in terms of theoretical framework or literature review, method, results, discussion and conclusions connected to each other and the research questions and hypotheses of the work.