The Detachment of Function and the Return to Essence: Exploring the Public’s Emotional Attitudes Towards Gamified Education
Round 1
Reviewer 1 Report
Comments and Suggestions for AuthorsThis research study is extremely interesting and has great potential. However, there are some shortcomings that need to be addressed.
First, there are several grammar and syntax errors in the text that require correction—for instance, in lines 33–35 and line 289, among others.
Second, although the references used are recent, there seems to be some confusion regarding certain aspects of the literature. Gamification and game-based learning are often used interchangeably, even though they are not the same. Additionally, while gamification is applied in various fields, its meaning in education is more specific, as originally defined by Deterding et al. (2011). Gamification in education encompasses more than just game elements; it also includes integrated learning strategies. This confusion persists later when the researcher mentions that “students can adapt their learning according to their personal learning style”—referring to adaptive gamification, which differs significantly from general gamification.
Furthermore, gamification is not exactly a “newly introduced method,” as stated in the study, given that it has been discussed for over a decade and has been extensively reviewed in the literature. However, this is not the case for adaptive gamification, which is a more recent methodology. These observations apply not only to the literature review but also to the discussion and conclusion sections.
Regarding the methodology, two minor issues need clarification:
1. While Duolingo is primarily a game-based learning platform for language learning, Kahoot is not specifically focused on this. Therefore, it should be clarified where the responses regarding language learning development were sourced. Were they only from comments under the Duolingo app, or also from Kahoot? If both, how were the Kahoot comments selected?
2. Additionally, how were the comments retrieved from the Google Play Store and Apple App Store? Was permission obtained, or were they accessed and used in accordance with the terms of service? If the latter, this should be explicitly stated.
Finally, regarding game-based learning, gamification in education (including its history), and adaptive gamification, I recommend the two references below. Both studies provide helpful literature reviews that could clarify these concepts and improve your understanding of them.
Deterding, S., Dixon, D., Khaled, R., & Nacke, L. (2011, September). From game design elements to gamefulness: defining" gamification". In Proceedings of the 15th international academic MindTrek conference: Envisioning future media environments (pp. 9-15).
Kalogiannakis, M., Papadakis, S., & Zourmpakis, A. I. (2021). Gamification in science education. A systematic review of the literature. Education sciences, 11(1), 22.
Zourmpakis, A. I., Kalogiannakis, M., & Papadakis, S. (2023). A review of the literature for designing and developing a framework for adaptive gamification in physics education. The international handbook of physics education research: Teaching physics, 5-1. https://doi.org/10.1063/9780735425712_005
Comments on the Quality of English LanguageI mentioned some examples in the above text.
Author Response
Comments 1:This research study is extremely interesting and has great potential. However, there are some shortcomings that need to be addressed.
First, there are several grammar and syntax errors in the text that require correction—for instance, in lines 33–35 and line 289, among others.
Response 1:Thank you for your detailed suggestions. We have made revisions to the grammar and syntax throughout the entire text. We hope this revision meets your approval.
Comments 2:Second, although the references used are recent, there seems to be some confusion regarding certain aspects of the literature. Gamification and game-based learning are often used interchangeably, even though they are not the same. Additionally, while gamification is applied in various fields, its meaning in education is more specific, as originally defined by Deterding et al. (2011). Gamification in education encompasses more than just game elements; it also includes integrated learning strategies. This confusion persists later when the researcher mentions that “students can adapt their learning according to their personal learning style”—referring to adaptive gamification, which differs significantly from general gamification.
Response 2:Thank you for your valuable feedback. We have carefully reviewed the literature you recommended, and it has been very insightful and helpful for our article. Based on these references, we have made substantial revisions to the relevant sections. The revised first paragraph introduces the concept of gamification, which then leads into the second paragraph discussing the development of gamified education. The third and fourth paragraphs focus on the return and divergence of educational functions within gamified learning. During the revision process, we paid particular attention to the distinction you mentioned between gamification and game-based learning. We hope this revision meets your approval.
Comments 3:Furthermore, gamification is not exactly a “newly introduced method,” as stated in the study, given that it has been discussed for over a decade and has been extensively reviewed in the literature. However, this is not the case for adaptive gamification, which is a more recent methodology. These observations apply not only to the literature review but also to the discussion and conclusion sections.
Response 3:Thank you for your valuable suggestions. Regarding the expression "the newly introduced method", we have made modifications and adopted more rigorous wording. Regarding adaptive gamification, we introduced in the citation section that it is mainly reflected in the fourth paragraph. In the discussion and conclusion section, we explored adaptive learning under spatio-temporal elasticity and suggested introducing an adaptive learning system in the conclusion to enhance the flexibility of gamified education. We hope this revision can be approved by you. Thank you again for your guidance!
Comments 4:While Duolingo is primarily a game-based learning platform for language learning, Kahoot is not specifically focused on this. Therefore, it should be clarified where the responses regarding language learning development were sourced. Were they only from comments under the Duolingo app, or also from Kahoot? If both, how were the Kahoot comments selected?
Response 4:Thank you for your question. Based on your suggestions, we have made improvements. We chose Kahoot and Duolingo because they are both currently popular gamified educational software. Duolingo mainly improves language ability by completing language learning tasks through a gamified task-driven mechanism, while Kahoot focuses on interactive questions and answers and classroom quizzes. Emphasize immediate feedback and a sense of collective participation in the learning process. There are certain commonalities in gamification strategies. They all enhance users' learning motivation and participation by increasing the fun and interactivity of learning through gamification.Therefore, the comments on Kahoot and Duolingo are all based on checking whether the comments mention the functional features, user experience, and aspects such as functional features, learning experience, interface design, learning effects, and improvement suggestions.
Comments 5:Additionally, how were the comments retrieved from the Google Play Store and Apple App Store? Was permission obtained, or were they accessed and used in accordance with the terms of service? If the latter, this should be explicitly stated.
Response 5:Thank you for your comment. The comment data of Google Play Store and Apple App Store mainly come from the third-party tool Appbot. Appbot uses the publicly available apis of these platforms to access and collect comment data in accordance with the terms of service, ensuring compliance with the terms of use and privacy policies of the relevant platforms.
Comments 6:Finally, regarding game-based learning, gamification in education (including its history), and adaptive gamification, I recommend the two references below. Both studies provide helpful literature reviews that could clarify these concepts and improve your understanding of them.
Response 6:Thank you for your literature recommendations, which have greatly helped us revise and improve our article. Especially "Gamification in Science Education: A Systematic Review of the Literature" provided us with new ideas and inspiration, helping us better refine the research framework. We deeply appreciate these references for clarifying the concepts of gamification and adaptive gamification, as well as understanding their applications in education. Thank you again for your guidance and support!
Reviewer 2 Report
Comments and Suggestions for AuthorsReview Report
Title and Abstract
The title effectively captures the study's focus on public emotional attitudes toward gamified education, though it could be slightly more concise. The abstract provides a good summary but could better emphasize the study’s novelty—particularly its exploration of "functional detachment" and "return to essence." The keywords are well-selected and relevant.
Introduction
The introduction successfully contextualizes gamified education and its increasing relevance. The literature review is thorough, though incorporating more recent studies (post-2023) would strengthen its timeliness. The research gap is clearly identified, but the framing of "functional detachment" and "return to essence" could be introduced earlier to better guide the reader.
Research Design
The choice of VADER for sentiment analysis is appropriate, but the justification for the sentiment thresholds (0.4, 0.6) is lacking—clarifying this would enhance methodological transparency. The LDA topic modeling is well-explained, though the rationale for selecting three topics could be expanded. The data sources (Google Play, App Store) are valid, but potential biases (e.g., platform-specific user demographics) should be acknowledged.
Methodology
The data collection process is well-documented, but the exclusion criteria for reviews (30,007 → 24,655) could be clarified further. Preprocessing steps (stop-word removal, deduplication) are standard, but handling non-English reviews should be addressed. The sentiment analysis execution is technically sound, but the inclusion of code snippets (Figures 2–3) may be overly detailed for a general audience—consider summarizing key steps instead.
Results
The sentiment analysis reveals a strong positive bias (69.7%), which aligns with expectations for gamified apps. However, the temporal fluctuations in sentiment (e.g., spikes in negativity) are noted without deep analysis—external factors like app updates or policy changes could be explored. The topic modeling identifies three coherent themes, though some overlap exists (e.g., "fun" in Topics 2 and 3). The high negativity in Topic 2 (52%) contrasts with overall positive sentiment, possibly reflecting frustration with language-learning challenges—this warrants further discussion. The visualizations (word clouds, sentiment charts) are effective but would benefit from captions highlighting key insights.
Discussion
The discussion effectively highlights the diversity of emotional responses, particularly the contrast between simple positive expressions and nuanced negative ones. However, the link to learning outcomes could be strengthened. The critique of functional detachment (e.g., distraction, shallow networks) is compelling but relies somewhat on anecdotal evidence—empirical support would bolster this argument. The return to essence argument, grounded in connectionism, is well-articulated but could better contrast with the identified challenges (e.g., balancing flexibility and rigor).
Conclusions and Recommendations
The conclusions offer practical recommendations, such as balancing entertainment with deep learning and leveraging AI for personalized support. However, the limitations section underplays potential biases (e.g., platform-specific user differences). The suggestions for future work (e.g., facial recognition for emotion analysis) are innovative but raise ethical concerns that should be addressed.
References
The reference list is comprehensive but includes some outdated sources (pre-2020). Incorporating recent meta-analyses (2023–2024) on gamification would enhance the literature review’s relevance.
Overall Assessment
The study is rigorous and well-structured, offering valuable findings for educators and designers. Key strengths include the robust methodology and clear presentation of findings. However, the discussion could be deepened, methodological choices better justified, and ethical considerations addressed. Recommendation: Accept with minor revisions (clarify methods, expand discussion, update references).
Author Response
Comments 1:The title effectively captures the study's focus on public emotional attitudes toward gamified education, though it could be slightly more concise. The abstract provides a good summary but could better emphasize the study’s novelty—particularly its exploration of "functional detachment" and "return to essence." The keywords are well-selected and relevant.
Response 1:Thank you very much for your valuable comments. In order to improve the quality of the article, we have further modified the abstract according to your suggestions. I hope the revised version will satisfy you.
Comments 2:The introduction successfully contextualizes gamified education and its increasing relevance. The literature review is thorough, though incorporating more recent studies (post-2023) would strengthen its timeliness. The research gap is clearly identified, but the framing of "functional detachment" and "return to essence" could be introduced earlier to better guide the reader.
Response 2:Thank you for your valuable suggestions. We have updated the literature, mainly referring to studies conducted after 2023, to enhance the timeliness of the literature review. In the introduction part, we have introduced the two frameworks of "functional separation" and "returning to the essence" in the third and fourth paragraphs to help better guide readers to understand the background and direction of the research. These adjustments are aimed at enhancing the depth and relevance of the research. Thank you again for your suggestions.
Comments 3:The choice of VADER for sentiment analysis is appropriate, but the justification for the sentiment thresholds (0.4, 0.6) is lacking—clarifying this would enhance methodological transparency. The LDA topic modeling is well-explained, though the rationale for selecting three topics could be expanded. The data sources (Google Play, App Store) are valid, but potential biases (e.g., platform-specific user demographics) should be acknowledged.
Response 3:
Thank you for your valuable suggestions. Based on your feedback, we have provided further clarification. The emotional thresholds (0.4, 0.6) represent the emotional transition zone, which corresponds to emotions that are either unclear or weak, categorized as neutral emotions. Since VADER does not explicitly define thresholds for emotional classification, text-based sentiment analysis applications should be universal and ensure consistency in the scoring system.This is mainly reflected in lines 111 to 120 of the article. The three themes are primarily conclusions drawn from LDA, based on keywords and summaries of the comments. These are explained in the Potential Theme Analysis section of the article. Regarding the data sources (Google Play, App Store), we also acknowledge in lines 147 to 157 of the article that there may be biases, such as differences in user experience caused by device types, platform preferences, and variations in user needs.
Comments 4:The data collection process is well-documented, but the exclusion criteria for reviews (30,007 → 24,655) could be clarified further. Preprocessing steps (stop-word removal, deduplication) are standard, but handling non-English reviews should be addressed. The sentiment analysis execution is technically sound, but the inclusion of code snippets (Figures 2–3) may be overly detailed for a general audience—consider summarizing key steps instead.
Response 4:
Thank you for your valuable suggestions. The exclusion criteria for the comment data are further explained in lines 179 to 188 of the article, mainly adding the screening process. The screening process mainly includes removing advertising content, insulting language and non-English text, and explains how to remove non-English text. The execution of sentiment analysis is technically summarized in lines 202 to 219 of the article. The key steps are summarized and the code snipards are streamlined.
Comments 5:The sentiment analysis reveals a strong positive bias (69.7%), which aligns with expectations for gamified apps. However, the temporal fluctuations in sentiment (e.g., spikes in negativity) are noted without deep analysis—external factors like app updates or policy changes could be explored.
Response 5:Thank you for your valuable suggestions. We have noticed that the overall positive sentiment of gamified applications is relatively strong, which indicates that users have enjoyed the positive experience brought by interactivity and fun during the usage process. However, fluctuations in negative emotions may reflect certain changes in the application, such as version updates, functional adjustments, or policy shifts. We mainly explored the obtained results in the discussion section, which are mainly reflected in lines 328 to 339 of the article.
Comments 6:The topic modeling identifies three coherent themes, though some overlap exists (e.g., "fun" in Topics 2 and 3).
Response 6:Thank you for your valuable suggestions. In the process of LDA topic modeling, the possible reasons for the overlap and similarity of topic words are as follows: First, the tandem effects under different topic context logics are different; Second, the meanings of words themselves vary in different situations. For example, in Theme 2, "fun" mainly refers to the fun in the process of language learning, emphasizing the improvement of the sense of participation and interest in learning through interaction, gamification and other means.However, in Theme 3, "fun" is more inclined to express experiences in terms of entertainment and social interaction, especially in scenarios combined with interactive games and social interaction. Although the word "fun" appears in both themes, its core meaning varies depending on the theme.
Response 7:The high negativity in Topic 2 (52%) contrasts with overall positive sentiment, possibly reflecting frustration with language-learning challenges—this warrants further discussion. The visualizations (word clouds, sentiment charts) are effective but would benefit from captions highlighting key insights.
Response 7:Thank you for your valuable suggestions. We have checked and revised the article. The proportion of negative emotions in Theme 2 might stem from the challenges users encounter during the language learning process, especially difficulties in grammar, pronunciation or memory. We have further analyzed these negative comments, identified the specific points where users are frustrated, and made improvements in terms of functional design and user support.We mainly explored the obtained results in the discussion part. And we have added explanatory text of key insights to the word cloud and sentiment chart based on your suggestions.
Response 8:The discussion effectively highlights the diversity of emotional responses, particularly the contrast between simple positive expressions and nuanced negative ones. However, the link to learning outcomes could be strengthened. The critique of functional detachment (e.g., distraction, shallow networks) is compelling but relies somewhat on anecdotal evidence—empirical support would bolster this argument. The return to essence argument, grounded in connectionism, is well-articulated but could better contrast with the identified challenges (e.g., balancing flexibility and rigor).
Response 8:Thank you for your valuable suggestions. Based on your feedback, we have strengthened the relationship between emotions and learning outcomes in the discussion section and added anecdotal evidence in areas such as distraction to support the argument.Meanwhile, we clearly put forward the challenges faced by gamified education in Part 6. It is hoped that these revisions can effectively improve the quality of the thesis. Thank you again for your guidance and help.
Comments 9:The conclusions offer practical recommendations, such as balancing entertainment with deep learning and leveraging AI for personalized support. However, the limitations section underplays potential biases (e.g., platform-specific user differences). The suggestions for future work (e.g., facial recognition for emotion analysis) are innovative but raise ethical concerns that should be addressed.
Response 9:Thank you for your valuable suggestions. Based on your feedback, we have acknowledged the limitations of the research, particularly highlighting the differences among users on different platforms.When using facial recognition for emotion analysis, ethical issues and challenges have been particularly raised. We will continue to pay attention to these issues and ensure that the relevant ethical factors are fully considered in future research. It is mainly reflected in lines 604 to 621 of the article.
Comments 10:The reference list is comprehensive but includes some outdated sources (pre-2020). Incorporating recent meta-analyses (2023–2024) on gamification would enhance the literature review’s relevance.
Response 10:Thank you for your suggestion. We have made appropriate changes to the literature and hope this change can meet the requirements.
Comments 11:The study is rigorous and well-structured, offering valuable findings for educators and designers. Key strengths include the robust methodology and clear presentation of findings. However, the discussion could be deepened, methodological choices better justified, and ethical considerations addressed. Recommendation: Accept with minor revisions (clarify methods, expand discussion, update references).
Response 11:Thank you for your affirmation and detailed suggestions, which are of great help to the improvement of the article. We have made modifications based on your suggestions and hope to get your affirmation again.
Reviewer 3 Report
Comments and Suggestions for Authors- Title and Abstract
The manuscript's title is original and thought-provoking, drawing interest by adopting a quasi-philosophical perspective on educational gamification. However, the abstract suffers from serious writing issues, including poor punctuation, convoluted structure, and an overly dense presentation of ideas. Key concepts are mentioned without clear definitions. A complete rewrite is recommended, with a clearer narrative flow, well-defined objectives, and quantified summary of the main findings.
- Introduction
The introduction provides a generally solid overview of the topic, referencing relevant historical and academic contexts. Nevertheless, the writing is redundant and lacks focus. There is excessive use of in-text citations without clear justification, and key terms such as “connectionism” are introduced without prior definition. This section should be restructured to explicitly outline the problem, research justification, theoretical framework, and objectives in a logical sequence.
- Methodological Design
The study makes effective use of current computational tools like VADER and LDA, and it correctly identifies suitable platforms for obtaining authentic user data. However, the methodology section is marred by repeated content, irrelevant technical justifications (e.g., the rationale for choosing Google Play), and a lack of clarity on inclusion and exclusion criteria. It is recommended to reorganize this section using standard academic components: population, sample, instruments, and procedures.
- Results
This section includes a substantial data set and is organized in a reasonably structured manner. Although graphical tools were used to complement findings, figures are not clearly presented in the manuscript. While sentiment and topic analyses are valid, the discussion lacks analytical depth. Minor inconsistencies in reported numbers are observed. Critical interpretation should be expanded and results better summarized with clearly labeled tables.
- Discussion and Conclusions
The discussion connects the findings with theoretical models like connectionism and reflects critically on the risks of “functional alienation” in gamification. However, it reiterates ideas already addressed in previous sections and overuses abstract terminology without sufficient empirical support. This section should be reorganized to compare the study's findings with existing literature and provide a more concise and focused conclusion.
- Academic Style and Writing
The manuscript exhibits multiple language issues likely resulting from literal translation or non-native English writing. Grammatical errors, incorrect punctuation, repetitive and vacuous phrases, and inconsistent referencing are prevalent. A thorough linguistic revision by a native academic editor is strongly recommended, as well as unifying the citation style according to an established academic standard.
Comments for author File: 
Comments.pdf
Although I am not a specialist in academic English language editing, it is evident that the manuscript would benefit from a thorough linguistic revision. The text contains numerous grammatical, syntactic, and stylistic issues that affect clarity and readability. I strongly recommend that the authors seek support from a professional academic editor or a native English speaker to ensure the language meets publication standards.
Author Response
Comments 1:The manuscript's title is original and thought-provoking, drawing interest by adopting a quasi-philosophical perspective on educational gamification. However, the abstract suffers from serious writing issues, including poor punctuation, convoluted structure, and an overly dense presentation of ideas. Key concepts are mentioned without clear definitions. A complete rewrite is recommended, with a clearer narrative flow, well-defined objectives, and quantified summary of the main findings.
Response 1:Thank you very much for your suggestions. We have made substantial revisions to the abstract based on your comments, including adjustments to symbols and structure, and have provided a quantitative summary of the main findings. We hope these revisions meet your expectations.
Comments 2:The introduction provides a generally solid overview of the topic, referencing relevant historical and academic contexts. Nevertheless, the writing is redundant and lacks focus. There is excessive use of in-text citations without clear justification, and key terms such as “connectionism” are introduced without prior definition. This section should be restructured to explicitly outline the problem, research justification, theoretical framework, and objectives in a logical sequence.
Response 2:Thank you for your valuable suggestions. We have made significant revisions to the relevant parts. The revised first paragraph first introduces the concept of gamification, then leads to the second paragraph about the development of gamified education, and the third and fourth paragraphs are based on the regression and dissociation of educational functions in gamified learning. According to your suggestion, the definitions of key terms such as "connectionism" have been given. Hope this revision can be approved by you.
Comments 3:The study makes effective use of current computational tools like VADER and LDA, and it correctly identifies suitable platforms for obtaining authentic user data. However, the methodology section is marred by repeated content, irrelevant technical justifications (e.g., the rationale for choosing Google Play), and a lack of clarity on inclusion and exclusion criteria. It is recommended to reorganize this section using standard academic components: population, sample, instruments, and procedures.
Response 3:Thank you for your suggestions. Based on your suggestions, we have simplified the repetitive content in the methodology section and the reasons for choosing Google Play, which are mainly reflected in the article - line. And this part has been reorganized. Currently, it includes three parts: user groups and sample data, usage tools and program details, and some contents have been adjusted and modified. It is hoped that this revision can improve the quality of the article.
Comments 4:This section includes a substantial data set and is organized in a reasonably structured manner. Although graphical tools were used to complement findings, figures are not clearly presented in the manuscript. While sentiment and topic analyses are valid, the discussion lacks analytical depth. Minor inconsistencies in reported numbers are observed. Critical interpretation should be expanded and results better summarized with clearly labeled tables.
Response 4:
Thank you for your suggestion. Based on your feedback, we have carefully examined the article and expanded the interpretation of its content. Meanwhile, for the table part, we have also added detailed annotations. It is hoped that these revisions can further enhance the clarity and readability of the article. Thank you again for your valuable suggestions.
Comments 5:The discussion connects the findings with theoretical models like connectionism and reflects critically on the risks of “functional alienation” in gamification. However, it reiterates ideas already addressed in previous sections and overuses abstract terminology without sufficient empirical support. This section should be reorganized to compare the study's findings with existing literature and provide a more concise and focused conclusion.
Response 5:Thank you for your suggestions. Based on your feedback, we have revised the discussion section of the article to reduce the views that have been discussed in the previous part and add empirical support. We hope that these adjustments will enhance the depth and persuasiveness of the article. Thank you for your valuable guidance.
Comments 6:The manuscript exhibits multiple language issues likely resulting from literal translation or non-native English writing. Grammatical errors, incorrect punctuation, repetitive and vacuous phrases, and inconsistent referencing are prevalent. A thorough linguistic revision by a native academic editor is strongly recommended, as well as unifying the citation style according to an established academic standard.
Response 6:Thank you for your detailed review of the manuscript and your valuable feedback. We have noted language-related issues in the manuscript and your comments are greatly appreciated. We have made linguistic changes to ensure that grammar, punctuation, and citation formatting meet academic standards, and that the citation style is consistent throughout. Thank you again for your support and suggestions.
Comments 7:Although I am not a specialist in academic English language editing, it is evident that the manuscript would benefit from a thorough linguistic revision. The text contains numerous grammatical, syntactic, and stylistic issues that affect clarity and readability. I strongly recommend that the authors seek support from a professional academic editor or a native English speaker to ensure the language meets publication standards.
Response 7:Thank you for your feedback and suggestions on the manuscript. Based on your recommendations, we have made language revisions to ensure the manuscript meets publication standards. Once again, thank you for your valuable input.
Round 2
Reviewer 1 Report
Comments and Suggestions for AuthorsThe study has been significantly improved, and the authors have adequately addressed all of my comments.
