A Participatory Design Approach to Designing Educational Interventions for Science Students Using Socially Assistive Robots

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

While the paper presents an interesting study on using socially assistive robots to improve lab safety through participatory design, it does not clearly align with the aims and scope of the journal Electronics. According to the journal, it publishes work related to the science of electronics and its applications, with a focus on areas like microelectronics, power electronics, control engineering, signal processing, embedded systems, semiconductor devices, artificial intelligence circuits and systems, and similar technical fields. In contrast, this paper focuses on user experience design, educational interventions, and student surveys. It does not present any new electronic design, control algorithm, signal processing method, or technical development related to electronics. The robot platform is used without technical modifications or engineering contributions. For these reasons, this work may be better suited to journals that focus on educational technology, social robotics, or human-robot interaction rather than a technical electronics journal.

Author Response

 

Reviewer 1 Comment:

 

While the paper presents an interesting study on using socially assistive robots to improve lab safety through participatory design, it does not clearly align with the aims and scope of the journal Electronics. According to the journal, it publishes work related to the science of electronics and its applications, with a focus on areas like microelectronics, power electronics, control engineering, signal processing, embedded systems, semiconductor devices, artificial intelligence circuits and systems, and similar technical fields. In contrast, this paper focuses on user experience design, educational interventions, and student surveys. It does not present any new electronic design, control algorithm, signal processing method, or technical development related to electronics. The robot platform is used without technical modifications or engineering contributions. For these reasons, this work may be better suited to journals that focus on educational technology, social robotics, or human-robot interaction rather than a technical electronics journal.

 

Our response:

 

Thank you for your comment and pointing this out. However, our paper addresses the scope of the special issue, which is stated in the CFP as:

https://www.mdpi.com/journal/electronics/special_issues/6ZF461RCJ1:

 

The emergence of new technologies and application areas in human–robot interaction is having significant and meaningful impacts on the ways people experience and interact with the world. This Special Issue sheds light on challenges in the design and use of robots and intelligent systems in our everyday life. Furthermore, this Special Issue invites scholars to critically reflect on the future perspectives of this research field.

We encourage the following types of submissions (among others):

• Design studies or evaluative research that highlight how the features of robots and intelligent systems are intended to support people’s engagement, learning, and behaviors in everyday life.
• Critical, sociological, and/or methodological articles on the opportunities/challenges of designing/using intelligent technology in this field.
• Towards the development of empathic machines: understanding and modeling human behavior to create machines that can respond to and understand humans at an emotional level.
• Affective haptics: sensors and/or actuators designed to support human–robot interaction through touch.
• Ethnographic and cultural topics related to human–robot interaction.
• Calm-technology approach to human–robot interaction.
• In-the-wild and field studies on human–robot interaction.
• Child–robot interaction.
• Infant–robot interaction.

 

Reviewer 2 Report

Comments and Suggestions for Authors

The paper presents a well-structured and innovative study on using socially assistive robots (specifically Misty II Plus) to enhance safety in science laboratories through a participatory design approach. The research addresses a significant gap in the literature by integrating social robots into educational settings to monitor and mitigate risky behaviors. The methodology is robust, combining contextual inquiry, consultation, participatory design, and prototyping. The results demonstrate a positive impact on students' perceptions and expectations regarding robot-assisted safety interventions. The paper is well-written, with clear objectives, a comprehensive literature review, and a detailed explanation of the LSA framework. However, there are areas where clarity and depth could be improved.

1. The paper briefly mentions the limitations of social robots in monitoring all risky behaviors but does not elaborate on the specific constraints (e.g., technical challenges, environmental factors, or ethical considerations). Adding a dedicated subsection in the Discussion or Conclusion to detail these limitations would provide a more balanced view of the study's applicability and future research directions. For example, discuss potential issues like sensor accuracy in dynamic lab environments or privacy concerns related to continuous monitoring.
2. While the paper highlights the positive outcomes of using the LSA framework, it would benefit from a more explicit comparison with existing solutions (e.g., traditional supervision or digital monitoring systems). Discussing how the proposed framework outperforms or complements these methods, supported by quantitative or qualitative data, would strengthen the argument for its adoption. For instance, include metrics like accident reduction rates or user satisfaction scores compared to baseline methods.

Author Response

Author's Reply to the Reviewer 2. Report

However, there are areas where clarity and depth could be improved.

1. The paper briefly mentions the limitations of social robots in monitoring all risky behaviors but does not elaborate on the specific constraints (e.g., technical challenges, environmental factors, or ethical considerations). Adding a dedicated subsection in the Discussion or Conclusion to detail these limitations would provide a more balanced view of the study's applicability and future research directions. For example, discuss potential issues like sensor accuracy in dynamic lab environments or privacy concerns related to continuous monitoring.

Error detection in dynamic images still has inadequate generalization performance on invisible categories. Domain generalization is essential for their practical implementation, yet tasks like crop disease detection remain difficult. Additionally, techniques for creating interpretable prompts need to be improved.

Chen, H., Li, H., Zhao, J., Ruan, C., & Huang, L. (2025). Enhancing crop disease recognition via prompt learning-based progressive Mixup and Contrastive Language-Image Pre-training dynamic calibration. Engineering Applications of Artificial Intelligence, 152, 110805.

The materials employed in the construction of the existing sensors limit their ability to detect physical events like humidity as a continuous monitoring approach, which leads to insufficient sensitivity. Additionally, a lot of continuous monitoring devices use variations in signal frequency to evaluate human conditions like breathing.

Yang, H., Guo, Q., Chen, G., Zhao, Y., Shi, M., Zhou, N., ... & Mao, H. (2025). An intelligent humidity sensing system for human behavior recognition. Microsystems & Nanoengineering, 11(1), 17.

 

We still don't fully understand how students feel about the collection and usage of their data. Students often worry about how much their personal information is monitored and used by educational institutions. Educational institutions still need to establish explicit policies and permission processes that notify students of the information being collected, how it will be used, and who will have access to it. A social robot can undoubtedly provide students with all the information they need to lessen their anxiety around their data.

Karimov, A., Saarela, M., Aliyev, S., & Baker, R. (2025, January). Ethical Considerations and Student Perceptions of Engagement Data in Learning Analytics. In Proceedings of the Annual Hawaii International Conference on System Sciences. University of Hawaiʻi at Mānoa.

 

1. While the paper highlights the positive outcomes of using the LSA framework, it would benefit from a more explicit comparison with existing solutions (e.g., traditional supervision or digital monitoring systems). Discussing how the proposed framework outperforms or complements these methods, supported by quantitative or qualitative data, would strengthen the argument for its adoption. For instance, include metrics like accident reduction rates or user satisfaction scores compared to baseline methods.

Because the dynamics of both quantitative and qualitative changes in science labs are time and space dependent, some substances can be harmful to humans at very low concentrations, and individual reactions vary depending on a number of factors, including the production of toxins, the traditional supervisor inside the labs cannot fully help students avoid risks.

Kozajda, A., & Miśkiewicz, E. (2025). Role of National Register of Biological Agents in health protection of employees exposed to biological agents used intentionally at work in Poland. International Journal of Occupational Medicine and Environmental Health, 38(1), 1-7.

 

This study aims to overcome the challenge that HARISM framework that enables outdoor safety monitoring may face such as the current framework does not fully capture the complexity of real-world interactions. And there is a need to consider topics such as optimal sensor position, appropriate communication protocols for local conditions, or a flexible architecture that can be easily changed. This study also tries to enhance emergency response specifically in the complex environments like science laboratory.

 

The goal of this study is to overcome the shortage that prior frameworks may have. For instance,  HARISM framework, which facilitates outdoor safety monitoring, may encounter, such as the fact that the current framework is unable to adequately represent the intricacy of interactions that occur in the actual world. Additionally, issues like the best location for sensors, local conditions-appropriate communication protocols, or an easily-modifiable architecture must be taken into account. Additionally, this study aims to improve emergency response, particularly in complicated settings such as science labs.

 

Chen, Y., Li, J., Blasch, E., & Qu, Q. (2025). Future Outdoor Safety Monitoring: Integrating Human Activity Recognition with the Internet of Physical–Virtual Things. Applied Sciences, 15(7), 3434. https://doi.org/10.3390/app15073434

Reviewer 3 Report

Comments and Suggestions for Authors

The manuscript “A Participatory Design Approach to Design Educational Interventions for Science Students using Socially Assistive Robots” is considered for publication in Electronics. In general, the document is well-structured, but it is necessary to include a conclusion section and follow my subsequent recommendations:

 

It is pertinent for the authors to expand their student sample size, as 20 participants are insufficient to obtain statistically representative and generalizable results. Such a small sample can generate significant biases in the analysis and limit the validity of the conclusions. It is recommended that a group of at least 50 students be chosen, which would allow for greater data diversity, better estimation of population parameters, and a reduction in the margin of error. Furthermore, a larger sample size would contribute to strengthening the study's methodological soundness and increase confidence in the findings presented.

 

Adding an appendix containing the list of questions used in the study is necessary. Including only an external link, which also requires requesting access, creates unnecessary dependence on the authors as the sole providers of this information. A viable alternative would be to keep the detailed results in the private link and include an appendix with the questions in the document. This would enable other researchers to replicate the methodological proposal without compromising data confidentiality, while also ensuring greater transparency and reproducibility in the research.

 

The authors should include graphical representations illustrating the analysis performed in the results section. The inclusion of appropriate graphics, such as histograms, bar charts, scatter plots, or comparative diagrams, would significantly facilitate understanding of the data presented and allow for a more precise visualization of the trends, differences, or relationships detected.

 

It is necessary to add a conclusion summarizing and supporting the results obtained, highlighting the study's main findings and their relevance to the context under investigation. It would also be pertinent to include a section outlining the research's limitations, such as sample size, time frame, and possible methodological biases. Finally, it is recommended that future lines of work be proposed that could continue or expand the scope of this research, thus allowing for its strengthening and evolution within the field of study.

Comments on the Quality of English Language

The document presents some inconsistencies in grammar, and the authors should review carefully the entire document.

Author Response

Comments and Suggestions for Authors

The manuscript “A Participatory Design Approach to Design Educational Interventions for Science Students using Socially Assistive Robots” is considered for publication in Electronics. In general, the document is well-structured, but it is necessary to include a conclusion section and follow my subsequent recommendations:

 

It is pertinent for the authors to expand their student sample size, as 20 participants are insufficient to obtain statistically representative and generalizable results. Such a small sample can generate significant biases in the analysis and limit the validity of the conclusions. It is recommended that a group of at least 50 students be chosen, which would allow for greater data diversity, better estimation of population parameters, and a reduction in the margin of error. Furthermore, a larger sample size would contribute to strengthening the study's methodological soundness and increase confidence in the findings presented.

 

Adding an appendix containing the list of questions used in the study is necessary. Including only an external link, which also requires requesting access, creates unnecessary dependence on the authors as the sole providers of this information. A viable alternative would be to keep the detailed results in the private link and include an appendix with the questions in the document. This would enable other researchers to replicate the methodological proposal without compromising data confidentiality, while also ensuring greater transparency and reproducibility in the research.

 

The authors should include graphical representations illustrating the analysis performed in the results section. The inclusion of appropriate graphics, such as histograms, bar charts, scatter plots, or comparative diagrams, would significantly facilitate understanding of the data presented and allow for a more precise visualization of the trends, differences, or relationships detected.

 

It is necessary to add a conclusion summarizing and supporting the results obtained, highlighting the study's main findings and their relevance to the context under investigation. It would also be pertinent to include a section outlining the research's limitations, such as sample size, time frame, and possible methodological biases. Finally, it is recommended that future lines of work be proposed that could continue or expand the scope of this research, thus allowing for its strengthening and evolution within the field of study.

 

Comments on the Quality of English Language

The document presents some inconsistencies in grammar, and the authors should review carefully the entire document.

Submission Date

30 April 2025

Date of this review

17 May 2025 04:33:47

 

 

 

6. Conclusion

The current study investigated the use of socially assistive robots (Misty II Plus) to improve safety in science labs. Three significant results are highlighted by our research. First off, the LSA architecture helps the lab manager or instructor deploy social robots to keep the students safe during potentially dangerous experiments. Second, by giving precise feedback, the social assistive robots can be used to regulate users' actions. Thirdly, students' emotions can be shared by social assistive robots, which can improve safety in a research lab. Human-looking social assistive robots demonstrated greater levels of engagement.

Finally, we should discuss the present study's limitations. We think that increasing the number of participants can yield more information that will help social robots better comprehend the risky behaviors that students may engage in. Additionally, it can give more appropriate feedback based on the different levels of risky behaviors that students may exhibit. Additionally, recording videos and gathering data for longer than a few weeks may highlight the benefits that users can experience while utilizing the social robot and framework in various types of educational labs. Conducting future research for detecting more risky behaviors in different learning environments like playgrounds. Also, there is a need to explore the effectiveness of using the suggested framework for using social robot while teaching students in primary school and kindergarten.

 

 

However, increasing the number of participants to 50 students can strengthen our study's methodology and add more value to our findings. According to published papers in electronic journals, exploring frameworks in the initial stage can be investigated by less than 20 participants. In medical domain, only eight participants are the sample size for Tracking in Robotic Surgery [1]. Moreover, a study for exploring the effect of Integrating a suggested Framework for Managing Childhood Obesity Based on Biobanks was conducted by using four joint parent–child classroom workshops which mean the sample size was less than 20 participants [2]. Additionally, the authors include specific limitations regarding the sample size and time frame in the conclusion section. For example, the interventions recommended in the current study include the need for additional research in the future regarding the instruction of younger students in primary school and kindergarten.

• Narasimhan, S., Turkcan, M. K., Ballo, M., Choksi, S., Filicori, F., & Kostic, Z. (2025). Monocular 3D Tooltip Tracking in Robotic Surgery—Building a Multi-Stage Pipeline. Electronics, 14(10), 2075. https://doi.org/10.3390/electronics14102075
• Vondikakis, I., Politi, E., Goulis, D., Dimitrakopoulos, G., Georgoulis, M., Saltaouras, G., Kontogianni, M., Brisimi, T., Logothetis, M., Kakoulidis, H., Prasinos, M., Anastasiou, A., Kakkos, I., Vellidou, E., Matsopoulos, G., & Koutsouris, D. (2025). Integrated Framework for Managing Childhood Obesity Based on Biobanks, AI Tools and Methods, and Serious Games. Electronics, 14(10), 2053. https://doi.org/10.3390/electronics14102053

 

 

Appendix

 

The authors add graphical representations illustrating the analysis performed in the results section.

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

This manuscript presents a socially assistive robotic framework designed to improve laboratory safety for science students through participatory design. There are several substantial issues that must be addressed before the paper can be considered for publication. 

1-   The manuscript claims that no previous studies have used robots for lab safety, yet it does not explore or compare with alternative (non-robotic) lab safety systems, such as smart sensor-based monitoring or AI-enhanced checklists used in industrial or university labs. A proper comparison would help validate the research gap more convincingly.

2- The methodology section provides a high-level view of the design process and robot components but lacks important details required for replicability. It does not explain how Misty II detects whether a student is wearing goggles or gloves, nor how proximity, emotion, or activity tracking is performed in practice. There is no mention of the algorithms used, any image processing tools, or thresholds set for detection.

3- The evaluation involved 20 students from Egypt and Japan, but only the Japanese participants interacted directly with the robot. Egyptian students only viewed printed or digital materials. Despite this imbalance, the authors pool all participants' responses together and present results without stratification. This creates an internal validity issue, as differences in emotional response or usability perception could result from the unequal exposure. The study design does not appear to include randomization or control conditions, and there is no explanation for how the setting or interaction duration may have affected the outcomes.

4- While the study used well established tools like the System Usability Scale (SUS), the actual SUS score reported (M = 36.4) is substantially below the industry average threshold of 68. The authors nevertheless claim this shows that students found the system usable. This is a clear misinterpretation of the metric. A score in the 30s typically reflects a poor user experience and should be treated as such

5- The results section presents a general trend of improvement in students' attitudes before and after using the LSA system. While non-parametric (Wilcoxon) and parametric (t-test) analyses are applied correctly, the data is not thoroughly reported. The manuscript does not provide descriptive statistics such as means and standard deviations for key questionnaire items, nor does it identify which questions showed the greatest improvement. Furthermore, no raw score tables or response breakdowns are included. This prevents readers from assessing the true magnitude or distribution of changes.

6- The discussion restates positive findings but does not reflect on known limitations of the study or the technology used. It avoids addressing the low SUS score entirely and fails to consider challenges such as the cost of deploying such systems in labs, the need for continuous maintenance, and the accuracy of Misty's behavior recognition capabilities. The unequal exposure of participants is also not discussed, despite being a key flaw in the experimental design. The lack of critical insight in this section diminishes the depth of the manuscript.

 

 

Author Response

1-   The manuscript claims that no previous studies have used robots for lab safety, yet it does not explore or compare with alternative (non-robotic) lab safety systems, such as smart sensor-based monitoring or AI-enhanced checklists used in industrial or university labs. A proper comparison would help validate the research gap more convincingly.

However, there have been some attempts to improve safety in scientific labs. These efforts have numerous drawbacks, and the current study offers valuable solutions. Detecting Hydrogen by using sensorshas several limitations when it comes to be applied through the real- world situations [1]. According to the findings, university laboratory safety is a very interdisciplinary area of study. In contrast to other safety areas, it comes within the minority research sector. Even though a few new research areas have emerged in the past ten years, researchers may still need to contribute innovative concepts, new subjects, and novel approaches or theories in this area. Such areas of study include emergency response, human error, safety communication, risk perception, resilience, and safety science in general [2]. And that is exactly what we done in our current study by using robot. Easy-to-use software and hardware systems to assist in the rapid development and implementation of smart sensing is important in science labs. According to [3] the combined use of dynamic real-time traceability and information visualization for laboratory safety management is still required for providing security inside science labs and that is exactly what we proposed in the current study through using a moveable social robot the can detect errors in a dynamic context.

1. Buttner, W. J., Post, M. B., Burgess, R., & Rivkin, C. (2011). An overview of hydrogen safety sensors and requirements. International Journal of Hydrogen Energy, 36(3), 2462-2470.
2. Yang, Y., Reniers, G., Chen, G., & Goerlandt, F. (2019). A bibliometric review of laboratory safety in universities. Safety Science, 120, 14-24.
3. Xiao, X. (2024). Smart sensing for laboratory safety management. JOURNAL OF ARTIFICIAL INTELLIGENCE, 1(1), 11-16.

2- The methodology section provides a high-level view of the design process and robot components but lacks important details required for replicability. It does not explain how Misty II detects whether a student is wearing goggles or gloves, nor how proximity, emotion, or activity tracking is performed in practice. There is no mention of the algorithms used, any image processing tools, or thresholds set for detection.

The authors added apparatus in the method and material section and mentioned the following information: The Misty II robot, created by the Misty Robotics company. It detects and recognizes faces taken by the camera in her visor using a module built on the Snapdragon Neural Processing Engine. Misty II is a 36-cm-tall robot designed to be a social companion and enhance human-robot combination. Microphones specifications of the Misty II. Include a Sensitivity polar patter (Omnidirectional), Signal to noise ratio (SNR) (64 dB), Sensitivity (-26 dBFS), Power supply reaction (PSR) (-70 dBFS). These devices offer significant benefits for the system's overall acceptability. Robotics for active and assisted living should be easily customizable to meet the needs of the user and adapt to changing environments.

Ciuffreda, I., Amabili, G., Casaccia, S., Benadduci, M., Margaritini, A., Maranesi, E., ... & Bevilacqua, R. (2023). Design and development of a technological platform based on a sensorized social robot for supporting older adults and caregivers: GUARDIAN ecosystem. International Journal of Social Robotics, 1-20.

It can function in inadequate lighting conditions and at three distinct head tilt degrees. When Misty's RGB camera turned on by itself, an ML algorithm evaluated the captured image for human detection. If a person was successfully identified, the system recorded their location; if not, it muted itself for a while before beginning the localization process again. RGB camera specifications. SONY IMX214 Camera parameters Power supply (Analog 2.7 V; Digital: 1.0 V and 1.8 V), Operating Temperature (− 20 ◦C - +70 ◦C Module size 8.5*8.5*6.15 mm (L*W*H)), Camera mass (Lens Specifications Total pixel number 4224 (H) * 3200 (V)),  Field of view (FOV) (Horizontal 63.2◦ Vertical 49.0◦ Diagonal 75.0◦), Image sensor size (1/3 inch), Ensemble of localized features (EFL) (3.86 mm). Previous tests carried out by the authors confirm that the best algorithm for human detection using the RGB camera mounted on Misty in indoor scenario is the YOLO-v3 algorithm (99,9%) [2].

[2] Ciuffreda, I., Battista, G., Casaccia, S., & Revel, G. M. (2023). People detection measurement setup based on a DOA approach implemented on a sensorised social robot. Measurement: Sensors, 25, 100649.

 

3- The evaluation involved 20 students from Egypt and Japan, but only the Japanese participants interacted directly with the robot. Egyptian students only viewed printed or digital materials. Despite this imbalance, the authors pool all participants' responses together and present results without stratification. This creates an internal validity issue, as differences in emotional response or usability perception could result from the unequal exposure. The study design does not appear to include randomization or control conditions, and there is no explanation for how the setting or interaction duration may have affected the outcomes.

According to the Kruskal-Wallis Test, there are no-significant differences between groups in the social robots' capacity to improve safety and sharing emotional interaction between students and the social robots in science labs. Students' perceptions regarding social robot capabilities and improving safety in science laboratory are as follows:  χ2(1) = 1.007, p = 0.316, with a mean rank for group 1. (9.42), and for group 2. (12.13). Students' perceptions regarding sharing feeling with the social robot capabilities and improving safety in science laboratory are as follows:  χ2(1) = 0. 434, p = 0. 510, with a mean rank for group 1. (9.79), and for group 2. (11.56). The authors combined the results to allow readers to concentrate on the primary findings for both groups without interruptions because of the positive data achieved in both groups.

4- While the study used well established tools like the System Usability Scale (SUS), the actual SUS score reported (M = 36.4) is substantially below the industry average threshold of 68. The authors nevertheless claim this shows that students found the system usable. This is a clear misinterpretation of the metric. A score in the 30s typically reflects a poor user experience and should be treated as such

The authors mentioned in (4.3. Procedure) sections: The second stage was to ask students about their prior experiences and expectations about social robots and their expectations about the use of socially assistive robots to enhance lab safety using the System Usability Scale (SUS). to receive feedback. Participants answered 12 questions about their understanding of the suggested interventions to improve safety in science laboratories by ranking each item on a Likert scale of 1 (strongly disagree) to 5 (strongly agree). Also, the authors add in the appendix the System Usability Scale (SUS) that the authors used in the current study. The scale data indicates that the students can receive a minimum score of 12 and a maximum score of 60.  Consequently, when the actual SUS score reported (M = 36.4), it indicates that a sufficient percentage of the students have passed the average score of the SUS scale.

5- The results section presents a general trend of improvement in students' attitudes before and after using the LSA system. While non-parametric (Wilcoxon) and parametric (t-test) analyses are applied correctly, the data is not thoroughly reported. The manuscript does not provide descriptive statistics such as means and standard deviations for key questionnaire items, nor does it identify which questions showed the greatest improvement. Furthermore, no raw score tables or response breakdowns are included. This prevents readers from assessing the true magnitude or distribution of changes.

 

We have added more information about the results, such as the sum rankings and statistical diagrams to support the results, as the authors indicated before the nonparametric test was performed. We believe this will help to clarify the results.

A Wilcoxon Signed Rank test was performed to evaluate the participants' expectations about how the integration of the suggested intervention into the LSA framework can provide a social assistive robot that provides us with a safe environment in the scientific laboratory (median = 106.5, Z = -2.39, p < 0.05, r = 0.53). In addition, the sum of the positive difference ranks (169.00) was larger than the sum of negative difference ranks (41.00), demonstrating a positive impact of the participants' expectations for using social robots’ capabilities to provide a safe laboratory. These results indicate that the effect size of using the suggested intervention is large in enhancing safety inside the scientific laboratory by using a social robot (Table 4).

 

A Wilcoxon Signed Rank test was performed to evaluate the experiences of participants about sharing feelings with a social robot that supports us to provide a secure environment in the scientific laboratory (Median = 22.5, Z = -2.36, p < 0.05, r = 0.53). In addition, the sum of the positive difference ranks (168.00) was larger than the sum of negative difference ranks (42.00), demonstrating a positive impact of the participants' expectations for using social robots’ capabilities to share feelings with a social robot to make a safe laboratory. These results indicate that the effect size of using the suggested intervention is large in evaluating the experiences of the participants about sharing feelings with a social robot and how it can support students to be in a safe environment in the scientific laboratory.

 

6- The discussion restates positive findings but does not reflect on known limitations of the study or the technology used. It avoids addressing the low SUS score entirely and fails to consider challenges such as the cost of deploying such systems in labs, the need for continuous maintenance, and the accuracy of Misty's behavior recognition capabilities. The unequal exposure of participants is also not discussed, despite being a key flaw in the experimental design. The lack of critical insight in this section diminishes the depth of the manuscript.

In conclusion, we add the limitations of the current study: Finally, we should discuss the limitations of the present study. We think that increasing the number of participants can yield more information that will help social robots better understand the risky behaviors that students may engage in. In addition, it can give more appropriate feedback based on the different levels of risky behaviors that students may exhibit. Additionally, recording videos and gathering data for more than a few weeks may highlight the benefits that users can experience while utilizing the social robot and framework in various types of educational lab. Conduct future research to detect more risky behaviors in different learning environments, such as playgrounds. Besides, a study for using a social robot to support students while conducting a specific experiment can provide us with more accurate data about the system usability. And more studies in various contexts may lead to a list of criteria for conducting a specific experiment in a specific context safely by using social robots. In addition, there is a need to explore the effectiveness of using the suggested framework for using a social robot while teaching students in primary school and kindergarten.

Reviewer 3 Report

Comments and Suggestions for Authors

The authors have followed all my recommendations so that the manuscript can be accepted in its current form

Author Response

Thank you for your feedback. We are happy that you are satisfied with our revisions.

Round 3

Reviewer 1 Report

Comments and Suggestions for Authors

1. Research Gap and Comparison with Non-Robotic Systems

Thank you for your response and the references provided. I understand that you aim to highlight the novelty of using a robot for lab safety. However, the concern was not only about the lack of robotic studies but also the absence of a clear comparison with existing non-robotic solutions.

While your response mentions some limitations of existing systems, it still does not present a structured or direct comparison with them. To strengthen the research gap, I encourage you to briefly discuss how your robot-based approach improves upon or complements existing non-robotic methods. Adding this comparison to the related work or introduction section would significantly improve the clarity and relevance of your contribution.

 

5. Lack of Detailed Results Reporting

It is good to see that you have added more statistical details, including Wilcoxon test results and rank sums. However, the original concern remains only partially addressed.

Readers would benefit from descriptive statistics such as means and standard deviations for individual questionnaire items and a clearer identification of which questions showed the most change. Including a response breakdown or visual summary  in a table or bar chart would also improve the clarity and usefulness of the results section.

 

Author Response

1. Research Gap and Comparison with Non-Robotic Systems

Thank you for your response and the references provided. I understand that you aim to highlight the novelty of using a robot for lab safety. However, the concern was not only about the lack of robotic studies but also the absence of a clear comparison with existing non-robotic solutions.

While your response mentions some limitations of existing systems, it still does not present a structured or direct comparison with them. To strengthen the research gap, I encourage you to briefly discuss how your robot-based approach improves upon or complements existing non-robotic methods. Adding this comparison to the related work or introduction section would significantly improve the clarity and relevance of your contribution.

 

In 2.3. Risky behaviors in science laboratory section you will find the following information:

Laboratory staff, such as instructors or lab assistants, are essential in avoiding accidents. However, each function they perform within the science laboratory has significant limitations. To keep users in a safe environment, educators can create a written safety policy. In addition, they have the power to prohibit students from using the laboratory until they have passed a test designed to gauge their familiarity with that procedure. As students require some experience to connect what they learn with what they encounter in the lab, there are several barriers to providing them with a secure environment. Each time a novel substance is used in the lab, the procedure must be reviewed, which adds time and effort. Although laboratory staff can keep an eye on every student at once, this nevertheless makes the science experiments uncomfortable for the students. Before students begin their work, lab staff can quickly verify that they are safe inside the lab.  However, they cannot always remain with students to monitor dangerous behavior while conducting studies. Using social robots like Misty II, all these problems can be solved with ease. Depending on how many robots can perform the tasks correctly, Misty II can supervise every student all the time. Table 1 below shows how Misty II’s capabilities can help with safety issues in science laboratories.

Table 1. Laboratory safety issues and Misty II’s capabilities [36], [37], [38], [39].

5. Lack of Detailed Results Reporting

It is good to see that you have added more statistical details, including Wilcoxon test results and rank sums. However, the original concern remains only partially addressed.

Readers would benefit from descriptive statistics such as means and standard deviations for individual questionnaire items and a clearer identification of which questions showed the most change. Including a response breakdown or visual summary  in a table or bar chart would also improve the clarity and usefulness of the results section.

 

The median, in our view, is significantly better for non-parametric tests. (Mean = 84.40, Median = 87, SD = 19.92) for the pre-test and (mean = 103.45, Median = 106.5, SD = 12.77) for the post-test.

 

The median, in our view, is significantly better for non-parametric tests. (Mean = 21.65, Median = 22.50, SD = 4.27) for the pre-test and (mean = 24.75, Median = 26, SD = 3.02) for the post-test.

The outcome demonstrates that students' expectations for robot capabilities and emotional sharing both rise to the same degree.

Round 4

Reviewer 1 Report

Comments and Suggestions for Authors

I recommend the acceptance of the manuscript in its current form.