Using Generative Artificial Intelligence Tools to Explain and Enhance Experiential Learning for Authentic Assessment

Round 1

Reviewer 1 Report

The present research addresses a highly topical and pertinent issue in the field of educational technology. The integration of Generative Artificial Intelligence (GenAI) tools in higher education is an emerging area that promises to revolutionise teaching and learning methodologies. Its focus on experiential learning and authentic assessment in the context of GenAI is particularly relevant given the rapid transformations in the educational field.

Having said that, the following are a few identified weaknesses and strengths of this work.

In relation to the areas for improvement of the paper:  

1. Clarity and Depth of definitions: Although the paper introduces the concepts of experiential learning and authentic assessments, the paper would benefit from an in-depth and detailed explanation of these concepts and how they relate specifically to GenAI tools. This would help readers to better understand the theoretical and conceptual framework on which the research is based.

2. Hypothesis Formulation: A more precise and robust formulation of the hypotheses is recommended. Although the research questions are well defined, the hypothesis is not explicitly stated. A clear and well-articulated hypothesis would improve the cohesion and direction of your study.

3. Methodology - Use of Ethnography of Things: "The employment of the 'ethnography of things' methodology in this study to analise the integration of GenAI tools, is innovative but may also raise questions about its applicability and scientific rigour. It would be advisable for the authors to clarify how this methodology fits with the research objectives and to raise any potential limitations related to its use that they consider relevant.

On the other hand, the most relevant elements are also worth mentioning: 

1. Innovation in the Use of GenAI Technology in Education: This paper explores the pioneering application of Generative Artificial Intelligence (GenAI) in higher education, an emerging and rapidly evolving field. The integration of GenAI tools in experiential learning and authentic assessment represents a significant contribution to the field of educational technology, addressing innovative aspects of teaching and learning.

2. Unique Methodology - Ethnography of Things: The adoption of 'ethnography of things' as a methodology to study interactions between GenAI tools and users is particularly distinctive. Employing a pioneering methodological approach, the paper provides a new perspective on educational research, allowing for a deeper exploration of how technological tools interact and are integrated into educational practices.

3. Exploring Practical Applications of GenAI in Education: This research not only theorizes about the application of GenAI in education, but also provides practical examples and suggestions on how these tools can be used to enhance learning and assessment. This includes the formulation of AI-enriched learning outcomes and the integration of GenAI at different stages of the experiential learning cycle.

4. Detailed Analysis of GenAI Tool Responses: The research presents a thorough analysis of the responses garnered from the GenAI tools, illustrating the ability of these tools to generate coherent and relevant responses in the context of experiential learning and authentic assessment.

In conclusion, your research represents a valuable contribution to the field of educational technology and GenAI. Appreciation is expressed for the opportunity to review such a meticulously crafted study and hope that my suggestions will be useful in strengthening your manuscript. Personally, I congratulate the entire team for their hard work and dedication to this important area of research.

Author Response

Dear reviewer,

Thank you for reviewing our manuscript and for your encouraging comments and valuable suggestions. We have addressed the latter thoroughly and hope you will find the amendments made to the manuscript appropriate. Please find attached a table with a point-by-point response to your suggestions and our revised manuscript with all changes highlighted to facilitate their identification. 

We are looking forward to hearing from you.

Kind regards,

The authors  

Author Response File: Author Response.pdf

Reviewer 2 Report

The authors used thing ethnography to explore authentic assessment and experiential learning in Generative AI-integrated education. The results provide references and inspiration to educators on possible ways of engaging Gen AI as learning support rather than merely generating answers.

I would advise the authors to enhance the transparence by detailing how reliability was achieved. Particularly, considering Gen AI can generate different answers to the same interview question, hence, leading to different categorizations/themes. Were there any countermeasure in place?

Author Response

Dear reviewer,

Thank you for reviewing our manuscript and for your encouraging comments and valuable suggestions. We have addressed them thoroughly and hope you will find the amendments made to the manuscript appropriate. Please find attached a table with a point-by-point response to your comments. Also, please find attached our revised manuscript with all changes highlighted to facilitate their identification. 

We are looking forward to hearing from you.

Kind regards,

The authors  

Author Response File: Author Response.pdf