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Active Learning, Mentoring and AI- Open Educational Resources: A Case Study in a Virtual Laboratory Cover

Active Learning, Mentoring and AI- Open Educational Resources: A Case Study in a Virtual Laboratory

Open Access
|Mar 2026

Figures & Tables

Figure 1

CASYE mentoring framework.

Source: Diesis Network (2022a), CASYE Mentoring Model Programme Framework.

Table 1

Alignment of mentor interventions with the CASYE framework.

CASYE COMPONENTMENTORING FUNCTIONEXTRACT FROM MENTORING NOTES
Mentoring approachStructured the start; clarified scope and expectations.“Participants have clarity on the tool to develop: a chatbot for HR that can accomplish specific tasks, although they haven’t defined them yet.”
Idea developmentPrompted function discussion of the OER.“I asked several questions for reflection: What problem are you trying to solve with the chatbot? Who is going to use it, and how will it help them? Could it support recruitment or a specific area in the institutional context?”
Your potentialRecognized and reinforced use of prior experience.“The strength of the group lies in their profiles; they have experience with generative AI tools, have worked together before, and developed OER.”
Your environmentRaised licensing concerns; prompted tool/platform choice.“I suggested they check the compatibility of licenses. Does ChatGPT allow for the kind of open, educational reuse you’re planning?”
They were considering ChatGPT. They decided to work with Poe instead.”
Your ideaReinforced coherent structure and communicability of outputs.“If you’re building additional materials make sure they follow the principles of OER. For the chatbot, I suggested they create a ‘catchy’ name related to human resources.”
Hard skillsHighlighted disciplinary contributions.“Col5, who is a medical doctor and was a first-time participant, asked how he could contribute. The team suggested he contributed with content connecting HR to health.”
Soft skillsSupported inclusion, validated absent participants.“They belong to the same university, are colleagues, and professors, which facilitates cohesion and collaboration. How can HR practices benefit from your expertise? Are other members joining the project?”
Team and ecosystemObserved and supported team dynamics and leadership rotation.“Col1 and Prom1 assumed leadership; tasks and decisions were distributed among the group”.
Access to financeNot directly applicable in this case.Not observed. All software and tools are used in the free trial version.
Legal formsReassured use of open licensing and attribution.“Remember to get your open license from the Creative Commons website”.
Community engagementPrompted alignment with 2030 Sustainable Development Goals (SDG) and social relevance.“In your final pitch, focus on the chatbot demonstration rather than explanation. Link it to the SDG as it matters in the context of the lab. You will only have 10 minutes.”
Impact and sustainabilityFramed product development with long-term use.Not observed. All OER from the laboratory were placed in a repository by the coordinators.
Table 2

Alignment of mentees’ collaborative actions with the CASYE framework.

CASYE COMPONENTMENTORING FUNCTIONCOLLABORATIVE ACTIONSEXTRACT FROM LAB NOTEBOOK
Mentoring approachStructured the start; clarified scope and expectations.Assigned roles; clarified project scope and deliverables.“The objective is to create a website that provides resources for orientation and learning to develop AI tools in HR.”
Idea developmentPrompted function discussion of the OER.Generated chatbot scenarios, defined content scope.“The design chatbot in ChatGPT is to evaluate job positions and HR departments, and perform specific tasks related to industrial and organizational psychology”.
Your potentialRecognized and reinforced use of prior experience.Mapped roles based on disciplinary expertise.“Col1: theory and chatbot; Col11: theory for Topic 5; Col6, Col7, and Col5: onboarding content.”
Your environmentRaised licensing concerns; prompted tool/platform choice.Compared Poe and ChatGPT, documented ethical/licensing decisions.“Reviewed Poe because ChatGPT does not allow the type of free use we are looking for”.
Your ideaReinforced coherent structure and communicability of outputs.Outlined components (chatbot, manual, video), aligned them.“We will use Wix to integrate the chatbot and the manual; we will also make a tutorial video.”
Hard skillsHighlighted disciplinary contributions.Wrote manual, drafted chatbot scripts, built web site.“This is what we need: Video procedure for chatbot development… Manual content: instructions, procedures, and chatbot development steps.”
Soft skillsSupported inclusion, validated absent participants.Used WhatsApp for coordination.“This is the recording for the meeting, if you couldn’t attend it today.”
Team and ecosystemObserved and supported group dynamics and leadership rotation.Rotated leadership, coordinated platform use, documented meetings.“Assignments: webpage – Prom1; magazine – Prom2; theory and chatbot- Col1; chatbot- Col2 and Col4, theory- Col11.”
Access to financeNot applicable in this case.Not applicable.Not observed.
Legal formsReassured use of open licensing and attribution.Obtained a Creative Commons license.The group got the Non-Commercial-Share-Alike license in the Creative Commons website.
Community engagementPrompted alignment with SDG and social relevance.Framed product as reusable for HR training and institutional use.Resources included video, PDF and text processor technical documents, to promote access to educational resources across different contexts.
Impact and sustainabilityFramed product development with long-term use.Packaged product for accessibility.The group published the final OER on the website.
Figure 2

Home page AI-OER website.

Source: Recursos Humanos-REA https://jgaticap1.wixsite.com/rh-rea/copy-of-videos.

Figure 3

Interface of AI- OER prototype.

Source: Recursos Humanos-REA. Bot RRHH 2024 https://poe.com/Bot-rrhh_2024.

Figure 4

User’s manual for personalized AI chatbots.

Source: Adapted from Manual RH-REA https://jgaticap1.wixsite.com/rh-rea/acerca-de.

Figure 5

Video tutorial to create a HRM chatbot.

Source: Recursos Humanos-REA. Laboratorio chatbot https://www.youtube.com/watch?v=s1qgugvgY-w.

Table 3

Assessment of the AI chatbot across the OER principles.

OER PRINCIPLEEVALUATIONLEVEL OF ALIGNMENTANALYSIS
Open LicensingThe chatbot is covered under the CC BY-NC-SA license via the overall project documentation.HighThe chatbot can be freely used and adapted under a non-commercial license, which benefits organizations looking to train staff or support HR tasks.
ReplicabilityInstructions are provided to guide the development of a similar chatbot, but the original chatbot’s logic and scripting are not published.MediumAlthough the chatbot’s programming isn’t shared, practical instructions and examples help HRM teams replicate the experience with limited tech skills.
AdaptabilityThe chatbot scenarios are framed around HRM tasks, which can be adapted, though flexibility depends on users’ technical skill.MediumThe design covers distinct HRM topics and could be tailored, but users cannot replicate or modify its architecture without recreating it in Poe independently.
AccessibilityIt is accessible through the RH-REA Wix site without login or access barriers, available for immediate use.HighAnyone can use the chatbot without logging in, making it easily accessible for HRM professionals or trainees.
TransparencyWhile intended use and design logic are explained in the manual, the inner workings are not exposed.MediumThe manual explains what the chatbot does, but not how it works behind the scene, which might limit deep customization by users.
UsabilityUsers interact with the bot via predefined inputs; it is intuitive to use but offers limited interactivity and no adaptive responses.MediumThe chatbot is simple and practical for typical HRM scenarios, though it doesn’t adjust its responses based on user behavior or learning progress.

[i] Source: RH-REA website (https://jgaticap1.wixsite.com/rh-rea).

Table 4

Assessment of the AI- OER package.

COMPONENTOPEN LICENSINGREPLICABILITYADAPTABILITYACCESSIBILITYTRANSPARENCY
WebsiteMediumMediumLowMediumMedium
ManualHighHighHighLowHigh
ChatbotLowLowLowMediumMedium
VideoMediumMediumMediumMediumMedium
Overall PackageMediumMediumMediumMediumHigh
DOI: https://doi.org/10.5334/jime.1033 | Journal eISSN: 1365-893X
Language: English
Submitted on: Apr 16, 2025
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Accepted on: Oct 24, 2025
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Published on: Mar 20, 2026
Published by: Ubiquity Press
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2026 Darlene González Miy, published by Ubiquity Press
This work is licensed under the Creative Commons Attribution 4.0 License.