A Framework for Hybrid Human-AI Learning: Insights from Liberal Education Courses in Lebanon

Reine Azzi

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Conference: 2025 ASEE Annual Conference & Exposition
Location: Montreal, Quebec, Canada
Publication Date: June 22, 2025
Start Date: June 22, 2025
End Date: August 15, 2025
Conference Session: Computers in Education Division (COED) Track 4.B
Tagged Division: Computers in Education Division (COED)
Page Count: 29
Permanent URL: https://peer.asee.org/55365

Paper Authors

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Reine Azzi Lebanese American University orcid.org/0000-0002-8107-4137

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Reine Azzi teaches liberal arts courses at the Lebanese American University. She received her Doctorate in Education from the University of Exeter, United Kingdom. She is passionate about exploring education technology and the disruptive power of Generative AI. She believes in the need for collaboration to debate shared beliefs, assumptions, and teaching practices.

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Abstract

The global debate over Generative Artificial Intelligence (GenAI) has continued in academic institutions, resulting in discussions on academic integrity and educational standards in a world where ‘ChatGPT’ use continues to permeate educational, professional, and social contexts. While some academic institutions initially called for banning GenAI tools, many have emphasized the need to introduce these tools within controlled classroom settings. At the Lebanese American University, nine faculty members began to experiment with GenAI use immediately after the release of ChatGPT in November 2022. The assessment design and results of that action research allowed participating faculty members to improve upon their application of GenAI in their second and third iterations of the exercise in their respective classes. In addition to sharing their experience, this paper focuses on a framework for pedagogical practice that could guide faculty as they critically plan their course activities and prepare their students for the use of GenAI in different academic settings. While emphasizing academic rigor, faculty using this framework will thoroughly analyze their existing course and program learning outcomes to accurately determine the potential for hybrid human-AI learning outcomes. Through Bloom’s Revised Taxonomy, faculty can re-evaluate the use of GenAI in their courses or programs, dissecting these outcomes to better utilize AI capabilities while highlighting Human skills. While many faculty members have been incorporating GenAI activities in their classes on an ad-hoc basis, this framework focuses on an in-depth approach, determining a collaborative approach to using GenAI tools, with learning outcomes clearly visualizing the hybrid process. A sample course on Hybrid Human-AI communication will also be shared to portray the process. This course is designed with GenAI in mind, allowing students to focus on learning with all the tools at their disposal. The detailed activities (which will be shared in the study) also expose students to another aspect of the pedagogical framework: A mindful awareness of the AI Usability Spectrum. For instance, while Bloom’s revised taxonomy is instrumental in the creation of Human-AI learning outcomes and course content, the framework also encourages faculty to reflect upon the AI Usability Spectrum. To maintain academic integrity and embrace the full use of Human-AI learning, faculty can engage students in the learning process, determining the ‘right’ amount of AI usage for every task. This practice includes breaking down tasks into categories pertaining to writing, critical thinking, and research while classifying AI use into low, medium, and high intensity. This interactive process introduces critical exercises where students compare different platforms to determine suitability for specific tasks, promoting a discussion on data ethics, privacy, and academic honesty. To promote further implications for practice, the study showcases opportunities for reflection, both as individual users and in groups through using Socratic Dialogue, as faculty and students test the limitations of different platforms and address the ethics of using GenAI in a world that increasingly blurs the lines pertaining to Cyberethics.

Citation
Format

Azzi, R. (2025, June), A Framework for Hybrid Human-AI Learning: Insights from Liberal Education Courses in Lebanon Paper presented at 2025 ASEE Annual Conference & Exposition , Montreal, Quebec, Canada . https://peer.asee.org/55365

TY  - CPAPER
AB  - The global debate over Generative Artificial Intelligence (GenAI) has continued in academic institutions, resulting in discussions on academic integrity and educational standards in a world where ‘ChatGPT’ use continues to permeate educational, professional, and social contexts. While some academic institutions initially called for banning GenAI tools, many have emphasized the need to introduce these tools within controlled classroom settings. At the Lebanese American University, nine faculty members began to experiment with GenAI use immediately after the release of ChatGPT in November 2022. The assessment design and results of that action research allowed participating faculty members to improve upon their application of GenAI in their second and third iterations of the exercise in their respective classes. In addition to sharing their experience, this paper focuses on a framework for pedagogical practice that could guide faculty as they critically plan their course activities and prepare their students for the use of GenAI in different academic settings. While emphasizing academic rigor, faculty using this framework will thoroughly analyze their existing course and program learning outcomes to accurately determine the potential for hybrid human-AI learning outcomes. Through Bloom’s Revised Taxonomy, faculty can re-evaluate the use of GenAI in their courses or programs, dissecting these outcomes to better utilize AI capabilities while highlighting Human skills. While many faculty members have been incorporating GenAI activities in their classes on an ad-hoc basis, this framework focuses on an in-depth approach, determining a collaborative approach to using GenAI tools, with learning outcomes clearly visualizing the hybrid process. A sample course on Hybrid Human-AI communication will also be shared to portray the process. This course is designed with GenAI in mind, allowing students to focus on learning with all the tools at their disposal. The detailed activities (which will be shared in the study) also expose students to another aspect of the pedagogical framework: A mindful awareness of the AI Usability Spectrum.  For instance, while Bloom’s revised taxonomy is instrumental in the creation of Human-AI learning outcomes and course content, the framework also encourages faculty to reflect upon the AI Usability Spectrum. To maintain academic integrity and embrace the full use of Human-AI learning, faculty can engage students in the learning process, determining the ‘right’ amount of AI usage for every task. This practice includes breaking down tasks into categories pertaining to writing, critical thinking, and research while classifying AI use into low, medium, and high intensity. This interactive process introduces critical exercises where students compare different platforms to determine suitability for specific tasks, promoting a discussion on data ethics, privacy, and academic honesty. To promote further implications for practice, the study showcases opportunities for reflection, both as individual users and in groups through using Socratic Dialogue, as faculty and students test the limitations of different platforms and address the ethics of using GenAI in a world that increasingly blurs the lines pertaining to Cyberethics.  
AU  - Reine Azzi
CY  - Montreal, Quebec, Canada 
DA  - 2025/06/22
PB  - ASEE Conferences
TI  - A Framework for Hybrid Human-AI Learning: Insights from Liberal Education Courses in Lebanon
UR  - https://peer.asee.org/55365
ER  -