Abstract:

This proposal aims to integrate Artificial Intelligence (AI)-enabled generative tools into the University’s undergraduate curriculum as a learning and teaching partner, fostering self-regulated learning (SRL) efficacy and stimulating critical and innovative thinking among students. The proposed 6-P pedagogical approach is designed to bolster students’ information literacy and academic integrity, guiding them through the non-sequential six key phases of Plan, Prompt, Preview, Produce, Peer Preview, and Portfolio Tracking when completing assignments in collaboration with AI learning partners. This novel learning and teaching partnership aligns with the University’s objectives of nurturing independent and innovative thinking among students while guiding them to use AI responsibly. The 13-month project will be a cross-faculty collaboration involving three faculties, five departments and one academic Centre. Faculty members will work together as a teaching team to implement the 6-P pedagogical approach and apply AI-enabled generative tools in the learning and teaching of at least eighteen selected undergraduate courses among ten different subject domains (>800 students) in the 2023/24 academic year. The selected courses encompass a diverse array including emotional well-being, field experience, cross-cultural perspective, global perspective, curriculum and assessment, law and enforcement, science and technology, computer-assisted linguistics, and Chinese language teaching. To ensure consistency in implementation, the principal project supervisor will collaborate with a LTTC team with the advisory group formed by the Co-supervisors to develop a centralized training e-package including three online interactive simulative adventure games for students and two videos for staff. The games will be designed as SRL tasks to let students apply the 6-P as game weapons to solve the simulative problems in the scenarios to develop students’ academic honesty, integrity and legal awareness. An introductory video produced by LTTC is adopted for informing students about the University’s policy and expectations centrally. A video will be produced for staff to understand what to be aware of and how to detect AI-related academic integrity breaches through an educative approach, not a punitive approach. Another video will conceptualize the teaching team’s wisdom in adopting AI in learning and teaching as the project outcome. Both students and the teaching team are co-developer of the e-package. The evaluated and improved e-package will be posted on the LTTC website for staff and students for long-term utilization. A mixed-method research approach will be employed to evaluate the project effectiveness including students’ SRL efficacy and other impacts in university education resulting from the implementation of the 6-P pedagogy and AI. The University’s validated questionnaires assessing the Generic Intended Learning Outcomes (GILOs) will be adopted for quantitative measurements of students’ problem solving skills, written communication skills and ethical decision making. Another validated tool namely Self-Regulated Academic Motivation (SRAM) (Wolters, 1999) will be adopted for assessing students’ SRL efficacy. Qualitative data will be collected from students in various milestone stages of the project as formative evaluation. The teaching team’s experience in adopting AI in their teaching process and their views on improving the e-package will also be continuously collected. The teaching team will incorporate the 6-P pedagogy, guiding students through their learning journey and developing their written communication skills and ethical decision making skills. AI will generate preliminary thoughts for preview based on students’ plans and prompts, supplementing output with additional knowledge, information, and alternative viewpoints for further exploration and elaboration in syntenic written drafts or other AI-generated products. Students will be guided to integrate AI-generated information with their own insights, fostering their ethical decision making capacity in selecting appropriate, accurate information with academic integrity and legal awareness. Peer review will refine the language and secure the content and reference reliability, while portfolio tracking serves as the final stage of academic writing, facilitating student self-reflection and the development of personalized improvement strategies. The project will support the University’s development and implementation of the 6-P pedagogy in conjunction with AI, enabling assessment of the pedagogy’s effectiveness in enhancing learning experiences. This proposal represents a long-term significant advancement in the integration of AI-enabled generative tools into the University’s education. Externally, the team targets to publish the findings from the project in high-calibre academic journals as professional sharing with worldwide counterparts.

Code:

T0277

Principal Project Supervisors:

• KONG, Suet Yee Suria

Keywords provided by authors:

• Artificial Intelligence
• 6-P Pedagogy
• Self-regulated Learning
• Learning and teaching partnership
• Gamification

Start Date:

01 Nov 2023

End Date:

31 Dec 2024

Status:

Completed

Financial Year:

2023-24

Type:

TDG