7A – Human Judgement, AI Support: Rethinking Competency Based Learning Design at NYP

17:00 - 17:30 22/03/27 ROOM MY 01 - 04

Abstract

Competency-Based Learning (CBL) is a pedagogy that is integral to designing industry-relevant and future-focused programmes. However, translating competency frameworks—such as Singapore’s SkillsFuture—into coherent curricula remains complex and resource-intensive. This session showcases how Nanyang Polytechnic (NYP) addresses this challenge through an AI-supported curriculum design approach that enhances, rather than replaces, educator judgement.

Participants will gain insights into how AI can systematically support the alignment of competencies with learning outcomes, assessments, and learning activities, while ensuring coherence with national frameworks and institutional criteria. Drawing on NYP’s practical experience, the session will illustrate how the tool is embedded within academic workflows to improve design efficiency, consistency, and quality—without diluting educator agency or professional expertise. Importantly, the session will highlight principles for responsible, human-centred AI adoption, emphasising ethical considerations, contextual decision-making, and sustained educator ownership. For institutions seeking to design and deliver innovative, workforce-relevant curricula, this presentation offers actionable strategies to leverage AI meaningfully—strengthening programme design while keeping educators at the core of the learning experience.

Learning objectives

  • Explain how AI can be used to augment (not replace) educator judgement in competency-based curriculum design, with educators retaining decision-making control throughout the process.
  • Illustrate how an AI-supported curriculum design tool can be aligned to national frameworks and institutional criteria, drawing on practical insights from NYP’s hands-on experience.
  • Apply key principles for responsible, human-centred AI adoption that participants can adapt and implement within their own institutional curriculum design contexts.

Target audience

Teaching and learning leaders, heads of curriculum, faculty leads, and curriculum innovators interested in how AI can support competency-based curriculum design.

Session members

Click underlined name to view biography.

Session members will be added shortly once they have confirmed their participation.

Presentations

Key Dates

General Proposal Submissions

General Proposal Submission:
24 June 2026 23:59 AEST Closed

Proposal notifications:
late September 2026

Academic Research Submissions

Phase 1: Abstract Submission:
3 June 2026 Closed

Phase 2: Full Paper Submission (for accepted abstracts):
12 August 2026 Closed

Phase 3: Revised Full Paper Submission (incorporating reviewer feedback):
12 November 2026

Registration

Early bird open: from mid-September 2026
Early bird close: 12 January 2027
Standard open: 13 January 2027
Standard close: 20 March 2027
Late open: 21 March 2027

APAIE 2027 Conference & Exhibition

Pre-conference workshops: 21 March 2027
APAIE 2027 Kuala Lumpur: 21 – 25 March 2027
Post-conference campus tours: 25 March 2027

Submissions

Proposal submission: 24 April – 24 June 2026
Research submission: 24 April – 3 June 2026
Pre-conf workshop submission: 24 April – 3 June 2026

Early bird open: from mid-Sepember 2026
Early bird close: 12 January 2027
Standard open: 13 January 2027
Standard close: 20 March 2027
Late open: 21 March 2027