Pedagogical Showcase

Explore where our faculty and IN-Learning collaborate to transform teaching.

Pedagogical Showcase

Discover how our faculty are reimagining teaching and learning. The Pedagogical Showcase highlights innovative practices that are transforming the learning experience across NIE.

Be inspired by stories of experimentation, collaboration, and educational excellence from our faculty, many made possible through close partnerships with IN-Learning and supported by the Incentivising ICT Use Innovation Grant (i3G). The i3G grant empowers faculty to bring bold, technology-enhanced ideas to life and supports NIE’s efforts to advance ICT integration in teaching and learning.

 

 

ALEX

What If AI Could Design Your Course?

Meet ALEX — the Generative AI partner helping faculty create aligned, engaging learning experiences.

Smarter Course Design, Powered by AI

Designing a constructively aligned course often involves balancing multiple elements — learning outcomes, activities, assessments, and institutional frameworks. ALEX (AI-Powered Learning Experience) was created to simplify this process without compromising academic rigor.

What is ALEX?

ALEX is a Generative AI-powered Microsoft Word add-in developed by NIE in collaboration with Microsoft. Integrated directly into Word, it enables faculty to generate contextually aligned course outlines within minutes. Powered by OpenAI’s GPT-4o, ALEX combines human expertise with AI efficiency to make course design faster and smarter.

How It Works


Faculty provide basic course details such as title, description, and duration. ALEX then produces a draft course outline that includes:

  • Intended learning outcomes aligned with institutional frameworks
  • A weekly plan with activities and assessments
  • Suggested resources and EdTech tools

Every outline is anchored on NIE’s TE21 Framework, NTU’s OBTL+ model, and the Blended Learning@NIE policy, ensuring academic quality and constructive alignment.

Why It Matters

Unlike generic AI tools, ALEX is designed specifically for faculty. It saves time, supports blended learning design, and allows faculty to retain full control over final decisions.

A screenshot of ALEX user interface

 

Learn more about ALEX and its development here:

 

Project PI: Associate Professor Shanti Divaharan, Head, LSA

Project Co-PI: Mdm Shamini D/O Thilarajah, Deputy Director and Head, IN-Learning

Supported by: Ms Punithavathy Palanisamy, Learning Specialist, IN-Learning; Mr Henry Ngoh, Academic Resource Developer, IN-Learning

 

 

 

PALAS

What If Learning Adapted to You? 

Discover how PALAS uses AI to personalise the journey of mastering Malay Morphology. 

 
In the Malay Morphology module, student teachers often start with varying levels of prior knowledge. To address this challenge, the Personalised Adaptive Learning and Assessment System (PALAS) was developed as an AI-enabled platform designed to personalise learning and assessment. Leveraging adaptive learning principles, PALAS dynamically adjusts instruction and practice based on each learner’s progress, enabling a more tailored and self-directed learning experience. 

 

Key Features of PALAS 

  • Learner-Centric Design: Offers each learner a unique pathway, allowing progression at an individual pace. 
  • Integrated Access: Delivered seamlessly through Blackboard NTULearn with single-login access. 
  • Adaptive Mastery Loop: Uses real-time diagnostics to estimate mastery levels and recommend next steps for learning. 
  • Actionable Analytics: Provides instructors with detailed data to support timely intervention and content adjustment. 

 

PALAS Homepage 

 

Development and Pilots 

The system was conceptualised and developed between July 2022 and December 2023 through collaboration among experts in linguistics, pedagogy, assessment, and educational technology. Two pilot runs were conducted with student teachers in 2023. Pilot 1 (March 2023) involved 44 users and focused on initial usability testing while Pilot 2 (October 2023) introduced improved UI/UX and recorded positive engagement and higher effect sizes in learning outcomes. Analytics from both pilots indicated strong concept coverage, high pass rates, and encouraging feedback from learners, including increased motivation and confidence in teaching Malay grammar. 

 

Pedagogical Framework 

PALAS is underpinned by a robust framework consisting of: 

  • Curriculum Mapping: Breaking lessons into assessable concepts. 
  • Content Authoring: Creating instructional and assessment items with calibrated difficulty. 
  • Mastery Loop Design: Guiding learners through Engage, Present, Guided Practice, and Assessment stages. 
  • Adaptive Feedback: Offering immediate feedback and personalised recommendations based on mastery estimates. 

 

Through continuous monitoring and adaptive adjustments, PALAS enables differentiated learning pathways while equipping faculty with data to inform lesson redesign and intervention strategies. 

PALAS Pedagogical Framework  

 

Explore the full story of PALAS here. 

 

Project PI: Dr Suryani Binte Atan, Teaching Fellow, ALC 

Supported by: Ms Punithavathy Palanisamy, Learning Specialist, IN-Learning 

 

Pedagogical Showcase Videos: 

Critical Visual Literacy 
Dr. Alexius Chia from ELL shares his approach to teaching critical visual literacy, a skill that has become increasingly vital in today’s world of pervasive visual media. His students reflect on how learning to critically engage with visuals helps them make sense of and navigate their everyday lives. 

Independent Learning with Branching Videos 
Dr. Roszalina Rawi from ALC introduces branching videos as an engaging tool for independent learning. Through their experiences, learners share how this approach enhances their autonomy and deepens their understanding through providing an interactive means of self-revision. 

Knowledge Building Pedagogy 
A/P Tan Seng Chee and Dr. Teo Chew Lee reflect on the growth of Knowledge Building Pedagogy at NIE since the early 2000s. They share strategies for designing lessons around its 12 guiding principles, while learners share how knowledge building has supported and enriched their learning experiences. 

 

 

 

AVAIL

AVAiL is an AI-powered video analytics platform that seeks to understand learner engagement in an online synchronous lesson. Funded by the I3G, it tracks online learners’ facial expressions in real time and allows tutors to make data-informed decisions through their learner’s affective engagement and emotional connection to their learning. Faculty will receive real-time and post-lesson data on the affective, cognitive and behavioural engagement of learners through a Zoom-based dashboard. The end goal is to enable faculty to improve the design of lessons and student engagement, adapt their teaching strategies, and foster a more inclusive and effective learning environment.

 

Project PI: Wang Qiyun, Associate Professor, LSA

Supported by: Wang Luhao, Learning Data Specialist, IN-Learning

 

 

 

Learning Buddy

Learning Buddy is a Gen-AI empowered self-learning platform to enhance student learning by providing a personalised, engaging, and interactive platform that supports self-regulated learning. Funded by the I3G, the platform integrates self-assessment strategies, Gen-AI driven feedback, and real-time feedback, analytics and prompts to promote self-reflection. This is achieved by guiding students in setting goals, conducting diagnosis quizzes, monitoring and tracking progress through self-assessments, and prompting students with questions at key points in their learning to encourage self-reflection and critical thinking.

 

Project PI: Dr Chua Kah Loong, Deputy Head, PCHD

Supported by: Ms Punithavathy Palanisamy, Learning Specialist, IN-Learning

 

 

 

Coaching Observation Tool

The Coaching Observation Tool (COT) is an AI-powered application that provides timely and meaningful feedback to sports practitioners to help them improve their craft in the aspect of values-driven teaching or coaching. Funded by the I3G, this technology-enabled learning solution aims to contribute towards values teaching and learning practices not just in PE and CCA but also across all other academic subjects taught in schools. With coding of both live teaching and recorded footage, the sports practitioner can make a comparison between his/her values-driven lesson plan (i.e. planned) and the statistic provided by the app (i.e. actual).

 

Project PI: Koh Koon Teck, Associate Professor, PESS

Supported by: Ahmad Adil Irfan Bin Muhammad Yusman, Digital Media Specialist, IN-Learning