LibGuides: AI@NIE Resource List: AI / GenAI Teaching and Learning Grants

Project Title	PI	co-PI(s) / collaborators	Project Description
Teacher's pet - A Lesson Planning Assistant	Mr Paul Lincoln	Ms Khek Bee Lian	The project proposes the development of an artificial intelligence lesson planning assistant designed to support teachers, especially beginners, in creating effective lesson plans. By providing a conversational interface similar to a chatbot, the application helps educators articulate their goals, suggests pedagogical strategies, and offers relevant content ideas, thereby reducing anxiety and improving the quality of lesson design. The project aims to integrate this tool into NIE’s programmes, with a focus on enhancing teaching practices and fostering confidence among new teachers.
Artificial Intelligence Support for Instruction in Science Experiments	A/P Tan Aik Ling	Ast/P Chng Wei Ming Edwin	The project seeks to develop an artificial intelligence (AI) agent to support teachers in science laboratories by monitoring student safety, providing learning assistance, and assessing laboratory skills. By utilising computer vision technology, the AI agent will continuously observe student activities and alert teachers to safety violations or students in need of support, thereby reducing the cognitive load on educators and enhancing the overall learning experience. The project is designed to improve classroom management and facilitate more effective teaching practices in science education.
The Use of Machine Learning to Enhance Teaching-learning Experiences in Physical Education	Dr Tommy Ng	Dr Steven Tan Dr Tan Shern Meng Dr Teo Wei Peng Dr John Komar	The project aims to enhance teaching and learning in Physical Education (PE) by developing a technology-based tool that leverages machine learning and human pose estimation. This tool will enable proficient demonstrations of motor skills, provide students with objective feedback on their performance, and assist teachers in effectively monitoring student progress. By utilising digital devices to record and analyse movements, the project seeks to improve assessment procedures and decision-making processes in PE, ultimately fostering better motor skill acquisition and collaborative learning among students.
Personalised Adaptive Learning and Assessment System (PALAS)	Dr Suryani Binte Atan	Ms Punithavathy A/P Roksana Dr Roszalina Mr Muhammad Irwan Ms Shamini Thilarajah Ms Niko Chen Ms Eveleen Ching Mr Eric Bonneau	The project aims to develop an AI-driven platform that provides individualised learning experiences for student teachers at NIE. By focusing on grammar mastery, PALAS will adapt learning pathways based on each learner's prior knowledge and mastery level, enabling self-directed learning. The initiative seeks to enhance teaching practices, improve student outcomes, and support tutors in monitoring progress through data-driven insights.
Artificial Intelligence-powered Learning Experience Design Tool	A/P Shanti Divaharan	Ms Shamini Thilarajah Ms Punithavathy	The ALEX project is an initiative designed to develop an Artificial Intelligence-powered Learning Experience design tool aimed at improving course design in higher education. By leveraging AI algorithms, ALEX seeks to align assessments and teaching activities with intended learning outcomes, thereby enhancing the quality of courses and faculty productivity. The tool will serve as an electronic course design assistant, providing real-time feedback and suggestions to faculty, ultimately fostering better outcomes-based teaching and learning practices while reducing the time and effort needed for course development.
Leveraging Generative AI for 21st Century Teaching and Learning	A/P Tan Seng Chee	Dr Teo Chew Lee Dr Alwyn Lee A/P Chen Wenli Dr Seow Sen Kee Peter Dr Mutlu Cukurova	The project seeks to enhance educational practices by utilising generative AI technologies, specifically Large Language Models like ChatGPT. It focuses on developing and evaluating strategies for both students and instructors to improve self-directed and collaborative learning. The project will conduct a comprehensive literature review, implement various AI applications in educational settings, and create ethical guidelines for AI usage in teaching. Additionally, it seeks to assess the impact of these innovations on teaching and learning outcomes over an 18-month period.
AI-powered Sports Coaching Observation Tool (COT) -A Mobile Application	A/P Koh Koon Teck	Mr Ahmad Adil Irfan Mr Oun Kai Hiong	The project focuses on developing an A-powered mobile application - the Coaching Observation Tool (COT) designed to enhance the quality of coaching/teaching by automating the categorization of coaches' or physical education (PE) teachers’ instructions during lessons. The application can generate insightful reports to reflect the quality of coaching/teaching. This project aims to enhance practitioners’ self-awareness and competency in integrating values and character education in sports and PE by providing real-time feedback and suggestions based on what was planned and what happened during lessons. It also aims to facilitate quality self-reflection and promote self-directed learning for coaches and PE teachers, ultimately enhancing their student-athletes learning outcomes in value and character education.
Developing an AI-Powered Video Analytics Tool to Monitor Student Engagement in Synchronous Online Learning	A/P Wang Qiyun	Ms Renuka d/o Nasendran Mr Wang Luhao Mr Dennis Lee	The project aims to develop an AI-powered video analytics tool that monitors student engagement in synchronous online learning environments. By utilising facial recognition and other data analytics, the tool will provide real-time insights into learners' affective, cognitive, and behavioral engagement during online classes. This information will help educators adapt their teaching strategies and improve lesson design, ultimately enhancing student participation and learning outcomes.
InsightPeer: An AI-supported Peer Feedback System to Improve Students’ Feedback Literacy	A/P Chen Wenli	Mr Eric Bonneau Ast/P Zhu Gaoxia	The project seeks to develop a digital prototype that enhances students' ability to give and receive constructive peer feedback. By utilising generative AI, the system will provide immediate guidance and support throughout the feedback process, focusing on key components such as setting clear criteria for feedback, assisting in constructing quality responses, and offering suggestions for improvement. The initiative seeks to address common challenges in peer feedback activities, ultimately fostering better collaboration, critical thinking, and communication skills among students. The project will be implemented over two years at NIE, targeting graduate education courses.
Building A Teacher Observation Optimisation Platform with AI to Assess Teachers’ Motivational Behaviour in the Classroom	Prof John Wang Chee Keng	A/P Liu Woon Chia A/P Kee Ying Hwa Dr Betsy Ng Dr Lim Seok Lai Mr Benny Lam Nah Peng	The project aims to create an AI-driven Teacher Observation Optimisation Platform that assesses teachers' motivational behaviors in the classroom. By leveraging machine learning, the platform will provide feedback on whether teachers employ autonomy-supportive style which is crucial for fostering a positive classroom environment. This tool is intended to enhance teaching practices and improve student engagement and outcomes, particularly for student teachers and NIE staff at Nanyang Technological University. The project will collect authentic classroom data and refine the AI system to ensure accurate assessment and feedback on teaching behaviors.
Learning Buddy - Gen-AI Platform to Facilitate Self-regulated Learning via Self-Assessment	Dr Chue Kah Loong	Dr Tay Hui Yong Ast/P Amelia Yeo Ms P Durka Devi Ms Punithavathy	The project aims to create a generative AI platform designed to enhance self-regulated learning among students. By integrating self-assessment strategies and providing personalised feedback, the platform will support learners in setting goals, tracking their progress, and reflecting on their learning. Targeting pre-service and in-service educators, the project seeks to address challenges in self-directed learning by offering tailored resources and interactive tools that promote metacognitive awareness and engagement, ultimately improving educational outcomes.
GenAI in Action: Transforming Analytics Course in Business Education	Ast/P Li Qiujie	Ast/P Tanmay Sinha Ast/P Tang Qinshen	The project aims to integrate GenAI into problem-based learning for business education as means to foster student-centered learning, where students lead the investigation of complex and uncertain problems and teacher facilitate the process through prompting techniques and worked examples.
PhET-style simulations to promote AI literacy	Ast/P Tanmay Sinha	Dr. Peter Seow Prof David Hung	The project aims to develop a curated library of interactive, high-quality web-based resources for teachers following an explore-then-instruct pedagogy that puts NIE at the forefront of AI literacy.