Goal
The purpose of the ideation session is threefold:1) To grow and align EdTech research in NIE and MOE
2) To share issues and identify priority areas in EdTech research
3) To promote collaborations for EdTech research with various funding tiers
Personalised Education Through Adaptive Learning And Assessment, One of the 5 initial Singapore AI Projects - to help teachers to better customise and improve the learning experience for every student.
The governments aim is to leverage AI through the Singapore Student Learning Space (SLS), an online learning platform for all students and teachers in the national school system, launched in May 2018.
Students’ learning experiences with the SLS will be enhanced by an AI-enabled Adaptive Learning System. The adaptive learning system will use machine learning to enable it to tell how each student responds to learning materials and activities, and to recommend a step-by-step pathway customised for each learner.
Teachers will be able to assess students’ work more efficiently and effectively with an AI-enabled Automated Marking System. The automated marking system will be able to assess open-ended student responses such as short-answer response questions and essays and provide quick feedback to students’ work.
This year the government will pilot an AI-enabled automated marking system for English Language with selected primary and secondary schools.
https://entuedu-my.sharepoint.com/:w:/g/personal/riduanm_niestaff_cluster_nie_edu_sg/EcUW5nUyQ0BGilfzaLyU5ToBLRdTJaiNqHRTGWVpXdLa6g?rtime=q7A2yAJp2Eg
Facilitators From Educational Technology Division / MOE
e-Assessment RG: Jean Phua, Lawrence Wee
Affective Tech RG: Samuel Tan
Digital Learning RG: Tay Siu Hua
Immersive Learning Tech & Environment RG: Soo Jiunn Huat
National Institute of Education
A/P Tan Seng Chee
Personalised learning is an educational approach that aims to customize learning for each student's strengths, needs, skills and interests. The student has a learning pathway that is based on what he or she knows about the target content, and how he or she can learn best.
To date, a key part of MOE’s plan to enable greater personalised learning involves the development of AI-enabled adaptive learning systems deployed via the Student Learning Space. But can greater personalised learning can also be achieve via expert algorithms (virtual labs inquiry learning task activities) and user data analytics (aggregated usage patterns) as well?
Concurrently, starting from July 2020, the Personalised Digital Learning Programme (PDLP) is being rolled out to secondary schools. One of the intended outcomes of PDLP is to support self-directed and collaborative learning. With every student equipped with a personal learning device (PLD), they are empowered to be self-directed learners who are intrinsically motivated. Students are also able to learn beyond curriculum time at their own pace using PLDs to meet their needs, to explore interests, passion and/or real-world problems anytime and anywhere.
What is the impact of Adaptive Learning System (ALS) augmented teaching and learning on students’ learning outcomes?
How do teachers make use of an AI enabled ALS to personalise learning for each child?
How can we apply current AIED approaches to less structured subjects?
What new pedagogies should be adopted to ensure collaborative and social learning even with personalised instruction?
How do students regulate their learning in a personalised digital learning environment?
SN
Scaffolding/Leading Questions
Notes of Discussion
Q1
What is the impact of Adaptive Learning System (ALS) augmented teaching and learning on students' learning outcomes?
Q2
How do teachers make use of an Al-enabled ALS to personalise learning for each child?
Q3
How can we apply current AIED approaches to less structured subjects?
Q4
What new pedagogies should be adopted to ensure collaborative and social learning even with personalised instruction?
Q5
How do students regulate their learning in a personalised digital learning environment?
Other Key Points
Students’ learning experiences with the SLS will be enhanced by an AI-enabled Adaptive Learning System. The adaptive learning system will use machine learning to enable it to tell how each student responds to learning materials and activities, and to recommend a step-by-step pathway customised for each learner.
Teachers will be able to assess students’ work more efficiently and effectively with an AI-enabled Automated Marking System. The automated marking system will be able to assess open-ended student responses such as short-answer response questions and essays and provide quick feedback to students’ work.
This year the government will pilot an AI-enabled automated marking system for English Language with selected primary and secondary schools.
EdTech Virtual Ideation Session – Breakout Room #1 Personalised Learning
https://tinyurl.com/OER-ETD-EdTech2020-1https://entuedu-my.sharepoint.com/:w:/g/personal/riduanm_niestaff_cluster_nie_edu_sg/EcUW5nUyQ0BGilfzaLyU5ToBLRdTJaiNqHRTGWVpXdLa6g?rtime=q7A2yAJp2Eg
Facilitators From Educational Technology Division / MOE
e-Assessment RG: Jean Phua, Lawrence Wee
Affective Tech RG: Samuel Tan
Digital Learning RG: Tay Siu Hua
Immersive Learning Tech & Environment RG: Soo Jiunn Huat
National Institute of Education
A/P Tan Seng Chee
Personalised learning is an educational approach that aims to customize learning for each student's strengths, needs, skills and interests. The student has a learning pathway that is based on what he or she knows about the target content, and how he or she can learn best.
To date, a key part of MOE’s plan to enable greater personalised learning involves the development of AI-enabled adaptive learning systems deployed via the Student Learning Space. But can greater personalised learning can also be achieve via expert algorithms (virtual labs inquiry learning task activities) and user data analytics (aggregated usage patterns) as well?
Concurrently, starting from July 2020, the Personalised Digital Learning Programme (PDLP) is being rolled out to secondary schools. One of the intended outcomes of PDLP is to support self-directed and collaborative learning. With every student equipped with a personal learning device (PLD), they are empowered to be self-directed learners who are intrinsically motivated. Students are also able to learn beyond curriculum time at their own pace using PLDs to meet their needs, to explore interests, passion and/or real-world problems anytime and anywhere.
What is the impact of Adaptive Learning System (ALS) augmented teaching and learning on students’ learning outcomes?
How do teachers make use of an AI enabled ALS to personalise learning for each child?
How can we apply current AIED approaches to less structured subjects?
What new pedagogies should be adopted to ensure collaborative and social learning even with personalised instruction?
How do students regulate their learning in a personalised digital learning environment?
SN
Scaffolding/Leading Questions
Notes of Discussion
Q1
What is the impact of Adaptive Learning System (ALS) augmented teaching and learning on students' learning outcomes?
Q2
How do teachers make use of an Al-enabled ALS to personalise learning for each child?
Q3
How can we apply current AIED approaches to less structured subjects?
Q4
What new pedagogies should be adopted to ensure collaborative and social learning even with personalised instruction?
Q5
How do students regulate their learning in a personalised digital learning environment?
Other Key Points
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