Master of Education (Learning Sciences and Artificial Intelligence)

Master (Coursework)

Provided by

Programme Type

Full-time, Part-time

NIE Graduate Programmes

gradstudies@nie.edu.sg
Enquire here Apply now

The Master of Education programme is primarily designed for educators working in Singapore schools and the Ministry of Education. University graduates with a background in education and wishing to advance your knowledge and skills in education are also welcome to apply.

The programme offers the degree in 16 areas of specialisation. These specialisations allow you to choose the area that best fits your interest as well as your career path, whether that path is towards the Master Teacher track, Specialist track or a general desire to update your knowledge and skills.

NIE is ranked #3 in Asia and #8 globally for Education in the 2026 QS World University Rankings by Subject.

The Master of Education (Learning Sciences & AI) equips you with perspectives from the learning sciences to understand and design learning in an AI-rich educational landscape.

Curious to know what our faculty and students think about our programmes? Click here to find out!

The Master of Education (Learning Sciences & AI) prepares educators to understand and shape the future of teaching and learning in the age of AI. Grounded in the learning sciences, the programme equips educators and learning designers to integrate AI and other technologies into pedagogical design and practice in ways that support meaningful learning. Learners will develop the knowledge and skills to critically evaluate emerging approaches and advance innovative learning practices across educational contexts.

The following are minimum admission requirements. Meeting these criteria does not guarantee admission, as selection is competitive.

  • A good Bachelor’s degree from a recognised university, or a relevant NTU FlexiMasters with good grades;

  • A teaching qualification such as the Postgraduate Diploma in Education from the National Institute of Education, Singapore
    or
    At least one year of relevant working experience in education

See detailed requirements for competency in English Language here.

There is generally only one intake for this programme, in August. You are advised to visit the website and look out for NIE’s announcements in November/December to confirm if the programme will be open for application at any particular intake.

Applicants who are currently working with sponsors, donors or financial institutions to fund their studies, are encouraged to submit their applications early to NIE so as not to miss out on our application period.

Applications are to be made online. Click here to sign up for an ISAAC (Integrated Student and Academic Administration System) account to apply with us. For those with an existing account, login to apply.

More information on required documents for application can be found here.

The coursework for this specialisation comprises of 1 core course, 1 required specialisation course, 2 specialisation elective courses, 2 open elective courses plus either:

  • A dissertation or
  • Two additional courses (one open elective course and MED 902 Integrative Project)

MED 902 Integrative Project is open only for applicants pursuing the degree totally by coursework.

Important note for matriculated students: 

Please refer to the ISAAC system for the programme structure relevant to your intake during Course Registration or consult Asst/Prof Wen Yun, your programme leader if you need clarifications.

Note: Programme structure is subject to changes

The degree of Master of Education is generally offered on a part-time basis although full-time studies are also available for some specialisations. The candidature periods are as follows:

Full-time

Minimum

1 year

Maximum

2 years

Part-time

Minimum

2 years

Maximum

4 years

The following is the detailed list of courses students have to complete:

Core Course

  • MED 900 Educational Inquiry

Required Specialisation Courses

  • MLA901 Foundations of the Learning Sciences & AI in Education

Specialisation Elective Courses

  • MLA902 Artificial Intelligence for Education: A Pedagogical Spectrum 
  • MLA903 Cognitive tools in the AI age
  • MLA904 Knowledge building with learning analytics, artificial intelligence and collaborative technologies
  • MLA905 Design of Interactive Learning Environments 
  • MLA906 Assessment in the Generative AI (GAI) Age 
  • MLA907 Digital Game-Based Learning 
  • MLA908 Learning Analytics for Educational Practitioners (4 AUs)

Open Elective Courses

Other than the core and specialisation courses, you may select open elective courses offered across all NIE Master's Degree programmes. The offer of electives is reviewed regularly to reflect developments in education and the respective fields. You are advised to take note of the prerequisites (if any) before registering.

Optional Specialisation Courses are offered subject to demand and availability of faculty expertise.  Hence, not all specialisation courses are available for selection to every intake.

 

Course Descriptors

MED900 Educational Inquiry (4 AUs)
This course introduces participants to the fundamental processes involved in conducting research such as formulating research questions, writing a review of the literature by synthesizing empirical studies, understanding various methodological approaches, collecting and interpreting research data. Participants in this course will have opportunities to develop the skills, knowledge and strategies needed to read, interpret, and evaluate the quality of research reports. In addition, participants will gain a critical understanding of quantitative, qualitative, and combined research approaches.

MED902 Integrative Project (2 AUs)
This capstone course requires participants to identify an education issue which forms the focus of inquiry, locate and read the most relevant literature to generate suggested potential solution to address the problem. The solution should show evidence that they are able to take the available information and restructure it in an appropriate way to deal with the issue.

MLA901 Foundations of the Learning Sciences & AI in Education (4 AUs)
TBC

 

MLA902 Artificial Intelligence for Education: A Pedagogical Spectrum (4 AUs)
Modern artificially intelligent systems for education (AIED) embody various pedagogical models to scaffold participants learning, each of which holds different implications for how the technology is designed and what kind of data is generated. This seminar-based course will showcase concrete use-cases of AI systems for education that are aligned with pedagogies such as mastery, inquiry learning, collaborative learning, socio-emotional learning, embodied learning, and demonstrate how they work and what their limitations are. By showcasing how these different learning possibilities can be created with AI-enabled technology, the course will enculturate participants into the practice of teaching with technology for active learning to create more participatory, connected and reflective classrooms. Taken together, in strong alignment with MOEs most recent EdTech masterplan 2030, this course will strengthen participants proficiency in e-pedagogies and their know-how of cutting-edge practices for creating and critiquing technology-enabled learning experiences drawing on artificial intelligence for education.

MLA903 Cognitive Tools in AI Age (4 AUs)
Topics include: 

*  Definition of cognitive tool and reasons for using technology as cognitive tools 

*  Classification of cognitive tools and research 

*  Concept of affordances 

*  Use of web 2.0 tools as cognitive tools 

*  Theoretical underpinning of concept/mind mapping tools 

*  Theoretical underpinning of computer supported collaborative learning (CSCL)

*  Affordances of CSCL tools for teaching and learning

MLA904 Knowledge building with learning analytics, artificial intelligence and collaborative technologies (4 AUs)
This course is relevant to school teachers or professional educators working in organizations. Knowledge building (KB)
 is a future-oriented pedagogy that aims to develop learners knowledge building capacity through collaborative idea improvement in schools or organizations. It is especially critical for the development of knowledge creation societies. An important supportive socio-cognitive and technological environment is critical. Technologies such as computer-supported collaborative learning (CSCL) have been used to support knowledge building. Emerging technologies such as learning analytics and artificial intelligence are also gaining traction.

In this course, you will participate as a member of a knowledge building community to explore and debate various issues related to fostering knowledge building in schools or your organizations. You will learn to craft inquiry-based learning activities, design thinking prompts to support intentional learning, facilitate social negotiation of ideas among learners and design both the face-to-face and online environments to help learners deepen their learning. You will also learn to leverage learning analytics and artificial intelligence to support learners in knowledge building.

MLA905 Design of Interactive Learning Environments (4 AUs)
Topics include: 

*  ILEs and Key findings from the Learning Sciences 

*  Critical Perspectives on Educational Technologies 

*  Design of Learning Environments  Orchestration 

*  Design of Scaffolding for Learning 

*  Design of Learning Experiences with New Media 

*  Design of Learning with Collaborative Technologies 

*  Design of Learning with Mobility 

*  Educational Games  

*  Design of Learning Spaces 

*  Assessment of Collaborative Learning 

*  Scaling educational innovations

MLA906 Assessment in the Generative AI (GAI) Age (4 AUs)
This course examines the evolving landscape of educational assessment in the age of generative AI (GAI). Rather than focusing on the technology itself, well critically analyze how GAI impacts assessment practices while upholding fundamental assessment principles. Well learn to design effective assessments that leverage GAI for personalized learning and feedback, while grounding ourselves in enduring assessment concepts. Well also investigate how GAI can uncover deeper insights from assessment data and facilitate self-directed learning. Using Selwyns socio-technical framework, we will problematise the context, looking into the limitations, and ethical considerations of GAI in assessment, emphasizing the enduring priorities in this rapidly changing times.

MLA907 Digital Game-Based Learning (4 AUs)
The course will deal with digital games and theories of play that can support digital game-based learning. Students will be exposed to different approaches to the use of digital games to support teaching and learning together with their underlying theoretical bases. They will also learn through a substantial game-based learning group project.

The specific topics include: 
- Digital games for education
- Theories of play for conceptualising digital games
- Theories of learning for conceptualising game-based learning
- Game-Based learning and Gamification
- Design for learning with digital games 

Students are required to spend at least 3 hours in course readings and class preparation each week.

MLA908 Learning Analytics for Educational Practitioners (4 AUs)
This course is designed for educational practitioners, particularly MEd (LST) students, who are interested in the theoretical foundations and applications of learning analytics across educational areas (e.g., primary to tertiary students, adult-learning). Activities will include in-class discussions, designs, and presentations, all of which are intended to help students build up a strong foundation in understanding the theoretical and educational use of learning analytics for teaching and learning. Participants will beable to engage with theories presented in the readings as well as to connect learned content to their own teaching practices; guided with learning from case studies and reviews. The course will help to enhance learners educational data literacy as well as their assessment literacy.

 

For tuition fees, please click here.

For more information about scholarships, please click here. 

For programme-related matters, please consult the programme leader, Asst/Prof Wen Yun for more information.

 

Related Programmes