Master of Education (Learning Sciences and Technologies)

Full-time

Minimum

1 year

Maximum

2 years

Part-time

Minimum

2 years

Maximum

4 years

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.

MLT901 Foundations of the Learning Sciences (4 AUs)
This course considers present day discourses on learning/learning sciences in the broader context of education and how people learn. Students will deepen their understanding of constructivist learning approaches and learn to be cognizant of the vital roles of language and inquiry in human learning.

Specific learning sciences topics include: 

*  Conceptual change 

*  Knowledge building 

*  Cognitive apprenticeship 

*  Learning in activity 

*  Computer-supported collaborative learning 

*  Learning in virtual worlds 

*  Teacher education from the perspective of learning sciences 

*  Design-based research

MLT902 Orchestrating and scaffolding 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.

MLT903 Technologies as Cognitive Tools (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

MLT906 Design of Technology-mediated Learning Environments (4 AUs)
The pervasiveness of technology is taken for granted in the new information age. Technology-mediated learning, whether using the Internet, using social media, or via mobile devices, are increasingly adopted. However, uninformed and uncritical uses of emerging technologies are often observed. This course aims to equip students with solid theoretical bases for making compelling design decisions with respect to technology- mediated learning environments in order to increase students cognitive engagement, learning experiences, and learning outcomes.

This course will first discuss the issues that underpin traditional approaches to learning. Second, it will broaden students exposure to new learning theories, models, and design principles that can guide them through the design, development, and evaluation of technology-mediated learning environments. Third, this course will elaborate on the key design components of a technology-mediated learning environment, which include pedagogical design, social design, and technical design.

MLT907 Neuroscience, Technology and Learning (4 AUs)
With advances in neuroscience and educational technology, teaching and learning accelerates into a new stratosphere. Accompanied by technological and social learning mobility, there's immense fluidity in the way content is delivered, how skills and dispositions are developed and how assessment is enacted. Learners have access to not only seamless digital learning experiences but so too experiences that can be informed by the latest neuroscientific research on how the brain works. At the same time, uninformed and uncritical uses of emerging neuroscientific technologies can perpetuate neuromyths and pose as impediments to the overall learning processes.

This course aims to equip students with solid theoretical bases for making compelling pedagogical design decisions with respect to the use of neuroscientific technologies for learning and to optimize future-ready learning, as arising from evidence-informed scientific research. This course will cover tenets of brain-based learning, learning as changes in neural connectivity, neuroscientific technology use, and applications for the use of neuroscientific technologies in pedagogy/andragogy practice.

MLT908 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

MLT909 Research Methodologies for the Learning Sciences (4 AUs)
1. Concept, purpose and process of conducting research

2. Research and ethics

3. Identifying research problem

4. Conducting critical literature review

5. Writing research questions

6. Designing surveys and interviews

7. Collecting quantitative data

8. Collecting qualitative data

9. Analysing quantitative data

10. Analysing qualitative data

11. Reporting research

MLT910 Technological and Pedagogical Considerations for ICT Integration (4 AUs)
The topics include: 
- Core issues of ICT integration
- Relevance of TPACK framework
- Key TPACK concepts
- Measuring TPACK
- Specific TPACK (seminar leading)
- Contextual influences of TPACK
- Students conception of TPACK 

MLT911 Instructional Leadership for Technology-mediated Learning (4 AUs)
The course aims to provide conceptual as well as practical understanding of Instructional Leadership for technology integration in schools. During the course, participants will use Activity Theory as a framework to analyse the various dynamic components that lead to effective technology integration in schools.

MLT912 Design for Blended Learning (4 AUs)
This course introduces the theoretical foundations of blended learning and different forms of blended learning -blended asynchronous learning (e.g., using discussion forums), blended synchronous learning (e.g., using video conferencing), and flipped classroom (e.g., using recorded videos) - and providing practical guidelines on designing the blended learning environment in the school context. The focus of the course is on designing the blended learning environment and facilitating student learning in the environment.

MLT913 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.

MLT914 Educational Design Research (4 AUs)
Topics include: 

*  research designs and design research 

*  two-fold yield of educational design research 

*  quality criteria for evaluating interventions 

*  educational design research models 

*  formative evaluation in educational design research 

*  challenges in educational design research

MLT916 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.

MLT917 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.