voyeurism

Disciplinary Intuitions / Six Learnings / Maker Motes / AI & data science offered as part of NTU's Undergraduate Research Experience on Campus (URECA) programme 2021/22

are you an NTU undergraduate eligible for the Undergraduate Research Experience on Campus (URECA) programme 2021/22?

if so, please do consider applying for

NIE21020 Exploring the potential roles that game-based worlds and immersive environments play in learning

NIE21021 Exploring the development of maker dispositions in learning through open-source hardware and software

NIE21152 Designing predictive models for analysing environmental sensor data from a network of IoT sensor devices

NIE21153 Exploring the role of coding, data science and machine learning in the Humanities classroom :-)

it would be my privilege to work alongside you :-)

visit our team's mini-campus in Frame VR

my team and i are very happy to invite you to visit a mini-campus - in Frame - which we have designed to showcase some of our work.

Frame is a website that lets people communicate and collaborate in a 3D space as avatars from a browser on desktop, mobile, or VR. It is currently still in beta.

for our mini-campus, we used one of the standard environments provided by Frame, and populated the space with examples of our work.

we are excited about Frame because the multiplicity of ways in which content may be accessed - from smartphone to full-blown desktop VR - coupled with the low barriers to access - visitors only need a standard web browser - points a way forward for immersive and VR learning spaces to come.

for example, Frame runs from a web browser on desktop (including Chromebook), mobile, or VR.

on desktops and notebooks, Frame is accessible through Chrome, Safari, Firefox, or Chromium-based Edge browsers.
in stand-alone VR, Frame is accessible through the Oculus Browser.
on mobiles and tablets, Frame is accessible through Chrome on Android, and Safari on iOS.

do have a go :-)

a trajectory in Artificial Intelligence, Data Science and Machine Learning

as my team's experience with Maker Motes and the Internet of Things has grown since our first forays eight years' ago, we have anticipated that the datasets generated by the sensor meshes we have emplaced within school campuses across Singapore would be growing, too.

in late 2019, we started monitoring the field of Artificial Intelligence (AI), Data Science and Machine Learning (ML), especially as applied to learning and education. 

we have been dissatisfied with the extent to which the particular paradigm of using AI as tools for analysing student behaviour and performance has been pervasive in much conversation around education.

we challenged ourselves to continue exploring and keeping open minds, and, in - Steve Jobs's words - not to "settle".

we particularly also wanted to extend the narrative around AI, Data Science and ML beyond the traditional domains of Mathematics and Computer Science.

this year, together with some of our students, we conceptualised two examples of the applications of AI, Data Science and ML to the Digital Humanities.

the first is an idea for a History lesson unit in which a dataset of historical commercial voyages is visualised using the R programming language, in order to show the extent to which Singapore as a trading post in the 19th century was connected to other parts of the world.

the second is an idea for poverty mapping in which several years of satellite imagery is analysed using trained Machine Learning models in order to identify patterns of development across regions and countries in Southeast Asia.

through God's grace, and through the very kind invitation of Seoul National University, i will be sharing these projects on a session themed on Education Technology and the Learning Sciences, as part of the 21st International Conference on Educational Research (ICER) to be held on the 21st and 22nd of October.

all thanks be to God alone.

Credit: Lambert & Co., G.R. / Singapore
Leiden University Library, KITLV, image 150813 Collection page Southeast Asian & Caribbean Images (KITLV)