The absolute
explosion of data created and generated by connected devices
(#IoT data) is changing the way businesses are run across many sectors. Also, new consumption patterns of smart technologies are reshaping the future of work in corporate life.
Higher Education & Research is also being re-calibrated, driven by the pandemic, and by possibilities offered by the Internet of Things (IoT), Artificial Intelligence (AI), and Machine Learning (ML).
What are some of the use cases? How for example can ML, AR and IoT transform education? Let’s look at the potential and some concrete use cases.
Immersive Learning
Sophisticated campus facilities are crucial to attracting students and teaching staff. IoT, VR / AR, and other currently available technologies can enable universities to build immersive educational spaces with mixed virtual-plus-reality environments to improve the learning experience and finally improve institutional goals/outcomes: successful students. By providing a sense of “being there,” specifically IoT, ML, and VR can enrich both students’ learning experience and the faculty’s teaching experience, in part by detecting conditions when it makes sense to switch to different learning scenarios, aka adaptive learning.
Imagine how medical students can immersive themselves performing surgery long before they will be conducting this in real life. Students will be able to practices advanced anatomical positions which will lead to better surgical outcomes and a reduction in surgery time.
Think about students at campus or at home who could interact with other students, educators, and experts across the globe studying the same topic, seeing and experience the same via VR and AR. These kinds of experiences can be of tremendous value for learning and eventual student success.
A great example of an institution that is making this real is the National University of Singapore. NUS is applying emerging technologies such as VR and AI to create more
immersive remote learning. NUS has created a number of projects that use VR and AR capabilities. They have bold ambitions in this space and are also planning to further use AI to analyze student behaviors and provide true “personalized education”.
Connected Campus
With campus infrastructures connected to the personal devices of teachers, researchers, and students, every campus stakeholder can dynamically plan and more efficiently use university space. Students will know whether study pods are full, and they should collaborate on projects online rather than meeting at the library, especially most relevant in times where campuses are still (partially)
closed due to COVID19.
Researchers can determine in real-time whether space in their favorite lab is available or book a lab and associated resources if needed.
Campus real-estate can be monitored and surveilled with empowered sensors, RFID’s, cameras, and other connected devices to improve safety and security. A Connected Campus can also be a safer campus. Think about utilizing smart IoT-based lantern pols or faculty building lights to provide a safe route away from disaster or incident. The more common use case is to utilize smart-lighting which has the potential to
drastically reduce CO2 emissions and as well can improve student’s
concentration in the classroom
Personalized Learning
With smart devices – such as mobile phones, smartwatches, health trackers, tablets, and more –
gathering information about students connected to an institution’s LMS and SIS, universities can create personalized learning solutions with study plans and learning paths tailored to individual students. For example, nudges to notify, motivate, inform students are possible once you start to keep track of their engagement data.
Data can be collected about students and their use of online learning resources, and AI and ML can be harnessed for the system to learn and adapt. For example, with a certain successful outcome of an assessment, the system can proactively offer more challenging learning resources to the student. Conversely, supplementary materials can be provided to a student who is struggling to comprehend the material, basically providing a digital personal tutor supporting the student in his journey to becoming successful in their studies.
You could even think about smart sensors like
eye trackers that can be harnessed to detect and determine challenges, such as when students are distracted during learning, and in almost real-time generate alternate learning scenarios or again giving them a nudge with relevant information related to the content they struggle with.
Increased Sustainability
IoT is already making a considerable difference in reducing costs and improving productivity and safety in the energy and real-estate sectors. Remote monitoring of classroom utilization and teaching equipment provides analytics to help higher education and research institutions conserve valuable energy and save significant spending. Facility management departments can use IoT-based HVAC data to make
data-driven decisions around the campus real-estate and assign equipment and rooms based on utilization to make sure resources are used in a sustainable manner.
Sophisticated sensors in research tools and assets can trigger predictive and proactive service to decrease maintenance costs and downtime. IoT-based sensors can also collect data on for example
air quality in campus buildings and classrooms. This is especially relevant in times of students returning to campus and the responsibility of institutions to provide a healthy environment for their students. IoT sensor data can be used to inform facility management and even directly the teacher in real-time about the air quality.
AI-powered Research
To guarantee high-velocity research outcomes researchers must collaborate across research projects while being acknowledged for their unique contributions. Technologies like ML and AI can be intelligently expanded and utilized in ways that researchers can have a personalized view of the available
grants matching their focus areas, interest, and historically awarded grants. It also provides the opportunity to intelligently expand the network for collaboration by identifying historical successful collaborations. Such ML/AI-based innovations for research will improve the quality of the overall grant application process, improve collaboration, and the eventual success rate of the application.
ML and AI can also play a crucial role in the pre-award phase, especially when the budget needs to be formed and resources and personnel planning are subject to a successful and complete grant application. With the available historical data from successful research projects, grant applications can be utilized to propose (and in fact predict) a specific budget to the principal investigator. This will give an enormous head start in their budget forming efforts. This is especially valuable given the known grudge against admin burden kind of tasks by academia...
Huge Potential
The technologies discussed provide educational institutions and research institutions new possibilities to reimagine and transform the very fabric of their core business. IoT and other tech can strip away barriers in education and research such as physical attendance, geography, and social/economic status and as well provide true automation of labor-intensive admin tasks.
The potential is huge and just too promising to ‘only keep the IT lights on' within your institution…
Learn more about a platform that can accelerate your innovation in Higher Education & Research here: Intelligent Technologies
#### Initially published on LinkedIn 24th September 2021 ####
