Extended reality Technology
It is not new to envision the future of education and the art of learning in general. The French artist Jean-Marc Côté imagined what education would look like in 2000, more than a century ago. The notion that literature might be electronically uploaded and processed straight into young people’s brains made many laugh when they saw his picture, but the idea would resurface in the science fiction film “The Matrix” from 1999.
Can art imitate life, though? In the upcoming years, will extended reality (XR) and artificial intelligence (AI) merge to create learning environments akin to those portrayed by Côté in “The Matrix”?
Just 16 billion, or 2%, of the $6.5 trillion K–12 education market is presently allocated to educational technology. Even so, a lot of teachers use technology to help their students reach their full potential. Even so, the majority of the time technology is only utilised to enhance passive teaching techniques (such as instruction via flat interactive panels, digital textbooks, online videos, and testing), which leads to minimal to nonexistent increase in academic achievements because of low student engagement. Active teaching techniques provided by AI and extended reality learning experiences, on the other hand, might be more beneficial to pupils.
The majority of extended reality experiences offered by content providers now are around STEM-based simulations, digital twins, virtual tours, and games. The convergence of AI modalities, however, presents us with a really transformative potential to fulfil the promise of “personalised” learning and produce quantifiable academic outcomes. These different generative AI applications will be put to use in the near future, automating them to provide real-time learning opportunities.
What can be done in the classroom today with generative AI?
With the help of generative AI, educators may design highly personalised classes. With minimal technical expertise, educators can rapidly produce dynamic movies to use as teaching aids through a series of manual procedures. Let’s discuss one such avenue for producing this kind of content:
Write a basic screenplay:
Request that Bard or ChatGPT compose a brief three- to five-minute video script that addresses the problem or instructive subject you want to tackle. Modify any content to meet quantifiable learning objectives.
Change to a script for a conversation:
To make the information produced by AI seem more real and conversational, copy and paste the original text into a programme like Quillbot.
Put together your audio story:
Paste the updated conversational text into Speechify or another application. You can choose from a variety of voices, such as Snoop Dogg and Gwenyth Paltrow, if you have their premium membership.
Make a video:
Using programmes like Movio or Invideo, upload your script and audio file, select the genre, and choose the delivery method (computer or the smartphone).
With the help of this technique and numerous others, teachers can add even more personalisation to their customised lectures. For instance, generative AI can produce lesson plans that highlight a student’s strengths and target their areas for growth. Teachers can free up time by training large language models to engage in discussions with children for targeted, on-demand support.
Though education has undoubtedly advanced in the current era thanks to technology, we primarily witness this in the form of computer and the tablet screens. Even with the familiar form of today’s 2D technology, children still find up staring at screens rather than engaging with their teachers and fellow students. Here’s where extended reality enters the picture and aims to close this gap. Combining generative AI with spatial computing capabilities to create an immersive learning environment that engages students with interactive and collaborative courses is another way that generative AI can be used in education.
Utilising artificial intelligence in extended reality learning
These days, the majority of extended reality learning opportunities take the form of walkthroughs or simulations, which are essentially an upgrade over standard lab and video materials. Most of them are singular experiences with distinct beginnings and ends. According to a PwC report, users were almost three times more confident in their ability to apply the skills they had gained from their extended reality training, and even with extended reality learning as it currently exists, learners absorbed information four times faster than in a typical classroom.
What if a real-time platform was equipped with the greatest generative AI techniques? I think the end product is a transformative tool that enables each learner to reach their full potential. Let’s examine a few ways that this idea of (Ai)daptive extended reality pronounced Ai-daptive can produce significant outcomes:
Introduces learning at the student’s present level:
Using (Ai)daptive XR to take into account the student’s actual abilities. Content is presented in that language right away if they feel more at ease doing so (thereby getting around a common challenge faced by ELL students nowadays).
Personalisation:
(Ai)daptive XR can provide actual personalisation, yet current attempts at personalisation frequently amount to nothing more than differentiated learning. The programme can quickly identify strengths and weaknesses and modify the learning objectives based on the first few difficulties in a simulation. For instance, if the learner finds it difficult to perform complex multiplication and the simulation’s objective is to measure the volume of spaces, the student will usually fail the simulation with minimal progress.
(Ai)daptive XR may identify the gap’s underlying cause fast and modify the learning objectives to assist the child in completing the prerequisites before reaching the original learning aim. On the basis of the identified learning obstacles, a new extended reality simulation is developed. Instead of letting these weaknesses build up and lead to the child’s future academic failure, the learner can then be better equipped to successfully achieve the objectives on a subsequent simulation.
Making learning relevant:
When students don’t recognise the relevance of the material, most classroom subjects fail to “engage” them. However, (Ai)daptive extended reality content can be swiftly modified to offer the material in a theme that is both effective and meaningful to the student by taking into account the student’s personal passion. For a young child who dreams of becoming a fashion designer, for instance, a simulation measuring an area of farmland may be instantly updated in real-time to measure an area of cloth. The result of that simulation may alter significantly as a result of that swift adjustment.
User-responsive:
(Ai)daptive XR is capable of responding to voice input from the user(s) in their native language, instead of just judging performance based on where the user “clicks” with a hand controller. Though conversational speech from the user will allow for more realistic interaction and enable the system to address inquiries or concerns, current extended reality simulations are restricted in their ability to gather user response.
Real-time feedback:
Learners can reinforce their mastery of earlier topics through simulations, in addition to seeing the actual ramifications of their decisions. Teachers frequently don’t have enough time in typical classroom settings to administer evaluations to their students. However, real-time natural assessments can be carried out in a stress-free setting several times a day with extended reality.
Collaboration:
Since it is simpler to produce individual-based content, few extended reality learning simulations permit numerous students to collaborate on a task. When a group of students collaborates, they can offer difficulties and novel scenarios, and (Ai)daptive XR can evaluate these and modify the content presented based on the group’s behaviour in the simulation.
Benefits of Extended Reality
With (Ai)daptive extended reality, the possibilities are virtually limitless
In the upcoming ten years, the development of instructional extended reality with AI will be a fantastic and welcome addition to EdTech. It is an opportunity to provide every child in every community with truly customised training. Considerable debates in a number of areas, such as governance, privacy, connectivity, and equity, will be necessary in light of these changes.
AI will permeate every aspect of our everyday lives as examples of generative Artificial Intelligence continue to be adopted by the general public over the course of the next ten years. Qualcomm Technologies, with its expertise in extended reality processing and AI, is at a crossroads in this industry. Seeing this through to completion throughout my lifetime is my dream.
