Hello, this Group A prepared the Opportunity Forecast team project about Neuroscience. We have addressed (in brief)
- BBL & Educational Neuroscience
- Neuroplasticity and Artificial Intelligence
- Market Analysis and Future Opportunities
You can participate in our activities and discussion questions after looking at our website for a week. ETEC522: Opportunities in Neuroscience (google.com)
As the topic of Neuroscience is quite broad and a lot has been covered in our website, you can focus and navigate to areas that are of greater importance to you.
Enjoy!
Activities
BBL & Educational Neuroscience:
- Activities from the Ministry of Education (Canada, South Korea)
- Take the MBTI test and share the results in Padlet. / Drawing and quiz activities.
- Identify feelings from “Inside Out”.
- Play the Best Mental Games and Exercises to Improve Memory.
- Share your dreams and students’ dreams.
- Attend a field trip or watch the Brain Awareness Week video. / Future Goals.
Market Analysis:
- Padlet responses on both Market Analysis and Future Opportunities.
- Market Analysis – Which of the products/services highlighted did you find interesting? Why? What do you think the impact of these products will be?
- Future Opportunities – Which of the potential products or services do you feel will have the greatest impact on their corresponding field? Why?
Neuroplasticity and AI:
- The inherent ethical challenges in AI and neuroscience are raised. There are also some Facts on Deep Learning and advances in AI for future opportunities- Take a peek at the websites for fun games and other information.
- There is a lot of new information from 2023 so take your time to read if you want to delve further.
Discussion Questions (Together) – Participate in discussion questions in Padlet or on the ETEC 522 website.
BBL & Educational Neuroscience: Share your positive experiences only here. Which activity did you try from the BBL & Educational Neuroscience? (Padlet)
Market Analysis: Current Market Analysis & Future Opportunities Padlet discussion
Neuroplasticity and AI: What legal regulations govern the use of AI as it increasingly used to source more information, invade individual personal privacy (despite claims to not do so) and shape decisions which may or may not be dependent upon bias fed into AI training?
- What rules prevent AI from using bias?
- Will deep learning prevent bias in shaping AI training?
- Will AI improve neuroplasticity and intelligence building or not? If not, then explain why
Haejin, Sheena, and Benjamin
Hi Neuroscience team!
What an interesting and dynamic topic! I think you outline some really cool connections between the human mind and machines, and while it’s a little terrifying (thinking about how AI is modeled off the human mind for example), I also think the opportunities of AI are really exciting. I was troubled when I read that there is not enough supervision of machine learning, and it seems to make a lot of sense that this would be the case considering the sheer scale of these projects, but it’s not a major concern I hear frequently.
I do not think it is possible to be entirely unbiased, we will always need to continue to be growing and changing as we move through our lives and have to navigate new societal changes. And I think this can be applied to products as well, like AI. I do not think deep learning is particularly the solution to biases in machine learning, though I am sure the method can allow for more targeted outcomes. With deep learning, there is a selection of curated data, meaning the researchers are choosing a data set that is refined and run through the machine. The question then becomes, who is selecting the data? And currently, with the diversity disparities in tech, it’s very likely that the people who are making the important decisions around data sets are all from similar backgrounds and identities. Obviously, that is not to say that this won’t change in the future, but presently, the majority of the programmers making these decisions are white affluent men, who are known within software development to be making biased decisions through ignorance (checking out Algorithms of Oppression by Nobel if you want some context/stats). Curated data sets will improve the outcomes of the algorithm if the instructions provided by the programmers take biases into consideration and actively work to dismantle these biases. That would mean ensuring that folks who can recognize and identify biases are able to contribute to the machine learning process. But that would mean diversifying perspectives at an authoritative, systemic level – which is a much bigger and more complex problem than just choosing different data sources. So to answer your question, while I think deep learning can offer the opportunity to reduce bias, I think the problem does not reside in the machines themselves, but in the folks programming them.
I agree with you on the issue of bias and datasets. It is interesting to think of the connection between the bias in Artificial Intelligence and the original biases in Intelligence Quotient tests. Essentially, we seem to be capable of recognizing intelligence in others and machines when it most closely corresponds to our own ideas of what intelligence is. This is an issue that permeates curriculum as well in my opinion. The most obvious choice for reducing bias in AI is to include ever greater diversity in the people who are selecting training datasets, yet this still presents bias through the training and interest required to be in the position to choose the datasets. Are there limitations to AI that may never be surpassed simply because there are too few people who have the right combination of skills? With the advancement of AI in education, what happens if the AI, which has been trained to only recognize certain types of intelligence, is given too much power in educational choices? We already live in an educational system that values some types of ability over others.
Hello Helena
thanks for this. Yes, to put the matter to the forefront, AI is a product of human intelligence and intellect. Unfortunately these gifts also come with pre-judgement and ultimately bias. While bias is part of the human psyche construct, so to speak, it is hoped that as intellect develops (ideally through neuroplasticity) so will self awareness of bias ideally, through self knowledge and reflection ie. why do I think this of this group and not another ? etc.
However, given the fact that the paradigm of globalization today should indicate benefits such as more learning, understanding and self -knowledge, so has our brilliance led us to AI, originally a cause celebre, While quality management and quality control are methods designed to root out weaknesses and improve functions, safety and excellence, these factors have largely been incorporated into industry, education and health care where internal audits are utilised and profit from findings, therefore increasing clinical performance through knowledge feedback and correction of weaknesses..
My impression is that finding an appropriate QC tool to monitor AI, it would seem that there is an urgent need to develop another set of quality control guide;lines to address the actions and consequences of AI – the question however hovers around whether this tool would devised and consist of human competencies and knowledge or whether we would need to incorporate AI into monitoring its own actions / consequences ie as a feedback loop or another type of Learning Loop.
Another great Opportunity Forecast, team!
It’s interesting to see how each week seems to build from the last, as this is a relatively complicated idea but it’s made easier to understand after learning about wearables and assistive technologies. When reading through your material I continually returned to the thought of what the future will look like. With that thought in mind I tackled the question ‘will AI improve neuroplasticity and intelligence building or not?’
As you showed with the memory activities, AI-based tools can provide cognitive training exercises and brain games that target specific cognitive skills, such as memory, attention, and problem-solving. Regular practice with these tools may potentially stimulate neuroplasticity and improve cognitive abilities. I know I’m going to need more practice as I was shocked at my poor memory.
The rapid processing and pattern recognition capabilities of AI can significantly impact data analysis. AI can analyze large datasets of brain imaging data and identify patterns or correlations that may help researchers understand neuroplasticity and intelligence better. This can lead to insights into how the brain changes and adapts in response to learning experiences and environmental factors. Imagine scientists having a machine do the calculations and they interpret the results.
Much like doctors and med schools are doing all over the world, AI-powered virtual reality environments and simulations can create immersive learning experiences. These can engage multiple senses and provide realistic scenarios for learners to interact with, potentially enhancing neuroplasticity and intelligence building through experiential learning. No need to have a cadaver anymore, all you need is an Oculus.
While I do see great potential, I do feel we are quite far from this becoming a reality.
Hi Simon,
I think you are spot on about the potential of neuroscience, especially when it comes to advances in AI, and how we are quite far away from a reality that effectively leverages that potential. During my research, one of the biggest barriers holding neuroscience research back, especially in relation to education and consequently neuroplasticity, was the education field’s haste to find a one-size-fits-all learning strategy that drew upon neuroscience concepts. In their hasty implementations, educational institutions were unprepared for the fact the the field is still very much in its infancy and many theories and practices related to education are still in need of significant refinement. The result was that many institutions implemented unproven theoretical educational practices connected to neuroscience, saw they were incomplete post implementation, and promptly discarded the practice while simultaneously questioning the future of neuroscience as whole.
Long story short, neuroscience has tremendous potential (like you mentioned) but the world needs to be patient and let research continue in order for it to have the greatest impact in the future.
Thanks Neuroscience team,
I attended a conference years ago where Dylan Wiliam was the keynote speaker and he spoke about the gap between neuroscience and education and how rare it was that educators actually understood anything about how the human brain worked and yet were solely responsible for its development. He was blunt in his delivery but the message was important. I think that AI and the neural pathway development piece will really help us understand the brain better.
I find the conversation about AI and bias really interesting. So much is being made of the way that data is collected and analyzed by AI but I find the process strikingly similar to how humans learn, process information and form their own bias. Human bias is typically formed through experience (and often that experience is limited). I think that there needs to be monitoring in regards to what conclusions AI makes about data, but deep learning should allow some recognition of this bias by the AI itself. I think if the AI is informed (if you can say that about a machine) about how the data was collected, who collected it and why it may be biased then it should be practically able to identify this bias and appropriately consider that in any decision making. As it would be making potential decisions without emotion, it should be able to approximately account for potential for bias in those decisions. It seems sometimes hypocritical to me that humans (who are full of various bias from our childhood exposures, media, family, workplace, etc.) are so critical of bias in AI? Although perhaps identifying our own bias and understanding that any data we present AI may have been collected with that bias is why we are worried?
Anyways, I think it is very important to have ethics specialists present at most stages of AI development to ensure the process moves forward in an ethical manner!
Thanks for your informative website.
Fantastic job neuroscience team! I love how dynamic and informative your OER is. It allows me to get a taste of the future of neuroscience applications.
I am also surprised by how little neuroscience is included in teacher education programs and many educators, including me, are not so familiar with how the human brain actually picks up information and acquires new skills. It should be something that we all know to do our job. I had students in the past who suffered from very poor working memory, and I didn’t know how to help the student. I wonder if I had more knowledge in neuroscience, would I be a better support. Seeing the example of memory activities and learning about how activity-dependent plasticity can have significant implications for learning and memory, I do believe that AI would improve neuroplasticity. On one hand, AI could assist researchers and lead to new discoveries, such as to what extent the neuron pathways can be altered, under what conditions, what types of activities would be more effective, etc. On the other hand, AI-based tools can pinpoint individual needs and personalize their brain training process, leading to better results.
Hi Trista,
Complete agree. One would think that educators should have a strong understanding of how our brain operates in relation to how knowledge is acquired, stored, and eventually applied but the reality is that this topic is almost never discussed or explored in Teacher Education programs beyond a surface level analysis. I could see a day where most schools employ a resident neuroscientist to explore student learning habits and help inform instructional practices or at the very least provide more professional development opportunities to assist educators to better understand how their students are processing information.
Many schools currently employ learning specialists to work with students with learning difficulties, counsellors to work on social/emotional difficulties, and data analysts to explore developing patterns and trends in student learning. I would argue employing an expert in understanding how students learn is a position that is desperately needed.
Hi Trish
Thank you for this. I would agree with this in the context of how we learn, the stages and the need for better understanding of neuroscience, and the concept of neuroplasticity. Something that is largely a given without core understanding. There are so many aspects which need R&D which would assist education and teachers at every level of learning development. However, learning has always been a type of quantum leap ie at a certain level and age, we tend towards weaning out and focusing upon decisions re future choices and simultaneously. Assessing and assuming understanding of congnition and concepts under the umbrella of pre-understanding while neuroscience/ learning and development continue along each person’s individual cognitive development.
Having a thoroughly trained competent and EQ endowed professional to assist at such crucial moments would certainly be a great support
Hello Neuroscience team,
Thank you for your website and for sharing some activities that students can try in the classroom. I see many of these as being good activities at the start of a lesson or at the end when teachers have that “fill in” time. I was a bit frustrated by the word game that was offered since the activity required you to choose their four letter word and there was no flexibility in answers. For example, my PALM was incorrect since it wanted LAMP. I think that a Boggle game is amazing for students so that they can expand their language vocabulary. I am consistently surprised in my French class when I hope students recognize English cognates, but they don’t know the corresponding English words (which for most students is their mother tongue). Many of my students comment on how they learn more English in my French class than in their English class…
I am interested in learning more on a philosophical level about how Marketing Neuroscience affects us. For example, why am I such an Apple enthusiast? The marketing of these products has no doubt influenced my subconscious into thinking that I simply would not be able to enjoy a different laptop. Even when I see other phones have the ability to take incredible photos, why am I hellbent on continuing to be an iPhone user? What I mean by philosophy are the questions about one’s self as it is shaped by technology. Spotify is a great example of a technological platform that moulds who I am. How did I get to the musical taste that I am at now? Surely, the recommended albums and AI generated playlists have a strong influence on my likes and dislikes.
How have we as a society become complacent into simply accepting that our phones are listening to us in everyday life and are then taking that information to produce targeted ads? Can you imagine if you were able to time travel to twenty, thirty years ago and to tell people that technology would get to this point but that we would simply accept it since we love technology’s affordances in regards to lifestyle ease?
Maurice
Great forecast! I especially enjoyed how the this team looked at how this field of educational research could affect industry outside of education, such as marketing. I have a tendency to view things in the perspective of how they are useful to my as a teacher, and in the educational market.
This was an interesting week of learning, great work putting together this forecast. I agree with comments above that it definitely built upon previous weeks with wearable and assistive technology. It helped my understanding of the applications of neuroscience to have those topics presented first. I appreciated the diverse and complex topics covered in your forecast.
Neuroscience is an area that I think should be better studied and utilized by teachers. Going through my teaching degree and PD opportunities I have had so far there has been very little information based on this and the complexity behind how students learn and acquire information. As a peer mentioned above, I too have taught students with working memory struggles and have felt lost with how to support them in the classroom. I think in the future we are going to see an increased use of wearable technology and through that hopefully more can be learned about this topic as well.
Hi Kelby,
Being completely honest, I was a teacher for 12 years and only truly heard about neuroscience through a previous MET course last year. This seems crazy to me as, at its core, understanding how and why we learn should be a fundamental concept in education. When I started in education, the big buzzword was differentiation (still is in many institutions) and while current differentiation practices target student learning from a very surface level perspective, I do feel advances in neuroscience research have the ability to grant us a educators a deeper look into the needs of each individual student. I could also see wearables playing a huge role in that regard as well.
Hi Neuroscience Team,
Thanks for a great week of learning. I enjoyed taking part in all of the activities you planned. I have to admit to spending a little too much time playing the brain games you shared with us (Especially when I didn’t do as well as I thought I should and wanted to improve my score). The patterning game brought me back to my childhood playing the game Simon. That was a throwback.
I definitely agree that teachers in training do not receive enough information on neuroscience. It is so applicable day-to-day in our students learning, motivation, and the challenges they face. Understanding neuroplasticity and how providing our students with multiple meaningful experiences around a concept can help strengthen neural pathways is key information that all teachers would find useful. As is recognizing that students build stronger neural pathways when learning is connected back to their own lives and experiences outside of school in multiple ways. There are so many learning challenges we see in our students these days and I have found myself wishing I knew more about neuroscience so I could better support them and their various learning needs. I think there is so much we could share with students about neuroscience and how the mind works that would help them better understand their own learning. I’m curious to see if neuroscience courses will become mandatory in teacher education in the future as we come to see its value.
Thank you for participating in the activities, brain games, and discussion questions prepared by the Neuroscience Opportunities Forecast team this week. I’m glad that the Padlet with stories and experiences has been completed by various educators and me and I could get to know more about teachers around the world. I hope you will have more positive experiences in your life and the activities we have prepared have been useful not only in the 2023 ETEC 522 but also in your educational environments where you belong. Have a great summer!
Thanks Neuroscience team, the brain game is great! Well, I believe that research in neuroscience has the potential to enhance teaching practices by providing educators with valuable insights into the processes of information processing and long-term memory storage. Educators can utilize this knowledge by implementing activities that promote organization, rehearsal, and elaboration of information, facilitating more efficient consolidation of knowledge into long-term memory. Furthermore, understanding critical periods of development, such as language acquisition and motor skill development, can inform the practices of Early Childhood Educators. Additionally, research findings can guide the design of age-appropriate educational activities based on the various developmental stages of learners, encompassing emotional, social, and cognitive aspects.
While a teacher may not require an in-depth understanding of neuroscience, their focus should be on the practical application as they directly work with students. A foundational understanding of core concepts, scientific literacy, and strong critical thinking skills can empower educators to implement evidence-based teaching practices. Given their direct involvement with students, teachers have a valuable opportunity to conduct action research, applying and evaluating the effectiveness of neuroscience findings, thereby bridging the gap between academic research and classroom implementation. It may be beneficial for Teacher’s Colleges to incorporate a basic understanding of neuroscience and developmental psychology into their curriculum, if it is not already included, to further support educators in their teaching practices.
Hi Terrence, I learned about this when I was in teacher education certificate programs, linguistics, and human physiology classes a long time ago. I like how you interpreted this forecast on neuroscience and I’m pleased that you enjoyed my brain games, too.