Welcome to Week 9 of ETEC’s Opportunity Forecast! Devon and I would like to encourage you to explore our OER around the topic of Neuroscience.
Our OER offers a unique look into how the convergence of neuroscience and education are shaping the future of learning and teaching and how AI will play a significant role in both areas in the future.
Visit our OER here: Opportunity Forecast – Neuroscience
Here is how to optimize your experience using our OER:
- Browse through the various topics and activities using the navigation bar at the top as well as the navigation buttons within the OER.
- Within our site make sure to take a look for the following:
- Introduction to neuroscience, education and AI
- Emerging markets in the field
- Future outlooks and opportunities
- After going through our OER go back through and look for the brain icons to complete the following activities:
- Answer at least 1 of the discussion questions. Please share your thoughts directly below in the comment section. Please include both the question and the answer.
- Participate in the padlet activity in the emerging markets section.
Enjoy!
Meagan and Devon
Hi Meagan and Devon – Great OER! This is a fascinating topic that seems to provide a lot of possibilities for future technology design. I must say, the WSJ video regarding AI in the classroom was a little unnerving… Althoguh, I would find it interesting to see the data that comes from this attention measuring device used on my own students.
Are you currently using AI in your educational journey or career? What place do you think it has in education?
While I have yet to bring AI directly into the classroom, I am excited about the idea after having read some of the ideas in this course so far. Up until this point, my main concern with AI is the common issue of “my students will get ChatGPT to do everything for them.” While I think this is an issue worth considering, I believe bringing it into the classroom can be worthwhile. In another course I am taking at the moment, a few colleagues and I are coming up with a toolkit that is designed to ease teachers and their students into using AI effectively. This toolkit will inform the teacher about how they might implement certain AI technologies, as well as how to inform students about the nature and proper use of AI. Coming up with this toolkit is somewhat based on the idea that students, once graduated from school, will be heading into a workforce that is becoming more and more AI focused. Therefore, becoming proficient with the use of AI should be incorporated into their education, promoting success post-graducation.
Hi Nik,
Thanks for your response, this topic was a large undertaking as there were so many places would have gone with it and like you said there are a lot of possibilities for future technology design.
Thanks for the reply to our discussion question, I think you bring up a great point that AI is not going anywhere and it is important that we focus on growing with it. I think there is a learning curve right now on how to properly implement it and have the students to learn to work with it and not just having it do students work for them. I know this was a hot topic at this years teachers convention in my area and it seems to be coming up at every tech and ed conference. The toolkit idea sounds great!
A friend of mine hosted a podcast exploring the impact that artificial intelligence could have on education and the importance of AI literacy for students and teachers alike. It Interesting listen. I linked it below here- https://youtu.be/SRXJ7rMxX0I
Thanks for the comments Nik.
I think we’re going to see a period of turmoil where many people hash out what AI really is and what we should do with it. One aspect of this is that although we’re seeing a lot of attention drawn to large language models and generative AI, the field is a lot broader than that, and many of us have already been using some form of AI/machine learning for quite some time.
For example, the Google algorithm, YouTube/Netflix/Amazon recommendation systems, spelling and grammar checkers, translation software, text extraction from images, photo editing software that can “erase” unwanted elements… Twenty years ago, these would have been seen as spookily effective and true sci-fi. It may be more that we’ve seen these develop slowly over time that they are less surprising; ChatGPT seems to have jumped from research lab to mainstream media really quickly.
I’m out of the classroom this year so haven’t been actively integrating AI, but I can see some potential uses. I teach high school math and science, and something like ChatGPT would be great to give a summary of a complex topic, similar to using Wikipedia as a starting point for research: not a superb source on its own, but to give an overview of a complex topic and ideas for where to go next, sure. Also, I’ve taught in international schools where most students are working in a second language, so using AI to paraphrase a complex article into a simpler version or summary also seems like a useful support function.
In another course, I’m investigating spaced repetition practice, which ties into neuroscience via understanding of memory and learning processes. In that context, the ability to have AI generate unique practice questions tailored to an individuals current progress looks like a promising direction. Quizlet apparently supports this already, although I haven’t dug into the details yet.
Devon
Devon, you’ve really highlighted an important issue: machine learning technologies have been with us for quite some time. When students turn in assignments that seem too polished for their level, I often find they’re not just using ChatGPT, as I had assumed, but also tools like Quillbot, which has been available for years. I know your point is about the larger impact of AI on society in general, but eroing in on one AI tool or model might just obscure the broader impact AI has on education.
As an English teacher, recognizing the role of large language models in teaching is becoming crucial. I used to help students with their 5,000-word essays relying on my own knowledge, but now I consult ChatGPT for pretty much everything. I don’t see the point in drawing a line between teachers, who are allowed to use AI, and students, who supposedly aren’t. I’m not about to limit my own use of AI. I run everything I write through ChatGPT, tweaking the prompts until I get the response I’m looking for. If GPT throws something back that doesn’t fit what I’m aiming for, I’ll let it know. It’s a constant process of fine-tuning. I think students need to get the hang of this, too. But I’m still figuring out when to cut them off from AI, since their exams are hand-written and don’t involve computers.
The penultimate version of this response, after much fine-tuning, started with this sentence: “Devon, you’ve really hit on a key point—that machine learning technologies like Quillbot have been around for a while.” However, after I clarified with my next prompt that “No, Devon’s not talking about Quillbot,” it led me to more or less (I tweaked it a little bit) the version that is currently posted.
Hi Meagan and Devon, thank you very much for this OER. It is very informative, and I like that in addition to information around neuroscience and AI, you provided practical information such as which universities offered neuroeducation programs, and real examples and applications of each neuroeducation category currently available in the market. The question I want to answer is: What are the ethical implications of using AI-powered educational tools that collect and analyze students’ brain data to personalize learning experiences? How can we ensure transparency, fairness, and privacy in the use of such technologies?
The gathering of brain data and using AI in education certainly raises concerns in many areas. Where are the data store? Are students and parents fully aware what is being collected and used? Is the data being use properly? What is the long term impacts on students using AI-powered tools? What are the psychological impacts when using brain data in education? I think ensuring privacy in the use of AI tool on brain data requires strict regulation and control on student and parental consent, who can access the data, and the full understanding of the data being analyzed and its purpose. To ensure transparency, we should encourage all students, educators and parents to understand what is being done with the data, instead of only understanding what kind of data is being collected. My biggest concern with using AI on brain data is how we can ensure fairness. With massive amount of data collected and analyzed, there is a potential risk of algorithmic bias. Depending on the available data collected and the developer’s own bias, certain groups of students may be disadvantaged (or advantaged) based on their demographic characteristics. Developers must taking into account diverse backgrounds of students and their learning styles. Because of all the ethical implications around this area, educators, technology developers, and policymakers should collaborate to establish clear guidelines and regulations.
Thanks for the comments Jennie.
I agree that neuroscience based tools, especially with data collection and AI integration, raise a whole range of ethical issues to be dealt with. We’re seeing a growing awareness of this with respect to information technology already, and this will expand on that. My thinking is that these tools will need to be treated more as medical equipment than regular computer technology, and the standards for transparency, data management and privacy will be on a similar level. Especially considering the data would be collected from/about children and likely by a for profit company, strong safeguards and due diligence will be needed.
You make a good point about algorithmic bias. During the earlier phases of technology development, getting enough diversity for test cases, pilot programs, etc. will be an area of concern. With the need for careful data management, informed consent, legal review, etc., can definitely see a temptation by developers to short cut the time and cost of that and use a smaller, less ideal test group.
Hi Jennie
Thanks for your response.. Your response reminded me of a similar discussion in this course on analytics and early intervention and I think there were the same concerns when it comes to bias as well as the use of this data. It is important like you said to be aware of biases present in the data used for predictive analytics and strive to minimize them. Regularly audit and update algorithms to ensure fairness, especially regarding factors like race, gender, socioeconomic status, and special education status. Consider using diverse datasets to train models. The first step is being aware that these things can exist and then move to strategies to help mitigate these issues.
Hi Meagan and Devon,
Thank you for your OER this week. You presented a lot of diverse information and offered many different examples and aspects of neuroscience in education. I came across an interesting read regarding AI and neuroeducation. It is my understanding that a lot of the brainwave data collected by EEGs is really noisy, meaning the desirable signal intended to interface with some object or artifact is highly colored and skewed with noise from other thoughts, and ultimately by the surrounding electromagnetic fields. So, EEG tech doesn’t seem to work that well when there is a lot of WIFI or electrical devices in the same area. One aspect of how AI is being used is in developing new algorithms that are showing to be capable of actually processing the EEG data to extract the meaningful signal from all of the noise. I thought that was an interesting point about AI and neuro-data that I didn’t catch in the OER. There is one device that was also touted to be able to produce text on a screen from reading EEG data from the wearer’s thoughts, which is crazy to think about. Computers might actually soon be able to read our minds. Obviously, there are huge implications for this around privacy, but also for the advancement of assistive technologies.
Further, there is also a website that serves as a sort of repository for neuroscience information. Literature on neuroscience is used to train a large AI language model in hopes that it will be better able to assimilate a lot of complex and vast information. As you showed in your OER, the literature base on neuroscience is expanding rapidly. I think AI will be a huge advantage in being able to identify connections across such a technical subject and will prove to advance our understanding further. This project is called BrainGPT (https://braingpt.org/). Coincidentally, so is the tech that is supposed to be able to read our thoughts to produce text on screen.
From your research, I’m wondering what you think the most lucrative and emerging markets are, specifically in Canada, or North America, and in an educational context? It’s hard to put my finger on it, and while there is a lot of research, I’m wondering who the market leaders are and what it is they are offering? Is it a device with software? Just a device? Is it embedded theory like Duolingo or Prodigy? Are those games really created on a foundation of neuroscience, or is it a complex combination of psychology, behaviorism, constructivism, etc., along with neuroscientific understandings? Or, does neuroscience simply offer more concrete scientific evidence to explain why such things are effective for learning?
Really, I think there is a lot to be discovered from neuroscience, and I think you both did a great job at presenting that. Clearly, there is still a lot about it that we don’t know which presumably may be indicative of the fact that there is opportunity there.
Thanks!
Thank you for sharing Braingpt – I have bookmarked it. Seems like an awesome starting place for researchers to explore a focus or pathway.
“Are those games really created on a foundation of neuroscience, or is it a complex combination of psychology, behaviorism, constructivism, etc., along with neuroscientific understandings? Or, does neuroscience simply offer more concrete scientific evidence to explain why such things are effective for learning?”
I love this question, it sent me on a journey of articles and evoked some critical thinking about my A1. Advancements in brain mapping due to abilities to process large data faster will really allow neuroscience to help explain long developed psychological theories. I came across this quote from Dr. Kristen Lindquist, a professor at UNC, “The brain creates the mind, so understanding how this happens shines new light on our psychological theories and interventions, in turn, understanding psychological theory and measurement of behavior means we can understand the functional meaning of firing neurons and blood flow to brain regions.”. To address your question, I am curious to see how new neuroscience developments continue to contribute to the science of reading (a body of work). I did my A1 on adaptive reading technologies based on the science of reading and am hopeful they can be more specific and attentive to potential new neurological understandings of how the brain learns to read.
(https://hms.harvard.edu/news/new-field-neuroscience-aims-map-connections-brain)
(https://www.apa.org/monitor/2022/01/special-frontiers-neuroscience)
Thanks for your comments Andrew.
I’ve never really thought about the science of reading as a specific focus before, sounds interesting. An initial thought I have from the research I did for this OER is to use the ability to monitor attention and focus to better understand how people read, and when/how they get distracted and lose focus. This might just be for research but potentially with some sort of feedback; I think many people have the experience of reading a paragraph but tuning out and not absorbing anything, so I could imagine device that could observe this and then actively suggest a break or other way to refocus.
If you want to get more extreme, it might be possible to create new ways to interface with text. Writing developed from limitations of the physical medium used; ink and paper are very convenient for recording but may not be the optimal way to read. There are things like https://www.spreeder.com/ that present words sequentially, supposedly allowing faster reading than presenting text conventionally. Something like this, that could adjust how text is given to a user, depending on their mental state (focus, comprehension, emotions)? Not sure if it would work (or justify the trouble) but an interesting research project for someone.
Thanks for your comments Bradley.
I’m far from an expert, but my understanding of EEG data is similar to yours: very messy data, on processes that are complex and not exactly well understood anyways. The use of AI to extract meaningful data is almost essential, especially in trying to keep to a small number of non-invasive sensors (i.e. not requiring holes in head). There actually is some of this discussed in the OER under the brain computer interface section of the Emerging Markets page. I didn’t go into huge detail as there was so much we wanted to cover; any one of the subsections is a book worthy topic already. The Galea device is an interesting take on the problem, as they use other biometric data (eye movement, heart rate, etc.) to supplement the EEG signals.
As to your question on lucrative markets, I think there will be two potential paths. One option is to develop specialist devices for therapeutic situations. This is a niche market, but the potential for significant quality of life improvements would make justify the expense, especially when combined with government or private medical insurance. Long development timeline needed, but whatever companies pursue this would likely gain some really useful knowledge that could be patented, spun off into other products, etc. High risk, high reward.
The other opportunity is wide spread development of apps. As you mentioned, things like prodigy or duolingo. Low barriers to entry but also lower cost to develop and scale to a large audience. If one can take knowledge from neuroscience and find a way to make a useful app from it, powerful market there.
Hi Meagan and Devon!
Thank you for your OER. I don’t know much about neuroscience, so your OER has provided me a brief overview of the different topics within the discipline.
I chose to answer this discussion question: How do you think traditional education methods are adapting to the demands of a rapidly changing technological landscape?
I think this is primarily seen in instructional design. Instructional designers help craft experiences so that learners can easily retain information. Usually, not a lot of people know that this field within education exists. The predominant view of education is still very much the traditional school system. I can see that there’s a push with translating traditional in-class materials to be communicated in e-learning modules.
Dissemination of information has totally changed with the internet. To bridge the technological skills needed to assess information online, some school systems have also started integrating media literacy. For example, Finland has woven media courses into its curriculums so that children have the tools to evaluate the accuracy of the information they see. They are not just teaching the subject matter but they’re also teaching the analytical skills. For example, they’re teaching children how reporting can be different depending on ideologies of news outlets. Critical thinking is needed as we’re constantly exposed to vast amounts of information on the internet.
Since we’re talking about neuroscience I wonder if you’ve encountered the importance of executive functioning (mental processes that allow us to plan, focus attention, remember instructions, and juggle multiple tasks successfully) in your research. I wonder how the wider role of technology in children’s lives affect the development of their executive functioning skills. I wonder how the school curriculums foster the development of these skills. Not only do these skills play a factor in academic performance in school but also when the children eventually become adults, they need these skills to carry out their jobs.
Hi Meagan and Devon,
Thank you for this OER! I enjoyed going through the Landscape of Neuroscience and Education page as it gave me a better idea of what is out there.
I would like to answer the question: Are there some things you are concerned with when it comes to AI being used in education?
I will admit that I am still new to AI but from what I have seen kind of scares me. I’ll touch on the point that scares me first and that is the ability to create something out of nothing. When my colleague and I tried ChatGPT for the first time, I was amazed at what it could do. For example, we asked ChatGPT to create an itinerary for a Hawaii trip for seven days. The fact that it was able to create an itinerary faster than I could was a bit freaky. However, as I’ve played with ChatGPT, I’ve got to understand it a little more and turn my fear into a strength. Now, the concern I have is mostly with being an educator. I wonder when the day will come when a student hands in something that I know isn’t something they created. I’m sure this is not the first and I know for post-secondary, there are scrubbers and filters that go through papers to ensure that it was genuinely made by the student, rather than AI, but at the secondary level, I have heard of a class in my school that used ChatGPT to do their assignment. Although the teacher caught it, it was still a concern that students will use it for their own negative personal gain. However, I am sure that instead of fighting a tool that can be useful, we can educate our students on understanding those concerns and build that trust to use AI for a good purpose and cause.
Thanks for the OER!
Jeremiah
Hi Jeremiah
Thanks for the reply. I think there is a lot of things to still learn when it comes to AI and I think we have a role to play in the education and proper use of of AI within education and with our students. Educating ourselves I think is one important step and then having students use it as another tool to help free up our cognitive space for other more meaningful tasks could be a beneficial approach to using AI.
I myself have been trying to learn as much as I can on AI and have gone through a couple free courses that some large companies and schools have created. Learning more about it and using it myself in my job has helped me to turn my hesitation into strength as well. I have linked of few of the courses below if anyone wants to take a look.
Google AI courses https://www.cloudskillsboost.google/paths/118
Microsoft AI Course https://microsoft.github.io/AI-For-Beginners/
Hi Meagan & Devon,
Thank you so much for your OER. Very eye opening. You listed many things here that I was not aware of. Neuroscience is such a specific market and one that needs to be handled very delicately. I can honestly say that you’ve done a wonderful job with this. I found all of your content very informative. I particularly enjoyed where you discussed gaming. I mentioned quite a bit in your padlet, as I believe that gaming is something that should be incorporated more into our educational infrastructure.
In what ways do you believe traditional education falls short in preparing students for the challenges they’ll face in the modern world?
In short, our curriculums need to be updated. Technology is evolving so quickly, and we are simply not preparing students for a world where tech knowledge is so vital. There needs to be a much stronger focus on technology education, and there absolutely needs to be further funding for more tech in schools. I teach in a school where my admins are trying to aim for a paperless environment. Due to a near-total lack of accessible technology, this is simply not possible. Also, it bothers me that we are moving into a place where technology is being BANNED from classrooms, Not only does this inhibit the proper education of the technology that students will use on a daily basis as adults, but it turns technology into something that is forbidden, making it almost more coveted for potentially negative purposes. We need to find ways to integrate technology education into our curriculum, not eliminate it. Teachers need to find new ways of incorporating it, and admins and school districts need to realize the importance of this education to allow our students to be able to function in a rapidly evolving world.
Again, thank you so much for your OER., Very insightful!
Thank you for checking out our OER and responding to our padlet and discussion questions. It was interesting to take a look at games in connection with neuroscience because I think there is so much to growth opportunity in this area. I would say one of the biggest barriers to this as well as education and neuroscience in general is that there is still a large gap between scientists and educators so work still needs to be done to continue to bring these fields together. As these groups continue to understand the work that each is doing I think it will help bring the two areas together.
I think you bring up some great points about traditional education and moving forward. It is hard when there is such a resistance to change and the inevitable. By banning and no incorporating technology into education you are not preparing students and in fact are doing them a disservice as they move forward. I think it extends beyond just technology as well we need to look at what and how we are teaching students. The fact that we need to prepare students for jobs that don’t exist yet is a big task. We need to look at the skills needed to live in the modern world and incorporate those into our teaching.
2. What are the ethical implications of using AI-powered educational tools that collect and analyze students’ brain data to personalize learning experiences? How can we ensure transparency, fairness, and privacy in the use of such technologies?
Personalized data analysis can be used to maximize learning, but it can also be used in a way that promotes biases and fails to consider human differences. Without implementing a control over these systems, AI systems can limit some opportunities that some students have. There is always a need for human oversight on these programs. I know within the Canadian government, AI systems that are used for administrative processes like these are currently not allowed to be used.
https://www.canada.ca/en/government/system/digital-government/digital-government-innovations/responsible-use-ai/guide-use-generative-ai.html#toc-6
3. Are there some things you are concerned with when it comes to AI being used in education?
Aside from the biases I mentioned earlier, I think that AI is expensive. While it can be an amazing tool for learning, if the amount of time, energy, and resources is not put into its implementation, you can potentially be using AI that does not maximize learning. New technologies, if not properly planned for, can actually be a detriment to learning and make learning inaccessible.
Hello Devon and Meagan,
I really enjoyed your OER on Neuroscience! I can honestly say that I’d rather learn about neuroscience and how it can increase the motivation needed for students to succeed in education than to read about it from some other online source. I like how you divided up your information and made it easy to navigate and use. I especially enjoyed the TEDtalk that discussed the basic knowledge of neuroscience in education and how everyone should at least have those fundamental thoughts regarding these ideas. Ponnet suggests that intrinsic motivational methods will be the ticket to successful learning experiences in the classroom. Really stimulating the mind and making things more important for students is where I want to be as an educator as well. Her activity that she shared to think about something that simply made you happy is such a true and valid example on what impacts us as human beings. That association memory is critical for learning to take place. Our most formidable memories and things that make us happy or motivated probably didn’t happen in a classroom. It probably happened on a hike, in a lake, or some sort of adventure with friends. These experiences are needed to be brought into our classrooms in order to make those mindful connections. Such a great thing to be reminded about, so thank you.
I looked at this questions:
How do you think traditional education methods are adapting to the demands of a rapidly changing technological landscape?
I am a big believer in a blended learning approach. Yes, it’s definitely important for educational practices to continue to share traditional styles of the past. These styles and approaches still have the ability to teach and create an impact on learners. However, just as important, is to adapt to the technological landscape of today’s generation of learners. The classroom should be a place where students can be introduced to a variety of learning experiences in an effort to create a balanced well rounded student. For me, personally, it was Covid19 that brought an accelerated change to my classroom. I feel that when I was literally forced to create alternative ways to deliver lessons then I jumped in the deep end and created content that I didn’t even know I could create. I had to figure out how to reach students in a digital world and it was fairly successful. However, when teachers get comfortable in their approach and things aren’t needing updates or changes, I don’t think we have enough time to make those changes. It’s a very demanding job that takes time to find the perfect storm. As Ponnet explains in the video, however, recent research in neuroscience suggests that, “our emotions are contagious and our brains are social organs.” We need to remember that although we can have the latest technology or even have planned the most successful lessons from years past, connection is everything. Meeting the needs of this quickly changing landscape in education is crucial, but so is the basic need of passion, drive, stimulation, experience and love for. learning.
A really great job that got me thinking quite a bit. Thanks very much!
Carlo
Hi Carlo
Thanks for going through our OER ad responding to our questions. The question you answered has been answered by a few and it has been interesting to see the differences in responses and how each of you has interpreted this question. I think you have focused in on something very important that has to be considered in all types of education in order for it to be successful and that is connection. I have done previous assignments in different classes focused on all types of learning and the research supports connection in every different method. Having students feel safe, supported and seen has positive impacts on learning and engagement. Regardless of the types of technology and changes we see in education this should be at the forefront.
Do you think connection will become harder or easier with AI technology?
Meagan
Thanks for sharing this response Carlo, I had some similar thoughts. I was reading everyone’s response to these questions about education’s speed of adaptation/innovation and instead of creating my own post I will contribute to the conversation here.
Public education will look and feel as if it is playing catchup to the innovations made by private institutions for many reasons, but especially due to bottlenecks in purchasing of technologies and guidance on implementation. For example, in my large Ontario public school board, we still don’t have officially published guidance on AI use in the classroom. I believe that, firstly, it is important for educators (and those in influential positions) to maintain positive pressure on the systems to adapt as fast as possible. Second, we should look for other ways to continue to evolve education apart from technology integration alone.
An impactful report is UNESCO’s 2023 report: “Global education monitoring report, 2023: technology in education: a tool on whose terms?”. The report addresses the role of the education technology market in the perception of education’s adoption of tech, saying:
“Exaggerated claims about technology go hand in hand with exaggerated estimates of its global market size….Education is criticized as being slow to change, stuck in the past and a laggard when it comes to innovation. Such coverage plays on users’ fascination with novelty but also their fear of being left behind.” (https://gem-report-2023.unesco.org/technology-in-education/).
I am bullish on technology use in the classroom, albeit an emphasis on thoughtful integration of technology in education. The report also points to three challenges in this area similar to what I mentioned above: equity of technology and content access, governance and regulation, and sufficient teacher education and capacity. There are implications for adopting technology without careful planning. Several studies showing only small-to-medium positive effects of technology use on learning outcomes compared to traditional teaching methods (UNESCO, p72). So the changes are POSITIVE, but perhaps the education community exaggerates how bad the situation is? We are not failing our students yet. In fact, trying to overcompensate without the thoughtful adoption of technology and teaching strategies can be detrimental. UNESCO’s report found that:
“by categorizing ICT usage at home and in school as low, medium or high, more intensive use beyond a threshold was most often found to be correlated with diminishing academic performance while moderate usage was most often associated with positive academic outcomes.” (UNESCO, p107).
To tie this back to our topic, the exploration of the benefits of neuroscience towards meaningful technology integration are important. This includes understanding learning processes, development of cognitive-based adaptive learning technologies, and potentially student-centered neurofeedback targeting attention and focus.
UNESCO. Global Education Monitoring Report. UNESCO Publishing, 26 July 2023, unesdoc.unesco.org/ark:/48223/pf0000385723. Accessed 10 Mar. 2024.
Hello Devon and Meagan,
What a fascinating topic. Thank you for sharing your work on neuroscience and education this week. I agree with Ponnet (2019) that basic knowledge of how the brain works should be involved in teacher-training programs. In her TedTalk, Ponnet (2019) said it simply that neuroscience is common sense in education. I understand how neuroscience and education are connected. However, I haven’t understood the relevance of AI until your Opportunity Forecast.
The brain-monitoring devices shared by the WSJ (2019), got me thinking about the following question: What are the ethical implications of using AI-powered educational tools that collect and analyze students’ brain data to personalize learning experiences? How can we ensure transparency, fairness, and privacy in the use of such technologies? I see several ethical concerns arising, with privacy issues being an obvious one. The privacy of the brain-monitoring devices used in China is unknown at this time (WSJ, 2019). Surprisingly, parents of these Chinese students are not overly concerned. Another ethical concern is that the information from these devices is taken seriously even though it’s unclear how effective these devices are. WSJ (2019) points out that their sensitivity may offer inaccurate information. And finally, the fear and pressures these devices place on children brings forward yet another ethical concern. Simply wearing the band puts pressure on students to pay attention. The fear of disappointing their parents seems to be the driving force of the motivation for these students. A learning environment should feel safe, as Ponnet (2019) points out, and this fear creates a space for students that is far from safe.
Emma
REFERENCES:
Ponnet, V. (2019, Nov 11). Using insights of neuroscience to improve teaching and learning. [Video]. YouTube. https://www.youtube.com/watch?v=NmAuawoYnUk
The Wall Street Journal. (2019, Oct 1). How China is using artificial intelligence in classrooms. [Video]. YouTube. https://www.youtube.com/watch?v=JMLsHI8aV0g
Hi Megan and Devon
This was a generous informative OER. The topic is very important and useful.
The discussion question: Are there some things you are concerned with when it comes to AI being used in education?
-One concern is privacy. The AI softwares collects our personal information and some patterns of student learning.
-A big problem with using AI in education is that it can make learning less personal. If AI algorithms create content and control lesson speed, students might miss out on the special guidance human teachers offer.
-Another issue is that students might not use AI in education in an ethical manner. There will be doubt about the integrity of their work.
These are 3 concerns that I could come up with but there are definitely more.
https://www.classpoint.io/blog/the-pros-and-cons-of-ai-in-education
Thanks Megan and Devon – I truly enjoyed your creation, and found it very educational.
Are there some things you are concerned with when it comes to AI being used in education?
What are the ethical implications of using AI-powered educational tools that collect and analyze students’ brain data to personalize learning experiences? How can we ensure transparency, fairness, and privacy in the use of such technologies?
These are such big questions, and enormously important to ask in the field of education and beyond. I think that they are closely tied together, so I’ve grouped them here. I share some concerns with previous posters, including Noor just above. Privacy, ethics, the temptation, and the ability to represent AI creation as your own – these are certainly concerns in using AI in education.
The ethics of using any tool that collects my students’ data weighs on me. I do believe that it is sometimes worth it, and will use technology that collects data if the benefit is notable. But as for transparency, fairness, and privacy in using the technology – we desperately need a government that is functioning efficiently and for the good of the citizens that will pass legislation and set standards that protect us. As much as I am cautious, and I’m cautious on behalf of my students, I believe that it is at the government and corporate level that true safety decisions must be made.
Thank you Megan and Devon,
This OER was very well done, a pleasure to read through this topic and included some great videos. Thank you.
I’d like to give my input on this question:
How can insights from cognitive neuroscience inform the design of AI-driven educational technologies to better align with the natural processes of learning and memory?
From the research presented in your OER, it reinforces what most educators intrinsically know to be true, that emotional stimulation cements learning and memories and that positive emotion opens the mind to learning. That is not to say that it is the only way to learn, certainly not, but there does seem to be evidence that it helps. When designing AI-driven education technologies, this can be a foundational question to return to. Is the student positively and emotionally engaged in using the AI learning tool? If yes, it may have a more impactful learning experience.
Hello Megan and Devon,
This was such an interesting and well designed and well informed website! Thank you for teaching us all about this fascinating topic.
The discussion question I chose to answer is this: How do you think traditional education methods are adapting to the demands of a rapidly changing technological landscape?
I believe that education is one field where adaptation is unecessarily slow and restrained. It is due to many reasons from funding to fear of technology and fear of the unknown. I believe we are not helping our students by having analog classrooms in a technological world. Or where we just take paper-based teaching and use technology to teach it. I believe we are not using technology to its advantage and the few cases where it is being used effectively, the results are astounding! There are individual cases where technology is at the core of education and I hope that this slowly becomes the norm.
I also believe that technology needs to be thought of as a moral development program as well. We need to teach children what goes into building technology but also connecting them together in new ways that technology allows. It can be a very isolating and individual conversation with regards to technology implementation so steps need to be taken to minimize this possible issue.
Hey Meagan and Devon,
Thanks for the comprehensive resource. It seems like there is a lot of potential here and also a lot of risk. I’d like to address the question: How can insights from cognitive neuroscience inform the design of AI-driven educational technologies to better align with the natural processes of learning and memory?
I believe understanding how the brain forms associations and schemas can guide AI in presenting information meaningfully, allowing students to link new knowledge with existing mental models. Additionally, insights from reward-based learning in neuroscience can be leveraged by AI to create engaging and motivating educational experiences. These principles are certainly good for any type of learning, which of course includes learning from an AI teaching tool. However, I think it’s possible AI will find new ways to assist people in creating mental schemas and providing reward systems within learning, and then us humans will be learning new teaching techniques from AI!