The AI Education Revolution is Coming – or is it? | Dr. Philippa Hardman | TEDxSantaBarbaraSalon
Summary
TLDRDieses Video-Skript präsentiert einen Einblick in die Welt der Bildungstechnologie (EdTech) und reflektiert über die Anwendung von künstlicher Intelligenz (KI) im Bildungssektor. Der Sprecher, Phil, ein Affiliated Scholar an der Universität Cambridge und EdTech-Gründer, diskutiert die historischen Bemühungen um das Finden der optimalen Lernbedingungen, wie sie von Benjamin Bloom 1984 beschrieben wurden, und kritisiert, dass EdTech häufig dazu dient, bestehende, ineffiziente Lehrmethoden zu verstärken, statt sie zu innovieren. Er betont die Notwendigkeit, KI nicht nur als Werkzeug zur Automatisierung, sondern als Katalysator für pädagogische Veränderung zu nutzen, um jedem Lernenden die gleichen Chancen zu bieten. Er ermutigt zu einer aktiven Akzeptanz von AI in der Bildung und zur Schaffung von Lernumgebungen, die individuell, interaktiv und von KI unterstützt sind.
Takeaways
- 🎓 Der Sprecher ist Phil, ein Affiliated Scholar an der Universität Cambridge, mit einem Hauptinteresse an EdTech und als Learning Scientist tätig.
- 🔍 Learning Science ist eine weitgehend unbekannte Disziplin, die über 30 Jahre Forschung über das menschliche Lernen umfasst, die jedoch oft nicht in die Praxis umgesetzt wird.
- 🏛️ Forschungsergebnisse in der Bildung bleiben oft hinter Paywalls und Ivory Towers eingeschlossen, was eine Diskrepanz zwischen Theorie und Praxis im Lerndesign verursacht.
- 🔑 Phils Arbeit zielt darauf ab, Technologien zu entwickeln, die diese Barrieren überwinden und jedem das Design von Lernereignissen ermöglichen, wie es ein Weltprofessor oder Learning Scientist tun würde.
- 📚 Die Geschichte von Benjamin Bloom aus dem Jahr 1984 zeigt, dass das optimale Lernumfeld für Menschen durch Aktivität, Projekte und individuellen Coaching stark verbessert werden kann.
- 👨🏫 Blooms Forschung betonte die Bedeutung von Problemorientiertem, aktivem Lernen und individueller Unterstützung für alle Lernenden, insbesondere für unterrepräsentierte Gruppen.
- 🛠️ Obwohl EdTech bereits seit 30-40 Jahren existiert, wurde sie bisher hauptsächlich verwendet, um das bestehende, ineffiziente Wissentransfersystem zu stärken, anstatt es zu innovieren.
- 🤖 Die Anwendung von KI in der Bildung hat in den letzten 60 Jahren und besonders in den letzten sechs Monaten dazu geführt, dass der Wissensträger-Prozess beschleunigt und automatisiert wird, anstatt pädagogische Innovationen zu fördern.
- 🚧 Der größte Risiko der KI in der Bildung ist, dass sie uns ineffiziente Praktiken effizienter macht, was von einigen Experten als Problematik erkannt wurde.
- 📚 Phil diskutiert, dass Technologien wie die Druckpresse ursprünglich verwendet wurden, um bestehende Systeme und Machtstrukturen zu stärken, anstatt sie zu innovieren.
- 🚀 Phil ist motiviert, darüber nachzudenken, wie wir Technologie besser nutzen können, um das Lernen zu optimieren und jedem Lernenden die gleichen Chancen zu geben, unabhängig von ihrem sozialen Status.
- 🤝 Die Diskussion um die Verwendung von AI in der Bildung ist aufgeladen, und Phil fragt, ob wir die Technologie nutzen werden, um die Vision von Bloom zu erfüllen und echte Veränderungen im Lernen zu bewirken.
Q & A
Was ist der Hauptantrieb hinter Phils Arbeit in der EdTech-Branche?
-Phils Hauptantrieb ist die Überwindung der Lücke zwischen der Theorie des menschlichen Lernens und der Praxis der Gestaltung von Lernerlebnissen. Er möchte Technologien schaffen, die dabei helfen, diese Lücke zu überbrücken.
Was ist die Bedeutung von Benjamin Blooms Forschung aus dem Jahr 1984 für Phils Arbeit?
-Benjamin Blooms Forschung über die optimalen Lernbedingungen für Menschen hat Phil beeinflusst und inspiriert, da sie zeigte, dass ein aktives, problemorientiertes und individuells Lernen bessere Lernergebnisse erzielt als das traditionelle 'Sage auf der Bühne' Modell.
Wie bezeichnet Phil die Gruppe von Menschen, die versuchen, Generative AI in der Bildung zu vermeiden?
-Phil bezeichnet diese Gruppe als 'Team Avoid', die aus Angst vor der Nutzung von AI in der Bildung auf traditionelle Lernmethoden zurückgreifen.
Was ist das Ziel von 'Team Bennett' in Bezug auf Generative AI?
-Das Ziel von 'Team Bennett' ist es, die Verwendung von Generative AI in der Bildung zu erkennen und als Plagiat zu bekämpfen, indem sie Tools verwenden, um solche Verstöße zu erkennen.
Welche Rolle spielt die persönliche Unterstützung in Blooms Forschung?
-In Blooms Forschung spielt die persönliche Unterstützung, wie z.B. ein-zu-eins Koaching, eine wichtige Rolle, da sie die Lernleistung aller, insbesondere aber von benachteiligten Gruppen, verbessert.
Wie beurteilt Phil die Verwendung von AI in der Bildung der letzten 60 Jahre?
-Phil sieht, dass AI in der Bildung der letzten 60 Jahre hauptsächlich dazu verwendet wurde, den alten, ineffizienten Wissenstransfer-Prozess zu beschleunigen und zu automatisieren, anstatt pädagogische Innovationen zu fördern.
Was ist Phils Meinung über die Verwendung von AI in der Bildung der Zukunft?
-Phil ist der Meinung, dass AI vollkommen in der Lage ist, die Bildung zu revolutionieren und die Vision von Bloom zu erfüllen, aber die entscheidende Frage ist, ob wir es zulassen werden.
Welche Rolle spielt die Khan Academy in der Integration von AI in den Lernprozess?
-Die Khan Academy hat AI in den Lernprozess integriert, um interaktive, auf Fragen basierende und personalisierte Lernerlebnisse für Schüler zu bieten, was Phil als Beispiel für positive AI-Nutzung in der Bildung ansieht.
Was ist Phils Meinung über die Diskussion zwischen Bildungstechnologie und Bildungspraxis?
-Phil glaubt, dass es notwendig ist, die Diskussion zwischen Bildungstechnologie und Bildungspraxis zu verstärken, um Technologien besser für pädagogische Innovationen einzusetzen.
Wie bezeichnet Phil die Gruppe, die Generative AI in der Bildung akzeptiert und nutzt?
-Phil bezeichnet diese Gruppe als 'Team Embrace', die die Verwendung von Generative AI in der Bildung anerkennt und in den Unterricht integriert, um Lehrer und Schüler zu unterstützen.
Welche Bedeutung hat die Erkenntnis, dass perfekte AI-Erkennung unmöglich ist, für 'Team Bennett'?
-Die Erkenntnis, dass perfekte AI-Erkennung unmöglich ist, zeigt 'Team Bennett', dass das Jagen nach Plagiat durch AI nicht nachhaltig ist und dass es notwendig ist, andere Ansätze zu suchen, um mit AI umzugehen.
Outlines
🎓 Die Rolle des Lernwissenschaftlers in der EdTech-Branche
Der erste Absatz stellt Phil vor, der als Affiliated Scholar an der Universität Cambridge und als Lernwissenschaftler tätig ist. Er betont das Versteckspiel der Lernforschung hinter Paywalls und Ivory Towers und die fehlende Intersektion zwischen dieser Theorie und der Praxis der Lerndesigns. Phils Motivation ist es, Technologien zu entwickeln, die diese Barrieren abbauen und jedem die Möglichkeit geben, Lernexperiences zu gestalten, als würden sie von einem Weltprofessor oder Lernwissenschaftler. Zudem erinnert er an die bedeutenden Erkenntnisse von Benjamin Bloom aus dem Jahr 1984 über die optimalen Lernbedingungen für Menschen und kritisiert, dass diese Erkenntnisse bisher nicht in der Praxis umgesetzt wurden.
🤖 AI in der Bildung: Innovation oder Automatisierung?
In diesem Absatz werden die langjährigen Bemühungen der Bildungstechnologie, die traditionelle Lehrmethoden zu stärken, anstatt neue, effektivere Ansätze einzuführen, kritisiert. Phil zeigt auf, wie AI-Technologien in der Bildung bisher dazu verwendet wurden, den ineffizienten Wissenstransfer-Prozess zu beschleunigen und zu automatisieren, anstatt pädagogische Innovationen zu fördern. Er zitiert Daniel Schwartz, der die Hauptgefahr der AI in der Bildung darin sieht, dass sie uns effizienter in ineffektive Praktiken macht. Phil betont die Notwendigkeit, über die tatsächliche Verwendung von AI nachzudenken und fragt, ob wir die Technologie nutzen werden, um die Vision von Bloom umzusetzen, oder ob wir stattdessen auf der Verstärkung bestehender Systeme bestehen.
🔍 Die drei Lager in der Reaktion auf generative AI in der Bildung
Der dritte Absatz beschreibt die verschiedenen Reaktionen der Bildungswelt auf die Herausforderungen, die mit generativer KI einhergehen. Es werden drei Lager identifiziert: Team Avoid, das auf die Vermeidung von AI in der Bildung setzt; Team Bennett, das sich auf die Erkennung und Verhinderung von AI-Plagiat konzentriert; und das aufkommende Team Embrace, das die Integration von AI in den Unterricht anstrebt. Phil diskutiert die Schwierigkeiten und das Potenzial dieser Ansätze und betont die Bedeutung der kritischen Reflexion über die Rolle von AI in der Bildung.
🚀 Die Zukunft der Bildung mit AI: Akzeptanz und Anwendung
In diesem letzten Absatz geht Phil auf die zunehmende Akzeptanz von AI in der Bildung ein und hebt die Bedeutung hervor, die Pädagogen dabei spielen, um Schüler über die Verwendung und die Grenzen von AI zu erziehen. Er erwähnt Studien, die zeigen, wie AI die Effizienz von Menschen erheblich steigern kann, und betont, dass die Zukunft der Bildung wahrscheinlich von AI geprägt sein wird. Phil appelliert an die Bildungssektoren, die Chancen von AI zu nutzen, um die Lernprozesse zu personalisieren und zu optimieren, und nicht nur auf die Verstärkung bestehender Praktiken zu bestehen.
Mindmap
Keywords
💡Edtech
💡Lernwissenschaft
💡Bloom
💡AI in Bildung
💡Aktives Lernen
💡Personalisiertes Lernen
💡Adaptives Lernen
💡Ivory Tower
💡Chat GPT
💡Team Embrace
Highlights
Phil introduces himself as an Affiliated Scholar at Cambridge University and a learning scientist with a focus on edtech.
Learning science has over 30 years of research but remains largely inaccessible due to paywalls and lack of integration with learning design.
Phil's work is driven by the desire to bridge the gap between learning theory and the design of learning experiences.
Bloom's 1984 research on optimal conditions for human learning emphasized the importance of active learning over traditional teaching methods.
Bloom found that problem-based, active learning significantly improves outcomes, especially for non-traditional learners.
Despite Bloom's findings, educational technology has been used to reinforce traditional teaching rather than innovate learning practices.
AI in education has been around for 60 years but has been used to automate and accelerate ineffective teaching methods.
Phil argues that AI has the potential to disrupt education but questions whether we will allow it to fulfill its promise.
The rise of generative AI has led to three camps: Team Avoid, Team Bennett, and Team Embrace, each with different responses to AI in education.
Team Embrace seeks to integrate AI into the classroom, recognizing its potential to enhance learning efficiency.
Sal Khan's integration of AI at Khan Academy exemplifies innovative use of AI for personalized and adaptive learning.
Microsoft's Reading Coach is another example of AI being used to support personalized learning in the classroom.
Phil emphasizes the need for discourse between education and technology to innovate pedagogy rather than just delivery.
AI detection tools for plagiarism are biased and not foolproof, leading to a cat-and-mouse game between institutions and students.
The future of education is likely to be AI-powered, necessitating a shift in educator roles to guide students on AI usage and its limitations.
Phil's concept of 'three teams' illustrates the varying reactions to AI in education and the evolving landscape of edtech.
The study showing a 35% increase in human efficiency with AI use highlights the potential transformative impact of AI on productivity.
Transcripts
hi Mark and hi everyone like thanks so
much for inviting me I'm very excited to
be here so yeah I'm Phil
um as you say I'm an Affiliated scholar
at Cambridge University uh but most of
all I am a uh someone who's been very
interested in edtech for an awfully long
time now as you as you mentioned I am
incredibly old
um I am like my official title is
learning scientist if that means nothing
to you then you can be absolutely
forgiven uh because learning science is
really one of the world's best kept
secrets
um we have now over 30 years of research
into how humans learn
um and yet that research remains locked
behind Ivory Towers behind paywalls and
for lots of very interesting reasons
that perhaps we will get into tonight
um but that I love to talk about
um there is a lack of intersection
between that theory and the way that we
design learning experiences and so
that's really what is driving my work
and as you say I am both a researcher
and an educator myself
um but also an edtech founder looking to
kind of explore how we can build
technologies that somehow help to break
down those those barriers and that lack
of intersection and make it easier for
anybody to design a learning experience
like like the world's best Professor or
learning scientist
um and if I may I just like to tell a
short story at the beginning
um take everybody back to 1984. uh I was
about four years old everyone else was
probably not born yet because as I say
I'm very old uh but yeah educational
psychologist uh Benjamin Bloom at this
point in time was doing had been
researching for around about two years
uh this really interesting research
question which I've since picked up uh
which is which was what is the optimal
conditions for human learning
uh Bloom kind of observed that through a
combination of precedent uh tradition
practicality we have inherited a system
of teaching and learning which I'm sure
is all very like familiar to all of us
which is all about uh a sage on the
stage
uh the teacher is the conveyor of
information
the student is the person who absorbs
the information and regurgitates it and
or perhaps uh restructures it reframes
it but that is the fundamental basis of
The Learning Experience what Bloom found
and got very excited about was actually
that the optimal learning experience for
a human is very different
and what he found is that for all
Learners and for me doubly excitingly
the um the effect was very significant
on all learners but especially
significant for
um non-traditional I don't like that
term but excluded Learners
um
if we change from this stage on the
stage uh knowledge transfer system to a
system of instruction that is more about
um
proposing problems projects learning not
by being told something but by being
asked something learning by exploration
by research learning by getting things
wrong and then correcting them learning
through comparison and discussion that
problem-based Active Learning approach
and importantly also uh increase support
ideally one-to-one coach support
transformed learning outcomes for
everybody but as I say especially
um for um kind of underrepresented
groups
and so we have this really great moment
where we're all like amazing we've
cracked the code let's change how we
teach and learn Bloom's like okay kind
of mic drop let's go uh change the world
and what's really interesting to me is
that that didn't happen
and so we have had education technology
for you know this concept of Education
technology we've had now for 30 40 years
so since bloom
but that technology has consistently
been used not to introduce this new
system which we know works better but to
reinforce the old system so to make us
better and faster at ineffective
practice effectively so if you think
about I mean this is not an impressive
list of stuff but if you think about Ed
Tech as like for example the overhead
projector or the PowerPoint or the
interactive whiteboard all of these
things uh they don't help us to deliver
more active personalized and adaptive
learning they help us to
right like deliver lectures
and what we're seeing is
the same Trend with AI
so
ai's been around in education now for
like 60 years
uh as we all know it has uh with the
with the rise of open Ai and generative
AI
um over the last six months it's really
come on to everybody's radar and it's
given everybody access to it which means
that you know discussion of it is
unprecedented but what we've seen over
the last 60 years that we've been using
AI in education and particularly the
last six months is that we're doing the
same thing we are building AI technology
not to innovate our pedagogy and
innovate our impact on outcomes but to
accelerate and automate this broken
knowledge transfer process so we're
seeing AI tools uh you know I'm sure
you've all seen them all but like make
more content faster uh generate a quiz
from content all of these things
um and there's a huge risk here and I
think this Daniel Schwartz who is I
think the head of Education technology
at Stanford something like he's a
professor said recently and it really
resonated with me that the biggest risk
of AI in education is that it makes us
much more efficient at ineffective
practice
and so yeah I'm really interested to
think about why that is I'm also very
interested to
to put on people's radar the fact that I
think often we think of Technologies
like AI as inevitably Innovative and
disruptive but that isn't the case
um and as a historian I'm really
interested in things like uh the rise of
the the printing press in the 15th
century sometimes we celebrate that as
this great Innovative moment when things
really changed and we started to see
modernization whereas in fact the
research shows that for the first 200
years that we have the printing press it
was used to perpetuate existing ideas
existing behaviors existing systems of
power
so we're really like in this really
interesting situation and what really
motivates me in this space is to think
about if we know these formulas are
great what great learning looks like uh
why aren't we using technology better
to achieve those scenarios to give every
learner the same opportunities that you
know privileged people who get to go to
Cambridge and wherever else also get
um and when people ask me this question
like Phil is AI finally going to disrupt
education
I think my answer is always that
I I don't doubt for a second that AI is
able to disrupt education AI is
absolutely able right now
to deliver on Bloom's Vision on this
vision of where every student achieves
more faster
the question is more like the bigger
question I think the more interesting
question is will we allow it to do that
because we've been in a position where
we could do that now for maybe 30 years
and for whatever reason we've used
technology as a force for shoring things
up
as a force for continuity rather than a
force for change
um and so yeah that's that's why this AI
Revolution you know TBC is so
interesting to me are we going to see
Faster Horses
or are we going to you know see finally
uh the evolution of the car and and and
and with that
um the delivery on the promise that we
will actually you know serve every
single student as well as we can in the
classroom
you've you've dropped like 800 questions
in there and that was all perfect thank
you so much and I want to remind people
they can ask questions in the chat we'll
get to those later
um what's Bloom doing now by the way
um I don't actually know if Bloom is
still with us lots of people lots of
people since Bloom and me included have
continued that research and so now we
know conclusively In Bloom like was the
the forefather of this that
um a learning experience that is active
uh and personalized and individually
coached is chef's kiss
um I guess is still he's still around on
the scene but very much is like the
forefather of this movement
so when when you started by saying you
know all of this is kept in the Ivory
Tower
what needs to happen because it feels
like we're in this perfect opportunity
for people in edtech to reinvent the The
Learning Experience
um two weeks ago at Ted Sal Khan uh
founder of the Khan Academy showed how
they had integrated AI into the learning
experience for kids and I think it just
floored everybody we we showed that just
last Saturday uh that it is very
interactive very experience based very
question based and it's and it wasn't
just for the student it was also for the
teacher and so that looked like a best
practice of ways to go forward did you
are you aware of the work he's doing
yeah absolutely
like when I watched that Ted Talk Back
it's like yes it's like finally are we
is it happening because what um Sal Khan
described is exactly what Bloom
recommended in 1984. it's this perfect
individual coaching encouragement
personalized pathways through to a
shared outcome
um and so yeah and we're seeing other
examples too so I know that Microsoft
have released a Reading Coach which
again which scene so where Khan Academy
is um car meago I think it's called is
designed to be used at home as a kind of
pre-class or a post-class extension to
learning
um there are more and more tools
um appearing like the Microsoft tools
the Reading Coach to be used which is
designed to be used by teachers in the
classroom to deliver the same sort of
again we all have one goal but we sit
and we pursue that goal powered by AI
um and take very personalized adaptive
paths to it and get different sorts of
feedback which drive us through
um different paths to the same goal so
you're right in that there is you know
it there are examples of innovation out
there there are examples of AI being
used in ways which drives learner
outcomes but I think we're also in a
situation where and this has been the
case ever since edtech existed where
there is still a thinker lack of
discourse between education technology
I've said it before and I will say it
again I'm sure after this but like one
of my one of my uh kind of taglines is
that we need to put the ad back into Ed
Tech I think often we we end up building
technology uh to solve an immediate pain
hair on fire pain because that's the
thing that sells it's like I need to you
know design a lecture tomorrow so let's
build a tool that will do that in
seconds
um and so it's you know most edtech
Works in that way but yeah Khan Academy
and Microsoft doing great work to really
highlight how we can use AI to innovate
pedagogy rather than just delivery if
that makes sense it makes total sense
and and one of the things that uh uh I
appreciated about your writing because I
follow the things that you're saying
because you're you're very good at
putting information out there for those
of us that are interested in this uh
this field but you have this concept of
three teams which I have repeated uh
since I first was exposed to it explain
to our our listeners here what the three
teams are
yeah so uh and in fact I think it might
now be two but let me let me give you
the story so yeah in formal education so
this is global it's K-12 it's he it's
further education as we would call it
it's education uh when uh generative AI
kind of caught fire at the end of last
year and came into the world we tended
to have like three camps emerge
um so the first Camp was uh Team avoid
um and so we saw an initial reaction
where
um Educators and it's understandable and
I was included in this you know it was
like the immediate response is like
shoot if uh if everyone can now use chat
GPT to uh write their essays then the
systems are broken so what we'll do is
uh we'll avoid this risk by getting
everyone back into the room so we saw
for example in Australia very rapid
change to higher education policy that
said okay from now on you write essays
and you do exams in a room and we'll
watch you the kind of you know
panoptican Bentham uh approach all the
other institutions uh did things like uh
require students to create images or
videos or have oral aspects to the
to the examinations
um I mean it gives you a sense of how
rapidly things are changing because now
we can create images using AI as well so
that's broken
so there's that there's that group
um and then there was team Bennett which
is really interesting and this is
ongoing this is a very interesting game
of cat and mouse going on which I've
been watching since about December where
um you know I guess I guess in line with
existing protocol
um a lot of Institutions education
institutions said hey if uh Chachi BT
can write essays then that's plagiarism
so let's detect it and then
um basically ban it so make that uh
misconduct and so we've seen a lot of
Institutions investing in in very
rapidly built ironically using AI uh
tools which can detect whether or not
your essay has been written by tragedy
BT so the GBP zero various turn it in
whatever
um and what's really interesting is that
as quickly as these things have been
built over here in December
uh Revenge of the Nerds were on YouTube
uh explaining to all the students how
you can actually kind of clean your data
so that it's not detectable anymore
um and this is ongoing and so now we
have at first it was kind of hacks
through YouTube and now we have uh
companies being built uh which are
student facing and they say like hey
we can answer it we can we can write any
essay and no one will ever know that
chat GPT wrote it and so this game of
cat and mouse is going on there's also
some really important research that's
happened to show that
um chat gbt detection Technologies are
biased they're biased towards certain
types of language certain types of
Concepts Etc so I think the key message
is that perfect AI detection is not
possible and team bannett are now kind
of starting to realize that that they're
caught in this cat and mouse game I
think some institutions are still in the
process of buying the tech and they're
now like what we're going to do
and then and then the emerging Group
which is getting bigger
um I would say by the month particularly
over the last two months is team Embrace
and this team instead of trying to
circumnavigate it or ban it kind of say
okay well what would it look like if we
embraced chat GPT in the classroom what
does that look like for me as a teacher
and for my students on the ground and
that really I think is if we had a
beautiful graph now it would be helpful
but I think I see the first two camps as
really having a very short shelf life
because it's not sustainable
here we have um so this team Embrace I
think is where the future is going
I am
people may have seen it but there was a
really interesting and one of the first
controlled studies that came out about
chat GPT came out maybe two three weeks
ago and what it found is that chat GPT
increased uh human efficiency by 35 some
people are saying that's a massive
underestimation now to put that into
context steam in the in the Victorian
period increased our productivity by 25
so there is there is no doubt in my mind
that the most likely future is one if AI
remains low cost or no cost is one where
our work and our lives are AI powered
and so team Embrace uh or the team that
kind of acknowledge this and acknowledge
that in that world we as Educators have
a really critical role to play in
educating our students like about what
AI is and how we use it and what its
weaknesses are what the risks are
um and that's that's exactly what I've
been doing and all the other members of
Team Embrace have been doing
um and yeah I'm going to get a T-shirt
and send it to you that says team
Embrace on it thank you for for helping
us understand this very complex and very
topical
conversation
absolutely
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