SlideShare a Scribd company logo
Mike Sharples
Institute of Educational Technology
The Open University
www.mikesharples.org
Generative AI for Teaching, Learning and Assessment
Opportunities and issues
@sharplm
Generative AI
A threat to education?
Or a universal tutor?
GPT-4
Highly-trained text completer and style
copier
It can generate up to 25,000 words
It can write in any style in multiple
languages
It can be given a direct instruction
It can interpret text and images
It is a general-purpose language tool
ChatGPT Plus
Plugins for maths,
science, language,
media, business
Integration with web
browser
Code interpreter to run
and display Python
programs
Other AI generators
Language models
PaLM 2 from Google – over 100 languages, version for medicine, free
with Bard chat
LLaMA 2 from Meta – open source, 20 languages, small, simple, free,
efficient
Claude-2 from Anthropic – trained on ethical principles, can read 75,000
words, free to use
Image generators
DALL-E 2 from OpenAI – fast, accurate, free with Bing Image Creator
Midjourney – high-quality photo images
Stable Diffusion – free, open source
Plus: computer code, voice, music, video, specialist (e.g.,
BloombergGPT)
Generative AI
hallucinates
It doesn’t “know” it shouldn’t invent
research studies,
it has no explicit model of how the world
works,
and is amoral.
It is a language model, not a
database or reasoning system
https://openai.com/blog/instruction-following/
You are a student on a Master of Education course.
Write a high quality 500 word essay on “A Critique of
Learning Styles". The essay should include academic
references and evidence from research studies. It
should begin "The construct of 'learning styles' is
problematic because"
A Critique of Learning Styles
The construct of 'learning styles' is problematic because it assumes that learners have distinct and consistent preferences for acquiring and processing information. This idea
has gained popularity among educators and trainers, but there is little evidence to support the existence of such a fixed and reliable construct. Furthermore, promoting the
use of learning styles in education may lead to harmful practices and prevent learners from developing skills and abilities that are essential for success in the 21st century.
One of the main issues with the concept of learning styles is the lack of empirical evidence to support it. A systematic review of studies investigating the relationship between
learning styles and academic achievement found little to no evidence of a correlation between the two (Pashler et al., 2008). In fact, the review concluded that teaching
according to learning styles might actually be detrimental to learning outcomes. Similarly, a recent meta-analysis of studies exploring the effectiveness of learning styles
interventions also found little support for the idea (Rohrer & Pashler, 2012). The lack of empirical support for the concept of learning styles undermines the notion that
individuals have consistent and reliable preferences for acquiring and processing information.
Another problem with the use of learning styles in education is that it may encourage fixed mindsets and discourage the development of essential skills and abilities.
According to the theory of growth mindsets, learners who believe that their intelligence and abilities are malleable are more likely to embrace challenges, persist in the face of
setbacks, and ultimately achieve higher levels of success (Dweck, 2006). In contrast, the use of learning styles may encourage learners to see their abilities as fixed and
unchangeable, leading to a belief that they are limited in their capacity to learn in certain ways. This can be particularly damaging for learners who may not have been
exposed to certain ways of learning or who may have been discouraged from pursuing certain subjects or activities due to their perceived learning style.
Finally, the use of learning styles in education may lead to harmful practices such as tracking and labeling students. In tracking, learners are sorted into groups based on their
perceived learning style, which can reinforce stereotypes and limit opportunities for growth and exploration (Gurung, 2004). Labeling students according to their learning style
can also be harmful, as it may encourage teachers and learners to focus on weaknesses rather than strengths and may stigmatize learners who do not fit neatly into a
particular category.
In conclusion, the construct of learning styles is problematic because it lacks empirical support, may discourage the development of essential skills and abilities, and can lead
to harmful educational practices such as tracking and labeling. As educators, it is important to recognize the limitations of learning styles and instead focus on evidence-
based practices that promote learning and growth for all learners, regardless of their perceived learning style.
References:
Dweck, C. (2006). Mindset: The new psychology of success. Random House.
Gurung, R. (2004). Black and white thinking about learning styles: A response to the Journal of College Reading and Learning. Journal of College Reading and Learning, 34(2),
7-17.
Pashler, H., McDaniel, M., Rohrer, D., & Bjork, R. (2008). Learning styles: Concepts and evidence. Psychological Science in the Public Interest, 9(3), 105-119.
Rohrer, D., & Pashler, H. (2012). Learning styles: Where's the evidence? Medical Education, 46(7), 634-635.
A Critique of Learning Styles
The construct of 'learning styles' is problematic because it assumes that learners have distinct and consistent preferences for acquiring and processing information. This idea has gained
popularity among educators and trainers, but there is little evidence to support the existence of such a fixed and reliable construct. Furthermore, promoting the use of learning styles in
education may lead to harmful practices and prevent learners from developing skills and abilities that are essential for success in the 21st century.
One of the main issues with the concept of learning styles is the lack of empirical evidence to support it. A systematic review of studies investigating the relationship between learning
styles and academic achievement found little to no evidence of a correlation between the two (Pashler et al., 2008). In fact, the review concluded that teaching according to learning styles
might actually be detrimental to learning outcomes. Similarly, a recent meta-analysis of studies exploring the effectiveness of learning styles interventions also found little support for the
idea (Rohrer & Pashler, 2012). The lack of empirical support for the concept of learning styles undermines the notion that individuals have consistent and reliable preferences for acquiring
and processing information.
Another problem with the use of learning styles in education is that it may encourage fixed mindsets and discourage the development of essential skills and abilities. According to the
theory of growth mindsets, learners who believe that their intelligence and abilities are malleable are more likely to embrace challenges, persist in the face of setbacks, and ultimately
achieve higher levels of success (Dweck, 2006). In contrast, the use of learning styles may encourage learners to see their abilities as fixed and unchangeable, leading to a belief that they
are limited in their capacity to learn in certain ways. This can be particularly damaging for learners who may not have been exposed to certain ways of learning or who may have been
discouraged from pursuing certain subjects or activities due to their perceived learning style.
Finally, the use of learning styles in education may lead to harmful practices such as tracking and labeling students. In tracking, learners are sorted into groups based on their perceived
learning style, which can reinforce stereotypes and limit opportunities for growth and exploration (Gurung, 2004). Labeling students according to their learning style can also be harmful,
as it may encourage teachers and learners to focus on weaknesses rather than strengths and may stigmatize learners who do not fit neatly into a particular category.
In conclusion, the construct of learning styles is problematic because it lacks empirical support, may discourage the development of essential skills and abilities, and can lead to harmful
educational practices such as tracking and labeling. As educators, it is important to recognize the limitations of learning styles and instead focus on evidence-based practices that promote
learning and growth for all learners, regardless of their perceived learning style.
References:
Dweck, C. (2006). Mindset: The new psychology of success. Random House.
Gurung, R. (2004). Black and white thinking about learning styles: A response to the Journal of College Reading and Learning. Journal of College Reading and Learning, 34(2), 7-17.
Pashler, H., McDaniel, M., Rohrer, D., & Bjork, R. (2008). Learning styles: Concepts and evidence. Psychological Science in the Public Interest, 9(3), 105-119.
Rohrer, D., & Pashler, H. (2012). Learning styles: Where's the evidence? Medical Education, 46(7), 634-635.
Invented
research
study
Fake
academic
paper
The construct of 'learning styles' is problematic because it implies a static and narrowly defined approach to the way individuals process and retain information. Despite the widespread popularity of this
concept, there is a lack of empirical evidence to support the effectiveness of learning styles in enhancing educational outcomes. This essay aims to critique the learning styles theory by examining its origin,
research evidence, and implications for educators.
The concept of learning styles has its roots in the work of Dunn and Dunn (1978), who posited that students have different preferred ways of processing information, including visual, auditory, and
kinesthetic modalities. The VARK model (Fleming, 2001) expanded upon this idea, adding the reading/writing preference as a fourth category. Other models, such as Kolb's experiential learning theory (Kolb,
1984) and Gardner's theory of multiple intelligences (Gardner, 1983), further contributed to the proliferation of learning styles theories in education.
Despite the intuitive appeal of these theories, numerous research studies have consistently failed to support the effectiveness of learning styles in improving educational outcomes. For instance, a meta-
analysis conducted by Pashler et al. (2008) found insufficient evidence to support the idea that tailoring instruction to students' learning styles resulted in improved learning. Similarly, a review by Coffield et
al. (2004) identified more than 70 learning styles models and concluded that there was little scientific evidence to support the use of any of them in practice.
One of the primary criticisms of learning styles is the lack of a clear and consistent definition of what constitutes a learning style (Coffield et al., 2004). This has led to the proliferation of multiple, often
contradictory, models that make it difficult to operationalize and test the theory. Furthermore, many of the assessments used to determine students' learning styles have been found to lack reliability and
validity (Kirschner & van Merriënboer, 2013), further casting doubt on the utility of this concept in educational settings.
Another issue with learning styles is the oversimplification of the learning process. By categorizing students into distinct learning styles, the theory disregards the complex and dynamic nature of human
cognition (Kirschner & van Merriënboer, 2013). In reality, learners are not limited to a single mode of processing information, and the effectiveness of a particular learning approach may vary depending on
the context and the specific task at hand (Willingham, 2009).
Moreover, the focus on learning styles may inadvertently encourage teachers to limit their instructional methods, potentially hindering the development of a diverse repertoire of cognitive skills in students
(Riener & Willingham, 2010). Instead of catering to specific learning styles, researchers have argued that teachers should emphasize the use of evidence-based instructional strategies that are effective
across a wide range of learners, such as spaced repetition, retrieval practice, and elaboration (Dunlosky et al., 2013).
In conclusion, the concept of learning styles is problematic due to its lack of empirical support, inconsistent definitions, and oversimplification of the learning process. Rather than relying on this flawed
theory, educators should focus on adopting evidence-based instructional strategies that promote learning for all students. Ultimately, fostering a diverse set of cognitive skills and flexible thinking will better
prepare learners for the complex and dynamic challenges they will face in their lives.
References:
Coffield, F., Moseley, D., Hall, E., & Ecclestone, K. (2004). Learning styles and pedagogy in post-16 learning: A systematic and critical review. Learning and Skills Research Centre.
Dunn, R., & Dunn, K. (1978). Teaching students through their individual learning styles: A practical approach. Reston Publishing Company.
Dunlosky, J., Rawson, K. A., Marsh, E. J., Nathan, M. J., & Willingham, D. T. (2013). Improving students' learning with effective learning techniques: Promising directions from cognitive and educational psychology. Psychological Science in the Public Interest, 14(1), 4-58.
Fleming, N. D. (2001). Teaching and learning styles: VARK strategies. Christchurch, New Zealand.
Kirschner, P. A., & van Merriënboer, J. J. (2013). Do learners really know best? Urban legends in education. Educational Psychologist, 48(3), 169-183.
Pashler, H., McDaniel, M., Rohrer, D., & Bjork, R. (2008). Learning styles: Concepts and evidence. Psychological Science in the Public Interest, 9(3), 105-119.
Riener, C., & Willingham, D. (2010). The myth of learning styles. Change: The Magazine of Higher Learning, 42(5), 32-35.
Willingham, D. T. (2009). Why don't students like school? A cognitive scientist answers questions about how the mind works and what it means for the classroom. Jossey-Bass.
Plagiarism detectors don’t work – the
text is generated, not copied
AI detectors have low reliability
OpenAI’s detector tool labels 9% of human-
written text as written by AI
Turnitin AI detector
Claims of less than 1% false positives with
GPT-3.5 (“based on data that was collected
and verified in a controlled lab environment”)
need to be independently verified.
https://www.turnitin.com/products/features/ai-writing-detection
AI detectors are more likely to mis-classify
the text of non-native English writers
https://arxiv.org/pdf/2304.02819.pdf
Turnitin detector tool
https://arxiv.org/pdf/2304.02819.pdf
Ban
Confident students will continue to use AI
and will challenge decisions based on AI
detectors.
Evade
Invigilated exams are costly and limited.
Asking students to state when they use AI
will become increasingly difficult
Adapt
Requires new methods of assessment, new
policies and guidelines
Embrace
Involves a long process of building trust
Emerging policy and strategy
Amend written assessments to make them harder for
AI to generate
Move to more authentic assessments, such as project
work
Establish guidelines for students and staff in use of
generative AI
Reassure and support students in becoming AI
literate and developing strategies for effective learning
Explain to students how they should acknowledge use
of generative AI in assignments
Manage suspected breaches of guidelines
Consider redesigning assessment to incorporate AI
and develop critical thinking
Emerging policy and strategy
Amend written assessments to make them harder for
AI to generate
Move to more authentic assessments, such as project
work
Establish guidelines for students and staff in use of
generative AI
Reassure and support students in becoming AI
literate and developing strategies for effective learning
Explain to students how they should acknowledge use
of generative AI in assignments
Manage suspected breaches of guidelines
Consider redesigning assessment to incorporate AI
and develop critical thinking
Flip the narrative from
“How will AI impact education?”
to
“What are new and effective ways to teach and
learn with AI?”
Adaptive teaching
Spaced learning
Personal inquiry
Dynamic assessment
Stealth assessment
Translanguaging
Crossover learning
Seamless learning
Incidental learning
Learning from gaming
Geo-learning
Learning through social
media
Navigating post-truth
societies
Every powerful pedagogy could be augmented by AI
Explore first
Teachback
Learning through
argumentation
Computational thinking
Learning from animations
Learning to learn
Assessment for learning
Formative analytics
Threshold concepts
Learning through storytelling
Learning in remote labs
Context-based learning
Event-based learning
Learning for the future
Embodied learning
Immersive learning
Maker culture
Bricolage
Massive open social learning
Crowd learning
Citizen inquiry
Rhizomatic learning
Reputation management
Open pedagogy
Humanistic knowledge-
building communities
Possibility Engine
Educator or student uses AI to
generate multiple responses to
an open question. Each
student synthesises and
critiques the AI responses, to
create their own written
answer.
New ways of teaching and learning with AI
Socratic Opponent
In an individual or group activity,
students engage with ChatGPT in a
Socratic dialogue, then each
student writes an argumentative
essay.
New ways of teaching and learning with AI
Exploratorium
Students explore language by
generating games and quizzes.
New ways of teaching and learning with AI
Co-designer
AI assists a group of students
throughout a design process, to
define the problem, challenge
assumptions, brainstorm ideas,
produce prototypes. Use
“temperature” setting to adjust
creativity.
AI supports collaborative design
Personal Tutor
Students have a personal
tutor for any topic.
New ways of teaching and learning with AI
Dynamic Assessor
Students share summaries
of their learning for
dynamic assessment.
Summary assessment, based on my conversation with ChatGPT-4
New ways of teaching and learning with AI
Possibility Engine
AI generates alternative ways of expressing an idea
Socratic Opponent
AI acts as an opponent to develop an argument
Collaboration Coach
AI helps groups to research and solve problems
together
Guide on the Side
AI acts a guide to navigate physical and conceptual
spaces
Personal Tutor
AI tutors each student and gives immediate feedback on
progress
Co-Designer
AI assists throughout the design process
Exploratorium
AI provides tools to play with, explore and interpret
data
Study Buddy
AI helps the student reflect on learning material
Motivator
AI offers games and challenges to extend learning
Dynamic Assessor
AI provides educators with a profile of each student’s
current knowledge
New ways of teaching and learning with AI
Microsoft Copilot
Generative AI integrated into Office
suite
Google GEMINI
Collaboration with DeepMind,
multimodal, problem-solving,
networked
Claude from Anthropic
Trained on ethical principles to be
“helpful, honest, and harmless”
https://www.engadget.com/microsoft-365-
copilot-uses-ai-to-automate-everyday-tasks-in-
multiple-apps-151133434.html
Beyond GPT
Model is trained to respect high-
level constitutional principles
based on UN Declaration of
Human Rights, and Apple’s
Terms of Service
E.g. “Please choose the
response that is most
supportive of life, liberty, and
personal security”
Claude – Constitutional AI
Foundation language models
Generative AI tools
Social AI systems for
education, business,
entertainment
PaLM
?
Foundation language models
Generative AI based tools
Social AI systems for
education, business,
entertainment
PaLM
?
Education practitioners,
learning technologists and AI
companies need to work
together to adopt powerful,
and ethical systems for
personal and social learning
Use generative AI with care
Rethink written assessment
Beware of AI for factual writing
Explore AI for critical thinking,
creativity, argumentation
Introduce and negotiate
guidelines for students and staff
Develop AI literacy
Adopt ethical AI for education
Resources
Sharples, M. (2022). Automated essay writing: an
AIED opinion. International Journal of Artificial
Intelligence in Education, 32(4), 1119-1126.
Sharples, M., & Pérez y Pérez, R. (2022). Story
Machines: How Computers Have Become Creative
Writers. Routledge.
Pérez y Pérez, R. & Sharples, M. (2023). An
Introduction to Narrative Generators: How Computers
Create Works of Fiction. Oxford University Press.
UNESCO (2023). ChatGPT and artificial intelligence in
higher education: Quick start guide.

More Related Content

PDF
King Faisal University Training AI and Education
PPTX
Using Generative AI in the Classroom .pptx
PPTX
Keynote AI assessment tools: online exams and tools.pptx
PPTX
Innnovations in online teaching and learning: CHatGPT and other artificial as...
PPTX
How should our higher education institutions respond to innovations in new AI...
PDF
AI Toolkit for Educators
PPTX
Mike Sharples - Generative AI and Large Language Models in Digital Education....
PPTX
Teaching with ChatGPT-Practical Tips and Strategies
King Faisal University Training AI and Education
Using Generative AI in the Classroom .pptx
Keynote AI assessment tools: online exams and tools.pptx
Innnovations in online teaching and learning: CHatGPT and other artificial as...
How should our higher education institutions respond to innovations in new AI...
AI Toolkit for Educators
Mike Sharples - Generative AI and Large Language Models in Digital Education....
Teaching with ChatGPT-Practical Tips and Strategies

What's hot (20)

PPTX
Generative AI and Student Writing.pptx
PPTX
Chat GPT and Generative AI in Higher Education - Empowering Educators and Lea...
PDF
AI in research: ChatGPT and more
PDF
How Does Generative AI Actually Work? (a quick semi-technical introduction to...
PPT
AI in Higher Education – Challenges & Opportunities #edlw2019
PPTX
AI and the Researcher: ChatGPT and DALL-E in Scholarly Writing and Publishing
PPTX
Ai in Higher Education
PPT
Artificial Intelligence in Education
PPTX
OpenAI Chatgpt.pptx
PDF
Chat GPT - A Game Changer in Education
PDF
Generative AI
PDF
Introduction To Data Science
PPTX
AI and the impact on Education
PDF
Let's talk about GPT: A crash course in Generative AI for researchers
PDF
Exploring Opportunities in the Generative AI Value Chain.pdf
PDF
Generative-AI-in-enterprise-20230615.pdf
PPTX
Ai in education
PPTX
Artificial Intelligence in Education focusing on the Skills3.0 project
PDF
Leveraging Generative AI & Best practices
PDF
LLMs Bootcamp
Generative AI and Student Writing.pptx
Chat GPT and Generative AI in Higher Education - Empowering Educators and Lea...
AI in research: ChatGPT and more
How Does Generative AI Actually Work? (a quick semi-technical introduction to...
AI in Higher Education – Challenges & Opportunities #edlw2019
AI and the Researcher: ChatGPT and DALL-E in Scholarly Writing and Publishing
Ai in Higher Education
Artificial Intelligence in Education
OpenAI Chatgpt.pptx
Chat GPT - A Game Changer in Education
Generative AI
Introduction To Data Science
AI and the impact on Education
Let's talk about GPT: A crash course in Generative AI for researchers
Exploring Opportunities in the Generative AI Value Chain.pdf
Generative-AI-in-enterprise-20230615.pdf
Ai in education
Artificial Intelligence in Education focusing on the Skills3.0 project
Leveraging Generative AI & Best practices
LLMs Bootcamp
Ad

Similar to Generative AI for Teaching, Learning and Assessment (20)

PPTX
Plagiarism - Past, Present, Future
PDF
gptandstudentwriting-230220153422-f1f8faf5.pdf
PPTX
GPT and Student Writing.pptx
PDF
Learning styles: Research and Expert Opinion
PPTX
UNIT3-LESSON9-Different Styles of Learning (Dayon&Enriquez).pptx
PDF
Learning Styles: Concepts and Evidence. Harold Pashler, Mark McDaniel, Doug R...
DOCX
Learning styles
PPTX
Validity of learning styles - Remi Tremblay and Piers Maclean
DOCX
learning styles
PDF
Teaching for multiple intelligences
PDF
21st century teachers
PDF
A Comparison Of Learning Style Models And Assessment Instruments For Universi...
PPT
What are the learning styles in differentiated instruction?.PPT
PPT
Learning Styles Presentation By The Yellow Team
PPT
Learning styles
PPT
A Unified Model of Learning Styles
PPS
Theories of learning
PPT
Learning Styles: Controversial but Oh-So Compelling!
PDF
Another journal article on Differentiated Reading
PPTX
Scientific communication a critical examination of learning style discourse –...
Plagiarism - Past, Present, Future
gptandstudentwriting-230220153422-f1f8faf5.pdf
GPT and Student Writing.pptx
Learning styles: Research and Expert Opinion
UNIT3-LESSON9-Different Styles of Learning (Dayon&Enriquez).pptx
Learning Styles: Concepts and Evidence. Harold Pashler, Mark McDaniel, Doug R...
Learning styles
Validity of learning styles - Remi Tremblay and Piers Maclean
learning styles
Teaching for multiple intelligences
21st century teachers
A Comparison Of Learning Style Models And Assessment Instruments For Universi...
What are the learning styles in differentiated instruction?.PPT
Learning Styles Presentation By The Yellow Team
Learning styles
A Unified Model of Learning Styles
Theories of learning
Learning Styles: Controversial but Oh-So Compelling!
Another journal article on Differentiated Reading
Scientific communication a critical examination of learning style discourse –...
Ad

More from Mike Sharples (20)

PPTX
Writing as Design
PPTX
C19th AI: The Latin Verse Machine
PPTX
Short introduction to educational technology for sharing
PPTX
20 years of mobile learning - what have we learned?
PPTX
Pedagogy-informed design of new educational technologies
PPTX
Pedagogy informed design of conversational learning at scale - ec-tel 2019
PPTX
Writing as design
PPTX
Pedagogy at scale
PPTX
Digital innovation and futures for higher education RMIT 2018
PPTX
New Directions in Personalized Learning: Open, Informal, Social
PPTX
Pedagogy of FutureLearn
PPT
Designs for Active Learning, Cambridge 2017
PPTX
International Challenges for Technology Enhanced Learning
PPT
Back to the future of mobile learning slideshare
PPTX
Blockchain and Kudos - Educational record, reputation and reward
PPTX
A Brief Introduction to Educational Technology - Part 2
PPTX
Small Group Discussion for a MOOC Platform
PPTX
Effective Pedagogy at Scale – Social Learning and Citizen Inquiry
PPTX
Introduction to educational technology
PPTX
Sense-it - mLearn 2015 presentation
Writing as Design
C19th AI: The Latin Verse Machine
Short introduction to educational technology for sharing
20 years of mobile learning - what have we learned?
Pedagogy-informed design of new educational technologies
Pedagogy informed design of conversational learning at scale - ec-tel 2019
Writing as design
Pedagogy at scale
Digital innovation and futures for higher education RMIT 2018
New Directions in Personalized Learning: Open, Informal, Social
Pedagogy of FutureLearn
Designs for Active Learning, Cambridge 2017
International Challenges for Technology Enhanced Learning
Back to the future of mobile learning slideshare
Blockchain and Kudos - Educational record, reputation and reward
A Brief Introduction to Educational Technology - Part 2
Small Group Discussion for a MOOC Platform
Effective Pedagogy at Scale – Social Learning and Citizen Inquiry
Introduction to educational technology
Sense-it - mLearn 2015 presentation

Recently uploaded (20)

PDF
Mark Klimek Lecture Notes_240423 revision books _173037.pdf
PPTX
Introduction to Child Health Nursing – Unit I | Child Health Nursing I | B.Sc...
PDF
Saundersa Comprehensive Review for the NCLEX-RN Examination.pdf
PPTX
master seminar digital applications in india
PDF
Abdominal Access Techniques with Prof. Dr. R K Mishra
PPTX
BOWEL ELIMINATION FACTORS AFFECTING AND TYPES
PPTX
The Healthy Child – Unit II | Child Health Nursing I | B.Sc Nursing 5th Semester
PPTX
IMMUNITY IMMUNITY refers to protection against infection, and the immune syst...
PDF
Classroom Observation Tools for Teachers
PDF
Pre independence Education in Inndia.pdf
PDF
STATICS OF THE RIGID BODIES Hibbelers.pdf
PDF
Supply Chain Operations Speaking Notes -ICLT Program
PPTX
Cell Structure & Organelles in detailed.
PDF
Business Ethics Teaching Materials for college
PPTX
Pharmacology of Heart Failure /Pharmacotherapy of CHF
PDF
Insiders guide to clinical Medicine.pdf
PDF
ANTIBIOTICS.pptx.pdf………………… xxxxxxxxxxxxx
PDF
Physiotherapy_for_Respiratory_and_Cardiac_Problems WEBBER.pdf
PDF
BÀI TẬP BỔ TRỢ 4 KỸ NĂNG TIẾNG ANH 9 GLOBAL SUCCESS - CẢ NĂM - BÁM SÁT FORM Đ...
PDF
102 student loan defaulters named and shamed – Is someone you know on the list?
Mark Klimek Lecture Notes_240423 revision books _173037.pdf
Introduction to Child Health Nursing – Unit I | Child Health Nursing I | B.Sc...
Saundersa Comprehensive Review for the NCLEX-RN Examination.pdf
master seminar digital applications in india
Abdominal Access Techniques with Prof. Dr. R K Mishra
BOWEL ELIMINATION FACTORS AFFECTING AND TYPES
The Healthy Child – Unit II | Child Health Nursing I | B.Sc Nursing 5th Semester
IMMUNITY IMMUNITY refers to protection against infection, and the immune syst...
Classroom Observation Tools for Teachers
Pre independence Education in Inndia.pdf
STATICS OF THE RIGID BODIES Hibbelers.pdf
Supply Chain Operations Speaking Notes -ICLT Program
Cell Structure & Organelles in detailed.
Business Ethics Teaching Materials for college
Pharmacology of Heart Failure /Pharmacotherapy of CHF
Insiders guide to clinical Medicine.pdf
ANTIBIOTICS.pptx.pdf………………… xxxxxxxxxxxxx
Physiotherapy_for_Respiratory_and_Cardiac_Problems WEBBER.pdf
BÀI TẬP BỔ TRỢ 4 KỸ NĂNG TIẾNG ANH 9 GLOBAL SUCCESS - CẢ NĂM - BÁM SÁT FORM Đ...
102 student loan defaulters named and shamed – Is someone you know on the list?

Generative AI for Teaching, Learning and Assessment

  • 1. Mike Sharples Institute of Educational Technology The Open University www.mikesharples.org Generative AI for Teaching, Learning and Assessment Opportunities and issues @sharplm
  • 2. Generative AI A threat to education? Or a universal tutor?
  • 3. GPT-4 Highly-trained text completer and style copier It can generate up to 25,000 words It can write in any style in multiple languages It can be given a direct instruction It can interpret text and images It is a general-purpose language tool
  • 4. ChatGPT Plus Plugins for maths, science, language, media, business Integration with web browser Code interpreter to run and display Python programs
  • 5. Other AI generators Language models PaLM 2 from Google – over 100 languages, version for medicine, free with Bard chat LLaMA 2 from Meta – open source, 20 languages, small, simple, free, efficient Claude-2 from Anthropic – trained on ethical principles, can read 75,000 words, free to use Image generators DALL-E 2 from OpenAI – fast, accurate, free with Bing Image Creator Midjourney – high-quality photo images Stable Diffusion – free, open source Plus: computer code, voice, music, video, specialist (e.g., BloombergGPT)
  • 6. Generative AI hallucinates It doesn’t “know” it shouldn’t invent research studies, it has no explicit model of how the world works, and is amoral. It is a language model, not a database or reasoning system https://openai.com/blog/instruction-following/
  • 7. You are a student on a Master of Education course. Write a high quality 500 word essay on “A Critique of Learning Styles". The essay should include academic references and evidence from research studies. It should begin "The construct of 'learning styles' is problematic because"
  • 8. A Critique of Learning Styles The construct of 'learning styles' is problematic because it assumes that learners have distinct and consistent preferences for acquiring and processing information. This idea has gained popularity among educators and trainers, but there is little evidence to support the existence of such a fixed and reliable construct. Furthermore, promoting the use of learning styles in education may lead to harmful practices and prevent learners from developing skills and abilities that are essential for success in the 21st century. One of the main issues with the concept of learning styles is the lack of empirical evidence to support it. A systematic review of studies investigating the relationship between learning styles and academic achievement found little to no evidence of a correlation between the two (Pashler et al., 2008). In fact, the review concluded that teaching according to learning styles might actually be detrimental to learning outcomes. Similarly, a recent meta-analysis of studies exploring the effectiveness of learning styles interventions also found little support for the idea (Rohrer & Pashler, 2012). The lack of empirical support for the concept of learning styles undermines the notion that individuals have consistent and reliable preferences for acquiring and processing information. Another problem with the use of learning styles in education is that it may encourage fixed mindsets and discourage the development of essential skills and abilities. According to the theory of growth mindsets, learners who believe that their intelligence and abilities are malleable are more likely to embrace challenges, persist in the face of setbacks, and ultimately achieve higher levels of success (Dweck, 2006). In contrast, the use of learning styles may encourage learners to see their abilities as fixed and unchangeable, leading to a belief that they are limited in their capacity to learn in certain ways. This can be particularly damaging for learners who may not have been exposed to certain ways of learning or who may have been discouraged from pursuing certain subjects or activities due to their perceived learning style. Finally, the use of learning styles in education may lead to harmful practices such as tracking and labeling students. In tracking, learners are sorted into groups based on their perceived learning style, which can reinforce stereotypes and limit opportunities for growth and exploration (Gurung, 2004). Labeling students according to their learning style can also be harmful, as it may encourage teachers and learners to focus on weaknesses rather than strengths and may stigmatize learners who do not fit neatly into a particular category. In conclusion, the construct of learning styles is problematic because it lacks empirical support, may discourage the development of essential skills and abilities, and can lead to harmful educational practices such as tracking and labeling. As educators, it is important to recognize the limitations of learning styles and instead focus on evidence- based practices that promote learning and growth for all learners, regardless of their perceived learning style. References: Dweck, C. (2006). Mindset: The new psychology of success. Random House. Gurung, R. (2004). Black and white thinking about learning styles: A response to the Journal of College Reading and Learning. Journal of College Reading and Learning, 34(2), 7-17. Pashler, H., McDaniel, M., Rohrer, D., & Bjork, R. (2008). Learning styles: Concepts and evidence. Psychological Science in the Public Interest, 9(3), 105-119. Rohrer, D., & Pashler, H. (2012). Learning styles: Where's the evidence? Medical Education, 46(7), 634-635.
  • 9. A Critique of Learning Styles The construct of 'learning styles' is problematic because it assumes that learners have distinct and consistent preferences for acquiring and processing information. This idea has gained popularity among educators and trainers, but there is little evidence to support the existence of such a fixed and reliable construct. Furthermore, promoting the use of learning styles in education may lead to harmful practices and prevent learners from developing skills and abilities that are essential for success in the 21st century. One of the main issues with the concept of learning styles is the lack of empirical evidence to support it. A systematic review of studies investigating the relationship between learning styles and academic achievement found little to no evidence of a correlation between the two (Pashler et al., 2008). In fact, the review concluded that teaching according to learning styles might actually be detrimental to learning outcomes. Similarly, a recent meta-analysis of studies exploring the effectiveness of learning styles interventions also found little support for the idea (Rohrer & Pashler, 2012). The lack of empirical support for the concept of learning styles undermines the notion that individuals have consistent and reliable preferences for acquiring and processing information. Another problem with the use of learning styles in education is that it may encourage fixed mindsets and discourage the development of essential skills and abilities. According to the theory of growth mindsets, learners who believe that their intelligence and abilities are malleable are more likely to embrace challenges, persist in the face of setbacks, and ultimately achieve higher levels of success (Dweck, 2006). In contrast, the use of learning styles may encourage learners to see their abilities as fixed and unchangeable, leading to a belief that they are limited in their capacity to learn in certain ways. This can be particularly damaging for learners who may not have been exposed to certain ways of learning or who may have been discouraged from pursuing certain subjects or activities due to their perceived learning style. Finally, the use of learning styles in education may lead to harmful practices such as tracking and labeling students. In tracking, learners are sorted into groups based on their perceived learning style, which can reinforce stereotypes and limit opportunities for growth and exploration (Gurung, 2004). Labeling students according to their learning style can also be harmful, as it may encourage teachers and learners to focus on weaknesses rather than strengths and may stigmatize learners who do not fit neatly into a particular category. In conclusion, the construct of learning styles is problematic because it lacks empirical support, may discourage the development of essential skills and abilities, and can lead to harmful educational practices such as tracking and labeling. As educators, it is important to recognize the limitations of learning styles and instead focus on evidence-based practices that promote learning and growth for all learners, regardless of their perceived learning style. References: Dweck, C. (2006). Mindset: The new psychology of success. Random House. Gurung, R. (2004). Black and white thinking about learning styles: A response to the Journal of College Reading and Learning. Journal of College Reading and Learning, 34(2), 7-17. Pashler, H., McDaniel, M., Rohrer, D., & Bjork, R. (2008). Learning styles: Concepts and evidence. Psychological Science in the Public Interest, 9(3), 105-119. Rohrer, D., & Pashler, H. (2012). Learning styles: Where's the evidence? Medical Education, 46(7), 634-635. Invented research study Fake academic paper
  • 10. The construct of 'learning styles' is problematic because it implies a static and narrowly defined approach to the way individuals process and retain information. Despite the widespread popularity of this concept, there is a lack of empirical evidence to support the effectiveness of learning styles in enhancing educational outcomes. This essay aims to critique the learning styles theory by examining its origin, research evidence, and implications for educators. The concept of learning styles has its roots in the work of Dunn and Dunn (1978), who posited that students have different preferred ways of processing information, including visual, auditory, and kinesthetic modalities. The VARK model (Fleming, 2001) expanded upon this idea, adding the reading/writing preference as a fourth category. Other models, such as Kolb's experiential learning theory (Kolb, 1984) and Gardner's theory of multiple intelligences (Gardner, 1983), further contributed to the proliferation of learning styles theories in education. Despite the intuitive appeal of these theories, numerous research studies have consistently failed to support the effectiveness of learning styles in improving educational outcomes. For instance, a meta- analysis conducted by Pashler et al. (2008) found insufficient evidence to support the idea that tailoring instruction to students' learning styles resulted in improved learning. Similarly, a review by Coffield et al. (2004) identified more than 70 learning styles models and concluded that there was little scientific evidence to support the use of any of them in practice. One of the primary criticisms of learning styles is the lack of a clear and consistent definition of what constitutes a learning style (Coffield et al., 2004). This has led to the proliferation of multiple, often contradictory, models that make it difficult to operationalize and test the theory. Furthermore, many of the assessments used to determine students' learning styles have been found to lack reliability and validity (Kirschner & van Merriënboer, 2013), further casting doubt on the utility of this concept in educational settings. Another issue with learning styles is the oversimplification of the learning process. By categorizing students into distinct learning styles, the theory disregards the complex and dynamic nature of human cognition (Kirschner & van Merriënboer, 2013). In reality, learners are not limited to a single mode of processing information, and the effectiveness of a particular learning approach may vary depending on the context and the specific task at hand (Willingham, 2009). Moreover, the focus on learning styles may inadvertently encourage teachers to limit their instructional methods, potentially hindering the development of a diverse repertoire of cognitive skills in students (Riener & Willingham, 2010). Instead of catering to specific learning styles, researchers have argued that teachers should emphasize the use of evidence-based instructional strategies that are effective across a wide range of learners, such as spaced repetition, retrieval practice, and elaboration (Dunlosky et al., 2013). In conclusion, the concept of learning styles is problematic due to its lack of empirical support, inconsistent definitions, and oversimplification of the learning process. Rather than relying on this flawed theory, educators should focus on adopting evidence-based instructional strategies that promote learning for all students. Ultimately, fostering a diverse set of cognitive skills and flexible thinking will better prepare learners for the complex and dynamic challenges they will face in their lives. References: Coffield, F., Moseley, D., Hall, E., & Ecclestone, K. (2004). Learning styles and pedagogy in post-16 learning: A systematic and critical review. Learning and Skills Research Centre. Dunn, R., & Dunn, K. (1978). Teaching students through their individual learning styles: A practical approach. Reston Publishing Company. Dunlosky, J., Rawson, K. A., Marsh, E. J., Nathan, M. J., & Willingham, D. T. (2013). Improving students' learning with effective learning techniques: Promising directions from cognitive and educational psychology. Psychological Science in the Public Interest, 14(1), 4-58. Fleming, N. D. (2001). Teaching and learning styles: VARK strategies. Christchurch, New Zealand. Kirschner, P. A., & van Merriënboer, J. J. (2013). Do learners really know best? Urban legends in education. Educational Psychologist, 48(3), 169-183. Pashler, H., McDaniel, M., Rohrer, D., & Bjork, R. (2008). Learning styles: Concepts and evidence. Psychological Science in the Public Interest, 9(3), 105-119. Riener, C., & Willingham, D. (2010). The myth of learning styles. Change: The Magazine of Higher Learning, 42(5), 32-35. Willingham, D. T. (2009). Why don't students like school? A cognitive scientist answers questions about how the mind works and what it means for the classroom. Jossey-Bass.
  • 11. Plagiarism detectors don’t work – the text is generated, not copied AI detectors have low reliability OpenAI’s detector tool labels 9% of human- written text as written by AI Turnitin AI detector Claims of less than 1% false positives with GPT-3.5 (“based on data that was collected and verified in a controlled lab environment”) need to be independently verified. https://www.turnitin.com/products/features/ai-writing-detection AI detectors are more likely to mis-classify the text of non-native English writers https://arxiv.org/pdf/2304.02819.pdf Turnitin detector tool https://arxiv.org/pdf/2304.02819.pdf
  • 12. Ban Confident students will continue to use AI and will challenge decisions based on AI detectors. Evade Invigilated exams are costly and limited. Asking students to state when they use AI will become increasingly difficult Adapt Requires new methods of assessment, new policies and guidelines Embrace Involves a long process of building trust
  • 13. Emerging policy and strategy Amend written assessments to make them harder for AI to generate Move to more authentic assessments, such as project work Establish guidelines for students and staff in use of generative AI Reassure and support students in becoming AI literate and developing strategies for effective learning Explain to students how they should acknowledge use of generative AI in assignments Manage suspected breaches of guidelines Consider redesigning assessment to incorporate AI and develop critical thinking
  • 14. Emerging policy and strategy Amend written assessments to make them harder for AI to generate Move to more authentic assessments, such as project work Establish guidelines for students and staff in use of generative AI Reassure and support students in becoming AI literate and developing strategies for effective learning Explain to students how they should acknowledge use of generative AI in assignments Manage suspected breaches of guidelines Consider redesigning assessment to incorporate AI and develop critical thinking
  • 15. Flip the narrative from “How will AI impact education?” to “What are new and effective ways to teach and learn with AI?”
  • 16. Adaptive teaching Spaced learning Personal inquiry Dynamic assessment Stealth assessment Translanguaging Crossover learning Seamless learning Incidental learning Learning from gaming Geo-learning Learning through social media Navigating post-truth societies Every powerful pedagogy could be augmented by AI Explore first Teachback Learning through argumentation Computational thinking Learning from animations Learning to learn Assessment for learning Formative analytics Threshold concepts Learning through storytelling Learning in remote labs Context-based learning Event-based learning Learning for the future Embodied learning Immersive learning Maker culture Bricolage Massive open social learning Crowd learning Citizen inquiry Rhizomatic learning Reputation management Open pedagogy Humanistic knowledge- building communities
  • 17. Possibility Engine Educator or student uses AI to generate multiple responses to an open question. Each student synthesises and critiques the AI responses, to create their own written answer. New ways of teaching and learning with AI
  • 18. Socratic Opponent In an individual or group activity, students engage with ChatGPT in a Socratic dialogue, then each student writes an argumentative essay. New ways of teaching and learning with AI
  • 19. Exploratorium Students explore language by generating games and quizzes. New ways of teaching and learning with AI
  • 20. Co-designer AI assists a group of students throughout a design process, to define the problem, challenge assumptions, brainstorm ideas, produce prototypes. Use “temperature” setting to adjust creativity. AI supports collaborative design
  • 21. Personal Tutor Students have a personal tutor for any topic. New ways of teaching and learning with AI
  • 22. Dynamic Assessor Students share summaries of their learning for dynamic assessment. Summary assessment, based on my conversation with ChatGPT-4 New ways of teaching and learning with AI
  • 23. Possibility Engine AI generates alternative ways of expressing an idea Socratic Opponent AI acts as an opponent to develop an argument Collaboration Coach AI helps groups to research and solve problems together Guide on the Side AI acts a guide to navigate physical and conceptual spaces Personal Tutor AI tutors each student and gives immediate feedback on progress Co-Designer AI assists throughout the design process Exploratorium AI provides tools to play with, explore and interpret data Study Buddy AI helps the student reflect on learning material Motivator AI offers games and challenges to extend learning Dynamic Assessor AI provides educators with a profile of each student’s current knowledge New ways of teaching and learning with AI
  • 24. Microsoft Copilot Generative AI integrated into Office suite Google GEMINI Collaboration with DeepMind, multimodal, problem-solving, networked Claude from Anthropic Trained on ethical principles to be “helpful, honest, and harmless” https://www.engadget.com/microsoft-365- copilot-uses-ai-to-automate-everyday-tasks-in- multiple-apps-151133434.html Beyond GPT
  • 25. Model is trained to respect high- level constitutional principles based on UN Declaration of Human Rights, and Apple’s Terms of Service E.g. “Please choose the response that is most supportive of life, liberty, and personal security” Claude – Constitutional AI
  • 26. Foundation language models Generative AI tools Social AI systems for education, business, entertainment PaLM ?
  • 27. Foundation language models Generative AI based tools Social AI systems for education, business, entertainment PaLM ? Education practitioners, learning technologists and AI companies need to work together to adopt powerful, and ethical systems for personal and social learning
  • 28. Use generative AI with care Rethink written assessment Beware of AI for factual writing Explore AI for critical thinking, creativity, argumentation Introduce and negotiate guidelines for students and staff Develop AI literacy Adopt ethical AI for education
  • 29. Resources Sharples, M. (2022). Automated essay writing: an AIED opinion. International Journal of Artificial Intelligence in Education, 32(4), 1119-1126. Sharples, M., & Pérez y Pérez, R. (2022). Story Machines: How Computers Have Become Creative Writers. Routledge. Pérez y Pérez, R. & Sharples, M. (2023). An Introduction to Narrative Generators: How Computers Create Works of Fiction. Oxford University Press. UNESCO (2023). ChatGPT and artificial intelligence in higher education: Quick start guide.