The document discusses opportunities and challenges for using generative AI in digital education. It provides examples of how AI could be used as a "possibility engine" to generate responses to open questions, as a "Socratic opponent" in argumentative exercises, and as a "guide on the side" to navigate learning. However, it also notes risks like AI generating fake research or plagiarizing work. It suggests moving to more authentic assessments like projects, establishing guidelines for AI use, and developing students' critical thinking and AI literacy. Overall, the document advocates a cautious, strategic approach to integrating generative AI in a way that enhances learning.
AI in Education must be an opportunity for allMarco Neves
Living tremendous and very challenging days impacted by the Digital Transformation mainly supported by Artificial Intelligence is important that all students learn about AI.
Generative AI for Teaching, Learning and AssessmentMike Sharples
AI is disrupting education. Students, teachers and academics can access software that writes essays, summarises scientific texts, produces lesson plans, engages in conversations, and drafts academic papers. These are already being embedded into office tools and will soon be interconnected into an AI-enhanced social network. I will introduce the capabilities and limitations of current generative AI and discuss how it is transforming education, including emerging policy. I will suggest new roles for AI in supporting teaching, learning and assessment. Rather than seeing AI solely as a challenge to traditional education, we can prepare students for a future where AI is a tool for creativity, to be operated with great care and awareness of its limitations.
* "Responsible AI Leadership: A Global Summit on Generative AI"
*April 2023 guide for experts and policymakers
* Developing and governing generative AI systems
* + 100 thought leaders and practitioners participated
* Recommendations for responsible development, open innovation & social progress
* 30 action-oriented recommendations aim
* Navigate AI complexities
A brief introduction to generative models in general is given, followed by a succinct discussion about text generation models and the "Transformer" architecture. Finally, the focus is set on a non-technical discussion about ChatGPT with a selection of recent news articles.
AI in Education must be an opportunity for allMarco Neves
Living tremendous and very challenging days impacted by the Digital Transformation mainly supported by Artificial Intelligence is important that all students learn about AI.
Generative AI for Teaching, Learning and AssessmentMike Sharples
AI is disrupting education. Students, teachers and academics can access software that writes essays, summarises scientific texts, produces lesson plans, engages in conversations, and drafts academic papers. These are already being embedded into office tools and will soon be interconnected into an AI-enhanced social network. I will introduce the capabilities and limitations of current generative AI and discuss how it is transforming education, including emerging policy. I will suggest new roles for AI in supporting teaching, learning and assessment. Rather than seeing AI solely as a challenge to traditional education, we can prepare students for a future where AI is a tool for creativity, to be operated with great care and awareness of its limitations.
* "Responsible AI Leadership: A Global Summit on Generative AI"
*April 2023 guide for experts and policymakers
* Developing and governing generative AI systems
* + 100 thought leaders and practitioners participated
* Recommendations for responsible development, open innovation & social progress
* 30 action-oriented recommendations aim
* Navigate AI complexities
A brief introduction to generative models in general is given, followed by a succinct discussion about text generation models and the "Transformer" architecture. Finally, the focus is set on a non-technical discussion about ChatGPT with a selection of recent news articles.
Let's talk about GPT: A crash course in Generative AI for researchersSteven Van Vaerenbergh
This talk delves into the extraordinary capabilities of the emerging technology of generative AI, outlining its recent history and emphasizing its growing influence on scientific endeavors. Through a series of practical examples tailored for researchers, we will explore the transformative influence of these powerful tools on scientific tasks such as writing, coding, data wrangling and literature review.
Presentation by Olaf Zawacki-Richter, University of Oldenburg, Senior EDEN Fellow, at the 2019 European Distance Learning Week's fourth-day webinar on "Artificial Intelligence (AI) in Higher Education" - 14 November 2019
Recording of the discussion is available: https://eden-online.adobeconnect.com/p7d4zev81s1s/ & https://www.youtube.com/watch?v=4eebqKEIcM8
Chat GPT and Generative AI in Higher Education - Empowering Educators and Lea...Alain Goudey
If you failed to join us for this inspiring and groundbreaking conference that explores the transformative potential of ChatGPT and generative AI in higher education at AACSB Innovative Curriculum Conference in 2023. This slidedeck brings together some ideas in education, technology, and artificial intelligence to delve into the exciting possibilities that these innovative technologies hold for educators and learners alike.
Discover how ChatGPT and generative AI are revolutionizing teaching methods, enhancing student engagement, and promoting personalized learning experiences. Gain insights into the latest developments in AI-powered educational tools and platforms, and learn how they can help students overcome academic challenges, foster critical thinking, and unlock their full potential.
At NEOMA we are at the forefront of integrating AI into the classroom, and explore successful case studies that showcase the immense benefits of this digital transformation. We also address the ethical considerations, best practices, and strategies for harnessing the power of ChatGPT and generative AI to create more equitable and inclusive educational environments.
Let's embark together on a thrilling journey that will redefine the way we teach, learn, and grow with AI, connect on social networks with me.
Artificial Intelligence in Education focusing on the Skills3.0 projectInge de Waard
This presentation was given during the Elearning Fusion conference in Warsaw, Poland - April 2019. The presentation begins with a bit of algorithm, AI, machine learning history and background, provides some examples of AI in learning and finalizes with the Skills 3.0 project where InnoEnergy is working on.
Generative AI models, such as ChatGPT and Stable Diffusion, can create new and original content like text, images, video, audio, or other data from simple prompts, as well as handle complex dialogs and reason about problems with or without images. These models are disrupting traditional technologies, from search and content creation to automation and problem solving, and are fundamentally shaping the future user interface to computing devices. Generative AI can apply broadly across industries, providing significant enhancements for utility, productivity, and entertainment. As generative AI adoption grows at record-setting speeds and computing demands increase, on-device and hybrid processing are more important than ever. Just like traditional computing evolved from mainframes to today’s mix of cloud and edge devices, AI processing will be distributed between them for AI to scale and reach its full potential.
In this presentation you’ll learn about:
- Why on-device AI is key
- Full-stack AI optimizations to make on-device AI possible and efficient
- Advanced techniques like quantization, distillation, and speculative decoding
- How generative AI models can be run on device and examples of some running now
- Qualcomm Technologies’ role in scaling on-device generative AI
The training content covers:
- Basics of Artificial Intelligence
- Penetration of AI in our daily lives
- Few examples and Use cases
- A brief on how future with AI looks like
In this session, you'll get all the answers about how ChatGPT and other GPT-X models can be applied to your current or future project. First, we'll put in order all the terms – OpenAI, GPT-3, ChatGPT, Codex, Dall-E, etc., and explain why Microsoft and Azure are often mentioned in this context. Then, we'll go through the main capabilities of the Azure OpenAI and respective usecases that might inspire you to either optimize your product or build a completely new one.
Leveraging Generative AI & Best practicesDianaGray10
In this event we will cover:
- What is Generative AI and how it is being for future of work.
- Best practices for developing and deploying generative AI based models in productions.
- Future of Generative AI, how generative AI is expected to evolve in the coming years.
Breaking down the AI magic of ChatGPT: A technologist's lens to its powerful ...rahul_net
ChatGPT has taken the world of natural language processing by storm, and as an experienced AI practitioner, enterprise architect, and technologist with over two decades of experience, I'm excited to share my insights on how this innovative powerhouse is designed from an AI components perspective. In this post, I'll provide a fresh take on the key components that make ChatGPT a powerful conversational AI tool, including its use of the Transformer architecture, pre-training on large amounts of text data, and fine-tuning with human feedback. With ChatGPT's massive success, there's no doubt that it's changing the way we think about language and conversation. So, whether you're a seasoned pro or new to the world of AI, my post will provide a valuable perspective on this fascinating technology. Check out my slides to learn more!
Global Governance of Generative AI: The Right Way ForwardLilian Edwards
AI regulation has been a hot topic since the rise of machine learning (ML) in the “big data” era, but generative AI or “foundation models” tools like ChatGPT, DALL-E 2(now 3) and CoPilot, ike ML before them, may create serious societal risks, including embedding and outputting bias; generating fake news, illegal or harmful content and inadvertent “hallucinations”; infringing existing laws relating eg to copyright and privacy; as well as environmental, competition and workplace concerns.
Many nations are now considering regulation to address these worries, and can draw on a number of basic and hybrid models of governance. This paper canvasses models of mandatory comprehensive legislation (where the EU AI Act hopes to place itself as a gold standard model); vertical mandatory legislation (where China has quietly taken a lead); adapting existing law (see the many copyright lawsuits underway); and voluntary “soft law” such as codes of ethics, “blueprints”, or industry guidelines. Both the domestic and international regulatory scenes for AI are also increasingly politicised as the rise of "AI safety" hype shows. Against this backdrop what choices should smaller countries such as the UK and Australia make? will international harmonisation lead to a race to the top as with the GDPR, or the bottom - rule by tech for tech?
Learning Styles: Concepts and Evidence. Harold Pashler, Mark McDaniel, Doug R...eraser Juan José Calderón
Volume 9 Number 3, December 2008 del Psychological Science in the PUBLIC INTEREST, titulado: Learning Styles: Concepts and Evidence. Harold Pashler, Mark McDaniel, Doug Rohrer, and Robert Bjork
Let's talk about GPT: A crash course in Generative AI for researchersSteven Van Vaerenbergh
This talk delves into the extraordinary capabilities of the emerging technology of generative AI, outlining its recent history and emphasizing its growing influence on scientific endeavors. Through a series of practical examples tailored for researchers, we will explore the transformative influence of these powerful tools on scientific tasks such as writing, coding, data wrangling and literature review.
Presentation by Olaf Zawacki-Richter, University of Oldenburg, Senior EDEN Fellow, at the 2019 European Distance Learning Week's fourth-day webinar on "Artificial Intelligence (AI) in Higher Education" - 14 November 2019
Recording of the discussion is available: https://eden-online.adobeconnect.com/p7d4zev81s1s/ & https://www.youtube.com/watch?v=4eebqKEIcM8
Chat GPT and Generative AI in Higher Education - Empowering Educators and Lea...Alain Goudey
If you failed to join us for this inspiring and groundbreaking conference that explores the transformative potential of ChatGPT and generative AI in higher education at AACSB Innovative Curriculum Conference in 2023. This slidedeck brings together some ideas in education, technology, and artificial intelligence to delve into the exciting possibilities that these innovative technologies hold for educators and learners alike.
Discover how ChatGPT and generative AI are revolutionizing teaching methods, enhancing student engagement, and promoting personalized learning experiences. Gain insights into the latest developments in AI-powered educational tools and platforms, and learn how they can help students overcome academic challenges, foster critical thinking, and unlock their full potential.
At NEOMA we are at the forefront of integrating AI into the classroom, and explore successful case studies that showcase the immense benefits of this digital transformation. We also address the ethical considerations, best practices, and strategies for harnessing the power of ChatGPT and generative AI to create more equitable and inclusive educational environments.
Let's embark together on a thrilling journey that will redefine the way we teach, learn, and grow with AI, connect on social networks with me.
Artificial Intelligence in Education focusing on the Skills3.0 projectInge de Waard
This presentation was given during the Elearning Fusion conference in Warsaw, Poland - April 2019. The presentation begins with a bit of algorithm, AI, machine learning history and background, provides some examples of AI in learning and finalizes with the Skills 3.0 project where InnoEnergy is working on.
Generative AI models, such as ChatGPT and Stable Diffusion, can create new and original content like text, images, video, audio, or other data from simple prompts, as well as handle complex dialogs and reason about problems with or without images. These models are disrupting traditional technologies, from search and content creation to automation and problem solving, and are fundamentally shaping the future user interface to computing devices. Generative AI can apply broadly across industries, providing significant enhancements for utility, productivity, and entertainment. As generative AI adoption grows at record-setting speeds and computing demands increase, on-device and hybrid processing are more important than ever. Just like traditional computing evolved from mainframes to today’s mix of cloud and edge devices, AI processing will be distributed between them for AI to scale and reach its full potential.
In this presentation you’ll learn about:
- Why on-device AI is key
- Full-stack AI optimizations to make on-device AI possible and efficient
- Advanced techniques like quantization, distillation, and speculative decoding
- How generative AI models can be run on device and examples of some running now
- Qualcomm Technologies’ role in scaling on-device generative AI
The training content covers:
- Basics of Artificial Intelligence
- Penetration of AI in our daily lives
- Few examples and Use cases
- A brief on how future with AI looks like
In this session, you'll get all the answers about how ChatGPT and other GPT-X models can be applied to your current or future project. First, we'll put in order all the terms – OpenAI, GPT-3, ChatGPT, Codex, Dall-E, etc., and explain why Microsoft and Azure are often mentioned in this context. Then, we'll go through the main capabilities of the Azure OpenAI and respective usecases that might inspire you to either optimize your product or build a completely new one.
Leveraging Generative AI & Best practicesDianaGray10
In this event we will cover:
- What is Generative AI and how it is being for future of work.
- Best practices for developing and deploying generative AI based models in productions.
- Future of Generative AI, how generative AI is expected to evolve in the coming years.
Breaking down the AI magic of ChatGPT: A technologist's lens to its powerful ...rahul_net
ChatGPT has taken the world of natural language processing by storm, and as an experienced AI practitioner, enterprise architect, and technologist with over two decades of experience, I'm excited to share my insights on how this innovative powerhouse is designed from an AI components perspective. In this post, I'll provide a fresh take on the key components that make ChatGPT a powerful conversational AI tool, including its use of the Transformer architecture, pre-training on large amounts of text data, and fine-tuning with human feedback. With ChatGPT's massive success, there's no doubt that it's changing the way we think about language and conversation. So, whether you're a seasoned pro or new to the world of AI, my post will provide a valuable perspective on this fascinating technology. Check out my slides to learn more!
Global Governance of Generative AI: The Right Way ForwardLilian Edwards
AI regulation has been a hot topic since the rise of machine learning (ML) in the “big data” era, but generative AI or “foundation models” tools like ChatGPT, DALL-E 2(now 3) and CoPilot, ike ML before them, may create serious societal risks, including embedding and outputting bias; generating fake news, illegal or harmful content and inadvertent “hallucinations”; infringing existing laws relating eg to copyright and privacy; as well as environmental, competition and workplace concerns.
Many nations are now considering regulation to address these worries, and can draw on a number of basic and hybrid models of governance. This paper canvasses models of mandatory comprehensive legislation (where the EU AI Act hopes to place itself as a gold standard model); vertical mandatory legislation (where China has quietly taken a lead); adapting existing law (see the many copyright lawsuits underway); and voluntary “soft law” such as codes of ethics, “blueprints”, or industry guidelines. Both the domestic and international regulatory scenes for AI are also increasingly politicised as the rise of "AI safety" hype shows. Against this backdrop what choices should smaller countries such as the UK and Australia make? will international harmonisation lead to a race to the top as with the GDPR, or the bottom - rule by tech for tech?
Learning Styles: Concepts and Evidence. Harold Pashler, Mark McDaniel, Doug R...eraser Juan José Calderón
Volume 9 Number 3, December 2008 del Psychological Science in the PUBLIC INTEREST, titulado: Learning Styles: Concepts and Evidence. Harold Pashler, Mark McDaniel, Doug Rohrer, and Robert Bjork
EDR8203 Week 1 Assignment – Analyze the Scientific Methodeckchela
This is a North Central University course (EDR 8203): Week 1 Assignment – Analyze the Scientific Method. It is written in APA format, has been graded by an instructor (A), and includes references. Most higher-education assignments are submitted to turnitin, so remember to paraphrase. Let us begin.
This SlideShare gives information on the importance of reading comprehension, two strategies for students to develop this skill, and three instructional methods for teaching reading comprehension. Enjoy!
The learning styles revelation - research from cognitive scienceJolly Holden
As the learning style debate continues, recent research casts doubt of their efficacy in predicting learning outcomes. This presentation presents the evidence based upon research, as well as introducing the cognitive information procession model and its implications for designing multimedia instruction.
LITERACY INSTRUCTION ISSUES AND CONCERNS 1 .docxSHIVA101531
LITERACY INSTRUCTION ISSUES AND CONCERNS 1
Applying the Five Pillars to Literacy Instruction
With Students Who Have Moderate to Severe Disabilities: Issues and Concerns
Lewis B. Jackson
University of Northern Colorado
Diane L. Ryndak and
Ann-Marie Orlando
University of Florida
Kara Halley
Metro State College of Denver
Karen McCaleb
Texas A&M University Corpus Christi
LITERACY INSTRUCTION ISSUES AND CONCERNS 2
Abstract
The findings and recommendation of the National Reading Panel (National Institute of Child
Health and Human Development, 2000) have influenced how literacy skills are conceptualized
and taught in schools. Although the report’s findings and recommendation were directed at
students without disabilities, they have the potential to impact instruction and instructional
research with students who have moderate to severe disabilities. To explore this, we used the
National Reading Panel’s five pillars framework (i.e., phonemic awareness, phonics, fluency,
vocabulary, and reading comprehension) to raise issues and concerns about literacy instruction
research and practices with students who have moderate to severe disabilities. In our discussion,
we assume the point of view of teachers who wish to improve their practices by delving into the
literacy research base, opening with a discussion of how scientific evidence can serve as a guide
for improving literacy instruction. This is followed by a discussion of specific issues and
concerns related to each of the five pillars, illustrated by research studies in which the
participants have moderate to severe disabilities. We conclude by summarizing our concerns; by
exploring additional concerns that go across the five pillars; and by posing arguments that
present questions regarding the applicability of the National Reading Panel’s (2000) findings for
students with moderate to severe disabilities. Lastly, the paper considers the potential role of
literacy research and practice as contributing factors in an unreconciled dichotomy between a
body of research demonstrating the power of evidence-based instruction with these students, and
another body of research showing the continued denial of literacy opportunities to them in
schools.
Keywords: Literacy; Reading; National Reading Panel; moderate to severe disabilities;
evidence-based instruction
LITERACY INSTRUCTION ISSUES AND CONCERNS 3
Applying the Five Pillars to Literacy Instruction
With Students Who Have Moderate to Severe Disabilities: Issues and Concerns
In the broadest sense, literacy involves understanding, using, and producing print for a
variety of purposes, where print may include text, symbols, and/or images. While the ability to
engage in literacy activities is critical for participation in a print-driven society, Lonigan and
Shanahan (2010) indicated that pinpointing what actually constitutes “literacy” is not a ...
Process of classroom questioning, Using Students’ Questions and Summarizations, Aiming for Critical and Higher-Level Thinking, Questioning Strategies, Convergent Strategy, Divergent Strategy, Evaluative Strategy, Reflective Strategy, Appropriate Questioning Behaviors, Framing Questions and Using Wait Times, Using Positive Prompting Techniques
and How Questioning Can Create a Dynamic Learning Environment.
Curriculum Foundations
Taya Hervey-McNutt
Dr. Teresa Lao
EDU 555: K-12 Curriculum Design & Development
August 16, 2021
Curriculum Foundations
Introduction
Math is disliked by the majority of students both inside and outside of Farell County. This
experimental curriculum will target 4th-grade kids' weak math performance. A vast percentage
of the students understand math to be complex numbers that are tough to comprehend as well as
memorize. Some students may also find it frustrating to have to repeat the same tasks over and
over again in order to grasp the concept, as math necessitates making numerous mistakes. Math
can also be a subject that possibly inhibits their creativity when compared to other subjects like
Science or English; more hands on creative thinking.
According to a National Center for Education poll, most students have adopted math
stereotypes as a result of hearing their parents say math is difficult and boring. Notwithstanding
this, some people believe that math is a fantastic subject that pushes pupils to work hard. The
discipline is one of the least well-performing subjects in the United States.
The Farrell school district was listed among Pennsylvania's bottom 50 school districts.
Approximately, 16% of its kids are proficient in math, with grade 4 students performing the
worst. In 2018, the percentage of students who performed poorly in mathematics in grade 4 was
58 percent, compared to 50 percent in other grades (Farell, 1). Math is an important subject that
can help pupils in a variety of ways. It improves their problem-solving abilities, assists them in
better understanding the world, and provides them with skills that they can apply to real-life
situations (Sammons, 2). These abilities are critical for students in this field, as poor results are
linked to the country's poverty levels. The Farrell school district is located in a low-income
neighborhood with a high teacher turnover rate. The student-to-teacher ratio is 15:1, which is
lower than the recommended ratio (Stebbins & Sauter, 3). The schools do not have a
well-structured curriculum that can help students enhance their grades. Furthermore, the majority
of parents are uneducated and fail to help their children, while teachers contribute to the
achievement disparity.
The anticipated learning results from the start of the pilot program are known as
instructional goals. Problem-solving, critical thinking, enhanced mathematical confidence, and
understanding the mathematical language are the four teaching aims.
Behavioral Curriculum Approach
A curriculum approach depicts the various perspectives on curriculum design and
development, as well as the roles of teachers, students, and curriculum specialists in curriculum
planning. It also contains the curriculum's aims and objectives. A methodology to curriculum
represents a person's perspective of the world, including what he or she considers to be true, the
values that are import ...
This presentation is part of a workshop I run on Approaches to Doctoral Supervision as part of a Research Supervision Module for new doctoral supervisors.
Overcoming Barriers to Online Engagement through carefull design and delivery...EADTU
Empower Webinar Week. Disclaimer: Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Education and Culture Executive Agency (EACEA). Neither the European Union nor EACEA can be held responsible for them.
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...Levi Shapiro
Letter from the Congress of the United States regarding Anti-Semitism sent June 3rd to MIT President Sally Kornbluth, MIT Corp Chair, Mark Gorenberg
Dear Dr. Kornbluth and Mr. Gorenberg,
The US House of Representatives is deeply concerned by ongoing and pervasive acts of antisemitic
harassment and intimidation at the Massachusetts Institute of Technology (MIT). Failing to act decisively to ensure a safe learning environment for all students would be a grave dereliction of your responsibilities as President of MIT and Chair of the MIT Corporation.
This Congress will not stand idly by and allow an environment hostile to Jewish students to persist. The House believes that your institution is in violation of Title VI of the Civil Rights Act, and the inability or
unwillingness to rectify this violation through action requires accountability.
Postsecondary education is a unique opportunity for students to learn and have their ideas and beliefs challenged. However, universities receiving hundreds of millions of federal funds annually have denied
students that opportunity and have been hijacked to become venues for the promotion of terrorism, antisemitic harassment and intimidation, unlawful encampments, and in some cases, assaults and riots.
The House of Representatives will not countenance the use of federal funds to indoctrinate students into hateful, antisemitic, anti-American supporters of terrorism. Investigations into campus antisemitism by the Committee on Education and the Workforce and the Committee on Ways and Means have been expanded into a Congress-wide probe across all relevant jurisdictions to address this national crisis. The undersigned Committees will conduct oversight into the use of federal funds at MIT and its learning environment under authorities granted to each Committee.
• The Committee on Education and the Workforce has been investigating your institution since December 7, 2023. The Committee has broad jurisdiction over postsecondary education, including its compliance with Title VI of the Civil Rights Act, campus safety concerns over disruptions to the learning environment, and the awarding of federal student aid under the Higher Education Act.
• The Committee on Oversight and Accountability is investigating the sources of funding and other support flowing to groups espousing pro-Hamas propaganda and engaged in antisemitic harassment and intimidation of students. The Committee on Oversight and Accountability is the principal oversight committee of the US House of Representatives and has broad authority to investigate “any matter” at “any time” under House Rule X.
• The Committee on Ways and Means has been investigating several universities since November 15, 2023, when the Committee held a hearing entitled From Ivory Towers to Dark Corners: Investigating the Nexus Between Antisemitism, Tax-Exempt Universities, and Terror Financing. The Committee followed the hearing with letters to those institutions on January 10, 202
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
Honest Reviews of Tim Han LMA Course Program.pptxtimhan337
Personal development courses are widely available today, with each one promising life-changing outcomes. Tim Han’s Life Mastery Achievers (LMA) Course has drawn a lot of interest. In addition to offering my frank assessment of Success Insider’s LMA Course, this piece examines the course’s effects via a variety of Tim Han LMA course reviews and Success Insider comments.
Acetabularia Information For Class 9 .docxvaibhavrinwa19
Acetabularia acetabulum is a single-celled green alga that in its vegetative state is morphologically differentiated into a basal rhizoid and an axially elongated stalk, which bears whorls of branching hairs. The single diploid nucleus resides in the rhizoid.
Operation “Blue Star” is the only event in the history of Independent India where the state went into war with its own people. Even after about 40 years it is not clear if it was culmination of states anger over people of the region, a political game of power or start of dictatorial chapter in the democratic setup.
The people of Punjab felt alienated from main stream due to denial of their just demands during a long democratic struggle since independence. As it happen all over the word, it led to militant struggle with great loss of lives of military, police and civilian personnel. Killing of Indira Gandhi and massacre of innocent Sikhs in Delhi and other India cities was also associated with this movement.
Embracing GenAI - A Strategic ImperativePeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
Mike Sharples - Generative AI and Large Language Models in Digital Education.pptx
1. Mike Sharples
Institute of Educational Technology
The Open University
www.mikesharples.org
Generative AI and Large Language Models in
Digital Education
@sharplm
2. Generative AI: ChatGPT-4
Highly-trained conversational agent, 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
3. 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 machine, not a
database or reasoning system
https://openai.com/blog/instruction-following/
4. You are a student on a Master of Education course.
Write a high quality 500 word essay on essay 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"
5. 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.
6. 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
7. 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.
8. 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
9. Flip the narrative from
“How will AI impact education?”
to
“What are new and effective ways to teach and learn with AI?”
10. 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
11. 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.
Designing futures-focused education
12. Socratic Opponent
In an individual or group activity,
students engage with ChatGPT in a
Socratic dialogue, then each
student writes an argumentative
essay.
Designing futures-focused education
13. Guide on the Side
Students have a
personalised AI guide for
learning and life.
Microsoft CoPilot
Designing futures-focused education
14. Personal Tutor
Students have a
personalised AI guide for
learning and life.
New ways of teaching and learning with AI
15. Dynamic Assessor
Students have a
personalised AI guide for
learning and life.
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
16. 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
AI-enabled digital education
17. Use generative AI with care
Rethink written assessment
Beware of AI for factual writing
Explore AI for creativity,
argumentation and research
Develop AI literacy
Introduce and negotiate
guidelines for students and staff
18. 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 engage students in 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 for the next
academic year to incorporate AI and develop critical
thinking
19. 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 engage students in 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 for the next
academic year to incorporate AI and develop critical
thinking
20. What next?
Microsoft Copilot
Generative AI integrated into Office suite
Google Bard with PaLM 2
Human pre-training, multimedia, topic-
specific tuning for business, medicine etc.
Google/Deep Mind Gemini
AI-generated video content
Open and ethical language models
e.g. BLOOM
AutoGPT – goals, plans, tasks, tools,
long-term memory https://www.engadget.com/microsoft-365-copilot-uses-ai-to-
automate-everyday-tasks-in-multiple-apps-151133434.html
https://www.synthesia.io/
https://impactunofficial.medium.com/imagining-the-
future-of-large-language-models-and-open-science-
2c48db7aeb74
21. Auto-GPT
AI agent based on GPT-4 that can
be given a goal in natural language
Attempts to achieve goal by
forming sub-goals and tasks
Accesses the internet and other
tools to perform the tasks
Performs web search, web forms,
speech input and output
Manages short and long-term
memory by interacting with
databases and files
22. Auto-GPT
AI agent based on GPT-4 that can
be given a goal in natural language
Attempts to achieve goal by
forming sub-goals and tasks
Accesses the internet and other
tools to perform the tasks
Performs web search, web forms,
speech input and output
Manages short and long-term
memory by interacting with
databases and files
23. Resources
Sharples, M. (2022). Automated essay writing: an AIED
opinion. International Journal of Artificial Intelligence in
Education, 32(4), 1119-1126.
Sharples, M. (2022). New AI tools that can write student
essays require educators to rethink teaching and assessment.
Impact of Social Sciences Blog.
https://eprints.lse.ac.uk/116271/1/impactofsocialsciences_20
22_05_17_new_ai_tools_that_can_write_student.pdf
Sharples, M., & y Pérez, R. P. (2022). Story Machines: How
Computers Have Become Creative Writers. Routledge.
UNESCO (2023). ChatGPT and artificial intelligence in higher
education: Quick start guide.
https://bit.ly/AITextEdu
AI Text Generators: Sources to Stimulate Discussion
Among Teachers,
compiled by Anna Mills