Maya Bodnick, a student at Harvard University, conducted an experiment to determine if GPT-4, an AI language model, was capable of passing college exams in the humanities and social sciences. Bodnick had GPT-4 write seven essays on topics such as economic concepts, presidentialism in Latin America, and a literary analysis. She then submitted the essays to professors for grading, without revealing whether they were written by herself or GPT-4. The results were impressive, with GPT-4 receiving grades ranging from A to B-. It achieved an average GPA of 3.57, which Bodnick called “respectable.” She noted that GPT-4 wrote all the essays based on the given prompts.
Bodnick disclosed that she submitted GPT-4’s answers without any edits, but with two exceptions. First, she combined multiple responses to meet the word count requirement, as GPT-4 could only generate up to 750 words at a time. Second, she asked the evaluators to disregard any missing citations that GPT-4 couldn’t provide, which would normally be essential for academic work. The evaluators praised GPT-4’s essays, commenting on their clarity, well-structured arguments, and detailed analysis. Only one essay received a lower grade, with the evaluator noting a flowery writing style and a lack of consideration for positive aspects of presidentialism and economic factors.
Bodnick believes that GPT-4’s performance suggests AI-generated essays could receive favorable grades at most universities, though possibly lower at institutions such as Princeton or UC Berkeley. She suggests that AI technology could revolutionize the teaching and learning methods in the humanities and social sciences. Cheating on essays has become easier, and with advancements in technology, including citation capabilities, it may become even more challenging to detect plagiarism.
As for the future, Bodnick questions the effectiveness of text detection systems, as OpenAI’s detector was withdrawn due to accuracy issues. She suggests that exams should involve personal conversations to mitigate concerns about AI writing essays. The fact that GPT-4 passed her exams hints at potential developments in Bodnick’s future field.professional field.
Caltech’s Division of Physics, Mathematics and Astronomy and The Feynman Lectures Website have released a new, modern online edition of the Feynman Lectures on Physics.
This edition has been designed for ease of reading on devices of any size or shape; text, figures and equations can all be zoomed without degradation.
This HTML5-based edition features LaTeX equations rendered by MathJax JavaScript, and scalable vector graphic (SVG) figures. Your browser must support javascript and permit scripts from mathjax.org. LocalStorage must be enabled. We recommend using a modern browser; some older browsers may not display this edition correctly. PNG figures (that degrade when scaled) may be served to browsers that do not support SVG. We do not support versions of Internet Explorer older than 8.0. For information about MathJax features and accessibility options, right-click on any display equation.
The recent emergence of Massive Open Online Courses, commonly known as MOOCs, is revolutionizing the online education world and is having a profound impact on higher education. With the growing adoption of MOOCs, the number of MOOC providers has also increased many folds. Below is a comprehensive and up-to-date list of MOOC providers; might be helpful to all interested.
Una de las nuevas metodologías de aprendizaje colaborativo está tomando fuerza a nivel mundial mi experiencia en estos cursos son muy didacticos, excelentes videos de apoyo y bien documentados.
Hawking has given many lectures to the general public. Below are some of the more recent public lectures. Included with these lectures is a Glossary of some of the terms used.
Into a Black Hole (2008): Is it possible to fall in a black hole, and come out in another universe? Can you escape from a black hole once you fall inside? What have we discovered about black holes?
The Origin of the Universe (2005): Why are we here? Where did we come from? The answer generally given was that humans were of comparatively recent origin, because it must have been obvious, even at early times, that the human race was improving in knowledge and technology. So it can't have been around that long, or it would have progressed even more.
Godel and the End of Physics (2002): How far can we go in our search for understanding and knowledge? Will we ever find a complete form of the laws of nature - a set of rules that in principle at least enable us to predict the future to an arbitrary accuracy, knowing the state of the universe at one time? A qualitative understanding of the laws has been the aim of philosophers and scientists, from Aristotle onwards.
Space and Time Warps (1999): In science fiction, space and time warps are a commonplace. They are used for rapid journeys around the galaxy, or for travel through time. But today's science fiction, is often tomorrow's science fact. So what are the chances for space and time warps?
Does God Play Dice (1999): Can predict the future, or is it arbitrary and random? In ancient times, the world must have seemed pretty arbitrary. Disasters such as floods or diseases must have seemed to happen without warning or apparent reason. Primitive people attributed such natural phenomena, to a pantheon of gods and goddesses, who behaved in a capricious and whimsical way. There was no way to predict what they would do, and the only hope was to win favour by gifts or actions.
The Beginning of Time (1996): Has time itself a beginning, and will it have an end? All the evidence seems to indicate, that the universe has not existed forever, but that it had a beginning, about 15 billion years ago. This is probably the most remarkable discovery of modern cosmology. Yet it is now taken for granted. We are not yet certain whether the universe will have an end.
Life in the Universe (1996): Speculations about how life has developed in the universe, and in particular, the development of intelligent life.
From massive open online courses (MOOCs) that are delivered to tens of thousands around the globe to adaptive digital tools that can improve outcomes by providing tailored learning experiences as well as mapping a student’s individual progress at every juncture, technology is transforming the 21st century student.
Classrooms haven't changed much in the past few centuries. Students attend class, take notes and do their homework. The teacher lectures and once in a while administers a test. Students get their grades and move on to the next topic. By and large, students—especially the most disadvantaged ones—attend the school or university closest to their home, regardless of its quality.
These routines are starting to change. In a small but growing number of schools, students watch lectures online and come to class prepared to tackle assignments and collaborate with teachers and peers. They interact with computer programs that allow them to work at their own pace, regardless of what the rest of the class is doing. Teachers rely on those same programs to grade tests and essays, allowing them to closely track more students at once. And local schools are no longer a pupil's only option. Start-ups and nonprofits make high-quality courses available online to anyone with an Internet connection.
What is driving this digital revolution? One factor is that schools and universities are under greater pressure than ever before. More and more students are pursuing higher levels of education at a time when budget-strapped principals and universities cannot hire the staff they need. At the same time, governments and institutions (prodded by employers) are raising standards for what students should know at every stage of school.
Software developer Mike Matas demos the first full-length interactive book for the iPad -- with clever, swipeable video and graphics and some very cool data visualizations to play with. The book is "Our Choice," Al Gore's sequel to "An Inconvenient Truth."
Free video course on Foundations of Modern Physics by Leonard Susskind of Stanford. This Stanford Continuing Studies course is a six-quarter sequence of classes exploring the essential theoretical foundations of modern physics.
This Stanford Continuing Studies course is a six-quarter sequence of classes exploring the essential theoretical foundations of modern physics. The topics covered in this course focus on classical mechanics, quantum mechanics, the general and special theories of relativity, electromagnatism, cosmology, black holes and statistical mechanics. While these courses build upon one another, each section of the course also stands on its own, and both individually and collectively they will allow the students to attain the "theoretical minnimum" for thinking intelligently about physics. Quantum theory governs the universe at its most basic level. In the first half of the 20th century physics was turned on its head by the radical discoveriies of Max Planck, Albert Einstein, Niels Bohr, Werner Heisenberg, and Erwin Schroedinger. An entire new logical and mathematical foundation - quantum mechanics - eventually replaced classical physics. This course explores the quantum world, including the particle theory of light, the Heisenberg Uncertainty Principle, and the Schroedinger Equation. The course is taught by Leonard Susskind, the Felix Bloch Professor of Physics at Stanford University.
Here is a comprehensive listing of all lectures from Dr. Susskind:
Technology can turn our entire lives into learning experiences via “socialstructed learning,” an aggregation of microlearning experiences drawn from a rich ecology of content and driven not by grades but by social and intrinsic rewards, suggests Marina Gorbis, Executive Director at the Institute for the Future.
“Today’s obsession with MOOCs is a reminder of the old forecasting paradigm: In the early stages of technology introduction we try to fit new technologies into existing social structures in ways that have become familiar to us,” she says.
What if we could access historical, artistic, demographic, environmental, architectural, and other kinds of information embedded in the real world via augmented reality devices?
“This is exactly what a project from USC and UCLA called HyperCities is doing: layering historical information on the actual city terrain. As you walk around with your cell phone, you can point to a site and see what it looked like a century ago, who lived there, what the environment was like.
“The Smithsonian’s free iPhone and iPad app, Leafsnap, responds when you take a photo of a tree leaf by instantly searching a growing library of leaf images amassed by the Smithsonian Institution.
“We are moving away from the model in which learning is organized around stable, usually hierarchical institutions (schools, colleges, universities) . … Replacing that model is a new system in which learning is best conceived of as a flow, where learning resources are not scarce but widely available, opportunities for learning are abundant, and learners increasingly have the ability to autonomously dip into and out of continuous learning flows.”
Unless you’re enrolled at one of the best online colleges or are an elite member of the science and engineering inner circle, you’re probably left out of most of the exciting research explored by the world’s greatest scientists.
But thanks to the Internet and the generosity of many universities and online colleges, you’ve now got access to the cutting edge theories and projects that are changing the world in this list below.
If you’re looking for even more amazing lectures, check out our updated list for 2012 with more talks from great minds.
International education will be more economical for the foreign students as the online education spreads around the world and fortified with accreditation issue.
The American Council on Education (ACE) has announced a wide-ranging research and evaluation effort that will examine the academic potential of massive open online courses (MOOCs).
The ACE College Credit Recommendation Service (ACE CREDIT) will evaluate for potential college credit select courses offered by Coursera, a leading provider of massive open online courses (MOOCs).
“MOOCs are an intriguing, innovative new approach that holds much promise for engaging students across the country and around the world, as well as for helping colleges and universities broaden their reach,” said ACE President Molly Corbett Broad.
Among the questions ACE will address in research undertaken in collaboration with the University of Illinois Springfield’s Center for Online Learning, Research, and Service are to what extent do MOOCs reach low-income young adult and older adult learners, what is the level of satisfaction of students enrolled in MOOCs, and do MOOCs have the potential to help lead to degrees or certificates.
Lecture is given by by Dimitar Sasselov, Harvard-Smithsonian Center for Astrophysics.
In 1543 Copernicus showed that our planet isn't the center of the universe. Centuries later, we know that just as Earth is not the center of things, the life on it is probably not unique either. Or is it? Tonight, learn how the search for "super-Earths" - rocky planets larger than our own that orbit other stars - may provide the key to answering essential questions about the origins of life here and elsewhere. You'll also hear how we face a moment of unprecedented potential - a convergence of pioneering efforts in astronomy and biology to peer into the unknown and determine how unique Earth life truly is.
his collection aims to highlight PLOS ONE's role in the emerging interdisciplinary field of synthetic biology. The collection has its roots in PLOS ONE's very first issue, which included two publications from the field and since then, the number of synthetic biology articles published by the journal has grown steadily. As the field continues to develop, this collection will be updated to include new publications, thereby tracking the evolution of this dynamic research area.
Synthetic biology occurs at the intersection of a number of traditional disciplines, including biology, chemistry, and engineering. It aims to create biological systems that can be programmed to do useful things such as producing drugs and biofuel. The interdisciplinary nature of synthetic biology can make it difficult to publish in traditional journals. PLOS ONE's broad scope, however, allows for the publication of work crossing many traditional research boundaries, making it an ideal venue for many different types of synthetic biology publications. In addition, the journal's focus on rigorous peer review without considering impact has made it possible to publish a body of articles that truly reflects the multifaceted nature of this research area.
One overarching theme of synthetic biology is standardization, which can only be achieved through concerted community effort. To this end, each article published in PLOS ONE can be the start of a lively conversation. The ability to comment on articles provides the community with a means to engage in a dialogue focused on specific articles, and the "Share this Article" feature allows readers to quickly send an article they find interesting to their entire networks, because all the content is openly accessible.
Over the recent weeks, millions of people have tried the new AI chat released by OpenAI, built on an upgrade of GPT3 (Generative Pre-trained Transformer). The tool uses a neural network to generate responses from data sourced from the internet. OpenAI, supported by Microsoft, also built and released the currently free DALL-E – an AI-generated art form.
By creating an easy user interface, the ChatGPT likely has many educators wondering about the future of learning. This platform will be rapidly improved when next-generation GPT4 models emerge, most likely early 2023 – meaning, it’s only going to get even better, much, much better.
AI already does and will continue to impact education – along with every other sector. Innovative education leaders have an opportunity (along with parallel emerging innovations in Web3) to build the foundation for the most personalized learning system we have ever seen. Using these tools, educators can design an equitable and efficient model for every learner to find purpose and agency in their lives – and the opportunity to help solve some of the world’s most pressing challenges.
AIChat Innovation
Artificial intelligence and/or machine learning are sets of code that build new understanding from existing underlying data. Unlike search engines (such as Google or Safari), AI machines can take huge amounts of data and predict, with strong accuracy, helpful and relevant responses (acknowledging here that plenty of stories came out this week of interesting responses from testing the new OpenAI release).
ChatGPT builds on the existing OpenAI platform by including responsiveness. ChatGPT remembers prior conversations so that it can build on previous responses. Vastly different from the first-generation help bots we all experience with online help desks, this step up creates a more natural, interactive and helpful conversation to support both learners and educators.
Future potential:
Personalized learning, where every student gets what they need, how they need it, and when they need it, increases chances of long-term success (i.e. family-sustaining wage, contributing citizenship, positive mental health). ChatGPT, can suggest next steps to any learning challenge at multiple levels of complexity. For example, if a student does not understand derivatives in Calculus, a simple search for “Explain derivatives using everyday terms” or “Provide step-by-step processes for solving derivative calculations” can instantly support a student where they are. As AI becomes more sophisticated, this can be in multiple modalities and media formats. The demand and evidence in support for 1:1 tutoring have risen dramatically to account for Covid losses and learning gaps. Personalized AI Tutors can address this issue.
Hundreds of millions of learners of all ages do not have access to quality education. Sophisticated AI tutors, built into simple and affordable platforms, can solve this challenge for those who have access to mobile devices. For example, students can ask for clarification on a concept they are studying and receive immediate responses via an AI tutor. Access to immediate support will help to limit and hopefully eliminate lost learning opportunities.
Through more efficiency in the learning process, and more personalization, more energy in learning spaces can be focused on purpose-driven work connected to complex and unpredictable challenges such as those described in Global Goals for Sustainable Development.
If you feed a piece of writing into ChatGPT and ask it to make recommendations for improvement, it will respond accordingly and then continue to guide the user through the revision process. Imagine formative assessment completed by ChatGPT and the time it would save educators to focus on relationships and create high engagement learning. ChatGPT can create rubrics when prompted appropriately, and then improve on these rubrics with continued questions.
The need for social-emotional and mental health support for young people is at an all time high. Just as 1:1 academic tutoring matters, so does the availability of counselors and mentors. ChatGPT, especially when combined with AR/VR technology, may serve as the front-line counselors for those who need it the most. Additionally, the use of ChatGPT could provide students with immediate access to resources for career and college planning, for seeking advice and other benefits that can come from having access to a counselor – especially given the overwhelming student numbers assigned to most school counselors.
Innovative learning experiences can take significant time (think high-quality project-based learning) to design. AI can address that challenge. Nolej, a newly launched AI platform available for beta in early 2023, can generate complete and sophisticated learning modules when fed a text, video or other media source on a topic. These modules contain tasks, assessments and eventually, AI-generated assessments to support learner growth. Future-oriented learning organizations like Sora Schools have an internal research team investigating the use of Large Language Models like ChatGPT in education. CEO Garrett Smiley says, “This has the potential to change everything. It could become a teacher’s best friend and help students create even high-quality projects. But, time will tell if that potential comes to fruition. There are still a lot of open questions.” As Seth Godin stated, “Technology begins by making old work easier, but then it requires that new work be better.”
Every educator (and possibly every human being) can benefit from a great coach. AIChat could provide that for teachers. Building on the solution introduced by Edthena last year, personalized coaching could be readily available for every educator. When schools lack coaches to support teachers, relying on virtual coaches helps all educators to receive feedback, to interact with a coach and build professional skills in an authentic way.
AIChat could act as a virtual research assistant for educators as they explore new content for courses, saving time in searching through Google and other resources. Asking AIChat to draft a lesson plan, write letters, and other communications could enable educators to redirect the time spent on these tasks toward students when AIChat is used for clerical tasks.
Adaptive. AIChat can adjust its response and information provided as it learns more from its interactions with the user. By analyzing the questions and ongoing conversations with the user, it then analyzes the data received to provide more personalized interactions that meet the specific needs and pace of each learner. This may also support learning differences by personalizing engagement by interacting with students through conversation, providing simple or complex explanations based on student needs, and chunking information and adapting learning based on a student’s input (such as explaining in more simple or more complex terms).
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All publicly funded scientific papers published in Europe could be made free to access by 2020, under a “life-changing” reform ordered by the European Union’s science chief, Carlos Moedas. The Competitiveness Council, a gathering of ministers of science, innovation, trade and industry, agreed on the target following a two-day meeting in Brussels last week.
The move means publications of the results of research supported by public and public-private funds would be freely available to and reusable by anyone. It could affect the paid-for subscription model used by many scientific journals, and undermine the common practice of releasing reports under embargo.
At present the results of some publicly funded research are not accessible to people outside universities and similar institutions without one-off payments, which means that many teachers, doctors, entrepreneurs and others do not have access to the latest scientific insights. In the UK, funding bodies generally require that researchers publish under open access terms, with open access publishing fees paid from the researcher’s grant.
The council said this data must be made accessible unless there were well-founded reasons for not doing so, such as intellectual property rights or security or privacy issues.
The changes are part of a broader set of recommendations in support of Open Science, a concept that also includes improved storage of and access to research data, Science magazine reports.
Open Science has been heavily lobbied for by the Dutch government, which currently holds the presidency of the Council of the EU, as well as by Moedas, the European commissioner for research and innovation. Moedas told a press conference: “We probably don’t realize it yet, but what the Dutch presidency has achieved is unique and huge. The commission is totally committed to help move this forward.”
Finally, all research publications free fo charge for the general public. Huge breakthrough! How will this impact: - the publishing industry? Will the combined revenue sources of the article processing fees payed by researchers and the extra, advanced digital services make up for the losses? - industry who has a new huge reservoir of knowledge freely available? - research communication? With a potentially larger audience and thus impact, will publications include extra sections to explain the findings and background in 'human' language? Should each of them include an infographic to facilitate disseminiation and uptake of the findings? - academics transitioning to industry? Will they be knowledge consultants, analyzing relevant literature and proposing an action plan as a service for industry? - ... Exciting times! Looking forward to participate in this knowledge ecosystem with AcademicLabs!
Why Is Machine Learning (CS 229) The Most Popular Course At Stanford? It turns out that artificial intelligence (AI) and the robotics that is tied to it, consists of two primary systems, control and perception.
UC San Diego is launching the first major online course that prominently features “massive open online research” (MOOR).
For Bioinformatics, UC San Diego computer science and engineering professor Pavel Pevzner and his graduate students are offering a course on Coursera that combines research with a MOOC (massive open online course) for the first time.
“All students who sign up for the course will be given an opportunity to work on specific research projects under the leadership of prominent bioinformatics scientists from different countries, who have agreed to interact and mentor their respective teams.”
“The natural progression of education is for people to make a transition from learning to research, which is a huge jump for many students, and essentially impossible for students in isolated areas,” said Ph.D. student Phillip Compeau, who helped develop the online course. “By integrating the research with an interactive text and a MOOC, it creates a pipeline to streamline this transition.”
Bioinformatics Algorithms (Part I) will run for eight weeks starting October 21, 2013, and students are now able to sign up and download some of the course materials. It is offered free of charge to everyone.
Another unique feature of the online course: Pevzner and Compeau have developed Bioinformatics Algorithms: An Active-Learning Approach, a e-book supporting the course, while Pevzner’s colleagues in Russia developed a content delivery system that integrates the e-book with hundreds of quizzes and dozens of homework problems.
The U.S.-Russian team, led by Pevzner’s foreign student Nikolay Vyahhi, also implemented the online course using the beta version of Stepic, a new, fully integrated educational platform and startup developed by Vyahhi. Stepic derives its name from the “step-by-step, epic” solution its developers delivered for electronic publishing.
The course also provides access to Rosalind, a free online resource for learning bioinformatics through problem solving. Rosalind was developed by Pevzner’s students and colleagues in San Diego and St. Petersburg with funding from the Howard Hughes Medical Institute, the Russian Ministry of Education, and Russian Internet billionaires Yuri Milner and Pavel Durov through their “Start Fellows” award. Rosalind already has over 10,000 active users worldwide.
Rosalind — named in honor of British scientist Rosalind Franklin, whose X-ray crystallography with Raymond Gosling facilitated the discovery of the DNA double helix by Watson and Crick — will grade the programming assignments. They come in the form of bioinformatics problems of growing complexity as the course progresses.
“We developed Rosalind to inspire both biologists and computer science students,” said Rosalind principal developer Vyahhi, who worked with Pevzner during the latter’s sabbatical in Russia. “The platform allows biologists to develop vital programming skills for bioinformatics at their own pace, and Rosalind can also appeal to programmers who have never been exposed to some of the exciting computational problems generated by molecular biology.”
Education in Science is a collection of resources for learners. Resources include videos and interactives that help scientific learners find out about the different fields of science and make connections to what they are learning in school, college or university.
Lessons are inquiry based and encourage exploration in life science, physical science, earth science and technology/innovation. We are at a point where almost everyone has a computer at home, each of them hooked up to enormous libraries where anyone can ask any question and be given answers.
Learn about a new "superpower" that isn't being taught in 90% of US schools.
Starring Bill Gates, Mark Zuckerberg, will.i.am, Chris Bosh, Jack Dorsey, Tony Hsieh, Drew Houston, Gabe Newell, Ruchi Sanghvi, Elena Silenok, Vanessa Hurst, and Hadi Partovi.
Directed by Leslie Chilcott. Executive producers Hadi and Ali Partovi.
Biomedical knowledge is growing exponentially. However, meta-knowledge around the data is often lacking. PubMed is a database comprising more than 21 million citations for biomedical literature from MEDLINE and additional life science journals dating back to the 1950s. To explore the use and frequency of biomarkers across human disease, researchers have recently mined PubMed for biomarker-disease associations. They ranked the top 100 linked diseases by relevance and mapped them to medical subject headings (MeSH) and, subsequently, to the Disease Ontology. To identify biomarkers for each disease, they queried Covance BioPathways, an online data resource that maps commercial biomarker assays to biological and disease pathways. They then integrated pathways-based information to describe both known and potential biomarkers, as well as disease-associated genes/proteins for select diseases (e.g., atherosclerosis and asthma). This approach identifies therapeutic areas with candidate or validated biomarkers, and highlights those areas where a paucity of biomarkers exists.
Main conclusion: Given the molecular interdependencies within a cell, a disease is rarely a consequence of a single gene abnormality, but instead reflects the perturbation of a complex network of biological and signaling pathways. The approach outlined here describes the detection and ranking of human disease based on research/clinical activity surrounding biomarkers. It also enables the identification of therapeutic areas with candidate or validated biomarkers. The strategy takes an integrative approach to identify candidate disease biomarkers by combining disease-associated genes/proteins with commercially validated assays for known biomarkers. A system-level model of disease that incorporates molecular interactions across biological and signaling pathways has been built that allowed to identify each gene/protein in the model that has an existing commercially validated assay. This strategy offers an alternative, comprehensive view of key relationships and pathway perturbations that may identify biomarkers of disease emergence or progression.
Massive Open Online Courses (MOOCs) might seem like best way to use the Internet to open up education, but you’re thinking too small. Technology can turn our entire lives into learning experiences.
Socialstructed learning is an aggregation of microlearning experiences drawn from a rich ecology of content and driven not by grades but by social and intrinsic rewards. The microlearning moment may last a few minutes, hours, or days, if you are absorbed in reading something, tinkering with something, or listening to something from which you just can’t walk away. Socialstructed learning may be the future, but the foundations of this kind of education lie far in the past. Leading philosophers of education --from Socrates to Plutarch, Rousseau to Dewey-- talked about many of these ideals centuries ago. Today, we have a host of tools to make their vision finally a reality.
Think of a simple augmented reality apps on the iPhone such as Yelp Monocle. When you point the phone’s camera toward a particular location, it displays “points of interest” in that location, such as restaurants, stores, and museums. Augmented reality -- but this is just the beginning. What if, instead of restaurant and store information, we could access historical, artistic, demographic, environmental, architectural, and other kinds of information embedded in the real world? All our cultural inheritance is only a click away.
This is exactly what a project from USC and UCLA called HyperCities is doing: layering historical information on the actual city terrain. As you walk around with your cell phone, you can point to a site and see what it looked like a century ago, who lived there, what the environment was like. Not interested in architecture, passionate about botany and landscaping instead? The Smithsonian’s free iPhone and iPad app, Leafsnap, responds when you take a photo of a tree leaf by instantly searching a growing library of leaf images amassed by the Smithsonian Institution. In seconds, it displays a likely species name along with high-resolution photographs of and information on the tree’s flowers, fruit, seeds, and bark. We are turning each pixel of our geography into a live textbook and a live encyclopedia.
So look beyond MOOCs (Massive Open Online Courses) in thinking about the future education. In our focus on MOOCs and how they are likely to disrupt existing classrooms and educational institutions, particularly colleges and universities, we are missing the much larger story. Today’s obsession with MOOCs is a reminder of the old forecasting paradigm: In the early stages of technology introduction we try to fit new technologies into existing social structures in ways that have become familiar to us.
MOOCs today are our equivalents of early TV, when TV personalities looked and sounded like radio announcers (or often were radio announcers). People are thinking the same way about MOOCs, as replacements of traditional lectures or tutorials, but in online rather than physical settings. In the meantime, a whole slew of forces is driving a much larger transformation, breaking learning (and education overall) out of traditional institutional environments and embedding it in everyday settings and interactions, distributed across a wide set of platforms and tools. They include a rapidly growing and open content commons (Wikipedia is just one example), on-demand expertise and help (from Mac Forums to Fluther, Instructables, and WikiHow), mobile devices and geo-coded information that takes information into the physical world around us and makes it available any place any time, new work and social spaces that are, in fact, evolving as important learning spaces (TechShop, Meetups, hackathons, community labs).
We are moving away from the model in which learning is organized around stable, usually hierarchical institutions (schools, colleges, universities) that, for better and worse, have served as the main gateways to education and social mobility. Replacing that model is a new system in which learning is best conceived of as a flow, where learning resources are not scarce but widely available, opportunities for learning are abundant, and learners increasingly have the ability to autonomously dip into and out of continuous learning flows.
SCIENCE has few more controversial topics than human intelligence—in particular, whether variations in it are a result of nature or nurture, and especially whether such variations differ between the sexes. The mines in this field can blow up an entire career, as Larry Summers found out in 2005 when he spoke of the hypothesis that the mathematical aptitude needed for physics and engineering, as well as for maths itself, is innately rarer in women than in men. He resigned as president of Harvard University shortly afterwards.
Khan Academy recently launched an online environment for learning to program. It offers a set of tutorials based on the JavaScript and Processing languages, and features a "live coding" environment, where the program's output updates as the programmer types.
Because my work was cited as an inspiration for the Khan system, I felt I should respond with two thoughts about learning: Programming is a way of thinking, not a rote skill. Learning about "for" loops is not learning to program, any more than learning about pencils is learning to draw.
People understand what they can see. If a programmer cannot see what a program is doing, she can't understand it. Thus, the goals of a programming system should be:
• to support and encourage powerful ways of thinking • to enable programmers to see and understand the execution of their programs
A live-coding Processing environment addresses neither of these goals. JavaScript and Processing are poorly-designed languages that support weak ways of thinking, and ignore decades of learning about learning. And live coding, as a standalone feature, is worthless. Alan Perlis wrote, "To understand a program, you must become both the machine and the program." This view is a mistake, and it is this widespread and virulent mistake that keeps programming a difficult and obscure art. A person is not a machine, and should not be forced to think like one.
How do we get people to understand programming? We change programming. We turn it into something that's understandable by people.
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