MIT has just announced a $1 billion plan to create a new college for AI — from technologyreview.com

Excerpt:

One of the birthplaces of artificial intelligence, MIT, has announced a bold plan to reshape its academic program around the technology. With $1 billion in funding, MIT will create a new college that combines AI, machine learning, and data science with other academic disciplines. It is the largest financial investment in AI by any US academic institution to date.

 

From this page:

The College will:

  • reorient MIT to bring the power of computing and AI to all fields of study at MIT, allowing the future of computing and AI to be shaped by insights from all other disciplines;
  • create 50 new faculty positions that will be located both within the College and jointly with other departments across MIT — nearly doubling MIT’s academic capability in computing and AI;
  • give MIT’s five schools a shared structure for collaborative education, research, and innovation in computing and AI;
  • educate students in every discipline to responsibly use and develop AI and computing technologies to help make a better world; and
  • transform education and research in public policy and ethical considerations relevant to computing and AI.

 

 
 

6 key trends to 21st century teaching — from edsurge.com

Excerpt:

It’s popular these days to complain that college teaching hasn’t changed in hundreds of years. And sure, it’s possible to find some professors on any campus holding yellowed lecture notes, or clinging to dusty chalk. But the reality is that the internet and digital technologies have already brought profound changes to instructional styles and tools in higher education.

So what are the new teaching approaches catching on at today’s campuses? And what are the broader cultural changes around college teaching?

We set out to answer those questions over the past year, with a series of articles and interviews exploring what teaching in the 21st century looks like. Some show the nuances of the challenges of teaching with technology by telling stories of innovative professors, including how a water agency official who teaches an online community college course got started in creating open educational resources when her class was incorporated into a zero-cost textbook degree program. Others dive into research on the culture of teaching, like a talk with an anthropologist studying how professors react to (and sometimes resist) research on teaching practices.

 

 

 

Tiny microbots fold like origami to travel through the human body — from digitaltrends.com by Georgina Torbet

Excerpt:

Tiny robots modeled after bacteria could be used to deliver drugs to hard to reach areas of the human body. Scientists at École polytechnique fédérale de Lausanne (EPFL) and the Swiss Federal Institute of Technology in Zurich (ETH Zurich) have developed what they call elastic microbots that can change shape depending on their environment.

 

The Lesson You Never Got Taught in School: How to Learn! — from bigthink.com by Simon Oxenham (from 2/15/13)
Psychological Science in the Public Interest evaluated ten techniques for improving learning, ranging from mnemonics to highlighting and came to some surprising conclusions.

 

Excerpts:

Practice Testing (Rating = High)
This is where things get interesting; testing is often seen as a necessary evil of education. Traditionally, testing consists of rare but massively important ‘high stakes’ assessments. There is however, an extensive literature demonstrating the benefits of testing for learning – but importantly, it does not seem necessary that testing is in the format of ‘high stakes’ assessments. All testing including ‘low stakes’ practice testing seems to result in benefits. Unlike many of the other techniques mentioned, the benefits of practice testing are not modest – studies have found that a practice test can double free recall!

Distributed Practice (Rating = High)
Have you ever wondered whether it is best to do your studying in large chunks or divide your studying over a period of time? Research has found that the optimal level of distribution of sessions for learning is 10-20% of the length of time that something needs to be remembered. So if you want to remember something for a year you should study at least every month, if you want to remember something for five years you should space your learning every six to twelve months. If you want to remember something for a week you should space your learning 12-24 hours apart. It does seem however that the distributed-practice effect may work best when processing information deeply – so for best results you might want to try a distributed practice and self-testing combo.

 

Also see:

 

 

 

 

Per Willingham (emphasis DSC):

  • Rereading is a terribly ineffective strategy. The best strategy–by far — is to self-test — which is the 9th most popular strategy out of 11 in this study.  Self-testing leads to better memory even compared to concept mapping (Karpicke & Blunt, 2011).

 

Three Takeaways from Becoming An Effective Learner:

  • Boser says that the idea that people have different learning styles, such as visual learning or verbal learning, has little scientific evidence to support it.
  • According to Boser, teachers and parents should praise their kids’ ability and effort, instead of telling them they’re smart. “When we tell people they are smart, we give them… a ‘fixed mindset,’” says Boser.
  • If you are learning piano – or anything, really – the best way to learn is to practice different composers’ work. “Mixing up your practices is far more effective,” says Boser.

 

Cumulative exams aren’t the same as spacing and interleaving. Here’s why. — from  retrievalpractice.org

Excerpts (emphasis DSC):

Our recommendations to make cumulative exams more powerful with small tweaks for you and your students:

  • Cumulative exams are good, but encourage even more spacing and discourage cramming with cumulative mini-quizzes throughout the semester, not just as an end-of-semester exam.
  • Be sure that cumulative mini-quizzes, activities, and exams include similar concepts that require careful discrimination from students, not simply related topics.
  • Make sure you are using spacing and interleaving as learning strategies and instructional strategies throughout the semester, not simply as part of assessments and cumulative exams.

Bottom line: Just because an exam is cumulative does not mean it automatically involves spacing or interleaving. Be mindful of relationships across exam content, as well as whether students are spacing their study throughout the semester or simply cramming before an exam – cumulative or otherwise.

 


From DSC:
We, like The Learning Scientists encourages us to do and even provides their own posters, should have posters with these tips on them throughout every single school and library in the country. The posters each have a different practice such as:

  • Spaced practice
  • Retrieval practice
  • Elaboration
  • Interleaving
  • Concrete examples
  • Dual coding

That said, I could see how all of that information could/would be overwhelming to some students and/or the more technical terms could bore them or fly over their heads. So perhaps we could boil down the information to feature excerpts from the top sections only that put the concepts into easier to digest words such as:

  • Practice bringing information to mind
  • Switch between ideas while you study
  • Combine words and visuals
  • Etc. 

 

Learn how to study using these practices

 

 

From DSC:
Not too long ago, I really enjoyed watching a program on PBS regarding America’s 100 most-loved books, entitled, “The Great American Read.”

 

Watch “The Grand Finale”

 

While that’s not the show I’m talking about, it got me to thinking of one similar to it — something educational, yet entertaining. But also, something more.

The program that came to my mind would be a program that’s focused on significant topics and issues within American society — offered up in a debate/presentation style format. 

For example, you could have different individuals, groups, or organizations discuss the pros and cons of an issue or topic. The show would provide contact information for helpful resources, groups, organizations, legislators, etc.  These contacts would be for learning more about a subject or getting involved with finding a solution for that problem.

For example, how about this for a potential topic: Grades or no grades?
  • What are the pros and cons of using an A-F grading system?
  • What are the benefits and issues/drawbacks with using grades? 
  • How are we truly using grades Do we use them to rank and compare individuals, schools, school systems, communities? Do we use them to “weed people out” of a program?
  • With our current systems, what “product” do we get? Do we produce game-players or people who enjoy learning? (Apologies for some of my bias showing up here! But my son has become a major game-player and, likely, so did I at his age.)
  • How do grades jibe with Individualized Education Programs (IEPs)? On one hand…how do you keep someone moving forward, staying positive, and trying to keep learning/school enjoyable yet on the other hand, how do you have those grades mean something to those who obtain data to rank school systems, communities, colleges, programs, etc.?
  • How do grades impact one’s desire to learn throughout one’s lifetime?

Such debates could be watched by students and then they could have their own debates on subjects that they propose.

Or the show could have journalists debate college or high school teams. The format could sometimes involve professors and deans debating against researchers. Or practitioners/teachers debating against researchers/cognitive psychologists. 

Such a show could be entertaining, yet highly applicable and educational. We would probably all learn something. And perhaps have our eyes opened up to a new perspective on an issue.

Or better yet, we might actually resolve some more issues and then move on to address other ones!

 

 

Guide to how artificial intelligence can change the world – Part 3 — from intelligenthq.com by Maria Fonseca and Paula Newton
This is part 3 of a Guide in 4 parts about Artificial Intelligence. The guide covers some of its basic concepts, history and present applications, possible developments in the future, and also its challenges as opportunities.

Excerpt:

Artificial intelligence is considered to be anything that gives machines intelligence which allows them to reason in the way that humans can. Machine learning is an element of artificial intelligence which is when machines are programmed to learn. This is brought about through the development of algorithms that work to find patterns, trends and insights from data that is input into them to help with decision making. Deep learning is in turn an element of machine learning. This is a particularly innovative and advanced area of artificial intelligence which seeks to try and get machines to both learn and think like people.

 

Also see:

 

Also see:

LinkedIn’s 2018 U.S. emerging jobs report — from economicgraph.linkedin.com

Excerpt (emphasis DSC):

Our biggest takeaways from this year’s Emerging Jobs Report:

  • Artificial Intelligence (AI) is here to stay. No, this doesn’t mean robots are coming for your job, but we are likely to see continued growth in fields and functions related to AI. This year, six out of the 15 emerging jobs are related in some way to AI, and our research shows that skills related to AI are starting to infiltrate every industry, not just tech. In fact, AI skills are among the fastest-growing skills on LinkedIn, and globally saw a 190% increase from 2015 to 2017.

 

 

Can space activate learning? UC Irvine seeks to find out with $67M teaching facility  — from edsurge.com by Sydney Johnson

Excerpt:

When class isn’t in session, UC Irvine’s shiny new Anteater Learning Pavillion looks like any modern campus building. There are large lecture halls, hard-wired lecture capture technology, smaller classrooms, casual study spaces and brightly colored swivel chairs.

But there’s more going on in this three-level, $67-million facility, which opened its doors in September. For starters, the space is dedicated to “active learning,” a term that often refers to teaching styles that go beyond a one-way lecture format. That could range from simply giving students a chance to pause and discuss with peers, to role playing, to polling students during class, and more.

To find out what that really looks like—and more importantly, if it works—the campus is also conducting a major study over the next year to assess active learning in the new building.

 

 

 

 

 

 

From DSC:
This is where the quizzing features/tools within a Learning Management System such as Canvas, Moodle, Blackboard Learn, etc. are so valuable. They provide students with opportunities for low-stakes (or no-stakes) practice in retrieving information and to see if they are understanding things or not. Doing such formative assessments along the way can point out areas where they need further practice, as well as areas where the students are understanding things well (and only need an occasional question or two on that item in order to reduce the effects of the forgetting curve).

 

 

 

 

Intelligent Machines: One of the fathers of AI is worried about its future — from technologyreview.com by Will Knight
Yoshua Bengio wants to stop talk of an AI arms race and make the technology more accessible to the developing world.

Excerpts:

Yoshua Bengio is a grand master of modern artificial intelligence.

Alongside Geoff Hinton and Yann LeCun, Bengio is famous for championing a technique known as deep learning that in recent years has gone from an academic curiosity to one of the most powerful technologies on the planet.

Deep learning involves feeding data to large neural networks that crudely simulate the human brain, and it has proved incredibly powerful and effective for all sorts of practical tasks, from voice recognition and image classification to controlling self-driving cars and automating business decisions.

Bengio has resisted the lure of any big tech company. While Hinton and LeCun joined Google and Facebook, respectively, he remains a full-time professor at the University of Montreal. (He did, however, cofound Element AI in 2016, and it has built a very successful business helping big companies explore the commercial applications of AI research.)

Bengio met with MIT Technology Review’s senior editor for AI, Will Knight, at an MIT event recently.

What do you make of the idea that there’s an AI race between different countries?

I don’t like it. I don’t think it’s the right way to do it.

We could collectively participate in a race, but as a scientist and somebody who wants to think about the common good, I think we’re better off thinking about how to both build smarter machines and make sure AI is used for the well-being of as many people as possible.

 

 

Alexa, get me the articles (voice interfaces in academia) — from blog.libux.co by Kelly Dagan

Excerpt:

Credit to Jill O’Neill, who has written an engaging consideration of applications, discussions, and potentials for voice-user interfaces in the scholarly realm. She details a few use case scenarios: finding recent, authoritative biographies of Jane Austen; finding if your closest library has an item on the shelf now (and whether it’s worth the drive based on traffic).

Coming from an undergraduate-focused (and library) perspective, I can think of a few more:

  • asking if there are any group study rooms available at 7 pm and making a booking
  • finding out if [X] is open now (Archives, the Cafe, the Library, etc.)
  • finding three books on the Red Brigades, seeing if they are available, and saving the locations
  • grabbing five research articles on stereotype threat, to read later

 

Also see:

 

 

 

EXCLUSIVE: Chinese scientists are creating CRISPR babies — from technologyreview.com by Antonio Regalado
A daring effort is under way to create the first children whose DNA has been tailored using gene editing.

Excerpt:

When Chinese researchers first edited the genes of a human embryo in a lab dish in 2015, it sparked global outcry and pleas from scientists not to make a baby using the technology, at least for the present.

It was the invention of a powerful gene-editing tool, CRISPR, which is cheap and easy to deploy, that made the birth of humans genetically modified in an in vitro fertilization (IVF) center a theoretical possibility.

Now, it appears it may already be happening.

 

Where some see a new form of medicine that eliminates genetic disease, others see a slippery slope to enhancements, designer babies, and a new form of eugenics. 

 

 

Combining retrieval, spacing, and feedback boosts STEM learning — from retrievalpractice.org

Punchline:
Scientists demonstrated that when college students used a quizzing program that combined retrieval practice, spacing, and feedback, exam performance increased by nearly a letter grade.

—-

Abstract
The most effective educational interventions often face significant barriers to widespread implementation because they are highly specific, resource intense, and/or comprehensive. We argue for an alternative approach to improving education: leveraging technology and cognitive science to develop interventions that generalize, scale, and can be easily implemented within any curriculum. In a classroom experiment, we investigated whether three simple, but powerful principles from cognitive science could be combined to improve learning. Although implementation of these principles only required a few small changes to standard practice in a college engineering course, it significantly increased student performance on exams. Our findings highlight the potential for developing inexpensive, yet effective educational interventions that can be implemented worldwide.

In summary, the combination of spaced retrieval practice and required feedback viewing had a powerful effect on student learning of complex engineering material. Of course, the principles from cognitive science could have been applied without the use of technology. However, our belief is that advances in technology and ideas from machine learning have the potential to exponentially increase the effectiveness and impact of these principles. Automation is an important benefit, but technology also can provide a personalized learning experience for a rapidly growing, diverse body of students who have different knowledge and academic backgrounds. Through the use of data mining, algorithms, and experimentation, technology can help us understand how best to implement these principles for individual learners while also producing new discoveries about how people learn. Finally, technology facilitates access. Even if an intervention has a small effect size, it can still have a substantial impact if broadly implemented. For example, aspirin has a small effect on preventing heart attacks and strokes when taken regularly, but its impact is large because it is cheap and widely available. The synergy of cognitive science, machine learning, and technology has the potential to produce inexpensive, but powerful learning tools that generalize, scale, and can be easily implemented worldwide.

Keywords: Education. Technology. Retrieval practice. Spacing. Feedback. Transfer of learning.

 

 

A Space for Learning: A review of research on active learning spaces — from by Robert Talbert and Anat Mor-Avi

Abstract:
Active Learning Classrooms (ALCs) are learning spaces specially designed to optimize the practice of active learning and amplify its positive effects in learners from young children through university-level learners. As interest in and adoption of ALCs has increased rapidly over the last decade, the need for grounded research in their effects on learners and schools has grown proportionately. In this paper, we review the peer-reviewed published research on ALCs, dating back to the introduction of “studio” classrooms and the SCALE-UP program up to the present day. We investigate the literature and summarize findings on the effects of ALCs on learning outcomes, student engagement, and the behaviors and practices of instructors as well as the specific elements of ALC design that seem to contribute the most to these effects. We also look at the emerging cultural impact of ALCs on institutions of learning, and we examine the drawbacks of the published research as well as avenues for potential future research in this area.

 

1: Introduction
1.1: What is active learning, and what is an active learning classroom?
Active learning is defined broadly to include any pedagogical method that involves students actively working on learning tasks and reflecting on their work, apart from watching, listening, and taking notes (Bonwell & Eison, 1991). Active learning has taken hold as a normative instructional practice in K12 and higher education institutions worldwide. Recent studies, such as the 2014 meta-analysis linking active learning pedagogies with dramatically reduced failure rates in university-level STEM courses (Freeman et al., 2014) have established that active learning drives increased student learning and engagement across disciplines, grade levels, and demographics.

As schools, colleges, and universities increasingly seek to implement active learning, concerns about the learning spaces used for active learning have naturally arisen. Attempts to implement active learning pedagogies in spaces that are not attuned to the particular needs of active learning — for example, large lecture halls with fixed seating — have resulted in suboptimal results and often frustration among instructors and students alike. In an effort to link architectural design to best practices in active learning pedagogy, numerous instructors, school leaders, and architects have explored how learning spaces can be differently designed to support active learning and amplify its positive effects on student learning. The result is a category of learning spaces known as Active Learning Classrooms (ALCs).

While there is no universally accepted definition of an ALC, the spaces often described by this term have several common characteristics:

  • ALCs are classrooms, that is, formal spaces in which learners convene for educational activities. We do not include less-formal learning spaces such as faculty offices, library study spaces, or “in-between” spaces located in hallways or foyers.
  • ALCs include deliberate architectural and design attributes that are specifically intended to promote active learning. These typically include moveable furniture that can be reconfigured into a variety of different setups with ease, seating that places students in small groups, plentiful horizontal and/or vertical writing surfaces such as whiteboards, and easy access to learning
    technologies (including technological infrastructure such as power outlets).
  • In particular, most ALCs have a “polycentric” or “acentric” design in which there is no clearly-defined front of the room by default. Rather, the instructor has a station which is either
    movable or located in an inconspicuous location so as not to attract attention; or perhaps there is no specific location for the instructor.
  • Finally, ALCs typically provide easy access to digital and analog tools for learning , such as multiple digital projectors, tablet or laptop computers, wall-mounted and personal whiteboards, or classroom response systems.

2.1: Research questions
The main question that this study intends to investigate is: What are the effects of the use of ALCs on student learning, faculty teaching, and institutional cultures? Within this broad overall question, we will focus on four research questions:

  1. What effects do ALCs have on measurable metrics of student academic achievement? Included in such metrics are measures such as exam scores, course grades, and learning gains on pre/post-test measures, along with data on the acquisition of “21st Century Skills”, which we will define using a framework (OCDE, 2009) which groups “21st Century Skills” into skills pertaining to information, communication, and ethical/social impact.
  2. What effects do ALCs have on student engagement? Specifically, we examine results pertaining to affective, behavioral, and cognitive elements of the idea of “engagement” as well as results that cut across these categories.
  3. What effect do ALCs have on the pedagogical practices and behaviors of instructors? In addition to their effects on students, we are also interested the effects of ALCs on the instructors who use them. Specifically, we are interested in how ALCs affect instructor attitudes toward and implementations of active learning, how ALCs influence faculty adoption of active learning pedagogies, and how the use of ALCs affects instructors’ general and environmental behavior.
  4. What specific design elements of ALCs contribute significantly to the above effects? Finally, we seek to identify the critical elements of ALCs that contribute the most to their effects on student learning and instructor performance, including affordances and elements of design, architecture, and technology integration.

 

Active Learning Classrooms (ALCs)

 

 

The common denominator in the larger cultural effects of ALCs and active learning on students and instructors is the notion of connectedness, a concept we have already introduced in discussions of specific ALC design elements. By being freer to move and have physical and visual contact with each other in a class meeting, students feel more connected to each other and more connected to their instructor. By having an architectural design that facilitates not only movement but choice and agency — for example, through the use of polycentric layouts and reconfigurable furniture — the line between instructor and students is erased, turning the ALC into a vessel in which an authentic community of learners can take form.

 

 

 

 

2018 Students and Technology Research Study — from library.educause.edu

Topics Covered

  • Device access, use, and importance to academic success
  • Campus Wi-Fi experiences
  • Learning management system use and satisfaction
  • Student learning environment preferences
  • Experiences with instructors and technology
  • Commuter students and internet access
  • Student online activities
  • Institutional awareness of student disability and accessibility
  • Student use and assessment of success tools

 

Looking for something?

Use the form below to search the site:

Still not finding what you're looking for? Drop a comment on a post or contact us so we can take care of it!

© 2019 | Daniel Christian