Reuters Top 100: The World’s Most Innovative Universities – 2017 — from reuters.com with thanks to eduwire for their posting on this

Excerpts:

Reuters’ annual ranking of the World’s Most Innovative Universities identifies and ranks the educational institutions doing the most to advance science, invent new technologies and power new markets and industries.

The top 10 innovative universities are:

  1. Stanford University
  2. Massachusetts Institute of Technology (MIT)
  3. Harvard University
  4. University of Pennsylvania
  5. KU Leuven
  6. KAIST
  7. University of Washington
  8. University of Michigan System
  9. University of Texas System
  10. Vanderbilt University

 

 

 

It’s Time for Student Agency to Take Center Stage — from gettingsmart.com by Marie Bjerede and Michael Gielniak

Excerpt:

Jason took ownership of his class project, exhibiting agency. Students who take ownership go beyond mere responsibility and conscientiously completing assignments. These students are focused on their learning, rather than their grade. They are genuinely interested in their work and are as likely as not to get up and work on a project on a Saturday morning, even though they don’t have to (and without considerations of extra credit.)

They complete their homework on time and may well go above and beyond, and they have interesting thoughts to add to classroom dialog. For many teachers, they are a joy to teach, but they are also the ones who may ask the hard questions and they may be quick to point out what they see as hypocrisy in the authority figures.

“Responsible” students, on the other hand, are compliant. Most teachers think they are a joy to teach. They complete their homework without fail, and pay attention and participate in class. These are the kids typically considered “good” students. They usually win most of the academic awards because they are thought of as the “best and brightest.”

Responsible students are concerned about their grades, and can be identified when they ask questions like::

  • “Will that be on the test?”
  • “How many words do I have to write?”
  • “What does it take to get an A?”

Students who take ownership, on the other hand ask questions like:

  • “There are several different viewpoints on this subject so why is that, and what does it mean?
  • “Is what you are teaching, or what is in my textbook, consistent with my research?”
  • “Why is this important?”

Compliance or agency? We need to decide.

 

 

The past decades have been the age of the responsible, compliant student. Students who used to be able to get into college and then immediately secure a good job. But the world and the workforce have changed.

 

 

 

 

 

AR and VR in STEM: The New Frontiers in Science  — from er.educause.edu by Emory Craig and Maya Georgieva

Excerpt:

Virtual and Augmented Reality are poised to profoundly transform the STEM curriculum. In this article, we offer several inspiring examples and key insights on the future of immersive learning and the sciences. Immersive technologies will revolutionize learning through experiential simulations, modelling and spatial representation of data, and a sense of presence in contextual gamification.

Understanding our place in the universe, building the next Martian Rover, designing new transportation systems, fostering sustainable communities, modeling economic stability — finding the solution for these pressing and interconnected challenges brings us to STEM and STEAM in teaching and learning. The movement behind STEAM advocates incorporating the arts and humanities to the science, technology, engineering and math curriculum.

 

 

Also see:

 

 

 

Artificial intelligence will transform universities. Here’s how. — from weforum.org by Mark Dodgson & David Gann

Excerpt:

The most innovative AI breakthroughs, and the companies that promote them – such as DeepMind, Magic Pony, Aysadi, Wolfram Alpha and Improbable – have their origins in universities. Now AI will transform universities.

We believe AI is a new scientific infrastructure for research and learning that universities will need to embrace and lead, otherwise they will become increasingly irrelevant and eventually redundant.

Through their own brilliant discoveries, universities have sown the seeds of their own disruption. How they respond to this AI revolution will profoundly reshape science, innovation, education – and society itself.

As AI gets more powerful, it will not only combine knowledge and data as instructed, but will search for combinations autonomously. It can also assist collaboration between universities and external parties, such as between medical research and clinical practice in the health sector.

The implications of AI for university research extend beyond science and technology.

When it comes to AI in teaching and learning, many of the more routine academic tasks (and least rewarding for lecturers), such as grading assignments, can be automated. Chatbots, intelligent agents using natural language, are being developed by universities such as the Technical University of Berlin; these will answer questions from students to help plan their course of studies.

Virtual assistants can tutor and guide more personalized learning. As part of its Open Learning Initiative (OLI), Carnegie Mellon University has been working on AI-based cognitive tutors for a number of years. It found that its OLI statistics course, run with minimal instructor contact, resulted in comparable learning outcomes for students with fewer hours of study. In one course at the Georgia Institute of Technology, students could not tell the difference between feedback from a human being and a bot.

 

 

Also see:

Digital audio assistants in teaching and learning — from blog.blackboard.com by Szymon Machajewski

Excerpts:

I built an Amazon Alexa skill called Introduction to Computing Flashcards. In using the skill, or Amazon Alexa app, students are able to listen to Alexa and then answer questions. Alexa helps students prepare for an exam by speaking definitions and then waiting for their identification. In addition to quizzing the student, Alexa is also keeping track of the correct answers. If a student answers five questions correctly, Alexa shares a game code, which is worth class experience points in the course gamification My Game app.

Certainly, exam preparation apps are one way to use digital assistants in education. As development and publishing of Amazon Alexa skills becomes easier, faculty will be able to produce such skills just as easily as they now create PowerPoints. Given the basic code available through Amazon tutorials, it takes 20 minutes to create a new exam preparation app. Basic voice experience Amazon Alexa skills can take as much as five minutes to complete.

Universities can publish their campus news through the Alexa Flash Briefing. This type of a skill can publish news, success stories, and other events associated with the campus.

If you are a faculty member, how can you develop your first Amazon Alexa skill? You can use any of the tutorials already available. You can also participate in an Amazon Alexa classroom training provided by Alexa Dev Days. It is possible that schools or maker spaces near you offer in-person developer sessions. You can use meetup.com to track these opportunities.

 

 

 

 

 

Some applications of VR from vrxone.com

Education
Virtual Reality to teach the skills needed for the future by enabling learners to explore, play, work as a team, compete, and be rewarded for their achievements through interactive lessons.

  • Virtual Field Trips
  • Immersive VRXOne Lab
  • VR for Arts & Design
  • Safe Laboratory Practicals through VR
  • Game based Learning
  • Geography, Marine Life VR Exploration
  • Astronomy & Space Research through VR
  • Architecture & Interiors
  • VR for Sports & Games
  • VR to improve Public Speech

Corporate Training
Virtual reality (VR) enhances traditional training methods through a new, practical and interactive approach. Improve Knowledge Retention by doing things in an immersive Environment.

* VR based Induction/ Onboarding
* Improving Health & Safety through VR
* Increase Knowledge Retention
* Hands-on VR Training Simulations
* Customer interactivity through VR
* VR to improve Marketing Strategy
* Special purpose training in VR
* High Risk Environment VR Simulation
* Critical National Infrastructure brief on VR
* VR for Business Planning

Healthcare
Virtual Reality has proven great results with 34% of Physical Health and 47% of Mental Health Improvements through various applications and learning programs.

* 360° Live streaming of Surgical Procedure
* Medical & Nursing Simulation
* Emergency Drill Scenario
* VR for pain & anxiety relief
* Assistive Technology for Special Education.
* Interactive Anatomy Lessons
* Yoga, Meditation and Recreational Therapy
* Virtual Medical Consultation
* Motivational Therapy for Aged Citizens
* VR for Medical Tourism

 

 

 

Lifeliqe Piloting Mixed Reality on Microsoft HoloLens for Grade 6-12 Classrooms — from thejournal.com by Richard Chang

Excerpt:

Using interactive 3D models and lesson plans from its app, Lifeliqe (pronounced “life like”) is now delivering educational content on two major immersive hardware platforms (Microsoft HoloLens and HTC Vive) as well as software platforms (Windows and iOS).

Students and teachers at Renton Prep Christian School in Washington state and Castro Valley Unified College in California participated in the pilot and were the first ever to try out Lifeliqe’s educational content on HoloLens during a science lesson (see video).

 

“The excitement we witnessed during the pilot shows us the great potential mixed reality has in sparking lightbulb moments.”

 

Lifeliqe is introducing pilots of mixed reality applications on Microsoft HoloLens — from lifeliqe.com

Excerpt:

Lifeliqe is thrilled to start piloting mixed reality educational scenarios for Microsoft HoloLens in grade 6-12 classrooms! The first two schools we are working with are Renton Prep in Seattle, WA and Castro Valley Unified College, CA. The students and teachers there were the first ever to try out Lifeliqe’s educational content on HoloLens during a Science lesson.

 

 

 

 

The 82 Hottest EdTech Tools of 2017 According to Education Experts — from tutora.co.uk by Giorgio Cassella

Excerpt:

If you work in education, you’ll know there’s a HUGE array of applications, services, products and tools created to serve a multitude of functions in education.

Tools for teaching and learning, parent-teacher communication apps, lesson planning software, home-tutoring websites, revision blogs, SEN education information, professional development qualifications and more.

There are so many companies creating new products for education, though, that it can be difficult to keep up – especially with the massive volumes of planning and marking teachers have to do, never mind finding the time to actually teach!

So how do you know which ones are the best?

Well, as a team of people passionate about education and learning, we decided to do a bit of research to help you out.

We’ve asked some of the best and brightest in education for their opinions on the hottest EdTech of 2017. These guys are the real deal – experts in education, teaching and new tech from all over the world from England to India, to New York and San Francisco.

They’ve given us a list of 82 amazing, tried and tested tools…


From DSC:
The ones that I mentioned that Giorgio included in his excellent article were:

  • AdmitHub – Free, Expert College Admissions Advice
  • Labster – Empowering the Next Generation of Scientists to Change the World
  • Unimersiv – Virtual Reality Educational Experiences
  • Lifeliqe – Interactive 3D Models to Augment Classroom Learning

 


 

 

 

 

Perfect marriage between universities and K12 public schools — from huffingtonpost.com by Dr. Rod Berger

 

Excerpt:

I sat down with Dr. Jeanice Kerr Swift at this year’s AASA conference in New Orleans to learn about the unique advantage of running a public school district that resides alongside one of our nation’s most prominent universities. The University of Michigan provides the district of Ann Arbor with rich partnerships that lift the learning experiences of the children in the community. Kerr Swift is delighted to have the enthusiasm of not only the University but the business community in reaching out to the students of Ann Arbor.

The implementation of real world projects matches University of Michigan scientists with teachers and students to enrich school learning environments. One example is the Woven Wind program that provides real life wind turbine applications. Students learn, and teachers have their classes bolstered by the input of advanced experimentation. Project Lead the Way is another example that is providing modules for classroom learning.

According to Jeanice Kerr Swift, technology should support and strengthen learning, not stand in the place of person-to-person engagement. Devices are there to serve and enhance, not replace teacher-student collaboration and critical thinking. Kerr Swift believes there is a balance of the “Cs” to consider: collaboration, connection, and community. If all the “Cs” are listening and working together, then a school district can thrive.

Jeanice Kerr Swift certainly makes the balance look easy and enviable in Ann Arbor Michigan.

 

 

 

 

 

The Enterprise Gets Smart
Companies are starting to leverage artificial intelligence and machine learning technologies to bolster customer experience, improve security and optimize operations.

Excerpt:

Assembling the right talent is another critical component of an AI initiative. While existing enterprise software platforms that add AI capabilities will make the technology accessible to mainstream business users, there will be a need to ramp up expertise in areas like data science, analytics and even nontraditional IT competencies, says Guarini.

“As we start to see the land grab for talent, there are some real gaps in emerging roles, and those that haven’t been as critical in the past,” Guarini  says, citing the need for people with expertise in disciplines like philosophy and linguistics, for example. “CIOs need to get in front of what they need in terms of capabilities and, in some cases, identify potential partners.”

 

 

 

Asilomar AI Principles

These principles were developed in conjunction with the 2017 Asilomar conference (videos here), through the process described here.

 

Artificial intelligence has already provided beneficial tools that are used every day by people around the world. Its continued development, guided by the following principles, will offer amazing opportunities to help and empower people in the decades and centuries ahead.

Research Issues

 

1) Research Goal: The goal of AI research should be to create not undirected intelligence, but beneficial intelligence.

2) Research Funding: Investments in AI should be accompanied by funding for research on ensuring its beneficial use, including thorny questions in computer science, economics, law, ethics, and social studies, such as:

  • How can we make future AI systems highly robust, so that they do what we want without malfunctioning or getting hacked?
  • How can we grow our prosperity through automation while maintaining people’s resources and purpose?
  • How can we update our legal systems to be more fair and efficient, to keep pace with AI, and to manage the risks associated with AI?
  • What set of values should AI be aligned with, and what legal and ethical status should it have?

3) Science-Policy Link: There should be constructive and healthy exchange between AI researchers and policy-makers.

4) Research Culture: A culture of cooperation, trust, and transparency should be fostered among researchers and developers of AI.

5) Race Avoidance: Teams developing AI systems should actively cooperate to avoid corner-cutting on safety standards.

Ethics and Values

 

6) Safety: AI systems should be safe and secure throughout their operational lifetime, and verifiably so where applicable and feasible.

7) Failure Transparency: If an AI system causes harm, it should be possible to ascertain why.

8) Judicial Transparency: Any involvement by an autonomous system in judicial decision-making should provide a satisfactory explanation auditable by a competent human authority.

9) Responsibility: Designers and builders of advanced AI systems are stakeholders in the moral implications of their use, misuse, and actions, with a responsibility and opportunity to shape those implications.

10) Value Alignment: Highly autonomous AI systems should be designed so that their goals and behaviors can be assured to align with human values throughout their operation.

11) Human Values: AI systems should be designed and operated so as to be compatible with ideals of human dignity, rights, freedoms, and cultural diversity.

12) Personal Privacy: People should have the right to access, manage and control the data they generate, given AI systems’ power to analyze and utilize that data.

13) Liberty and Privacy: The application of AI to personal data must not unreasonably curtail people’s real or perceived liberty.

14) Shared Benefit: AI technologies should benefit and empower as many people as possible.

15) Shared Prosperity: The economic prosperity created by AI should be shared broadly, to benefit all of humanity.

16) Human Control: Humans should choose how and whether to delegate decisions to AI systems, to accomplish human-chosen objectives.

17) Non-subversion: The power conferred by control of highly advanced AI systems should respect and improve, rather than subvert, the social and civic processes on which the health of society depends.

18) AI Arms Race: An arms race in lethal autonomous weapons should be avoided.

Longer-term Issues

 

19) Capability Caution: There being no consensus, we should avoid strong assumptions regarding upper limits on future AI capabilities.

20) Importance: Advanced AI could represent a profound change in the history of life on Earth, and should be planned for and managed with commensurate care and resources.

21) Risks: Risks posed by AI systems, especially catastrophic or existential risks, must be subject to planning and mitigation efforts commensurate with their expected impact.

22) Recursive Self-Improvement: AI systems designed to recursively self-improve or self-replicate in a manner that could lead to rapidly increasing quality or quantity must be subject to strict safety and control measures.

23) Common Good: Superintelligence should only be developed in the service of widely shared ethical ideals, and for the benefit of all humanity rather than one state or organization.

 

 

 

Excerpts:
Creating human-level AI: Will it happen, and if so, when and how? What key remaining obstacles can be identified? How can we make future AI systems more robust than today’s, so that they do what we want without crashing, malfunctioning or getting hacked?

  • Talks:
    • Demis Hassabis (DeepMind)
    • Ray Kurzweil (Google) (video)
    • Yann LeCun (Facebook/NYU) (pdf) (video)
  • Panel with Anca Dragan (Berkeley), Demis Hassabis (DeepMind), Guru Banavar (IBM), Oren Etzioni (Allen Institute), Tom Gruber (Apple), Jürgen Schmidhuber (Swiss AI Lab), Yann LeCun (Facebook/NYU), Yoshua Bengio (Montreal) (video)
  • Superintelligence: Science or fiction? If human level general AI is developed, then what are likely outcomes? What can we do now to maximize the probability of a positive outcome? (video)
    • Talks:
      • Shane Legg (DeepMind)
      • Nick Bostrom (Oxford) (pdf) (video)
      • Jaan Tallinn (CSER/FLI) (pdf) (video)
    • Panel with Bart Selman (Cornell), David Chalmers (NYU), Elon Musk (Tesla, SpaceX), Jaan Tallinn (CSER/FLI), Nick Bostrom (FHI), Ray Kurzweil (Google), Stuart Russell (Berkeley), Sam Harris, Demis Hassabis (DeepMind): If we succeed in building human-level AGI, then what are likely outcomes? What would we like to happen?
    • Panel with Dario Amodei (OpenAI), Nate Soares (MIRI), Shane Legg (DeepMind), Richard Mallah (FLI), Stefano Ermon (Stanford), Viktoriya Krakovna (DeepMind/FLI): Technical research agenda: What can we do now to maximize the chances of a good outcome? (video)
  • Law, policy & ethics: How can we update legal systems, international treaties and algorithms to be more fair, ethical and efficient and to keep pace with AI?
    • Talks:
      • Matt Scherer (pdf) (video)
      • Heather Roff-Perkins (Oxford)
    • Panel with Martin Rees (CSER/Cambridge), Heather Roff-Perkins, Jason Matheny (IARPA), Steve Goose (HRW), Irakli Beridze (UNICRI), Rao Kambhampati (AAAI, ASU), Anthony Romero (ACLU): Policy & Governance (video)
    • Panel with Kate Crawford (Microsoft/MIT), Matt Scherer, Ryan Calo (U. Washington), Kent Walker (Google), Sam Altman (OpenAI): AI & Law (video)
    • Panel with Kay Firth-Butterfield (IEEE, Austin-AI), Wendell Wallach (Yale), Francesca Rossi (IBM/Padova), Huw Price (Cambridge, CFI), Margaret Boden (Sussex): AI & Ethics (video)

 

 

 

Brillant Representation of Our Solar System — by Justin Van Genderen from fubiz.net

 

 

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!

© 2017 | Daniel Christian