Learning Ecosystems

How faculty can ‘click’ their way to a more inclusive classroom [Hogan & Sathy]

On 12/09/2018, in adjunct faculty, assessment, attention, Bring your own device (BYOD), colleges, community colleges, education technology, engagement / engaging students, faculty, higher education, ideas, instructional design, K-12 related, pedagogy, teachers, teaching & learning, tools, universities, by Daniel Christian

How faculty can ‘click’ their way to a more inclusive classroom — from edsurge.com by Kelly Hogan and Viji Sathy

Excerpt:

What do you think is important for an instructor to do when using classroom response systems (polling software or clickers)? Select all that apply.

A) Choose questions that most students will be able to answer correctly.

B) Vary the types of poll questions beyond multiple choice.

C) Ask students “Please discuss your answer with a neighbor.”

D) Stress that students answer questions independent of their peers.

Classroom response systems (CRS) have a mixed reputation. Studies have suggested that these tools, which allow students to respond in real time to questions provided by an instructor, can improve student learning. But other reports show that is not always the case.

Like many education tools, it depends. And in the case of clickers and other classroom polling software, it largely depends on how instructors are using them. If used thoughtfully, we’ve seen that CRSs can help facilitate active learning in a classroom. What’s more, these tools can be used to also facilitate an inclusive classroom.

What do we mean by an inclusive classroom? Faculty risk excluding certain students and impeding their ability to succeed when they aren’t intentional about design and facilitation. Inclusive course design involves more than choosing content; it also requires considering the number of assessments, opportunities for practice, the chances for students to assess their understanding of material, among other attributes.

From DSC:
First of all, an excerpt from an email from RetrievalPractice.org:

Last week, we talked about an activity we call Flash Forward. Simply ask your students these questions:

“Now that you’ve taken this class, what is one thing you want to remember 10 years from now (and why)?”

“How will you remember that one thing? What will you do to make sure you don’t forget?”

Second of all, the topic of remembering something 10 years from now (from some current learning) made me think about obtaining a long-term return on investment (ROI) from that learning.

In the online-based course that I’ve been teaching for a while now, I’m all about helping the students in my classes obtain long-term benefits from taking the class. Grades aren’t the key. The learning is the key!

The class is entitled, “Foundations of Information Technology” and I want them to be using the tools, technologies, services, and concepts (that we learned about) loooooong after they graduate from college! We work on things like RSS feeds, Twitter, LinkedIn, WordPress, building their network, building their personal brand, HTML/web design, Microsoft Excel, the Internet of Things and much more. I want them to be practicing those things, leveraging those tools, pulse-checking their surroundings, networking with others, serving others with their gifts, and building on the foundations that they put into place waaaay back in 201__.

Forecast 5.0 – The Future of Learning: Navigating the Future of Learning [Prince, Swanson, & King]

On 12/08/2018, in 21st century, adjunct faculty, algorithms, analytics, Artificial Intelligence / Machine Learning / Deep Learning, bots, change, Christian education, cognitive computing, colleges, community colleges, data mining, digital citizenship, digital learning, education, education technology, emerging technologies, formal learning, future, future of higher education, game-changing environment, higher education, human-computer interaction (HCI), ideas, instructional design, intelligent systems, intelligent tutoring, internet, leadership, learning, learning ecosystem, learning from the living [class] room, learning spaces, Mobile learning, multimedia, Natural Language Processing (NLP), online learning, online tutoring, pace of change, parents, personalized/customized learning, platforms, science, smart classrooms, social learning / networks, social media, society, sociology, student teaching/teacher education, student-related, teachers, teaching & learning, teaching online, technology (general), tools, trends, United States, universities, virtual tutoring, vision, web-based collaboration, by Daniel Christian

Forecast 5.0 – The Future of Learning: Navigating the Future of Learning — from knowledgeworks.org by Katherine Prince, Jason Swanson, and Katie King
Discover how current trends could impact learning ten years from now and consider ways to shape a future where all students can thrive.

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.

Humans are hardwired to forget. But research shows that strategies like peer-to-peer explanations, regular review, and interleaving can boost retention. pic.twitter.com/0IVVz2M3FJ

— edutopia (@edutopia) December 6, 2018

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).

AI Now Report 2018: 10 Recommendations for AI [AI Now Institute]

On 12/07/2018, in 21st century, algorithms, Amazon, Apple, Artificial Intelligence / Machine Learning / Deep Learning, bots, business, career development, change, Christian education, cognitive computing, colleges, community colleges, computer science, corporate / business world, emerging technologies, ethics, Facebook, future, game-changing environment, Google, higher education, human-computer interaction (HCI), IBM, ideas, innovation, intelligent systems, internet, Law Schools, legislatures / government / legal, machine-to-machine communications, Microsoft, morals/values, pace of change, platforms, programming, society, sociology, surviving, Technologies for your home, technology (general), the downsides of technology, tools, trends, United States, universities, vendors, vision, workplace, by Daniel Christian

AI Now Report 2018 | December 2018 — from ainowinstitute.org

Meredith Whittaker , AI Now Institute, New York University, Google Open Research
Kate Crawford , AI Now Institute, New York University, Microsoft Research
Roel Dobbe , AI Now Institute, New York University
Genevieve Fried , AI Now Institute, New York University
Elizabeth Kaziunas , AI Now Institute, New York University
Varoon Mathur , AI Now Institute, New York University
Sarah Myers West , AI Now Institute, New York University
Rashida Richardson , AI Now Institute, New York University
Jason Schultz , AI Now Institute, New York University School of Law
Oscar Schwartz , AI Now Institute, New York University

With research assistance from Alex Campolo and Gretchen Krueger (AI Now Institute, New York University)

Excerpt (emphasis DSC):

Building on our 2016 and 2017 reports, the AI Now 2018 Report contends with this central problem, and provides 10 practical recommendations that can help create accountability frameworks capable of governing these powerful technologies.

Governments need to regulate AI by expanding the powers of sector-specific agencies to oversee, audit, and monitor these technologies by domain.
Facial recognition and affect recognition need stringent regulation to protect the public interest.
The AI industry urgently needs new approaches to governance. As this report demonstrates, internal governance structures at most technology companies are failing to ensure accountability for AI systems.
AI companies should waive trade secrecy and other legal claims that stand in the way of accountability in the public sector.
Technology companies should provide protections for conscientious objectors, employee organizing, and ethical whistleblowers.
Consumer protection agencies should apply “truth-in-advertising” laws to AI products and services.
Technology companies must go beyond the “pipeline model” and commit to addressing the practices of exclusion and discrimination in their workplaces.
Fairness, accountability, and transparency in AI require a detailed account of the “full stack supply chain.”
More funding and support are needed for litigation, labor organizing, and community participation on AI accountability issues.
University AI programs should expand beyond computer science and engineering disciplines. AI began as an interdisciplinary field, but over the decades has narrowed to become a technical discipline. With the increasing application of AI systems to social domains, it needs to expand its disciplinary orientation. That means centering forms of expertise from the social and humanistic disciplines. AI efforts that genuinely wish to address social implications cannot stay solely within computer science and engineering departments, where faculty and students are not trained to research the social world. Expanding the disciplinary orientation of AI research will ensure deeper attention to social contexts, and more focus on potential hazards when these systems are applied to human populations.

Also see:

After a Year of Tech Scandals, Our 10 Recommendations for AI — from medium.com by the AI Now Institute
Let’s begin with better regulation, protecting workers, and applying “truth in advertising” rules to AI

Also see:

Excerpt:

As we discussed, this technology brings important and even exciting societal benefits but also the potential for abuse. We noted the need for broader study and discussion of these issues. In the ensuing months, we’ve been pursuing these issues further, talking with technologists, companies, civil society groups, academics and public officials around the world. We’ve learned more and tested new ideas. Based on this work, we believe it’s important to move beyond study and discussion. The time for action has arrived.

We believe it’s important for governments in 2019 to start adopting laws to regulate this technology. The facial recognition genie, so to speak, is just emerging from the bottle. Unless we act, we risk waking up five years from now to find that facial recognition services have spread in ways that exacerbate societal issues. By that time, these challenges will be much more difficult to bottle back up.

In particular, we don’t believe that the world will be best served by a commercial race to the bottom, with tech companies forced to choose between social responsibility and market success. We believe that the only way to protect against this race to the bottom is to build a floor of responsibility that supports healthy market competition. And a solid floor requires that we ensure that this technology, and the organizations that develop and use it, are governed by the rule of law.

From DSC:
This is a major heads up to the American Bar Association (ABA), law schools, governments, legislatures around the country, the courts, the corporate world, as well as for colleges, universities, and community colleges. The pace of emerging technologies is much faster than society’s ability to deal with them!

The ABA and law schools need to majorly pick up their pace — for the benefit of all within our society.

A few items re: web design, graphic design, logo design, & more

On 12/07/2018, in art, corporate universities / corporate training, design, Graphics, training / L&D, vendors, web design and production, by Daniel Christian

Top Graphic Design Trends 2019: Fresh Hot & Bold — from graphicmama.com

Open compositions
3D: Depth of a new generation
Anti-gravity: Flying & floating elements
Vivid colors & Dreamy color combos
Metallic effect: Golden, silver, iridescent
Fluid & liquid effect
Maxi typography
Outline typography
Text with background
Alternative art
Realism + Flat mix
The color of the year 2019

Top 9 Logo Design Trends for 2019: The Brands’ New Looks — from graphicmama.com
9 trends that will dictate the rules of branding and logo design in 2019: bright & vibrant colors, gradients, minimalism and more!

30 of The Best Animated Explainer Videos in 2018 — from graphicmama.com

Also, you may want to check out their blog.

The Biggest Graphic Design Trends of 2019 [Infographic] — from socialmediatoday.com

Excerpt:

So what are the design trends set to dominate in 2019? The team from Venngage have put together this infographic which outlines their data-backed predictions for what’s coming, and where you should be looking in your process.

Definitely, these trends look like standing out – you can read Venngage’s full report here or check out the graphic below.

This type of functionality from Chegg will likely be a piece of a next gen learning platform

On 12/06/2018, in 21st century, adjunct faculty, algorithms, Artificial Intelligence / Machine Learning / Deep Learning, bots, colleges, community colleges, education technology, emerging technologies, faculty, higher education, homeschooling/homeschoolers, human-computer interaction (HCI), innovation, instructional design, intelligent systems, intelligent tutoring, K-12 related, learner profiles, learning, Learning Agents, learning ecosystem, learning from the living [class] room, learning preferences, mathematics, online learning, personalized/customized learning, platforms, productivity / tips and tricks, Smart/Connected TV, student teaching/teacher education, student-related, teachers, teaching & learning, teaching online, Technologies for your home, tools, universities, usability, user experience (UX), vendors, by Daniel Christian

The information below is from Heather Campbell at Chegg
(emphasis DSC)

Chegg Math Solver is an AI-driven tool to help the student understand math. It is more than just a calculator – it explains the approach to solving the problem. So, students won’t just copy the answer but understand and can solve similar problems at the same time. Most importantly,students can dig deeper into a problem and see why it’s solved that way. You can learn more about us here.

In every subject, there are many key concepts and terms that are crucial for students to know and understand. Often it can be hard to determine what the most important concepts and terms are for a given subject, and even once you’ve identified them you still need to understand what they mean. To help you learn and understand these terms and concepts, we’ve provided thousands of definitions, written and compiled by Chegg experts. Further details here.

From DSC:
I see this type of functionality as a piece of a next generation learning platform — a piece of the Living from the Living [Class] Room type of vision. Great work here by Chegg!

Likely, students will also be able to take pictures of their homework, submit it online, and have that image/problem analyzed for correctness and/or where things went wrong with it.

What Blockchain Could Mean for the Future of Journalism [Dossett]

On 12/06/2018, in Blockchain, business, change, emerging technologies, Facebook, future, Google, journalism, new business models, by Daniel Christian

What Blockchain Could Mean for the Future of Journalism — from mediablog.prnewswire.com by Julian Dossett

Excerpt:

The digital era has utterly changed the way readers interact with the news.

Traditional news outlets struggle to remain relevant as the media sector’s influence is refocused online.

Journalism in the U.S. faces a number of challenges that blockchain technology has the potential to address and possibly solve — if the technology actually can achieve what it promises.

2018 itself has seen journalism move into uncharted waters as the industry comes up against issues, stemming from the continued digital migration of news organizations.

Because blockchain functions as a platform to facilitate peer-to-peer transactions, there are a few news organizations that believe blockchain technology finally will enable micropayments to be widely adopted in the U.S.

Intelligent Machines: One of the fathers of AI is worried about its future [Knight]

On 12/04/2018, in 21st century, algorithms, Artificial Intelligence / Machine Learning / Deep Learning, bots, change, emerging technologies, ethics, future, game-changing environment, global / globalization, morals/values, platforms, research, science, society, by Daniel Christian

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.