learning agents

Like Netflix, new college software seeks to personalize recommendations

On 10/14/2010, in education technology, learner profiles, learning agents, personalized/customized learning, by Daniel Christian

Like Netflix, new college software seeks to personalize recommendations — from InsideHigherEd.com by Marc Parry

Anaheim, Calif. —Amazon. Netflix. Google. All personalize recommendations based on what they know about users.

A new project, unveiled at the Educause conference here today, plans to provide college students a similar experience on academic Web sites.

It’s called Sherpa, like the guides who lead climbers up Mount Everest. The goal of the software, developed by the South Orange County Community College District, is to mine data about students to guide them to courses, information, and services.

That’s a change from what students experience starting and finishing classes on the Blackboard course-management system, said Robert S. Bramucci, South Orange’s vice chancellor for technology and learning services.

Tagged with: customized learning • educational technology • learner profiles • Learning Agents • personalized learning

Thoughts on lecture capture, personalization, web-based learner profiles

On 10/11/2010, in 21st century, Artificial Intelligence/Agents/LLMs/and Related, competency-based learning/education, education technology, emerging technologies, game-changing environment, innovation, instructional design, intelligent tutoring, learner profiles, learning agents, online learning, online tutoring, by Daniel Christian

From DSC:
I was reading a white paper from Tegrity today (see below graphics). It mentioned that the next frontier for lecture capture technologies is focused on developing more personalized learning experiences.

— A brief aside from DSC:
Reminds me of some of the functionality found in Livescribe’s echo smartpen.

The ability to integrate lecture capture platforms with Learning Management Systems (LMS’s) can help to automate the authentication and authorization needed to ensure learners get to review what they are allowed to review. Integration hooks provided by lecture capture and LMS vendors are viable as methods of ensuring a baseline approach to secure access. Yet most lecture capture systems do not know who the viewer is (as the LMS does the authentication and authorization); they only know that the stream is permitted to play and that students of the course are watching.

This sets the stage for the next transformation of lecture capture solutions – into platforms that can understand not just who their users are, but also what those users need to do and how their experience can be personalized and enhanced.

The coming shift will bring creation of custom learning environments that cater to the individual student by offering personal context-sensitivity, the ability to draw on the knowledge of peers and instructors, and the ability to better manage and monitor each individual learner’s behaviors and customize their experience to their individual needs. Among the major effects of this shift:

Democratization of the content creation process as learners themselves contribute to or otherwise use lecture capture tools to learn from or teach others

Faster learning by enabling learners to access information more quickly through bookmarks – and placing efficiencies within the platform to streamline teaching and learning

Changing impact on educators, who can rely on lecture capture feedback loops based on features like bookmarking to enable them to adjust content and teaching styles to suit learner needs

Use of presence and the fact that a system can know a learner to automate and make more efficient the act of finding peers or instructors for further learning interactions

Greater ability to deliver content and offer customized features via mobile devices

This white paper focuses on the evolution of lecture capture as a tool for creating a coherent environment for learner-centered instruction, showing the possibilities for improved efficiencies and better learning outcomes.

From DSC:
The integration of a lecture capture system w/ an LMS got me to thinking…what if each person in the world had a constantly-updated, adaptive, web-based learner profile that detailed their current age, current and past places of residence, language(s), hobbies, interests, courses taken, major(s), minor(s), last grade completed, which RSS feeds they subscribe to, which sources of educational content they prefer, etc. Given permission by the student, a vendor’s tool could then query the database and look for particular fields…plugging that content into their own application for greater context and engagement.

So if a 3rd grader in India loved horses, the math problems could utilize that information to make the problems more engaging to that person.

Hmmm…along these lines, I think I’ll set up some Google alerts to include:

Multi-agent systems
Adaptive learning systems
Artificial intelligence education
Distributed e-learning systems
Semantic web education
Learning agents
Intelligent tutoring
Online tutoring

The next few years should be veeeerrrryyy interesting. Fasten your seatbelts!

Tagged with: 1:1 • AI • competency-based learning/education • customized learning • educational technology • game-changing environment • innovation • instructional design • learner profiles • Learning Agents • lecture recording • online learning • personalized learning

References from “Developing Adaptive and Personalized Distributed Learning Systems…”

On 09/14/2010, in Artificial Intelligence/Agents/LLMs/and Related, learning agents, personalized/customized learning, by Daniel Christian

From DSC:
Though I can’t re-publish this article (it costs $19), I do hope it’s ok that I share the abstract and the references of the article (if not Birol or Mustafa, please advise). They are definitely onto something here, and we all need to continue to keep our eyes on such keywords as:

learning agents
multi agent systems
1:1
personalized/customized learning
artificial intelligence (AI)
the semantic web
…as these items represent where technology can be powerfully leveraged in the future.

Developing Adaptive and Personalized Distributed Learning Systems with Semantic Web Supported Multi Agent Technology

Birol Ciloglugil
Dept. of Comp. Engineering
Ege UniversityIzmir, Turkey

Mustafa Murat Inceoglu
Dept. of Comp. Education and Instructional Technology
Ege University
Izmir, Turkey

Abstract—The early e-learning systems were developed with the one-size-fits-all approach where the differences among the learners were disregarded and the same learning materials were supplied to each user. Nowadays, with the technological advances and the new trends in system design, the newly-developed systems take into consideration the needs, the preferences and the learning styles of the learners. As a result of this, more personalized e-learning systems have been developed. This thesis will investigate how possible technologies such as multi-agent systems and semantic web can be used to achieve more adaptive and more personalized distributed e-learning environments.

Keywords-adaptive systems; e-learning, multi agent systems; personalized e-learning systems; semantic web

REFERENCES

[1] H. Wang, P. Holt, “The design of an integrated course delivery system for Web-based distance education”, Proceedings of the IASTED International Conference on Computers and Advanced Technology in Education (CATE 2002), 2002, pp. 122-126.

[2] F. O. Lin, Designing Distributed Learning Environments with Intelligent Software Agents, Information Science Publishing, 2004.

[3] B. Ciloglugil, M. M. Inceoglu, “Exploring the state of the art in adaptive distributed learning environments”, LNCS, vol. 6017, 2010, pp. 556-569.

[4] I. S. B. Gago, V. M. B. Werneck, R. M. Costa, “Modeling an Educational Multi-Agent System in MaSE”, LNCS, vol. 5820, 2009, pp. 335-346.

[5] S. Garruzzo, D. Rosaci, G. M. L. Sarne, “ISABEL: A multi agent elearning system that supports multiple devices”, IEEE/WIC/ACM International Conference on Intelligent Agent Technology, 2007, pp.85-88.

[6] T. Berners-Lee, J. Hendler, O. Lassila, The semantic web, Scientific American, 2001, pp. 34-43.

[7] A. Gladun, J. Rogushina, F. Garc?a-Sanchez, R. Martínez-Béjar, J. T. Fernández-Breis, “An application of intelligent techniques and semantic web technologies in e-learning environments”, Expert Syst. Appl., vol. 36, 2, 2009, pp. 1922-1931.

[8] M. Gaeta, F. Orciuoli, P. Ritrovato, “Advanced ontology management system for personalised e-learning”, Know.-Based Syst., vol. 22, 4, 2009, pp. 292-301.

[9] B. G. Aslan, M. M. Inceoglu, “Machine learning based learner modeling for adaptive Web-based learning”, LNCS, vol. 4705, 2007, pp. 1133-1145.

[10] W. S. Lo, I. C. Chung, H. J. Hsu, “Using ontological engineering for computer education on online e-Learning community system”, International Conference on Education Technology and Computer, Singapore, 2009, pp. 167-170.

[11] L. Romero, H. P. Leone, “An ontology on learning assessment domain”, New Perspectives on Systems and Information Technology, vol. 2, 2007, pp. 137-148.

[12] A. Canales-Cruz, V. G. Sanchez-Arias, F. Cervantes-Perez, R. Peredo-Valderrama, “Multi-agent system for the making of intelligence and interactive decisions within the learner’s learning process in a web-based education environment”, Journal of Applied Research and Technology, vol. 7, 3, 2009, pp. 310-322.

Tagged with: 1:1 • AI • customized learning • Learning Agents • personalized learning • semantic web

Buffett, Gates persuade 40 billionaires to donate half of wealth — from OregonLive.com

SEATTLE — Forty wealthy families and individuals have joined Microsoft co-founder Bill Gates and billionaire investor Warren Buffett in a pledge to give at least half their wealth to charity.

Those who have joined the Giving Pledge, as listed on its website, are: Paul G. Allen, Laura and John Arnold, Michael R. Bloomberg, Eli and Edythe Broad, Warren Buffett, Michele Chan and Patrick Soon-Shiong, Barry Diller and Diane von Furstenberg, Ann and John Doerr, Larry Ellison, Bill and Melinda Gates, Barron Hilton, Jon and Karen Huntsman, Joan and Irwin Jacobs, George B. Kaiser, Elaine and Ken Langone, Gerry and Marguerite Lenfest, Lorry I. Lokey, George Lucas, Alfred E. Mann, Bernie and Billi Marcus, Thomas S. Monaghan, Tashia and John Morgridge, Pierre and Pam Omidyar, Bernard and Barbro Osher, Ronald O. Perelman, Peter G. Peterson, T. Boone Pickens, Julian H. Robertson Jr., David Rockefeller, David M. Rubenstein, Herb and Marion Sandler, Vicki and Roger Sant, Walter Scott Jr., Jim and Marilyn Simons, Jeff Skoll, Tom Steyer and Kat Taylor, Jim and Virginia Stowers, Ted Turner, Sanford and Joan Weill and Shelby White.

From DSC:
This is fantastic news! Excellent. I’m a big supporter of various charities myself — albeit with far fewer O’s ($$) behind the amounts of my checks than what these folks are able to provide! 🙂 But it got me to thinking…

If the United States government — or the government from another interested nation — could even get 1-2 billion of this enormous accumulation of wealth, think what could be done to create interactive, multimedia-based, engaging, customized/personalized, online learning-based materials that could be offered FREE of charge to various age groups/cognitive levels. Creative simulations and animations could be built and offered — free of charge — to students throughout the world. The materials would be available on a variety of devices for maximum flexibility (laptops, notebooks, iPads, iPhones, tablet PCs, workstations, etc.)

An amazing amount of digital scaffolding could be provided on a variety of disciplines. THIS could represent the Walmart of Education that I’ve been talking about…wow!

Tagged with: budgetary • business side of he • cost of getting an education • costs • disruption • educational technology • engagement • engaging students • future of higher education • game-changing environment • Global learning • internet • Keeping students engaged • leadership • learning objects • multimedia • new business models in he • ocw • online learning • strategy • student-related • Walmart of Education

Web 3.0, A witness protection program for Artificial Intelligence (AI) — from inventorspot.com [via SteveKnode.com]

On 06/07/2010, in Artificial Intelligence/Agents/LLMs/and Related, learning agents, by Daniel Christian

Web 3.0, A witness protection program for Artificial Intelligence (AI) — from inventorspot.com [via SteveKnode.com]

(Emphasis below from DSC)

In our current era of privacy concerns with Facebook and Google, the next decade will see an ushering in of pull technology replacing push. This will address a lot of the security issues we face today. Artificial Intelligence (AI) agents will pull information for us based on the parameters we establish and control. They will then deliver it to the social networks that exist inside our own data networks that we supervise – dissimilar to Facebook’s Open Graph philosophy.

According to Valeria Maltoni, brand strategy and co-author of The Age of Conversation, “Web 3.0 is the true era of conversation, where the real dialogue begins.” She sees the next generations of browsers as ‘smart clients’ working online and offline to facilitate connections of one’s AI agents with someone else’s AI agents, similar to how humans currently match up experts with various business opportunities.

“Our agents will in turn carry out sophisticated tasks for users, making meaningful connections between bits of information so that “computers can perform more of the tedious work involved in finding, combining, and acting upon information on the Web,” notes its originator, Internet pioneer Sir Tim Berners-Lee…

Also see:
Primal.com

Primal Storm – Your online brainstorming assistant. Give Primal Storm a few words to start and it will suggest related ideas.
Primal Search – Select from a cloud of thoughts to express a big idea. Primal Search will find web pages about your idea as a whole.
Primal Fusion – Store your ideas in a thought network so you can explore, discover and act on them anytime. Interested in a particular topic? Struggling to organize and capture your thinking around it? Use Primal Fusion to remember your thoughts about the stuff that matters to you.
Labs – Check out our playground for Primal prototypes. Here you’ll find new products, concepts and ideas that we are exploring. Visit often and tell us what you think.

Tagged with: 1:1 • AI • Learning Agents

Excerpts from Future of Learning Technology – 2015 — The Upside Learning Solutions Blog

On 05/07/2010, in educational games / serious games, elearning, instructional design, learning agents, simulations, training / L&D, workplace, by Daniel Christian

Excerpts from Future of Learning Technology – 2015 — The Upside Learning Solutions Blog

5. Games (and simulations) will become integral part of workplace learning. Overall the culture of gaming is becoming pervasive and the cost of game development is decreasing. Both these trends are increasing the acceptance of games for workplace learning, an area where cost of development and delivery have always been a concern. As the focus of learning departments change to being facilitators rather than providers of training, engaging solutions like games will become crucial.

6. Birth of new Authoring Tools. We will also see new authoring tools which allow designers to make application scenarios easily and quickly. Tools like thinking worlds are great for quickly creating 3D based decision simulations (or even simple 3D games). Dr. Michael Allen (creator of Authorware) is working on a new tool called Zebra (which he talks about here — from DSC ID’s should check that video out) that would make engaging eLearning creation easy with drag and drop objects.

Michael Allen describes the future of authoriing

Dr. Michael Allen -- discussing their new authoring tool -- Zebra

7. Emergence of Personal Learning Agents. As the semantic web finally starts to form and common ontologies for various types learning content are developed, intelligent personal learning software agents will emerge as learning content mediators. Having a software agent that runs on a personal computing device such as a mobile phone or tablet and constantly monitors content streams on the internet to provide up-to-date information based on personal preferences, workplace conditions, or for the task at hand will make a good performance support and learning assistance system.

Tagged with: elearning • games • instructional design • Learning Agents • simulations • tools • workplace

Top ten electronic education trends for the 21st Century — from BigGyan’s blog

On 04/11/2010, in 21st century, change, faculty/staff, future, future of higher education, game-changing environment, higher education, innovation, K-12 related, learning agents, learning ecosystem, learning preferences, multimedia, personalized/customized learning, trends, by Daniel Christian

Top ten electronic education trends for the 21st Century — from BigGyan’s blog

Don’t miss this interesting list of the top ten Electronic Education Trends for the 21st Century from James Canton.

Posted on – April 11, 2010

Dr. James Canton is a renowned global futurist, social scientist, keynote presenter, author, and visionary business advisor. For over 30 years, he has been insightfully predicting the key trends that have shaped our world. He is a leading authority on future trends in innovation and The Economist recognizes him as one of the leading futurists, worldwide. He is the author of The Extreme Future: The Top Trends That Will Reshape the World in the 21st Century, Dutton 2006, and Technofutures: How Leading-Edge Innovations Will Transform Business in the 21st Century, Next Millennium Press, 2004.

The Top Ten Electronic Education Trends for the 21st Century

1. Electronic education via the Net will enable interconnected learning experiences, choices, and opportunities for billions worldwide.
2. Educational content will be delivered by new computer, interactive TV, satellite, and Internet technologies in the new millennium.
3. Interactive online multimedia and multidimensional content will revolutionize learning.
4. Self-paced, self-directed individualized virtual learning will dominate business training.
5. Students and teachers will prefer on-demand virtual learning to traditional school programs
6. Corporations will prefer Net-based training where workers can learn at their own pace.
7. Virtual Reality scenarios that depict real-world and fantasy experiences will increase the learning impact for all types of education.
8. Real-time Net chats with other global learners will make virtual education a satisfying social experience beyond the limits of time and distance.
9. Teachbots-smart agents-will transform education, providing personalized guidance when and where people need it.
10. People will learn to design their own electronic learning programs, which will increase their understanding, skills, creativity, and career choices.

Tagged with: 21st century • future • future of higher education • innovation • K-12 • Learning Agents • personalized learning • trends

Intelligent Agents: Watson — via Steve Knode’s newsletter

On 03/29/2010, in intelligent tutoring, learning agents, by Daniel Christian

Intelligent Agents
Watson, IBM’s Jeopardy-playing computer, trumps humans (video) – “A fascinating and insightful update on Watson, IBM’s computer being developed to appear on Jeopardy and compete with humans using the same game playing rules.”

From DSC:
This is both exciting and potentially-disturbing to me. At times, I don’t like to cover a lot of things related to artificial intelligence (AI) — as the motivations of those seeking advances in AI are sometimes suspect to me and at times border on arrogance — but to turn my head and ignore everything that’s happening in this area is not helpful either.

The disturbing part lies in who uses such technology and for which purposes. The exciting part is how intelligent agents can work for us. In fact, I created the following graphic back in May 2008 (with slight edits on the wording made today):

Also see:
Digital doomsday: the end of knowledge – Even as we are acquiring ever more extraordinary knowledge, we are storing it in ever more fragile and ephemeral forms. If our civilization runs into trouble, like all others before it, how much would survive?

Tagged with: 1:1 • intelligent tutoring • Learning Agents

Next Entries

Learning Ecosystems

Like Netflix, new college software seeks to personalize recommendations

Excerpts from Future of Learning Technology – 2015 — The Upside Learning Solutions Blog

Intelligent Agents: Watson — via Steve Knode’s newsletter

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