Learning Agents

Some reflections on Visions 2020.2

On 11/09/2010, in 21st century, 24x7x365 access, 3D, analytics, Augmented Reality (AR), collaboration, convergence, digital audio, digital learning, digital textbooks, digital video, distance education, e-books, e-readers, education technology, educational games / serious games, elearning, emerging technologies, engagement / engaging students, faith, game-changing environment, human-computer interaction (HCI), immersion, innovation, intelligent tutoring, interactivity, internet, K-12 related, learning agents, learning ecosystem, learning preferences, mathematics, mobile learning, mobile technologies, multimedia, online learning, online media, online tutoring, personalized/customized learning, religion, simulations, social learning / networks, student-related, technologies for your home, telepresence, tools, videoconferencing, virtual field trips, virtual K-12 schools, Virtual Reality (VR) / worlds / learning, virtual tutoring, vision/possibilities, by Daniel Christian

From DSC:
Below are some notes and reflections after reading Visions 2020.2: Student Views on Transforming Education and Training Through Advanced Technologies — by the U.S. Department of Commerce, U.S. Department of Education, and NetDay

Basic Themes

Digital Devices
Access to Computers and the Internet
Intelligent Tutor/Helper
Ways to Learn and Complete School Work Using Technology

Several recurring words jumped off the page at me, including:

Voice activation
A rugged, mobile, lightweight, all-convergent communications and entertainment device
Online classes
Interactive textbooks
Educational games
3D virtual history enactments — take me there / time machine
Intelligent tutors
Wireless
24x7x365 access
Easy to use
Digital platforms for collaborating and working with others on schoolwork/homework
Personalized, optimized learning for each student
Immersive environments
Augmented reality
Interactive
Multimedia
Virtual
Simulations
Digital diagnostics (i.e. analytics)
Wireless videoconferencing

Here are some quotes:

Math and reading were often cited specifically as subjects that might benefit from the use of learning technologies. (p. 5)

No concept drew greater interest from the student responders than some sort of an intelligent tutor/helper. Math was the most often mentioned subject for which tutoring help was needed. Many students desired such a tutor or helper for use in school and at home. (p. 17)

…tools, tutors, and other specialists to make it possible to continuously adjust the pace, nature and style of the learning process. (p.27)

So many automated processes have been built in for them: inquiry style, learning style, personalized activity selection, multimedia preferences, physical requirements, and favorite hardware devices. If the student is in research mode, natural dialogue inquiry and social filtering tools configure a working environment for asking questions and validating hypotheses. If students like rich multimedia and are working in astronomy, they automatically are connected to the Sky Server which accesses all the telescopic pictures of the stars, introduces an on-line expert talking about the individual constellations, and pulls up a chatting environment with other students who are looking at the same environment. (p.28)

— Randy Hinrichs | Research Manager for Learning Science and Technology | Microsoft Research Group

From DSC:
As I was thinking about the section on the intelligent tutor/helper…I thought, “You know…this isn’t just for educators. Pastors and youth group leaders out there should take note of what students were asking for here.”

Help, I need somebody
Help me with ____
Many students expressed interest in an “answer machine,” through which a student could pose a specific question and the machine would respond with an answer. <– I thought of online, Christian-based mentors here, available 24x7x365 to help folks along with their spiritual journeys

Tagged with: 1:1 • 21st century • 24x7x365 • 3D • analytics • augmented reality • collaboration • convergence • customized learning • digital audio • digital learning • digital textbooks • digital video • e-books • e-readers • educational technology • emerging technologies • engagement • faith • game-changing environment • human-computer interaction (HCI) • immersion • innovation • intelligent tutoring • interactivity • internet • K-12 • Learning Agents • learning ecosystem • learning preferences • math • Mobile learning • mobile technology • multimedia • online learning • online tutoring • personalized learning • religion • simulations • social learning • student-related • technologies for the home • telepresence • videoconferencing • virtual field trips • virtual schools • virtual tutoring • vision • web-based collaboration

Agents and multi-agents — most likely a part of our future learning ecosystems

On 10/30/2010, in Artificial Intelligence / Machine Learning / Deep Learning / Algorithms, computer science, Daniel S. Christian, learning agents, learning ecosystem, programming, by Daniel Christian

Below graphics from:
Introduction to MultiAgent Systems

From DSC:

Tagged with: AI • computer science • Daniel S. Christian • Learning Agents • learning ecosystem • programming

Kosmix

On 10/23/2010, in 21st century, 24x7x365 access, data related items, innovation, learning agents, learning ecosystem, social learning / networks, social media, by Daniel Christian

Tagged with: data mining • innovation • internet • Learning Agents • learning ecosystem • social learning • social media

Emerging Interactive Ed. Tech: Classmate Assist and Wayang Outpost

On 10/22/2010, in 21st century, 24x7x365 access, analytics, education technology, emerging technologies, intelligent tutoring, learner profiles, learning agents, mobile learning, online tutoring, by Daniel Christian

Emerging Interactive Ed. Tech: Classmate Assist and Wayang Outpost – Sensors, AI, and Context Awareness for Learning -and Teaching — by Lynn Marentette (emphasis below from DSC)

I’ve been following developments in intelligent tutoring systems for a while, and find it interesting to see how researchers are combining artificial intelligence, learning theory, affective computing, and sensor networks to create applications that might prove to be useful and effective.

The advantage of using intelligent tutoring applications in some cases is that it provides students with additional support and feedback the moment it is needed, something that is difficult for teachers to provide to students in large classrooms. With the increase in use of smartphones and other mobile devices such as the iPad, there is a good chance that this sort of technology will be used to support learning anywhere, anytime.

Although most intelligent tutoring systems are geared for 1-1 computing, I think there are some components that could be tweaked and then transfered to create intelligent “tutoring” systems for collaborative learning. Students like game-based learning, and what could be more fun than playing AND learning with a partner or group of peers? (I plan to revisit the research in this area in an upcoming post.)

Below I’ve highlighted two “intelligent” tutoring systems that incorporate the use of sensors in one form or another to generate information about student learning in a way that simulates what good teachers do every day. The ClassroomAssist application was developed by researchers at Intel, in collaboration with several universities. The Wayang Outpost application was developed by researchers at UMASS, and is aligned with the principles of Universal Design for Learning.

Tagged with: 1:1 • 21st century • 24x7x365 • analytics • educational technology • emerging technologies • intelligent tutoring • learner profiles • Learning Agents • Mobile learning • online tutoring

Check out the topics in this symposium — talk about a game-changing environment!

On 10/19/2010, in 21st century, Artificial Intelligence / Machine Learning / Deep Learning / Algorithms, future, game-changing environment, human-computer interaction (HCI), innovation, intelligent tutoring, internet, learning agents, learning ecosystem, multimedia, pace of change, programming, robotics, simulations, telecommunications, trends, web-based collaboration, by Daniel Christian

Symposium on Progress in Information and Communication Technology (SPICT’10)

Conference date: 12-13 Dec,2010
Conference venue: The Royale Bintang, Kuala Lumpur
Conference country: Malaysia

SPICT’10 aims to bring together scientists, industry practitioners and students to exchange the latest fundamental advances and trends, and identify emerging research topics in the field of information and communication technology.

Activities:

* Agent & Multi-agent Systems
* Antennas & Propagation
* Artificial Intelligence
* Bioinformatics & Scientific Computing
* Business Intelligence
* Communication Systems and Networks
* Complex Systems: Modeling and Simulation
* Computer Vision
* Database and Application
* Geographical Information Systems
* Grid and Utility Computing
* Image Processing
* Information indexing & retrieval
* Information Systems
* Intelligent Systems
* Internet Technology
* Knowledge Management
* Mobile Communication Services
* Multimedia Technology and Systems
* Natural Language Processing
* Network Management and services
* Ontology and Web Semantic
* Optical Communications and Networks
* Parallel and Distributed Computing
* Pattern Recognition
* Pervasive Computing
* Real-Time and Embedded Systems
* Remote Sensing
* Robotic Technologies
* Security and Cryptography
* Sensor Networks
* Service Computing
* Signal Processing
* Software Engineering
* Strategic Information Systems

Tagged with: 1:1 • 21st century • AI • future • game-changing environment • human-computer interaction (HCI) • innovation • internet • Learning Agents • learning ecosystem • multimedia • pace of change • robotics • semantic web • telecommunications • trends • web-based collaboration

What are our motivations? What’s the state of our hearts?

On 10/18/2010, in analytics, Artificial Intelligence / Machine Learning / Deep Learning / Algorithms, Daniel S. Christian, data related items, ethics, faith, future, intelligent tutoring, learner profiles, learning agents, morals/values, pace of change, by Daniel Christian

We need to be constantly checking and praying about the state of our hearts.

The State of the Heart

From DSC:
My conscience prompts me to write this…as my recent posting on developing and using web-based learner profiles was not meant to try and ultimately recreate the human brain. I don’t think that’s possible. Rather, I was hoping that we could use such methods and breakthroughs to promote the personalization, customization, and engagement levels of the learning materials and experiences that we are able to offer each other.

But the posting got me to reflecting on a variety of technological advancements…and I couldn’t help but wonder about the motivations at play sometimes here.

That is, things can begin innocently enough and with excellent intentions. For example, with stem-cell research, such research can offer understanding on how stem cells might be able to help treat debilitating conditions such as Parkinson’s disease, traumatic spinal injury, or be used for positively affecting other clinical and therapeutic applications. And that’s great! Excellent!

But the problem for me in many of these endeavors lies in the hearts of mankind. Because, who knows where things could go from there…

Will we one day find ourselves being able to create fellow human beings? If so, who determines what those fellow human beings are like? Will we be able to program a robot to continually learn? If so, how will such devices be used by individuals? Corporations? Governments? Nations?

I know…it sounds rather bizarre and far-fetched. But with the rate of technological advancements, I just think we need to take a pulse check on the motivations involved. I’m suspect that the motivations of many folks out there are not in mankind’s ultimate best interest…plus…sometimes these individuals and organizations just don’t have the heart.

Ezekiel 11:19 (NIV)¹⁹ I will give them an undivided heart and put a new spirit in them;
I will remove from them their heart of stone and give them a heart of flesh.

P.S. from DSC:
I need to say that my heart is in constant need of attention as well;
I don’t claim to be perfect…but I also don’t claim to want to play God.

Tagged with: Daniel S. Christian • data mining • ethics • faith • future • intelligent tutoring • learner profiles • Learning Agents • morals/values • pace of change • religion

What if we could apply this same concept towards learning?

On 10/18/2010, in analytics, learner profiles, learning agents, learning ecosystem, personalized/customized learning, by Daniel Christian

About IQNOMY

IQNOMY is an S.a.a.S. (Software as a Service) solution which enables any website to adapt itself to each individual visitor in next to no time.

As a result of the emergence of new media, the distance between institutions and individuals is getting ever smaller. Individuals have gained more and more power and are increasingly using this to demand personal attention and recognition. For companies and organizations, the difficulties associated with holding on to today’s critical consumer are therefore growing.

For a long time now, simply supplying information has not been enough. Customers and consumers are looking for an experience that is presented at the right moment and within the right context. We call this Real-time Interaction Marketing. Central to this discipline is the fact that you as an organization are able to get to know and understand your customers and that you actively learn to support them in discovering new and relevant information. This form of personal and direct one-to-one marketing will play an increasingly important role in commercial markets in the future.

Tagged with: 1:1 • analytics • customized learning • learner profiles • Learning Agents • learning ecosystem • personalized learning

The thinking LMS

On 10/18/2010, in 21st century, 24x7x365 access, analytics, CMS/LMS, data related items, learner profiles, learning agents, learning ecosystem, online learning, by Daniel Christian

The thinking LMS — from InsideHigherEd.com by — Steve Kolowich

If Facebook can use analytics to revolutionize advertising in the Web era, McQuaig suggested, colleges can use the same principles to revolutionize online learning.

The trick, she said, is individualization. Facebook lets users customize their experiences with the site by creating profiles and curating the flow of information coming through their “news feeds.” In the same motion, the users volunteer loads of information about themselves.

…

Unlike analog forms of student profiling — such as surveys, which are only as effective as the students’ ability to diagnose their own learning needs — Phoenix’s Learning Genome Project will be designed to infer details about students from how they behave in the online classroom, McQuaig said. If students grasp content more quickly when they learn it from a video than when they have to read a text, the system will feed them more videos. If a student is bad at interpreting graphs, the system will recognize that and present information accordingly — or connect the student with another Phoenix student who is better at graph-reading. The idea is to take the model of personal attention now only possible in the smallest classrooms and with the most responsive professors, make it even more perceptive and precise, and scale it to the largest student body in higher education.

“[Each student] comes to us with a set of learning modality preferences,” McQuaig said. The online learning platform Phoenix wants to build, she said, “reject[s] the one-size-fits-all model of presenting content online.” In the age of online education and the personal Web, the standardized curriculum is marked for extinction, McQuaig said; data analytics are going to kill it.

Tagged with: 1:1 • 21st century • 24x7x365 • analytics • CMS/LMS • data mining • learner profiles • Learning Agents • learning ecosystem • online learning

Some reflections re: web/cloud-based learner profiles

On 10/16/2010, in 21st century, 24x7x365 access, Artificial Intelligence / Machine Learning / Deep Learning / Algorithms, assessment, cloud-based computing / apps / other cloud-related, CMS/LMS, colleges, community colleges, competency-based learning/education, Daniel S. Christian, data related items, digital learning, education technology, elearning, emerging technologies, human-computer interaction (HCI), innovation, instructional design, intelligent tutoring, internet, K-12 related, learning agents, learning ecosystem, learning preferences, lifelong learning, mobile learning, multimedia, online learning, online media, online tutoring, personalized/customized learning, training / L&D, ubiquitous learning, universities, workplace, by Daniel Christian

Reflections on web-based learner profiles -- by Daniel S. Christian

Tagged with: 1:1 • 21st century • 24x7x365 • AI • assessment • Blackboard • cloud-based computing / apps / other cloud-related • CMS/LMS • colleges • community college • competency-based learning/education • corporate training / universities • customized learning • Daniel S. Christian • data mining • digital learning • e-learning • educational technology • emerging technologies • evaluation • HCI • innovation • instructional design • intelligent tutoring • internet • K-12 • Learning Agents • learning ecosystem • learning preferences • Lifelong learning • Mobile learning • Moodle • personalized learning • scaffolding • training • ubiquitous learning • universities

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 / Machine Learning / Deep Learning / Algorithms, 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 / Machine Learning / Deep Learning / Algorithms, 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

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

On 06/07/2010, in Artificial Intelligence / Machine Learning / Deep Learning / Algorithms, 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

The evolution of ubiquitous learning — Chris Dede

On 05/05/2010, in Artificial Intelligence / Machine Learning / Deep Learning / Algorithms, intelligent tutoring, personalized/customized learning, ubiquitous learning, workplace, by Daniel Christian

Tagged with: 1:1 • customized learning • Learning Agents • personalized learning • ubiquitous learning

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