.
— originally saw this at Ray Schroeder’s Educational Technology blog
Blackboard’s next phase — from insidehighered.com by Steve Kolowich
Blackboard built its e-learning empire on its learning management system, trading legal blows with some competitors and gobbling up others as it raced to satisfy demand for a technology that had rapidly become de rigueur in higher education.
That period of conquest is now over. Last fall, close to 95 percent of institutions had some learning management system in place, according to the Campus Computing Project. Accordingly, Blackboard’s business strategy is changing: with the company adding four new, separately licensed products to its menu in the last three years, Blackboard expects that it will soon no longer rely on Learn, its popular learning management system, to bring home the bacon.
…
The fact that Blackboard is staking so much of its anticipated growth in the domestic higher education market on the success of its newer products could put colleges in a better position to haggle, Urdan added. “The whole notion of the market being saturated and [Blackboard] being reliant on new products to build their revenue stream — maybe the negotiating power is shifting a little more toward the client and a little bit away from Blackboard,” he said. This might be especially true given the gradual erosion of Blackboard’s market dominance in recent years.
Blackboard buys into data analytics — from CampusTechnology.com by Dian Schaffhauser
Blackboard has expanded its forays outside of its traditional academic realm by entering into the territory of administrative operations with the announcement of a new set of data analytics applications. The news comes just weeks after Blackboard quietly acquired iStrategy, a private company focused on data warehousing and business intelligence for higher education.
On 02/08/2011,
in analytics, Augmented Reality (AR), e-books, e-readers, education technology, educational games / serious games, mobile learning, mobile technologies, tablets,
by Daniel Christian
The 2011 Horizon Report — from the New Media Consortium; via Educause
.
.
Time-to-Adoption: One Year or Less
- Electronic Books
- Mobiles
Time-to-Adoption: Two to Three Years
- Augmented Reality
- Game-Based Learning
Time-to-Adoption: Four to Five Years
- Gesture-Based Computing
- Learning Analytics
Also see:
On 02/04/2011,
in 21st century, analytics, Artificial Intelligence/Agents/LLMs/and Related, emerging technologies, IT in HE, learner profiles, learning agents, personalized/customized learning, trends,
by Daniel Christian
.
Along these lines, check out:
‘Jeopardy’ champs take on IBM’s Watson
“This is huge; this isn’t just about answering questions,” says computational linguistics expert George Luger of the University of New Mexico in Albuquerque, who was not part of IBM’s team. “Everything before this was just a run-up to computers as true personal assistants.”
On 01/18/2011,
in 21st century, analytics, computer science, learner profiles, learning agents, learning ecosystem, mathematics, music, personalized/customized learning, programming, science,
by Daniel Christian
The Ultimate Study Guide: Wolfram Alpha Launches “Course Assistant” Apps — from ReadWriteWeb by Audrey Watters
The computational knowledge engine Wolfram|Alpha is launching the first three of a series of new “course assistant” apps today. These apps, available for iPhone, iPod Touch, and iPad, are designed to take advantage of the Wolfram|Alpha technology in the service of supporting some of the most popular courses in high school and college.
The idea is to be able to quickly access the pertinent capabilities of Wolfram|Alpha relevant for specific subject areas. Currently, these subject areas are Algebra, Calculus, and Music Theory. But the company says it plans to add apps for other subjects – “for every major course, from elementary school to graduate school,” – including those fields outside math and science.
From DSC:
Notice the term engine (in bold maroon above). This is the type of sophisticated programming that will increasingly be baked into future learning products — as the software seeks to learn more about each learner while providing each learner with a more customized learning experience…pushing them, but aiming to encourage — not discourage — them. I can see an opt-in program where each of us can build a cloud/web-based learner profile — and allow such an engine to be “fed” that data.
On 01/17/2011,
in analytics, elearning, face-to-face, multimedia, online learning, online media, open courseware and systems,
by Daniel Christian
e-learning outlook for 2011 — from Tony Bates
Tony discusses course redesigns, mobility, open educational resources (OER), multimedia, learning analytics, and shared services.
On 01/14/2011,
in 24x7x365 access, analytics, collaboration, education technology, expectations, future, future of higher education, higher education, online learning, open courseware and systems, professional development, social learning / networks, web-based collaboration,
by Daniel Christian
Includes the acceleration of learning analytics and learner-generated content, knowledge application supplanting information access, digital textbooks making their move, data-intensive computing challenging IT — as well as predictions concerning faculty development (as even more courses move online), mobile learning, student expectations, open education, collaboration, social media and others.
On 01/10/2011,
in 21st century, 24x7x365 access, analytics, education, education reform, Google, innovation, online learning, personalized/customized learning,
by Daniel Christian
Is the Google-fication of education underway? — from cnnmoney.com by Scott Olster (emphasis below from DSC)
Among tablets and 3D TVs at CES, one-size-fits-all learning is facing a digital death knell.
Excerpt:
Similar to the way that Google collects data based on its users’ search patterns, Knewton collects data from every student that has taken one of its courses and uses it to improve its courses. Eduational content that achieves better student results will then be ranked higher in the system and be used more often. Ideally, the system becomes smarter and better over time.
“It’s like a giant recommendation engine on steroids,” says Ferreira.
The data that the company collects could potentially prove useful to educational researchers.
“We’re still trying to map out the way people learn. Collecting more data rather than looking at course grades is a welcome change,” says Miller.
— from nextbigfuture.com
On 12/10/2010,
in analytics, cloud-based computing / apps / other cloud-related, collaboration, communications, instructional design, learning ecosystem, RSS, social learning / networks,
by Daniel Christian
Connections, Clouds, Things & Analytics –– from George Siemens
From DSC:
In looking through George’s presentation, the following graphic reminded me of a learning ecosystem. The idea of activity and content streams speaks of constant flow, change, new information. Look are the sources of where learning can come from:
.
As an instructional designer, how do we incorporate all of this?
Finally, one other thought, if we are not connected to a network of bloggers (and have a series of RSS feeds keeping us constantly up-to-date) or have some other means of tapping into these streams of activities and sources of content, we will look like this:
On 11/09/2010,
in analytics, cloud-based computing / apps / other cloud-related, collaboration, computer science, future, game-changing environment, mobile technologies, tablets, trends, ubiquitous learning, web-based collaboration,
by Daniel Christian
Gartner’s top 10 technologies for 2011 — from GlobalKnowledge.com by Larry Dignan; with special thanks to Mr. Cal Keen, Calvin College, for this resource
- Cloud computing
- Mobile apps and media tablets
- Next-gen analytics
- Social analytics
- Social communication and collaboration
- Video
- Context-aware computing
- Ubiquitous computing
- Storage class memory
- Fabric based infrastructure and computers
The Data Analytics Boom — from Forbes.com by John Jordan
A multitude of converging facts has given rise to numbers-based decision-making.