I just noticed that National Geographic is now requiring log in to access some of their content.
For example, you can see what the login/signup experience is like by trying to read the top article on the homepage, Surprising Hybrid Dolphins Revealed.
Pay close attention to the "Why am I joining?" page. It includes a video for why you should sign up (along with a reminder that it is FREE).
For other stories like Forecast: More Vessels Stuck in Antarctic Ice no log in is required.
Then for other stories, article log in is strongly suggested but not required. You can see an example of this on Our Favorite Space Pics This Week.
Over the past year, we've developed a bunch of APIs to support EdLab applications and systems (e.g., EdLab Account, Data Dashboard, E-Commerce, mSchool, NLT, Vialogues). During this time, Pranav has also talked about exposing and/or developing APIs for researchers, users, partners, customers, etc.
Well, I just read this story from Wired titled, "Leveraging APIs as Part of Digital Strategy" and I think it nicely summaries Pranav's perspectives on EdLab APIs. The story also gives a nice overview of the API Economy, how to provide APIs, and API strategy.
Learn more here.
Check out this story from Wired about why most A/B testing is inadequate.
While A/B testing makes sense on big websites where you can run hundreds of tests per day and have hundreds of thousands of hits, only a few offers can be tested at one time in cases like direct mail. The variance that these tests reveal is often so low that any meaningful statistical analysis is impossible.
Worse, the results don’t identify which variables caused consumers to respond.
As a result, response rates for emails, catalogs, and other direct marketing campaign methods — still a staple of many businesses — are very low — usually less than 5% and often less than 0.5% — and they’re declining.
So what role should A/B testing play in the EdLab product development/iteration process?
- "... people are most active on their smart devices at 9pm, with a lull setting in between 3am and 4am."
- "News app readerships hit a peak at 7am but drop off precipitously at 9am, when workers clock in for the day."
- "Smartphones consistently rate above tablets, with the most variance in usage coming around the core work hours."
Kate recently shared a story about Disney Connected Learning. Well, the American Museum of Natural History just became "the first American museum to offer a free-standing master's program in teaching science."
Full story here.
It's not surprising that museums are in this space. Check out this story about how museums are supporting science learning (via New Learning Times/Fred Rossoff).
Teachers College alumni John King was on hand for the festivities. You can learn more about his views on teacher training at Vialogues.
Over the years, various staff in the EdLab have asked, "How do we get 'x' to go viral?" Some times "x" is a video. Other times "x" is a resource. Well, researchers at West Point have found the answer. Check out this paper titled, "A Scalable Heuristic for Viral Marketing Under the Tipping Model" to learn more.
In a "tipping" model, each node in a social network, representing an individual, adopts a property or behavior if a certain number of his incoming neighbors currently exhibit the same. In viral marketing, a key problem is to select an initial "seed" set from the network such that the entire network adopts any behavior given to the seed. Here we introduce a method for quickly finding seed sets that scales to very large networks. Our approach finds a set of nodes that guarantees spreading to the entire network under the tipping model. After experimentally evaluating 31 real-world networks, we found that our approach often finds seed sets that are several orders of magnitude smaller than the population size and outperform nodal centrality measures in most cases. In addition, our approach scales well - on a Friendster social network consisting of 5.6 million nodes and 28 million edges we found a seed set in under 3.6 hours. Our experiments also indicate that our algorithm provides small seed sets even if high-degree nodes are removed. Lastly, we find that highly clustered local neighborhoods, together with dense network-wide community structures, suppress a trend's ability to spread under the tipping model.
Check out this story about how a group of professors at University of Winnipeg pushed for changes in the math curriculum in Manitoba, Canada.
I thought it was an interesting read, particularly in light of this story in the NYTimes about education reform in Massachusetts.
Did Manitoba move away from the “new math” and “inquiry-based” teaching approaches too quickly? It took MA "two decades of sustained efforts to lift science and mathematics education."
Most folks in the EdLab are already aware of the work we are doing around Search and Recommendation. It is a core part of our products/services and an important part of the learning experiences in mSchool.
So I thought I would share this resource on Google Knowledge Graph.
Additionally, here is a short introductory video clip on the Knowledge Graph featuring interviews with Google team who worked on this.
Check out this article about WiSee from arstechnica. Long story short, Wisee "uses radio waves from Wi-Fi to sense human body movements." The team at Washington is developing it to detect command gestures but I can imagine using this technology to do data capture of individual's movements in a dynamic multimodel learning environment.