Money follows eyeballs. I saw that phrase on a slide in a conference presentation about marketing with social media.
Everyone wants your attention. Your children want your attention. Your spouse wants your attention. You want the attention of your students. Nothing new about that concept and there are plenty of ways to get someone's attention.
But it is a more recent way of thinking about attention to consider it as economics. I was listening to the audiobook of A Beautiful Mind recently. It's a book (and a good but highly romanticized film) about the mathematician John Nash. Nash received the Nobel Prize in Economics for his work on game theory as it was applied to economics. His ideas, presented in the 1950s, certainly must have seemed novel at the time, but 40 years later they seemed logical. That will probably be true of attention economics. There are already a good number of people writing about it.
Attention economics is an approach to the management of information that treats human attention as a scarce commodity. With attention as a commodity, you can apply economic theory to solve various information management problems.
Attention is a scarce commodity or resource because a person has only so much of it.
Not only in economics but in education and other areas that focused mental engagement that makes us attend to a particular item, leads to our decision on whether to act or not. Do we buy the item advertised? Do we do what mommy said to do?
We are deep into the Information Age and content is so abundant and immediately available, that attention has become a limiting factor. There are so many channels and shows on the many versions of "television" competing for our attention that you may just decide not to watch at all. Or you may to decide to "cut the cord" and disconnect from many of them to make the choices fewer.
Designers know that if it takes the user too long to locate something, you will lose their attention. On web pages, that attention lasts anywhere from a few seconds to less than a second. If they can't find what they were looking for, they will find it through another source.
The goal then becomes to design methods (filters, demographics, cookies, user testing etc.) to make the first content a viewer sees relevant. Google and Facebook want you to see ads that are relevant to YOU. That online vendor wants the products on that first page to be things you are most interested in buying. Everything - and everyone - wants to be appealing to everyone.
In attention-based advertising, we measure the number of "eyeballs" by which content is seen.
"You can't please everyone." Really? Why not?
In the history section of the entry on "Attention Economy" on Wikipedia, it lists Herbert A. Simon as possibly being the first person to articulate the concept of attention economics. Simon wrote: "...in an information-rich world, the wealth of information means a dearth of something else: a scarcity of whatever it is that information consumes. What information consumes is rather obvious: it consumes the attention of its recipients. Hence a wealth of information creates a poverty of attention and a need to allocate that attention efficiently among the overabundance of information sources that might consume it" (Simon 1971, pp. 40–41).
Simon was talking about the idea of information overload as an economic concept and that has led to business strategists such as Thomas H. Davenport to use the term "attention economy" (Davenport & Beck 2001).
Where will this lead? On the outer edges are those who speculate that "attention transactions" will replace financial transactions as the focus of our economic system (Goldhaber 1997, Franck 1999).
Designers of websites, software, apps and any user interface already take into account attention, but information systems researchers have also adopted the idea. Will we see mechanism designs which build on the idea of creating property rights in attention?
I am a proponent of the concept of teaching in a STEAM (science, technology, engineering, art, math) framework that goes across disciplines. I have seen many attempts to use science and math in teaching art - some successful, some not.
A new project that does this in an engaging way is a collaboration between Pixar Animation Studios and Khan Academy that is sponsored by Disney. Called "Pixar in a Box," it gives a look behind-the-scenes at how artists at Pixar need to use STEM to make art.
To make balls bounce, leaves in trees move in the wind, fireworks explode or realistic rippling water takes more than drawing skills. It requires computer skills and considerations of math, science such as physics and digital humanities.
In this learning series of videos on simulations, the Pixar artists use hair as an example of an animation problem that needed to be solved. Using examples from their films, such as the character Merida in Brave with her bouncy and curly hair, you learn how millions of hairs can be simulated if you think of them as being a huge system of springs.
As the lessons progress, you can learn about animation roles and will discover what a technical director does in the animation process.
The lessons are appropriate for grades 5 and up - though I can see many adults and younger kids interested in animation from a technical or artistic side enjoying the free series.
I wrote earlier about LinkedIn Learning, a new effort by the company to market online training. I said then that I did not think this would displace higher education any more than MOOCs or online education. If successful, it will be disruptive and perhaps push higher education to adapt sooner.
LinkedIn’s vision is to build what it calls the Economic Graph. That graph will be created using profiles for every member of the work force, every company, and "every job and every skill required to obtain those jobs."
That concept reminded me immediately of Facebook's Social Graph. Facebook introduced the term in 2007 as a way to explain how the then new Facebook Platform would take advantage of the relationships between individuals to offer a richer online experience. The term is used in a broader sense now to refer to a social graph of all Internet users.
LinkedIn Learning is seen as a service that connects user, skills, companies and jobs. LinkedIn acknowledges that even with about 9,000 courses on their Lynda.com platform they don't have enough content to accomplish that yet.
They are not going to turn to colleges for more content. They want to use the Economic Graph to determine the skills that they need content to provide based on corporate or local needs. That is not really a model that colleges use to develop most new courses.
But Lynda.com content are not "courses" as we think of a course in higher ed. The training is based on short video segments and short multiple-choice quizzes. Enterprise customers can create playlists of content modules to create something course-like.
One critic of LinkedIn Learning said that this was an effort to be a "Netflix of education." That doesn't sound so bad to me. Applying data science to provide "just in time" knowledge and skills is something we have heard in education, but it has never been used in any broad or truly effective way.
The goal is to deliver the right knowledge at the right time to the right person.
One connection for higher ed is that the company says it is launching a LinkedIn Economic Graph Challenge "to encourage researchers, academics, and data-driven thinkers to propose how they would use data from LinkedIn to generate insights that may ultimately lead to new economic opportunities."
Opportunities for whom? LinkedIn or the university?
This path is similar in some ways to instances of adaptive-learning software that responds to the needs of individual students. I do like that LinkedIn Learning also is looking to "create" skills in order to fulfill perceived needs. Is there a need for training in biometric computing? Then, create training for it.
You can try https://www.linkedin.com/learning/. When I went there, it knew that I was a university professor and showed me "trending" courses such as "How to Teach with Desire2Learn," "Social Media in the Classroom" and "How to Increase Learner Engagement." Surely, the more data I give them about my work and teaching, the more specific my recommendations will become.
DARPA has a program called MUSE (Mining and Understanding Software Enclaves) that is described as a "paradigm shift in the way we think about software." The first step is no less than for MUSE to suck up all of the world’s open-source software. That would be hundreds of billions of lines of code, which would then need to be organized it in at database.
A reason to attempt this is because the 20 billion lines of code written each year includes lots of duplication. MUSE will assemble a massive collection of chunks of code and tag it so that programmers can automatically be found and assembled. That means that someone who knows little about programming languages would be able to program.
Might MUSE be a way to launch non-coding programming?
This can also fit in with President Obama’s BRAIN Initiative and it may contribute to the development of brain-inspired computers.
Cognitive technology is still emerging, but Irving Wladawsky-Berger, formerly of IBM and now at New York University, has said “We should definitely teach design. This is not coding, or even programming. It requires the ability to think about the problem, organize the approach, know how to use design tools.”
Most teachers have stated learning objectives for their courses. They describe what we plan to teach and how we plan to assess students.
You may have read this summer about a case involving whether a professor can be required to write those down on a syllabus. A professor at the College of Charleston brought a lawsuit against the school that claimed that he was losing his job for refusing to include learning outcomes (the same as objectives?) in his syllabus.
The answer to the question of whether a course can not have learning objectives is a pretty resounding No. Of course, I'm sure students could point out some truly dreadful courses that did not have clear objectives or outcomes. Whether they are stated explicitly to students, probably in the syllabus, is the real question in that case. My answer to this second question of whether or not a course can not have clearly stated objectives is a resounding Yes.
Faculty need to consciously establish their goals and objectives in designing the course, but they also need to communicate those to students.
I would say that kind of information information should be available to a student before she even signs up for the course, perhaps in a course catalog or online page about the course. The objectives should also be explained in greater detail in the syllabus and in the course itself.
That is an instructional design task. I was very surprised how difficult it was to get faculty that I worked with on course design to understand the difference between a goal and an objective. We can get bogged down and confused in talking about goals, objectives and outcomes. If faculty are confused, certainly the students will be confused as well.
In a bit of an oversimplification, a goal is an overarching principle that guides decision making, while objectives are specific, measurable steps that can be taken to meet the goal.
You can further muddy this academic water by adding similar, but not interchangeable, terms such as competencies and outcomes. In this document I found online and used in some version for faculty workshops, it says: "From an educational standpoint, competencies can be regarded as the logical building blocks upon which assessments of professional development are based. When competencies are identified, a program can effectively determine the learning objectives that should guide the learners’ progress toward their professional goals. Tying these two together will also help identify what needs to be assessed for verification of the program’s quality in its effectiveness towards forming competent learners...In short, objectives say what we want the learners to know and competencies say how we can be certain they know it."
Whatever terminology you use, teachers need to know the larger goals in order to design the ways they will be presented and how they will be measured. Students need to knew as early as possible those last two parts.