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What is a learner profile?  A learner profile includes three elements: Learning transcript: grades, courses (and/or learning levels), state and district achievement data Personalized learning information: supplemental achievement data, record of services received, feedback on work habits, record of extracurricular activities and work/service experiences. Portfolio of student work: collection of personal best work products.

What about children with disconnected parents? As the number of learning options expands many students and families would benefit from a chosen guide. The Donnell Kay Foundation imagines a new system of education where learners create customized paths with advocates who work with them to connect their present learning to their desired future. This role of mentor/advocate/coach could benefit all students but particularly students without the benefit of engaged parents. In some cases, parents/guardians will choose to allow designees (e.g., mentors, relatives) to manage learner profile privacy settings. Young people in the foster care and juvenile justice system may have a court (or state) appointed guide that would manage privacy settings.

Data Quality Campaign recently noted, “With access to current education data child welfare staff can help the highly mobile students in foster care achieve school success by providing support such as the following: helping with timely enrollment and transfer of credits if a school change is needed, identifying the need for educational supports, working with school staff to address attendance and discipline issues, and assisting with transition planning to post-school activities such as higher education.”

But investing in both strategies to minimize those issues (via a sophisticated commenting, social management, or forum system) and people to help soothe the pain is very much a way to help solve those pain points. If you’re not investing, you’re just opening yourself up to problems.

A controlled community of members commenting on a subject? Perhaps a better one.

public interaction—particularly, the framing of that interaction—needs to make sense with your association’s overall business goals,and if it doesn’t, it’s worth considering cutting bait.

Drucker’s solutions for fragmented executives—reserve large blocks of time on your calendar, don’t answer the phone, and return calls in short bursts once or twice a day—sound remarkably like the ones offered up by today’s time- and information-management experts.2

Add to these challenges a torrent of e-mail, huge volumes of other information, and an expanding variety of means—from the ever-present telephone to blogs, tweets, and social networks—through which executives can connect with their organizations and customers, and you have a recipe for exhaustion. Many senior executives literally have two overlapping workdays: the one that is formally programmed in their diaries and the one “before, after, and in-between,” when they disjointedly attempt to grab spare moments with their laptops or smart phones, multitasking in a vain effort to keep pace with the information flowing toward them.

First, multitasking is a terrible coping mechanism.

Ecosystem” conveys the idea that all the pieces of an economy come together in particular places, and that their strength and interactions determine prosperity and economic growth.

Think of it as your garden, where you need fertile soil, seeds, and other ingredients to make things grow.

Four issues strike me as key: turning ideas into enterprises; linking small and large businesses; better connecting education to jobs; and encouraging cross-sector collaboration.

Algorithms have become one of the most powerful arbiters in our lives. They make decisions about the news we read, the jobs we get, the people we meet, the schools we attend and the ads we see. Yet there is growing evidence that algorithms and other types of software can discriminate.

The people who write them incorporate their biases, and algorithms often learn from human behavior, so they reflect the biases we hold.

Fairness, Accountability and Transparency in Machine Learning workshop, which considers the role that machines play in consequential decisions in areas like employment, health care and policing.

teachers are far more likely to use technology to make their own jobs easier and to supplement traditional instructional strategies than to put students in control of their own learning. Case study after case study describe a common pattern inside schools: A handful of "early adopters" embrace innovative uses of new technology, while their colleagues make incremental or no changes to what they already do.

numerous culprits

Washington-based International Society for Technology in Education

Also swelling is the number of adjuncts. They now make up 50 to 75 percent of those teaching in higher education. Why colleges rely so much on adjuncts has been discussed thoughtfully and at length elsewhere; chief among the reasons are that they are not as expensive as tenure-track professors, their scheduling can more easily align with the needs of the college, and firing them is not fraught with the same peril as firing full-time faculty members. It should hardly come as a surprise that all of the factors that make adjuncts attractive to administrators make them equally attractive to union organizers. For example, at Washington University in St. Louis, where adjuncts voted 138 to 111 in favor of organizing, the core issues were low wages, lack of benefits, and lack of job security.

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