diigo Hub

0 0

--Originally published at t509massive on Diigo

Annotations:
  • Privatization of data – be it of online users or students – is a challenge for social science and social justice. It is exacerbated by algorithms, terms and conditions, and disparities in bureaucratic access.
  • This is the counter history of disruption that isn’t about Roaming Autodidacts but rank and file men and women trying to make a dollar out of fifteen cents financed at 6.21% and amortized over 15 years.
  • we should reinvigorate inequality regimes as an analytical framework to expand the understanding of organizational contexts to span physical and digital spaces.
  • methodological choices that come from that framework: hybrid methods, institutional ethnographies, platform studies and longitudinal analysis are well-suited to these shifting socio-organizational contexts.

Tags:

0 0

--Originally published at t509massive on Diigo

Annotations:
  • semi-automated system to alert students to when they’re in danger of doing poorly in a course. It makes use of data points like grades as well as “time on task,” while adding in academic risk factors derived from their demographic profile. The same grades and time on task for a low-risk student may not trigger a warning as they would for a high-risk student.
  • the goal is to improve grades and increase retention. By these measurements, Course Signals, at least to some (still debatable) degree, “works.”

  • What if we believe that a student’s education should extend beyond “tips, tricks, and hints,” for getting better grades?

     

    What if we believe that failure is a productive part of learning?

     

    What if we worry that their adult lives will not come with Course Signal warnings?

     

    And mostly, what if we worry that this institutional focus on capturing and employing data distracts us from what is most meaningful about the college experience at places like Purdue?

  • two key areas: student support, and student experiences.

     

    Under support, they asked if students had, “at least one professor who made me excited about learning,” if their “professors cared about me as a person,” and if they “had a mentor who encouraged me to pursue my goals and ambitions.”

  • The experiential criteria focuses on the type and breadth of work, whether or not they had the opportunity to work on a semester-long project, if they did an internship that seemed related to their studies, and if they were active in extracurricular organizations.

  • Perhaps Course Signals is a way to engender feelings that their professors care about them as people.

     

    Or maybe Course Signals tells students that they are a data point. Or maybe Course Signals becomes a crutch, substituting tips and tricks for in-depth human interaction, the kind we know alters lives.

  • If I look into Course Signals and see two students with identical grades, but only one of whom receives a warning, I will know that there is a demographic red flag on one of their records.
  • As Kamenetz says at the end of her article, “Learning analytics has yet to demonstrate it’s big beneficial breakthrough” its “penicillin” in the words of HarvardX researcher Justin Reich.
  • we’re not paying a huge swath of college instructors a living wage. In the zero sum game of higher ed budgets, every dollar to technology is one less for actual human labor. Ask the average instructor if they’d rather have Course Signals for their course, or a raise.

Tags:

0 0

--Originally published at t509massive on Diigo

Annotations:
  • semi-automated system to alert students to when they’re in danger of doing poorly in a course. It makes use of data points like grades as well as “time on task,” while adding in academic risk factors derived from their demographic profile. The same grades and time on task for a low-risk student may not trigger a warning as they would for a high-risk student.
  • the goal is to improve grades and increase retention. By these measurements, Course Signals, at least to some (still debatable) degree, “works.”

  • What if we believe that a student’s education should extend beyond “tips, tricks, and hints,” for getting better grades?

     

    What if we believe that failure is a productive part of learning?

     

    What if we worry that their adult lives will not come with Course Signal warnings?

     

    And mostly, what if we worry that this institutional focus on capturing and employing data distracts us from what is most meaningful about the college experience at places like Purdue?

  • two key areas: student support, and student experiences.

     

    Under support, they asked if students had, “at least one professor who made me excited about learning,” if their “professors cared about me as a person,” and if they “had a mentor who encouraged me to pursue my goals and ambitions.”

  • The experiential criteria focuses on the type and breadth of work, whether or not they had the opportunity to work on a semester-long project, if they did an internship that seemed related to their studies, and if they were active in extracurricular organizations.

  • Perhaps Course Signals is a way to engender feelings that their professors care about them as people.

     

    Or maybe Course Signals tells students that they are a data point. Or maybe Course Signals becomes a crutch, substituting tips and tricks for in-depth human interaction, the kind we know alters lives.

  • If I look into Course Signals and see two students with identical grades, but only one of whom receives a warning, I will know that there is a demographic red flag on one of their records.
  • As Kamenetz says at the end of her article, “Learning analytics has yet to demonstrate it’s big beneficial breakthrough” its “penicillin” in the words of HarvardX researcher Justin Reich.
  • we’re not paying a huge swath of college instructors a living wage. In the zero sum game of higher ed budgets, every dollar to technology is one less for actual human labor. Ask the average instructor if they’d rather have Course Signals for their course, or a raise.

Tags:

0 0

--Originally published at t509massive on Diigo

Annotations:
  • If history MOOCs catch on, fewer academic historians will be working at research and indeed working at all. Most historical research at present is done by academics whose primary responsibility is teaching. If successful teaching can be delivered via MOOCs, then why should thousands of colleges and universities across the land (and for that matter, around the world) employ historians to teach and to do research?
  • The MOOC market, like televangelism and professional athletic endorsements, will be a winner-take-all market, in which a few star performers rake in almost all the business. So whoever has the most successful MOOC on the American Revolution will likely be well paid, especially if universities can make money selling MOOC tuition, certificates, or degrees—and no one else need be paid at all
  • he number of people researching the American Revolution, and the variety of approaches brought to the subject, will plummet.
  • If history MOOCs work, far more historians will have more time for research. A boom in historical research and debate will follow. At present, most academic historians spend most of their working hours, and in many cases most of their waking hours, engaged in routine (if sometimes agreeable) tasks. They prepare lectures or discussion sections. Sometimes they give the same lecture more than once in the same day or week, and they often lead small-group discussions on the same topic several times a week. They grade student tests and papers. Much time might be saved if they instead convert their courses into MOOCs.
  • some veterans of the process say preparing a MOOC takes 12 times as many hours as preparing a conventional course.
  • Today hundreds of historians teach the American Revolution but scarcely do any research on anything because their harried lives—chock full of class prep and grading—do not permit it. With MOOCs, their routine burdens will be lightened and their opportunity to research, write, and publish will expand in proportion. MOOCs will not only allow the very best teachers to reach hundreds of thousands, maybe millions, of students around the world at almost no cost, but will free up gazillions of professor-hours that could go into research.

Tags:

0 0

--Originally published at t509massive on Diigo

Annotations:
  • I think it's time for us non-superprofessors to forcefully explain to our newly famous colleagues how their MOOCs are already adversely affecting the terms and conditions of our employment, and are likely to do so even more in the future.
  • While MOOCs may serve a purpose as nerdy edu-tainment for people who are so inclined, a workforce trained without close contact with professors of any kind might as well not attend college at all. Going to the library and reading a bunch of books would be equally effective, and probably a whole lot cheape

Tags:

0 0

--Originally published at t509massive on Diigo

Annotations:
  • The History Channel gives the university a foothold in television, while bringing higher production values than would an entry in a course catalog or a pamphlet in a guidance counselor’s office.
  • we should use technology for the things technology is good at,”
  • And bringing the sights and sounds of history to life is something that technology can be really good at.”

Tags:

0 0

--Originally published at t509massive on Diigo

Annotations:
  • The History Channel gives the university a foothold in television, while bringing higher production values than would an entry in a course catalog or a pamphlet in a guidance counselor’s office.
  • we should use technology for the things technology is good at,”
  • And bringing the sights and sounds of history to life is something that technology can be really good at.”

Tags:

Prev123...5Next Page 2 of 5
© This site was designed by EdTechTeacher, Inc