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--Originally published at t509massive on Diigo

Annotations:
  • The Mobile Minds Specialists were selected due to their ability to integrate technology into their classrooms, demonstrating that teaching with technology as a vehicle to deliver content and further engage students can impact learning beyond what we had previously thought possible.
  • our teachers, principals and Mobile Minds Specialists collaborate during weekly PLC meetings to develop technology-embedded lesson plans.

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--Originally published at t509massive on Diigo

Annotations:
  • The Mobile Minds Specialists were selected due to their ability to integrate technology into their classrooms, demonstrating that teaching with technology as a vehicle to deliver content and further engage students can impact learning beyond what we had previously thought possible.
  • our teachers, principals and Mobile Minds Specialists collaborate during weekly PLC meetings to develop technology-embedded lesson plans.

Tags:

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--Originally published at t509massive on Diigo

Annotations:
  • The Mobile Minds Specialists were selected due to their ability to integrate technology into their classrooms, demonstrating that teaching with technology as a vehicle to deliver content and further engage students can impact learning beyond what we had previously thought possible.
  • our teachers, principals and Mobile Minds Specialists collaborate during weekly PLC meetings to develop technology-embedded lesson plans.

Tags:

0 0

--Originally published at t509massive on Diigo

Annotations:
  • The Mobile Minds Specialists were selected due to their ability to integrate technology into their classrooms, demonstrating that teaching with technology as a vehicle to deliver content and further engage students can impact learning beyond what we had previously thought possible.
  • our teachers, principals and Mobile Minds Specialists collaborate during weekly PLC meetings to develop technology-embedded lesson plans.

Tags:

0 0

--Originally published at t509massive on Diigo

Annotations:
  • The Mobile Minds Specialists were selected due to their ability to integrate technology into their classrooms, demonstrating that teaching with technology as a vehicle to deliver content and further engage students can impact learning beyond what we had previously thought possible.
  • our teachers, principals and Mobile Minds Specialists collaborate during weekly PLC meetings to develop technology-embedded lesson plans.

Tags:

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--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.

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--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: