Searching for "gen z"

bio lab in emergency teaching

https://www.facebook.com/groups/onlinelearningcollective/permalink/599387467358622/

Hi everyone- my mom has been teaching Bio 101 with a lab for 39 years. I’m working with her to get ready for the fall semester online but Science isn’t my field. Any recommendations for online bio labs?

Stephanie Edelmann I’m still working on my lab, but here is an extensive list of online resources that was shared with faculty at our school.

https://docs.google.com/…/1Mv0EyCw2QeFIpW5P5qNR5EW…/edit

Rebecca Westphal Carolina has kits…. but they are mostly on back order and hard to get for fall (in US?). You could think of putting together your own kits for students to pick up. There are also many labs using “household” materials such as this spinach photosynthesis lab http://www2.nau.edu/…/photosynthesis/photosynthesis.html.

For introducing basic chemistry I really like the “Build an Atom” simulation on the PhET website, although it’s more of an activity than a “lab”. HHMI biointeractive has lots of free resources and data sets that you could build on, including lots for natural selection — try searching “rock pocket mouse natural selection” on the biointeractive website.

Rachel Scherer https://phet.colorado.edu/_m/ is one of my go to favorites. I have some instructors testing labster out this summer. I haven’t heard anything back so I am guessing it is working well for them. Also

https://docs.google.com/spreadsheets/d/18iVSIeOqKjj58xcR8dYJS5rYvzZ4X1UGLWhl3brRzCM/htmlview?fbclid=IwAR2h4vyLqHtXW6M80CXTHZ4eUrv-TY8ljCMMZ52zMRGCqqgxwNt6Qq8zpF0#gid=0

Cheryl DeWyer Lindeman https://www.biointeractive.org

Cheryl DeWyer Lindeman https://www.shapeoflife.org/

Sondra LoRe https://qubeshub.org/community/groups/quant_bio_online

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more on emergency teaching in this IMS blog
https://blog.stcloudstate.edu/ims?s=emergency+teaching

Emergency Remote Teaching and Online Learning

The Difference Between Emergency Remote Teaching and Online Learning

 Published:

https://er.educause.edu/articles/2020/3/the-difference-between-emergency-remote-teaching-and-online-learning

Moving instruction online can enable the flexibility of teaching and learning anywhere, anytime, but the speed with which this move to online instruction is expected to happen is unprecedented and staggering.

“Online learning” will become a politicized term that can take on any number of meanings depending on the argument someone wants to advance.

Online learning carries a stigma of being lower quality than face-to-face learning, despite research showing otherwise. These hurried moves online by so many institutions at once could seal the perception of online learning as a weak option

Researchers in educational technology, specifically in the subdiscipline of online and distance learning, have carefully defined terms over the years to distinguish between the highly variable design solutions that have been developed and implemented: distance learning, distributed learning, blended learning, online learning, mobile learning, and others. Yet an understanding of the important differences has mostly not diffused beyond the insular world of educational technology and instructional design researchers and professionals.

Online learning design options (moderating variables)

  • Modality
    • Fully online
    • Blended (over 50% online)
    • Blended (25–50% online)
    • Web-enabled F2F

    Pacing

    • Self-paced (open entry, open exit)
    • Class-paced
    • Class-paced with some self-paced

    Student-Instructor Ratio

    • < 35 to 1
    • 36–99 to 1
    • 100–999 to 1
    • > 1,000 to 1

    Pedagogy

    • Expository
    • Practice
    • Exploratory
    • Collaborative

    Role of Online Assessments

    • Determine if student is ready for new content
    • Tell system how to support the student (adaptive instruction)
    • Provide student or teacher with information about learning state
    • Input to grade
    • Identify students at risk of failure
  • Instructor Role Online
    • Active instruction online
    • Small presence online
    • None

    Student Role Online

    • Listen or read
    • Complete problems or answer questions
    • Explore simulation and resources
    • Collaborate with peers

    Online Communication Synchrony

    • Asynchronous only
    • Synchronous only
    • Some blend of both

    Source of Feedback

    • Automated
    • Teacher
    • Peers
Source: Content adapted from Barbara Means, Marianne Bakia, and Robert Murphy, Learning Online: What Research Tells Us about Whether, When and How (New York: Routledge, 2014).
Typical planning, preparation, and development time for a fully online university course is six to nine months before the course is delivered. Faculty are usually more comfortable teaching online by the second or third iteration of their online courses.
In contrast to experiences that are planned from the beginning and designed to be online, emergency remote teaching (ERT) is a temporary shift of instructional delivery to an alternate delivery mode due to crisis circumstances. It involves the use of fully remote teaching solutions for instruction or education that would otherwise be delivered face-to-face or as blended or hybrid courses and that will return to that format once the crisis or emergency has abated.
A full-course development project can take months when done properly. The need to “just get it online” is in direct contradiction to the time and effort normally dedicated to developing a quality course. Online courses created in this way should not be mistaken for long-term solutions but accepted as a temporary solution to an immediate problem.

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More on online learning in this IMS blog
https://blog.stcloudstate.edu/ims?s=online+learning

Genrefication School Libraries Like Bookstores

How Genrefication Makes School Libraries More Like Bookstores

Gail Cornwall Jul 22, 2018 https://www.kqed.org/mindshift/51336/how-genrefication-makes-school-libraries-more-like-bookstores

Under the Dewey Decimal System that revolutionized and standardized book shelving starting in 1876, nonfiction essentially already gets the genrefication treatment with, for example, Music located in the 780s and Paleontology in the 560s. Yet most fiction is shelved in one big clump alphabetized by author’s last name.

Many librarians say the “search hurdle” imposed by Dewey classification (a system originally designed for adults) significantly reduces the odds of a child finding something new they’re likely to enjoy. In a genrefied library, on the other hand, a young reader standing near a favorite book need only stick out a hand to find more like it. (It’s a bit like the analog version of Amazon’s recommendation feature: “Customers who bought this item also bought”)

The Dewey-loyal also oppose genrefication in principle for, interestingly enough, the same reason others support it: self-sufficiency. Sure, they argue, kids might be better able to find a book independently in their school library, but what happens when they go to the public one? When they get to high school?

The debate has led to compromise positions. Some leave books for older students in the Dewey arrangement while genrefying for younger ones. Other librarians rearrange middle readers and young adult books but leave picture books shelved by author since it can be unclear how to categorize a story about a duck driving a tractor.

Policy for Artificial Intelligence

Law is Code: Making Policy for Artificial Intelligence

Jules Polonetsky and Omer Tene January 16, 2019

https://www.ourworld.co/law-is-code-making-policy-for-artificial-intelligence/

Twenty years have passed since renowned Harvard Professor Larry Lessig coined the phrase “Code is Law”, suggesting that in the digital age, computer code regulates behavior much like legislative code traditionally did.  These days, the computer code that powers artificial intelligence (AI) is a salient example of Lessig’s statement.

  • Good AI requires sound data.  One of the principles,  some would say the organizing principle, of privacy and data protection frameworks is data minimization.  Data protection laws require organizations to limit data collection to the extent strictly necessary and retain data only so long as it is needed for its stated goal. 
  • Preventing discrimination – intentional or not.
    When is a distinction between groups permissible or even merited and when is it untoward?  How should organizations address historically entrenched inequalities that are embedded in data?  New mathematical theories such as “fairness through awareness” enable sophisticated modeling to guarantee statistical parity between groups.
  • Assuring explainability – technological due process.  In privacy and freedom of information frameworks alike, transparency has traditionally been a bulwark against unfairness and discrimination.  As Justice Brandeis once wrote, “Sunlight is the best of disinfectants.”
  • Deep learning means that iterative computer programs derive conclusions for reasons that may not be evident even after forensic inquiry. 

Yet even with code as law and a rising need for law in code, policymakers do not need to become mathematicians, engineers and coders.  Instead, institutions must develop and enhance their technical toolbox by hiring experts and consulting with top academics, industry researchers and civil society voices.  Responsible AI requires access to not only lawyers, ethicists and philosophers but also to technical leaders and subject matter experts to ensure an appropriate balance between economic and scientific benefits to society on the one hand and individual rights and freedoms on the other hand.

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more on AI in this IMS blog
https://blog.stcloudstate.edu/ims?s=artificial+intelligence

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