onlinelearning

December 16, 2020 150 × 100 5 lessons learned about virtual school during the pandemic

Illustration of student looking at monitor of online classroom (Image: Hatice EROL/Pixabay)

Latest Library Links

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Kelly Jensen writes: “Thanks to a new proviso in the South Carolina state budget, at least one public library system in the state has made the decision to acquire no new books for those under the age of 18. In a statement released across York County Public Library’s social media October 11, the library board chair announced the moratorium on new purchases until the State better clarifies what is and is not permitted in public libraries.”

Book Riot, Oct. 14; York County (S.C.) Public Library, Oct. 11
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Hailley Fargo writes: After chairing a double search committee this spring, “I’m happy to report our two searches were successful and our new folks started this summer. Now that our new departmental colleagues are settled, I thought I would write a bit about how we approached onboarding and things I’ve learned in that process. In January, as we developed our departmental goals for the year, we decided to have an onboarding specific goal. This meant everyone had a vested interest in creating this experience.”

ACRLog, Oct. 10
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Ted Lewis writes: “This semester will likely be extra difficult for LGBTQ+ youth and particularly transgender youth, as their very identities are up for debate in the presidential election. Libraries and librarians can make the difference in the lives of their transgender students by being the safe place and affirming adults that these youth desperately need. The Human Rights Campaign Foundation’s Project THRIVE [of which the American Association of School Librarians is a partner] has created the 2024 Back-to-School Checklist that features best practices and policies to support LGBTQ+ and particularly transgender students.

Knowledge Quest, Oct. 10
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Jay Waagmeester writes: “Florida education policies targeting classroom discussion and materials related to sexual orientation, gender identity, race, and ethnic studies are being felt by educators and parents, a new study found. The Limitation Effect: Experiences of State Policy-Driven Education Restriction in Florida’s Public Schools, was conducted by professors at New York University and the University of California San Diego. Results have included librarians refraining from purchasing books mentioning LGBTQ experiences, limits on discussions of Black experiences, denial of access to Advanced Placement courses, limits on professional development to support students with disabilities, and teachers ceasing use of literature not approved by the state.”

New study documents impact of censorship in schools
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Dan Groberg writes: “In July 2023, on my 12th day as executive director of Kellogg-Hubbard Library (KHL) in Montpelier, Vermont, there was a massive flood. I had barely learned where to hang my coat, let alone how to process payroll, before I was dealt an unforeseeable crisis. Beyond the financial strain [of rebuilding], staffers at KHL and I still had much to do to pick up the pieces. The past year has taught us how to balance recovering from disaster while remaining a pillar for the community in a time of need.

American Libraries column, Sept./Oct.
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Ted Quiballo and Sarah P. Lee write: “For nearly a decade, Northwestern University (NU) in Evanston, Illinois, and the Chicago office of the national nonprofit World Relief have worked together to offer free summer programming for families who are refugees or seeking asylum. In 2021, after the US military withdrew its final troops from Afghanistan, tens of thousands of Afghan families fled to the US. That’s when NU’s Seeley G. Mudd Library joined the partnership, hosting dozens of these families’ children in its makerspace each summer. The program encourages participants to gain new academic skills, leadership experience, and build connections in their new community.”

American Libraries Trend, Sept./Oct.
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Charles Q. Choi writes: “Artificial intelligence chatbots such as ChatGPT and other applications powered by large language models have found widespread use, but are infamously unreliable. A common assumption is that scaling up the models driving these applications will improve their reliability—for instance, by increasing the amount of data they are trained on, or the number of parameters they use to process information. However, more recent and larger versions of these language models have actually become more unreliable, not less, according to a new study,” largely because recent models are less likely to acknowledge if they don’t know an answer for certain.

IEEE Spectrum, Oct. 3; Nature, Sept. 25

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