Digital Literacy for St. Cloud State University
Jan Resseger: Trust The Teacher to Tell You How Your Child Is Doing, Not Big Data
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more on big data and education in this IMS blog
https://blog.stcloudstate.edu/ims?s=big+data+education
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more on big data in this IMS blog
https://blog.stcloudstate.edu/ims?s=big+data
more on IoT in this IMS blog
https://blog.stcloudstate.edu/ims?s=iot
South Korea is using the analysis, information and references provided by this integrated data — all different real-time responses and information produced by the platform are promptly conveyed to people with different AI-based applications.
Whenever someone is tested positive for COVID-19, all the people in the vicinity are provided with the infected person’s travel details, activities, and commute maps for the previous two weeks through mobile notifications sent as a push system.
counting how many times students use electronic library resources or visit in person, and comparing that to how well the students do in their classes and how likely they are to stay in school and earn a degree. And many library leaders are finding a strong correlation, meaning that students who consume more library materials tend to be more successful academically.
carefully tracking how library use compares to other metrics, and it has made changes as a result—like moving the tutoring center and the writing lab into the library. Those moves were designed not only to lure more people into the stacks, but to make seeking help more socially-acceptable for students who might have been hesitant.
a partnership between the library, which knows what electronic materials students use, and the technology office, which manages other campus data such as usage of the course-management system. The university is doing a study to see whether library usage there also equates to student success.
The issue of privacy also emerged during a session on libraries and data at the annual Educause conference earlier this month.
https://www.facebook.com/BusinessInsiderUK/videos/vb.1649495281942842/2504257946466567/
#FakeNews #DigitalRecommendationEngines interpretation of data, market dependency “stupid smart recommendation engines” monopolistic structure, keep competitiveness, big data, market concentration
Reinventing Capitalism in the Age of Big Data (Basic Books / Hachette, 2018) by Viktor Mayer-Schönberger and Thomas Ramge.
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more on this broad topic in this IMS blog:
https://blog.stcloudstate.edu/ims/2018/03/05/quit-social-media/
and in the LIB 290 blog:
http://blog.stcloudstate.edu/lib290/2018/03/01/duckduckgo-privacy-free-service/
February 9, 201811:37 AM ET ADAM FRANK
Combine the superfast calculational capacities of Big Compute with the oceans of specific personal information comprising Big Data — and the fertile ground for computational propaganda emerges. That’s how the small AI programs called bots can be unleashed into cyberspace to target and deliver misinformation exactly to the people who will be most vulnerable to it. These messages can be refined over and over again based on how well they perform (again in terms of clicks, likes and so on). Worst of all, all this can be done semiautonomously, allowing the targeted propaganda (like fake news stories or faked images) to spread like viruses through communities most vulnerable to their misinformation.
According to Bolsover and Howard, viewing computational propaganda only from a technical perspective would be a grave mistake. As they explain, seeing it just in terms of variables and algorithms “plays into the hands of those who create it, the platforms that serve it, and the firms that profit from it.”
Computational propaganda is a new thing. People just invented it. And they did so by realizing possibilities emerging from the intersection of new technologies (Big Compute, Big Data) and new behaviors those technologies allowed (social media). But the emphasis on behavior can’t be lost.
People are not machines. We do things for a whole lot of reasons including emotions of loss, anger, fear and longing. To combat computational propaganda’s potentially dangerous effects on democracy in a digital age, we will need to focus on both its howand its why.
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more on big data in this IMS blog
https://blog.stcloudstate.edu/ims?s=big+data
more on bots in this IMS blog
https://blog.stcloudstate.edu/ims?s=bot
more on fake news in this IMS blog
https://blog.stcloudstate.edu/ims?s=fake+news
By Dian Schaffhauser 05/17/17
https://campustechnology.com/articles/2017/05/17/new-report-examines-use-of-big-data-in-ed.aspx
new report from the National Academy of Education “Big Data in Education,” summarizes the findings of a recent workshop held by the academy
three federal laws: Family Educational Rights and Privacy Act (FERPA), the Children’s Online Privacy Protection Act (COPPA) and the Protection of Pupil Rights Amendment (PPRA).
over the last four years, 49 states and the District of Columbia have introduced 410 bills related to student data privacy, and 36 states have passed 85 new education data privacy laws. Also, since 2014, 19 states have passed laws that in some way address the work done by researchers.
researchers need to get better at communicating about their projects, especially with non-researchers.
One approach to follow in gaining trust “from parents, advocates and teachers” uses the acronym CUPS:
Second, researchers must pin down how to share data without making it vulnerable to theft.
Third, researchers should build partnerships of trust and “mutual interest” pertaining to their work with data. Those alliances may involve education technology developers, education agencies both local and state, and data privacy stakeholders.
Along with the summary report, the results of the workshop are being maintained on a page within the Academy’s website here.
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more on big data in education in this IMS blog
https://blog.stcloudstate.edu/ims?s=big+data
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more on big data in this IMS blog
https://blog.stcloudstate.edu/ims?s=big+data
http://www.npr.org/2016/09/09/492297006/how-will-big-data-change-the-way-we-live
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more on big data in this IMS blog