Artwork

Nội dung được cung cấp bởi Marshall Poe. Tất cả nội dung podcast bao gồm các tập, đồ họa và mô tả podcast đều được Marshall Poe hoặc đối tác nền tảng podcast của họ tải lên và cung cấp trực tiếp. Nếu bạn cho rằng ai đó đang sử dụng tác phẩm có bản quyền của bạn mà không có sự cho phép của bạn, bạn có thể làm theo quy trình được nêu ở đây https://vi.player.fm/legal.
Player FM - Ứng dụng Podcast
Chuyển sang chế độ ngoại tuyến với ứng dụng Player FM !

Matthew Berland and Antero Garcia, "The Left Hand of Data: Designing Education Data for Justice" (MIT Press, 2024)

52:54
 
Chia sẻ
 

Manage episode 418353964 series 2421486
Nội dung được cung cấp bởi Marshall Poe. Tất cả nội dung podcast bao gồm các tập, đồ họa và mô tả podcast đều được Marshall Poe hoặc đối tác nền tảng podcast của họ tải lên và cung cấp trực tiếp. Nếu bạn cho rằng ai đó đang sử dụng tác phẩm có bản quyền của bạn mà không có sự cho phép của bạn, bạn có thể làm theo quy trình được nêu ở đây https://vi.player.fm/legal.

Educational analytics tend toward aggregation, asking what a “normative” learner does. In The Left Hand of Data: Designing Education Data for Justice (MIT Press, 2024, open access at this link), educational researchers Matthew Berland and Antero Garcia start from a different assumption—that outliers are, and must be treated as, valued individuals. Berland and Garcia argue that the aim of analytics should not be about enforcing and entrenching norms but about using data science to break new ground and enable play and creativity. From this speculative vantage point, they ask how we can go about living alongside data in a better way, in a more just way, while also building on the existing technologies and our knowledge of the present.

The Left Hand of Data explores the many ways in which we use data to shape the possible futures of young people—in schools, in informal learning environments, in colleges, in libraries, and with educational games. It considers the processes by which students are sorted, labeled, categorized, and intervened upon using the bevy of data extracted and collected from individuals and groups, anonymously or identifiably. When, how, and with what biases are these data collected and utilized? What decisions must educational researchers make around data in an era of high-stakes assessment, surveillance, and rising inequities tied to race, class, gender, and other intersectional factors? How are these complex considerations around data changing in the rapidly evolving world of machine learning, AI, and emerging fields of educational data science? The surprising answers the authors discover in their research make clear that we do not need to wait for a hazy tomorrow to do better today.

Jen Hoyer is Technical Services and Electronic Resources Librarian at CUNY New York City College of Technology. Jen edits for Partnership Journal and organizes with the TPS Collective. She is co-author of What Primary Sources Teach: Lessons for Every Classroom and The Social Movement Archive.

Learn more about your ad choices. Visit megaphone.fm/adchoices

Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/education

  continue reading

999 tập

Artwork
iconChia sẻ
 
Manage episode 418353964 series 2421486
Nội dung được cung cấp bởi Marshall Poe. Tất cả nội dung podcast bao gồm các tập, đồ họa và mô tả podcast đều được Marshall Poe hoặc đối tác nền tảng podcast của họ tải lên và cung cấp trực tiếp. Nếu bạn cho rằng ai đó đang sử dụng tác phẩm có bản quyền của bạn mà không có sự cho phép của bạn, bạn có thể làm theo quy trình được nêu ở đây https://vi.player.fm/legal.

Educational analytics tend toward aggregation, asking what a “normative” learner does. In The Left Hand of Data: Designing Education Data for Justice (MIT Press, 2024, open access at this link), educational researchers Matthew Berland and Antero Garcia start from a different assumption—that outliers are, and must be treated as, valued individuals. Berland and Garcia argue that the aim of analytics should not be about enforcing and entrenching norms but about using data science to break new ground and enable play and creativity. From this speculative vantage point, they ask how we can go about living alongside data in a better way, in a more just way, while also building on the existing technologies and our knowledge of the present.

The Left Hand of Data explores the many ways in which we use data to shape the possible futures of young people—in schools, in informal learning environments, in colleges, in libraries, and with educational games. It considers the processes by which students are sorted, labeled, categorized, and intervened upon using the bevy of data extracted and collected from individuals and groups, anonymously or identifiably. When, how, and with what biases are these data collected and utilized? What decisions must educational researchers make around data in an era of high-stakes assessment, surveillance, and rising inequities tied to race, class, gender, and other intersectional factors? How are these complex considerations around data changing in the rapidly evolving world of machine learning, AI, and emerging fields of educational data science? The surprising answers the authors discover in their research make clear that we do not need to wait for a hazy tomorrow to do better today.

Jen Hoyer is Technical Services and Electronic Resources Librarian at CUNY New York City College of Technology. Jen edits for Partnership Journal and organizes with the TPS Collective. She is co-author of What Primary Sources Teach: Lessons for Every Classroom and The Social Movement Archive.

Learn more about your ad choices. Visit megaphone.fm/adchoices

Support our show by becoming a premium member! https://newbooksnetwork.supportingcast.fm/education

  continue reading

999 tập

Minden epizód

×
 
Loading …

Chào mừng bạn đến với Player FM!

Player FM đang quét trang web để tìm các podcast chất lượng cao cho bạn thưởng thức ngay bây giờ. Đây là ứng dụng podcast tốt nhất và hoạt động trên Android, iPhone và web. Đăng ký để đồng bộ các theo dõi trên tất cả thiết bị.

 

Hướng dẫn sử dụng nhanh