Support

Support Options

  • Knowledge Base

    Find information on common questions and issues.

  • Support Messages

    Check on the status of your correspondences with members of the QUBES team.

Contact Us

About you
About the problem

DIGging Into Data and getting the credit

By Kaitlin Bonner1, Arietta Fleming-Davies2, Kristine Grayson3, Ben Wu4, Raisa Hernández-Pacheco3

1. St. John Fisher College 2. QUBES; Radford University 3. University of Richmond 4. Texas AM University

Presentation on using and adapting OER data-centric resources

Listed in Teaching Materials | resource by group Evolution of Data in the Classroom: From Data to Data Science (SW 2019)

Version 1.0 - published on 18 Jul 2019 doi:10.25334/E04E-K962 - cite this

Licensed under CC Attribution-ShareAlike 4.0 International according to these terms

digging into data first slide.PNG

Description

With the importance of quantitative skill development in biology curricula clearly articulated in Vision and Chang (AAAS, 2012), numerous educators have answered the call to create and facilitate innovative data-centric pedagogies to promote data literacy and skill development in their classrooms. Data-centric curricula using authentic inquiry are now readily available, allowing faculty to find and adapt resources for use in their classroom without reinventing the wheel. Many of these data-centric resources are nested within the educational paradigm of Open Education Resources (OERs), and while these resources are freely accessible adoption and adaptation of these resources is not quite ubiquitous. In this session you will learn about where and how to find OER data-centric resources, what it means to go through the OER lifecycle of a resources, and how to get credit for your educational scholarship by posting your adaptations of these resources on QUBES. Come ready to explore the data-centric resources on QUBES and start thinking about how you would Use, Adapt, Refine, and Share your adaptations with the QUBES community and beyond.

For more information about the DIG project click here

Contents

Cite this work

Researchers should cite this work as follows:

Tags

Evolution of Data in the Classroom: From Data to Data Science (SW 2019)

When watching a resource, you will be notified when a new version is released.