LASER Orientation

Instructional materials for the LASER Orientation and other modules are linked below and make extensive use of the following tools:

  1. GitHub is used to host LASER curriculum repositories, websites, and webpages and are accessible to the public. Instructors are welcome to fork or clone this repository and adapt for their own purposes.

  2. Posit Cloud and accompanying workspaces are where students complete interactive coding assignments in R or Python such as Code-Alongs, Case Studies, Badges and Microcredentials.

  3. Quarto is used to create all curriculum materials and activities for LASER, including presentations, coding activities, and even this website.

To learn more about the suite of tools used for the design and delivery of instructional activities, visit the LASER Toolkit page.

Github
Repository for Instructors
Posit Cloud Workspace for Learners

Orientation Module: The LASER Toolkit

The Orientation Module is designed to get learners up and running with the concepts, tools, and processes that guide the LASER curriculum. The orientation begins with a Conceptual Overview focused on the benefits of reproducible research (Gandrud 2013) and tools used by LASER to for this purpose. The Code-Along is a gentle introduction to R/Python and the data-intensive research workflow introduced by Krumm, Means, and Bienkowski (2018) and covered in greater depth by . The coding Case Study expands upon the code-along and introduces working with Quarto, an open-source scientific and technical publishing system. Finally, learners earn their first LASER Badge by publishing their work to the web.

Conceptual
Overview
The LASER Toolkit & Reproducible Research
Code Along The Data-Intensive Research Workflow in R | Python
Readings &
Reflection
Reproducible Research & DIR Workflow
Case Study A Coding Case Study with Quarto | R Key | Python Key
Badge LASER Orientation Badge
Module Survey Feedback Form After Finishing Module

References

Gandrud, Christopher. 2013. Reproducible Research with r and r Studio (3rd Edition). CRC Press. http://github.com/christophergandrud/Rep-Res-Book.
Krumm, Andrew, Barbara Means, and Marie Bienkowski. 2018. Learning Analytics Goes to School. Routledge. https://doi.org/10.4324/9781315650722.