Blogs (1) >>

This program is tentative and subject to change.

Thu 27 Feb 2025 14:03 - 14:22 at Meeting Rooms 315-316 - Data Science #1

Computing education is often confined to the context of formal education or after-school programs; however, there is a growing industry built around adult education, including workshops, coding intensives, online learning, and the workplace. Amidst these efforts, little research has explored the workplace as a site for novice adult learners to develop computing skills. In this experience report, we present an integrated training curriculum for adults at DAP (Data Apprenticeship Program), an organization that trains and employs novice adults from groups historically underrepresented in computing who seek to advance their career through on-the-job learning. “Data Apprentices” are hired to complete client projects by providing data services for local organizations, nonprofits, and businesses. Training is integrated into employees’ weekly responsibilities at DAP, and the curriculum consists of four modules: Microsoft Excel, Critical Data Literacy, Python Fundamentals, and Career Development. In this report, we reflect holistically on the evolution of the curriculum over the years. We distill our reflection into insights to inform other integrated training programs that aim to equip novice adults with computing skills in the workplace.

This program is tentative and subject to change.

Thu 27 Feb

Displayed time zone: Eastern Time (US & Canada) change

13:45 - 15:00
Data Science #1Papers at Meeting Rooms 315-316
13:45
18m
Talk
Approachable Machine Learning Education: A Spiral Pedagogy Approach with Experiential Learning
Papers
Meiying Qin York University
14:03
18m
Talk
A Window into DataWorks: Developing an Integrated Work-Training Curriculum for Novice Adults
Papers
Lara Schenck Georgia Institute of Technology, Dana Priest DataWorks at Georgia Tech, Gabe Dubose Emory University, Zajerria Godfrey Maynard Jackson High School, Annabel Rothschild Georgia Institute of Technology, Benjamin Shapiro Georgia State University, Betsy Disalvo Georgia Institute of Technology
14:22
18m
Talk
"I'm not sure, but...": Expert Practices that Enable Effective Code Comprehension in Data Science
Papers
Christopher Lum UC San Diego, Guoxuan Xu UC San Diego, Sam Lau University of California at San Diego
14:41
18m
Talk
Larger than Life In-Class Demonstrations for Introductory Machine Learning
Papers
Henry Chai Carnegie Mellon University, Matthew R. Gormley Carnegie Mellon University