Computing-Integrated Teacher Education at the City University of New York

Analyze and Visualize Data

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The Premise

Computers give us the ability to collect, analyze, and visualize data quickly and efficiently which opens the possibility to collect more data, conduct iterative or exploratory analyses, and to tinker with our visualizations in order to best express our ideas. This integration will focus on help teacher candidates build their understanding of the social context of these data analysis and visualization and the possibilities opened up by computational tools.

Courses that would lend themselves to this integration

  1. Foundations – Childhood, Early Childhood, Secondary
  2. Disciplinary methods courses
  3. Student teaching seminar
  4. Education Technology

Potential Conversations and Activities

Teaching in this area could support teacher candidates to teach and learn…

About computing/tech

To support teacher learning

  • Teacher candidates read about the history of standardized testing and discuss the context and purpose of this form of testing and unpack the ideas of a distribution of scores and measures of centrality
  • Teacher candidates collect data from their community, organize it in matrices (each row an observation, item, etc.), to filter, sort, or group the data, and draw inferences

To support teacher pedagogy

  • Teacher candidates graph student test scores in a fictional data set against other variables about students and draw inferences
With computing/tech

To support teacher learning

  • Teacher candidates are given data visualizations of student populations and school performance of school of education partner schools and asked to connect theory to potential practical interventions

To support teacher pedagogy

  • Teacher candidates are given mock student survey data reporting their personal and family technology use and asked to develop a plan to communicate effectively with students and their families
  • Teachers use data, historical or current, to help students understand the scale or relevance of a disciplinary topic
Through computing/tech

To support teacher learning

  • In preparation for a mock interview with a principal, teacher candidates analyze multiple publicly available DOE school data sources to develop a set of recommendations that will help the school improve its school quality scores

To support teacher pedagogy

  • In a methods course, teacher candidates incorporate data analysis in a lesson, curating the data set if necessary, choose the tool to be used, and develop any technical guides/aids
Against computing/tech

To support teacher learning

  • Teacher candidates develop an set of rules for student grade promotion that are based on data and discuss the constraints of using data analysis for this type of decision-making (potentially show disparate impacts with visualizations)

To support teacher pedagogy

  • Teacher candidates develop data visualizations of the same data that tell different stories – some representative, some not representative – and develop questions for learners to reflect on the potential harm associated with data visualizations.

Summer 2022 Professional Development Workshops Related to Analyzing & Visualizing Data

  • Tuesday, July 12, 10am-12pm, Accessibility for All: Teaching Accessibility via Games, Hosted by Devorah Kletenik
  • Wednesday, July 20, 10am-12pm, Artificial Intelligence and Student Data Literacy, Hosted by Julia Stoyanovich
  • Wednesday, July 20, 2pm-4pm, Split Breakout Workshops, Hosted by Michelle Wilkerson, David Stokes, and Cherise McBride & Kathryn Lanouette
  • Tuesday, July 26, 2pm-4pm, K12 Equitable CS: Practices, Implementation, and a Vision for the Future, Hosted by Shana White & Frieda McAlear
  • Wednesday, July 27, 2-4pm, Scientific Simulations and Agent-Based Models with StarLogo Nova, Hosted by Gabrielle Rabinowitz

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