Assignment
Keeping It Real: Teach ACRL Information Literacy Frames with FRED data
A hybrid teaching module with two elements: an interactive online module for students to complete ahead of class and a face-to-face lesson plan that builds on the skills learned in the online lesson. The in-class session provides students with a critical exploration of the purchasing power of minimum wages across states and/or the earnings gap between men and women employed full time.
The pre-class online course is titled: “FRED Interactive: Information Literacy” available through www.econlowdown.org. In the online course, students review a FRED graph made in the course; define the concepts nominal, real, and inflation; and discuss basic strategies for establishing the reliability of a data source.
The in-person class lesson is titled: ACRL Information Literacy Frames as FRED-Integrated Abilities: The frames Research as Inquiry, Information Creation as a Process, Scholarship as Conversation, and Authority Is Constructed and Contextual are highlighted. The instructor has two possible tasks for students;
-Option A, students work in FRED and use the formula real = (nominal/CPI)*100 to plot inflation-adjusted minimum wage rates for two states and compare the results.
-Option B, students work in FRED to plot and compare nominal and real earnings differentials for men and woman.
The lesson includes a variety of in-class and out-of-class assessment activities and links to resources and a glossary of terms provide additional learning opportunities.
Students will:
Create
❏ New FRED® graphs
Define
❏ Minimum wage
❏ Nominal and real wages
❏ Consumer price inflation (CPI)
Identify
❏ Metadata in a FRED graph
❏ Additional questions for further research
Describe
❏ The frequency of data collection
❏ The components of a data citation
❏ The difference between data sources and aggregators
❏ The reasons for knowing how data are collected
❏ The difference between nominal and real wages
❏ The issues of authority regarding trustworthiness, reliability, and credibility of data sources
Comments
Additional authors are Diego