algorithms

Teaching Resource

Home for the IMLS Grant RE-72-17-0103-17 - “RE:Search” - Unpacking the Algorithms That Shape Our UX.

Submitted by Shelby Hallman on June 9th, 2022
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Short Description: 

Algorithms are not neutral but this does not mean they are not useful tools for research. In this workshop on algorithmic bias, student learn how algorithms can perpetuate bias and discrimination and how to critically evaluate their search results.

Learning Outcomes: 

•Students will be introduced to the machine bias inherent in algorithmic decision making, with a focus on information systems.

•Students will discuss the effects of algorithm bias in order to articulate how some individuals or groups of individuals may be misrepresented or systematically marginalized in search engine results.

•Students will develop an attitude of informed skepticism in order to critically evaluate search results. 

Individual or Group:

Course Context (e.g. how it was implemented or integrated): 

Stand-alone workshop; co-curricular workshop. 

Assessment or Criteria for Success
Assessment Short Description: 
Formative assessment was conducted via the in-session activities. Summative assessment was conducted via an end of session survey form.
Suggested Citation: 
Hallman, Shelby. "Rise Against the Machines: Understanding Algorithmic Bias." CORA (Community of Online Research Assignments), 2022. https://projectcora.org/assignment/rise-against-machines-understanding-algorithmic-bias.
Submitted by Alexandria Chisholm on October 14th, 2021
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Short Description: 

This algorithmic literacy workshop puts a new spin on media literacy by moving beyond fake news to examine the algorithms that shape our online experiences and how we encounter information in our everyday lives.

Attachments: 
AttachmentSize
#ForYouWorkshopLessonPlan_Chisholm.pdfdisplayed 1768 times163.64 KB
AttentionAutonomyPlan_#ForYouWorkshop.pdfdisplayed 1156 times83.03 KB
Learning Outcomes: 

By the end of the #ForYou: Algorithms & the Attention Economy workshop, students will be able to:

  1. describe recommender system algorithms in order to examine how they shape individuals' online experiences through personalization
  2. analyze their online behaviors and subsequent ad profiles in order to reflect on how they influence how individuals encounter, perceive, & evaluate information, leading to echo chambers & political polarization
  3. assess how their data is used to personalize their online experience in order to build algorithmic awareness & make informed, intentional choices about their information consumption
Discipline: 
Multidisciplinary

Information Literacy concepts:

Individual or Group:

Suggested Citation: 
Chisholm, Alexandria. "#ForYou: Algorithms & the Attention Economy." CORA (Community of Online Research Assignments), 2021. https://projectcora.org/assignment/foryou-algorithms-attention-economy.