Computational Thinking in Humans and Machines
By: Steve Azeka and Teon Brooks
Unit 1: Language
Established Goals
Understandings
- Test
Essential Questions:
- How do you perceive fake news and propaganda?
- How do you know if the article is a conspiracy theory?
Students will know:
- Source of the content
- Style of the writing
- Number of words
- Sentence structure
- Data science
- Machine learning AI
Students will be able to do:
- Identify key attributes of real and fake articles
Performance Tasks
Goals
- To identify fake news articles and social media posts
Role
- Data scientists working for CIELabs
Audience
- Reads of news
Situation
- They’re hired by CIELabs to scan through different articles to find if they’re real or not.
- (Election...)
- Crowd source political articles
Product
- Classifier (Identifies articles as being real or fake) - Will be a trusted new source
Standards for Success
Other Evidence
Introduction: What’s the problem? Why should we care?
Introduction to Data Science in Journalism: Show video of people in the field doing the work
- TODO: Reach out to Xavier about real-time scenario about fake news on the web. https://www.instagram.com/p/CD_1rAbAnQN/?igshid=17riidpompq6v
- TODO: Reach out to Lam about participating in a brief video series on the impact of misinfo in journalism
- Context: https://t.co/cHrbsYrShR?amp=1
- Charge: Video end with charge to students to help them solve the problem. Frame the problem Outline structure for the unit
List of things to look for in science articles:
- Get list
Lesson 1: Where did this problem come from? Lesson: Historical context of fake news
- Technology’s role in promoting fake news
Activity: Explore examples requiring them to look at multiple articles that are not and are (varying levels- different sources - Social media) - CT approach? - Decompose the article, abstract the articles,... (look for guides) - Patterns
- Google Doc: Create a list of differences and highlight what we should be looking for
- Articles: https://sports.theonion.com/scientists-study-brains-of-baseball-fans-to-find-out-ho-1845081906
Find - credible source - Science (Secondary sources) -
https://guides.lib.berkeley.edu/fake-news
Lesson 2: Analytics skill required
Based on the prior information you collected how can we use analytics to tell if articles are good or not
- Give list of things we look for
- (examples should be shown in TidyBlocks)
Activity: Have students undergo another analysis using a particular analytical technique by using a calculator. The students should come to a realization that this is a lot of work and there should be a better way (leading to Tidyblocks)
(Note: Need to do something with graphing.)
Lesson 3: Introduction of skill
What are some tools that we can use? Add the steps required for using tidyblocks
- Analysis
- Tie to the steps we have for what the students will learn
Activity: Remixing an existing TidyBlocks setup to see how changing the different variables or blocks can influence the outcomes.
- There must be some deficits in the model (or else why wouldn’t they just use this one moving forward)
Lesson 4: Creating your own TidyBlocks
Define the problem and parameters of the problem for students
Activity: Students will create their own model to analyze articles
Pre/Post Survey - What are we measuring