LA Pathway D: Critical analysis of computational texts and practices(Overview)
< Back to Building BlockThese building blocks focus on ways to provide students with the language and frameworks to critically analyze computational texts and computational practices.
Many teachers may already use critical analysis frameworks to interpret and critique texts through an array of socio-cultural lenses (class, gender, race, sexuality, etc.). This integration pathway has educators focus on guiding students through critical questioning activities in order for students to understand and analyze their own relationship with computational culture and explicitly treat computational artifacts as texts in order to assess their author’s intent and impacts on their lives and society.
This building block highlights two practices to integrate computational thinking in the Language Arts (LA) classroom:
D1. Understand the relationship between communication culture and computational culture
D2. Assess an author's (e.g., creator, programmer) intent, motive, and impact of computational tools or platforms (“tools as texts”)
The next steps in this project will break down each of the two practices a bit further and provide brief examples of how each practice can look and feel in a classroom.
The second project in this building block will guide educators through a more in-depth Language Arts activity covering D2.
Reflection
As you complete this project, and others in this building block, consider the following questions for your own classroom instruction:
- What does it look like for students to engage in critical analysis of computational texts and practices in the classroom?
- Do these practices support critical-thinking skills and the ability to closely and attentively read computational texts? How?
D1 focuses on deepening understanding of how communication culture and computational culture interact. This practice encourages students to analyze how individuals engage with other people, share information, drive conversations, and encourage others to share their voices (communication culture) in relation to computational culture, that is the socio-cultural contexts in which people interact with and through technology, including when producing computational products and "texts."
Practice in Action
Students can spend a few days tracking the types of comments they see on specific content creators, influencers, and celebrities and how "comment culture" plays out on YouTube and TikTok. Students can then compare the comment culture of popular social media sites to the comment culture they see playing out in computational tools like Google Docs, Scratch, Google Classroom, etc. Independently or in small groups, students can identify patterns across all computational tools and platforms. After, students can create videos or written essays that answer questions such as:
- Are computational tools being used as intended? Why or why not? Where can you search to determine how a tool is "intended" to be used?
- Compare and contrast at least two computational tools or platforms by examining how these tools differ in their computational culture and the impacts these computational tools or platforms have on users' communication?
D2 focuses on using critical analysis to:
- Analyze computational tools or platforms as texts by posing questions.
- Analyze how authors’ (e.g., creator, programmer) intent and motive shape the design of computational tools or platforms.
- Analyze strengths and weaknesses of computational tools or platforms.
Practice in Action
A lesson progression could ask students to evaluate the selection algorithm used by popular streaming services to make recommendations by taking note of what types of media it recommends for them. Students can then compare and contrast the recommendations of each student in the class. A whole group of students can discuss bias, intent, and positionality (who wrote the code) of the computational platform (computational text) and come up with claims or questions. Students then search for publications, news articles or studies that dispute or confirm claims or answer questions. Finally, students can determine the potential positive and/or negative effects the streaming service's selection algorithm has on a user.