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Created byLinda Garrett

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The Algorithmic Critic: Coding Literary Lenses into Short Stories

Grade 11English3 days

In this innovative 11th-grade English project, students engineer "logic-bots" that use conditional "if/then" parameters to simulate specific critical lenses, such as feminism or Marxism. By treating short stories as data sets, students systematically identify recurring patterns and significant "silences" to expose hidden power structures and authorial biases. The project culminates in an Algorithmic Audit Report where students evaluate the tension between objective logical frameworks and the subjective interpretation of the human experience.

Critical TheoryAlgorithmic BiasComputational ThinkingLiterary AnalysisPower DynamicsPerspectiveTextual Evidence

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Inquiry Framework

Question Framework

Driving Question

The overarching question that guides the entire project.How can we engineer a "logic-bot" that uses specific critical lenses to expose the hidden patterns, biases, and "silences" that shift the meaning of a story?

Essential Questions

Supporting questions that break down major concepts.

How does the "lens" through which we read a story change who we perceive as the hero, the victim, or the villain?
If we define a set of logical 'if/then' rules for a specific ideology (like feminism or Marxism), what hidden patterns emerge in a text that a 'normal' reader might miss?
What specific 'data points' (recurring words, character interactions, or power dynamics) are required to program a logic-bot to recognize a specific critical theory?
To what extent is a text’s meaning controlled by the author versus the 'program' or perspective used by the reader?
How do the silences or omissions in a story become visible when we apply a rigid logical filter to the narrative?
Can an 'algorithmic' approach to literature actually lead to a more objective understanding of subjective human experiences?

Standards & Learning Goals

Learning Goals

By the end of this project, students will be able to:

Analyze complex literary texts through the application of specific critical theories (e.g., Marxism, Feminism, Post-colonialism) to identify hidden power structures and biases.
Develop a logical algorithm or 'logic-bot' that uses conditional 'if/then' parameters to simulate the perspective of a critical lens.
Identify 'silences' or omissions in a narrative by comparing the text's surface meaning with the findings of an algorithmic critical filter.
Synthesize textual evidence to support claims about how specific literary 'data points' (recurring motifs, character status, dialogue) influence reader perception.
Evaluate the effectiveness of using rigid logical frameworks versus subjective intuition when interpreting human experiences in literature.

Common Core State Standards (ELA)

CCSS.ELA-LITERACY.RL.11-12.1

Primary

Cite strong and thorough textual evidence to support analysis of what the text says explicitly as well as inferences drawn from the text, including determining where the text leaves matters uncertain.Reason: This project requires students to treat texts as data sets, citing specific patterns and 'data points' to fuel their logic-bots and support their critical interpretations.

CCSS.ELA-LITERACY.RL.11-12.6

Primary

Analyze a case in which grasping a point of view requires distinguishing what is directly stated in a text from what is really meant (e.g., satire, sarcasm, irony, or understatement).Reason: Critical theory is centered on finding hidden meanings and 'silences.' Students must distinguish between the surface narrative and the underlying ideological implications revealed by their lens.

CCSS.ELA-LITERACY.RL.11-12.3

Secondary

Analyze the impact of the author's choices regarding how to develop and relate elements of a story or drama (e.g., where a story is set, how the action is ordered, how the characters are introduced and developed).Reason: The logic-bots will specifically look for patterns in character development and plot structure to determine if the author's choices reinforce or challenge specific social hierarchies.

CCSS.ELA-LITERACY.W.11-12.2

Secondary

Write informative/explanatory texts to examine and convey complex ideas, concepts, and information clearly and accurately through the effective selection, organization, and analysis of content.Reason: Students will need to document the 'code' or logical rules of their bot and explain how those rules translate a critical theory into a functional analytical tool.

CSTA K-12 Computer Science Standards

CSTA 3A-AP-24

Supporting

Evaluate how the ability to provide precise information, insights, and data is affected by the design of an algorithm.Reason: While an ELA project, the 'logic-bot' concept introduces computational thinking by forcing students to consider how the 'design' of their critical filter (the algorithm) biases the 'data' (the story output).

Entry Events

Events that will be used to introduce the project to students

The Case of the Murdered Meaning

The classroom is transformed into a crime scene where the 'victim' is the traditional meaning of a well-known story. Students are 'Forensic Linguists' given a set of 'Evidence Bags' containing different 'Eyewitness Reports' (short critical snippets) that interpret the story in wildly different, contradictory ways (e.g., one sees a tragedy of poverty, another sees a triumph of the individual). Students must identify the 'hidden motive' (the underlying theory) behind each witness's perspective without using any academic jargon.

The 'Perspective Goggle' Live Stream

Students are given 'Perspective Goggles' (actual glasses or cardboard cutouts) labeled with bizarre, non-academic names like 'The CEO Lens,' 'The Outcast Lens,' or 'The Traditionalist Lens.' They are challenged to 'live-stream' a 60-second reaction to a short story while wearing their goggles, strictly adhering to that persona's priorities. This leads to a 'Goggle Swap' where they realize that changing the 'hardware' (the lens) fundamentally alters the 'data' (the story's meaning).

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Portfolio Activities

These activities progressively build towards your learning goals, with each submission contributing to the student's final portfolio.

Activity 1

Blueprinting the Logic-Bot: The Rules of Obsession

In this initial activity, students move from the 'Perspective Goggles' entry event to formalizing their lens into a 'Logic-Bot Blueprint.' Instead of learning the names of critical theories, they choose a 'System Obsession'—such as 'The Flow of Money,' 'Gender Roles,' or 'The Presence of the Past.' They must then translate this obsession into a set of 5-7 logical 'If/Then' rules that their bot will use to scan a text. For example: 'IF a character speaks without being spoken to, THEN award them 1 Power Point.' This forces students to define the parameters of a critical lens through logic rather than jargon.

Steps

Here is some basic scaffolding to help students complete the activity.

1. Select one 'System Obsession' from a provided list (e.g., Power Dynamics, Environmental Impact, Gender Equality) that will serve as the bot's primary filter.

2. Identify three literary 'Data Points' relevant to that obsession (e.g., who owns property, who performs domestic labor, who makes the final decision in a conflict).

3. Draft five 'If/Then' rules. These should be designed to catch specific patterns. Example: 'IF a character's physical appearance is described more than their actions, THEN flag this as an Objectification Event.'

4. Test your rules against a single paragraph of a familiar fairy tale to see if the rules generate a consistent 'reading' or result.

Final Product

What students will submit as the final product of the activityA 'Logic-Bot Blueprint' document that includes the bot's name, its primary 'Obsession,' and a list of at least five conditional rules (If/Then statements) that will govern its reading of any text.

Alignment

How this activity aligns with the learning objectives & standardsThis activity aligns with CCSS.ELA-LITERACY.RL.11-12.3 by requiring students to analyze how specific authorial choices (character status, setting, dialogue) are perceived through different filters. It also introduces CSTA 3A-AP-24 by asking students to design a primitive algorithm (a set of 'if/then' rules) that dictates how data (text) is processed.

Activity 2

The Data Harvester: Tagging the Silences

Armed with their blueprints, students are given a selection of three diverse short stories. They must act as the bot's 'Processor,' reading through one story and 'tagging' it according to their rules. Every time an 'If' condition is met, they must highlight the text and record the 'Then' result in the margins. Students are specifically looking for 'Data Voids'—moments where the story seems to ignore their bot's obsession entirely (e.g., a story about a factory that never mentions the workers' wages). This activity turns the reading process into a systematic search for evidence and ideological silences.

Steps

Here is some basic scaffolding to help students complete the activity.

1. Read the assigned short story once for general comprehension without applying the bot's rules.

2. Perform a 'Secondary Scan' where you highlight every instance in the text that triggers one of your Logic-Bot's 'If/Then' rules.

3. Label each highlight with the specific rule number it corresponds to and a brief note on the 'output' (e.g., 'Rule 2: Loss of Agency').

4. Identify at least two 'Data Voids'—major plot points or characters where your bot expected to find data but found nothing (the 'silences' of the text).

Final Product

What students will submit as the final product of the activityAn 'Annotated Data-Set' (the short story text) featuring color-coded highlights for every triggered rule and a 'Data Void Log' at the end of the text summarizing what the story 'refused' to show the bot.

Alignment

How this activity aligns with the learning objectives & standardsThis activity aligns with CCSS.ELA-LITERACY.RL.11-12.1, as students must cite thorough textual evidence to fuel their bot's logic. It also hits RL.11-12.6 by forcing students to look for 'silences'—the things the bot flags as missing or understated (what is 'really meant' vs. what is stated).

Activity 3

The Algorithmic Audit: Exposing the Bias

In the final stage, students synthesize their findings into an 'Algorithmic Audit Report.' They must explain how their bot's specific design 'biased' the reading of the story to reveal a hidden power structure or social pattern. Students will compare their bot's 'Output' with a 'Standard Reading' (the surface plot). This is where the teacher finally introduces the academic names for their bots (e.g., 'Your bot was performing a Marxist Critique'). Students then argue whether the 'Algorithmic' approach found a deeper truth or if it ignored the human element of the story too much.

Steps

Here is some basic scaffolding to help students complete the activity.

1. Review your 'Annotated Data-Set' and group the results into 2-3 major 'Patterns of Influence.'

2. Write a 'Findings' section that explains what the bot discovered about the story's hidden priorities (e.g., 'The bot revealed that the setting's beauty is actually a mask for economic decay').

3. Draft a 'Bias Reflection' explaining what the bot was 'blind' to because of its programming (e.g., 'My bot was so focused on gender that it missed the importance of the character's religious faith').

4. Compare your bot's findings with a peer who used a different bot on the same story, noting how the same 'data' produced two different meanings.

5. Finalize the report by mapping your bot's 'Obsession' to its official name in Critical Theory (provided by the teacher at this final stage).

Final Product

What students will submit as the final product of the activityAn 'Algorithmic Audit Report' that includes a summary of the 'Data-Set,' a defense of the bot's findings, a reflection on the 'Bias by Design,' and a final conclusion on how the 'lens' changed the story's meaning.

Alignment

How this activity aligns with the learning objectives & standardsThis activity aligns with CCSS.ELA-LITERACY.W.11-12.2, as students must write an explanatory text conveying complex analytical findings. It also addresses the 'Algorithm Bias' component of CSTA 3A-AP-24 by requiring students to reflect on how their bot's design intentionally limited the story's meaning to reveal a specific truth.

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Rubric & Reflection

Portfolio Rubric

Grading criteria for assessing the overall project portfolio

The Algorithmic Critic: Bias by Design Rubric

Category 1

Algorithmic Literacy & Evidence Extraction

Assesses the student's ability to develop and apply a logical framework to extract deep textual evidence.

Criterion 1

Algorithmic Blueprinting & Logic Design

The ability to translate a complex critical perspective (System Obsession) into a functional set of conditional 'If/Then' rules that can scan a text for specific data points.

Exemplary

4 Points

The Blueprint features highly sophisticated and consistent 'If/Then' rules that capture nuanced literary elements. The logic is so precise that it allows for a clear, repeatable, and innovative reading of the text, demonstrating a deep mastery of how to define a critical lens.

Proficient

3 Points

The Blueprint contains clear and logically sound 'If/Then' rules that align well with the chosen 'System Obsession.' The rules are functional and provide a thorough framework for analyzing the text beyond surface-level observations.

Developing

2 Points

The Blueprint shows an emerging understanding of how to use conditional logic, but rules may be inconsistent or overly simplistic. The connection between the 'If/Then' statements and the 'System Obsession' is present but requires more refinement to be effective.

Beginning

1 Points

The 'If/Then' rules are either missing, logically flawed, or unrelated to the 'System Obsession.' There is a struggle to move from a general idea to a specific logical parameter for text analysis.

Criterion 2

Data Harvesting & Evidence Precision

The precision and depth with which the student identifies and tags textual evidence according to their bot's rules, specifically focusing on 'Data Voids' or the silences in the narrative.

Exemplary

4 Points

Provides meticulous, color-coded evidence throughout the text that perfectly aligns with the 'Logic-Bot' rules. Analysis of 'Data Voids' is profound, identifying subtle omissions and 'silences' that reveal a sophisticated understanding of the text's ideological gaps.

Proficient

3 Points

Effectively tags the text with clear evidence that triggers the 'Logic-Bot' rules. The 'Data Void Log' identifies significant omissions and demonstrates a thorough understanding of what the text leaves unsaid or 'uncertain.'

Developing

2 Points

Identifies some textual evidence and silences, but the application of the 'Logic-Bot' rules is inconsistent. Some 'Data Voids' are noted, but they may be surface-level or lack a strong connection to the specific critical lens.

Beginning

1 Points

Evidence tagging is sparse or inaccurate, failing to demonstrate how the text triggers the bot's rules. There is a lack of recognition regarding 'Data Voids' or the importance of what is missing from the narrative.

Category 2

Critical Synthesis & Metacognition

Assesses the student's ability to communicate findings, connect to established theories, and reflect on the nature of analytical bias.

Criterion 1

Theoretical Synthesis & Interpretation

The capacity to synthesize 'bot' findings into a cohesive argument about the text's hidden power structures and shift in meaning when viewed through a specific lens.

Exemplary

4 Points

Synthesizes findings into a complex and compelling argument that reveals a deep shift in the story's meaning. Successfully maps the 'Obsession' to its official Critical Theory with a nuanced defense of how the lens uncovers hidden truths.

Proficient

3 Points

Provides a clear and well-organized explanation of the bot's findings. Accurately relates the 'Obsession' to its Critical Theory and explains how the lens changes the perception of characters or plot dynamics.

Developing

2 Points

Summarizes the bot's results but struggles to synthesize them into a larger argument about the text's meaning. The connection to the formal Critical Theory is attempted but may be shaky or superficial.

Beginning

1 Points

The final report is largely a summary of the plot or the bot's raw output without meaningful analysis of what the findings signify. Fails to connect the 'Logic-Bot' results to a broader critical framework.

Criterion 2

Metacognitive Reflection & Bias Awareness

Evaluation of how the 'design' of the bot (the algorithm) creates a specific bias, and a reflection on the tension between objective logic and subjective human experience.

Exemplary

4 Points

Offers a profound reflection on 'Bias by Design,' identifying exactly how the bot's programming forced a specific interpretation while intentionally ignoring others. Critically evaluates the tension between 'algorithmic' and 'human' reading with high-level metacognition.

Proficient

3 Points

Clearly identifies the limitations of the bot's programming and explains what the bot was 'blind' to. Effectively reflects on how a fixed perspective (the algorithm) influences the resulting data and interpretation.

Developing

2 Points

Shows emerging awareness of lens bias but may struggle to articulate exactly how the bot's rules limited the scope of the reading. Reflection on the 'algorithmic' approach vs. human intuition is basic.

Beginning

1 Points

Shows little to no awareness of how the bot's design created a biased reading. Reflection is missing or fails to address how the 'program' (the lens) fundamentally limited the meaning of the story.

Reflection Prompts

End-of-project reflection questions to get students to think about their learning

Question 1

How did applying rigid 'If/Then' rules change your relationship with the text compared to your usual way of reading? Did it make the story more or less 'real' to you?

Text

Required

Question 2

On a scale of 1 to 5, how much more 'objective' do you feel your analysis was when using the logic-bot compared to a standard class discussion?

Scale

Required

Question 3

Now that your 'System Obsession' has been linked to an official Critical Theory, which of the following best describes your discovery about literary 'meaning'?

Multiple choice

Required

Options

The author's intent is the only thing that matters, regardless of the lens.

The lens we choose acts as a filter that highlights some truths while hiding others.

A story has one 'true' meaning, and algorithms help us find it faster.

The 'silences' or gaps in a story are just mistakes made by the author.

Question 4

Describe a specific 'Data Void' (a silence) your bot encountered. What does the absence of that information tell you about the world the author created, or the limitations of the 'program' you designed?

Text

Required