Lab Sassion : Digital Humanities
Lab Sassion : Digital Humanities
Poem Written by a human or a computer?
n this activity, gives one written by a human poet and one generated by AI (computer). Our task was to carefully read both poems and decide which one belonged to a human and which to AI.
Learning Outcomes:
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Close Reading Skills – I learned to pay attention to tone, imagery, emotions, and style to identify the difference between human and AI writing.
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Signs of Human Writing – Human poems often had:
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Deeper emotions and originality
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Personal voice or lived experience
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Use of complex metaphors and cultural references
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Signs of AI Writing – AI poems often showed:
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Smooth rhythm and structure but less emotional depth
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Repetition of common words or generic ideas
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Sometimes lacked surprise, ambiguity, or subtle meaning
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Critical Thinking – The activity trained me to think critically, not just read passively. I had to analyze hidden meanings, creativity, and context to judge authorship.
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Awareness of AI in Literature – I realized that AI can create poems that look like human writing, but human creativity still carries something unique and personal.
Learning Outcomes from Voyant Activity on Frankenstein
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Cirrus (Word Cloud):
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I learned how to identify the most frequent words (like life, death, creature, Victor, nature) which helped me to understand the central themes of the novel.
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DreamScape:
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I learned to see how words are connected with places, characters, and ideas, which deepened my understanding of relationships and themes in the story.
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Knots (Network Graph):
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I learned to analyze connections between words (e.g., Victor–Creature, Life–Death), which showed me the conflicts and emotional tensions in the novel.
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TermsBerry:
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I learned how to study word pairings and collocations (e.g., Monster + horror, Victor + ambition), which revealed the tone and recurring ideas of the text.
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Mandala:
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I learned to visualize central words with surrounding contexts, which showed the positive and negative associations (e.g., Monster linked with fear/misery, Life linked with creation/science).
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StreamGraph:
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I learned how to track changes of word frequency over time, which helped me to see the development of themes (e.g., Creature in the middle, death and misery at the end).
Cirrus (Word Cloud):
-
I learned how to identify the most frequent words (like life, death, creature, Victor, nature) which helped me to understand the central themes of the novel.
DreamScape:
-
I learned to see how words are connected with places, characters, and ideas, which deepened my understanding of relationships and themes in the story.
Knots (Network Graph):
-
I learned to analyze connections between words (e.g., Victor–Creature, Life–Death), which showed me the conflicts and emotional tensions in the novel.
TermsBerry:
-
I learned how to study word pairings and collocations (e.g., Monster + horror, Victor + ambition), which revealed the tone and recurring ideas of the text.
Mandala:
-
I learned to visualize central words with surrounding contexts, which showed the positive and negative associations (e.g., Monster linked with fear/misery, Life linked with creation/science).
StreamGraph:
-
I learned how to track changes of word frequency over time, which helped me to see the development of themes (e.g., Creature in the middle, death and misery at the end).
Overall Learning Outcome:
By using these Voyant tools, I learned how digital humanities methods can uncover patterns, relationships, and thematic shifts in Frankenstein. This activity improved my analytical skills, helped me combine close and distant reading, and gave me a deeper understanding of the novel’s focus on creation, destruction, ambition, and human suffering.
Click Activity :
once upon time :
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