Pow! Zap! Wham! Creating Comic Books from Picture Books in Social Studies Classrooms
Bibliographic record
Abstract
Students' documented lack of interest in social studies has led to many attempts by teachers to make school learning more relevant to the lives of their learners. This article demonstrates two ways to deal with that apathy: First, the use of picture books is encouraged and second, a popular culture format, the comic book, is advocated as a method for students to use to illustrate their learning. We provide suggestions on how to help students create their own comic books to demonstrate their learning of social studies content gained in part through study of picture books. Specific instructions are given about how to create comic books and a student example of a comic book showing his understanding of Inuit culture is featured. Having a sense of been there, seen that, I can never resist a smile when I read popular Canadian story-teller Robert Munsch's book Thomas ' Snowsuit (1985). I've seen some dreadfully ugly snowsuits during my time in Canada, but it didn't take me long to recognize that, at least in my life, warmth takes precedence over fashion. Despite my mirth, I find I cannot help but wonder if there really is much to laugh about when enduring those long, cold Canadian winters. There have been times when I've opted for something akin to three warm snowsuits, three warm parkas, six warm mittens, six warm socks and one pair of very warm boot sort of things called mukluks! (Munsch 1986). It is a special kind of person who can face those frozen Arctic breezes with a smile on the face. Life in Canada's North Country presents all types of difficult challenges--especially when one considers the additional threat of the mythical Qallupilluit wanting to drag little children through cracks in the ice (Munsch Kusugak 1988)! One cannot help but be filled with admiration for the Inuit people who for so long have endured Canada's seemingly endless winters, struggling against the elements while retelling legends that help to explain their surroundings.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".