KQED61%

UCLA Just Launched a Massive AAPI Textbook for the TikTok Generation. And It's Free 16%

By Josie Huang0% LAist0%

5/24/2026, 11:00:02 AM

BS Summary: This article contains 21 faulty reasoning types, including In-Group Bias, Framing Effect, and Appeal to Authority, with Hasty Generalization as the most egregious example at 11.5% saturation with 80 hits. Analysis detected 623 faulty-reasoning hits from 697 analyzed words, generating a BS Score of 32.1% and a BS Rank of 16% (18,405 of 21,887 articles). This article is better (less manipulative) than 84.10% of the article peer group.

This story was originally published by LAist. 
A rich trove of Asian American and Pacific Islander history lives in academic journals and university library stacks that many students don’t know how to tap into. 
A new multimedia textbook developed out of UCLA’s Asian American Studies Center is trying to change that. 
Called Foundations and Futures, the online platform combines written chapters, archival documents and artwork with videos and podcast clips, geared at students in high school and up, along with their teachers. 
“It’s the largest collection of Asian American and Pacific Islander histories in one location  free and open access for anyone with an Internet connection,” said Karen Umemoto, director of the UCLA center and one of the project’s co-editors. 
The textbook officially launched this month  Asian American and Pacific Islander Heritage Month  after some six years of development with contributions from more than 100 authors and curriculum developers from across the country. 
Designed with the TikTok generation in mind, the platform is optimized for phones and tablets for easy scrolling. 
“A lot of young people, of course, are really into TikTok videos and Instagram posts,” Umemoto said. 
“So we thought, ‘Let’s leverage that.’” 
Responding to invisibility 
The project was seeded in 2020 when Umemoto and co-editor and fellow UCLA professor Kelly Fong began drafting proposals chapter by chapter. 
At the time, California was moving toward implementing an ethnic studies graduation requirement. 
The professors worried AAPI histories could still be sidelined without dedicated resources. 
Then came the COVID-19 pandemic and a surge in anti-Asian hate incidents. 
“There’s so many people who have no idea who we are, where we come from, how we got here,” Umemoto said. 
The textbook grew into a $12 million project, supported through a mix of state funding, grants and private donations. 
A major boost came in 2022, when the California Asian Pacific Islander Legislative Caucus helped secure a $10 million state allocation. 
Much of the textbook does focus on AAPI history in California, like the Filipino farmworker movement and Vietnamese refugee communities in Orange County. 
But other modules cover Chinese immigrant garment workers in New York and Asian American communities in the South. 
Getting into schools 
Umemoto said the textbook is for anyone to use as needed, but a major goal is helping educators incorporate AAPI perspectives into existing courses. 
“We’re so woefully invisible and underrepresented in educational curricula,” she said, noting that there are few teachers to instruct from lived experience. 
Just 2% of public school teachers in the U.S. are AAPI. 
The plan is to offer everything from two-day in-person teacher workshops to national webinars in partnership with teachers unions. 
Even with the project’s launch, organizers say their work continues with raising funds for teacher training, as well as outreach and operations. 
The team is seeking another $5 million for the next three years. 
“I’m a professor not trained in doing startups or ed tech projects, and so I didn’t realize how much it would take just to keep the lights on,” Umemoto said. 
All the while, the team is building the textbook to 50 chapters. 
It’s currently at 42. 
Learning amid polarization 
The project arrives amid charged political debates over how race and identity are taught in schools. 
Umemoto acknowledged that some critics view ethnic studies as divisive, but she said the goal of the textbook is the opposite. 
“We need to learn about each other’s history so that we can build an inclusive society,” she said. 
For Umemoto, the work is deeply personal. 
She said she grew up knowing her parents and grandparents had been forced into camps during World War II, but did not fully understand the broader history behind the incarceration of Japanese Americans until later in life. 
“I grew up thinking everybody was in camp,” she said. 
Ultimately, she hopes the textbook helps students better understand both themselves and one another. 
“In all my years of teaching, there has not been a student who has left the classroom unchanged,” Umemoto said. 
“If we want to deal with the problems of polarization, we need to start in the classroom.” 
Article reasoning-pattern comparisonThis article: 0.0%Josie Huang: 1.9%CalMatters: 1.9%Confirmation Bias0.0%This article: 4.3%Josie Huang: 2.2%CalMatters: 0.9%Anchoring Bias4.3%This article: 3.9%Josie Huang: 3.1%CalMatters: 3.0%Availability Heuristic3.9%This article: 2.6%Josie Huang: 1.3%CalMatters: 1.0%Representativeness Heuristic2.6%This article: 5.3%Josie Huang: 1.3%CalMatters: 0.5%Hindsight Bias5.3%This article: 2.9%Josie Huang: 3.6%CalMatters: 1.2%Overconfidence Bias2.9%This article: 10.0%Josie Huang: 5.8%CalMatters: 6.3%Framing Effect10.0%This article: 0.0%Josie Huang: 0.1%CalMatters: 1.0%Loss Aversion0.0%This article: 0.0%Josie Huang: 0.0%CalMatters: 0.7%Status Quo Bias0.0%This article: 3.2%Josie Huang: 1.6%CalMatters: 0.2%Sunk Cost Effect3.2%This article: 2.6%Josie Huang: 3.7%CalMatters: 3.5%Optimism Bias2.6%This article: 1.7%Josie Huang: 0.9%CalMatters: 1.4%Pessimism Bias1.7%This article: 0.0%Josie Huang: 2.2%CalMatters: 6.4%Negativity Bias0.0%This article: 4.3%Josie Huang: 2.2%CalMatters: 1.7%Self-Serving Bias4.3%This article: 0.0%Josie Huang: 0.0%CalMatters: 0.7%Fundamental Attribution Error0.0%This article: 0.0%Josie Huang: 0.0%CalMatters: 0.2%Actor-Observer Bias0.0%This article: 11.2%Josie Huang: 3.6%CalMatters: 1.7%In-Group Bias11.2%This article: 0.0%Josie Huang: 0.0%CalMatters: 0.4%Out-Group Homogeneity Bias0.0%This article: 1.0%Josie Huang: 1.6%CalMatters: 2.7%Halo Effect1.0%This article: 0.0%Josie Huang: 0.0%CalMatters: 0.1%Horn Effect0.0%This article: 0.0%Josie Huang: 0.0%CalMatters: 0.0%Dunning-Kruger Effect0.0%This article: 1.7%Josie Huang: 0.4%CalMatters: 0.9%Recency Bias1.7%This article: 0.0%Josie Huang: 1.3%CalMatters: 0.3%Primacy Effect0.0%This article: 0.0%Josie Huang: 0.0%CalMatters: 0.0%Blind-Spot Bias0.0%This article: 0.0%Josie Huang: 0.0%CalMatters: 0.6%Ad Hominem0.0%This article: 3.0%Josie Huang: 0.8%CalMatters: 0.2%Straw Man3.0%This article: 5.6%Josie Huang: 7.6%CalMatters: 3.1%Appeal to Authority5.6%This article: 2.4%Josie Huang: 2.0%CalMatters: 1.1%False Dilemma2.4%This article: 0.0%Josie Huang: 0.0%CalMatters: 0.8%Slippery Slope0.0%This article: 0.0%Josie Huang: 0.0%CalMatters: 0.1%Circular Reasoning0.0%This article: 11.5%Josie Huang: 7.8%CalMatters: 3.6%Hasty Generalization11.5%This article: 0.0%Josie Huang: 0.0%CalMatters: 0.2%Red Herring0.0%This article: 0.0%Josie Huang: 0.8%CalMatters: 0.7%Bandwagon0.0%This article: 3.2%Josie Huang: 3.0%CalMatters: 5.3%Appeal to Emotion3.2%This article: 2.6%Josie Huang: 1.9%CalMatters: 0.6%Begging the Question2.6%This article: 0.0%Josie Huang: 0.9%CalMatters: 2.0%Post Hoc (False Cause)0.0%This article: 0.0%Josie Huang: 0.0%CalMatters: 0.1%Tu Quoque0.0%This article: 0.0%Josie Huang: 0.4%CalMatters: 0.3%Burden of Proof0.0%This article: 0.0%Josie Huang: 0.0%CalMatters: 0.2%Appeal to Nature0.0%This article: 0.0%Josie Huang: 0.8%CalMatters: 0.2%Composition/Division0.0%This article: 1.4%Josie Huang: 4.5%CalMatters: 3.1%Anecdotal1.4%This article: 0.0%Josie Huang: 0.0%CalMatters: 0.0%No True Scotsman0.0%This article: 0.0%Josie Huang: 1.4%CalMatters: 1.2%Ambiguity (Equivocation)0.0%This article: 0.0%Josie Huang: 0.0%CalMatters: 0.0%Gambler’s Fallacy0.0%This article: 0.0%Josie Huang: 0.0%CalMatters: 0.1%Middle Ground0.0%This article: 0.0%Josie Huang: 0.0%CalMatters: 0.1%Personal Incredulity0.0%This article: 0.0%Josie Huang: 0.0%CalMatters: 0.1%Special Pleading0.0%This article: 0.0%Josie Huang: 0.0%CalMatters: 0.1%Genetic Fallacy0.0%This article: 0.0%Josie Huang: 1.4%CalMatters: 0.8%Unattributed Quote0.0%This article: 0.0%Josie Huang: 0.0%CalMatters: 0.7%Quote-first Misdirection0.0%This article: 0.0%Josie Huang: 3.9%CalMatters: 3.1%Biased Writer Voice0.0%This article: 5.0%Josie Huang: 5.2%CalMatters: 1.9%Indoctrination5.0%This article: 0.0%Josie Huang: 0.8%CalMatters: 1.1%Politically Left Leaning Bias0.0%This article: 0.0%Josie Huang: 0.0%CalMatters: 0.1%Politically Right Leaning Bias0.0%This article: 0.0%Josie Huang: 9.3%CalMatters: 1.2%Attempt to Sell a Product or S…0.0%

697 words analyzed.

Speakers

1speaker29%attributed speech497writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 11 words • 0.0% coverageWriter's voice • 3 words • 0.0% coverageWriter's voice • 7 words • 0.0% coverageWriter's voice • 27 words • 0.0% coverageWriter's voice • 17 words • 0.0% coverageWriter's voice • 31 words • 0.0% coverageKaren Umemoto • 39 words • 0.0% coverageWriter's voice • 35 words • 0.0% coverageWriter's voice • 18 words • 0.0% coverageKaren Umemoto • 17 words • 0.0% coverageKaren Umemoto • 6 words • 0.0% coverageWriter's voice • 3 words • 0.0% coverageWriter's voice • 22 words • 0.0% coverageWriter's voice • 13 words • 0.0% coverageWriter's voice • 12 words • 0.0% coverageWriter's voice • 12 words • 0.0% coverageKaren Umemoto • 21 words • 0.0% coverageWriter's voice • 19 words • 0.0% coverageWriter's voice • 21 words • 0.0% coverageWriter's voice • 23 words • 0.0% coverageWriter's voice • 18 words • 0.0% coverageWriter's voice • 3 words • 0.0% coverageWriter's voice • 24 words • 0.0% coverageKaren Umemoto • 22 words • 0.0% coverageWriter's voice • 11 words • 0.0% coverageWriter's voice • 19 words • 0.0% coverageWriter's voice • 22 words • 0.0% coverageWriter's voice • 12 words • 0.0% coverageKaren Umemoto • 30 words • 0.0% coverageWriter's voice • 12 words • 0.0% coverageWriter's voice • 4 words • 0.0% coverageWriter's voice • 3 words • 0.0% coverageWriter's voice • 16 words • 0.0% coverageWriter's voice • 21 words • 0.0% coverageKaren Umemoto • 18 words • 100.0% coverageWriter's voice • 7 words • 0.0% coverageWriter's voice • 37 words • 0.0% coverageKaren Umemoto • 10 words • 0.0% coverageWriter's voice • 14 words • 0.0% coverageKaren Umemoto • 20 words • 0.0% coverageKaren Umemoto • 17 words • 100.0% coverage
Selected voice

Karen Umemoto

97%flagged-word coverage
200 attributed words100% of attributed speech51% writer coverage
0%10.0%20.0%Indoctrination+17.5 ptsWriter: 0.0%Karen Umemoto: 17.5%17.5%

Attribution is sentence-level. Pattern percentages are calculated only from words assigned to that voice.

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Analysis

Hover over highlighted words in the article to view the associated bias or fallacy analysis.