YouTube’s
ABCs and 123s:
Describing the quality ofearly literacy and mathvideos on YouTube
Claire Christensen & Madeline Cincebeaux,
SRI Education

Authors
Claire Christensen, Ph.D.
Madeline Cincebeaux, BS
SRI Education

Suggested Citation
Christensen, C., & Cincebeaux, M. (2024). YouTube’s ABCs and 123s: Describing the qualityof early literacy and math videos on YouTube. Menlo Park, CA: SRI International.

Acknowledgments
Thanks to the advisors who shaped our codebook for YouTube content: Todd Grindal,
Erika Gaylor, Sarah Gerard, Sara Rutherford-Quach, Phil Vahey, Carlin Llorente, and Jenny
Radesky. Thanks to the staff who annotated hundreds of hours of YouTube videos for thisproject: Mallory Scott, Heidi Norton, Estefania Rios, and Molly Morgan.

©2024 SRI International. SRI International is a registered trademark and SRI Education is a trademark of SRI
International. All other trademarks are the property of their respective owners.

YouTube’s ABCs and 123s: Describing the quality of early literacy and math videos on YouTube

Contents
There is little research on the educational quality of early learning
videos on YouTube

1

What makes an educational video high-quality?

2

Research questions

4

Methods

4

Annotation

8

Results and discussion

8

Conclusion

13

References

15

Video Image Sources

17

Appendix A: Video annotation

20

YouTube’s ABCs and 123s: Describing the quality of early literacy and math videos on YouTube

YouTube’s ABCs and 123s:
Describing the quality of early literacy
and math videos on YouTube
Claire Christensen & Madeline Cincebeaux, SRI Education

There is little research on the educational quality ofearly learning videos on YouTube
Online videos have potential to shape young children’s early learning and development, yet we know little
about the educational value of these videos’ content. Young children consume 2.5 hours (ages 2 to 4) to 3
hours (ages 5 to 8) of screen media a day on average (Rideout & Robb, 2020). Young children now spend
more time watching videos on sites like YouTube than on any other platform, including streaming services
and television shows (Rideout & Robb, 2020). The sheer volume of online video content makes it difficult
to categorize or describe young children’s online video exposure: On YouTube alone, around 500 hours ofcontent are uploaded each minute (YouTube, n.d.).

I don't like or trust YouTube. [The kids] don't get to watch the platform
unless I am in the room. It’s too big.

-Parent of a first-grade child

Many parents hope their children will learn something new or explore their interests when watching videos
on YouTube, but it can be hard for parents to judge the educational quality of the videos their child watches.
Ensuring that young children have access to high-quality educational videos is important, as researchshows that children can learn both math and literacy skills from high-quality educational videos (e.g., Hurwitz,
2019; Silander et al., 2016). Early research suggests the quality of online educational videos, on average,
may be poor. One study found that only 1 in 20 videos children watch online are of high educational value(Radesky et al., 2020).

I also want them to watch content with educational value, not justentertainment.

-Parent of a first-grade childYouTube’s ABCs and 123s: Describing the quality of early literacy and math videos on YouTube1

To advance our understanding of the likelihood that children will learn from the videos available to them
online, this paper focuses on educational videos for prekindergarten and kindergarten children on YouTube.
We describe the quality, duration, and popularity of a sample of YouTube videos focused on early literacy
and math topics, as defined by the Head Start Early Learning Outcomes Framework for prekindergarten
literacy and math (Office of Head Start, 2015), and the Common Core State Standards for kindergarten
literacy and math (National Governors Association Center for Best Practices & Council of Chief State
School Officers, 2010). We illustrate findings with quotes from interviews with parents of young children(in prekindergarten through first grade). This study is part of a broader initiative to detect the presenceand quality of educational content in online videos using machine learning (National Science Foundation
Award No. 2139219).1

What makes an educational video highquality?
Researchers have proposed several components of high-quality
educational media. For example, Fisch’s (2000) capacity model
identifies program characteristics theorized to support
comprehension of educational content. Fisch statesthat educational content should be, among otherthings, clear, explicit, and integral to the narrative.
According to the Four Pillars of Learning
framework (Hirsh-Pasek et al., 2015; Meyer etal., 2021), quality educational apps should supportsocial interaction with characters or caregivers andshould contextualize learning content within children’s
everyday experiences.
This paper focuses on five indicators of high-quality earlylearning videos. To identify these indicators, we reviewed theresearch literature, including existing rating systems for educational
videos (e.g., Jordan et al., 2001; Radesky et al., 2020), and solicitedrecommendations from an expert advisory board. We tested potential
quality indicators on a sample of videos to arrive at five indicators that are wellaligned with the types of educational content available on YouTube for young
children and that can be clearly operationalized (Exhibit 1).

1

This project developed a machine learning-based tool to identify early childhood math content in online videos for young children.

YouTube’s ABCs and 123s: Describing the quality of early literacy and math videos on YouTube

2

Exhibit 1. Indicators of educational quality in online videos to teach early literacy and matha

Quality indicatorand description

Example(s)that meet criteria

Example(s) that does
not meet criteria

Is primarily
educational: The video
focuses on teaching
preK or K math orliteracy content.

A video that focuses on
Elmo counting different
animals in a barn.

Directly addresses
the audience: The
video asks the viewer toengage in the learning
content, then pauses
for a response.

After eating some
Skittles, a teacher
looks at the camera
and asks, “How many
Skittles do I have left?”
and then pauses.

The host looks at thecamera and asks,“Are you excited?”

Involves characters:
The video includes
any onscreen, verbal
character who is involvedin the learning content.

Blippi plays with andtalks about objects thatstart with each letterof the alphabet.

A video withvoiceover only (noonscreen characters).

Includes concrete
examples: The video
illustrates learning
content with objects
or examples a childwould encounter intheir daily life.

Many early literacy
videos take the format of“A is for apple,” etc.

A video that describes
shapes (e.g., “A triangle
has three sides”)
without likening them
to familiar objects in achild’s environment.

Children can better
comprehend educational
content when it activatesprior knowledge(Fisch, 2000).

Integrates mathcontent into narrative.
Math content is integral
to solving the problem
within a video’s narrative.a

A video focuses onplanning a birthday
party. Characters use
counting to determine
how many treats to buy
for each guest.

A video that does
not include narrative(e.g., only includes an
educational song).

Children are better
able to comprehend
educational content
when it is integral to anarrative (Fisch, 2000).

An unboxing video inwhich a child counts
toy accessories.
A gaming video inwhich the host spells
the name of thecharacter he is creating
while typing it into thecharacter creator.

A geometry video might
liken a triangle to apiece of pizza.

One character asks
another, “What starts
with C?” and the othercharacter responds.

A video in which the
only onscreen character
introduces the video but
does not participate inlearning content (e.g.,“Hey kids, let’s sing a
song!” followed by aneducational song withno characters).

Supporting research
Fisch’s (2000)
capacity model statesthat educational
content should beclear and explicit.

Program familiarityand participatory cues
produced the greatest
educational content
comprehension in asample of preschoolage children(Piotrowski, 2014).
Meaningful relationships
with media characters
can help young
children learn earlymath and other logicalreasoning skills (Howard
Gola et al., 2013;
Lauricella et al., 2011).

We did not measure this indicator for literacy content because it was uncommon in a test sample of videos.

YouTube’s ABCs and 123s: Describing the quality of early literacy and math videos on YouTube

3

Research questions
1.

What percentage of educational videos in the sample demonstrate one or morecomponent of quality?

2. How prevalent are educational quality components (directly addressing the audience,
involving characters, including concrete examples, and integrating math content into
narrative) in early literacy and math videos in this sample?
3. To what extent is the presence of each educational quality component in avideo associated with number of views and number of likes?
4. To what extent is the breadth of educational quality components
and literacy or math topics in a video associated with numberof views and number of likes?

Methods
Searching and screening for videos
Our sample is a curated collection of videos that covera wide range of prekindergarten and kindergarten literacy
and math topics. It consists of videos that include at least one
early literacy or math topic. The sample is not intended to be an
exhaustive collection or representative sample of early literacy- or
math-focused YouTube content, but instead to provide one snapshot of
the types of videos available on YouTube.
To identify candidate videos for the sample, from February to April 2023, ourteam conducted YouTube searches using keywords associated with each early
literacy and math content category (e.g., “learning to rhyme,” “basic addition”). We
instructed trained research assistants to switch to a new keyword when the search
results no longer appeared relevant. Research assistants also reviewed videos that
YouTube recommended adjacent to the videos that were included in the sample. Video titles
and/or descriptions were usually indicative of the presence of early literacy or math content, but research
assistants were instructed to watch the first minute or so of each video to confirm the content was present
and intended for prekindergarten- or kindergarten-age children. We aimed to ensure that the sample
included a variety of representations of each literacy and math content code (Exhibit 2). If one channel had
several similar videos covering a narrow scope of content—for example, a channel that had 26 different
videos that described each letter of the alphabet—we asked research assistants to only screen andannotate the first few videos before moving on to a different channel or search topic.

YouTube’s ABCs and 123s: Describing the quality of early literacy and math videos on YouTube

4

Exhibit 2. Early literacy and math codes based on the Head Start Early Learning Outcomes
Early literacy and math content categories based on
Frameworkfor prekindergarten
and theand
CommonCoreEarly
StateStandards
for kindergarten
CommonCore State Standards
Head Start
Learning
Outcomes
Framework

Literacy

MathLetter names

Counting

Written numerals

Letters in words

Cardinality

Comparing 2 ormore groups

Letter sounds

Subitizing

Addition andsubtraction

Sounds in words

Measurable
attributes

Sorting

Sight words

Spatial language

Shape names

Following words
left to right

Shape analysis
and comparison

Building anddrawing shapes

Rhyming

Patterns

Note: Screenshots are from YouTube videos sharable under Creative Commons CC BY 3.0 license. See “Video Image Sources” for citations.

YouTube’s ABCs and 123s: Describing the quality of early literacy and math videos on YouTube

5

Each video in our final screened sample contained at least one early literacy or one early math topic.
We defined these literacy and math topics using a codebook based on the Head Start Early Learning
Outcomes framework for prekindergarten and the Common Core State Standards for kindergarten (seeExhibit 2; National Governors Association Center for Best Practices Council of Chief State School Officers,
2010; Office of Head Start, 2015). In addition, we excluded videos with any of the following characteristics:• Videos in a language other than English• Videos obviously not intended for prekindergarten- or kindergarten-age children• Videos longer than 15 minutes

YouTube’s ABCs and 123s: Describing the quality of early literacy and math videos on YouTube

6

Final video sample
The final video sample consisted of 1,198 videos: 648 videos with early literacy content (54% of the sample)
and 550 videos with early math content (46% of the sample).
The videos in this sample were uploaded to 670 unique YouTube channels.2 Exhibit 3 presents all channels
that produced more than 1% of either the early literacy or math videos in the sample. On average, eachchannel created 1.8 videos in this dataset, ranging from 1 to 75 videos. The channels that created more
videos in this dataset tended have more followers, r = .08, p < .05. This may indicate that the YouTube
algorithm pushed more content from popular channels.

Exhibit 3. Channels that produced more than 1% of the early literacy or math videos in this dataset
Videos in dataset

Percent of subsample(literacy or math)Jack Hartmann Kids Music Channel

75

11.6%

Alphablocks

17

2.6%

ChuChu TV Nursery Rhymes & Kids Songs

15

2.3%

Rock ’N Learn

13

2.0%

Super Simple ABCs

12

1.9%

Learning Time Fun

11

1.7%

Read Kids

11

1.7%

Scratch Garden

8

1.2%

HeidiSongs

7

1.1%

Kids Academy

7

1.1%

Little Learners

7

1.1%

Teach for Life

7

1.1%

The Sea Star’s Virtual Classroom!

7

1. 1%

Jack Hartmann Kids Music Channel

22

4%

Kids Academy

20

3.6%

JoAnn’s School

12

2.2%

MatholiaChannel

9

1.6%

Learning Time Fun

8

1.5%

Roving Genius

6

1.1%

Scratch Garden

6

1.1%

Smile and Learn – English

6

1.1%

ChannelLiteracy videos n (N=648)

Math videos (N=550)

2

A YouTube channel is the home page for a user’s YouTube account, which houses all videos created by that user.

YouTube’s ABCs and 123s: Describing the quality of early literacy and math videos on YouTube7

Annotation
We trained a team of three research assistants to use the codebook to assign content categories andquality indicators to each video—a process we refer to as annotation (see Appendix A for additional
details). Research assistants began annotating on their own (operational annotation) upon reaching atleast 80% agreement with an expert annotator on a training set of videos. Research assistants annotatedvideos from March 2022 to October 2023. Videos were annotated in batches, with annotation of eachbatch lasting about 4 weeks. To reduce draft during annotation, during each annotation round, research
assistants annotated one video per week in common and discussed discrepancies. Research assistants
annotated each video for the subject area in which it was screened; that is, videos were annotatedfor either early literacy content and quality indicators or early math content and quality
indicators, but not both.

Results and discussion
Nearly all videos in the final sample are
primarily educational and include
at least one other indicator of
educational quality
Nearly all (88%) of the videos in our final
sample appeared primarily educational inpurpose. This is likely a result of our screening
process, as the sample only includes videos
that both appeared in a search for an early literacy
or math keyword and did in fact include some early
literacy or math content.3 Videos in the sample that were
not primarily educational tended to be entertainmentfocused videos that included incidental literacy or mathcontent. Similarly, nearly all (84%) of the videos in the sample
both are primarily educational and include at least one other quality
indicator (directly addressing the audience, involving characters,
including concrete examples, or integrating math content into thenarrative). This result suggests that most of the educational videos in our
sample have at least some degree of educational quality.

3

An example of a video that might have appeared in our search but been screened out is a music video for adults associated with the searchterm “rhyming.”

YouTube’s ABCs and 123s: Describing the quality of early literacy and math videos on YouTube

8

Concrete examples are the most common quality component in early
literacy and math videos; integrating math into the narrative is least
commonThe channels in our sample used different strategies to teach educational content, as indicated by wide
variation in the prevalence of educational quality indicators (Exhibit 4). For example, 81% of early mathvideos used concrete examples, whereas only 7% of math videos included math content that was integral to
the narrative.

Exhibit 4. Prevalence of educational content quality indicators in videos that include early literacy
and math content

YouTube’s ABCs and 123s: Describing the quality of early literacy and math videos on YouTube

9

Unsurprisingly, most videos in our sample (72% of literacy videos and 81% of math videos sampled) included
concrete examples, or examples a child can relate to their own life. For example, most alphabet videos
include objects common to many children, such as apples and balls, and many math videos involve counting
familiar objects (Exhibit 5). The relative frequency of this quality indicator makes sense: An audiovisual
medium requires visuals, and familiar objects are an obvious choice.

Exhibit 5. An alphabet video that uses concrete examples (in this case, “f” for frog)

Note: Screenshots are from YouTube videos sharable under Creative Commons CC BY 3.0 license. See “Video Image Sources” for citations.

About half of math videos (51%) and two fifths of literacy videos (40%) directly address the audience inrelationship to the educational content. Many videos address the audience by asking the child either tosing along with a familiar song such as the alphabet, or to count along (Exhibit 6). Directly addressing theaudience may be more challenging in videos that present more complex or less familiar content, or in videos
with narratives that do not break the “fourth wall.”

Exhibit 6. A counting video that directly addresses the audience by asking them what sound “A”
makes

Note: Screenshots are from YouTube videos sharable under Creative Commons CC BY 3.0 license. See “Video Image Sources” for citations.

YouTube’s ABCs and 123s: Describing the quality of early literacy and math videos on YouTube

10

Slightly less than half of videos in this sample (46% of literacy videos and 43% of math videos sampled) include
the involving characters quality component. Examples of popular characters in educational YouTube videos forchildren include Blippi, Jack Hartmann, and the Alphablocks (Exhibit 7). That the majority of early literacy and mathvideos in this sample do not include relatable characters is surprising and may represent a significant departurefrom educational television programs, which typically include one or more characters. Songs are common
examples of educational YouTube videos that do not include characters. For example, an “A is for apple” type ofalphabet song might present letters and objects voiced by an off-screen narrator but include no visible characters.
These kinds of videos may be simpler to produce than videos with original characters, but research suggests they
may be less effective in supporting children’s learning (Howard Gola et al., 2013; Lauricella et al., 2011).

Exhibit 7. A video with characters who teach shapes

Note: Screenshots are from YouTube videos sharable under Creative Commons CC BY 3.0 license. See “Video Image Sources” for citations.

Few early math videos in our sample (7%) integrated math content into the narrative (Exhibit 8). This is
likely because few videos on YouTube have a clear narrative arc into which math could be integrated. For
example, song-based videos rarely include a narrative. This may be a key difference between online videos
and studio-produced educational television programs for children, in which the plot often centers aroundsolving a problem. For example, a prior study found that television programs that teach social-emotional
learning frequently use educational content to advance the plot (Christensen & Myford, 2014).

Exhibit 8. An educational video in which a character needs help with a secret mission to find themissing shapes

Note: Screenshots are from YouTube videos sharable under Creative Commons CC BY 3.0 license. See “Video Image Sources” for citations.

YouTube’s ABCs and 123s: Describing the quality of early literacy and math videos on YouTube

11

Sample videos that directly address the audience are less popular, as
measured by number of views and likes
We used metadata associated with the videos in our sample to explore the relative popularity of videos that
include each educational quality indicator, compared with videos that do not (Exhibit 9). Videos that directly
address the audience had fewer views and likes, on average, than videos that do not address the audience.
That these videos had fewer views may suggest that the YouTube algorithm recommends them lessfrequently. That these videos had fewer likes may suggest that viewers find them less engaging. Because
these videos break the fourth wall, they may be less narrative-centered and more didactic in structure, andthus children may find them less appealing.

Exhibit 9. Correlations between the presence of four quality indicators and duration, view count,and like count
Quality indicator

View countLike countIs primarily educational-.020-.056+

Includes concrete examples

.007

.021

Involves characters

-.015

.023

Directly addresses the audience-.074*-.093**

Integrates math content into the narrative

-.025

-.030

* p < .05. ** p < .01. + p < .10.

Sample videos that include more variety of math content tend tohave fewer views and likes
While the number of literacy and quality codes in a video was unrelated to number of likes and views in thissample, videos in our sample with more math codes had fewer views and likes, whereas videos with fewer
math codes had more views and likes (Exhibits 10 and 11). This finding may indicate both that the YouTube
algorithm is more likely to recommend “deep dives” into fewer topics and that parents are searching forspecific math topics for their children to watch. That more narrowly focused videos have more likes may
suggest that viewers are more likely to enjoy them. Perhaps videos focusing on a smaller number of mathtopics have more time to devote to other engaging elements, such as music or humor.

Exhibit 10. Correlations between variety of literacy, math, and quality codes and duration, viewcount, and like count
Variable

View countLike countCount of literacy codes

.018

-.035

Count of math codes-.093*-.096*Count of quality codes-.050+-.045* p < .05. + p < .10.

YouTube’s ABCs and 123s: Describing the quality of early literacy and math videos on YouTube

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Exhibit 11. An educational video that includes several math topics such as counting, written
numerals, and cardinality (left) and another video that only incorporates one math concept of
written numerals (right)

Note: Screenshots are from YouTube videos sharable under Creative Commons CC BY 3.0 license. See “Video Image Sources” for citations.

Conclusion
Although young children watch more videos online than on television (Rideout & Robb, 2020), little is known
about the characteristics and quality of online educational videos for young children. To sketch this landscape,this study describes a dataset of prekindergarten- and kindergarten-level literacy and math videos on YouTube.
In this section, we present key findings and implications for parents, content creators, and researchers.
Fewer than half of the videos in our sample include relatable characters, and only 7% use mathskills to further the narrative.
For parents: Whereas most educational television programs include narratives and characters,
fewer online educational videos do. There is more rigorous evidence for the learning benefits ofhigh-quality educational television programs than for educational online videos.
 or content creators: Educational content creators can distinguish themselves in this crowdedFfield by weaving educational content into narratives with relatable characters.
 or future research: To what extent do the inclusion of narratives and characters influenceFchildren’s learning from educational videos? While prior research has explored the role of familiar
versus unfamiliar characters (Howard Gola et al., 2013; Lauricella et al., 2011), less is known about
whether the presence versus the absence of narratives and characters influences learning.

YouTube’s ABCs and 123s: Describing the quality of early literacy and math videos on YouTube

13

Among the educational videos in our sample, those that directly address the audience had fewerviews and likes than those that do not.
For parents: Talk with children about what they learn from educational online videos. It can help
kids get more out of the videos they watch.
 or content creators: Content creators are experts in creating effective calls to action, such as
Fcalls to like and subscribe. There is an opportunity to use this expertise to create more engaging
calls for children to interact with educational content in videos.
 or future research: What is the effect of participatory cues (directly addressing the audience)Fin short-form videos on engagement, interaction, and comprehension? While some research
indicates that participatory cues support children’s learning from educational television programs(e.g., Piotrowski, 2014), these cues may function differently on YouTube, where children may have astronger expectation of passive entertainment and a greater temptation to skip to the next video.
Among our sample of early math videos, those with deeper, rather than broader, topic coverage
had more views and likes.
For parents: When searching for math videos for children on YouTube, use keywords specific toa skill your child is working on (e.g., counting) rather than their age or grade level (e.g., kindergartenmath), which may yield videos with a broader focus.
 or content creators: The algorithm may be more likely to recommend math videos focused onFfewer topics than videos focused on a wider range of topics.
 or future research: Are there other video characteristics that may explain why videosF
presenting fewer math topics get more views and likes? For example, do more narrowly focused
videos include other engaging elements?

Limitations and Next Steps
One key limitation of our dataset is its context: The dataset was pre-screened to include examples of early
literacy or math videos. Our findings may not generalize to videos typically watched by prekindergartenand kindergarten-age children. More research is needed to describe children’s actual content exposure
when using YouTube. We intend to use the machine learning algorithm we are developing with these data to
describe videos that children watch when browsing YouTube naturalistically.
Until very recently, young children watched most of their educational content in the form of television
programs created by major studios. As their screen time shifts online, they are increasingly exposed to usergenerated, rather than studio-created, educational videos. There is a great need to understand the content
and quality of these user-generated videos as a context for children’s early learning and development. Our
analyses highlight important ways that user-generated educational videos may differ from educational
television programs, including the breadth of creators producing this content and decreased reliance on
narratives and characters. In addition, our findings hint at novel influences on the content and quality of
online videos, such as the likelihood that the algorithm will recommend a video or that a viewer will like it.
More research is needed to guide the creation of effective educational content in this uncharted territory.
YouTube’s ABCs and 123s: Describing the quality of early literacy and math videos on YouTube

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Video Image Sources
Video images included in this report are taken from YouTube videos with Creative Commons licensing. They
are not drawn from our annotated sample of videos.

Exhibit 2, Literacy column (top to bottom)
ABC Sounds and Words (Learn Alphabet Letter Sounds and Words) [Video], by English Learning
Fun Station, 2021, November 22, YouTube (https://www.youtube.com/watch?v=EEXEg1_
OEF4). CC BY 3.0.
ABC Phonics – ABC Letter Sounds – Say It – Sound It – Alphabet Letters for Kids [Video],
by Funny Bunny Teacher, 2023, December 6, YouTube (https://www.youtube.com/
watch?v=gDNojkrNosE). CC BY 3.0.
How to Learn ABCD Beginning Letter Sound S Words Their comparison With M and R
Word [Video], by MOON KIDS tv, 2022, May 29, YouTube (https://www.youtube.com/
watch?v=UqIcqU2XTMM). CC BY 3.0.
Phonics Song for Children| Alphabet Song | Letter Sounds | Signing for Babies | Learn Uppercase | #27[Video], by Learn with Jokjizz, 2023, March 29, YouTube (https://www.youtube.com/watch?v=_
BdhScnwlng). CC BY 3.0.
Learn ONCE in This Short Video Kids || Only Sight Words [Video], by KIDS Channel With Titi Bird, 2021,
September 17, YouTube (https://www.youtube.com/watch?v=xgbyrSRbXVw). CC BY 3.0.
Read Along Storybook for Kids Ages 2–4 | Monster Love [Video], by Curious World, 2017, May 23, YouTube(https://www.youtube.com/watch?v=ZhvZ-KjQlWE). CC BY 3.0.
Rhyming Two Out of Three [Video], by Teach for Life, 2019, September 22, YouTube(https://www.youtube.com/watch?v=UFs2FKQIFgs). CC BY 3.0.

Exhibit 2, Math column (left to right, top to bottom)
Counting Song [Video], by DaileyKailey, 2021, April 19, YouTube (https://www.youtube.com/
watch?v=hPj908UW0iI). CC BY 3.0.
Counting to 10 – Thanksgiving [Video], by The Primary Techie, 2022, October 26, YouTube(https://www.youtube.com/watch?v=zQK7XDKv3W4). CC BY 3.0.
Counting on Fingers [Video], by Teach for Life, 2019, September 22, YouTube (https://www.youtube.com/
watch?v=8Qf4SfPLp-s). CC BY 3.0.
Counting Objects [Video], by Teach for Life, 2019, September 25, YouTube (https://www.youtube.com/
watch?v=MBPhqzWw0xY). CC BY 3.0.

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Flashcards Practice: Ten Frames 02 Numbers 0 to 7 [Video], by Professor Pete’s Classroom, 2015, March 7,
YouTube, (https://www.youtube.com/watch?v=zsCbkuz4zGk). CC BY 3.0.
Addition for Kids Kindergarten [Video], by Learning Channel for Kids, 2020, November 30, YouTube(https://www.youtube.com/watch?v=Yj0-NexNtZc). CC BY 3.0.
Compare Sizes for Kindergarten – Big and Small [Video], by Learning Channel for Kids, 2020, December 4,
YouTube (https://www.youtube.com/watch?v=HCKmOvYJTiI). CC BY 3.0.
Sorting by Shape [Video], by Teach for Life, 2019, September 22, YouTube (https://www.youtube.com/
watch?v=hjFlTU6AEYc). CC BY 3.0.
Position Words [Video], by Teach for Life, 2019, September 22, YouTube (https://www.youtube.com/
watch?v=rrnHWXHGVkw). CC BY 3.0.
2D Shapes [Video], by The Primary Techie, 2022, July 13, YouTube (https://www.youtube.com/
watch?v=sYxDzQ6URzw). CC BY 3.0.
Learn Shapes in the Jungle | Pinkfong Shape Songs | 15-Minute Learning With Baby Shark [Video], byPinkfong Baby Shark – Kids’ Songs & Stories, 2023, November 25, YouTube(https://www.youtube.com/watch?v=EmUsz5GVWok). CC BY 3.0.
Learning Videos for Toddlers Shapes // FUN #Episode 3 [Video], by Learnkids, 2019, February 18, YouTube(https://www.youtube.com/watch?v=patjOtWL3mE). CC BY 3.0.
Patterns Using Natural Materials [YouTube], by Teach for Life, 2019, September 22, YouTube(https://www.youtube.com/watch?v=3YcNc3uLZoo). CC BY 3.0.

Exhibit 5
ABC Sounds and Words (Learn Alphabet Letter Sounds and Words) [Video], by English Learning
Fun Station, 2021, November 22, YouTube (https://www.youtube.com/watch?v=EEXEg1_
OEF4). CC BY 3.0.

Exhibit 6
Learn Shapes in the Jungle | Pinkfong Shape Songs | 15-Minute Learning With Baby Shark [Video], byPinkfong Baby Shark – Kids’ Songs & Stories, 2023, November 25, YouTube(https://www.youtube.com/watch?v=EmUsz5GVWok). CC BY 3.0.

Exhibit 7
Learning Videos for Toddlers Shapes // FUN #Episode 3 [Video], by Learnkids, 2019, February 18, YouTube(https://www.youtube.com/watch?v=patjOtWL3mE). CC BY 3.0.

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Exhibit 8
Secret Agent Shapes (Song for Kids About Finding Basic Shapes in the Room) [Video],
by Harry Kindergarten Music, 2015, June 26, YouTube (https://www.youtube.com/
watch?v=7aStqhksCuY). CC BY 3.0.

Exhibit 11 (left to right)
Let’s Count With Dinosaurs | Dinosaur Cartoon | Pinkfong Dinosaurs for Kids [Video], byPinkfong Dinosaurs for Kids, 2023, December 30, YouTube (https://www.youtube.com/
watch?v=IaqyUCwRDo0). CC BY 3.0.
Shapes Song | Kids Learning Video | Baby Rhymes & Songs for Children [Video], by Zoobees Kids ABC
TV – Baby Songs & Nursery Rhymes, 2019, October 3, YouTube (https://www.youtube.com/
watch?v=SS4ntXD10r8). CC BY 3.0.

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Appendix A: Video annotation
Training the annotation team
We trained our staff on a process we refer to as annotation—using the codebook to assign early literacy
and math content categories and quality indicators to videos. Three research assistants with previous
experience in early education but no formal background in education research or early childhood media
research were trained to annotate videos. The team was trained and led by an experienced education
researcher who helped develop the codebook. We trained the research assistants on the kindergarten
codebook first and the prekindergarten codebook second. During each training, the three research
assistants reviewed the prekindergarten or kindergarten content categories and quality indicators
and watched exemplar videos. They were asked to independently annotate a set of 20 videos forprekindergarten and a set of 20 videos for kindergarten. The annotation team lead reviewed the annotations
and provided feedback, and the research assistants revised accordingly. The research assistants began
annotating on their own (operational annotation) once they reached at least 80% agreement with the lead.
To reduce draft during annotation, during each annotation round, research assistants annotated one video
per week in common and discussed discrepancies.

Applying the codebook
Research assistants used an online scoresheet to record each video’s early literacy or math content. As
they watched each video, they checked off any content categories and quality indicators that occurred atleast once. The scoresheet then asked follow-up questions about the selected content categories, suchas whether the video included related audio and/or visual information. We used this information to verify
that the selected content categories met the criteria in the codebook. We used some follow-up items toautomatically categorize videos as including either prekindergarten or kindergarten literacy or math content.
For example, the counting content category is relevant to both prekindergarten and kindergarten standards.
The prekindergarten standards focus on counting 0–20 whereas the kindergarten standards focus oncounting 0–100. If counting was selected as a content code, a follow-up item on the scoresheet asked
research assistants to indicate the lowest number in the count sequence so that videos with numbers
above 20 will not be identified as containing prekindergarten content. After selecting content categories,
research assistants indicated whether any quality indicators were present at least once in the video.

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