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Tiffany Wu

@tiffanyxwu.bsky.social
855 followers 528 following 16 posts

Edpsych PhD & Stats dual master's @UMich | IES Predoc Fellow | #rstats enthusiast | Former teacher | @NorthwesternU & @UChicago alumna | 🇹🇼🇺🇸 Website: tiffany-wu.github.io

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Reposted by Tiffany Wu
Yiqing Xu @yiqingxu.bsky.social · 24/05/2026
On panelView, and why we should always look at our data first.. yiqingxu.substack.com/p/plot-your-...
yiqingxu.substack.com
Please look at your (panel) data
Many of the most egregious issues can be avoided by simply looking at the data.
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Ambassador Frank Hull @frankiethull.bsky.social · 04/03/2026
i love data, me too meme
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University of Michigan Gerald R. Ford School of Public Policy @fordschool.bsky.social · 07/02/2026
@tiffanyxwu.bsky.social, an EPI postdoctoral fellow, was recently featured in an Education Week article on academic absenteeism. Read the full story: myumi.ch/9pMwX
myumi.ch
Should schools lower the chronic absenteeism threshold? New EPI research suggests they should
New evidence from the Ford School's Education Policy Initiative (EPI) shows absenteeism may hurt student's academics long before it is considered a chronic pattern. These findings, published in a Janu...
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Anton Strezhnev @astrezh.bsky.social · 22/01/2026
The Spring 2026 course website for my grad causal inference class is up and running. Was inspired by @andrew.heiss.phd and @mattblackwell.bsky.social to move my materials over to a standalone site and use as little of Canvas as possible. www.antonstrezhnev.com/ps813/
antonstrezhnev.com
PoliSci 813
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Betsy Wolf @betsyjwolf.bsky.social · 22/01/2026
Curious about what people said in response to the RFI about "re-imagining" the Institute of Education Sciences (IES)? I put the public comments in one file (763 pages) and used AI to analyze the themes and areas of agreement and disagreement (5 pages) by audience ⬇️: docs.google.com/document/d/1...
docs.google.com
Loading Google Docs
Web word processing, presentations and spreadsheets
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Richard McElreath 🐈‍⬛ @rmcelreath.bsky.social · 09/12/2025
I'm teaching Statistical Rethinking again starting Jan 2026. This time with live lectures, divided into Beginner and Experienced sections. Will be a lot more work for me, but I hope much better for students. I will record lectures & all will be found at this link: github.com/rmcelreath/s...
course schedule as a table. Available at the link in the post.
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Julia M. Rohrer @dingdingpeng.the100.ci · 18/12/2025
Just gave my last talk of the year! 2025 was quite packed, I gave talks about: - the age-period-cohort problem - making rigorous causal inference more mainstream - mediation analysis - marginaleffects - causal graphs (x10) If you're curious, check out my slides here: juliarohrer.com/resources/
juliarohrer.com
Resources
Here you can find a collection of things that may be helpful, including slide decks, a curated list of introductory papers and blog posts, as well as some infographics I have generated to explain v…
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Posit @posit.co · 11/12/2025
New data from @sara-altman.bsky.social & @simonpcouch.com, using the vitals and ellmer packages, looks at LLM performance metrics for #RStats. 👀 Sneak peek: Claude Opus 4.5, Claude Sonnet 4.5, & OpenAI GPT-5 lead in generating correct R code. Read the full breakdown: posit.co/blog/r-llm-e...
posit.co
Which LLM writes the best R code? - Posit
The vitals package delivers a dedicated framework for measuring how well Large Language Models perform with code.
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Paul Bruno @paul-bruno.com · 22/09/2025
The Relationship Between Student Attendance and Achievement, Pre- and Post-COVID journals.sagepub.com/doi/abs/10.1...
journals.sagepub.com
Sage Journals: Discover world-class research
Subscription and open access journals from Sage, the world's leading independent academic publisher.
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Aaron Sojourner @aaronsojourner.org · 12/03/2025
We invest 9X less per child-year in care & education in the first 5 years of life than the next 13. This gap in public investment is why K12 is free for parents & early care & education is expensive. www.hamiltonproject.org/publication/...
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Shaun M. Dougherty @doughesm.bsky.social · 29/08/2025
🚨Interested in a PhD focusing on quant methods and education & social policy? I'm recruiting this year at @bclynchschool in the Measurement, Evaluation, Statistics, and Assessment program www.bc.edu/bc-web/schoo...
bc.edu
Doctor of Philosophy (Ph.D.) in Measurement, Evaluation, Statistics, and Assessment - Lynch School of Education and Human Development - Boston College
MESA has been training students to examine educational programs, design quantitative research studies, develop assessment instruments, and analyze educational data to help inform policy-making for ove...
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Annenberg Institute @annenberginstitute.bsky.social · 25/08/2025
📢 #EdWorkingPapers: How can we measure student behavior at scale? @tiffanyxwu.bsky.social, @weilanch.bsky.social, @mattadiemer.bsky.social, Rebecca Unterman, @annakshapiro.bsky.social, & Thomas Staines use PCA and factor analysis to build behavior composites from admin data. 📄 bit.ly/4ofre5b
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Joshua Goodman @joshua-goodman.com · 25/06/2025
🔥What’s the only thing hotter than this week’s weather?🔥 Our new @wheelockpolicybu.bsky.social working paper: “School Enrollment Shifts Five Years After the Pandemic” In it, BU Wheelock PhD @abbyfrancis.bsky.social and I ask: Has the pandemic permanently changed families' schooling choices?
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Paul Bruno @paul-bruno.com · 16/06/2025
If we're heading into summer that means academic job market season is looming. As a reminder, my collected tips are here (along with my standing offer to set up time to chat with folks): www.paul-bruno.com/2021/07/tips...
paul-bruno.com
Some Basic Tips About the Academic Job Market – Paul Bruno
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Joshua Goodman @joshua-goodman.com · 11/06/2025
Re-upping my advice about how to write a good title and abstract for an academic paper, appropriately called: "How to Write a Title and Abstract" Feel free to share this thread, which will focus on titles. #EconSky #AcademicSky
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Tiffany Wu @tiffanyxwu.bsky.social · 28/05/2025
🤔 What kind of Pre-K experience sets students up for long-term success? Our new working paper offers important new evidence to help answer this question! 🔗 edworkingpapers.com/sites/default/files/ai25-1194.pdf And 🧵👇
A screenshot of the abstract of the working paperFigure 1: School Enrollment Pathways for Lottery Winners and Control Group Students through 8th Grade. This figure represents school enrollment pathways across different school types (BPS, BPS Exam School, non-BPS district school, charter school, and other) for both lottery winners and the control group. The thickness of the lines represents the percentage of lottery winners/control group students that are enrolled in each type of school. Blue lines show the pathways taken by lottery winners, and BPS-specific school categories are highlighted in the light blue boxes. BPS = Boston Public Schools.
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Annenberg Institute @annenberginstitute.bsky.social · 27/05/2025
🚀 Launching the EdWorkingPapers Policy & Practice Series! Too much good research never reaches the people making real decisions. Our new series changes that. Each 2-pager highlights key findings from #EdWorkingPapers, made for busy leaders and policymakers. 📄 Read the first three: bit.ly/3Z1Kok2
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Christina Weiland @weilanch.bsky.social · 22/05/2025
Using data from Michigan, we find that third grade retention for struggling readers may be a much less important component of the benefits of literacy reforms than previously understood. (Thx, @annenberginstitute.bsky.social, for the dissemination bump!)
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John Holbein @johnholbein1.bsky.social · 12/05/2025
Wow! Each $1 spent on Universal Pre-Kindergarten generates between $3-$20 dollars in aggregate earnings. That's enough to offset the costs of Universal Pre-Kindergarten through higher tax revenues.
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Andrew Heiss @andrew.heiss.phd · 18/04/2025
Thing I just learned in #rstats: unz() lets you connect to a .zip and load files from inside it without actually unzipping it (great for a file I'm working with that's 30 MB zipped and 1+ GB unzipped, with multiple CSVs in it)
# unz() lets you connect to a .zip and treat it like a mini file system, 
# and you can load files from inside it
one_zipped_csv_among_others <- readr::read_csv(
  unz("lotsa_zipped_csvs.zip"), "one_csv.csv"
)

# readr::read_csv() can read a .zip with a single CSV in it
one_zipped_csv <- readr::read_csv("big_zipped_file.zip")
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chloe gibbs @chloergibbs.bsky.social · 18/04/2025
I hope it is not lost, in all of the chaos at the federal level, that there are many longstanding, discretionary programs that are on the Administration's chopping block, either directly or through the erosion of agency staff, expertise, and capacity. Programs enacted and reauthorized through...
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Vincent Arel-Bundock @vincentab.bsky.social · 10/04/2025
📚😅🎉 Yay!! I just submitted the complete manuscript of my upcoming book to the publisher! Learn to easily and clearly interpret (almost) any stats model w/ R or Python. Simple ideas, consistent workflow, powerful tools, detailed case studies. Read it for free @ marginaleffects.com #RStats #PyData
Model to Meaning: How to interpret statistical models with marginaleffects for R and Python
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Andrew Heiss @andrew.heiss.phd · 20/03/2025
I’ve long used FiveThirtyEight’s interactive “Hack Your Way To Scientific Glory” to illustrate the idea of p-hacking when I teach statistics. But ABC/Disney killed the site earlier this month :( So I made my own with #rstats and Observable and #QuartoPub ! stats.andrewheiss.com/hack-your-way/
Screenshot of the linked Quarto website, with input checkboxes to change different conditions for a regression model that predicts economic performance based on US political party, with a reported p-value
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Prof Dynarski @dynarski.bsky.social · 15/03/2025
If you have research dependent on these data here is my suggestion 1/N Big picture: Create a dataset of cell means (cells must be big enough to pass disclosure) - load these cell means into many, many tables & put through review -These cell means can then be used in OLS - which runs on means
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Cara Jackson @carajackson.bsky.social · 12/03/2025
Objective, comprehensive, rigorous, timely, and useful: A digital hub for evidence-based education policy research. #EdResearch #EdPolicy livehandbook.org
livehandbook.org
Evidence-Based Education Policy Research | Live Handbook
Explore evidence-based education policy research at our digital hub. Access data-driven insights to improve learning outcomes and shape effective policies.
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Andrew Heiss @andrew.heiss.phd · 12/03/2025
New preprint! A general overview of stats in public policy research with this (oversimplified but still helpful) separation of methods into description, explanation, and prediction #policysky HTML/PDF: stats.andrewheiss.com/snoopy-spring/ SocArXiv: doi.org/10.31235/osf...
This essay provides an overview of statistical methods in public policy, focused primarily on the United States. I trace the historical development of quantitative approaches in policy research, from early ad hoc applications through the 19th and early 20th centuries, to the full institutionalization of statistical analysis in federal, state, local, and nonprofit agencies by the late 20th century. I then outline three core methodological approaches to policy-centered statistical research across social science disciplines: description, explanation, and prediction, framing each in terms of the focus of the analysis. In descriptive work, researchers explore what exists and examine any variable of interest to understand their different distributions and relationships. In explanatory work, researchers ask why does it exist and how can it be influenced. The focus of the analysis is on explanatory variables (X) to either (1) accurately estimate their relationship with an outcome variable (Y), or (2) causally attribute the effect of specific explanatory variables on outcomes. In predictive work, researchers as what will happen next and focus on the outcome variable (Y) and on generating accurate forecasts, classifications, and predictions from new data. For each approach, I examine key techniques, their applications in policy contexts, and important methodological considerations. I then consider critical perspectives on quantitative policy analysis framed around issues related to a three-part “data imperative” where governments are driven to count, gather, and learn from data. Each of these imperatives entail substantial issues related to privacy, accountability, democratic participation, and epistemic inequalities—issues at odds with public sector values of transparency and openness. I conclude by identifying some emerging trends in public sector-focused data science, inclusive ethical guidelines, open research practices, and future directions for the field.	Description	Explanation	Prediction
General question	What exists?	Why does it exist? How can it be influenced?	What will happen next?
Focus of analysis	Focus is on any variable—understanding different variables and their distributions and relationships	Focus is on X —understanding the relationship between X and Y, often with an emphasis on causality	Focus is on Y —forecasting or estimating the value of Y based on X, often without concern for causal mechanisms
Names for variable of interest	—		Explanatory variable
	Independent variable
	Predictor variable
	Covariate		Outcome variable
	Dependent variable
	Response variable
Goal of analysis	Summarize and explore data to identify patterns, trends, and relationships	Estimation: Test hypotheses or theories and make inferences about the relationship between one or more X variables and Y
 
Causal attribution: A special form of estimating—make inferences about the causal relationship between a single X of interest and Y through credible causal assumptions and identification strategies	Generate accurate predictions; maximize the amount of explainable variation in Y while minimizing prediction error
Evaluation criteria	—	Confidence/credible intervals, coefficient significance, effect sizes, and theoretical consistency	Metrics like root mean square error (RMSE) and R^2; out-of-sample performance
Typical approaches	Univariate summary statistics like the mean, median, variance, and standard deviation; multivariate summary statistics like correlations and cross-tabulations	t-tests, proportion tests, multivariate regression models; for causal attribution, careful identification through experiments, quasi-experiments, and other methods with observational data	Multivariate regression models; more complex black-box approaches like machine learning and ensemble modelsTable of contents
Introduction
Brief history of statistics in public policy
Core methodological approaches
Description
Explanation
Prediction
The pitfalls of counting, gathering, and learning from public data
Future directions
References
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Beth Schueler @bethschueler.bsky.social · 05/03/2025
It's that time of year to circulate this list of orgs for those seeking ed policy jobs/internships. Please let me know if there are opportunities/orgs I should add. Good luck out there! docs.google.com/spreadsheets...
docs.google.com
The Unofficial List of Ed Policy Orgs for Job/Internship Seekers
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Nick Huntington-Klein @nickchk.com · 25/02/2025
After a long wait, the working paper for the Many-Economists Project: The Sources of Researcher Variation in Economics. We had 146 teams perform the same research three times, each time with less freedom. What source of freedom leads to different choices and results? papers.ssrn.com/sol3/papers....
papers.ssrn.com
The Sources of Researcher Variation in Economics
We use a rigorous three-stage many-analysts design to assess how different researcher decisions—specifically data cleaning, research design, and the interpretat
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Rachel M. Perera @rachelmarisa.bsky.social · 11/02/2025
this from a representative at American Institutes for Research about DOGE/Trump cancelling IES contracts is spot on (& good on them for speaking out clearly about this)
“This is an incredible waste of taxpayer dollars, which have been invested—per Congressional appropriations and many according to specific legislation—in long-standing data collection and analysis efforts, and policy and program evaluations,” Tofig said. “These investments inform the entire education system at all levels about the condition of education and the distribution of students, teachers, and resources in school districts across America. Many of these contracts are nearing completion and canceling them now yields the taxpayers no return on their investment. If the purpose of such cuts is to make sure taxpayer dollars are not wasted and used well, the evaluation and data work that has been terminated is exactly the work that determines which programs are effective uses of federal dollars, and which are not.”
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Erica Greenberg @ericahgreenberg.bsky.social · 10/02/2025
🌟 Did you know that most federal education data are archived in the @urbaninstitute.bsky.social Education Data Explorer? It's a great resource for research and analysis - and there's even a full API version linked in thread. 🌟 #EduSky #EdPoliSky #EduSkyECEC educationdata.urban.org/data-explorer
educationdata.urban.org
Education Data Explorer
Explore education data
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Lucy D’Agostino McGowan @lucystats.bsky.social · 31/01/2025
a bit more #Severance data please enjoy all analyses equally 👉 lucymcgowan.github.io/mdr-website/ and for my #rstats friends: 👉 lucymcgowan.github.io/mdr/
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Tiffany Wu @tiffanyxwu.bsky.social · 23/01/2025
"Data is carved out of the world, by someone, for some purpose, with some limits."
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Jin X. Goh | 吴晋勋 @jinxungoh.bsky.social · 18/01/2025
If you/ your students are interviewing for PhD psych programs in US (especially social psych), check out the resource page on my website. There are guides prepped by grad students + questions to ask faculty etc. Good luck! www.pbandjlab.com/resources
pbandjlab.com
The PB&J Lab - Resources
Resources
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Simon P. Couch @simonpcouch.com · 16/01/2025
Meet gander, a chat interface for R data scientists🪿 gander automatically incorporates context from your #rstats environment and surrounding code and can be used with any model supported by ellmer in either RStudio or Positron. Read more: simonpcouch.github.io/gander/
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Betsy Wolf @betsyjwolf.bsky.social · 15/01/2025
New paper 'mapping' the settings, students, and outcomes in the What Works Clearinghouse evidence base. 🧵https://www.tandfonline.com/doi/full/10.1080/19345747.2024.2427762
tandfonline.com
What Works for Whom: Exploring the Students, Settings, and Outcomes in What Works Clearinghouse Study Data
The What Works Clearinghouse (WWC) at the Institute of Education Sciences reviews rigorous research on educational practices, policies, programs, and products with a goal of identifying “what works...
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Center for Political Studies @umisrcps.bsky.social · 10/01/2025
@tiffanyxwu.bsky.social, a former public high school teacher in the South Side of Chicago, is using the Sarri Family Fellowship to advance research for educational equity. Learn more about this work and fellowship now open for applications: buff.ly/4247VTt
Tiffany Wu of the University of Michigan Center for Political Studies: I examine how modern machine learning algorithms can be used for the vital task of proactively identifying students who are at risk of becoming chronically absenteeism, thereby facilitating timely interventions and supports, and improving these students' chances of succeeding in school.
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Jeremy Singer @jeremylsinger.bsky.social · 10/01/2025
Indeed! We found Detroit’s citywide asthma rate was > other major cities, which helps explain its high absenteeism rate; and asthma rates are strongly correlated with other citywide measures of inequality like poverty, segregation, and population loss over time. journals.sagepub.com/doi/abs/10.1...
journals.sagepub.com
Advancing an Ecological Approach to Chronic Absenteeism: Evidence from Detroit - Jeremy Singer, Ben Pogodzinski, Sarah Winchell Lenhoff, Walter Cook, 2021
Background/Context Chronic absenteeism has received increased attention from educational leaders and policy makers, in part because of the association between a...
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Christina Weiland @weilanch.bsky.social · 09/01/2025
High-quality curricula can move the needle on early learning, but implementation varies widely. We’re excited to start 2025 off with a new effort to systematically measure implementation readiness & target supports at baseline: fordschool.umich.edu/news/2025/u-...
fordschool.umich.edu
U-M’s Education Policy Initiative launches project to boost early learning success with new curriculum readiness measure
To improve early learning programs nationwide, policymakers and funders are investing in curriculum, professional development, and assessments. However, ensuring educational partners are well-prepared...
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Urban Institute @urbaninstitute.bsky.social · 09/01/2025
Can artificial intelligence (AI) reliably identify K–12 students at risk of dropping out? Learn more about Nevada’s experience and what role AI could play in education processes in a new Urban Wire piece.
urban.org
Can AI Reliably Identify K–12 Students At Risk of Dropping Out? Other States Can Learn from Nevada’s Experience.
Nevada recently used artificial intelligence to identify students at risk of dropping out of high school, but the model undercounted by more than 200,000 students, compared with what the state was use...
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Andrew Heiss @andrew.heiss.phd · 08/01/2025
The course websites for my Spring 2025 causal inference and data visualization classes (both with #rstats) are live! evalsp25.classes.andrewheiss.com datavizsp25.classes.andrewheiss.com
evalsp25.classes.andrewheiss.com
Program Evaluation for Public Service – Program Evaluation
Combine research design, causal inference, and econometric tools to measure the effects of social programs
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Mine Çetinkaya-Rundel @minecr.bsky.social · 27/12/2024
If your New Year's resolution is to learn #datascience w/ #rstats + #tidyverse + #quarto, check out www.coursera.org/specializati... -- covering data transformation, visualization, importing + data science ethics. Two additional courses (on modeling + inference) to be added in 2025.
coursera.org
Data Science with R
Offered by Duke University. Master Data Science with R. Transform, visualize, and analyze data responsibly Enroll for free.
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Lisa Fazio @lkfazio.bsky.social · 23/12/2024
Reminder that this wonderful tool exists to quickly list all the dates your class will meet in the spring. Such a life-saver 🛟 wcaleb.rice.edu/syllabusmake...
wcaleb.rice.edu
Generic Syllabus Maker
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Stephanie Wang @sweiwang.bsky.social · 12/12/2024
It's always Datapalooza at @casbsstanford.bsky.social 1. @annowens.bsky.social has assembled "school segregation data for every state, county, metro area, commuting zone, geo school district, and local educational agency in the US since 1991." edopportunity.org/segregation/... #econsky
edopportunity.org
The Segregation Explorer
Use our interactive map to explore dimensions of segregation in America
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Steve Haroz @steveharoz.com · 09/12/2024
The lesson here, which is important for students, is that science is never wrapped up in a nice clean bow. We never "have the answer". We are always working towards more accurate and more complete explanations.
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Michael Friendly @datavisfriendly.bsky.social · 06/12/2024
📊 #dataviz A couple of years old, but still worth reading-- The Science of Visual Data Communication: What Works A very thorough review of ideas and evidence by @SteveFranconeri, @LacePadill and others. journals.sagepub.com/doi/epub/10....
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Tiffany Wu @tiffanyxwu.bsky.social · 04/12/2024
Striving to be the type of person Bluesky thinks I am 🦋 For a dose of AI fun today, check out blueskyroast.com by @fekri.io ✨ Your ego will thank you (or not).
A profile summary of Tiffany Wu labeled 'Data Diva Extraordinaire,' showcasing AI-generated attributes. The description reads: 'A blend of educational zeal and data wizardry, Tiffany brings the academic party to Bluesky!' A highlighted quote says: 'The perfect mix of intellectual rigor and social humor, like a well-poured cup of artisanal coffee.'
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Andrew Ujifusa @andrewujifusa.bsky.social · 04/12/2024
"The extent of the decline seems to be driven by the lowest performing students losing more ground, a worrying trend that predates the pandemic." www.chalkbeat.org/2024/12/04/t...
chalkbeat.org
Some countries show improvements in math post-pandemic. Not the United States.
U.S. math scores dropped sharply in 2023 on a major international assessment, even as fourth graders posted higher scores in more than a dozen countries.
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