Data-Driven Education Insights

Bad data = bad decisions. The decision of the U.S. Department of Education to cancel #IPEDS trainings isn't just a budget cut—it’s a #data #quality #crisis in the making. I’ve spent the past decade as an IPEDS Educator with National Center for Education Statistics (NCES) and Association for Institutional Research (AIR)—leading workshops, creating tutorials, and supporting literally thousands of new and veteran institutional researchers. My goal has always been to help ensure accurate reporting and meaningful use of higher education data. That mission is now at serious risk. The Department has chosen not to renew AIR’s contract to provide free, expanded training on IPEDS. You may think, why should we care? Here’s why this matters: 💡 IPEDS isn’t just another bureaucratic form—it underpins nearly every dataset about enrollment, financial aid, completion, and student outcomes. 💡 Over 6,000 institutions rely on it to make decisions that support student success. 💡 Funding for institutions is based in large part on it. 💡 Search engines for students to help them find the college that best fits their needs is based on it. 💡 Higher education policy is based on it. 💡 Accreditors make determinations based on it. Institutional Research isn’t a field people typically enter on purpose. There’s no straight path. Most IR professionals are promoted from within, trained on the job, and handed massive reporting responsibilities with little preparation. That’s why these workshops matter. That’s why they’ve existed. IPEDS training has been the foundation for quality, consistency, and confidence in data collection and use. When training disappears, data quality drops. Episodes of inconsistency, misreporting, and misinterpretation aren’t theoretical—they’re inevitable, affecting policy decisions, public trust, and student impact. Let’s start asking tough questions: ❓ Who will train the next generation of data professionals? ❓ If we lose these supports now, we won’t just miss a workshop—we’ll miss an entire culture of data accountability? ❓ Who is going to ensure consistency and accuracy across institutions? ❓ Who is going to build a common language around enrollment, outcomes, and equity? ❓ Who is going to help data professionals turn compliance into insight? Now, with the Department of Education discontinuing this support, we’re risking a decline in data quality, a growing burden on institutions, and the erosion of one of the most important public datasets in higher education. The loss won’t just affect campuses. It affects policymakers. Researchers. Journalists. And ultimately, students. Because when we get education data wrong, we get education policy wrong. https://lnkd.in/eriVUF6R

“Beta dhokha dega, data nahi.” Sounds reassuring, right? But in education especially Online courses, this belief can quietly mislead us. Yes, data analytics in education helps us track logins, completion rates, drop-offs, quiz scores. It tells us what happened. But from a Behavioural Science lens, data rarely tells us WHY it happened. 📉 A learner drops out of a MOOC. Data says: Low engagement after Week 3. Behavioural reality may be: 👉 Cognitive overload 👉Loss of identity (“people like me don’t finish MOOCs”) 👉Present bias (“I’ll do it later”) 👉Lack of social accountability None of this shows up cleanly on a dashboard. When we become obsessed with metrics, we risk: Designing for completion rates, not learning Nudging clicks instead of shaping habits ❌ Treating learners as datapoints, not humans with context, emotion, and constraints In #MOOCs, more data ≠ better decisions Unless it’s paired with: 🧠 behavioural diagnostics 🧪 experimentation (A/B tests with theory) 💬 qualitative insight So maybe the wiser mantra is: “Beta bhi dhokha de sakta hai, data bhi .....agar behaviour ko samjhe bina dekha.” Data is a tool. #Behaviour is the truth behind it.

Children spend just 190 days of the year in school. That leaves 175 days where learning is shaped elsewhere. Yet our education policy debates often treat schools as though they operate in isolation. Attainment gaps, literacy development, attendance, behaviour and aspiration are not solely the product of what happens between 9am and 3pm. Positive outcomes are influenced by: • home stability • access to books • youth provision • community safety • parental confidence • cultural capital • enrichment opportunities If we are serious about raising standards and narrowing gaps, policy cannot stop at the school gates. With such little time being spent in school we need to be innovative about how, when and where we educate our young people. Funding decisions around youth hubs, libraries, early years support, family services and community provision are not peripheral to education policy, they are central to it. We cannot demand that schools compensate for structural disadvantage in 190 days a year while reducing the infrastructure that supports children in the other 175 days. Education reform must move beyond classroom reform. Outcomes are shaped by ecosystems, not institutions alone.

Monday’s termination of scores of Department of Education contracts includes virtually all contracts that the National Center for Education Statistics relies on for its data collection and numerous products, according to various news outlets. Without NCES products, families, communities, and decisionmakers throughout the country will be left in the dark on many aspects of our education system. NCES’s reports on the status of student learning on state-by-state and international basis are widely used by parents, administrators, and policymakers to make decisions on school programs based on what’s working and isn’t working. Students and parents use NCES resources to monitor school safety and help locate public and private schools and colleges that meet their needs. Policymakers in the private and public sector use NCES products to develop programs, allocate resources, and track the latest trends in education. States, localities, and institutions around the United States use the data to compare themselves with others on tuition, salaries, staffing, expenditures, student achievement, graduation rates, and many other measures. Businesses use NCES data to inform their recruitment and siting for new facilities. Federal, state, and local governments as well as businesses and corporations used the data to determine the supply of labor with specific skills and training. Researchers use data to study progressions from early childhood through postsecondary education and into early careers to help answer questions such as whether students’ high school academic achievement is related to college enrollment and completion. I call on the administration and Congress to immediately rectify the situation so that NCES can continue being an invaluable resource to families, communities, and policymakers who need objective and timely information to inform their decisions in the best interests of America’s students and the country’s future.

🚀 Can teaching students “how to learn” actually change how they engage with their coursework? In this study published in the British Journal of Educational Technology, we used over 257,000 online learning “clicks” from biology students to track how their study habits evolved. Researchers moved beyond simply counting clicks—they mapped patterns of engagement, like how regularly students moved between different resources (quizzes, notes, calendars). Key findings: Students who received a short “science of learning to learn” training showed more organized, regular study patterns—and kept them up all semester. This regularity (think: consistent, purposeful learning routines) was a strong predictor of final grades—above and beyond just how much students clicked. Complexity-based network analysis offers powerful, AI-ready ways to monitor and support student self-regulated learning in real time. 💡 The big idea: Success isn’t just about what you study—it’s about building adaptive, organized habits you can sustain. https://lnkd.in/er9mmBfa

You ran the data meeting on Friday. Everyone nodded. Nothing changed on Monday. Here's what really happened. Data was collected. The team discussed the data. But nobody decided 𝙝𝙤𝙬 𝙩𝙤 𝙩𝙚𝙖𝙘𝙝 𝙙𝙞𝙛𝙛𝙚𝙧𝙚𝙣𝙩𝙡𝙮. Here's the problem: we've confused 𝘤𝘰𝘭𝘭𝘦𝘤𝘵𝘪𝘯𝘨 data with 𝘶𝘴𝘪𝘯𝘨 it. Data without a clear instructional response isn't a system. It's a filing cabinet. So what does acting on data actually look like? After your next assessment, before your data meeting, ask your team one question: "𝗕𝗮𝘀𝗲𝗱 𝗼𝗻 𝘁𝗵𝗶𝘀 𝗱𝗮𝘁𝗮, 𝘄𝗵𝗮𝘁 𝗮𝗿𝗲 𝘄𝗲 𝗳𝗼𝗰𝘂𝘀𝗶𝗻𝗴 𝗼𝗻 𝗮𝗻𝗱 𝗵𝗼𝘄 𝗮𝗿𝗲 𝘄𝗲 𝘁𝗲𝗮𝗰𝗵𝗶𝗻𝗴 𝗶𝘁 𝗱𝗶𝗳𝗳𝗲𝗿𝗲𝗻𝘁𝗹𝘆 𝗻𝗲𝘅𝘁 𝘁𝗶𝗺𝗲?" Not re-teaching the same lesson. Not moving on and hoping it clicks. 𝗛𝗼𝘄 𝗮𝗿𝗲 𝘄𝗲 𝗮𝗽𝗽𝗿𝗼𝗮𝗰𝗵𝗶𝗻𝗴 𝗶𝘁 𝗱𝗶𝗳𝗳𝗲𝗿𝗲𝗻𝘁𝗹𝘆? Here's a simple three-step protocol to make that question actionable: 𝗦𝘁𝗲𝗽 𝟭: 𝗡𝗮𝗺𝗲 𝘁𝗵𝗲 𝗺𝗶𝘀𝗰𝗼𝗻𝗰𝗲𝗽𝘁𝗶𝗼𝗻, 𝗻𝗼𝘁 𝗷𝘂𝘀𝘁 𝘁𝗵𝗲 𝗺𝗶𝘀𝘁𝗮𝗸𝗲. Don't stop at "students got question 4 wrong." Ask why. Was it a procedural error? A conceptual gap? A language barrier? The misconception tells you how to respond. The mistake only tells you something went wrong. 𝗦𝘁𝗲𝗽 𝟮: 𝗠𝗮𝘁𝗰𝗵 𝘁𝗵𝗲 𝗶𝗻𝘀𝘁𝗿𝘂𝗰𝘁𝗶𝗼𝗻𝗮𝗹 𝗺𝗼𝘃𝗲 𝘁𝗼 𝘁𝗵𝗲 𝗺𝗶𝘀𝗰𝗼𝗻𝗰𝗲𝗽𝘁𝗶𝗼𝗻. If students have a conceptual gap, teachers should use the CRA model (Concrete, Representational, Abstract) as a guide. Start with manipulatives or real-world context, move to visuals, then rebuild the abstract. If it's procedural, slow down the steps and make student thinking as visible as possible. The response has to match the root cause, not just re-cover the content. 𝗦𝘁𝗲𝗽 𝟯: 𝗣𝗿𝗮𝗰𝘁𝗶𝗰𝗲 𝗮𝗻𝗱 𝗮𝘀𝘀𝗶𝗴𝗻 𝗼𝘄𝗻𝗲𝗿𝘀𝗵𝗶𝗽 𝗯𝗲𝗳𝗼𝗿𝗲 𝗹𝗲𝗮𝘃𝗶𝗻𝗴 𝘁𝗵𝗲 𝗿𝗼𝗼𝗺. Every instructional response needs a name attached to it. Who is trying what, in which class, by when and what does that instruction actually look like? Without ownership, the plan dies in the meeting. 𝗗𝗮𝘁𝗮 𝗺𝗲𝗲𝘁𝗶𝗻𝗴𝘀 𝘀𝗵𝗼𝘂𝗹𝗱 𝗲𝗻𝗱 𝘄𝗶𝘁𝗵 𝗮 𝘁𝗲𝗮𝗰𝗵𝗶𝗻𝗴 𝗽𝗹𝗮𝗻, 𝗻𝗼𝘁 𝗷𝘂𝘀𝘁 𝗮 𝘁𝗮𝗹𝗸𝗶𝗻𝗴 𝗽𝗼𝗶𝗻𝘁. ♻️ If this idea resonates, repost to help school leaders and math teams turn data into action, not just conversation. 📧 If you're interested in more practical strategies like this, I'm launching a new newsletter called The 3-1-4, where I share practical strategies for improving math instruction and leadership. The first issue goes out on Pi Day (March 14). Link in the comments. _______________________________ Hi, I'm Dwight Williams. A proud first-gen everything, and I help schools and districts strengthen math instruction through coaching, curriculum support, and data-informed systems that drive student confidence and achievement. 👍🏿 Like | 🔔 Follow | 💬 Comment | 🔁 Repost

I am pleased to share our new publication, "Navigating centralized admissions: The role of parental preferences in school segregation in Chile," recently published in the International Journal of Educational Research (co-authored with Macarena Kutscher). https://lnkd.in/gAyJ8iTR The question we investigated: Why doesn't equal access lead to equal outcomes in school choice? In 2015, Chile enacted the Ley de Inclusión, eliminating school screening practices—no more entrance exams, parent interviews, or income verification. Every family gained equal access through a centralized, algorithm-based system. Key objective: reduce school segregation. The result: Recent evidence by Kutscher and Urzua found minimal impact on integration. Our paper confirms and extends these findings. We analyzed 133,000+ prekindergarten applications to understand why equal access hasn't translated into more integrated schools. By examining families' rank-ordered school choices using discrete choice models, we uncovered systematic differences in how low-SES families navigate school selection. Key findings: Low-income families systematically choose different schools—not because of barriers, but due to distinct preferences: 🔹 They prioritize safety, climate, and belonging over test scores 🔹 They're significantly less likely to apply to high-SES schools 🔹 They strongly favor schools with fewer violent incidents and lower discrimination 🔹 They avoid previously selective schools, even when entitled to fee waivers 🔹 Distance matters far more—they're much less willing to travel The deeper story: Disadvantaged families seek schools where their children will feel welcomed and safe. They rely on observable signals—student behavior, familiar environments, community connections. These choices reflect legitimate concerns about belonging, but may also reflect information gaps about school quality. What this means for policy: Simply removing barriers isn't enough. Effective centralized choice systems need: ✓ Comprehensive information on both academic quality AND school climate ✓ Clear data on safety, inclusiveness, and well-being ✓ Better platform design—parents often spend only minutes applying ✓ Personalized guidance, not just generic rankings ✓ Explicit explanation of how matching algorithms work The opportunity: Pioneering work by Jishnu Das and colleagues in Pakistan and Chris Neilson and colleagues in Chile demonstrated that targeted information interventions can dramatically improve parental choices. We've replicated these approaches in Haiti, Ecuador, and Peru with similar findings. We're now testing these insights on choice platforms in Recife, Brazil, with promising early results. The welfare gains from improving school access for disadvantaged students are substantial. This research points toward specific design features that could help centralized choice systems deliver on their promise of integration.

In the field of #education, data are not just numbers on a page. They tell us who is in school and who is left behind, where teachers are needed most, and how to direct resources for the greatest impact. 𝗗𝗮𝘁𝗮 𝗮𝗿𝗲 𝘁𝗵𝗲 𝗳𝗼𝘂𝗻𝗱𝗮𝘁𝗶𝗼𝗻 𝗼𝗳 𝗲𝘃𝗶𝗱𝗲𝗻𝗰𝗲-𝗯𝗮𝘀𝗲𝗱 𝗽𝗼𝗹𝗶𝗰𝘆𝗺𝗮𝗸𝗶𝗻𝗴, and they ensure that education investments reach those who need them most. Today, key education indicators continue to evolve. Critical data gaps persist, particularly in areas such as early-grade learning, education in emergencies, and technical and vocational education and training (TVET). As we refine how we measure education progress, we recognize its deep connections with other development priorities—from health and labor to climate and digital transformation. UNESCO 𝗵𝗮𝘀 𝗮𝗹𝘄𝗮𝘆𝘀 𝘃𝗮𝗹𝘂𝗲𝗱 𝗱𝗮𝘁𝗮 𝗮𝗻𝗱 𝗽𝗿𝗼𝗺𝗼𝘁𝗲𝗱 𝗱𝗮𝘁𝗮-𝗱𝗿𝗶𝘃𝗲𝗻 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻-𝗺𝗮𝗸𝗶𝗻𝗴 𝘀𝗶𝗻𝗰𝗲 𝗶𝘁𝘀 𝗶𝗻𝗰𝗲𝗽𝘁𝗶𝗼𝗻. The Organization was founded in 1945, and just a year later, in 1946, it established an international statistical service on education. The UNESCO Institute for Statistics (UIS) was established in 1999, building on a rich tradition of data production and taking it to new heights. For the past 25 years, the UIS has been a leader in making data matter in education, science, and culture. It remains the go-to source for accurate, policy-relevant data, the creator of innovative methodologies, the consensus builder among various stakeholders, and the facilitator of national capacities. It's like the Swiss Army knife of statistics. The UIS's history is marked by milestones supporting global, regional, and national initiatives, guiding policymaking, and supporting Member States and the international community. One such milestone was the 𝗳𝗶𝗿𝘀𝘁-𝗲𝘃𝗲𝗿 𝗨𝗡𝗘𝗦𝗖𝗢 𝗖𝗼𝗻𝗳𝗲𝗿𝗲𝗻𝗰𝗲 𝗼𝗻 𝗘𝗱𝘂𝗰𝗮𝘁𝗶𝗼𝗻 𝗗𝗮𝘁𝗮 𝗮𝗻𝗱 𝗦𝘁𝗮𝘁𝗶𝘀𝘁𝗶𝗰𝘀 𝗶𝗻 𝟮𝟬𝟮𝟰, which provided an expert forum for monitoring, advising, and steering the development of methodologies, standards, and indicators. The next conference is planned to take place in 2027. As the UIS moves forward, it remains dedicated to innovation and adaptation, fostering robust dialogue among Member States to ensure that data supports equity and quality of development globally. This commitment is key to the steady future of UNESCO’s statistics. We need to continue to ensure that data are accessible, comparable, and actionable, especially as new technologies redefine how we collect, analyze, and use education data. By strengthening education data, we strengthen education, ensuring that policies are built on knowledge and that 𝗻𝗼 𝗹𝗲𝗮𝗿𝗻𝗲𝗿 𝗶𝘀 𝗹𝗲𝗳𝘁 𝗯𝗲𝗵𝗶𝗻𝗱. Learn more by clicking on the link in the comment below 👇

The impact of data loss will have a devastating effect on high school juniors and seniors, recent high school graduates, and people looking to return to community college and colleges and universities. Even subscription-based #edtech companies rely on this data as the backend to their services - including matching, referrals, and tools to navigate the complexity of college admissions. You might not know IPEDS, but every high school counselor, parent, and student who wants to navigate post-secondary success will feel the effects of no longer having access to this data. Hear from one user - “I work with students navigating the college application process. The IPEDS data is the underlying data set for multiple platforms that high schools, community-based organizations, and individuals like me use to find colleges that fit particular student needs. The federal government-run College Scorecard and College Navigator are free. Some other platforms offer additional functionality and are subscription-based. Without IPEDS data, reliable key information that helps me help students find appropriate higher education options would be much harder, possibly impossible, to source. In addition, nearly all U.S. high schools offer college search capability to students (and manage relevant document handling) through subscription platforms that rely on IPEDS data. Many of those users are likely unaware that IPEDS is the source data underpinning the tools they use. Loss of IPEDS data would impact high school students and school staff across the country.”

Hey #highered leaders - if you're still using static pivot tables to inform strategy, this post is for you ⤵ Take a peak at the below screenshot. This example, which shows two "paired predictors", is just one way you can turn data into action: 📈 ▶ The top right quadrant are “high achievers”. They have a high GPA + high credit earn ratio. These students might simply receive a message of encouragement. ▶ The top left quadrant are “strivers”. They have lower GPAs, but higher credits earned. These students might receive a nudge related to maximizing their use of available academic resources. ▶ The bottom right quadrant are “setbacks”. They have higher overall GPA, likely from good grades in their early coursework, but are earning fewer credits towards graduation requirements in key courses in their major. These students should probably receive messaging about the need for high-touch interaction with their advisors to stay on track and not lose their early momentum. ▶ The students in the bottom left quadrant are in "survival mode”. They are below average in both areas. These students are probably due for some real human-to-human conversation to better understand their needs. They may need in-depth intervention, with accompanied supports for finding the most successful path towards goals that match the students’ strengths and interests. You may consider nudging and re-nudging them throughout a term. ⤵ There's so many more examples of how Civitas Learning partners are disaggregating data to close equity gaps. If you're curious to learn more, let's connect 💌 #studentsuccessanalytics