Data-Driven Education Insights

There are 1.1M credentials but our latest research finds that only 12% offer significant wage gain earners wouldn’t have otherwise gotten. The Burning Glass Institute is launching the Credential Value Index to show which ones work, evaluating the outcomes from 23,000 non-degree credentials from over 2,000 providers, including every certification in America—from Coursera digital marketing certificates to OSHA certifications. To see whether they actually deliver for workers, we analyzed how each changed the course of the careers of 7 million people who had earned them. While only 1 in 3 credentials meet a minimum threshold vs. counterfactual peers for either boosting wages, facilitating career changes, or moving people up within their field, we still found 8,000 credentials that really move the needle for workers—often in ways that are transformative. The top decile of credentials yields annual wage gains of nearly $5,000 vs. counterfactual peers, increases by 7x vs. bottom credentials the chances of switching jobs into an aligned career, and boosts by 17x the probability of an earner’s getting promoted within their current field. We found wide variances in outcomes even for the same credential across named providers–and across the portfolio of credential offerings of even high-reputation providers. That says that learners can’t just trust brands and they can’t just trust that a credential will help just because it’s in a high-paying field. Instead, they need real data to help them make informed decisions. Our goal in this work is practical: to put these evaluations in the hands of workers and learners, employers, education institutions & training providers, and policymakers. The Credential Value Index–available through our Navigator site available on https://lnkd.in/e_BTX9bs –makes all 23,000 evaluations accessible to the public, with easy-to-understand metrics of performance, comparisons with other credentials, and helpful context, like which roles earners find themselves working in, which employers they’re working for, and which skills they master along the way. Our research is summarized in an American Enterprise Institute working paper which I coauthored with AEI senior fellow Mark Schneider and Burning Glass Institute colleagues Shrinidhi Rao, Scott Spitze, and Debbie Wasden. You can find it on https://lnkd.in/ezynMA-v. I want to express my deep thanks to Ellie Bertani, Matt Zieger, and the GitLab Foundation for all they have done to support this initiative. I am grateful for your partnership. And a big thank you to Patti Constantakis and Sean Murphy at Walmart for the opportunity to test this framework in a real-world laboratory. Finally, the Credential Value Index builds on a close partnership with Jobs for the Future (JFF). Many thanks to Maria Flynn, Stephen Yadzinski, and their terrific team. #education #careers #highereducation #learning #skills

“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.

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

In meetings, you might hear phrases like "the data speaks for itself" or "we’re just looking at the facts." These statements can give the impression that data offers a neutral view of reality. But data is never completely neutral. Here’s why. Data reflects a world shaped by existing systems of power. Disparities in education, health, and incarceration show how these systems' social structures are maintained. However, it’s common to interpret disparities in social data as individual failures or successes. For example, someone’s health is often seen as a matter of personal responsibility. Yet no matter which data metric we use—whether deprivation, income, or education—there is a strong social SYSTEM gradient. The poorer you are, or the less education you have, or the more deprived your neighbourhood, the more likely you are to die younger and sicker. This pattern holds across almost every condition or disease. It is not shaped by individuals, but institutional systems of power. So, if you share data about people and communities, you have more responsibility than you might realise. You have the power to influence your peers, government decisions, and ultimately public opinion. By explaining the conditions that shape data, we make it harder for inequities to go unnoticed. To use data responsibly, we have to recognise its dual role. Data can be a mirror that reflects inequality and a magnifier that can make it worse if misinterpreted. ---- Kia ora, I'm Kat 👋 I wrote The Data Storyteller's Handbook. My next book exposes how powerful systems like racism, sexism, and classism shape not only our world but the data we rely on every day.

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.

Students are now getting a warning on their FAFSA: “Some of the colleges you selected show lower earnings.” Sounds like a smart move. Who doesn’t want transparency? But it’s not that simple. The Department of Education is flagging schools where median earnings, four years after graduation, are lower than for high school graduates. But the measure is based on broad institutional data, not by program. So, a strong nursing or tech credential could get penalized because other degrees at the same college don’t pay as well. It also ignores regional economies, public service jobs, and career choice. Yes, we need transparency. Yes, everyone should see value from their college investment. But we have to be careful. Measuring that value by earnings just four years out is a narrow view. It misses how long it takes some graduates to gain traction, especially those starting with fewer resources or entering lower-paying but essential careers. It also ignores lifetime earnings, which we know are significantly higher for degree holders. And it assumes a single definition of success, one where public service, regional impact, or career satisfaction don’t count if the paycheck is smaller. Good data should inform choices. But rushed signals and blunt metrics can push students away from opportunity instead of toward it. We don’t just need transparency. We need context. https://lnkd.in/gXg5ZNr3

The headline says it all — “The missing link between classrooms and jobs.” From my experience working closely with academia and industry, this gap is not theoretical — it’s real, visible, and urgent. We are producing graduates at scale. But are we producing industry-ready talent at scale? Some key reflections: 🔹 Skilling is a continuous journey It cannot begin at the final year — it must start early and evolve with industry needs. 🔹 Degrees alone don’t guarantee employability Skills, exposure, adaptability, and mindset define outcomes today. 🔹 Internships & apprenticeships are powerful bridges Yet, quality, access, and structured implementation need serious attention. 🔹 Industry–academia collaboration is critical Institutions cannot operate in silos if we want better placement outcomes. 🔹 Career awareness is still missing Many students don’t lack ability — they lack direction and informed choices. What we need going forward: ✔️ Industry-aligned curriculum ✔️ Early and continuous exposure to real work environments ✔️ Structured internship & apprenticeship pathways ✔️ Strong career guidance systems ✔️ A mindset shift from “degree-focused” to “outcome-focused” education The conversation is no longer about education vs employment — it is about integration. Bridging this gap is not optional. It is essential for the future of our workforce and our nation. #Employability #Skilling #HigherEducation #FutureOfWork #IndustryAcademia #Leadership #CareerDevelopment #TNATPO

How can we bridge the gap between academia and policymaking to create more effective public policies? This report provides actionable recommendations on improving academic-policy engagement. Key recommendations include: 🔶 Proactive Support: Universities and policy institutes should actively provide information and resources to aid academic engagement with policymaking. Effective signposting to these resources is also essential. 🔶 Recognition in Academic Frameworks: Institutions need to acknowledge policy engagement within workload models and career progression frameworks. This is frequently highlighted during research impact training and is crucial to get right. 🔶 Tailored Guidance: Policymakers should create specific resources for academics to navigate policy engagement opportunities. 🔶 Addressing Geographic Disparities: Mechanisms should be developed to increase engagement with universities outside London and the South East. 🔶 Sustained Engagement: Continuous interactions between policymakers and academics should be facilitated, considering the workload implications. 🔶 Case Studies and Transparency: Publicly accessible case studies of successful academic-policy engagements and transparent use of research evidence are essential. There is wide agreement that engagement between academia and policymakers is a positive step, but it can be challenging to implement. Ensuring that research effectively informs decision-making is key. #AcademicEngagement #PolicyMaking #ResearchImpact #HigherEducation #PublicPolicy #KnowledgeExchange #EvidenceBasedPolicy #AcademicResearch