Edtech and online learning after the pandemic: Applied learning science

Jeffrey Stewart My Blog Mon, Mar 2, 2026Mon, Mar 9, 2026

Let me walk you through what’s really happening here. The conversation around edtech and online learning after the pandemic deserves better than the surface-level takes we usually get. Once you dig into the details, the picture becomes much clearer.

The question worth asking is this: are micro-credential programs actually gaining employer acceptance as degree alternatives? When you look at what the data actually shows, not just what people want it to show, you get a more honest picture.

The Science: Setting the Terms

Here’s the baseline that makes everything else make sense: Coursera and edX combined now have 100 million enrolled users, and those numbers have leveled off. This isn’t just another data point. This is the foundation that everything else builds on. These conditions didn’t appear overnight. They’ve been building for years, and now we’re seeing them converge in ways that feel different from what came before.

Two things are happening at once: micro-credential programs are gaining some employer acceptance as degree alternatives, while K-12 learning loss from COVID is still showing up in standardized tests five years later. When you put these together, you start to see a pattern that EdSurge education technology has been tracking: these changes run deeper than the headlines suggest, and they’re sticking around longer than anyone expected.

Compare what was true three years ago to what’s true now. The change isn’t just in the numbers. The players have changed. The infrastructure has changed. The incentives have changed. And instead of canceling each other out, these changes are building on each other.

What makes this worth paying attention to isn’t that it’s completely new. It’s that patterns we’ve been watching for years have hit a point where you have to actively ignore them to miss them. We’ve crossed a threshold.

AI tutoring tools showing 1-sigma improvement in math outcomes in randomized controlled trials fits into this same picture. These aren’t separate trends. They’re parts of the same structural shift.

The Learning Science Take: The Analysis

Let me get specific about those AI tutoring results. The surface story is straightforward and not wrong, but it misses the mechanism. And the mechanism matters because that’s where you find the practical insights. The mechanism here is teacher shortages in STEM subjects hitting crisis levels across OECD countries. Understanding that changes how you interpret the AI tutoring data.

Teacher shortages in STEM didn’t just happen. They’re the result of structural problems that have been building up for years. Previous attempts to solve similar problems failed because people treated the symptoms instead of the causes. The structural explanation is less exciting as a headline but more useful for actually understanding what’s going on.

Looking at previous cycles is helpful precisely because this one is different. Similar surface conditions played out differently before because the underlying conditions were different. Homeschool rates tripling from pre-pandemic baseline and staying there represents a fundamental change in the system, not just a temporary spike. That distinction matters when you’re trying to figure out what comes next.

I get the skeptical response: we’ve seen similar moments before that didn’t lead to the big changes people predicted. That’s true. But this time we have something those previous moments lacked: homeschool rates tripling and holding steady. That’s not just a preference change. That’s infrastructure. And infrastructure changes tend to stick around in ways that sentiment changes don’t. The74 education journalism is tracking this dimension with the attention it deserves.

There’s also a question that doesn’t get asked enough: who benefits from these changes, and who pays the costs? The overall picture might be positive, but the distribution of benefits and costs matters enormously to the people actually living through this. You can’t read the situation clearly if you only look at the aggregate numbers.

Implications: What This Means If You Care About Learning

The effects of these changes in edtech and online learning go beyond education. Coursera and edX hitting 100 million combined enrollments, plus everything else I’ve described, creates ripple effects in adjacent areas that aren’t always obvious. The second-order effects are often more important than the first-order ones.

Here’s where I think the mainstream coverage gets it wrong: K-12 learning loss still showing up in standardized tests five years after COVID isn’t just a consequence of what already happened. It’s a signal of what’s coming. The people who respond to what this signals, rather than just what it confirms, are going to be less surprised by what happens next.

How you should respond depends on where you sit relative to these changes. If you’re directly involved in edtech, the implications are immediate and operational. If you’re further away, this is more about strategy and understanding which pressures are building and which things you thought were stable might not be.

The question isn’t whether to engage with these dynamics but how. That depends on your context and your actual time horizon. But step one is the same for everyone: understand what’s actually happening instead of just going with the most convenient narrative.

A few concrete points worth pulling out. First: micro-credential programs gaining employer acceptance isn’t temporary. This is the new baseline. Second: teacher shortages in STEM hitting crisis levels tells us the adjustment period isn’t over. Third, and most important: organizations and individuals treating the current moment as a steady state rather than an ongoing transition are making an error that will be expensive to fix later.

The Case Against: What the Critics Get Right

Honesty requires engaging with the strongest counterarguments, not just the easy ones. The case against the optimistic reading of edtech and online learning isn’t trivial. There are real structural problems in the current picture that deserve direct engagement.

The most serious objection is about sustainability. K-12 learning loss still showing up in standardized tests five years later might not be a foundation to build on. It might be a ceiling. If the current state has already captured most of the early adopters, the remaining growth might be much slower than the recent trajectory suggests.

There’s also the regulatory dimension. Coursera and edX stabilizing at 100 million combined enrollments describes what’s happening in a relatively hands-off regulatory environment. Regulatory responses to this scale aren’t guaranteed, but they’re not impossible either. Organizations planning as though the current regulatory environment is permanent are making an assumption that the history of fast-growing sectors doesn’t support.

My response to these concerns isn’t that they’re wrong. It’s that they’re already partially baked into how the field currently operates. Homeschool rates tripling from pre-pandemic baseline and holding steady reflects an environment where participants are already adapting to constraints rather than operating in an unconstrained space. The ecosystem has more adjustment capacity than a purely top-down view of the risks suggests.

Looking Forward

The direction is clearer than the timing. Anyone claiming to know exactly when specific thresholds will be crossed should be treated with skepticism. But the direction toward continued growth in platform enrollments and further development of the conditions I’ve described is supported by evidence in ways that don’t depend on any single thing going perfectly.

Homeschool rates are the variable to watch as the leading indicator. Historical patterns suggest this moves first, with broader metrics following with some delay. This doesn’t make outcomes certain, but it makes them readable. And being able to read what’s happening is what you need to make good decisions.

Three questions worth holding as this develops. First: are the structural conditions that enabled the current state durable, or are they cyclical? Second: who benefits from the next phase, and does that differ from who benefited in the current phase? Third: what would clean evidence against the optimistic thesis look like, and is there any sign of that emerging? You don’t need answers today, but asking these questions changes what you notice going forward.

For most people reading this, the next step is modest. We’re in a moment where people who have built an accurate model of what’s actually happening are better positioned than people relying on the surface story. Building that model takes time, but it’s doable. This analysis is one input into that process.

What learning science finding has most changed how you study or teach?

What Example-first pedagogy Reveals About Higher education affordability crisis

Jeffrey Stewart My Blog Thu, Feb 26, 2026Mon, Mar 9, 2026

Let’s work through what is actually happening here, step by step. The higher education affordability crisis deserves more careful attention than the typical coverage provides, and the reason is not complicated once you know where to look.

The useful question to ask at this point is, viewed through the lens of example-first pedagogy, is college enrollment declining for fourth consecutive year as ROI questioned. The practical read of the situation is also the more accurate one once you examine what the evidence actually shows.

The Pedagogy: Setting the Terms

Average US student loan debt at $37,000 per borrower in 2025 is not just a data point in the story of higher education affordability crisis. It is the structural condition that makes everything else in this analysis legible. Context like this doesn’t age quickly. The conditions that produced it have been building for years, and the convergence is what makes the current moment distinct from previous moments that looked similar from a distance.

College enrollment declining for fourth consecutive year as ROI questioned and vocational trades programs at record enrollment amid skilled labor shortage. When you look at both together, a pattern emerges that Inside Higher Ed news has been covering from the inside: the conditions are more durable than they first appear, and the implications extend further than the immediate headline suggests.

To understand why this matters, it helps to look at what was true three years ago versus what is true now. The difference isn’t simply quantitative, it’s qualitative. The participants, the infrastructure, and the incentive structures have all shifted in ways that compound rather than cancel out. That compounding is the most important element to track.

What makes this moment worth examining carefully isn’t the novelty but the confirmation. The underlying dynamics have been visible for some time. What’s new is that they’ve reached a threshold where ignoring them requires active effort rather than simple inattention. That threshold crossing is the event, not the underlying movement that produced it.

And coding bootcamp market consolidating after 2020-2022 expansion is part of that same picture. These elements don’t exist in separate silos. They’re reinforcing conditions in the same structural shift.

The Worked Example: The Analysis

Coding bootcamp market consolidating after 2020-2022 expansion is where the analysis gets more specific. The surface reading is accessible and not wrong, but it misses the mechanism. The mechanism is where the practical insight lives. The useful question to ask at this point is the mechanism is community college attendance growing as cost-effective pathway, and understanding it changes what you do with the information.

Consider what community college attendance growing as cost-effective pathway represents in context. It’s not a correlation that happened to appear, it’s a downstream consequence of structural factors that have been compounding. Previous readings of similar situations failed because they treated the symptom as the cause. The structural account is less satisfying as a headline but more useful as an analytical tool.

The comparison to prior cycles is instructive precisely because of where it breaks down. Superficially similar conditions resolved differently in previous iterations because the substrate was different. What income share agreements tested as alternative to traditional student loans represents is a substrate change, the kind that alters the elasticity of the system rather than just its current value. Recognizing that distinction is what separates analysis from pattern-matching.

The skeptical counterargument deserves honest engagement: prior moments with similar surface characteristics didn’t produce the outcomes that seemed logical at the time. That history is real. What’s different now is income share agreements tested as alternative to traditional student loans, which isn’t a minor variable, it’s the infrastructure condition that previous cycles lacked. Infrastructure changes tend to be persistent in ways that sentiment-driven changes aren’t. College Board research is one source tracking this dimension with the rigor it requires.

There’s also a distributional question that often goes unaddressed in coverage of higher education affordability crisis: who captures the value created by these shifts, and who absorbs the disruption costs? The aggregate picture can be positive while the distribution is uneven in ways that matter enormously to specific participants. I think keeping that distributional lens in view is part of reading the situation clearly rather than simply optimistically.

Implications: What This Means If You Care About Concept explainers

The implications of higher education affordability crisis extend beyond the immediate context. Average US student loan debt at $37,000 per borrower in 2025 combined with the structural conditions described above creates a situation where adjacent fields, decisions, and communities get affected in ways that aren’t always visible from inside the primary story. The second-order effects are frequently more important than the first-order ones, and they’re where careful attention pays the highest returns.

The frame that matters here, and this is where this perspective departs from the mainstream coverage, is that vocational trades programs at record enrollment amid skilled labor shortage is a leading indicator rather than a lagging one. The people positioned to respond to what this signals, rather than to what it confirms, are the ones who will be less surprised by what follows.

The practical response depends heavily on your position relative to the dynamics at play. For those closest to the core of higher education affordability crisis, the implications are immediate and operational. For those at greater distance, the implications are strategic, a matter of understanding which adjacent pressures are building and which assumed stabilities are more fragile than they appear.

The practical question isn’t whether to engage with these dynamics but how. The answer depends on context, on what role you occupy relative to higher education affordability crisis and what your actual decision horizon is. But the first step is the same regardless: accurate understanding of what’s actually happening rather than what the most available narrative says is happening.

A few concrete observations are worth separating out from the broader analysis. First: college enrollment declining for fourth consecutive year as ROI questioned isn’t a temporary condition, it’s a new baseline. Second: community college attendance growing as cost-effective pathway suggests that the adjustment period isn’t over. Third, and most important: the organizations and individuals who are treating the current moment as a new steady state rather than a transition are making a categorization error that will be costly to unwind later.

The Case Against: What the Critics Get Right

Intellectual honesty requires acknowledging the strongest counterarguments, not just the weakest ones. The case against the optimistic reading of higher education affordability crisis isn’t trivial. There are structural vulnerabilities in the current picture that deserve direct engagement rather than dismissal.

The most serious objection is the one about sustainability. Vocational trades programs at record enrollment amid skilled labor shortage can be read not as a foundation but as a ceiling, a point beyond which growth becomes self-limiting because of the very dynamics that produced it. If the current state has already incorporated most of the available supply of early-adopting participants, the remaining growth curve may be structurally shallower than the recent trajectory implies.

There’s also the policy and regulatory dimension. Average US student loan debt at $37,000 per borrower in 2025 describes a condition in a relatively permissive environment. Regulatory responses to the scale implied by these numbers aren’t inevitable, but they’re not implausible either. The organizations that are planning as though the current regulatory environment is permanent are making an assumption that the history of fast-growing sectors doesn’t support.

The rebuttal to these concerns isn’t that they’re wrong, it’s that they’re already partially priced into the current state of the field. Income share agreements tested as alternative to traditional student loans reflects an environment where participants are already adapting to constraints rather than operating in an unconstrained space. The adjustment capacity of the ecosystem is higher than a purely top-down view of the risks suggests.

Looking Forward

The trajectory here is clearer than the pace. Making predictions about when specific thresholds will be crossed is genuinely difficult, and anyone claiming precision about timelines should be treated with skepticism. But the direction, toward average US student loan debt at $37,000 per borrower and continued development of the conditions described above, is supported by the evidence in a way that isn’t contingent on a single variable going right.

Income share agreements tested as alternative to traditional student loans is the variable to watch as the leading indicator. Historical patterns suggest it moves first, with broader metrics following with some lag. This doesn’t make the outcome certain, but it makes it legible, and legibility is the precondition for good decisions.

Three questions are worth holding as the story develops. First: are the structural conditions that enabled the current state durable, or are they cyclical? Second: who is positioned to benefit from the next phase, and does that differ materially from who benefited in the current phase? Third: what would a clean falsification of the optimistic thesis look like, and is there any evidence of that signal emerging? These questions don’t need answers today, but having asked them changes what you notice in the months ahead.

The next step, for most people reading this, is a small one. The current moment in higher education affordability crisis is one where the people who have built an accurate model of the underlying dynamics are better positioned than the people who are relying on the surface story. Building that model isn’t a quick task, but it’s a tractable one, and this analysis is intended as one input into it.

What would you use this approach to teach? Or what didn’t land, I want to fix it.

The Real Picture on Higher education affordability crisis

Jeffrey Stewart My Blog Thu, Feb 26, 2026Mon, Mar 9, 2026

The useful question to ask at this point is simple: College enrollment is declining for the fourth consecutive year as ROI gets questioned. And honestly? When you look at what the evidence actually shows, this makes complete sense.

The Pedagogy: Setting the Terms

Average US student loan debt hitting $37,000 per borrower in 2025 isn’t just another statistic about the higher education affordability crisis. It’s the structural reality that makes everything else in this analysis click into place. These conditions have been building for years, and what makes this moment different from previous ones that looked similar from a distance is how everything is converging at once.

College enrollment declining for fourth consecutive year as ROI questioned, while vocational trades programs hit record enrollment amid a skilled labor shortage. When you look at both together, a pattern emerges that Inside Higher Ed news has been covering: these conditions are more durable than they first appear, and the implications reach way beyond the immediate headlines.

To understand why this matters, compare what was true three years ago versus what’s true now. The change isn’t just about numbers. It’s qualitative. The players, the infrastructure, and the incentive structures have all shifted in ways that build on each other rather than cancel out. That compounding effect? That’s what matters most.

What makes this moment worth examining carefully isn’t the novelty but the confirmation. These underlying dynamics have been visible for some time. What’s new is that they’ve reached a threshold where ignoring them takes active effort rather than simple inattention. Crossing that threshold is the real event, not the underlying movement that produced it.

And the coding bootcamp market consolidating after its 2020-2022 expansion? That’s part of the same picture. These elements don’t exist in separate worlds. They’re reinforcing conditions in the same structural shift.

The Worked Example (alt): The Analysis

The coding bootcamp market consolidating after 2020-2022 expansion is where the analysis gets more specific. The surface reading is accessible and not wrong, but it misses the mechanism. And the mechanism is where the practical insight lives. The real question is: what does community college attendance growing as a cost-effective pathway actually tell us?

Consider what community college attendance growing as a cost-effective pathway represents in context. This isn’t some random correlation. It’s a downstream consequence of structural factors that have been building up. Previous attempts to read similar situations failed because they treated the symptom as the cause. The structural account is less satisfying as a headline but way more useful as an analytical tool.

The comparison to prior cycles is instructive precisely because of where it breaks down. Similar-looking conditions resolved differently in previous cycles because the foundation was different. Income share agreements being tested as alternatives to traditional student loans represents a foundation change. The kind that alters how elastic the system is, not just its current state. Recognizing that distinction separates actual analysis from simple pattern-matching.

The skeptical counterargument deserves honest engagement: previous moments with similar surface characteristics didn’t produce the outcomes that seemed logical at the time. That history is real. What’s different now is income share agreements tested as alternative to traditional student loans, which isn’t a minor variable. It’s the infrastructure condition that previous cycles lacked. Infrastructure changes tend to stick around in ways that sentiment-driven changes don’t. College Board research is one source tracking this with the rigor it requires.

There’s also a distributional question that often goes unaddressed in coverage of the higher education affordability crisis: who actually captures the value created by these shifts, and who absorbs the disruption costs? The big picture can look positive while the distribution is uneven in ways that matter enormously to specific people. I think keeping that lens in view is part of reading the situation clearly rather than just optimistically.

Implications: What This Means If You Care About Concept explainers

The implications of the higher education affordability crisis extend beyond the immediate context. Average US student loan debt at $37,000 per borrower in 2025, combined with the structural conditions described above, creates a situation where adjacent fields, decisions, and communities get affected in ways that aren’t always visible from inside the primary story. The second-order effects are frequently more important than the first-order ones.

Here’s where this perspective departs from mainstream coverage: vocational trades programs at record enrollment amid skilled labor shortage is a leading indicator rather than a lagging one. The people positioned to respond to what this signals, rather than to what it confirms, are the ones who will be less surprised by what comes next.

The practical response depends heavily on your position relative to these dynamics. For those closest to the core of the higher education affordability crisis, the implications are immediate and operational. For those at greater distance, the implications are strategic. It’s about understanding which adjacent pressures are building and which assumed stabilities are more fragile than they appear.

The practical question isn’t whether to engage with these dynamics but how. The answer depends on context, on what role you occupy relative to the higher education affordability crisis and what your actual decision horizon looks like. But the first step is the same regardless: accurate understanding of what’s actually happening rather than what the most available narrative says is happening.

A few concrete observations are worth separating out from the broader analysis. First: college enrollment declining for fourth consecutive year as ROI questioned isn’t a temporary condition. It’s a new baseline. Second: community college attendance growing as a cost-effective pathway suggests that the adjustment period isn’t over. Third, and most important: the organizations and individuals who are treating the current moment as a new steady state rather than a transition are making a categorization error that will be costly to unwind later.

The Case Against: What the Critics Get Right

Intellectual honesty requires acknowledging the strongest counterarguments, not just the weakest ones. The case against the optimistic reading of the higher education affordability crisis isn’t trivial. There are structural vulnerabilities in the current picture that deserve direct engagement rather than dismissal.

The most serious objection is about sustainability. Vocational trades programs at record enrollment amid skilled labor shortage can be read not as a foundation but as a ceiling. A point beyond which growth becomes self-limiting because of the very dynamics that produced it. If the current state has already incorporated most of the available supply of early-adopting participants, the remaining growth curve may be structurally shallower than the recent trajectory implies.

There’s also the policy and regulatory dimension. Average US student loan debt at $37,000 per borrower in 2025 describes a condition in a relatively permissive environment. Regulatory responses to the scale implied by these numbers aren’t inevitable, but they’re not implausible either. Organizations planning as though the current regulatory environment is permanent are making an assumption that the history of fast-growing sectors doesn’t support.

The rebuttal to these concerns isn’t that they’re wrong. It’s that they’re already partially priced into the current state of the field. Income share agreements tested as alternative to traditional student loans reflects an environment where participants are already adapting to constraints rather than operating in an unconstrained space. The adjustment capacity of the ecosystem is higher than a purely top-down view of the risks suggests.

Looking Forward

The trajectory here is clearer than the pace. Making predictions about when specific thresholds will be crossed is genuinely difficult, and anyone claiming precision about timelines should be treated with skepticism. But the direction toward continued growth of alternative education models and the conditions described above is supported by evidence that doesn’t depend on a single variable going right.

Income share agreements tested as alternative to traditional student loans is the variable to watch as the leading indicator. Historical patterns suggest it moves first, with broader metrics following with some lag. This doesn’t make the outcome certain, but it makes it readable. And readability is what you need for good decisions.

Three questions are worth holding as the story develops. First: are the structural conditions that enabled the current state durable, or are they cyclical? Second: who is positioned to benefit from the next phase, and does that differ materially from who benefited in the current phase? Third: what would clean evidence against the optimistic thesis look like, and is there any sign of that signal emerging? These questions don’t need answers today, but having asked them changes what you notice in the months ahead.

The next step, for most people reading this, is a small one. The current moment in the higher education affordability crisis is one where people who have built an accurate model of the underlying dynamics are better positioned than people relying on the surface story. Building that model isn’t quick, but it’s doable. And this analysis is intended as one input into it.

What would you use this approach to teach? Or what didn’t land? I want to fix it.

The Worked Example (alt): Edtech and online learning after the pandemic

Jeffrey Stewart My Blog Thu, Feb 26, 2026Mon, Mar 9, 2026

Let’s work through what is actually happening here, step by step. The topic of edtech and online learning after the pandemic deserves more careful attention than the typical coverage provides, and the reason is not complicated once you know where to look.

The useful question to ask at this point is, viewed through the lens of example-first pedagogy, are micro-credential programmes actually gaining employer acceptance as degree alternatives? The practical read of the situation is also the more accurate one once you examine what the evidence shows.

The Pedagogy: Setting the Terms

Coursera and edX platform enrolments stabilizing at 100 million combined isn’t just a data point in the story of edtech and online learning after the pandemic. It’s the structural condition that makes everything else in this analysis make sense. Context like this doesn’t age quickly. The conditions that produced it have been building for years, and the convergence is what makes this moment different from previous moments that looked similar from a distance.

micro-credential programmes gaining employer acceptance as degree alternatives and K-12 learning loss from COVID still measurable 5 years later in standardized tests. When you look at both together, a pattern emerges that EdSurge education technology has been covering from the inside: the conditions are more durable than they first appear, and the implications extend further than the immediate headline suggests.

To understand why this matters, it helps to look at what was true three years ago versus what is true now. The delta isn’t simply quantitative, it’s qualitative. The participants, the infrastructure, and the incentive structures have all shifted in ways that compound rather than cancel out. That compounding is the most important element to track.

What makes this moment worth examining carefully is not the novelty but the confirmation. The underlying dynamics have been visible for some time. What’s new is that they have reached a threshold where ignoring them requires active effort rather than simple inattention. That threshold crossing is the event, not the underlying movement that produced it.

And AI tutoring tools showing 1-sigma improvement in maths outcomes in RCT studies is part of that same picture. These elements don’t exist in separate silos. They’re reinforcing conditions in the same structural shift.

The Worked Example (alt): The Analysis

AI tutoring tools showing 1-sigma improvement in maths outcomes in RCT studies is where the analysis gets more specific. The surface reading is accessible and not wrong, but it misses the mechanism, and the mechanism is where the practical insight lives. The useful question to ask at this point is: what’s driving this? Teacher shortages in STEM subjects reaching crisis levels across OECD countries. Understanding it changes what you do with the information.

Consider what teacher shortages in STEM subjects reaching crisis levels across OECD countries represents in context. It’s not a correlation that happened to appear. It’s a downstream consequence of structural factors that have been compounding. Previous readings of similar situations failed because they treated the symptom as the cause. The structural account is less satisfying as a headline but more useful as an analytical tool.

The comparison to prior cycles is instructive precisely because of where it breaks down. Superficially similar conditions resolved differently in previous iterations because the substrate was different. What homeschool rates tripling from pre-pandemic baseline and holding steady represents is a substrate change, the kind that alters the elasticity of the system rather than just its current value. Recognizing that distinction is what separates analysis from pattern-matching.

The skeptical counterargument deserves honest engagement: prior moments with similar surface characteristics didn’t produce the outcomes that seemed logical at the time. That history is real. What’s different now is homeschool rates tripling from pre-pandemic baseline and holding steady, which isn’t a minor variable. It’s the infrastructure condition that previous cycles lacked. Infrastructure changes tend to be persistent in ways that sentiment-driven changes are not. The74 education journalism is one source tracking this dimension with the rigor it requires.

There’s also a distributional question that often goes unaddressed in coverage of edtech and online learning after the pandemic: who captures the value created by these shifts, and who absorbs the disruption costs? The aggregate picture can be positive while the distribution is uneven in ways that matter enormously to specific participants. Keeping that distributional lens in view is part of reading the situation clearly rather than simply optimistically.

Implications: What This Means If You Care About Concept explainers

The implications of edtech and online learning after the pandemic extend beyond the immediate context. Coursera and edX platform enrolments stabilizing at 100 million combined, along with the structural conditions described above, creates a situation where adjacent fields, decisions, and communities are affected in ways that aren’t always visible from inside the primary story. The second-order effects are frequently more important than the first-order ones, and they’re where careful attention pays the highest returns.

The frame that matters here, and this is where this perspective departs from the mainstream coverage, is that K-12 learning loss from COVID still measurable 5 years later in standardized tests is a leading indicator rather than a lagging one. The people positioned to respond to what this signals, rather than to what it confirms, are the ones who will be less surprised by what follows.

The practical response depends heavily on your position relative to the dynamics at play. For those closest to the core of edtech and online learning after the pandemic, the implications are immediate and operational. For those at greater distance, the implications are strategic, a matter of understanding which adjacent pressures are building and which assumed stabilities are more fragile than they appear.

The practical question isn’t whether to engage with these dynamics but how. The answer depends on context, on what role you occupy relative to edtech and online learning after the pandemic and what your actual decision horizon is. But the first step is the same regardless: accurate understanding of what is actually happening rather than what the most available narrative says is happening.

A few concrete observations are worth separating out from the broader analysis. First: micro-credential programmes gaining employer acceptance as degree alternatives isn’t a temporary condition. It’s a new baseline. Second: teacher shortages in STEM subjects reaching crisis levels across OECD countries suggests that the adjustment period isn’t over. Third, and most important: the organizations and individuals who are treating the current moment as a new steady state rather than a transition are making a categorization error that will be costly to unwind later.

The Case Against: What the Critics Get Right

Intellectual honesty requires acknowledging the strongest counterarguments, not just the weakest ones. The case against the optimistic reading of edtech and online learning after the pandemic isn’t trivial. There are structural vulnerabilities in the current picture that need direct engagement rather than dismissal.

The most serious objection is the one about sustainability. K-12 learning loss from COVID still measurable 5 years later in standardized tests can be read not as a foundation but as a ceiling, a point beyond which growth becomes self-limiting because of the very dynamics that produced it. If the current state has already incorporated most of the available supply of early-adopting participants, the remaining growth curve may be structurally shallower than the recent trajectory implies.

There’s also the policy and regulatory dimension. Coursera and edX platform enrolments stabilizing at 100 million combined describes a condition in a relatively permissive environment. Regulatory responses to the scale implied by these numbers aren’t inevitable, but they’re not implausible either. The organizations that are planning as though the current regulatory environment is permanent are making an assumption that the history of fast-growing sectors doesn’t support.

The rebuttal to these concerns isn’t that they’re wrong. It’s that they’re already partially priced into the current state of the field. homeschool rates tripling from pre-pandemic baseline and holding steady reflects an environment where participants are already adapting to constraints rather than operating in an unconstrained space. The adjustment capacity of the ecosystem is higher than a purely top-down view of the risks suggests.

Looking Forward

The trajectory here is clearer than the pace. Making predictions about when specific thresholds will be crossed is genuinely difficult, and anyone claiming precision about timelines should be treated with skepticism. But the direction, toward Coursera and edX platform enrolments stabilizing at 100… and continued development of the conditions described above, is supported by the evidence in a way that isn’t contingent on a single variable going right.

homeschool rates tripling from pre-pandemic baseline and holding steady is the variable to watch as the leading indicator. Historical patterns suggest it moves first, with broader metrics following with some lag. This doesn’t make the outcome certain, but it makes it legible, and legibility is the precondition for good decisions.

The next step, for most people reading this, is a small one. The current moment in edtech and online learning after the pandemic is one where the people who have built an accurate model of the underlying dynamics are better positioned than the people who are relying on the surface story. Building that model isn’t a quick task, but it is a tractable one, and this analysis is intended as one input into it.

What would you use this approach to teach? Or what didn’t land, I want to fix it.

The Worked Example (alt): Edtech and online learning after the pandemic

Jeffrey Stewart My Blog Thu, Feb 26, 2026Mon, Mar 9, 2026

The useful question to ask at this point is, viewed through the lens of example-first pedagogy, are micro-credential programmes gaining employer acceptance as degree alternatives? The practical read of the situation is also the more accurate one once you examine what the evidence actually shows.

The Pedagogy: Setting the Terms

Coursera and edX platform enrollments stabilizing at 100 million combined is not just a data point in the story of edtech and online learning after the pandemic. It’s the structural condition that makes everything else in this analysis legible. Context like this doesn’t age quickly. The conditions that produced it have been building for years, and this convergence is what makes the current moment distinct from previous moments that looked similar from a distance.

Micro-credential programmes are gaining employer acceptance as degree alternatives while K-12 learning loss from COVID is still measurable 5 years later in standardized tests. When you look at both together, a pattern emerges that EdSurge education technology has been covering from the inside: the conditions are more durable than they first appear, and the implications extend further than the immediate headline suggests.

To understand why this matters, it helps to look at what was true three years ago versus what is true now. The delta is not simply quantitative, it’s qualitative. The participants, the infrastructure, and the incentive structures have all shifted in ways that compound rather than cancel out. That compounding is the most important element to track.

What makes this moment worth examining carefully is not the novelty but the confirmation. The underlying dynamics have been visible for some time. What is new is that they have reached a threshold where ignoring them requires active effort rather than simple inattention. That threshold crossing is the event, not the underlying movement that produced it.

And AI tutoring tools showing 1-sigma improvement in math outcomes in RCT studies is part of that same picture. These elements don’t exist in separate silos, they’re reinforcing conditions in the same structural shift.

The Worked Example (alt): The Analysis

AI tutoring tools showing 1-sigma improvement in math outcomes in RCT studies is where the analysis gets more specific. The surface reading is accessible and not wrong, but it misses the mechanism, and the mechanism is where the practical insight lives. The useful question to ask at this point is: what’s the mechanism? It’s teacher shortages in STEM subjects reaching crisis levels across OECD countries, and understanding this changes what you do with the information.

Consider what teacher shortages in STEM subjects reaching crisis levels across OECD countries represents in context. It’s not a correlation that happened to appear, it’s a downstream consequence of structural factors that have been compounding. Previous readings of similar situations failed because they treated the symptom as the cause. The structural account is less satisfying as a headline but more useful as an analytical tool.

The comparison to prior cycles is instructive precisely because of where it breaks down. Superficially similar conditions resolved differently in previous iterations because the substrate was different. Homeschool rates tripling from pre-pandemic baseline and holding steady represents a substrate change, the kind that alters the elasticity of the system rather than just its current value. Recognizing that distinction is what separates analysis from pattern-matching.

The skeptical counterargument deserves honest engagement: prior moments with similar surface characteristics didn’t produce the outcomes that seemed logical at the time. That history is real. What’s different now is homeschool rates tripling from pre-pandemic baseline and holding steady, which is not a minor variable, it’s the infrastructure condition that previous cycles lacked. Infrastructure changes tend to be persistent in ways that sentiment-driven changes are not. The74 education journalism is one source tracking this dimension with the rigor it requires.

Implications: What This Means If You Care About Concept Explainers

The implications of edtech and online learning after the pandemic extend beyond the immediate context. Coursera and edX platform enrollments stabilizing at 100 million combined, combined with the structural conditions described above, creates a situation where adjacent fields, decisions, and communities are affected in ways that aren’t always visible from inside the primary story. The second-order effects are frequently more important than the first-order ones, and they’re where careful attention pays the highest returns.

The practical question is not whether to engage with these dynamics but how. The answer depends on context, on what role you occupy relative to edtech and online learning after the pandemic and what your actual decision horizon is. But the first step is the same regardless: accurate understanding of what is actually happening rather than what the most available narrative says is happening.

A few concrete observations are worth separating out from the broader analysis. First: micro-credential programmes gaining employer acceptance as degree alternatives is not a temporary condition, it’s a new baseline. Second: teacher shortages in STEM subjects reaching crisis levels across OECD countries suggests that the adjustment period isn’t over. Third, and most important: the organizations and individuals who are treating the current moment as a new steady state rather than a transition are making a categorization error that will be costly to unwind later.

The Case Against: What the Critics Get Right

The most serious objection is about sustainability. K-12 learning loss from COVID still measurable 5 years later in standardized tests can be read not as a foundation but as a ceiling, a point beyond which growth becomes self-limiting because of the very dynamics that produced it. If the current state has already incorporated most of the available supply of early-adopting participants, the remaining growth curve may be structurally shallower than the recent trajectory implies.

There’s also the policy and regulatory dimension. Coursera and edX platform enrollments stabilizing at 100 million combined describes a condition in a relatively permissive environment. Regulatory responses to the scale implied by these numbers aren’t inevitable, but they’re not implausible either. The organizations that are planning as though the current regulatory environment is permanent are making an assumption that the history of fast-growing sectors doesn’t support.

The rebuttal to these concerns isn’t that they’re wrong, it’s that they’re already partially priced into the current state of the field. Homeschool rates tripling from pre-pandemic baseline and holding steady reflects an environment where participants are already adapting to constraints rather than operating in an unconstrained space. The adjustment capacity of the ecosystem is higher than a purely top-down view of the risks suggests.

Looking Forward

The trajectory here is clearer than the pace. Making predictions about when specific thresholds will be crossed is genuinely difficult, and anyone claiming precision about timelines should be treated with skepticism. But the direction, toward Coursera and edX platform enrollments stabilizing at 100… and continued development of the conditions described above, is supported by the evidence in a way that isn’t contingent on a single variable going right.

Homeschool rates tripling from pre-pandemic baseline and holding steady is the variable to watch as the leading indicator. Historical patterns suggest it moves first, with broader metrics following with some lag. This doesn’t make the outcome certain, but it makes it legible, and legibility is the precondition for good decisions.

What would you use this approach to teach? Or what didn’t land, I want to fix it.

The System Design: Higher education affordability crisis

Jeffrey Stewart My Blog Tue, Feb 24, 2026Mon, Mar 9, 2026

The useful question to ask at this point is, from the perspective of curriculum and system design, why is college enrollment declining for a fourth consecutive year as ROI gets questioned? The systematic read of the situation is also the more accurate one once you examine what the evidence actually shows.

The Design: Setting the Terms

Average US student loan debt at $37,000 per borrower in 2025 isn’t just a data point in the story of higher education affordability crisis. It’s the structural condition that makes everything else in this analysis make sense. Context like this doesn’t age quickly. The conditions that produced it have been building for years, and the convergence is what makes this moment different from previous ones that looked similar from a distance.

College enrollment declining for a fourth consecutive year as ROI gets questioned, while vocational trades programs hit record enrollment amid a skilled labor shortage. When you look at both together, a pattern emerges that Inside Higher Ed news has been covering from the inside: the conditions are more durable than they first appear, and the implications reach further than the immediate headline suggests.

To understand why this matters, it helps to look at what was true three years ago versus what’s true now. The change isn’t simply quantitative, it’s qualitative. The participants, the infrastructure, and the incentive structures have all shifted in ways that build on each other rather than cancel out. That compounding effect is the most important element to track.

What makes this moment worth examining carefully isn’t the novelty but the confirmation. I’ve been watching these dynamics for some time. What’s new is that they’ve reached a threshold where ignoring them requires active effort rather than simple inattention. That threshold crossing is the event, not the underlying movement that produced it.

And the coding bootcamp market consolidating after 2020-2022 expansion? That’s part of the same picture. These elements don’t exist in separate silos. They’re reinforcing conditions in the same structural shift.

The System Design: The Analysis

The coding bootcamp market consolidating after 2020-2022 expansion is where the analysis gets more specific. The surface reading is accessible and not wrong, but it misses the mechanism. And the mechanism is where the practical insight lives. The question to ask at this point is why community college attendance is growing as a cost-effective pathway, and understanding it changes what you do with the information.

Consider what community college attendance growing as a cost-effective pathway represents in context. It’s not a correlation that happened to appear. It’s a downstream consequence of structural factors that have been compounding. Previous readings of similar situations failed because they treated the symptom as the cause. The structural account is less satisfying as a headline but more useful as an analytical tool.

The comparison to prior cycles is instructive precisely because of where it breaks down. Superficially similar conditions resolved differently in previous iterations because the foundation was different. What income share agreements tested as alternative to traditional student loans represents is a foundation change, the kind that alters how elastic the system is rather than just its current value. Recognizing that distinction is what separates analysis from pattern-matching.

The skeptical counterargument deserves honest engagement: prior moments with similar surface characteristics didn’t produce the outcomes that seemed logical at the time. That history is real. What’s different now is income share agreements tested as alternative to traditional student loans, which isn’t a minor variable. It’s the infrastructure condition that previous cycles lacked. Infrastructure changes tend to stick around in ways that sentiment-driven changes don’t. College Board research is one source tracking this dimension with the rigor it requires.

There’s also a distributional question that often goes unaddressed in coverage of higher education affordability crisis: who captures the value created by these shifts, and who absorbs the disruption costs? The aggregate picture can be positive while the distribution is uneven in ways that matter enormously to specific participants. Keeping that distributional lens in view is part of reading the situation clearly rather than simply optimistically.

Implications: What This Means If You Care About Skill Learning Roadmaps

The implications of higher education affordability crisis extend beyond the immediate context. Average US student loan debt at $37,000 per borrower in 2025 combined with the structural conditions described above creates a situation where adjacent fields, decisions, and communities are affected in ways that aren’t always visible from inside the primary story. The second-order effects are frequently more important than the first-order ones, and they’re where careful attention pays the highest returns.

A few concrete observations are worth separating out from the broader analysis. First: college enrollment declining for a fourth consecutive year as ROI gets questioned isn’t a temporary condition, it’s a new baseline. Second: community college attendance growing as a cost-effective pathway suggests that the adjustment period isn’t over. Third, and most important: the organizations and individuals who are treating the current moment as a new steady state rather than a transition are making a categorization error that will be costly to unwind later.

The Case Against: What the Critics Get Right

Looking Forward

Income share agreements tested as alternative to traditional student loans is the variable to watch as the leading indicator. Historical patterns suggest it moves first, with broader metrics following with some lag. This doesn’t make the outcome certain, but it makes it readable, and readability is the precondition for good decisions.

Three questions are worth holding as the story develops. First: are the structural conditions that enabled the current state durable, or are they cyclical? Second: who’s positioned to benefit from the next phase, and does that differ materially from who benefited in the current phase? Third: what would a clean falsification of the optimistic thesis look like, and is there any evidence of that signal emerging? These questions don’t need answers today, but having asked them changes what you notice in the months ahead.

What would you change in this system based on your own experience learning this?

Edtech and online learning after the pandemic: Curriculum and system design

Jeffrey Stewart My Blog Tue, Feb 24, 2026Mon, Mar 9, 2026

The useful question to ask at this point is this: viewed through the lens of curriculum and system design, are micro-credential programmes gaining employer acceptance as degree alternatives? The systematic read of the situation is also the more accurate one once you examine what the evidence actually shows.

The Design: Setting the Terms

Coursera and edX platform enrolments stabilizing at 100 million combined is not just a data point in the story of edtech and online learning after the pandemic. It’s the structural condition that makes everything else in this analysis legible. Context like this doesn’t age quickly. The conditions that produced it have been building for years, and the convergence makes the current moment distinct from previous moments that looked similar from a distance.

Look at micro-credential programmes gaining employer acceptance as degree alternatives and K-12 learning loss from COVID still measurable 5 years later in standardized tests. When you examine both together, a pattern emerges that EdSurge education technology has been covering from the inside: the conditions are more durable than they first appear, and the implications extend further than the immediate headline suggests.

To understand why this matters, it helps to look at what was true three years ago versus what is true now. The delta is not simply quantitative. It’s qualitative. The participants, the infrastructure, and the incentive structures have all shifted in ways that compound rather than cancel out. That compounding is the most important element to track.

The System Design: The Analysis

AI tutoring tools showing 1-sigma improvement in maths outcomes in RCT studies is where the analysis gets more specific. The surface reading is accessible and not wrong, but it misses the mechanism, and the mechanism is where the practical insight lives. The useful question to ask at this point is what the mechanism actually is. Teacher shortages in STEM subjects reaching crisis levels across OECD countries helps explain this, and understanding it changes what you do with the information.

The comparison to prior cycles is instructive precisely because of where it breaks down. Similar conditions resolved differently in previous iterations because the substrate was different. Homeschool rates tripling from pre-pandemic baseline and holding steady represents a substrate change, the kind that alters the elasticity of the system rather than just its current value. Recognizing that distinction separates analysis from pattern-matching.

The skeptical counterargument deserves honest engagement: prior moments with similar surface characteristics didn’t produce the outcomes that seemed logical at the time. That history is real. What’s different now is homeschool rates tripling from pre-pandemic baseline and holding steady, which is not a minor variable. It’s the infrastructure condition that previous cycles lacked. Infrastructure changes tend to be persistent in ways that sentiment-driven changes are not. The74 education journalism is one source tracking this dimension with the rigor it requires.

Implications: What This Means If You Care About Skill learning roadmaps

The implications of edtech and online learning after the pandemic extend beyond the immediate context. Coursera and edX platform enrolments stabilizing at 100 million combined, plus the structural conditions described above, creates a situation where adjacent fields, decisions, and communities get affected in ways that aren’t always visible from inside the primary story. The second-order effects are frequently more important than the first-order ones, and they’re where careful attention pays the highest returns.

The frame that matters here (and this is where this perspective departs from the mainstream coverage) is that K-12 learning loss from COVID still measurable 5 years later in standardized tests works as a leading indicator rather than a lagging one. The people positioned to respond to what this signals, rather than to what it confirms, are the ones who will be less surprised by what follows.

The practical response depends heavily on your position relative to the dynamics at play. For those closest to the core of edtech and online learning after the pandemic, the implications are immediate and operational. For those at greater distance, the implications are strategic. It becomes a matter of understanding which adjacent pressures are building and which assumed stabilities are more fragile than they appear.

A few concrete observations are worth separating out from the broader analysis. First: micro-credential programmes gaining employer acceptance as degree alternatives is not a temporary condition. It’s a new baseline. Second: teacher shortages in STEM subjects reaching crisis levels across OECD countries suggests that the adjustment period is not over. Third, and most important: the organizations and individuals who are treating the current moment as a new steady state rather than a transition are making a categorization error that will be costly to unwind later.

The Case Against: What the Critics Get Right

Intellectual honesty requires acknowledging the strongest counterarguments, not just the weakest ones. The case against the optimistic reading of edtech and online learning after the pandemic is not trivial. There are structural vulnerabilities in the current picture that need direct engagement rather than dismissal.

There’s also the policy and regulatory dimension. Coursera and edX platform enrolments stabilizing at 100 million combined describes a condition in a relatively permissive environment. Regulatory responses to the scale implied by these numbers are not guaranteed, but they’re not implausible either. The organizations that are planning as though the current regulatory environment is permanent are making an assumption that the history of fast-growing sectors doesn’t support.

The rebuttal to these concerns is not that they’re wrong. It’s that they’re already partially priced into the current state of the field. Homeschool rates tripling from pre-pandemic baseline and holding steady reflects an environment where participants are already adapting to constraints rather than operating in an unconstrained space. The adjustment capacity of the ecosystem is higher than a purely top-down view of the risks suggests.

Looking Forward

The trajectory here is clearer than the pace. Making predictions about when specific thresholds will be crossed is genuinely difficult, and anyone claiming precision about timelines should be treated with skepticism. But the direction (toward Coursera and edX platform enrolments stabilizing at 100 million and continued development of the conditions described above) is supported by the evidence in a way that doesn’t depend on a single variable going right.

Homeschool rates tripling from pre-pandemic baseline and holding steady is the variable to watch as the leading indicator. Historical patterns suggest it moves first, with broader metrics following with some lag. This doesn’t make the outcome certain, but it makes it legible. And legibility is the precondition for good decisions.

The next step, for most people reading this, is a small one. The current moment in edtech and online learning after the pandemic is one where the people who have built an accurate model of the underlying dynamics are better positioned than the people who are relying on the surface story. Building that model is not a quick task, but it is a doable one. This analysis is intended as one input into it.

What would you change in this system based on your own experience learning this?

Forsite — Learning Without Limits

Jeffrey Stewart My Blog Sun, Feb 22, 2026Mon, Mar 9, 2026

Forsite — Learning Without Limits

Educational content that actually makes you want to learn more.

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Education is the most important thing we do as a society, and it deserves way better resources than what most students and teachers actually get. We write explanations, guides, and research summaries that cut through the noise and help you understand what matters.

Topics we cover: For Students · For Educators · Research · Explainers · Tools · Career

What Applied learning science Reveals About Higher education affordability crisis

Jeffrey Stewart My Blog Sat, Feb 21, 2026Mon, Mar 9, 2026

Let’s work through what is actually happening here, step by step. The higher education affordability crisis deserves more careful attention than most coverage gives it, and the reason isn’t complicated once you know where to look.

The useful question to ask at this point is, viewed through applied learning science, why is college enrollment declining for a fourth consecutive year as ROI gets questioned? The evidence-based read of the situation is also the more accurate one once you examine what the data actually shows.

The Science: Setting the Terms

Average US student loan debt hitting $37,000 per borrower in 2025 isn’t just another data point in the higher education affordability crisis. It’s the structural condition that makes everything else in this analysis make sense. Context like this doesn’t age quickly. The conditions that created it have been building for years, and this convergence is what makes right now different from previous moments that looked similar from a distance.

College enrollment is declining for a fourth consecutive year as ROI gets questioned, while vocational trade programs hit record enrollment amid a skilled labor shortage. When you look at both together, a pattern emerges that Inside Higher Ed news has been covering from the inside: these conditions are more durable than they first appear, and the implications reach further than the immediate headlines suggest.

To understand why this matters, look at what was true three years ago versus what’s true now. The change isn’t just quantitative, it’s qualitative. The participants, the infrastructure, and the incentive structures have all shifted in ways that compound rather than cancel out. That compounding is the most important thing to track.

What makes this moment worth examining carefully isn’t the novelty but the confirmation. These underlying dynamics have been visible for some time. What’s new is that they’ve reached a threshold where ignoring them requires active effort rather than simple inattention. Crossing that threshold is the real event, not the underlying movement that produced it.

And the coding bootcamp market consolidating after its 2020-2022 expansion is part of that same picture. These elements don’t exist in separate silos, they’re reinforcing conditions in the same structural shift.

The Learning Science Take (alt): The Analysis

The coding bootcamp market consolidating after its 2020-2022 expansion is where this analysis gets more specific. The surface reading is accessible and not wrong, but it misses the mechanism. And the mechanism is where the practical insight lives. The useful question here is understanding why community college attendance is growing as a cost-effective pathway, because understanding it changes what you do with the information.

Consider what growing community college attendance as a cost-effective pathway actually represents in context. It’s not a correlation that happened to appear, it’s a downstream consequence of structural factors that have been compounding. Previous readings of similar situations failed because they treated the symptom as the cause. The structural account is less satisfying as a headline but more useful as an analytical tool.

The comparison to prior cycles is instructive precisely because of where it breaks down. Superficially similar conditions resolved differently in previous iterations because the substrate was different. What income share agreements being tested as alternatives to traditional student loans represents is a substrate change, the kind that alters the elasticity of the system rather than just its current value. Recognizing that distinction separates analysis from pattern-matching.

The skeptical counterargument deserves honest engagement: prior moments with similar surface characteristics didn’t produce the outcomes that seemed logical at the time. That history is real. What’s different now is income share agreements being tested as alternatives to traditional student loans, which isn’t a minor variable, it’s the infrastructure condition that previous cycles lacked. Infrastructure changes tend to persist in ways that sentiment-driven changes don’t. College Board research is one source tracking this dimension with the rigor it requires.

There’s also a distributional question that often goes unaddressed in coverage of the higher education affordability crisis: who captures the value created by these shifts, and who absorbs the disruption costs? The aggregate picture can be positive while the distribution is uneven in ways that matter enormously to specific participants. Keeping that distributional lens in view is part of reading the situation clearly rather than just optimistically.

Implications: What This Means If You Care About Spacing effect

The frame that matters here, and this is where this perspective departs from mainstream coverage, is that vocational trade programs hitting record enrollment amid a skilled labor shortage is a leading indicator rather than a lagging one. The people positioned to respond to what this signals, rather than to what it confirms, are the ones who will be less surprised by what follows.

The practical response depends heavily on your position relative to these dynamics. For those closest to the core of the higher education affordability crisis, the implications are immediate and operational. For those at greater distance, the implications are strategic, a matter of understanding which adjacent pressures are building and which assumed stabilities are more fragile than they appear.

The practical question isn’t whether to engage with these dynamics but how. The answer depends on context, on what role you occupy relative to the higher education affordability crisis and what your actual decision horizon is. But the first step is the same regardless: accurate understanding of what’s actually happening rather than what the most available narrative says is happening.

The Case Against: What the Critics Get Right

The most serious objection is about sustainability. Vocational trade programs hitting record enrollment amid a skilled labor shortage can be read not as a foundation but as a ceiling, a point beyond which growth becomes self-limiting because of the very dynamics that produced it. If the current state has already incorporated most of the available supply of early-adopting participants, the remaining growth curve may be structurally shallower than the recent trajectory implies.

The rebuttal to these concerns isn’t that they’re wrong, it’s that they’re already partially priced into the current state of the field. Income share agreements being tested as alternatives to traditional student loans reflects an environment where participants are already adapting to constraints rather than operating in an unconstrained space. The adjustment capacity of the ecosystem is higher than a purely top-down view of the risks suggests.

Looking Forward

Income share agreements being tested as alternatives to traditional student loans is the variable to watch as the leading indicator. Historical patterns suggest it moves first, with broader metrics following with some lag. This doesn’t make the outcome certain, but it makes it readable, and readability is the precondition for good decisions.

Three questions are worth holding as this story develops. First: are the structural conditions that enabled the current state durable, or are they cyclical? Second: who is positioned to benefit from the next phase, and does that differ materially from who benefited in the current phase? Third: what would a clean falsification of the optimistic thesis look like, and is there any evidence of that signal emerging? These questions don’t need answers today, but having asked them changes what you notice in the months ahead.

The next step, for most people reading this, is a small one. The current moment in the higher education affordability crisis is one where the people who have built an accurate model of the underlying dynamics are better positioned than the people who are relying on the surface story. Building that model isn’t a quick task, but it’s a doable one, and this analysis is intended as one input into it.

What learning science finding has most changed how you study or teach?

Are You Ready for Liftoff? The New Wave of Space Travel is Here

Jeffrey Stewart My Blog Wed, Jun 25, 2025Mon, Mar 9, 2026

Hey, fellow earth-dwellers! Today, I’m blasting off (pun very much intended) into the universe of space travel. It’s an incredible time to be alive because, let’s face it, we’re watching a space renaissance that our ancestors could only dream about. Picture this: humans planning to vacation on Mars, a summer getaway involving an Earth-rise instead of a sunset, and zero gravity spa experiences in space hotels. Yeah, I know it sounds like science fiction, but it’s charging at us faster than a Falcon 9 rocket.

Hold on to your seats while I walk you through this new wave of space travel.

The State of Play: Where Are We Now?

First things first, let’s catch up to where we are today. SpaceX, Elon Musk’s brainchild, is practically a household name, dropping rockets into space as casually as I drop phones (don’t ask). With reusable rockets and reduced launch costs, they’re laying the groundwork for making space accessible to everyone, not just astronauts or billionaire moonlighters.

Then there’s Jeff Bezos’ Blue Origin, which has been making headlines with its aim to build an entire ecosystem in space. Think colonies, factories, and solar power stations, but in the ultimate off-shore location: upper Earth orbit!

NASA, the granddaddy of space exploration, isn’t sitting around either. It’s ramping up plans for lunar missions and, brace yourselves, a potential human trip to Mars. If your bags aren’t packed yet, they should be!

The Cosmic Commute: Tech Breakthroughs Driving Progress

You knew it wouldn’t just be SpaceX and Blue Origin, right? No way. This movement is packed with exciting tech!

Reusability: The New Black

Rockets usually make one-way trips, how fancy! But now, thanks to advances in reusability, we’re looking at rockets like they’re revved-up Ubers. Reusable rockets, developed by SpaceX and followed by others, drastically reduce the cost of space travel, making it more economical to “phone home.”

Advanced Propulsion Systems

Imagine if your car went from 0 to 60 faster because it adopted ion thrusters. Whaaaat? Yes, NASA and various companies are developing cutting-edge propulsion technologies that might one day power spacecraft to other planets at lightning speeds, assuming lightning traveled at a practical velocity anyway.

Life Support and Sustainability

No trip to space would be complete without a robust life support system. Cutting-edge research is happening in closed-loop life support systems, basically self-sustaining ecologies within spacecraft. These systems make it possible to think about longer hauls, like a 9-month journey to Mars. Talk about a long road trip!

New Frontier: Commercial Space Travel

Now for the juicy part! We’re entering an era where going to space isn’t just for astronauts holding glorified diplomas.

Space Tourism Takes Off

This year, we saw ordinary people becoming ‘Astronaut Tourists’. Companies like Virgin Galactic and SpaceX are offering rides to space, whether it’s a brief experience or a multi-day trip. The catch? It currently costs as much as my first home. Oh well, one can dream.

Cosmic Real Estate

There are already discussions about naming rights, land usage, and property laws for celestial bodies. Yep, folks, the next big real estate boom could be on the moon, or Mars. So if you’re looking to invest, well, space is the literal limit!

Challenges and Cosmic Curves

Of course, where there’s rocket fuel, there are also hurdles. Space travel ain’t easy, and it’s not all stardust and zero-G cocktails.

Safe or Sorry?

Certifying safety standards for non-professional astronauts is tough, sounds like they’ll need a cosmic DMV. And considering space is full of radiation, micrometeorites, and politically complex orbits, it’s not exactly a walk in the park.

Environmental Concerns

Let’s not forget good ol’ Earth. Space launches produce a carbon footprint that we’d rather shrink. Advanced research is underway to develop eco-friendly rocket fuels. Yes, you read that right! Eco-consciousness is going interplanetary!

What’s Next for Space Travel

What comes next? My crystal ball (or is that crystal space helmet?) suggests more partnerships between governments and private companies, possibly some wild card startups jumping into the mix, and further innovations that will bring us closer to being an interstellar species.

In the not-too-distant time, some of us might reminisce over our space ‘bucket list’, talking about strange creatures we met on alien lands, critters of pure imagination. Or maybe, we’ll just check out the Martian art scene.

Who knows? It’s a big universe full of surprises. Until then, let’s keep our feet on the ground while dreaming of the stars. I mean, space doesn’t have Wi-Fi yet, but it sure promises a lot more!

Now let’s stop daydreaming and make reality as epic as our wild imaginations. Here’s to the wild adventures waiting for us beyond our blue planet!

Catch you on the next cosmic wave! If you’ve got thoughts or questions about the next frontier, hit the comments. I’m always here to chat about out-of-this-world topics.