The following transcript has been edited for readability. Timestamps have been removed and minor transcription errors corrected. Speaker comments and context have been preserved.

Opening Remarks

Rich Portelance

Hi everyone, my name is Rich Portelance. I'm your host of the EdGate Powers Podcast webinar series. Today I'm excited to have Zarek Drozda from Data Science 4 Everyone. He's the executive director. This is a project that comes out of the University of Chicago. Zarek and I have worked together over the past couple of years; he is a friend of EdGate’s, and I'm absolutely positive he's going to bring some very interesting perspectives to this conversation. And also, just to remind everybody that on March 25th, we have a webinar coming up. There is going to be a link in the description area below. Please register today, it's going to be a great conversation. Along with Zarek, Peter Coe from Student Achievement Partners is going to be joining us, as well as Hillary Raldi from Whiteboard Advisors and Larry Johnson from EdGate. So, we're going to have this great panel, and we're going to be talking about Future-Ready Alignments: Redefining Curriculum for What Comes Next, and that's kind of where I want to start today with Zarek. 

So, Zarek, could you give the audience a little bit of your background, and then we'll kick in.

Zarek Drozda

Sure, and Rich, thanks again for having me on. I'm excited to dive into some of these really tricky topics with you, but also exciting ones. 

So, I’m Zarek Drozda, the executive director of Data Science 4 Everyone. DSE is a national initiative based at the University of Chicago where we advance and advocate for data literacy and data science introductory skills for students across, you know, public education. And our hope is that by the time a student graduates from high school, that they graduate data literate, that they're ready to navigate a changing world with artificial intelligence and many other emerging technologies that are, you know, both changing the economic and the workforce journeys that a student might encounter, but also are changing daily life, the way that we interact with our civics, and the way that we interact with each other in digital spaces. We know that students need a stronger toolkit in a lot of those domains, so we're hoping that we can bring that to bear.

Rich Portelance

It's a fantastic introduction, and just to lead in, I'm a big believer in what you're doing. You know, when I was back working with CareerPath for 10 years, we were trying to look at different pathways, but these basic core skills are helping define what jobs of the future look like. And jobs of today, they're changing so rapidly that students need this toolkit as you described it. 

Discussion

Rich Portelance

So, I'm curious, if I'm looking at today's classroom versus the skills students will actually need when they get into the workforce, where are the biggest gaps in your mind?

Zarek Drozda

That's a great question. You know, I think… first and foremost, it might not surprise you that we think that there's a huge gap around data skills. And when I say data skills, that really refers to an umbrella around, you know, understanding the technicals of how to manipulate data, how to work with data tables, how to make visualizations, and how to find data sets online and convert them into a format that'll be useful for an analysis that you might be doing on any topic. There's a whole set of technical skills that are incredibly valuable as of today, and I think will only get more valuable, especially as AI tools are further integrated into a variety of different job tasks, regardless of what sector you're in. 

There's also, I think, a bucket around… I would name this as a kind of detailed or quantitative definition of critical thinking. And this relates to, you know, everything around correlation and causation– is the claim that I'm looking at premised on a study that had some sort of biased data underneath when they were doing the analysis at the get-go? You know, are there outliers here that I'm looking at that are actually not part of the broader trend? And then I'm just, you know, anchoring on some anecdotes that seem attention-grabbing but might not be what's happening to most people. And, you know, you can apply– I think we often espouse critical thinking as a broad goal for education, but I think it's far too rare that we've defined that with much precision. And I also think a lot of our existing content in the curriculum is justified by kind of a vague notion of, “Oh, well, if you manipulate these integrals or derivatives enough, and you'll see the logic behind the reasoning steps to get there, you'll develop critical thinking. That's not a good enough justification, nor is that very specific. 

And so, I think there's a broader kind of reasoning toolkit that we want students to be equipped with that is relevant for a world of, you know, AI tools showing up in more places, having to navigate profound amounts of information, both true and false, both fake and real online, and to be able to question a lot of the outputs of these tools as like, an automatic muscle. That's a huge gap that we think we're beginning to see integrated in the curriculum, but it's not there enough yet. 

I think the last gap that I just pointed to, and this is more of an instructional delivery approach rather than the concepts themselves that we cover, I think we need to do a better job of motivating our existing school subjects to students, when they live in a reality in which you can Google any fact. You can ask ChatGPT for help with any skill that you're trying to build, at least in the digital knowledge domain. And, you know, really, like, we just have profound access to knowledge and skill-building opportunities all over the place. And so, that should force a conversation about how do we allocate time within our existing curriculum, and are we allocating that time in the best possible way given this profound change that we've experienced, not just in the past, like, two or three years since AI developed, but over the past 20 or 30 years since search engines came online, and since we had the internet, and since all these amazing things have reduced the barriers to access around information and skills.

So, I think we're also missing the “why” behind why we teach some of our existing school subjects in the way that we do, and I think we could do a better job at that. 

Rich Portelance

Yeah. No, thank you for that. I think, you know, you shed some good light on kind of where things are. And I'm just kind of– I'm curious, because data has always been there, and as you said, you know, for the past 25 years or so, as the Internet has come to be, and now AI and other tools, it's coming more top of mind, but it's always been there. So why do you think that it has this notion of “advanced” or “extra”, and not just core to who we are? I mean, data is critical in terms of our thinking and decision-making, and if we don't have those skills, we're kind of lost.

Zarek Drozda

Yeah. I think the reason it's not in the curriculum, in the status quo, is because of a strange quirk of how we've dealt with statistics education, and how we've restructured math education historically. So, you know, historically, especially in high school, students go through a very standard sequence of, you know, you learn K-8 mathematics to get you ready for Algebra 1. Then you do the “geometry sandwich” as it's often referred to, so, Algebra 1, Geometry, Algebra 2, on a road to Calculus. And that mathematics sequence was designed for, you know, the Space Race. It was really popularized and it was literally called the “race to calculus”. It was emphasized, you know, as a result of the Sputnik era, which made a lot of sense at the time. We needed amazing, top-tier scientists who we could cultivate through the K-12 education, you know, the public system, to be able to help us, you know, defeat the Soviets, hand calculate rocket trajectories, and do a number of other, I think, you know, at that time, cutting-edge quantitative work to advance our national goals. The downside of that approach is that it sweeps away some other forms of mathematics that fall under the broader umbrella of quantitative preparation, including statistics. 

And there's been maybe a 40, 50-year effort to try to better emphasize statistics, mathematical modeling, probability, and data in the math domain. But I think that the inertia and just sort of the existing sequence that we have for high school preparation and college preparation is just so locked in that it was hard to shift. I think the realities of tech today have made it so much more obvious that the shift needs to take place, right, that we need to be not getting rid of other forms of mathematics in the curriculum. They certainly have to still be there. But it's dial adjusting the time that we spend on the two. And, you know, as a result, when you went through school, when I went through school, data was not emphasized. I got very little exposure to data tables or spreadsheets or how digital information is organized until halfway through college, which is ridiculous in a world in which, you know, data runs all the algorithms that we interact with. 

It determines what Spotify recommends to you as your next, you know, favorite song, it determines what Netflix is recommending to you as your next favorite TV show, and it’s the fuel that helps autonomous vehicles now operate, which are increasingly seen on the streets of San Francisco, or Phoenix, or LA. And I think on the personal side, we also know data is being collected on us all the time, and we have very little insight into how it's being used by, you know, a variety of online actors. Whether that's good or bad, whether we're comfortable with it or not. And, you know, I think that creates an environment of… people don't know what they don't know, and that's kind of a scary place to be in, is… you know, I would much rather everyone have confidence and knowledge around how their personal data is being used in a variety of contexts, and then be able to make an informed and well-balanced decision around what they want to share and what they don't.

Rich Portelance

That's a great point. And there are so many different places that data comes in. 

As you bring skills into the curriculum, you're working with K-12, really, you know, and really more towards the early grades, I believe, right? K-8 is your focus primarily? What are schools and districts most surprised by as you're trying to build real data literacy into their curriculum and instruction?

Zarek Drozda

Great question. So we do full K-12 work, and I would say the majority of data science education courses have actually been at the high school level, so 11th through 12th grade. Many schools and districts are offering a data science elective as a way to continue a student's mathematics journey. You know, there are far too many students in the country, and there are several states that only require two years of mathematics in high school. And we want to see students, you know, do that third and fourth year, especially if it's in a course or a subject in which it's going to show up regardless of the career pathway they take, right? Whether they try to pursue a STEM degree at MIT (Massachusetts Institute of Technology), or whether they're going to go become an HVAC operator– which is a very high wage, high demand job these days– or they're going to go work in, you know, social studies, or media, or wherever the path is, we want to see students taking more mathematics and we think this is one way to do it because also broadens the perspective. 

I think what schools and districts are maybe most surprised by… what we know to be true in our team and what I think what we're always really glad to hear is that school administrators and also math teachers will, for the first time, see their students– both the students who have been straight A folks and who love school, and the folks who were really turned off by math– get engaged intrinsically in a math class. You know, even I will tell you as someone who got great grades in school, and a lot of my friends did pretty well, none of us enjoyed learning math. It was a dreadfully boring, abstract subject that we only did to get into, you know, university or to go to a good college. And that's unfortunately the reputation it has because we don't structure the curriculum or give teachers the support to show how compelling, important, and relevant it actually is as a subject. 

And when students work with, you know… that they're learning about exponents, or logarithms, or linear regression models, but they're seeing it in the context of data sets that they're really intrinsically excited about, like, you know, NBA scores, or they're looking at how Spotify recommendation algorithm works, or they're looking at the relationship between– this is a real example in Pennsylvania– looking at the relationship between crime and the bus schedule, and do more crimes get committed if the bus comes less frequently? There are real problems you can actually sink your teeth into and ask a lot of questions, and then suddenly, the motivation for learning mathematical functions and quantitative manipulation skills becomes really apparent and obvious. And then you see students get truly invested in the problem, learning the techniques along the way. And I think that's always been most shocking, but we hear it every time someone implements one of these programs. It's just again, and again, and again. 

Rich Portelance

It's amazing, you know, it's like the person who's a physical learner, they get their hands on something, and all of a sudden the dynamic completely changes. And you're kind of saying the same thing is, you know, by presenting things in a different way– in a way that's more practical– that people can get engaged with it, right? And learn more thoroughly and understand where it's coming from and why it's so important. 

I'm kind of curious– we have nomenclature that's out there, like future-ready skills and, you know, it's this kind of amorphous thing that people say. From your perspective, are current academic standards keeping pace with those future-ready skills, or are they already behind? And if so, what do they need to do to catch up? 

Zarek Drozda

One of the great challenges of the K-12 sector is, you know, the state standards that we all follow and help set learning targets for the field, updated on cycles of anywhere from five to 10 to 12 years. And, you know, a huge challenge is that that is the policy context that we live in. And then we have AI tools that are updating every two weeks, every month, every, you know,  sometimes multiple times in a week, you'll hear of a new model breakthrough. So, that's just a challenging juxtaposition. And then, as K-12 education leaders, you have to say, "Oh, I'm going to make a judgment call or a discernment about which skills matter most 12 years from now for today's kindergarteners." That is a wicked hard problem. Not only is the policy context constraining, but we also just don't know where the target is moving. 

So, I think yes, obviously, everything is out of date, right? And the actual interesting question, or the important problem, is okay, well, what do you do to transition? And how do you adapt the curriculum in this new environment, given an impossible moving target? And I think the approach that we've landed on is, well, what are the skills that will be durable in a world in which you assume the technology is going to change 10 or 20 more times? You know, I think it's a mistake for school leaders to try to keep up with the latest AI model development. That's not a good use of their time. But what we should be thinking about is what's the specific critical thinking framework that will be durable, last, and help students adapt to new technology? Is there a basket of technical skills that we can say, you know, this is a strong base that will not only allow you to do well today, but will allow you to adapt over time to new tools as they come out? And then, you know, what's foundational knowledge that you need no matter what happens? You know, I don't think we're getting rid of basic instruction in writing and literacy anytime soon. I think students still need a pretty robust survey of the knowledge that we've generated across physics, biology, and chemistry to understand how the world works at a mechanistic level. Students still need to be learning history. None of those things go away, and I worry about the folks who try to push that hard of a change. I think that foundational knowledge is still critical. I think it's really how we can find ways to adjust the way that we interact with the foundational knowledge that we want to teach, as well as the kind of new set of skills that will get us there. 

So yes, it's out of date, we know that. I think the big challenge is, like, what is the way in which we do the updates? And how can we take a long-term view of the future to make some bets that we think will last?

Rich Portelance

Yeah. I would agree with you and I'm going to just pile on to the list that you just presented because I believe in durable skills, I think that's the right model that schools need to also appreciate the arts for what they bring about, because there's a critical thinking component and a creative thinking component that also is adaptable to just about anything that we do, and the arts brings that out like nothing else. So I would just– I don't know if you would agree with that, but to me, it's someplace where I see some cost-cutting measures, and it just frightens me, because you take away that creative thinking process, and you limit the students’ ability.

Zarek Drozda

Yeah. Just because I'm a data scientist doesn't mean I'm anti-art!

Rich Portelance

Oh, I wasn’t suggesting that at all!

Zarek Drozda

Yeah, and, you know, there are a number of emerging frameworks that are in the category of durable skills, and under that are things like communication, collaboration, and analytical problem solving. Creativity is one that is in that basket, and I think is critical to keep in the curriculum. You know, I defer to the art teacher and how to, you know, and the artists who are in the education community for how to build those details out and continue to do so. I think from a standards level, I don't know if states have figured out what the constituent parts are yet.  Because that translation has not been done, right? It’s like, what are the constituent… really, like, deep kind of underlying mechanisms that we would count as creativity? And is there a way to assess that in some way from a state policy perspective? That is a really tricky question. 

Rich Portelance

That is a tricky question. 

So, in that paradigm of durable skills, are you seeing some encouraging movement at a state level? Are things going in a good direction in some states, at least?

Zarek Drozda

I think several states, if not the majority, have forwarded portraits of a graduate, right? Which tries to capture a more holistic set of durable skills that I think will be relevant for the age of AI that we're headed into, and do try to shift the curriculum directionally towards a world in which we are emphasizing communication, collaboration, analytical thinking, you know, making decisions with data, thinking probabilistically, applying, you know, grit and persistence when problem solving. I think we often take those for granted in the curriculum, and we don't view them as explicit topics to teach, but that's what employers have been asking the public education system for decades. So it's also not new, I think it's just been revealed further by how technology has changed.

I think the challenge– and I don't know if any state has really figured this out yet– is how to take their portraits of a graduate, and implement them in a meaningful way that drives and gives permission for change in the classroom at the teacher level. You know, locally, across many diverse schools and districts. And I think where the rub is… is, you know we haven't found a good way to pair the existing academic curriculum we have, that, again, I think is still incredibly valuable, and still needs to be the base of what students experience in school, with this new set of holistic, durable skills, in addition to things like financial literacy, civics and some of the other… like the “soup” that is being asked to be added to the curriculum. Those two things often are like two ships passing in the night, and I don't think the work has been done to translate the two or synthesize in the end. 

And I think in some ways, we're in the early innings of our team figuring out how to do that. Just with the narrow lens of, you know, taking the math curriculum as is and looking at the new skills around data science, AI, computational thinking, and trying to bridge those two. We're like a microcosm of, I think, the broader work that needs to be done to pair our existing academics with some of the new emerging durable skills that folks are looking to prioritize.

Rich Portelance

So, obviously, your job has become exponentially more difficult with the states– with Common Core breaking up, and now 50 states having 50 sets of standards. One theme that we're exploring here at EdGate is alignment as infrastructure. Essentially saying, you know, it has to be a core part of your business if you're in the publishing space, not just something that you do every once in a while, because things are changing so quickly. Standards, curriculum, instruction, skills, etc. Why has alignment become such a critical issue right now for data science, and what you do?

Zarek Drozda

Yeah, certainly, I think, well, the first thing I'd say is that we've built out a network of, you know, university-based research teams who have built curriculum and high-quality instructional materials for data science and data literacy at a K-12 level. And that has been created and built up at the same time as we've been working with now, you know, 35 states around the country on pilot programs for K-12 data science, launching professional development opportunities for teachers at a statewide level, or working on updating their mathematics standards. And I should also say, like, we have a really tight relationship with mathematics for, I think, obvious reasons, but we're also exploring and continue to look at the connections between science, social studies, and computer science. And I think there's even some possibility around communication of technical ideas with ELA, and thinking about how to tell better stories and clear, accurate arguments with data in English classrooms, especially in high school. So, you know, we've been, I think, at the forefront of helping states think about how to modernize their standards in math, and then increasingly in those other subjects. 

I think it's… you know, a lot of the university-based small course teams or supplemental materials that we have been helping kind of steward and help grow as a community are at the cutting edge of how to think about instructional delivery around all those new skills. Your existing publishers, I think, are now trapped by a really complicated landscape of not only do they have 50 states that are diverse, but all those 50 states are changing, and they're changing in slightly different ways as they, you know, determine locally how to grapple with the massive changes that our education system is undergoing. So I think, you know, clearly alignment is going to be expensive, and it's going to be a time-intensive task for larger education curriculum developers. 

I also think, and I'm concerned that the broader stakeholders in education publishing are not tracking or forecasting how quickly or large these changes are about to be. And, you know, I'm hoping, like– we put out research every year that shows the spread of data science and data literacy programs, and all the states that have updated their standards to help dial adjust the math curriculum. That will start to happen to all the other school subjects as well, and it's going to start to come pretty fast, I think, in the next, you know, three, five years? And I do want to elevate, you know… folks should be paying attention as these changes start to emerge.

Rich Portelance

Yeah, I agree. I think, you know, we see these changes, and it's like this buildup before the storm, and you're going to see the sweeping change. 

I'm curious, you know, about good data, and you would prioritize– and metadata in particular, it can change the way alignment decisions get made. How do you… Can you react to that kind of statement? How can good data change the way those decisions are made?

Zarek Drozda

Well, I mean, I certainly believe that at our core as an organization, and, you know, around the skills that we think students need to build. 

I think– the other thing I would say is, you know, especially thinking about, like, your average publisher, or your average curriculum materials producer/designer, you know, we have… the folks we have worked with, to date, I think we've seen, you know, a lot of excitement for the fact that the standards are getting updated, and they are getting modernized. And because, I think, oftentimes we've heard, like, curriculum authors are kind of constrained by some of the outdated requirements around learning goals that students are are you expected to progress through, and the changes that we are helping to hopefully integrate into the system are leading to a lot more creative opportunities for curriculum developers, designers, and edtech providers to think much more holistically about what the student learning experience can look like. And, you know, I think as the system grapples with those changes, it'll be really important to track them at a much higher grade size than we're used to doing. 

So, I think that would be my, you know, kind of circle back to the metadata question of… as we're getting to the world of formative assessments and open-ended tasks and… you know, we're thinking about what does creativity, collaboration, or communication look like? And across school subjects, at least from the durable skills movement, as our own team is thinking about what high-quality, project-based data analysis activities look like that bring in really rigorous and challenging statistical and mathematical techniques to solve problems. The curriculum arc for a student has the opportunity to be a lot more exciting, and therefore diverse, which will need, I think, a much higher kind of infrastructure to track those changes.

Rich Portelance

Okay, thank you for that. You know, we talk about metadata– and EdGate, they obviously are busy building– when standards come in, they attach their concepts to the new standard, and then build metadata into it. So there can be more rapid alignment; there can be, you know, understanding cross-platform as things change, and from one state to another, and states don't all– like you were talking about earlier– they don't do all this at once; everybody's on different time schedules. And so, you know, there's a real advantage to being able to understand gap analysis and correlation from one state to the next in a more rapid fashion, so you can embed those new skills as different standards change at different times. So there's a whole world there that you dove into headfirst with Data Science 4 Everyone and with your partners as well, and I know you have some excellent partners, who I would ask you at some point just mention, because I think it's important you're backed by some high-powered folks throughout the country who want to see this happen because it's so critical.

Just to get into the curriculum a little bit deeper, you've been very clear that data science isn't just a math issue, and we've established that. How should education leaders be thinking about it across subjects? If you had to give them some, you know, thought bubble here.

Zarek Drozda

I think… kind of the data science movement, but also just the opportunity to teach about data provides a really fantastic zone of exchange, or sort of glue between our existing school subjects, because now a student can learn the methods of data analysis and statistical modeling in a math class. They can then bring those methods to study, you know, ecosystems, or the spread of genes in a biology class, they can look at historical phenomena and track economic booms and busts over time in a history course; and they can look at the spread of the plague over time in quantitative data sets as a project in social studies. And it allows, I think, not only do you see the value of the subjects blending, but it actually is the… like, activities with data sets on the topic that you already have to cover as a teacher. This allows you to do the blurring of the school subjects that so many folks have been opining for a while. You know, “How can we get rid of the silos between our school subjects?” “How can we make things more interdisciplinary?” But it's really hard to actually do that concretely in practice. And I think this is– I don't want to call it easy, but it's much more approachable. And the way you could design lessons, it's almost built in, and so, like, we're really excited about that.

I think the other thing is it would be a shame if we only make this, you know, a methods-based set of instruction that only shows up in the math curriculum, that you don't get to explore those extensions in social studies, that you go don't get to make your typical lab exercises in biology really come to life, and then potentially interact with data that researchers have collated on any number of topics in the broader world. You can really go beyond just the four walls of the classroom and the lab kit that's in front of you. You can look at real data coming from, you know, the Human Genome Project (HGP) in your biology classroom. So I think the frontier is really exciting.

Rich Portelance

That is exciting, the way you laid it out. I mean, it really can go across subjects and be embedded in so many different places. And you and Data Science 4 Everyone, you know, kind of is coming into this ecosystem that's already existed and crashing a party, in a sense, where you have the educators, you have the publishers, and you have the alignment groups, and, you know, they're all interacting, and here you come with this new perspective and trying to say, “Hey, do this!” 

What role do you believe that the publishers and edtech providers should be taking in terms of embedding data skills more intentionally?

Zarek Drozda

Well, you know, I love crashing parties when feasible… and then I guess when invited. 

You know, I think we do think a lot about what the system levers are that we have to pull to make sure that students are getting modern skills that matter. I think that that's our big picture mission, that's what I spend a lot of my time thinking about. The last thing we want to do as a team is reinvent the wheel, and so we thought really intentionally about how do we work with existing partners in the space who've been doing this for years and decades? You know, I think this includes working with the state education agencies on standards. This includes working with, you know, folks who help shepherd those transitions, you know, like EdGate. This includes working with the existing publishers. 

I think the advice I'd have is, there is… we've pulled together a whole community of, you know, folks who've been working and thinking about the future of what these subjects should look like. You know, they’re university faculty in college education, they're folks who have built NSF (National Science Foundation)-funded curriculum and technology projects that are really cutting edge. And we have a really great network of content and subject matter experts who are, I think, you know, standing ready to help any publisher or a larger education company think about how to offer these experiences authentically, because the hardest thing for a publisher or a larger company that has an existing edtech platform will be to create a student experience that feels authentic to the way that data analysis is done today in the real world. You know, something that feels overly sandboxed and prevents connections to the Internet, where you can find any data set online on any topic, that's not going to cut it. We have to find ways that are, you know, still safe and compliant with IT policies at districts, but allow students to do, you know, the broader research tasks or looking at data on the Internet. You know, we'll have to bring in tools that mimic what's used in industry. You know, that goes from things as simple as spreadsheets, it also goes up to Python or, you know, R, or any of the more popular data analysis programs. 

And I think it comes down to topics. Students are all the more sensitive to something that feels out of date today. You know, we can't be giving them datasets or just lesson plan topics on, you know, when are two trains going to meet each other at a depot? Or we can't be showing them consumer product trends from the year 2000. We have to try to make those things up-to-date, current, and feel like they matter today, not that they mattered to, you know, a textbook author 20 years ago. Because we're just going to lose them otherwise.

Rich Portelance

So, you know, talking about some of those standards, and we're seeing standards, whether they're academic or CTE– for sure– change faster than ever. And we know what's driving that acceleration; we've talked about it. How prepared are education organizations for the pace of change? And from your perspective, because you've been working with them?

Zarek Drozda

It's a good question, and I know from my perspective, the whole education sector is still grappling with the massive changes in technology that we are experiencing. And I don't just mean AI, I really do mean the Internet, search engines, and the history of personal computing. I don't think we've reconciled with that much broader change. The fact that, you know, again, knowledge is free, opportunities to find skill-building are incredibly low cost, and, you know, we should be preparing young adults for that world, and how to harness it well. So that's a much larger change I'm worried about. 

I think within the education sector, I don't know if really the more transformative changes have happened yet at a state standards level, I think those are still coming. And I also want to name, like, I think the system, we still have the overhang of COVID and the pandemic-induced learning loss that we, you know, experienced as a sector. There are now pretty significant disruptions and changes coming to federal education funding that have also just introduced a lot of uncertainty for leaders. And then finally, you have, you know, I think young people who are clearly dealing with a variety of social and mental health challenges as a result of the time that they spend in their personal lives online. So there's a lot of really big issues in front of education leaders right now, and I don't know if we have had the time or space to address this long-term, but also equally urgent issue of, you know, how are we retooling the curriculum for the fact that the world is changing kind of beneath our feet. 

And so, I do think that, you know, the well-resourced education organization, publisher, or edtech company should be thinking about not just investing in how do I use AI to improve my existing edtech tool, or put an AI engine under something. I think everyone's doing that, and it's, you know, great that we're exploring those productivity gains. I think not nearly enough people, because of the many resource constraints, are thinking about that long-term question of, you know, we might be in the middle of a broader industrial revolution that's occurring right now, and we haven't spent enough time or resources to think about how do we retool all of our learning targets for that world. 

Rich Portelance

Just to remind everybody, on March 25th, Zarek is going to join us on our upcoming webinar. We've covered a lot of topics today. There's a lot more to discuss, as Zarek has rightfully pointed out. And perhaps we can even induce him to do a round two, because there's so, so much that we can dive into when it comes to standards, when it comes to preparing students for the world of the future, and embedding data science into a very fragmented world of academic curriculum. 

Zarek, I know we only have a couple of minutes left, you know, what risk do you see if alignments and review processes stay manual and fragmented over time? Because it still exists out there, and it's still quite onerous.

Zarek Drozda

Great question. 

I worry first and foremost that our existing, you know, review processes, the way that we stamp and approve high-quality instructional materials, and other, you know, validation kinds of mechanisms that we have in the education policy system right now, are currently not equipped to do holistic reviews of any digital curriculum. Anything that involves online connectivity, you know, things that are… things that will necessarily allow students to explore under guidelines, supervision, and some safety protocols. You know, the current AI tools are the current and best ways that you can easily access data online and do an analysis on any subject under the sun. Or just using, you know, again, the vast power of Google and Bing that we've had access to for the past 20 years, and is basically everywhere except the core curriculum in K-12. And I think we need to be thinking about our instructional materials in that context. 

I also– the other thing that I want to name is that I think the existing infrastructure around curriculum review and standards review is, either rightfully or wrongfully, definitely an impediment to innovation, because we know a lot of, you know, NSF-funded, university-based, really just like high-quality curriculum projects, and student software tools have been developed that are K-12 appropriate, age appropriate, and are meant to slot into a typical school semester, that aren't able to go through those traditional review processes, simply because they're too new, or they haven't assembled the long checklist of all the wraparound resources that they need. And because the old requirements simply just don't mesh very well with the digital landscape that we now find ourselves in. And so, I do think that there needs to be, you know, significant updates there that balance innovation, and making sure we don't move too fast.

Closing Thoughts

Rich Portelance

You're joining us for the upcoming webinar on future-ready alignments. What are you most looking forward to unpacking during that conversation?

Zarek Drozda

You know, our team spent a lot of time with both SAP (Student Achievement Partners) and Whiteboard Advisors. So, from my view, it will just be another hangout! But I'm excited to, you know, try to dig into any topic that you can push our thinking on. So I'm looking forward to it, and thanks again for the opportunity to speak here, and also to join your upcoming webinar.

Rich Portelance

You know, it's so much fun to provide these thought sessions. That's the way I look at it. It's, you know, knowledge for everyone, and having guests like yourself really gets– we get to unlock some really cool information for the audience, so thank you for your time. 

You know, in closing and looking a few years out, what makes you optimistic about where education is headed, Zarek? 

Zarek Drozda

I think we're in a profound, you know, window of change for education more broadly. And it started with the pandemic. It's continuing now with technology and the massive improvements we've seen in artificial intelligence and all the things before. And I think there is a– there's both an opportunity and a risk. You know, I think that the digital divide is still a real concern of mine. I think that exists both within the U.S.; it exists within towns and cities, and it also exists globally, right? That there's massive differences between Internet infrastructure, what folks can self-teach, you know, in the U.S. versus a developing country. There is an opportunity here to really create a truly equal-opportunity, level playing field with technology, and with all the amazing tools we now have emerging. There's also a huge opportunity to get that wrong, and I think we have to do everything we can to thoughtfully design our policy over the next few years to make the most of this window that we have.

Rich Portelance

Well, I agree, and I really thank you for your time today, Zarek. This was a great conversation. I'm looking forward to the webinar. We're going to wrap it up, and I'm going to ask you the final question, which is the most serious one.

Where can people follow your work, and learn more about Data Science 4 Everyone?

Zarek Drozda

Of course, they can. So, they can always go to datascience4everyone.org. We have a monthly newsletter where folks can sign up for updates. We're pretty intentional about making it monthly; we don't want to spam your inboxes. There is too much data information flowing to people all the time these days, so we try to be limited and focused in our outreach. We also have a great Slack community. It's about 1500 members strong and it continues to grow every week. Lots of engaged folks on there if you really want to be in the know for the most latest updates in the data education world. 

Thanks so much for having me on. It was a great conversation.

Rich Portelance

All right. Thank you. We'll talk to you again soon.