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Marc Seter’s Journey: Balancing Life, Learning, and a 90-Minute Swim

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Marc Seter’s Journey: Balancing Life, Learning, and a 90-Minute Swim

Many adult learners juggle full-time work, family, and personal commitments while earning their degrees. For seasoned civil engineer, Marc Seter, this balancing act isn’t just a challenge—it’s a skill he’s mastered. Between working full-time, caring for family, and pursuing his Master’s in Computer Science degree from CU Boulder, he’s found creative ways to make learning fit into his life. One of his most unique study strategies? Incorporating coursework into his daily swim routine. 

As someone who regularly works 60 hours a week, enjoys a range of hobbies, and is active in a plethora of familial commitments, Marc celebrates the flexibility of this program. His journey isn’t just about earning a degree; it’s about staying curious, continuously growing, and proving that with the right mindset, learning never has to stop.

Diving into his studies

Each day, Marc spends 90 minutes in the pool, but instead of just counting laps, he listens to audio lectures or has Siri read his textbook aloud to him. It’s his way of making the most of every moment.

“If there’s ever readings from a textbook, I’ll buy 2 copies. I’ll take one of them, remove the spine with my miter saw, and run the whole textbook through my scanner and OCR (Optical Character Recognition) it. Then turn that into text that Siri can read to me while I’m in the swimming pool.”

Moreover, once Marc realized that not all of the readings in his textbook are easily understood by Siri, he took it a step further and taught her how to interpret the Greek alphabet as well as a many of the mathematical symbols. 

“And so I went ahead and found a way to teach Siri the Greek alphabet. I taught Siri to speak my textbook to me while I swim,” he shared with a laugh. “That’s my study time. And I feel like I’m rocking and rolling on my curriculum now.”

For Marc, learning doesn’t happen in isolation—it’s woven into his routine, and his core values, proving that with the right approach, even the busiest schedules can accommodate continued education.

Why Flexibility Matters

Marc’s schedule is packed—not just with his career and other hobbies, but with family responsibilities, too. As a caretaker for his wife, two children, and in-laws, he notes that emergencies can often happen unexpectedly. Being able to hit pause on school when needed has been critical for managing the balancing act of his busy life. 

“There are times when everything’s going great, and I’m moving really fast. And then there are other times when, for whatever reason, I need to slow down a little bit. That for me is just absolutely huge,” he explained.

The program’s flexibility allows him to adjust his pace depending on what life throws at him, whether that means working ahead when things are calm or stepping back when his family needs him.

From Learning to Application

For Marc, learning doesn’t happen just for the sake of learning—he applies what he picks up immediately. At work, he’s used dynamic programming techniques he learned in class to optimize an algorithm called an auto reconciler, which helps match financial transactions more efficiently.

“I applied some dynamic programming techniques to accelerate one of the algorithms we have,” he explained. “That was a direct takeaway from my coursework.”

For Marc, this is the biggest win—not just earning a degree, but gaining skills that make a real difference in his job.

Loving the Learning Process

Marc has been thoroughly enjoying the curriculum and is not in a rush to graduate. In fact, he’s struggling to choose which specialization to focus on because he finds value and takes an interest in each one.

“I want to take them all,” he admitted. “I’m thinking about the wilder approach—taking every credit except one to graduate, just so I can fit in all the specializations. But, practically speaking, I feel like I can finish the program, get the Master’s degree, and continue to take classes through the other various specializations.”

His interests are broad, ranging from quantum computing to robotics to artificial intelligence ethics. The rapid advancements in AI excite him, and he sees a growing need for professionals who understand both the technology and its ethical implications.

“The market for AI is only growing, and that’s a skill set that’s going to be in high demand,” he said.

The Value of Mistakes (and a Good Joke)

Marc also appreciates how the program allows him to make mistakes and learn from them. Unlike traditional assessments where a wrong answer is just a mark against your grade, this program turns errors into teaching moments.

“One of the things that I really love is the quizzes and the assignments. I feel like I learn more when I make a mistake than when I just get it right the first time,” he said. “I’ve even been tempted to go through some of those and answer with all of the wrong answers because the feedback that the professor provides is extremely useful”

What makes the process even better? His professor’s sense of humor.

“The professor’s got a great sense of humor and will often include jokes in the feedback with the wrong answers. I really appreciate that—it makes it a lot of fun.”

Looking Ahead

Despite juggling so much, Marc is thriving. His ability to blend education into his everyday life—whether in the pool, at work, or in moments of downtime—keeps him on track without feeling overwhelmed.

His story truly speaks to what’s possible with online education. The ability to study on his own terms, apply new skills immediately, and learn in unconventional ways proves that higher education doesn’t have to be rigid—it can adapt to fit your life.

When Was the Last Time You Read a Whole Book?

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When Was the Last Time You Read a Whole Book?

Do you like to read? Do you ever read for fun on your own? If so, what are your favorite kinds of books? If not, do you remember a time when you enjoyed reading?

Now think about the reading you do for school. Do your teachers tend to assign whole books, or just excerpts from novels or nonfiction works? When was the last time you remember reading a whole book for school that you enjoyed or learned from?

In a recent essay for the Opinion section, Tim Donahue, who has taught high school English for decades, pleads: “Let Students Finish the Whole Book. It Could Change Their Lives.” Here is how he begins:

In her memoir, Dorothy Allison writes, “Two or three things I know for sure and one of them is that telling the story all the way through is an act of love.”

Throughout my teaching career at independent schools, which began during the Clinton administration, I’ve also been telling students that reading a story all the way through is an act of love. It takes stillness and receptivity to realize this, it takes a willingness to enter the life of someone you’ll never meet, and it requires great practice.

It’s easy to join the hand-wringing chorus, blaming TikTok’s corn drill challenge, Jake Paul and their ilk for the diminuendo of Dickens. But we cannot let reading become another bygone practice. In their more than eight hours of screen time a day, on average, students navigate a galaxy of mediated experiences; schools need to be a bastion of the analog experience of the physical book.

The study of English involves more than reading. It includes written expression and the cultivation of an authentic voice. But the comprehension of literature, on which the study of English is based, is rooted in the pleasure of reading. Sometimes there will be a beam of light that falls on a room of students collectively leaning into a story, with only the scuffing sounds of pages, and it’s as though all our heartbeats have slowed. But we have introduced so many antagonists to scrape against this stillness that reading seems to be impractical.

The test scores released at the end of last month by the National Assessment of Educational Progress reveal disturbing trend lines for the future of literacy in our country. Thirty-three percent of eighth graders scored “below basic” on reading skills, meaning they were unable to determine the main idea of a text or identify differing sides of an argument. This was the worst result in the exam’s 32-year history. To make matters worse, or perhaps to explain how we got here, the assessment reported that in 2023 only 14 percent of students said they read for fun almost every day, a drop of 13 percentage points since 2012.

Later in the essay, Mr. Donohue describes today’s English classrooms and how they have changed from the past, when teachers assigned full books more frequently. He writes:

What might have been a full read of “The Great Gatsby” is replaced by students reading the first three chapters, then listening to a TED Talk on the American dream, reading a Claude McKay poem, dressing up like flappers and then writing and delivering a PowerPoint presentation on the Prohibition. They’ll experience Chapters 4 through 8 only through plot summaries and return to their texts for the final chapter.

Going mostly by summary and assumption, students get thumbnail versions of things. They see the Cartesian grid, the lines on a map that chart the ocean, but they “don’t see the waves,” as the media theorist Douglas Rushkoff recently said about the reality in which many seem to be living in now. They see “the metrics that can be measured rather than the reality that those metrics are simply trying to approximate.” He is not an alarmist, but he is alarmed about losing the “in-between, this connective reality.”

Students, read the entire article and then tell us:

  • According to a survey linked in this article, only 14 percent of students said they read for fun almost every day. Are you part of that 14 percent? If so, what do you read? If not, did you ever read for fun? What inspired you then, and how has that changed?

  • Do you agree with Mr. Donahue that there is value in reading whole books and fully “entering the life of someone you’ll never meet”? If so, have you ever had an experience like that with a book, whether in childhood or recently?

  • If you don’t think there is value in reading whole books, what experiences, for you, bring meaning? For instance, do you think digital interactions, like scrolling social media or playing video games, can be just as meaningful?

  • Do your teachers tend to assign whole works, or do they do as this writer describes and assign only pieces of a text?

  • In general, how have you felt about the reading you’ve been assigned in school? Have those works been relevant to you and your life? What books have you especially enjoyed? What books have you not enjoyed?

  • Have you had any memorable experiences discussing a work of literature in class? In the essay, Mr. Donahue describes a classroom conversation about a work of fiction and says that discussions like that can become a part of forming a teenager’s identity. Have you ever read and discussed a book in school that somehow became a part of who you are or changed how you think?

  • If you could recommend a book everyone your age should read for fun, what would it be? Why?

  • If you could recommend a book that every high school English teacher should teach, what would it be? Why?

Students 13 and older in the United States and Britain, and 16 and older elsewhere, are invited to comment. All comments are moderated by the Learning Network staff, but please keep in mind that once your comment is accepted, it will be made public and may appear in print.

Find more Student Opinion questions here. Teachers, check out this guide to learn how you can incorporate these prompts into your classroom.

A Helping Hand

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A Helping Hand

Use your imagination to write the opening of a short story or poem inspired by this illustration, or describe a memory from your own life that this image makes you think of.

Tell us in the comments, and then read the related article to learn more.

Students 13 and older in the United States and Britain, and 16 and older elsewhere, are invited to comment. All comments are moderated by the Learning Network staff, but please keep in mind that once your comment is accepted, it will be made public and may appear in print.

Find more Picture Prompts here.

Word of the Day: laconic

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Word of the Day: laconic

The word laconic has appeared in 31 articles on NYTimes.com in the past year, including on Jan. 16 in the obituary “David Lynch, Maker of Florid and Unnerving Films, Dies at 78” by J. Hoberman. The article includes a description of Mr. Lynch’s way of speaking:

Distrustful of language, viewing it as a limitation or even a hindrance to his art, he often spoke in platitudes. Like those of Andy Warhol, Mr. Lynch’s interviews, at once laconic and gee-whiz, were blandly withholding.

Can you correctly use the word laconic in a sentence?

Based on the definition and example provided, write a sentence using today’s Word of the Day and share it as a comment on this article. It is most important that your sentence makes sense and demonstrates that you understand the word’s definition, but we also encourage you to be creative and have fun.

If you want a better idea of how laconic can be used in a sentence, read these usage examples on Vocabulary.com. You can also visit this guide to learn how to use IPA symbols to show how different words are pronounced.

If you enjoy this daily challenge, try our vocabulary quizzes.

Students ages 13 and older in the United States and the United Kingdom, and 16 and older elsewhere, can comment. All comments are moderated by the Learning Network staff.

The Word of the Day is provided by Vocabulary.com. Learn more and see usage examples across a range of subjects in the Vocabulary.com Dictionary. See every Word of the Day in this column.

The Pitfalls of Relying on Client Feedback in LMS Development

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The Pitfalls of Relying on Client Feedback in LMS Development

Here is a funny story – tell me if you have heard it before.

Two Learning Systems vendors, an LXP and an LMS, walk into a conference.

Each of them has a lot of fans, and each is trying to land new clients.

They show their respective systems and discuss the benefits and what makes them different.

The potential client sits back in awe – this company is just like me.

They get me.

I get them.

Too bad somebody beat you to the punch.

Their other clients

Some are big, okay, and some aren’t; thus, those two systems aren’t so different.

Pretty funny, huh?

The Above Scenario

I would love to tell you that it is a very unfunny joke that doesn’t exist.

Sadly, though, it does – way too often.

The Numbers

I’m going to get right to the numbers.

Numbers speak louder than words, which is why I am writing this post.

Ha, I made a funny – move over Peanuts.

A few unpersonal favorites I’ve heard from vendors on the percentage of their system roadmap being driven by their client base

  • 75%
  • 90%
  • 65%
  • 50%
  • 35%
  • 55%
  • 82% (I always wanted to know how they could figure out the extra two percentage points)

Who are the clients providing that are driving the product development and roadmap?

Please be aware that not every vendor uses or identifies with the list below, but there are vendors who do.

  • Clients who use the system the most
  • Large Enterprise clients
  • Clients with over 25,000 users
  • A few big-name clients (I can say that one of them – has this power in not one but a few systems -and it isn’t who you think – although I am aware of those you do believe. Oh, and that power? Each vendor has gone down a rabbit hole due to that client)
  • Select 50 clients – Well-known, F500.
  • Clients who use the system the most
  • Large Enterprise clients
  • Clients with over 25,000 users
  • A few big-name clients (I can say that one of them – has this power in not one but a few systems -and it isn’t who you think.  Oh, and that power? Each vendor has gone down a rabbit hole due to that client)
  • Select 50 clients – Well-known, F500.
  • Focus Groups—Plenty of data backs up their effectiveness, specifically their lack thereof.
  • Eilict feedback from everyone: There is information out there showing why this is a bad idea, too.

Why in earth’s name would you want a vendor to rely on so and so, big names, or client feedback of more than 10% (percent) on the development of the system?

Most vendors in this industry have a product management team or, at minimum, a product development team.

Each group always has one person at the top of the food chain.

Plenty of vendors have someone called CPO. R2D2 went on strike.

CPO – Chief Product Officer.

These people are not being paid to offset their brains and expertise with only client feedback.

If they are, use AI.

It is a lot cheaper and probably knows how to follow steps to create at least a basic system—ditto for that product management team.

What is the percentage?

No more than ten percent. That is it.

Ten percent.

Ideally, it should be about two to three percent, but if a vendor doesn’t exceed ten percent – not just from the best or widely used clients, then it is acceptable.

Numbers Game 2.0

Vendor A has 335 clients.

Everyone’s feedback is essential. It is something the vendor pushes in their pitch.

This should be 100%

The vendor, though, really listens to 40

Reality – 8.37%

That’s it.

8.37% of their clients are the power brokers for the system you buy and will use.

Would you still want to purchase the system if you knew that amount?

75% to 90%

Yuck.

My mouth dropped when I heard those numbers.

The assumption here, and I can only surmise this, is that those folks—the clients—know more about the current trends, where the industry is heading, and everything in a system.

Vendors say that the feedback—use cases—helps them, and the vendor develops a system to meet those use cases better.

Because the folks contacting them use the system, and therefore blah blah blah.

Who contacts a vendor?

Let me rephrase this.

When you contact a vendor, is it for a plus reason or a problem?

My gut says the latter.

How does a vendor get that feedback that drives product development?

The 8.37%?

Studies have shown higher levels of honesty when someone can respond anonymously.

90%

Why are you in business?

If some PE firm gave the vendor money, are they aware that you are giving others the driver’s seat and that you, as the vendor, are just along for the ride?

Being Clear

Yes, you have read this post.

Yes, you are aware that as an analyst, even a fellow person like yourselves – back in the day of buying a system, would find this information disturbing at best.

It is disingenuous at its worst.

The idea that a tiny percentile of X clients leads the charge is cringeworthy.

Bottom Line

8.37%

You can thank them

Assuming the vendor will share that information with you

Then, send those clients a gift, such as a bouquet.

Then request a refund and go to an entity whose system achieves what you want,

At a fraction of the cost

My dear friend,

AI:

Our Learning Management System (LMS) is designed to be a learner-driven, easy-to-use platform that supports upskilling and continuous professional development. It combines personalized learning paths, AI-driven recommendations, and an intuitive interface to enhance engagement and skill acquisition.

Key Features & Approach

  • User-Centric Design: Simple, intuitive interface requiring minimal onboarding.
  • Adaptive Learning Paths: AI-driven recommendations tailor courses based on user progress and career goals.
  • Upskilling & Reskilling Focus: Extensive library of microlearning modules, certifications, and industry-relevant courses.
  • Gamification & Engagement Tools: Interactive elements like quizzes, leaderboards, and social learning for motivation.
  • Seamless Integration: Works with existing enterprise systems (HR, CRM) and third-party learning content.
  • Analytics & Performance Tracking: Real-time insights into learner progress, skill gaps, and engagement trends.

E-Learning 24/7

7 Popular Jobs in AI and Machine Learning

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7 Popular Jobs in AI and Machine Learning

These days, it feels like everyone is talking about generative AI — AI agents, AI apps, AI-generated images — even AI-enabled refrigerators! Nearly every aspect of our daily lives is being revolutionized by by this new technology, from how we work to how we shop and even how we relax.

Even though we’re just scratching the surface of possibilities when it comes to the power of generative AI and machine learning, it’s already shaping our everyday lives and the decisions we make. Major companies like Google, Amazon, Netflix, and Tesla are actively using generative AI and machine learning to deliver personalized results to millions of users, understand and interpret human conversation, train neural networks to predict what a human driver would do, and so much more.

Learn something new for free

It’s no wonder that, according to the 2024 Skillsoft IT Skills & Salary Report, professionals with skills in machine learning and AI are among the most in-demand with a whopping 47% percent of organizations saying that AI and machine learning is their top priority this year.

This significant demand, as well as the opportunities to develop new and exciting technology, has attracted many professionals to the industry. While there are the obvious titles — like AI Engineer or Machine Learning Engineer — there are also other positions you can explore that use generative AI machine learning but might not be as obvious.

Here are seven popular jobs that use generative AI and machine learning, along with information on how to get started in each role.

1. Machine Learning Engineer

Machine Learning Engineer is one of the most popular positions in the machine learning industry, and you’re likely to find many roles with this exact title during your job search. These engineers design and implement machine learning models, expand and optimize data pipelines and data delivery, and assemble large, complex data sets. Models developed by Machine Learning Engineers are used to reveal trends and predictions that can help companies meet business objectives and goals.

Machine Learning Engineers build the recommender systems that power many digital platforms. From your favorite new artist on Spotify to your next Netflix binge, many of the relevant content and products put in front of us online are thanks to recommender systems that learn our preferences. Recommender systems are powerful technologies that many of us interact with every day, and you can learn how to build them in our beginner-friendly Build a Recommender System skill path. (Or you can try our free course Learn Recommender Systems if you’ve already mastered the basics of Python and machine learning.)

On average, Machine Learning Engineers in the U.S. make $135,499 a year. Learn more about what Machine Learning Engineers do and how to land your dream job as a Machine Learning Engineer.

2. AI Engineer

Artificial Intelligence (AI) Engineer is another one of the most popular positions where generative AI and machine learning can be used. Since machine learning is a subset of AI, there are many AI Engineers with expertise in machine learning tools and applications.

You might develop and modify machine learning models, apply machine learning techniques for image recognition, and develop neural network applications using popular frameworks like TensorFlow and PyTorch as an AI Engineer with a machine learning specialty.

If a career in AI is in your future, skills like Python, R, and Java are common for this role, as well as linear algebra and ​​statistics. U.S.-based A.I. Engineers earn an average salary of over $106,000 a year.

3. AI Architect

An AI Architect is a professional who designs and oversees the implementation of AI systems within an organization, which is understandably becoming a more and more common role that every company needs. Their primary responsibility is to ensure that AI technologies are integrated seamlessly into existing infrastructure and that they meet the specific needs of the business.

Since AI Architects often bridges the gap between technical teams and non-technical decision-makers, they need a deep understanding of machine learning, deep learning, natural language processing, and data engineering.

Salaries for AI Architects in the U.S. range from $91,000 to $166,000, making an average of $128,756 a year.

4. Natural Language Processing (NLP) Scientist

A Natural Language Processing Scientist uses algorithms to pinpoint natural language rules, and then use them to enable computers to speak and understand the language. Machine learning makes this easier because you can design an algorithm that discovers and tests patterns for you — so you don’t have to do it manually or with elaborate spreadsheets. In a way, a Natural Language Processing Scientist builds bridges between languages and machines, making it possible for machines to understand people and vice-versa.

As an NLP Scientist, you may specialize in a subfield of NLP, such as computational linguistics, human language technologies, automatic speech recognition, or machine translation. And you’ll likely also collect, explore, and improve the quality of data used to adapt and extend machine learning-based technologies that support these areas.

U.S.-based Natural Language Processing Scientists make between $98,500 to $136,000 per year, with a median salary of $122,738. If you’re interested in a career as a Natural Language Processing Scientist, check out our How to Get Started with Natural Language Processing course or our Apply Natural Language Processing with Python skill path.

5. Software Developer

Software Developers design and build applications for mobile and desktop use, as well as the underlying operating systems. Generative AI and machine learning can help Software Developers analyze data to predict how users will react to certain features of an application, design models that output data according to what users want to see, and create programs that enable chatbots to interact with end-users in more natural ways.

Generally, Software Developers fall into one of three buckets — Front-End Developer, Back-End Developer, or Full-Stack Developer — and each one focuses on a certain area of the development process.

If you’re interested in a software development position that specifically involves machine learning, you could learn TensorFlow, an open-source platform for machine learning, or Pandas, a tool in machine learning that’s used for data cleaning and analysis. Focusing on learning the tools and programming languages that are typically used in machine learning will help you qualify for these types of software development jobs.

On average, Software Developers earn around $132,270 a year.

6. Data Scientist

A Data Scientist analyzes, processes, models, and interprets data to help create actionable plans and guide business decisions for companies and organizations. As a Data Scientist, you have the potential to be one of the most useful team members in your company, largely because your ideas and suggestions are backed by hard data.

Data Scientists working in the machine learning industry help write algorithms that can discover patterns, which are then used to provide insights and recommendations. The critical role of Data Scientists is reflected in their salaries, too. You can earn an average salary of over $125,000 a year as a Data Scientist.

Learn the skills you’ll need to succeed in this role by taking our Data Scientist career path, and then once you’re ready to apply for jobs, you can check out our interview prep that’s specifically for Data Scientists.

7. Cybersecurity Analyst

Cybersecurity Analysts are in charge of figuring out the best ways to defend a company’s digital infrastructure and assets. This involves using many different technologies and can be far easier with generative AI and machine learning. This is because a Cybersecurity Analyst has to collect and study large amounts of data that reflect the vulnerabilities and threats a company may face.

If you have a background in generative AI or machine learning and you’re interested in working in cybersecurity, you may have the opportunity to tweak, upgrade, or create new algorithms used to protect an organization. The crucial role of Cybersecurity Analysts frequently earns them salaries in the six-figure range. The average annual pay is about $135,557.

You can learn about cybersecurity in our Introduction to Cybersecurity course, and when you’re ready to apply for jobs, be sure to check out Cybersecurity Analyst Interview Prep.

What’s next?

If you’re looking for more opportunities to learn about machine learning, check out our Machine Learning Fundamentals and Feature Engineering skill paths. You may also want to learn a new programming language that’s popular in machine learning, such as Python, R, and Java.

Once you’ve picked the type of generative AI or machine learning job you want, it’s important to build your resume and cover letter to emphasize the skills and experience most valuable for that position. And to prepare for the types of interview questions specific to that role.

You can use this guide to help you write your technical resume, and this advice on landing a machine learning job is a great resource.

Here are common machine learning interview questions that you can practice before your interviews. And be sure to check out our Career Center for more resume and interviewing tips.

This blog was originally published in May 2022 and has been updated to include the latest popular job roles and statistics.

What’s Going On in This Picture? | March 10, 2025

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What’s Going On in This Picture? | March 10, 2025

1. After looking closely at the image above (or at the full-size image), think about these three questions:

2. Next, join the conversation by clicking on the comment button and posting in the box that opens on the right. (Students 13 and older are invited to comment, although teachers of younger students are welcome to post what their students have to say.)

3. After you have posted, try reading back to see what others have said, then respond to someone else by posting another comment. Use the “Reply” button or the @ symbol to address that student directly.

Each Monday, our collaborator, Visual Thinking Strategies, will facilitate a discussion from 9 a.m. to 2 p.m. Eastern time by paraphrasing comments and linking to responses to help students’ understanding go deeper. You might use their responses as models for your own.

4. On Thursday afternoons, we will reveal at the bottom of this post more information about the photo. How does reading the caption and learning its back story help you see the image differently?

We’ll post more information here on Thursday afternoon. Stay tuned!

More?

• See all images in this series or slide shows of 40 of our favorite images — or 40 more.

• Learn more about this feature in this video, and discover how and why other teachers are using it in their classrooms in our on-demand webinar.

• Find out how teachers can be trained in the Visual Thinking Strategies facilitation method.

Students 13 and older in the United States and Britain, and 16 and older elsewhere, are invited to comment. All comments are moderated by the Learning Network staff, but please keep in mind that once your comment is accepted, it will be made public.

What’s Going On in This Graph? | March 12, 2025

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What’s Going On in This Graph? | March 12, 2025

On Wednesday, March 12, teachers from our collaborator, the American Statistical Association, will facilitate this discussion from 9 a.m. to 2 p.m. Eastern time.

5. By Friday morning, March 14, we will reveal more information about the graph, including a free link to the article that includes this graph, at the bottom of this post. We encourage you to post additional comments based on the article, possibly using statistical terms defined in the Stat Nuggets.

We’ll post more information here by Friday morning. Stay tuned!

More?

• See all graphs in this series or collections of 75 of our favorite graphs, 28 graphs that teach about inequality and 24 graphs about climate change.

• View our archives that link to all past releases, organized by topic, graph type and Stat Nugget.

• Learn more about the notice and wonder teaching strategy from this 5-minute video and how and why other teachers are using this strategy from our on-demand webinar.

• Sign up for our free weekly Learning Network newsletter so you never miss a graph. Graphs are always released by the Friday before the Wednesday live moderation to give teachers time to plan ahead.

• Go to the American Statistical Association K-12 website, which includes teacher statistics resources, Census in the Schools student-generated data, professional development opportunities, and more.

Students 13 and older in the United States and Britain, and 16 and older elsewhere, are invited to comment. All comments are moderated by the Learning Network staff, but please keep in mind that once your comment is accepted, it will be made public.

The Most Annoying Phrases, According to Teenagers

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The Most Annoying Phrases, According to Teenagers

Another popular phrase that annoys me is “good boy.” Could you please have some respect for people? If someone gets you something you ask for, say, “Thank you,” and not “good boy” or “good girl,” which have the same meaning and disrespect.

— Faouzane, Maya Angelou French Immersion IB School

The phrase “good girl” frustrates me immensely. I work with young kids, and I sometimes see parents or babysitters saying “good girl” if a young girl (or even an older girl) does something that they like. Firstly, I find it a bit odd, as it’s the type of thing I hear people say to their dogs, and I feel like your children should be treated differently than your dog. Secondly, I notice that “good girl” is a lot more common than “good boy,” which I definitely think says something about societal expectations placed on girls to be “good.” Thirdly, I don’t use it myself, because I don’t like placing kids in boxes of “good” and “bad” based on a few things that they do. Instead, if a child that I’m looking after does something well, like putting away their toys after using them, I say, “Nice job!” or “Thank you” to express my appreciation instead, and I wish that more people did the same.

— Ella, Carrboro High School

Hearing “it’s all good” makes me think what I’m doing isn’t a problem, which doesn’t let me fix the behavior, so if it does end up being a problem, it would be much more useful to know. Even though having to communicate through the issue can be awkward, it’s still better than having to eventually explain that it in fact was not “all good,” especially when the problem has at that point become irreversible.

— Mohammed, VSNHS

One popular phrase that most people use that annoys me is the word “Ight” or just the word “ok.” I am a big overthinker when it comes to talking to people or even texting them. Whenever you’re texting your friends or significant other, you can’t see their facial expressions or body languages. It is much harder to tell their tone when texting. There have been multiple instances where I have gotten worried that my friend was mad or upset with me because of the way they were texting. Most of those times, they used the words “Ight” and or “ok” …

I tend to appreciate more when a person takes time out of their day to not send me a dry response and actually put more letters into a word than just keep it abbreviated.

— Amaylee, CPHS, Fayettevile, NC

Let’s Discuss: What’s It Like to Be a Professional Opinion Writer?

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Let’s Discuss: What’s It Like to Be a Professional Opinion Writer?

Welcome to Conversations With Journalists! In this new series, we invite students every two weeks to join a discussion about a New York Times article with a Times journalist and other teenagers from around the world. Learn more about the feature and find a schedule of the pieces we’ll be reading together in the future here.

What’s it like to share your opinions with millions of readers each week? How do you decide what to write about? How do you craft your arguments so they will be compelling to a wide audience? What impact has your writing had?

So far in this series we have featured reporters whose work is to gather facts and information to inform readers about a topic with as much objectivity as possible. The job of an opinion writer is different: Though they too are journalists who must gather reliable information, their role is to express a point of view about it.

Why are we featuring a Times Opinion writer now? Because our annual opinion-writing contest for students opens March 12, and we hope having a conversation with someone who does this kind of writing for a living can illuminate and inspire.

This year we’re inviting students to write open letters on the issues that matter to them. As you might already know if you’ve read the Rev. Dr. Martin Luther King Jr.’s Letter From Birmingham Jail, an open letter is a literary device. Though it may seem to be intended for just one individual or group, and therefore usually reads like a personal letter, it is really a persuasive essay addressed to the public.

Our guest for this discussion is Margaret Renkl, a contributing Opinion writer for The New York Times. Her weekly column focuses on nature, politics and culture in the American South, and she often makes powerful use of the open letter format.

Whether you’re participating in our contest or not, we hope you’ll have many thoughts and questions for Ms. Renkl — about the role of an opinion columnist in a newspaper in general, and her role in particular; about how open letters work and when and why a writer might employ them; or about the moving pieces you’ll read below.

To join the conversation, just post to the comments by March 13.

We will be discussing two of Ms. Renkl’s pieces this week: “An Open Letter to John Lewis,” addressed to the civil rights leader after the news of his terminal cancer diagnosis, published Jan. 6, 2020, and “An Open Letter to Governor Lee on the Slaughter of Our Children,” written to the governor of Tennessee after a school shooting in Nashville, published March 29, 2023.

You might also consider her piece, “An Open Letter to Jimmy Carter, on His 100th Birthday,” published Sept. 30, 2024.

To learn more about Ms. Renkl’s work, you can also read some of her recent columns:

We’ll be joined by Margaret Renkl, a contributing Opinion writer, who reports from Nashville. She is the author of “Late Migrations: A Natural History of Love and Loss” (2019), “Graceland, at Last: Notes on Hope and Heartache From the American South” (2021) and “The Comfort of Crows: A Backyard Year” (2023). Since 2017, she has been a contributing Opinion writer for The Times, where her essays appear each Monday. She is a graduate of Auburn University and the University of South Carolina.

  • What parts of each essay — whether individual lines, paragraphs, quotes or anything else — stand out to you? Why?

  • Is there anything that challenges what you know or thought you knew? What did you learn?

  • What connections can you make between these pieces and your own life?

  • Is there anything missing from either essay that you wish was included? If so, what and why?

  • What questions do these pieces raise for you?

  • What would you like to ask or say to Ms. Renkl?

  • What would you like to ask or say to other teenagers who are joining this conversation with you?

  • Focus questions: What’s it like to be a professional opinion writer? How are these essays crafted to make them as persuasive as possible? Why might one choose to write in the format of an open letter rather than a traditional essay?

  • First, read the featured Opinion essays. Use the questions above to help you reflect on them.

  • Respond in the comments. Be sure to introduce yourself and then share your reactions to what you saw and read. Ask Ms. Renkl a question, either about the pieces or about her work in general.

  • Post your response by Thursday, March 13. Ms. Renkl will begin responding by Monday, March 17.

  • Come back to the conversation to read Ms. Renkl’s replies and to respond. What is something she shared that intrigued you? What is something you learned about her reporting process? What questions do you still have?

  • Remember that you can reply to and recommend other students’ comments throughout the two weeks. We hope you’ll keep the conversation going.

  • Lastly, remember: We are timing this Conversation With Journalists with the start of our second annual Open Letter Contest for Students, which is open to teenagers around the world. If you’d like to read the work of last year’s teen winners, visit this page.

    (Not sure what to ask? Check out this list of more than 20 ideas (PDF) — but don’t feel that you have to stick to them!)

Students 13 and older in the United States and Britain, and 16 and older elsewhere, are invited to comment. All comments are moderated by the Learning Network staff, but please keep in mind that once your comment is accepted, it will be made public and may appear in print.

Are you a teacher or student who has feedback on this new feature or would like to suggest a Times piece for future discussion? Please post a comment here.

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