When a Library Feels Like a Candy Store

Eight students stood in line whispering to one another and fidgeting in excitement. A few of them had peeked into the windows to see what was new. One girl had a tiny notebook with a list. Most of the students had pulled out their phones to check key information. There was a buzz in the air that settled into an intense, quiet excitement. But this wasn’t a concert or a line to buy smart phones or the front gate of a sporting event. This was our first assigned library day of the school year. Being new to this school, I wasn’t sure what to expect. I had heard that this school kept reading fun and the library was the epicenter.

A boy walked up to me and asked, “What are you going to get?”

“I already have a book I’m reading,” I answered.

He shook his head. “Nah, Spencer, you’re going to get something. Everyone leaves with at least two books but no more than four.”

“Is that a rule?” I asked.

He laughed at the ridiculousness of the question. The rule? It was like making a rule that you have to eat at the buffet. It wasn’t a rule. It was just the way things were around here.

Right then, the librarian opened the door and the students streamed in . . . loudly. They scurried from display to display, reading the back covers and debating books. Our librarian seemed to embrace the noise as she called out specific books and named specific kids.

“Carlos! You’ll love this one,” she yelled from across the library.

Some of the students had been checking out books all summer but she had built up “release dates” for the first week of school.

The cynical side of me would have scoffed at middle school students getting this excited about books. After all, there is a cultural perception that reading is inherently uncool. As a child of the 1980’s, I always felt that those “READ” posters (you know the ones with Mr. T or Michael J Fox and the word “READ” in all caps behind them) backfired. It was like the Ad Council was trying too hard with its advertising. It made reading seem important and necessary but not fun. After all, we didn’t need signs imploring us to play or goof off.

But any cynicism I felt began to melt as I watched the sincerity of my students. They were pulling out their phones and reading the QR codes to get book reviews. They debated the merits of various series and, on occasion, mocked other students for their choices in books (something I would address in our first whole class meeting).

The library was like a candy store for the mind and my students were beyond excited to be there.

At one point, the librarian called students to an open space and reminded them of some strategies for finding the right book. She talked about reading sample pages, checking out the synopsis on the back of the book, checking the 3-Star Amazon Reviews (which often provides the most measured review of the pros and cons) and even looking at the book covers to see who they were marketing it toward.

This library experience defied the stereotypes of the stodgy, quiet library. However, I’d argue that many school libraries have a similar environment because librarians, as a whole, are finding innovating ways to get students excited about reading.

Looking back at it, our school librarian was a leader of an empowered community. She was a true expert in reading, curation, media literacy, and library science. But she never presented herself as the sole expert in reading. Instead, she built relationships with students and worked with them to help find texts that would connect with their interests. As a true curator, she read a broad variety of books and constantly explored new authors and genres with the hopes of helping students fall in love with reading.

She was also a master architect who designed systems that would empower students. She launched a buddy reader program where my eighth graders would read to first graders. She coordinated author visits and worked with teams of students to do book talks and book preview videos. In other words, she helped design the ecosystem of reading that would allow me, as the teacher to build a classroom culture of empowered readers. This was moment was a reminder of the power of authentic personalized learning.

 

What Do We Mean by Personalized Learning?

“Here’s the booklet. It tells you exactly what to do to help students get into the reading intervention software. Everything should stay inside the program. It’s cloud-based but everything has been downloaded, meaning they really can’t go onto the internet if they tried,” the district representative explained.

“What do I do?” I asked.

“Walk around. Monitor. If they have any questions, they’ll raise their hands,” he explained.

“But what about the discussions?”

“No, it’s personalized. There are no discussions,” he said.

“No literary circles?” I asked.

“No, it’s fully individual. They do targeted skill practice based on a pre-test. This is state of the art adaptive learning. That means they’ll get vocabulary practice and reading intervention work that targets their key deficiencies. You don’t have to do any assessment. I mean, yes, once a week, you’ll read the printout to them and talk about goals. But it’s driven by the adaptive learning software. You’ll get data on how they master every standard. You’ll get a fluency score. As they move up to higher reading levels, they’ll get badges.”

“And what do I do?” I asked again.

“Just monitor them,” he says. “It’s honestly the easiest class you’ll teach. This is the future of reading intervention. Personalized learning is finally a reality.”

As I implemented the program, I couldn’t help but feel that “personalized” was the wrong word. If anything, it felt impersonal. Students sat at computers doing digital worksheets meant to teach everything from phonics and blending to reading comprehension. They wore headphones as I walked around the rows and kept them on track. This was the first glimpse of adaptive learning fueled by artificial intelligence. A series of cryptic algorithms set the tone and pace of the learning and all I did was sit back and watch.

Three weeks later, I approached my principal with a new idea. After nearly a semester of this adaptive learning program (with a previous teacher and now myself), students weren’t reaching their goals. They were bored and frustrated.

So, I pitched a different idea.

We would head out to the library and choose books. Students would read silently each day and build up reading endurance. We would use recommendations from algorithms (recommended reading from Amazon) but also lean heavily on our amazing librarian. We would form literary circles and do shared read alouds. But we would also do five minutes of the adaptive learning fluency work. We wouldn’t avoid AI but we wouldn’t let the machines drive the learning. Instead, our focus would remain on the human connection.

Four weeks later, we compared this blended approach to the adaptive learning program. It turned out our students had higher reading scores than the district average for those in reading intervention. By focusing on motivation and building up reading endurance, students improved. By engaging in meaningful discussions centered on critical thinking, students improved in their overall reading comprehension.

I would never claim that adaptive learning programs don’t work. Nor would I claim that my experience is normative. But I do find it fascinating that we are starting to see the cracks in the promises of adaptive learning. The data seems to be mixed. For certain phonics-based discrete skills, adaptive learning seems to work. But for actual reading compression and deeper skill development, these programs often fail.

But for me, this story is a bigger reminder that personalized learning has to begin with the person. It has to focus on voice and choice. It needs to include a human element. And, while technology is great on the back-end side, it often works best when the student-facing side is low-tech.

Personalized Learning or Adaptive Learning?

The line between personalized learning and adaptive learning is blurry. In some contexts, people use these terms interchangeably. In other contexts, people view adaptive learning as a part of personalized learning. Still others view adaptive learning as a part of customized learning. For me, personalized learning is human-centered and adaptive learning is machine-centered. I realize this will annoy certain folks in educational technology but these are the two terms I use.

	Personalized Learning	Adaptive Learning
The Structure	Human-Driven: Personalized learning might use algorithms to inform the design but it is ultimately human-centered.	Algorithm-Driven: Students progress through pre-set curriculum and the AI adapts the levels to the skill level and interests of students.
The Learning Tasks	Authentic: Students engage in authentic problem-solving. There are opportunities to do creative work.	Programmed: Students don’t have as many opportunities to connect to the world or to solve authentic problems. Often, they work on targeted standards using digital worksheets.
The Grouping	Collaborative: Personalized learning requires interdependent student work. Even when students work on individual projects, they engage in peer feedback.	Individualized: Students work alone at a computer. The work is at their level and follows their pace.
Assessment	Varied: Students engage in self-reflections, peer feedback, and teacher assessments. They might even use AI but it’s simply one of many options.	Singular: Students might engage in a self-reflection as an assignment, but the AI is at the heart of the assessment process. It’s fast and efficient. Students get immediate feedback and the algorithm uses the assessment data to adjust the next learning task.
The Process	Messy: While personalized learning still leans into structures and scaffolds, the process is often messy.	Efficient: Adaptive learning tends to move efficiently with specific feedback and adjustments happening in the moment.
The Role of the Learner	Empowers the Learner: Genuine personalized learning focuses on learner agency. There’s a sense of freedom.	Engages the Learner: Adaptive learning is less about agency and more about providing targeted instruction. Students might get choices but they have no real voice in the process.
The Role of the Teacher	Active Facilitator: The teacher plays the role of instructional designer and often takes a step back as the “guide on the side” giving individual feedback or pulling small groups. But the teacher also engages in direct instruction and leads whole class activities.	Manager: The teacher might still do some tutoring or pull-outs by having the whole class use the adaptive learning program while they act as an active facilitator. But within most adaptive learning programs, the teacher is the manager of the system. Teachers review the data and make sure students are on task.

There’s nothing inherently wrong with adaptive learning programs. I’ve seen these programs work well for certain types of skill practice – especially in world languages and math. But we need to be cognizant of the false promise that AI will provide personalized learning.

It won’t.

I’m already seeing bold promises of using generative AI for even better, more targeted adaptive learning. This newer generation will not only provide leveled work, but it will potentially create original math word problems, science examples, and non-fiction texts that connect to student interests while also being written at a student’s reading level with a focus on matching their skill level to the challenge of the task. Not only that, but students will also be able to interact with the AI like a tutor. They’ll ask questions and clarify misunderstandings.

While there might be a time and place for such adaptive learning programs, this feels like yet another iteration of a tech-centric model of personalized learning. What if we began with a human-centered view of personalized learning and then considered ways that we could use AI to augment rather than replace the human element?

Check out the following video I created about this very topic:

 

What This Mindset Misunderstands About Learning

For the last three decades, I have watched as ed tech evangelists have promised that the newest cutting edge technology would bring about a renaissance in learning and revolution education. Better achievement. Better engagement. You get the idea.

I heard it with the advent of the internet. Hop on the information superhighway. Ask Jeeves and he’ll send you what you need. Then it was specialized CD Roms. Then one-to-one devices and then tablets and eventually adaptive learning programs. Now it’s generative AI tutoring systems.

The truth is, we are getting better at delivering content, assessing student learning, and adapting as a result. The ed tech evangelists aren’t wrong about the power of AI to deliver better instruction in a dynamic way.

And yet . . .

This ed tech philosophy is built on a content delivery model that essentially treats students as passive recipients of knowledge. It’s an overly simplified view of the mind as an information processing machine. With the right engineering, we can match the instruction perfectly and efficiently to each student in an individualized way.

However, that’s not how our brains work. Memory is much more fluid than a machine. We experience more interference based on prior knowledge and current understandings than what a machine can pick up. The neural pruning process is deeply physical, connecting to factors like sleep, food, and social interaction.

But I also think this model fails to grasp how we actually learn. We are not passive recipients of knowledge. We actively construct our knowledge from infancy. When we use a content delivery model, we rob students of their agency and the net result is a lack of self-direction. When we give them instant feedback at all times, they fail to develop resilience due to the lack of productive struggle.

Moreover, learning is inherently social. We develop deeper understanding through collaborative learning and peer assessment. When we place students in front of a screen for hours in isolation, they fail to understand nuanced perspectives or gain feedback that can help them develop deeper understanding but also intellectual humility.

In other words, in an age of generative AI, students need to develop the depth advantage that they’ll need in an unpredictable world. They will need deeply human skills that they cannot gain in a content delivery model.

So, does this mean we abandon AI entirely? Not so much. We can actually use AI ethically for deeper learning as a study tool (something I’ll share at the end of this article). But we can also use it on the back end.

 

Using AI on the Back-End

Two years ago, I created this continuum showing how we might approach the use of AI in schools.