The Learning Struggle Gap: Why Students Don’t Ask for Help, With Elizabeth Pearsall

Full Transcript

Cristi Ford (00:00):
What happens when learners need help but never ask for it? In this episode, Elizabeth Pearsall joins me to discuss the learning struggle gap, the difference between productive and unproductive struggle, and how educators create learning environments where students feel seen, supported, and empowered to succeed. Join me for the conversation.
Intro (00:23):
Welcome to Teach and Learn, a podcast for curious educators brought to you by D2L.
Cristi Ford (00:28):
Each week we’ll meet some of the sharpest minds in the K to 20 space. Sharpen your pencils, class is about to begin. Listeners, welcome back to another episode. I’m Dr. Cristi Ford, your host today. And in today’s episode, I am so delighted to welcome Dr. Elizabeth Pearsall, assistant provost for teaching and learning at the American College of Financial Services. She’s also an educator, an innovator, a thought leader whose work explores how institutions can better support learners by identifying barriers, fostering belonging, and creating opportunities for help seeking before students disengage. Elizabeth, it was so great to see you last week and I’m so, so happy to have you here today.
Elizabeth Pearsall (01:13):
It was wonderful to see you last week as well, and I am thrilled to be here today.
Cristi Ford (01:18):
So as I was thinking about us having this conversation today, before we jump in, I’d love for you to just share a little bit with our listeners who may not know a lot about American College of Financial Services. So maybe we’ll start there and then we’ll dive into this exciting topic.
Elizabeth Pearsall (01:34):
Sounds good. So the American College of Financial Services educates individuals who help families make consequential financial decisions. Financial planners is the term most people are familiar with. So we offer professional education and graduate study in the financial services industry. Many of our learners are balancing coursework with careers, families, other responsibilities, and by many I mean like 99% of them. And so that makes the question that we’re discussing today very real for us and for others. When someone gets stuck, can they find a useful way forward before that moment becomes a reason to step away and disengage.
Cristi Ford (02:11):
Fantastic. Thanks for sharing that. So I want to jump right in. There was a concept that you articulated recently called the learning struggle gap. And it’s such a powerful way of describing something many educators talk about, they think about and observe every day, but may not have language for. Can you maybe introduce listeners to the concept and explain why it’s become such a central part of the work that you’re doing?
Elizabeth Pearsall (02:39):
Absolutely. I use the phrase learning struggle gap for the space between a moment when a learner realizes they need support and then the moment when they actually ask for it, if they ask for it, it’s that gap right in the middle. As educators, we tend to assume they’re going to raise their hand, they’re going to send an email, they’re going to visit office hours, they’re going to ask a question. But sometimes learners can’t quite put their questions into words or they worry that it’s something they should already know. And at the end of the day, the asking never happens in some cases. And when that occurs, a manageable question can become delayed work, errors, disengagement, or where a learner feels like, “Maybe this isn’t right for me.” And those are possible paths, not conclusions that we can draw about any one learner. But as an educator, something that I’ve learned over the years is that silence is not proof of understanding when just because a class is
Cristi Ford (03:34):
Quiet,
Elizabeth Pearsall (03:34):
A learner is quiet, that doesn’t mean they’re actually
Cristi Ford (03:37):
Understanding.
Elizabeth Pearsall (03:38):
And I started paying more attention to this when I started teaching online over a decade ago now. In a classroom, you might see a puzzled face and then the instructor may take a pause or you may not see some confusion. But then again, blank looks can give us a little
Cristi Ford (03:53):
Bit
Elizabeth Pearsall (03:53):
Of insight too. And as I move from teaching into broader academic leadership, I have continued to teach online classes and I’ve never lost sight of where learners stall and then what is it that they need? So in that learning struggle gap, what is it that we can do in that gap to actually reach those learners at that moment? And I see the learning struggle gap as a design question, things that we can actually control as we are designing our courses and as we are instructing them with our students or our learners.
Cristi Ford (04:23):
When you talk about this learning struggle gap, one of the things you talk about is your personal connection and how tied you are to this topic as your experience as a student. Maybe you can share with me a little bit about those moments and how they’ve shaped the educator that you’ve become in this work that you’re taking on now.
Elizabeth Pearsall (04:44):
Yeah. As an undergrad, Cristi, I was working a full course load or taking a full course load. I worked full-time. Most of the time I had two jobs and I was planning for graduate school. I never in a million years though I was going to be a professor and that my career would be in academic administration or academia in general. And my background, my doctorate’s biochemistry, so I’ve taken a lot of large science classes and you don’t want to be the one student out of a hundred or 200 with a question that delays the whole class. And I remember sitting there and feeling like I had these questions, but it’s like, nope, I shouldn’t ask. I’m going to delay the class. I should know this. And really one example that I shared that with you previously I think is from my calculus class in undergrad.
(05:31):
And there was this day the professor was doing an example and we had the problem and then we had what he said was step one. And I was really confused. I was like, “You went from step one to five, so how did you get there?” I was really confused. And so I asked the question and do you know what he said to me? He said, “You should have learned that in pre-calc. It’s not my job to teach you that.” And that taught me a lot. It also taught me to not ask any questions in that class anymore. But looking back, I actually can say I think that experience really made it so that I wasn’t comfortable asking questions in a lot of my classes, especially some of those more consequential, those foundational courses typically if they’re larger, but they are so consequential later on.
(06:21):
And that experience has stayed with me. And I try when I’m teaching, if somebody needs a different explanation or need me to show a step, that actually tells me something really useful about how learning’s going. A question can tell me how the instruction is going, but it doesn’t tell me whether or not they belong. And I say that with that math professor completely made me feel insignificant like I didn’t belong in his class. And so I really tried to learn to make room for those types of questions and respond to ways that help learners. I mean, one question, and you know this, is that somebody asked a question and frequently there’s other people who had the same question.
Cristi Ford (07:05):
Same question.
Elizabeth Pearsall (07:06):
They just didn’t want to ask. So just that little bit of information is one part of why this work is so personal to me and really why my experiences and just how they’ve helped me evolve and really given me that different perspective as I’ve been diving into this type of work.
Cristi Ford (07:26):
It’s such a powerful example. And I think many educators listening probably have their own examples where they resonate with that and really are like you are trying to be the change they want to see in the world and how they come to the classroom and help learners to be successful. I want to double click on this learning struggle gap a little bit. And you talk about this distinction between productive struggle and unproductive struggle. How do you define those and why is it important for educators to understand the difference between the two?
Elizabeth Pearsall (07:58):
So I’m going to address that, but really fast, I want to go back to something you said about the educators listening and how they’ve probably had an experience. Something else that has sat with me for years is that I can pinpoint those experiences that were challenges really easily. But if you ask me what were the good moments, that’s a lot harder of a question. And so I know for myself and some others I’ve talked to over the years that the things that our professors did that maybe were not great actually helped define us much more so than the ones who were excellent. So I want to just touch on that just because you mentioned it and it just popped into my brain, but back to productive struggle and unproductive struggle and why it’s important. So productive struggle is really the effort that contributes to learning, right?
(08:47):
Retrieving a concept, applying it to a new case, testing out a theory or looking at your answer, getting feedback and then revising it. And all of those things can be incredibly difficult, but that difficulty is connected to the actual learning goal and the learner has a way to make sense of exactly what’s going on of that attempt. Unproductive struggle consumes effort, but has nothing to do with learning material. So for example, in an in-person class, finding the right classroom, that absolutely, finding the classroom or if the class moved, oh my, that is struggle that takes away some of your mental capacity for learning at that moment in time, but has nothing to do with it. If you think about online courses and the LMS, imagine there’s a menu called tools and there’s 10 things listed, but there’s no predictable order. Alphabetizing them, things like that actually reduces the cognitive load there.
(09:49):
Or you’re in an online class and you spent 10 minutes going, where do I submit this? How do I find my assignment? All of that is struggle, but it’s unproductive. It has absolutely nothing to do with learning the content. And the distinction between productive and unproductive struggle matter because sometimes we call that type of friction rigor. And productive struggle asks learners to think hard. Unproductive struggle makes them work hard just to reach the ability to do the thinking. We want our learners to spend their effort learning and mastering content, not trying to figure out where a resource or a classroom is.
Cristi Ford (10:32):
Yeah. As I listen to you, it seems like a simple distinction, but oftentimes to your earlier points, where we’re not seeing ourselves in the student’s eyes, we may be missing those opportunities to reduce that unproductive struggle or even completely eliminate it. And so as those that are listening, I often talk to faculty members and we know higher education values, challenge and rigor and criteria and standards and those are all really important, but how do we help educators think about this unproductive struggle? How do we help them remove unnecessary barriers without eliminating the effort and persistence that needs to happen for learning to occur?
Elizabeth Pearsall (11:23):
Cristi, I had a simple test for this for myself and the question is, if I do this, does the learner still have to do the thinking, the learning and experimenting with the content? Nine times out of 10, that answer is yes. And that’s great. So clear directions, a consistent course structure, an easy path to help learners direct more of their energy towards the judgment and the knowledge that we want them to develop. Even small choices matter. And rigor I believe really starts with what is it we want learners to do? Let’s say for example, a case study. So a learner is working through a case study. I want them to weigh the options, consider what are the circumstances, what information might be missing, what is the recommendation, what would they do? And then maybe even look at it and say, oh, by the way, here’s some new information.
(12:19):
Now what? And that should take effort. I want them to wrestle with that and that’s rigor. But when a learner gets stuck, they need a way to keep going. And that’s where clear expectations, the opportunity to practice and feedback they can
Cristi Ford (12:35):
Use
Elizabeth Pearsall (12:36):
On the next attempt where it doesn’t just give them the answer. This way, it helps the learners stay with that productive struggle and truly become more ingrained with the information we’re wanting them to learn. So one of the other things I ask is, is the difficulty that my learners are experiencing, does this help them develop their judgment or is it really using their energy before they can do the work? So we can remove those unnecessary barriers and still 100% expect learners to practice, to persist, to critical think about situations and defend whatever it is that they may want to do in a case study, for example. Rigor is in the quality of the thinking and the learning, not how long someone has to struggle just to get there.
Cristi Ford (13:24):
Yeah, I think that’s really profound. And I’m thinking about, especially in the era, and I know we’re going to talk about AI and technology and all the things, because how could we not in the era that we’re all teaching and learning in? But one of the things I want to talk about before we get there is where you and I talked about this calculus example with this professor where you asked the question. You talked in that example about his response, and we know that sometimes other students hesitate to ask for help. Either they have that fear or that judgment like you talked about, maybe uncertainty or simply don’t know where to start. And so what have you learned about creating environments where learners feel safe enough to reach out? Because what you said to me is this is a design conversation aspect. And so I’d love to unpack that with you a little bit.
Elizabeth Pearsall (14:16):
Absolutely. Safety is established by what happens after a learner asks a question. I can tell somebody all day long, please ask me questions, but are they going to? And a lot of times they’re going to judge that by the response they receive. A 2018 study of college students found that perceived threat was 100% associated with whether students approach instructors for help outside of class. And when that study looked at the question of will I look foolish if I ask? And as I think about that, I try to listen, what is the question the learner has, even if it’s not a perfect question? And a lot of times if a learner says, I’m lost, but I have no idea how to get here, then great, let’s find a starting point together. And for a learner to feel safe for safety in asking these questions, is there a private way to start asking a question?
(15:09):
Whereas they may feel uncomfortable asking in front of others. One of the things that I did when I was teaching chemistry in person, when we get to calculations, anybody who’s done chemistry knows that chemistry is really math in disguise with some funny words. And one of the things I would do is we would do practice questions in class. I finally got to a point after probably my third or fourth year of teaching, I stopped taking a calculator to class. I would design new questions with new numbers and then I didn’t do the problem. I refused. I made the class do it. So the class did it, they discussed it, but then there was inevitably, wait a minute, but I did this. Why did you do that? And so that created a safe environment for students to ask questions, for those learners to really ask questions about what was confusing.
(15:56):
And in doing that, I didn’t have to wait and look at blank faces and try to guess. They were much more open. And I think I normalized, in that case, I normalized asking questions. I made it part of the learning experience that they expected. Now, one of the things with learners is sometimes they ask a question and the actual support that they need isn’t just the answer. Sometimes it is really help taking the I’m lost into something actionable. In an online course, that could mean a clear route to their instructor or a TA, a short explanatory video, extra examples or an announcement that all address a common point of confusion. Now to create that safety, maybe we do that even before the question is asked. We know this is a hard topic this week. Let’s do an extra little something and provide it to our learners so that they’re a little more comfortable.
(16:55):
The other thing is that feedback matters that if you simply say you lost 10 points for not doing X, that may be helpful because it kind of gives a reason, but it actually doesn’t help learning. It doesn’t tell them what to revisit or how to improve the next time. And if we start doing that more, then we’ve provided that useful information. And I know that for myself, if I ask you a question and I get a really useful response, even if it’s not what I necessarily think I want, if I ask you, “Hey Cristi, what’s the answer to this?” Then you’re like, “Oh,” and you kind of lead me through the steps without giving me the answer next time because that was so useful, it’s going to be a lot easier for me to ask the question in the future.
Cristi Ford (17:37):
Absolutely. And what I love about your response is I always talk with people about learning really being social. And so to your point, it’s not about getting the answer, but it’s about the process of learning and sometimes it’s about being able to connect to those other sources. I was talking with some colleagues around, we’re talking about some of the work that we’re doing here at D2L around tutoring in the AI space with Lumi tutoring and the importance of not being able to give students the answers, but using Socratic method and all types of methodology to be able to do that. So I think it really echoes what you talk about and really being able to think through the way in which people can, back to your earlier point, have that productive struggle, but able to leave and learn something. And so I just think that is really profound.
(18:30):
And I want to move us into really talking about something we started off with in terms of learners feeling seen and heard. You talk about psychological safety and belonging, but maybe you can share with our listeners a bit in your role how you’ve used proactive outreach, maybe to reconnect with learners who may be disengaging. Can you talk a little bit about course embedded AI, where the technology and the human meet to make available supports often available for students as they arise? What kinds of experiences has taught you that learners need, what kind of supports learner needs in those moments and what is the role of technology in being able to mediate that without replacing humans? I said a lot, but I think you have a lot to offer there.
Elizabeth Pearsall (19:21):
You said a lot. We’re going to see if I can address all of it. We’ll see where we go. I don’t know. So I really think it’s a multifaceted approach and there’s two main prongs that I’ve used, but I do think it’s multifaceted. And the first that I’m going to touch on, it’s actually not necessarily AI, but rather intelligence and intelligent agents. And this goes back to timely outreach. So something that I explored about a year and a half ago was, okay, online course, it’s like day five, week one. Who hasn’t logged in or who hasn’t been in the content? Maybe they logged in and they left, but they haven’t actually engaged in the content, haven’t done a discussion or anything like that, but they logged in and they left and it’s the first week of class and we want to keep them in class, right?
(20:12):
Or again, it’s Friday, week one, they haven’t logged in yet. Where are they and how do we get them back? So one of the things that I started doing, and we actually did this across multiple courses and programs at the American College, and it is now something very standard for us. And basically we used data and information inside the LMS and we said, okay, if a student has not logged in or submitted work by day five, week one, let’s send them a message. It has to be encouraging. It’s, “Hi, we know class started this week. We know life gets busy. Everything happens, but there’s still time. Don’t forget.” So we send this really encouraging message. And what I can share with you is that I went back and actually pulled up my data on this to make sure I was right, but in sending that message across multiple courses and programs, approximately 50% of the learners who received that message logged into the class and did something within four days, 50%.
(21:18):
And for me, that’s 50% of students that I might not have gotten. I don’t know what their situation was. Maybe 30% would’ve logged in anyways. I don’t know. But what I can say is that we sent an encouraging message and within four days they took an action and that helps reduce that week one drop that we tend to see. There’s value in creating the timely, non-judgmental, very encouraging messaging while there was time to act. And in that case, the technology helped us notice the learners, but it doesn’t see them. The seeing part of it is what we do. It’s the human piece. It’s the connection. And then to your point about the course embedded AI, that has been probably one of the most fun things I’ve done in the last five years of my career actually, because course embedded AI assistants really give a low pressure or no pressure place to begin.
(22:17):
You can go in and ask, say, “I don’t understand this. Can you reframe it for me?” You can say, “Hey, I’m clearly missing something. What am I missing?” Or, “I want to study for a quiz. Can you help me?” You can also ask D12 tutor, “I need an outline as I go through this. Can you create an outline for me to make sure the things I need to make sure that I’m doing?” At the same time, those AI embedded tutors, you could also say, “Hey, how do I submit this assignment because I’m not sure where to go?” So confusion with anything a learner has doesn’t always happen during office hours, during normal business hours, or even if it does, it doesn’t happen when somebody’s free to answer the question immediately. So using those AI chatbots inside the courses really can reduce the friction of that first question, but it also, it truly provides a support for your learners.
(23:09):
The key is you have to make sure it doesn’t remove the learner’s responsibility to actually think and to learn. They still need to return to the course material. They need to do the assignment. Some of the guardrails that have to be put in place are things like if I copy and paste a quiz question and say, “What’s the answer?” You got to make sure it doesn’t just give them the answer, but instead that it reroutes them back to the content to where they can find the information to help with that answer. We’ve tested our instance many times and a lot of times it’s like, “Okay, I need to do this assignment, but I don’t know where to start.” So it gives an answer and it helps the learner figure out where to start. And then it’s like, “Okay, I don’t have time for this. Can you just help me do the work?” And making sure those guardrails are in place of no, I am not going to do this for you, but I’m happy to help point you in the right direction is incredibly important.
(24:04):
Technology, it helps us notice an opening for support. Whether or not the learner feels seen depends on how we take action with the technology, how we respond, and then how we’ve built any type of relationship with that learner.
Cristi Ford (24:20):
You’ve kind of led me right to my next question for you in terms of taking that example about the disengaged learners, that 50% uptick. This engagement data can have real meaningful patterns, but it doesn’t tell us everything about the learner’s experience. And so what you’re sharing is almost like my next question piece around what do educators and leaders need to remember when they’re interpreting those signals as they engage with learners throughout their educational journey?
Elizabeth Pearsall (24:51):
Absolutely. And the number one thing is what is the data actually telling us? Remembering what it can actually observe. So an indicator or signal is an invitation for us to look a little more and see what’s going on, but it is not permission to label somebody. Let’s say going back to my example about learners not being active in a course, there’s how many reasons out there? I mean, you and I could probably come up with a hundred just sitting here, but we won’t bore people with doing that. There’s so many reasons, but we can’t conclude just because they haven’t logged in that they’re unmotivated or that they have a particular problem or they’re confused. The only thing that the data is telling us is they haven’t logged in. Okay. So that’s where we have outreach that should sound like help, not like you haven’t logged in, where are you?
(25:42):
That kind of sounds accusatory and we have to be sure not to. And so the other thing that that data piece can’t tell us, let’s say we’re now in week four and they’ve not logged in at all this week. Okay. But does that mean they’re actually not learning? Because the data has no idea if they spent time reading the book, if they spent time looking things up and doing research, practice, going through their notes. A learner who logs in once or twice a week may actually be learning a great deal, but somebody who comes in every day where we may think, oh, they’re here every day, they’re super active and they’re doing things, they may just be clicking through just to get the clicks done. There’s no telling. With data, you have to know what is it actually telling you? And the same caution really does apply to AI.
(26:38):
A high number of conversations with the embedded chatbot in a course tells me, “Hey, people are using it. That’s great.” But that doesn’t tell me, are they asking more than one question?
Cristi Ford (26:48):
If it’s effective. Yeah.
Elizabeth Pearsall (26:49):
Right, if it’s effective. And so to know whether the support is helping, we have to look at the evidence and then we actually have to engage with our learners. The signal, it’s not the whole story. Data, it tells us where to look and gives us ideas on what to ask next, but it doesn’t actually diagnose any person that’s behind the pattern that we’ve seen in the data.
Cristi Ford (27:14):
As vice provost of teaching and learning, I’d love to maybe have you look forward with me. And as we talked about AI and analytics and learner support and these technologies continue to evolve, what do you believe institutions must protect to ensure learners retain the dignity, their agency, trust, and meaningful human connection?
Elizabeth Pearsall (27:37):
There’s a few things. Institutions need to protect a lot of things. In this case, they really have to protect learner’s agency, the work of learning, the rigor, the productive struggle, and relationships. When an institution considers a new tool or when I do, what is it made possible for the learner? What question are we trying to answer? If it’s depending on the type of tool, does it help the learner take a useful next step while leaving the reasoning of judgment to them? Do they have a choice about getting help and how easy is it to use? We have to think beyond the moment that a system was to flag somebody in need, right? Who receives that signal? Do they have the time and the context to respond thoughtfully? I mean, if one of my students comes to me and says, “Hey, what are the prerequisites for this class and how do I enroll?” I have no idea.
(28:31):
I don’t have the context needed to respond to that. That’s going to be more of an advising type of question. So making sure that the person who is receiving all of these signals has the time and context to respond thoughtfully. Can a learner tell us that we’ve misunderstood what’s going on or can we simply offer help and them accept it where we don’t even ask them to explain? We simply just say, “We’re here and that’s it because their private life is still their private life.” And going back to learner dignity, I think we have to protect that. And then a human handoff cannot be an afterthought. It really has to be something that we design intentionally and make time for. And all of this takes us back to something that has been a very strong topic for the last year and that’s trust.
(29:24):
We need to tell learners why we’re reaching out. When they respond, we need to listen. And then we need to actually follow up and say, “Hey, did what we do actually help? Because if it didn’t help, then we need to go back to the drawing board.” Having a high number of alerts or messages or even just a high number of AI conversations, that’s not necessarily the information that I want to celebrate. I want to know, did the learners move forward? Did they thinking themselves? Were they comfortable? And are they doing it repeatedly? Are they asking multiple questions in a conversation, not just one, multiple questions Shows us that they’re engaging with the AI.
Cristi Ford (30:03):
More deeply.
Elizabeth Pearsall (30:03):
And if they come back, then they’re doing it repeatedly. And something that I would say for leaders everywhere and for faculty is smart to start small. Find a point where your learners routinely stall or where they go silent and then ask you what part of that difficulty is worth walking through and working through and what can we remove? What’s productive? What’s unproductive? Let’s remove those unproductive barriers. Let’s keep the productive ones because that will ultimately help us protect the learner’s agency, the work of learning and the relationships. If all we do is detect the struggle, we measured a gap, but we didn’t help the learner get across the gap and we didn’t close the gap. All we did was detect it. We have to detect it and then we have to figure out how to address it and how to help those learners shorten that gap or make it across the gap.
Cristi Ford (31:03):
This is so helpful. As I think about Oh We’re up against, it makes me feel very happy to know that you are in this fight with us to really help learners succeed as we’re moving into this next era. And as I start to wrap up this episode, Elizabeth, I’ve been asking guests to finish a sentence. So I’m going to ask you to finish this one for us as we wrap up here today. Productive struggle becomes possible when learners know
Elizabeth Pearsall (31:32):
That the hard part is worth doing and that somebody is going to help them through it but not do it for them.
Cristi Ford (31:43):
Very well said. Elizabeth, thank you so much. Thank you for being here today. Thank you for the conversations. Thank you to our dedicated listeners and curious educators everywhere. Please remember to follow us on social media. You can find us on LinkedIn, Instagram, Facebook, X at D2L and subscribe to the D2L YouTube channel. You can also sign up for the Teaching Learning Studio email list for updates on new updates like this, episodes, articles, and more. And if you’ve enjoyed today’s conversations, please remember to rate, review, share this episode and subscribe so you never miss a thing. Thanks for joining us today.
Elizabeth Pearsall (32:22):
Thanks for having me, Cristi.
Outro (32:24):
You’ve been listening to Teach and Learn, a podcast for curious educators brought to you by D2L.
To learn more about our K through 20 and corporate solutions, visit d2l.com. Visit the teaching and learning studio for more material for educators by educators, including masterclasses, articles, and interviews.
And remember to hit that subscribe button. And please take a moment to rate, review, and share the podcast. Thanks for joining us. Until next time, school’s out.