Over the years, many professors have conceded that a teacher-centered, information-download, sage-on-the-stage, lecture is probably not the best way to get introductory astronomy students excited about science. Even when precisely illustrated, articulately delivered, and cleverly constructed, most professors realize that most students aren’t able to absorb everything that a professor could say during an hour long information-download lecture simply by listening and taking notes.
There are, of course, some brilliant and notable exceptions. Sometimes, these folks are so good that their lectures have been video recorded and sold on DVD—I even purchased a few. These professors are highly talented story tellers who can capture students’ attention and hold it for almost hour at a time. Unfortunately, I’m not one of them; although I sure wish I was. And, I suspect most folks reading this aren’t either one of those either. (Of course, far too many of us believe we’re good drivers, fantastic chefs, and great lecturers mostly because we haven’t received a statistically significant number of authoritative complaints.)
Not too many years ago, it used to be the case that when a professor earned lousy teaching evaluations from students, their Department Chair would assign that professor to go sit in on some graduate courses—not courses on how to teach, but graduate-level science courses. The misconception was that the only way to get low teaching evaluations would be if one didn’t know the material deeply enough, to which the solution was to re-experience Jackson-level E&M lectures.
We know today that the solution to improving teaching rarely is about the teacher achieving a better understanding the concepts. In fact, it could be far worse than this. For instance, in K-12 mathematics, mathematics education research has clearly illustrated that the more advanced mathematics classes one takes, the lower their students’ test scores. Imagine a graph of student’s math scores plotted against the number of mathematics courses their instructor has taken. Common sense might suggest that the result would be a monotonically increasing line with positive slope; however, perhaps surprisingly, there is a maximum inflection point given by the first derivative test and student test scores start to decline pretty rapidly the more mathematics their instructor has taken. We’re not sure the degree to which this is true across the sciences and in astronomy in particular—anyone looking for a great research project, here you go!—but we assume it does and we have strong suspicions about why this might occur.
Allow me to digress for a moment and present some evidence from the famous Feynman Lectures on Physics at Cal Tech in the 1970s. Nobel Laureate Richard Feynman is famous for a number of things ranging from quantum mechanics to philosophy to his work on the Manhattan Project to his gregarious personality. If you haven’t had a chance to read Feynman’s trade books, I’d start with Surely You’re Joking; if you haven’t had a chance to listen to Feynman’s interviews, I’d start with YouTube. There was even a movie made about his life staring Mathew Broderick, but I digress too far. The point I’m trying to get around to make is that professors who deeply understand physics enthusiastically believe his lectures are brilliant, insightful, creative, deeply engaging and, most importantly, make physics concepts very easy to understand. But, at the same time, undergraduates who were in that class decades about only really remember that they could barely understand what in the world Feynman might have been talking about. It seems reasonable to assume that undergraduate physics majors at Cal Tech were mostly talented and high aptitude students—many of which went on to become professors. Yet, they struggled to understand what the expert of experts was trying to simplify for them. Feynman was definitely brilliant and is fun to listen to; but was he a great teacher of undergraduates?
The principle reason that deeply knowledgeable professors are in perilous danger of being lousy teachers seems to be because of fundamental differences between how novices and experts cognitively structure their understanding. And, it isn’t just that experts know more than novices, experts really do have physically different brains! Consider for one that novices trying to learn new concepts are not able to readily distinguish what is relevant from what is irrelevant. For example, the common situation where an undergraduate physics student tries to memorize every single equation listed in a textbook chapter. As experts we know this is silly because most of the textbook’s equations are simply derivations steps explaining how to get from one really important formula to another really important formula. In the case of astronomy students, we are flustered because astronomy students don’t readily distinguish between comets and meteors or sometimes even between stars and galaxies. This is because to novices just starting to learn astronomy, it’s all just a bunch of indistinguishable stuff that’s beyond Earth.
Another difference between novices and experts has to do with how go about approaching end-of-chapter problems. As an example from physics, consider when a professor asks a student about why they used a particular formula to answer a particular end-of-chapter homework question, students are apt to state that they used the previously listed formula for the previous homework question, so they assume that the next homework problem must use the equation following the previous one in the book. This is illustrative of novice students grabbing at every formula rather than following principles. This happens in astronomy when students don’t seem to read the book; rather, they just flip through the pages trying to figure out where the answer is to their assigned end-of-chapter questions which, of course, are sequenced in the same sequence as the chapter! One might wonder if it wouldn’t just be easier for students to learn the material rather than try to game the end-of-chapter questions; but one giant difference between experts and novices is that novices don’t yet have a structure to organize their thinking other than the sequence from the textbook or lecture. Of course, the sequence presented in the textbook makes sense to use experts because it was also created by an expert.
Expert problem solvers are distinguished from novice problem solvers in that experts know how to get un-stuck. Getting unstuck is a learned skill that comes from lots of practice working lots of problems. Novice problem solvers will try one equation from their book to solve a problem, and if that doesn’t work, they don’t know what to do next. It is a hard earned skill that undergraduate physics and astronomy majors learn to try to work a problem from multiple angles until they can get traction and move forward. One reason that it is a hard earned skill is that few professors make mistakes when working problems at the front of the lecture hall, and students incorrectly assume that the best problem solves drive a straight path from question to solution with no hiccups, U-turns, or backward steps. Few astronomy professors realize the tremendous benefits of showing their students what getting stuck and unstuck looks like. Instead, we too often give flawless performances of problem solving or practice quiz question solving or even giving faulty essay answers on classroom activities like Lecture-Tutorials for Introductory Astronomy and, in doing so, give students the impression that successful science is a mistake-free endeavor. All of this makes me think, oh, if my students could just appreciate the grant proposal reviews and publication referee reports I get; then they’d know science isn’t mistake-free.
As it turns out, astronomy experts aren’t automatically experts in everything—in contrast with what we often seem to believe. Just like we can observe that novice astronomy students initially only see undifferentiated, superficial aspects to a phenomena compared to astronomy experts, we also readily see this occur with professors trying to learn how to teach astronomy better. In recent years, our teaching excellence workshops have started to use more and more ASTRO 101 classroom videos showing students and their professors. The challenge to using these videos in workshops is that novice professors aren’t readily able to distinguish between relevant and irrelevant aspects even when they have had decades of teaching experience—years of teaching experience doesn’t automatically correlated to levels of teaching expertise. For example, a novice professor watching another classroom usually focuses on the preciseness of the professor’s facts being presented or the professor’s mannerisms and, occasionally the seeming chaos of the classroom during a student-activity. Only after explicitly being highlighted repeatedly by the workshop leader, will novice professors start to move their attention from readily observable professor’s specific lecture delivery to more salient characteristics about how deeply students’ are intellectually engaged in wrestling with an new idea, the extent to which an artful professor uses complex questioning and rapid feedback to help students understand ideas more flexibly, and how the professor helps students connect complex astronomical ideas to individual experiences without asking students to memorize the professor’s personal analogies. In other words, becoming a master teacher involves some hard work moving from being a novice to an expert too.
The bottom line here is that experts, compared to novices, know what is relevant and irrelevant about a situation. This knowledge about relative relevance in irrelevance allows experts to chunk knowledge more efficiently than novices. Most of us have heard that humans usually have a limit of about seven things they can mentally juggle at the same time. Sometimes we describe that as having about seven available slots of working memory to work on solving a problem. Compared to novices, experts don’t waste valuable and highly limited working memory slots to irrelevant aspects. Moreover, experts are able to efficiently chunk seemingly disparate ideas together into the same working memory slot. As a result, experts seem to be able to manage more complex thinking than novices.
Putting all of this together, experts can struggle mightily with teaching novices. For one, professors sometimes don’t recall why they know what they know—far too many of our workshop attendees think they learned astronomy by listening to lectures and somehow seem to have forgotten all the late night group study sessions where they wrestled with complex ideas and the long problem sets they worked in undergraduate and graduate schools. I can’t understate the surprising number of professors who believe that they learned stellar evolution only by listening to some professor in grad school lecture to them for an entire semester for two to three hours each week. It’s a fragile perspective that can easily be undone when examined more closely; but, it’s a tacit assumption that we professors ourselves don’t often challenge without some nudging.
More than not correctly recalling why they know what they know, it has often been a while since professors themselves have struggled with the concepts they are often charged with teaching their students. Stephen Brookfield is often quoted as saying, “The best learners … often make the worst teachers. They are, in a very real sense, perceptually challenged. They cannot imagine what it must be like to struggle to learn something that comes so naturally to them.” In other words, professors don’t often recall which parts of a new concept were challenging. This manifests itself in some subtle, but self-evident ways. For one, we often hear from professors teaching a new course for the first time that they didn’t really understand a particular, newly encountered idea until they had to teach it; in ASTRO 101, this most often comes up when discussing how to teach seasons—a topic rarely covered in graduate school. Getting up to speed to teach a new class for the first time reminds one of which aspects are complex and potentially troubling to students. For another, when it has been a while since you first learned a new idea, it is likely that you have forgotten which aspects are troubling because now you have an expertly organized cognitive view of the entire landscape of the targeted concept and how it fits into the larger sequence of ideas that students are encountering. This means, as an expert, you’re not always in the best position to help students learn a complex idea.
Wait a minute—you say—if the expert isn’t best positioned to teach students, who is? Let me back pedal for just a moment and say, “no, my good professor, experts are indeed in a great position to teach students, as long as they are aware that they know more ideas and think about these ideas differently than novices do.” But, there are people who are often in a great position to help a struggling student. These are the people that most recently learned it. As a surprising example, consider the student in your class right now who sitting right next to a struggling student. Because they just recently wrestled with an idea, they might be in the best position to best explain a new idea to a struggling student.
We used to think that think-pair-share, Peer Instruction, clicker-questioning techniques worked so well because students could solidify their understanding by explaining ides in the students’ own natural language instead of the scientific jargon professor’s used; instead, we now think that the reason this works is more based in cognition than language in that students can help struggling students focus on the most relevant aspects of an idea and help discard the irrelevant, so it can all be done in available working memory.
Another person who is well suited to help struggling students consider the most relevant aspects to a complex idea in the service of learning are students who learned it last term. The use of peer-aged tutors and mentors, both outside of class time and inside of class time are demonstrating some great success in improving student learning across a wide variety of contexts. Even graduate students are often able to help undergraduates in highly effective ways because the distance in time from when they learned ideas to now is much shorter for them than for most professors.
To take advantage of these ideas for improving student learning of complex ideas—including bridging the novice-expert barrier and providing ample opportunities to practice through conversation, problem solving, and repeated engagement with challenging ideas—a considerate professor has to think about how to set up scenarios where students are intellectually wrestling with ideas rather than just listening to someone talk about ideas from the front of the room. This means that the role of the professor changes from being one who dispenses knowledge to one who focuses on listen to student thinking, providing rapid feedback, using individual questioning to extend student thinking into novel situations, and providing a classroom environment that is about what the students are doing, rather than about how clearly the lecturer can be seen and heard by all students simultaneously. Working in these environments requires not a great performance lecturer; rather, these teaching environments require a professor who is an expert in the field who has rapidly accessible knowledge and can help students deepen their understanding by posing examples and counter examples of ideas to give students needed rapid feedback when they are ready for it, sometimes without warning! Only experts in the field can do this; which is why you are the expert and tasked with teaching a particular class.
For some professors, this perspective represents a giant change in thinking amounting to nothing less than a paradigm shift of epic proportions. This dramatic shift in teaching philosophy is currently referred to as a change from a professor-centered classroom to a student-centered classroom. And, if it really is a big, hairy deal; but it works. The baby-steps version of this are to break lectures up with 3-minute rest breaks using Peer Instruction, think-pair-share, clicker questions where students defend their answers to one another. Or, a bigger step is to use 10-15 minute activities to break up lecture where students wrestle with Socratic-style tutorial activities or context-rich, open-ended case study type prompts.
But, the biggest step is to flip the traditional classroom teaching model completely on its head. In the traditional model, a professor dispenses information from the front of the room and students quietly listen and take notes before going home to do actual learning through homework assignments and study groups. An alternative approach that goes all the way flips this to where professors task students with listening to video-lectures and reading the textbook outside of class and then reallocate valuable class time, nearly in its entirety, to students working in groups, solving problems, and doing learning tasks that in the old model would have been relegated to outside of class. In this way, the professor can engage student thinking while they are in the active learning process, not while they are simply listening. Such an approach puts the professor in a position to use their expertise when it is most needed; when students are struggling and actually trying to learn something. This flipped classroom approach to course design has a solid foundation in cognitive science learning principles; but, more than that, can be a highly fulfilling endeavor for the professor who is really interested in watching and supporting student learning.
For first steps toward “flipping your classroom in astronomy,” check out the TURN TO YOUR NEIGHBOR BLOG post on how to engage in the astronomy flipped classroom.
Tim Slater, Senior Fellow at the CAPER Center for Astronomy & Physics Education Research, email@example.com