Although we all wish it were otherwise, your students have every reason to assume you’re not really coming to class each day to help them learn or that you will actually follow an obviously organized pathway to get them there.
This is due in part to students having had more than a decade of learning experiences before taking your class, some overwhelmingly positive, and many others not so much. Your students are also probably taking several other classes during the same semester you’re teaching them. It will be useful to you if you are compassionately sensitive to the fact that college students have numerous distractions and requirements across different professors in disconnected courses with contrasting demands adding to their long-history of widely varying school-learning experiences.
That’s a lot to consider, and there is a whole lot more to teaching science than standing at the front of the room and accurately saying all the right words in front of pretty pictures; if that is all that was required, we’d simply hire out of work Hollywood actors to stand and deliver information. Colleges don’t hire actors to teach because it turns out that your scientific expertise is a vitally necessary condition to successful teaching if you have to goal of helping your students to love science. But, although your scientific expertise is necessary, it isn’t sufficient by itself. There are lots of highly knowledgeably people who can’t teach their way out of the proverbial wet paper sack.
In the day-to-day scientific enterprise, we often encounter complex systems with numerous, interacting variables. When this happens, we often organize our thinking into a model that can be used to test ideas and make predictions. In much the same way, we can apply this powerful idea of using models to manage some of our science teaching-decisions and make some predictions about which teaching approaches will likely work and which are probably doomed to fail a priori. Let’s consider a model describing the variables of student motivation about loving science.
Stephanie Slater from the CAPER Center for Astronomy & Physics Education Research has helped me understand that scientists sometimes think that motivation is a vaguely vague thing, but there are highly-respected scholars from the opposite side of campus who have thought carefully about motivation. These scholars, along with Stephanie, describe student motivation toward learning something as a robust mixture of three distinct things: (i) is there value in the task, (ii) what is the probability of success, and (iii) is there supportive help available? Let’s consider each of these in turn.
Value The first component of motivation to learning something is based on an assessment of value. In other words, students ask themselves, “does this class help me meet my goals? Students’ first answer might be related to intrinsic value of education and the wonders of the universe, but more than likely not. Unless you rationally and intentionally convince students otherwise, their values naturally are inclined to meeting social goals, graduation goals, career goals, and the like. If you want students to have different motivation stemming from something else they should value, then you as the professor will need to put in purposeful effort to change the value-proposition. To be blunt, the position that students should enter college already valuing science and that professors’ have no responsibility to change students thinking is academically pleasant, but naively foolhardy.
Perhaps unintentionally, too many professors do precisely the opposite of selling their course’s value to students. The fastest way to reduce the “value” a student sees in your class is to put your class in conflict with things that the student values more: their graduation, their job, their kids or their family. This might surprise you because you might not have noticed that college today is vastly different that the college’s we went to. Remember only about 15% of college students nationally are traditional, non-working, dorm-living, college-aged students. If you have an attitude that your lecture is more important than other values students have—whether or not you agree with those values—you’re going to reduce their motivation. Fortunately, there are easy-to-implement tactics available to you to instead increase the perceived value of your course.
Probability of Success The second component of motivation to learning something is based on a student’s calculation of the probability of learning science in your class. In other words, students ask themselves, “Can I do this thing that I have to do for this class?
Many of your students have had less than successful experiences in the past with science courses, and perhaps more detrimentally, in mathematics courses. Perhaps some of your students were forced to participate in a K-12 science fair and none of their plants grew, resulting in them thinking science isn’t for them. Maybe some of your students struggled with their pre-algebra class and gave up on the possibility of being successful in courses that feature numbers and arithmetic a long, long time ago. You might find that you need to make sure you class doesn’t look anything like unsuccessful experiences your students have had in the past. One time-tested strategy to efficiently convince your wary students that this science class is going to be yet another unsuccessful and unpleasant experience is to emphasize the importance of strictly using unfamiliar metric units in the seemingly complex mathematical formulas of science on the very first day of class.
Availability of Supportive Help The third component of motivation to learning something is based on a student’s assessment of if there is help and support in learning science. In other words, students ask themselves, “Is the professor going to help me learn this?” and “Is there an organized course structure that will help me learn this?
I am still astounded at the number of professors who proudly tell me that they always explain to their students on the first day of class that about 1/3 of their students drop their class. This is reminiscent of the age-old story of professors trying unsuccessfully to motivate their students to work hard in their class by instructing their students to look first to their right, and then to look to their left, and then informing students that by the midterm exam, one of them will no longer be in the class. The problem is that this approach works really well: Many students naturally give up before they even start.
Instead, knowledgeably professors know that their students are making this calculation and purposefully build their entire course organizational structure around supporting student-success. To the uninformed professors who haven’t read this book, they might naively think that professors interested in student motivation are simply dumb-ing down their courses or catering to students by making things less than rigorous. The problem is that unmotivated students simply don’t learn. These students also appropriately give professors lousy course evaluation scores. In stark contrast, professors who explicitly organize their course based on supporting students’ learning are more than half-way toward becoming an award-winning astronomy teaching guru. The hidden secret that no one says out loud is that building a highly organized course makes life profoundly easier on busy professors too.
Tim Slater, University of Wyoming, Tim@CAPERteam.com
Suggested Citation: Slater, T. F. (2018, October). Is it possible to motivate non-science students? Society of College Science Teachers Blog, 4(3), https://www.scst.org/blog
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