- Is IBL only good for the good students?
- Is IBL only good for the weaker students?
- Does lack of coverage harm students?
If you're pressed for time, the answers are "No, no, and no."
In this post I'd like to focus on dispelling a few of the myths embedded in the questions above with some data. A recently published article by Kogan and Laursen provides evidence that helps us answer these questions.
Our study indicates that the benefits of active learning experiences may be lasting and significant for some student groups, with no harm done to others. Importantly, “covering” less material in inquiry-based sections had no negative effect on students’ later performance in the major. Evidence for increased persistence is seen among the high-achieving students whom many faculty members would most like to recruit and retain in their department.
One of the findings in the paper is that the low achieving students in IBL courses did almost a half grade point better (2.41 vs 1.95) in subsequent required math courses. Basically what Kogan and Laursen did was to split the students into three groups (low, medium, high), based on prior academic achievement. Then the students took IBL and non-IBL math courses, and then Kogan and Laursen measured students' grades in subsequent required math courses. Simultaneously, the high-achieving IBL students did the same as high-achieving non-IBL students in subsequent required courses, despite being exposed to less material. It's a win-win. There is no compromise in terms of grade outcomes in subsequent courses.
The everyday way to say this is that some of the students learned to learn better, and they carried that with them. The high-achieving students do the same, and the low-achieving students (and medium-achieving students) learned to be more effective thinkers in IBL classes.
Lack of coverage: There's an easy fix to this issue that is orthogonal to IBL vs. non-IBL. Just make reading assignments, give mini lectures, or do a screen cast on your tablet to cover some topics to get the exposure of topics up to whatever level desired. The coverage issue should be a non-issue going forward, now that everyone has a smart phone or access to the internet at college.
In fact the notion that IBL courses somehow create a disadvantage/advantage is completely off the mark, and if fact it is likely that traditional instruction is guilty of creating bias and imbalances. Recent data suggests that traditional instruction can be damaging to certain subgroups, particularly women. For example, there is evidence of a gender bias in traditional courses from at least two separate data sets. What we are finding is that women are particularly disadvantaged in traditional math courses, seeing greater declines in confidence, interest in Mathematics, and persistence. This trend has statistical significance in the MAA Calculus Study (Link See David Bressoud's talk at 25:00) and in related work by Laursen's group (Link See Laursen's talk at 11:00).
Kogan and Laursen also make an interesting observation about traditional instruction vs. IBL. IBL instructors, especially the first ones in a department to try IBL, have been asked to provide justification or evidence that IBL works. This is ironic in that there is no equivalent scrutiny of traditional methods. In fact, when you consider the evidence from the past two decades, all the vectors are pointing towards active, student-centered instruction. This is the case across levels and disciplines.
All along, I have said that I'll follow the data. If the data said lecture is better, I would lecture. So far there's isn't any evidence that says this. Further, I am not wedded to a particular teaching style, but I am deeply interested in basing my teaching methodology on the best, empirically-validated evidence we have. Personally, I have never had an IBL class as a student. Ever. K thru PhD was all traditional instruction, and it worked for me. But I realize that as a mathematician I'm peculiar (more on that later). Thus, I encourage all instructors (math or otherwise) to be open to new methods and consider the implications from data gathered by researchers. By working together and being open to new ideas, we can progress faster and smarter. At the moment, IBL instructors have data that supports their work, and the data continues to pile up validating IBL.
Keep on keeping on!