Repost: Active Learning is Better even if Students Don't Like It

Active learning is a set of techniques that require the student to take an active role in their learning during lecture.   Research strongly supports that students will learn more when the lecture utilizes these techniques.  And I have measured this effect in my own courses.  However, this research shows that students like lectures that use these techniques less even though they are learning more.  And I have also informally measured this, such as students who say at the end of the first lecture, "If you are going to require me to participate in lecture, I will not return".  Unfortunately, the present educational model is based on the student evaluations (primarily measuring what students like) to evaluate the quality of instruction.  Therefore perversely, this aggregate model encourages suboptimal teaching and learning.

The paper recommends then that professors take time in the beginning of the semester to demonstrate the benefits and gain buy in from the students.  And then continue to do so.  Students want to learn, so they will support this pedagogy.  And many students will recognize the value with time, if they give it.

Conference Attendance SIGCSE 2017 - Day 1

Here in Seattle, where I used to live, attending SIGCSE 2017.

Exposed! CS Faculty Caught Lecturing in Public: A Survey of Instructional Practices - Postsecondary Instructional Practices Survey (24 items), 7000 CS faculty invited, about 800 responses. If the evidence is clear that active-learning is better for instruction, then we should be doing that more. The overall split for CS was equal between student-centered and instructor-centered (exactly same avearge, 61.5). The survey showed clear differences between non-STEM (student) and STEM (instructor). So CS is doing better than its overall group.

Now, to dig into which differences there are in the demographics. The major difference in instructors is women, and those with 15 years of experience versus 30, both showing a 5+ point difference between student and instructor centered. However, 60s are still "whatever" and are not strongly committed. For those who are strongly committed, there are about 20% for each, while the remaining 60% are whatevers.

Investigating Student Plagiarism Patterns and Correlations to Grades - What are some of the patterns of the plagiarism, such as parts or all and how do students try to obfuscate their "work". Data from 2400 students taking a sophomore-level data structure course. After discarding those assignments with insufficient solution space, four assignments remained from six semesters. Used a plagiarism detector, to find likely cases of cheating.

First, even though the assignments remained unchanged, the rate of cases stayed constant. Most cases involved work from prior semesters. About two thirds of students who cheated, did so on only one assignment. Second, the rate of cheating on the individual assignments was similar to the partner assignment. Third, while students who cheated did better on those assignments, but they did not receive perfect scores and that those cheating did worse in the course than those who did not. And that those who took the follow-on course showed a larger grade difference (p=0.00019). Fourth, the analysis used the raw gradebook data that is independent of the detection and result of that detection.

Six detectors used. Lazy detector (common-case, no comments or whitespace), Token-based (all names become generic, sort functions by token length): identical token stream, modified token edit distance, and inverted token index (compute 12-grams and inversely weight how common these are). "Weird variable name" (lowercase, removed underscores). Obfuscation detector (all on one line, long variable names, etc). Fraction of total cases found by each detector: 15.69%, 18.49%, 49.71%, 72.77%, 67.35%, 0.38%.

Repost: Learn by Doing

I want to take a brief time to link to two of Mark Guzdial's recent posts.  Both including an important theme in teaching.  Students learn best by doing not hearing.  Oddly students commonly repeat this misconception.  If I structure our class time to place them as the ones doing something, rather than me "teaching" by speaking, the appraisal can be that I did not teach.  They may not dispute that they learned, but I failed to teach them.

Students learn when they do, not just hear.  And Learning in MOOCs does not take this requirement into account.

I have to regularly review these points.  So much so that I was able to give them to a group of reporters last week (part of new faculty orientation, but still).

Teaching Inclusively in Computer Science

When I teach, I want everyone to succeed and master the material, and I think that everyone in the course can.  I only have so much time to work with and guide the students through the material, so how should I spend this time?  What can I do to maximize student mastery?  Are there seemingly neutral actions that might impact some students more than others?  For example, before class this fall, I would chat with the students who were there early, sometimes about computer games.  Does those conversations create an impression that "successful programmers play computer games"?  To these questions, I want to revisit a pair of posts from the past year about better including the students.

The first is a Communications of the ACM post from the beginning of this year.  It listed several seemingly neutral decisions that can bias against certain groups.  Maintain a tone of voice that suggests every question is valuable and not "I've already explained that so why don't you get it".  As long as they are doing their part in trying to learn, then the failure is on me the communicator.

The second is a Mark Guzdial post on Active Learning.  The proposition is that using traditional lecture-style advantages the privileged students.  And a key thing to remember is that most of us are the privileged, so even though I and others have "succeeded" in that setting, it may have been despite the system and not because of the teaching.  Regardless of the instructor, the teaching techniques themselves have biases to different groups.  So if we want students to master the material, then perhaps we should teach differently.

Active learning has a growing body of research that shows using these teaching techniques help more students to succeed at mastering a course, especially the less privileged students.  Perhaps slightly less material is "covered", but students will learn and retain far more.  Isn't that better?