Statement on Teaching
Philosophy
Subbarao Kambhampati
The lecturer should give the
audience full reason to believe that
all his powers have been
exerted for their pleasure and instruction
--Michael Faraday
Of
the many comments I had received from my students in my teaching career, the
ones that I treasure most are those that go:
“His courses are demanding and I had to work much harder. But, I
learned more.” I am gratified by such comments because I believe that
learning is great fun -- but not as a spectator sport. As my teaching portfolio
shows, my courses are very demanding both on my, and my students’ time. As a teacher, I see my primary duty as using
my talents (if any) to make the demanding courses also “fun” and engaging
courses. I try to accomplish this in
several ways.
I work hard in designing my courses,
updating them significantly every time I teach them. I go out of my way to showcase my own
enthusiasm for the subject that I am teaching. I use many techniques—humor,
off-the-wall analogies, interaction, catchy visual aids—to keep the classes
lively. I provide multiple open
communication channels to my students.
I use the Web, the class homepage and e-mail lists extensively to keep
in touch with my students' minds even when they are not in the class
room. I provide the students many and
varied opportunities to demonstrate their mastery of the material. Finally,
using the Web and other electronic means, I give the students several opportunities to provide anonymous
feedback on the conduct of the course during the semester.
My methods seem to work reasonably well
for me. Despite the reputation my courses have acquired of being challenging
and demanding, I have consistently
received good teaching
evaluations. I have even been nominated
three times for the CEAS teaching awards. In the following, I will briefly
describe some of the teaching practices that I found particularly effective
over the years.
Teaching: First and foremost, I do everything possible
to showcase my own enthusiam for the subject that I am teaching. As a somewhat
quixotic example of this, on the first day of class for CSE 471 (Introduction
to Artificial Intelligence), I always start with a catchy multi-media
motivational presentation (with background music—2001 Space Odyssey
soundtrack—and the works).[1] Amateur though this exercise might be, it
never fails to get the point across to the students—that I am mighty
smitten by the subject I am teaching.
By
keeping up with the state-of-the art research, I continually revise my course
materials and keep them current. I also attempt to connect the material being
taught to the material they would have learned in the past, as well as the many
places in which they will be using it in the future. I use the computer mediated class room capabilities in novel ways
to develop effective and up-to-date overhead slides.[2]
The lectures themselves use a judicious mix of prepared overheads, and
impromptu white-board explanations. I also keep the lectures very interactive,
focusing not only on the “How” but also on the
“Why?” aspect of the material being taught. As an example, I would
always bring up a naïve algorithm for solving a problem before presenting a
more efficient way.
Grading/Evaluation: In all my classes at least 50% of the grade depends
on the work that the students do outside the class room—including projects and
homeworks. I set my project and homework assignments so that they have a strong
flavor of design and analysis. My common exhortation to the students is “in
other classes, you may be done when
your program works. But, over here, a
working program is just the first step to the much more important analysis
phase”. I provide students multiple avenues for showing me that they have
mastered the material. Most projects have significant extra credit portions[3]
that the students can do to make-up for any shortfall in the exam scores. As a rule, I prefer giving take-home
examinations as they, while more time-consuming to set and evaluate, are better
at testing the students’ understanding. Even when I give in-class exams, I
offer the students a chance to take a copy of the in-class exam home and answer
it again in a more relaxed setting. Both the in-class and the at-home versions
of the exam are graded and a weighted average is taken as the grade.[4]
The idea of letting students work on the exam at home has turned out to be a
very useful way of motivating students to understand the mistakes they made
under time-pressure, and to correct them. Finally, and perhaps more importantly, I expend significant effort in
setting my exams and projects so that they are engaging and entertaining,
in addition to being instructive and evaluative.[5]
Communication: I view the course
as a semester long contract with the students, rather than as a twice-weekly
contact with them. I see class room as
just the beginning of my contact. I use the class mailing lists to keep in
continual touch with my students. The mailing list is used both to respond to
requests for clarification, and also—in many instances—to add to or elaborate
on the material discussed in the class. For example, the mail archive for CSE
471 (taught in Fall 2001) contained 158 messages and the archive for CSE 494
(taught in Spring 2001) contained 166 messages. The courses all have very
comprehensive web sites, that contain all the course-related
information—including all the homeworks, examinations, lecture notes,
handouts as well as pointers to any
additional reading material.
Feedback/Monitoring: I
provide my students several opportunities to give me feedback on the way the
course is going during the semester. At approximately 6-8 weeks into the
semester, they are offered a chance to give structured feedback.[6] The feedback is done online and anonymously.
I discuss the results of these surveys in the class and make any necessary
fine-tuning adjustments. In addition to this, throughout the semester the
students have an opportunity to send me anonymous[7] full-text messages.[8] At the end of each semester, rather than me
doing a dry review of the topics I thought I covered, I conduct an “interactive
review” session where the students share with the rest of the class the topics
they found most and least interesting.
Graduate
Student Mentoring: If I have been successful in my research
program at ASU, it is to a large extent thanks to the quality of graduate
students I have had the pleasure work with. I have always spent a considerable
time recruiting high-quality students into ASU graduate program (and my lab). Every student working with me is supported
by my research grants. I attempt to
inspire/encourage my graduate students in many ways, including getting them
into contact with researchers at other schools, and supporting their travel to
national conferences. All my MS and
Ph.D. students are encouraged to do research that is publishable in high
quality conferences and journals. I
have 54 technical publications co-authored with my students—including 6 journal
articles and 30 papers in rigorously
refereed conferences. This track record has brought significant international
recognition to my research group as a whole.
Four students completed their Ph.D. and
eleven students completed their Masters degrees under my supervision. One of my Ph.D. students, Amol Mali, is a
tenure-track faculty member at University of Wisconsin-Milwaukee. Another
student, Biplav Srivastava, is with IBM Research Labs, India. I am currently
advising seven students—five in the Ph.D. program and 2 in the M.S. program.
Two of the five Ph.D. students completed their proposals.
Pedagogical
Activities outside the Classroom: The specific ways of teaching
particular topics that I develop in the classroom often make their way into
tutorial and survey papers. As an example, I have written several tutorial
articles, and delivered two well received tutorials on automated planning—based
to a large extent on the notes I developed in my graduate level courses. Cora, a Computer Science research paper
search engine[9], lists six
of my survey papers among the top ten influential survey papers in automated
planning. I am currently involved in writing a textbook on the foundations of
automated planning and scheduling.
[1] Slides from the most recent presentation are enclosed along with CSE471 material.
[2] Sample lecture slides from CSE471 enclosed in the portfolio
[3] The grade-cutoff is determined without looking at the extra credit points. However, the student’s grade is determined by comparing his/her cumulative marks (including the extra credit portion) to the grade cutoffs. This way, students who do extra credit work are rewarded without penalizing those students who did not use the extra credit option.
[4] The usual weights are .66 for in-class and .34 for at-home. If the student doesn’t do the exam at home, their marks on the in-class version stand. Specifically, the score is max(in-class score, [.66*in-class-score+.33*at-home-score]).
[5] Sample projects and exams enclosed in the course portfolios
[6] Examples from CSE471 and CSE494 are enclosed
[7] Full anonymity is ensured by having the students access the feedback page through anonymizer.com
[8] A few examples of such messages are enclosed