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Here's my understanding of the agreements / decisions / announcements
from last night:
(a) Course evaluation
80% your
seminar (if you present twice, I'll take both into account)
20% participation
in seminars of others
homework
(not for credit, but I will take it into account at your request for participation
credit)
(b) Topic scheduling
A seminar topic requires AT LEAST two weeks of work. I suggest that you
start working on your topic sooner than that. What I am saying is that
we have to coordinate in advance.
- Tuesday or (at the very latest) Wednesday MORNING, one week before
your seminar, meet with me to review your seminar material and agree
on the reading assignments for next week
- Tuesday (or at the very latest) Wednesday BEFORE class, email your
reading assignments to the class.
- Wednesday, one week before your seminar. If you are handing out papers
to read, print them and bring them to this class
- Thursday or Friday before your seminar -- do a practice run privately
with me, especially if you are inexperienced with seminars. I will make
suggestions for improvements. My goal is a polished presentation on
the day of your seminar, for which I will gladly give you a good mark.
NOTE: I WILL NOT DESIGN YOUR SEMINAR FOR YOU. THE DEPTH OF SUGGESTIONS
THAT I GIVE WILL VARY BASED ON THE QUALITY OF YOUR STARTING MATERIAL.
IF YOU START WITH WEAK STUFF, AND DO EVERYTHING THAT I SUGGEST, THAT
MIGHT ONLY BRING YOU UP FROM A "D" TO A "C".
- Wednesday -- seminar.
(c) Topic assignments so far
Jan 23 Research
papers part 2 -- becky
Standards
for Ph.D. and M.Sc. -- Cem with help of Lucia, Ramon, Giri and Jiahui
Jan 30 Sampling
techniques -- Amit
Feb 6 Case
studies -- Pat
Feb 13 Ethics of research -- Tim
Feb 20
Feb 27 NO CLASS
March 6 NO CLASS
March 13 Interviewing
skills -- Helayne
March 20 Probably,
interviewing skills follow-up (Cem & ???)
March 27
April 3
April 10
April 17
April 24
May 1 NO
EXAM
(d) Assigned but no date yet
Basic statistics review (includes basic hypothesis testing, descriptive
stats, fitting equations to data and how to lie with statistics) Pat.
- Note on the stats review that much of it will be reference to the
course text, Fraenkel & Wallen. If there is a live presentation,
it will be half a class and will focus on how to lie with statistics.
Measurement -- Nadim
Survey design -- Ramon
Demonstrative research -- Giri
Model-based research -- Lucia
Threats to validity - Ibrahim
How do I know when my project is in trouble? Attila
(e) Not yet assigned, but important
topics
Typical quantitative experimental designs
Narrowing and focusing a research topic
More research papers (review / evaluate)
Control of variables in experiments
(f) Additional tasks
Preparing reference lists that adapt Fraenkel / Wallen to the computing
context. I'll call for volunteers.
========================================
"An eye for an eye makes the whole world blind"
--- Mahatma Gandhi.
Cem Kaner
Professor of Computer Sciences
Florida Institute of Technology
www.kaner.com
www.badsoftware.com
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