Hi Michael
A student at Dickinson College would be exposed to multiple regression
and factor analysis (as the most complex analyses) but probably not in
sufficient detail to actually carry out the analyses. Occasionally a
faculty member teaches a meta-analysis class where they learn to do
their own meta analysis and conduct the appropriate analyses.
I wonder if knowing what a student learns in class is a good guide for
detecting "unmerited authorship". My lab students work with me closely
and receive individual tutoring on the appropriate analyses. They often
become very competent in the specific types of analyses that I do in my
lab and often work with me for several years. So although most of my
students would not be able to do anything more sophisticated that
correlations and ANOVA a few exceptional students do learn to do much
more than that. An occasionally I get a lab student who is also an
exceptional writer (and again is trained in my lab for several years).
So although I'm sure that unmerited authorship occurs I think it would
be really tough to pick out simply by looking at the quality of the
student's writing and statistical sophistication.
Marie
Miguel Roig wrote:
Tipsters, over the years, I have reviewed a number of papers that are
submitted to local and national conferences, as well as to other outlets of
student research (e.g., student journals, competitive awards). In many cases
you can 'hear' the student 'voice' in their writing with respect to the
various stock phrases (e.g., "many experiments show ..."), inappropriate use
of terms (e.g., utilize, prove) that we often find in student papers. You
also get a general idea that the paper is, indeed, the student's own
research by, for example, the type of topic chosen (e.g., eating disorders
is a fairly popular one), the general design of the study, and even in type
of the data analyses used (e.g., correlations, t-tests simple ANOVAs). In
sum, in those cases I have no doubts that the project was the students' own
even if I suspect that the student has received considerable assistance from
a mentor. However, in other cases, a student submission is written at a
professional or near-professional level, the literature review shows a
fairly thorough grasp of relevant issues, and the data are analyzed with
fairly sophisticated statistical techniques (e.g., hierarchal regression,
MANOVAs, ANCOVAS, structural equations). Some of these papers are of such
high quality that, frankly, one begins to wonder the extent of the student's
contribution to the paper.
I actually have some evidence indicating that some students are given
unmerited authorship (see
http://facpub.stjohns.edu/%7Eroigm/presentations/student%20authorship%20in%2
0EPA%2006.ppt). However, it is with respect to students' knowledge of
advanced statistical techniques that I now want to pick your brains. So,
here are my questions for the group: What are the most advanced data
analysis techniques that you are covered in the Statistics course offered in
your department? Does your department offer an advanced statistics course
and what areas do you cover in those courses? For both questions, a link to
a syllabus or course description will be sufficient.
TIA
Miguel
---
To make changes to your subscription go to:
http://acsun.frostburg.edu/cgi-bin/lyris.pl?enter=tips&text_mode=0&lang=english
--
****************************************************
Marie Helweg-Larsen, Ph.D.
Associate Professor of Psychology
Dickinson College, P.O. Box 1773
Carlisle, PA 17013
Office: (717) 245-1562, Fax: (717) 245-1971
http://alpha.dickinson.edu/departments/psych/helwegm
****************************************************
---
To make changes to your subscription go to:
http://acsun.frostburg.edu/cgi-bin/lyris.pl?enter=tips&text_mode=0&lang=english
