<div dir="ltr"><div><div> A name has come to mind that is probably the name of the ETS researcher I mentioned to Ken re efforts to predict the difficulty of math test items -- Isaac Bejar (pronounced Behar). Probably there were other such efforts at ETS for obvious reasons. However, that work did not involve cognitive modeling.<br>
</div> Frank Ritter's response reminded me that David Kieras (quite possibly in collaboration with Bovair) did some very impressive work on transfer of training operational procedures for a mythical machine. Very precise prediction of learning times in relation to order of training and overlapping production rules was achieved. I used graphs showing these results in briefings at ONR to impress the physical scientists and engineers that we really were doing SCIENCE.<br>
<br></div>Susan Chipman<br></div><div class="gmail_extra"><br><br><div class="gmail_quote">On Tue, Apr 29, 2014 at 6:30 AM, GUNZELMANN, GLENN F DR-03 USAF AFMC 711 HPW/RHAC <span dir="ltr"><<a href="mailto:glenn.gunzelmann@us.af.mil" target="_blank">glenn.gunzelmann@us.af.mil</a>></span> wrote:<br>
<blockquote class="gmail_quote" style="margin:0 0 0 .8ex;border-left:1px #ccc solid;padding-left:1ex"><br>
Here's a paper that looks at different types of problems in the Tower of<br>
Hanoi that vary in difficulty, with a model that predicts exploratory/final<br>
path behavior:<br>
<a href="http://palm.mindmodeling.org/~glenng/pubs/journalarticles/2003-gunzelmann_an
derson.pdf" target="_blank">http://palm.mindmodeling.org/~glenng/pubs/journalarticles/2003-gunzelmann_an<br>
derson.pdf</a><br>
<br>
Here's a second, with a model with three different strategies, one of which<br>
accounts for performance across seven different instrument-flight maneuvers<br>
of varying difficulty in a UAV simulation:<br>
<a href="http://palm.mindmodeling.org/~glenng/pubs/journalarticles/2010-myers_gluck_g
unzelmann_krusmark.pdf" target="_blank">http://palm.mindmodeling.org/~glenng/pubs/journalarticles/2010-myers_gluck_g<br>
unzelmann_krusmark.pdf</a><br>
<br>
Finally, in case it is relevant when task difficulty varies as a function of<br>
the individual's state (i.e., well-rested versus sleep-deprived), this one<br>
looks at errors (and RT) in a simple addition/subtraction task:<br>
<a href="http://palm.mindmodeling.org/~glenng/pubs/journalarticles/2012-gunzelmann_mo
ore_gluck_dinges.pdf" target="_blank">http://palm.mindmodeling.org/~glenng/pubs/journalarticles/2012-gunzelmann_mo<br>
ore_gluck_dinges.pdf</a><br>
<span class="HOEnZb"><font color="#888888"><br>
-Glenn<br>
</font></span><div class="im HOEnZb"><br>
<br>
-----Original Message-----<br>
From: ACT-R-users [mailto:<a href="mailto:act-r-users-bounces@ACTR-SERVER.HPC1.CS.cmu.edu">act-r-users-bounces@ACTR-SERVER.HPC1.CS.cmu.edu</a>]<br>
On Behalf Of Ken Koedinger<br>
Sent: Monday, April 28, 2014 9:50 AM<br>
To: <a href="mailto:act-r-users@ACTR-SERVER.HPC1.CS.cmu.edu">act-r-users@ACTR-SERVER.HPC1.CS.cmu.edu</a><br>
Subject: [ACT-R-users] Ref for empirical tests of cognitive models by<br>
predicting task difficulty<br>
<br>
<br>
</div><div class="HOEnZb"><div class="h5">I'm looking for references for the following statement and figure the ACT-R<br>
community may have some:<br>
<br>
"One way to empirically evaluate the quality of a cognitive model is to test<br>
whether it can be used to accurately predict differences in task<br>
difficulty."<br>
<br>
I'm particularly interested in references to models that predict error rates<br>
(but reaction time prediction is ok too) across a number of related tasks.<br>
Models that predict errors at steps in tasks and/or specific strategy or<br>
error differences are even better. One such reference is our own tech<br>
report below -- see constraint C3 in Table 1.<br>
<br>
Koedinger, K.R., & MacLaren, B. A. (2002).Developing a pedagogical domain<br>
theory of early algebra problem solving.CMU-HCII Tech Report 02-100.[PDF<br>
<<a href="http://pact.cs.cmu.edu/koedinger/pubs/Koedinger,%20McLaren%20.pdf" target="_blank">http://pact.cs.cmu.edu/koedinger/pubs/Koedinger,%20McLaren%20.pdf</a>>]<br>
<br>
Others? Including your own work?<br>
<br>
Thanks!<br>
Ken<br>
<br>
<br>
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<br></blockquote></div><br></div>