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<pre>
  Workshop on Non-Cognitive Factors &
  Personalization for Adaptive Learning
                (NCFPAL)
Many computer-based learning environments adapt to individual learners based on
cognitive factors like skill mastery, but recently research has been increasingly directed
at improving personalization and adaptation in such systems by harnessing non-
cognitive factors such as learner affect, motivation, preferences, self-efficacy, self-
regulation, and grit. This workshop brings together researchers studying non-cognitive
factors in a variety of environments and contexts, using various experimental,
measurement, and/or data mining and statistical methods. In addition to presenting on-
going research on specific non-cognitive factors and their impact of learning outcomes,
speakers at the workshop will present various creative approaches to address
methodological issues endemic to research on non-cognitive factors.

Of one invited paper and five accepted papers, three papers explore non-cognitive
factors in intelligent tutoring systems (ITSs) used in K-12 schools. Walkington and
collaborators, in an invited paper, provide an account of various text-based features of
mathematics word problems that are associated with learner performance in ITSs
(specifically, Carnegie Learning’s Cognitive Tutor). While explanations that point to
both cognitive and non-cognitive factors may account for this association, Bernacki and
Walkington follow up this observational study by exploring an intervention in the same
ITS wherein word problems are personalized based on learners’ out-of-school interests
in areas like sports and music and find that personalization has benefits for both
learner interest and measures of learning. A third study by Ostrow and colleagues
considers an intervention in the ASSISTments system in which learners were
presented with different types of “growth mindset” motivational messages (e.g.,
animations, audio, etc.). The impact of these messages on measures like persistence
and learning are considered.

The next three papers consider data from college-level courses and learners. Ezen-
Can and Boyer present an unsupervised method for classifying dialogue acts (e.g., ask
a question, give a command) when learners interact with (human) tutors in a text-based
dialogue environment; their method leverages gender and learner self-efficacy as
noncognitive factors along which sub-populations of learners can be identified so that
dialogue acts can be better classified. Next, Moretti and colleagues mine data about
university computer science courses that are publicly available on the web to determine
factors (e.g., choice of programming language and grading criteria) that are associated
with learner feedback and other aspects of instruction. Finally, Gray and colleagues
provide an analysis, using both classification and regression methods, of various
psychometric measures of non-cognitive factors as predictors of whether students are
“at risk” or likely to fail in their university courses.

The papers that comprise these proceedings represent a diverse set of measurement
and analytical approaches and of student populations and learning platforms to which
they are applied. We take this as a sign of developments to come, especially as
researchers and developers in the learning sciences, educational data mining, and
learning analytics increasingly turn to non-cognitive factors as possible “levers” to
adapt and personalize learning experiences in more and more sophisticated
technology-enhanced learning platforms and environments.
We gratefully acknowledge the following members of the workshop program
committee:
      Vincent Aleven, Carnegie Mellon University
      Ryan S.J.d. Baker, Columbia University
      Matt Bernacki, University of Nevada, Las Vegas
      Alan Drimmer, Apollo Group, Inc.
      Andrew Krumm, SRI International
      Timothy Nokes-Malach, University of Pittsburgh
      John Stamper, Carnegie Mellon University
      Candace Walkington, Southern Methodist University
      Michael Yudelson, Carnegie Learning, Inc.


                                              The NCFPAL workshop organizers
                                                                 Steven Ritter
                                                           Stephen E. Fancsali

</pre>