A COMPENDIUM OF SCALES for use in the SCHOLARSHIP OF TEACHING AND LEARNING

example, McCabe (2015) examined the extent to which there is a generation effect for learnercreated
keyword mnemonics and real-life examples when learning neuroscience material in the
introductory psychology course. This research is certainly appropriate for teachers of
Introductory Psychology.
Daniel and Chew nicely described what they (and I) see as a divide between SoTL and learning
sciences, with researchers tending to fall into one camp or the other, but rarely overlapping,
despite the enormous desirability and potential for such overlap. In many ways, I see this divide
as similar to the notion that researchers tend to get classified, rightly or wrongly, as either
“basic” researchers or “applied” researchers (with the former typically being perceived as
“better” researchers). Many perceive that there is often no middle ground, which I believe
hinders the progress of both types of research.
Much like the divide between personnel selection and personnel evaluation researchers, or the
divide between basic and applied researchers, the divide between SoTL and learning sciences
researchers is, in my opinion, unfortunate. I believe that this e-book is a large step toward
bridging this divide between the learning sciences and SoTL researchers. Indeed, much of the
information it contains, particularly in Gurung’s (2015) and Wilson-Doenges’ (2015) chapters, is
actually rooted in the learning sciences. For example, in chapter 2 of this e-book, Gurung listed
10 different scales that could be useful in SoTL research. In reality, all but two of these scales
(the Lifelong Learning Scale and the Textbook Assessment and Utility Scale) are rooted in basic
individual differences research. Specifically, researchers in the learning sciences have long
tended to use scales that have undergone extensive psychometric work. For instance, the Need
for Cognition Scale (Cacioppo, Feinstein, Jarvis, & Petty, 1996), which received a great deal of
psychometric evaluation, has been used extensively in learning sciences research. At the time
of publication of this chapter, a quick PsycINFO search on “need for cognition” and “learning
science” revealed 46 hits in the past three years, with articles appearing in a broad spectrum of
journals, such as Learning and Individual Differences, Computers in Human Behavior, Creativity
Research Journal, and Psychology of Women Quarterly. A similar search with “scholarship of
teaching and learning” substituted for “learning science” revealed but one hit. Of course, this
examination relies on a sample of one. However, when I review for journals such as the ones
listed previously, it seems as though using psychometrically vetted measurement tools is an
expected practice.
In Chapter 5, Wilson-Doenges (2015) describes the current state of psychometric work on SoTL
scales. As she notes, such work is becoming more prevalent and more rigorous in SoTL in recent
years. It is essential that such work continue and be displayed in prominent SoTL outlets. SoTL is
to applied research what the learning sciences are to basic research. This should not be a
problem; however, extending the (what I believe to be grossly inaccurate) perception that basic
research is more scientific and rigorous that applied research, SoTL work may be perceived as
inferior to work in the learning sciences.
Why might psychometric issues receive less attention in SoTL work than in learning science
work? I can offer only two reasons, and both are purely speculation. First, perhaps because of
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