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University, at a time before Pokémon Go
was released to the public and became the
most-downloaded app of all time (GSA
Data Repository1 expanded methodology;
http://idias.usu.edu/; Shelton et al., 2012).
For each AR field trip the entirety of
Grand Canyon has been scaled down to a
100 m playing field. The absolute geo-
graphic location of the player does not
matter; however, because GPS is inte-
grated into the application, the module
must be played outside (Fig. 1). The design
takes advantage of the benefits of games
that provide immersion-in-context,
rewards for correctness, and immediate
feedback in response to student interac-
tion. Each module takes ~20 min to play, a
length of time aimed to fit within a wide
range of class types and capture the typical
student’s attention span (Middendorf and
Kalish, 1996; Milner-Bolotin et al., 2007).
This study uses three fundamental geo-
science topics that can easily be explored
within Grand Canyon as the basis for the
AR field trips: (1) geologic time, (2) geologic useful, and important the course content is
structures, and (3) hydrologic processes.
For all three AR field trips the stops run
downstream from Lees Ferry to Lake Mead
with photographs, videos, questions, and
interactive touchscreen activities (Table 1).
As of 2016, these applications (called GCX
Geologic Time, GCX Geologic Structures,
and GCX Hydrologic Cycles) are available
on both Android (Google Play) and iOS
(App Store) platforms.
METHODS
Participants
Students at three educational institutions
completed all three AR field trip modules
to provide data for analysis (n = 391).
Students at a fourth school completed
two modules (n = 138), and students at a
fifth school only completed one module
(n = 319). Finally, additional students at
two of the schools (n = 291) acted as con-
trol subjects, completing the pre- and post-
tests and surveys for their regular labs
without participating in the AR field trip
modules. All of the classes utilized in this
study were traditional lecture-based
courses with accompanying labs. The data
set overall represents diverse demograph-
ics and institutions (classed as teaching
focus, teaching-research split, and research
1 GSA Data Repository Item 2017056, expanded description of methodology, statistics, and geoscience interest survey, is online at http://www.geosociety.org/
datarepository/2017/.
Figure 1. Students play “Grand Canyon Expedition: Geologic Time” on the campus quad. Insets (left
to right) are screen shots of the base map with visited locations (orange) and new location (green),
and a screen shot of the Great Unconformity at Blacktail Canyon video, information, and question.
focus), reported in Data Repository Table interest: interest in the subject residing
S1 [see footnote 1]. within the individual prior to taking the
course; and situational interest: emerging
Interest Index spontaneously in response to exposure in
the environment) have been validated by
All students, including intervention and the educational psychology field, and have
control groups, completed a demographics been adapted to suit the geosciences
survey, geoscience content questions (for (Pintrich and DeGroot, 1990; Pintrich et
the student learning component of this al., 1993; McConnell et al., 2006, 2009;
research, not reported in this paper), and McConnell and van Der Hoeven Kraft,
the Geoscience Interest Survey. The evalu- 2011; Harackiewicz et al., 2008; van der
ation instrument (the GeoIS) was used at Hoeven Kraft et al., 2011; Gilbert et al.,
the beginning of the semester and then 2012). The MSLQ has robust reliability
after all interventions were complete. The data with prior studies and has both pre-
GeoIS is a modified subset of the Motivated dictive validity and construct validity in
Strategies for Learning Questionnaire the form of a confirmatory factor analysis.
(MSLQ) using the task value component
subscale and the situational interest sub- Two main research questions guided the
scale; see Data Repository Figure S1 [see analysis of data: (1) How do these AR field
footnote 1]. The MSLQ subset that com- trips impact student interest in learning
prises the GeoIS evaluates how interesting, geoscience material? and (2) Which
demographic and experiential factors
to the student, and should relate to student combined with the AR field trips best
engagement by assessing changes in inter- predict student motivation and interest to
est post-intervention (Pintrich et al., 1991; learn geoscience material?
Harackiewicz et al., 2008). Motivation self-
report subscales used to measure value DATA ANALYSIS AND RESULTS
beliefs (intrinsic goal orientation, extrinsic
goal orientation, and task value beliefs) The data analysis used three steps:
and self-report interest subscales (individual (1) determining reliability and validity of
the data, and generating a correlation
www.geosociety.org/gsatoday 5