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Teaching movement science with full-body motion capture in an undergraduate liberal arts psychology class

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Movement science is a field that is quickly growing in its scope, leaning heavily on psychological expertise for research design with human participants but requiring computational and engineering ability. Undergraduate psychology curricula are in a unique position to train some of its future scholars. This report reviews an attempt to pilot a class on motion capture for undergraduate psychology students. Recent developments in motion-capture technology have opened up the opportunity for giving hands-on experience with high-quality motion capture for students at liberal-arts colleges with leaner research budgets. Post-course responses to the Research on Integrated Science Curriculum (RISC) survey demonstrated that our students made significantly large gains in their ability to organise an empirical approach to study a complex problem with no clear solution, and to collect and analyse data to produce a coherent insight about that problem. Students may benefit from incorporating motion capture into their undergraduate psychology curriculum.
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*Corresponding author. Email: keltysda@grinnell.edu
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Citation: Research in Learning Technology 2018, 26: 2119 - http://dx.doi.org/10.25304/rlt.v26.2119
Research in Learning Technology
Vol. 26, 2018
ORIGINAL RESEARCH ARTICLE
Teaching movement science with full-body motion capture in an
undergraduate liberal arts psychology class
Shengwei Yaoa, Elizabeth Queathemb, David Nevillec and Damian Kelty-Stephend*
aPsychology Department, Grinnell College, Grinnell, IA, United States of America; bBiology
Department, Grinnell College, Grinnell, IA, United States of America; cCenter forTeaching,
Learning & Assessment, Grinnell College, Grinnell, IA, United States of America;
dPsychologyDepartment, Grinnell College, Grinnell, IA, United States of America
(Received: 23 July 2018; nal version received: 30 August 2018)
Movement science is a eld that is quickly growing in its scope, leaning heavily on
psychological expertise for research design with human participants but requiring
computational and engineering ability. Undergraduate psychology curricula are in a
unique position to train some of its future scholars. This report reviews an attempt
to pilot a class on motion capture for undergraduate psychology students. Recent
developments in motion-capture technology have opened up the opportunity for
giving hands-on experience with high-quality motion capture for students at liber-
al-arts colleges with leaner research budgets. Post-course responses to the Research
on Integrated Science Curriculum (RISC) survey demonstrated that our students
made signicantly large gains in their ability to organise an empirical approach to
study a complex problem with no clear solution, and to collect and analyse data
toproduce a coherent insight about that problem. Students may benet from incor-
porating motion capture into their undergraduate psychology curriculum.
Keywords: motion capture, psychology, movement science, integrated science
curriculum, inertial measurement units
Often neglected in the shadowy academic space between biomechanics, physiol-
ogyand psychology (Rosenbaum 2005), the science and technology of coordinated
bodily movement is currently coming into its own. Movement science is becoming
essential for an ageing population, for a health care industry keen to advocate phys-
ical tness as a preventative measure that is cheaper and more effective than treating
the symptoms of sedentary lifestyles and for a technological industry eager to make
machines more responsive and better adapted to our motor capacities. Movement
science will require a multidisciplinary perspective as capable to do the mathematics
of biomechanical modelling as to troubleshoot the software and hardware. Whatever
movement science learns, the translation of those insights will come in the form of
instructions or wearable technologies that need to t the human users and support the
many constraints, preferences and quirks texturing individual people’s goal- directed
movement, that is, to support a truly complex system with a personal, idiosyncratic
touch (Cavanaugh, Kelty-Stephen, & Stergiou 2017). Therefore, movement science
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will remain a solidly psychological science, and we may better serve our psychology
students by giving them exposure to this eld of research with hands-on experience
and skills. Conversely, exposure to movement science will provide students with skills
beyond what standard psychology classes might train.
Aims for the report
The goal of this article is to provide evidence that newly accessible technology for
human motion capture offers a rich opportunity for inquiry-driven science training,
allowing not only domain-specic training in movement science but also supporting
a variety of domain-general skills for an integrated science curriculum for liberal arts
students. This article documents the piloting of a class format built around content
and technology often completely absent from the curriculum and resources of a small
liberal arts class. We aim to bridge the gap between liberal arts and technical train-
ings, emphasising critical thinking across disciplines and domain-specic skills, re-
spectively. It may seem that ‘critical thinking’ is too diffuse to be valuable, and it may
equally seem that technical skills are too narrowly focused to support the growth of
a fully functioning citizen or professional employee. Newly available technology at
prices within the budget of a small liberal arts college’s research funds might allow
new expressions of the close-knit, collaborative energies of liberal arts students. The
potential here is for learning new skills in navigating complex empirical/theoretical
challenges when technology becomes sufciently accessible to fall into the hands of a
group of students typically more dedicated to training of critical-thinking skills.
Our intent is not to make an air-tight experiment demonstrating the superiority
of this format to any other comparable class format. We have used a survey standard
to a consortium of small liberal arts colleges, and we used this class format in one se-
mester amidst the service requirements for more standard class offerings. The survey
provides a pre-semester assessment and a post-semester assessment, but the sample
is small because we work at a small liberal arts college, and there is no control group
suitable to this intent because we are not full-time educational psychologists. These
limitations have drawn understandably harsh peer review, but we persist in thinking
that these results are worth sharing if only as an existence proof.
The motion-capture class
The recent release of lower cost but high-precision motion-capture technology has
opened up greater opportunities to situate motion capture in alternate class formats
(e.g. Geroch 2004; Thewlis et al. 2013), including those available to students at liberal
arts colleges with leaner research budgets. Through internal funding focused speci-
cally on developing innovative pedagogies, we were able to purchase six of Noitom’s
Perception Neuron full-body suit (less than $2000 each), and in Spring 2017, we offered
a 300-level course in the Psychology Department called ‘Motion Capture of Human
Movement’ to pilot the proposal that liberal arts psychology students would benet
from the integrated science framework prompted – or sooner demanded – by working
with motion-capture technology. We therefore anticipated that giving psychology stu-
dents the suits to work with in the classroom would be a productive, educational expe-
rience unlike what they might have expected to nd in a psychology classroom.
The format of the classroom was supercially exible in day-to-day delivery
but rmly rooted around workshop-style pedagogical principles. The supercial
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exibilities were permitted by the class size allowing for catch-up time, for remedial
redeliveries of lecture material or for class discussion. However, at the root of the
course planning was the ethos of investing student effort in repeated iterations of
inquiry-driven work. The iterations repeated a similar form, sending students from
communal to individual work and back to communal work each week: brief lecture-
like instruction with a brief reading sample would open a topic or challenge, students
would break into small groups or solo efforts to observe and discover, documenting
their observations and experiences in formal American Psychological Association
(APA) format would bring their independent or smaller group ruminations and ob-
servations into a more communal/communicative mindset, and lastly, the students
and class would come back together to share lessons learnt and reect on how the
next installment of lecture might bring new questions and discoveries into focus.
This iterative fanning-out to smaller groups and returning to the larger class group
repeated around progressively more elaborate, more abstract principles important to
the science. This iterative, inquiry-driven process has been a proven way to scaffold
undergraduate science students’ feelings of understanding and belonging amidst the
scientic culture (Di Bartolo et al. 2016; Gregg-Jolly et al. 2011, 2016; Schneider
2001; Walker and Kelemen 2010; Walker and Schneider 1996).
The rst week began with lecture on history of motion capture, brief details on how
inertial measurement units (IMUs) work and some hands-on orientation to donning
and calibrating the suit. The class also included time searching peer-reviewed literature
on movement research because the constraints of course offerings at a small liberal arts
college left most students unaware that movement itself was a topic of peer-reviewed
basic research. Roughly each week afterwards, there were weekly assignments: students
had the task of delving briey into a small research project, making their own variant
of a general concept/task, collecting a rudimentary data set, performing rudimentary
statistical and time-series analysis in the computer language R (R Core Team 2013),
and interpreting their ndings and reecting on use of the motion-capture suits as well
as the software. Their weekly assignments culminated in short narratives about the
topic of research and their experience using the motion-capture technology and the
software, noting difculties, discoveries and successes along the way.
Topics included ne-motor synchronisation to a metronome, dancing to music,
playing Dance Dance Revolution, playing Rock Band, free-throw basketball shoot-
ing, playing table tennis and target practice with bean bags or Nerf guns. The rst
three topics allowed them to practice analysing the measured time-series data to em-
pirically determine the frequency of regularly oscillating movements. The fourth topic
appeared only after the students had a week of lecture to work through basic concepts
of motor coordination, conceived as a set of phase relationships amongst joint an-
gles (Latash and Turvey 1996). Students then had to estimate not only frequency at
one limb but also task-relevant phase relationships. For instance, the game aspects of
Rock Band allowed students to generate pilot data, examining possible relationships
between phase patterns and total points scored.
Gradually, the class moved closer to more standard focuses of movement science.
A brief set of lectures introduced the notion of motor learning in terms that Bernstein
(1967) made popular, that is, an initial freezing of motor components and then, with
greater expertise, a relaxing of those limbs to open them up to reactive forces avail-
able from the context (e.g. Latash 2008). Students were all relatively inexpert in table
tennis, and so the repeated exposure to it allowed them to test hypotheses about how
practice across a week led to observable differences in phase relationships. The newly
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developed Immersive Experiences Laboratory on campus – dedicated to explor-
ing new ways to approach liberal arts pedagogies through three-dimensional (3D),
virtual- and augmented-reality technologies – offered students an opportunity to in-
vestigate motor adaptation to using virtual reality equipment, posing the intriguing
logistical challenge of exploring the mechanical compatibility of two separate pieces
of to-be-worn technology. Virtual reality also poses an altogether new question about
how movement might change as users learn to move in two spaces at once: the virtual
space of the immersive visual stimulus and the lab space whose limits (e.g.walls and
furniture) run at odds with what the virtual space invites.
The last third of the class focused on gait. Bipedal gait analysis required students
to estimate the time-averaged gait cycle (with 95% condence interval) for ankle, knee,
and hip and to estimate phase relationships under the different manipulations of
walking with eyes open or with eyes closed. Next, we borrowed from a research para-
digm that investigated intralimb coordination between dyads linked mechanically to-
gether while walking, for example, with the hands of the rear walker on the shoulders
of the front walkers (Harrison and Richardson 2009). Lastly, we encouraged students
to take the motion-capture suits across the campus to nd accessibility problems and
to examine how different constraints (e.g. walking with a crutch or with a heavy back-
pack) changed the movement coordination situated in its context.
The RISC survey
To evaluate what the students drew from this experience, in addition to consulting
end-of-course evaluations, we administered the RISC survey (Lopatto 2010) (see
the ‘Methods’ section for full details). Many of the items on the survey focused on
learning specic subject matter, and we did not expect students to have learnt many
facts; rather we expected that gains would be apparent in specically those items
addressing working in groups, working on problems without clear solutions, on
data collection/organisation and interpretation, and on using this technology and
related data to describe the complexity of human movement. The capacity of the
RISC survey or its components to measure students’ increasing dexterity with these
research skills has been demonstrated repeatedly in inquiry-driven science class-
rooms (Burnette and Wessler 2013; Call et al. 2007; Clark et al. 2009; Jordan etal.
2014; Kowalski, Hoops and Johnson 2016; Lopatto et al. 2008; Mader et al. 2017;
Makarevitch, Frechette and Wiatros 2015; Miller et al. 2013; Reed and Richardson
2013; Sarmah et al. 2016; Staub et al. 2016). We aimed to identify whether there
were post-course gains that might exceed the average of all students responding to
the RISC of that semester.
Method
Participants
The enrolment for the spring 2017 offering of the course ‘Motion Capture of
Human Movement’ at a small liberal arts college included 11 third- and fourth-year
students. The RISC survey included questions about demographics, major eld of
undergraduate study, amount of science background and plans for future science
training. The total number of students completing the RISC survey in the same
semester was 3301.
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Materials
RISC survey
The RISC survey has been developed by member schools within the Interdisciplinary
Learning Consortium (ILC), whose founding members are Carleton College, Grinnell
College, Hope College, St. Olaf College and Whitman College. RISC surveys have
been exempted from IRB review. Participation in the survey is voluntary and not a
requirement for receiving course credit, and students may discontinue the survey or
leave any questions unanswered.
A pre-course RISC survey prompts students, ‘For each [of 48] Course Element[s],
[to] give an estimate of [their] current level of ability before the course begins’ (RISC
Survey, n.d.; see selection of total 48 in Table 2). These course elements appear in list
form as verb phrases (e.g. ‘collecting data’ or ‘analysing data’) and address under-
standing the cultural values of science at large, blending concepts from more than
one eld together and engaging in science creatively with hands-on problems without
clear solutions. The pre-course RISC survey prompts students to rate their own ability
in each item on a scale from 1 (‘no experience or feel inexperienced’) to 5 (‘extensive
experience or mastered this element’). The post-course RISC survey prompts students
to ‘please rate how much learning [they] gained from each element [they] experienced
in this course’ (RISC Survey n.d.) for precisely the same list of 48 verb phrases as
in the pre-course survey and asks for ratings from 1 (‘no gain or very small gain’)
to 5 (‘very large gain’). The post-course RISC survey also asks students to evaluate
their learning gains on 21 skills normally developed in summer research experiences
(Table1). Specically, the RISC survey asks students to ‘consider a variety of possible
benets you may have gained from your course experience’ and to rate each of a list
of skills (e.g. ‘ability to integrate theory and practice’) on a scale from 1 (‘no gain or
very small gain’) to 5 (‘very large gain’).
End of course evaluations
Students lled out evaluations, indicating their agreement with each of six statements
on a scale from 1 (strongly disagree) to 6 (strongly agree). The rst ve statements
dealt specically with how well the class meetings, instructor, group activities, oral/
written exercises and readings each supported student learning, and the sixth state-
ment queried the students’ estimation of whether they had ‘learnt a lot’ in the class.
Table 1. End-of-course evaluations.
Statement to agree or disagree with Average SE
The course sessions were conducted in a manner that helped me to
understand the subject matter of the course.
5.22 0.28
The instructor helped me to understand the subject matter of the course. 5.56 0.18
Worked completed with and/or discussion with other students in this
course helped me to understand the subject matter of the course.
5.56 0.29
The oral and written work, tests and/or other assignments helped me
tounderstand the subject matter of the course.
5.33 0.24
Required readings or other course materials helped me to understand
thesubject matter of the course.
4.86 0.36
I learned a lot in this course. 5.56 0.24
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Results and discussion
Table 1 shows the average response as well as standard error (SE) on a scale from 1
(strongly disagree) to 6 (strongly agree) in response to the six statements about the
class from student’s end-of-course evaluations. Students rated the class favourably
across all items, with the lowest average rating for readings (Question 4) but with all
other responses between 5 and 6. This low point is understandable given that there
was no single text, and the students’ readings came from literature searches of peer-re-
viewed literature.
Response to the RISC survey includes both Course Element Gains and Learning
Gains. Students rate their gains on the post-course survey on a scale from 1 (least
gain) to 5 (most gain). Table 2 lists the post-course Course Element Gains for which
the present course exceeded the average for all students completing the RISC survey.
This course led students to feel they had gained most in the skills of approaching
a new problem with unknown solution, learning to plan an empirical approach in
a group and to have direct input into that plan that included collecting, analysing
and interpreting data under uncertainty using computer models to understand a
complex system.
The other Course Elements not listed here (but available through online supplemen-
tal materials) had more to do with mastery of subject-specic content. The students
did not rate other gains higher than average for the other Course Elements, perhaps
because they saw motion capture as homogeneous no matter the subject material.
While the course posed a diverse set of subject materials for applying motion-capture
technology, the instruction kept needed data organisational and data analytical tools
to a minimum so as to give students a set of tools to practice and hone without over-
whelming the students with options. Perhaps a repeat offering of the course might
include more about different approaches to analysing the motion-capture data. How-
ever, keeping the programming needs to a minimum allowed students unfamiliar with
programming to master this small number of approaches and gain more condence
in their new skills. Course Elements focused on reading primary materials, listening
to lecture and providing poster/oral presentation did not show stronger gains because
this class directed student effort mostly towards hands-on experimentation in groups,
and only written documentation. Oral presentations might make a nice addition to a
potential future iteration of the course, particularly if the students had the challenge
of developing a semester-long project around a theme of their choice.
Table 2. Gains on Course Elements reported on the post-course RISC survey.
Course element My students All students
Problems where no one knows the answer 4.50 3.31
At least one problem assigned and structured by the instructor 4.13 3.74
A problem where students have input into process or topic 4.38 3.84
Work in small groups or teams 4.00 3.86
Collect data 4.38 3.68
Analyse data 4.63 3.89
Approach problems in different and conicting ways 4.00 3.81
Present intellectual work in written papers or posters 4.00 3.54
Attempt complete understanding of a complex problem 4.00 3.72
Computer modelling of complex systems 4.00 3.26
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As for Learning Gains, students in the motion-capture class reported signicantly
higher ratings than the entire sample of RISC respondents in all but four goals (Tabl e 3).
These ratings suggest that this course was a successful attempt to train students in ap-
plying theory and technology to build their own empirical projects and to collect data
that can talk about theoretical issues. Specic learning gains included interpretation
of results, integrating theory into practice, understanding how scientists work on real
problems and surmounting obstacles in a communal process, ability to analyse data
and synthesise disparate sources of information. The experience gave students better
command of scientic communication and of their ability to teach the science that
they had learnt. It was also a helpful experience in helping students understand science
in general, as a social process in which multiple voices work to construct knowledge in
a social process that leaves room for independence while also affording group work in
the search for new evidence and/or better solutions to pressing problems.
Not all learning gains were better in this class than in other classes. Ethical issues
may not have t organically with the rest of the class business, but future offerings of
this class could attempt it. The other items with lower ratings were not part of original
goals for the class; therefore, they highlight room for development of the course rather
than shortcomings.
Detailed reections and example of student experiences
The course necessarily involved a uid, context-sensitive format in which students regu-
larly discovered previously unknown constraints as well as unknown capacities. We see
Table 3. Learning Gains, ranked from highest to lowest in my class and compared to all
SURE-item respondents.
Learning gains My students All students
Skill in the interpretation of results 4.25 3.46
Ability to integrate theory and practice 4.25 3.45
Understanding of how scientists work on real problems 4.25 3.58
Ability to analyse data and other information 4.13 3.62
Tolerance for obstacles faced in the research process 4.00 3.47
Understanding the research process in your eld 4.00 3.44
Understanding science 4.00 3.50
Becoming part of a learning community 4.00 3.49
Understanding that scientic assertions require supporting evidence 3.88 3.55
Learning laboratory techniques 3.88 3.39
Understanding how knowledge is constructed 3.75 3.40
Skill in science writing 3.75 3.24
Self-condence 3.75 3.74
Learning to work independently 3.75 3.25
Readiness for more demanding research 3.63 3.40
Understanding of how scientists think 3.63 3.34
Condence in my potential as a teacher of science 3.25 2.89
Learning ethical conduct in your eld 3.25 3.32
Ability to read and understand primary literature 2.83 3.29
Skill in how to give an effective oral presentation 2.50 3.12
Clarication of a career path 2.38 3.01
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some of this in the strong learning gains in the understanding of the scientic process
and learning to apply theory, while also learning to tolerate obstacles. Asan illustrative
example, one pair of students struggled with the motion-capture suit failing to function
as usual 1 day. These two students took the occasion to debug the problem – indeed,
they might not have recognised their efforts as debugging, but they were discovering
their very own principled manner of testing the functioning of subparts. These two
students – relatively untrained in programming or engineering – were able to isolate the
specic part of the suit that had broken, and furthermore, they discovered a exibility
in the motion-capture system that allowed alternative connections around the broken
portion, that is, patching a work-around that allowed typical motion capture through
most of the suit. Motion-capture research can be peppered with unanticipated and un-
clear technology failures that can and do frustrate professional researchers and require
letting participants go without any successful data collection. This debugging served as
only one among many exercises in problem solving that the students experienced.
Practiced scholars in movement science elds have taken that patient diligence
on as a second nature. Behind this illustrative case of experience with debugging is a
crucial point. Liberal arts students may often feel insecure and unable to wield tech-
nology as anything more than an end-user swiping a touch screen, and there has been
much clamour and controversy about the value of a liberal arts education as con-
trasted with more vocational training in technical skills (e.g. Breneman 1994). But the
dichotomy between liberal-arts values of learning how to learn in any context and
vocational values of honing technical skills with digital technology may just be a false
dichotomy (Grubb and Lazerson 2005; Selingo 2016). There is an opportunity not
only for greater skill with digital technologies but also for metacognition about how
critical thinking really will transfer to tasks that do not look like traditional liberal
arts. In other words, digital technologies such as motion capture may be a ready vehi-
cle for liberal arts lessons.
Overall, this project was a productive and instructive early effort. The initial re-
sults suggest that a motion-capture laboratory ts well with the aims and constraints
of a small liberal arts college setting.
Acknowledgements
We acknowledge the support of Grinnell College Psychology, Grinnell College
Immersive Experience Laboratory and the Grinnell College Innovation Fund.
Ethics, consent and permissions
This article documents data from the Research on Integrated Science Curriculum
(RISC) survey, for which participation is voluntary and exempted from Institutional
Review Board (IRB) review. The RISC survey is administered by the Center for
Teaching, Learning and Assessment (CTLA) at Grinnell College, and the CTLA reg-
ularly consults with Grinnell College’s federally compliant IRB to ensure ethicality of
continued data collection.
Permission to publish
All participants consent before completing the RISC survey to contributing their
responses to the Grinnell College CTLA for research and publication purposes.
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TheCTLA aggregates individual student responses into whole-class data summaries,
and instructors whose students complete the RISC survey (e.g. the authors) receive
this information only in terms of whole-class data summaries but receive no individ-
ual student responses. Hence, this article only reports on class-data summaries and
does not document any individual student responses. Indeed, while the authors pos-
sess no information on individual student responses, all individual student responses
remain secure in the records of the CTLA.
Competing interests
The authors have no competing interests with regard to the publication of this article.
Grinnell College is a non-prot institution.
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