<p>Pilot
training and certification have largely remained the same since the Practical
Test Standards (PTS) were issued more than twenty years ago by the Federal
Aviation Administration (FAA). Within
the last several years, the general aviation training sector has acquired the
capability to collect and analyze digital data from certain training aircraft. With the implementation of digital
information analysis, a more accurate picture of the capabilities of student
pilots is possible. These advancements
could be used by flight instructors in the assessment process of flight
students. With the inclusion of digital
data from the aircraft, the cognitive load necessary to make an accurate
assessment of a student’s performance could be affected, ideally in a positive
manner. Cognitive load researchers
typically focus on three aspects to enhance the likelihood of success in
learning or task completion. There are
three techniques to reduce cognitive load: (a) reduce extraneous load, (b)
manage intrinsic load, and (c) optimize germane load (Young, Cate, O’Sullivan,
& Irby, 2016). The current research
project focused on the impact to the cognitive load of flight instructors who
were presented with digital information retrieved from an airplane during their
assessment of a student pilot’s aircraft landing competence, endorsement readiness
for initial solo, the willingness of the instructor to mentor the student, and
how well they liked the student pilot.
The study found that a digital condition, when presented alone, created
extraneous cognitive load and did not enable flight instructors to accurately
rate student landing performance.
Additionally, flight instructors were not able to use a combined digital
+ traditional condition to accurately assess student landing performance. When student performance was on the extreme
(i.e. ‘poor’ and ‘good’), flight instructors were better able to determine
whether or not a student was ready for a solo endorsement, but instructors did have
difficulty distinguishing an ‘average’ student from a ‘good’ performing student.
Lastly, all of the conditions presented failed
to provide the proper visualizations to allow participants to make assessments
of their willingness to mentor the students, and participants indicated that
they did not like the students presented with the digital condition. Digital visualizations from aircraft
data will require careful development in order to limit the extraneous load and
reduce the intrinsic load for student flight assessment, and should be
developed in collaboration with flight instructors to provide information to
assist the analysis of student flight performance. </p>
| Identifer | oai:union.ndltd.org:purdue.edu/oai:figshare.com:article/8041223 |
| Date | 15 May 2019 |
| Creators | Brian G Dillman (6634799) |
| Source Sets | Purdue University |
| Detected Language | English |
| Type | Text, Thesis |
| Rights | CC BY 4.0 |
| Relation | https://figshare.com/articles/AN_APPLICATION_OF_COGNITIVE_LOAD_THEORY_ASSESSMENT_OF_STUDENT_PILOT_PERFORMANCE/8041223 |
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