Page 206 - Contributed Paper Session (CPS) - Volume 6

CPS1883 Christina A. et al.
3. Application of the Flipped Classroom Approach
For many years, the course Multivariate Data Analysis was taught as a
traditional classroom course, consisting of a mixture of theory lectures and
computer-based exercise sessions. In order to facilitate for the students to
combine studies with work and family life, i.e. a usually busy schedule, the
course has in later years been taught as an online course. The first time the
course was taught online, this was done as a blended learning approach, i.e.
the course contained mostly online components, but also on-site meetings at
the campus. However, the students didn’t show much interest in attending the
voluntary on-site meetings and therefore the course now takes place
completely online.
The first attempt to strengthen the student-centered activities was done
in this online-taught course by the use of the cooperative learning technique
jigsaw (Andersson and Logofatu, 2016). The application of the jigsaw
technique to the multivariate data analysis course was successful in the sense
that the student activity increased in the course and the resulting feedback
from the students was mostly positive to the approach. A drawback with the
jigsaw technique, applied to this course, was that the students suffered
severely when group members dropped out and decided not to complete the
course.
Therefore, we now consider the inverted classroom as an alternative
method to activate the students. The online implementation of the course is
based on the learning management system Moodle (Moodle, 2015). There are
mainly two reasons for this choice of e-learning platform: Firstly, this platform
is the most frequently used e-learning platform at FRA-UAS. Secondly,
mathematical formulas can easily be constructed in Latex in Moodle.
In accordance with the traditional flipped classroom approach (Wilson,
2013; Touchton , 2015; Cilli-Turner, 2015; Winquist and Carlson, 2014; Chen et
al., 2015, Phillips and Phillips, 2016; Vidic and Clark, 2016), we divided the
learning activities in the course Multivariate Data Analysis into out-of-class
and in-class activities. In our case, both kind of activities take place completely
online in order to facilitate time and location independent studies for the
students. The tuition components of the course can be described as follows:
Description of the out-of-class activities
• The students were partitioned into groups with three or four students in
each group.
• Each group received a specific multivariate method (PCA, PLS, cluster
analysis, discriminant analysis etc.) to learn about, i.e. the members of
each group should become experts concerning their topic during the
semester. This learning process should take place as a more or less
completely student-centered activity, where the lecturers only act as
guides if explicitly needed.

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