Internet Learning Volume 3, Number 2, Fall 2014 | Page 87

Internet Learning
Figure 21. Instructor Participation Across Seven Discussion Threads. Instructor posts
(Jakata and Naya) are highlighted, showing a distinctive pattern of posting across threads
within a narrow time window
can provide valuable data and insights that
instructors can use to help students, and
that students and instructors can use to
help themselves. For example, longitudinal
analysis could show changes in the character
of a student’s corpus over time, or reveal
instructor strategies and interventions that
work more or less well for individual students.
An instructor might realize she tends
to interact more with advanced students,
even though they are not the ones who
need the most support. It is also important
to note that automated metrics could be
based on the structural and mathematical
properties of the schema, so that even if the
metrics are imperfect or approximate, they
can provide a consistent yardstick against
which to better understand, measure, and
improve social environments for learning.
Two instructors may come to different conclusions
about a student based on their expertise
and course requirements, but they
would have the same tools and evidence
available to support their decision-making
process. A wide variety of education
research studies could conceivably be conducted
using a consistent descriptive baseline
of participation metrics, conceptual
content, social learner models, and comparative
conversation analysis tools.
Access to such tools could also have
powerful implications for instructional design
and teaching practice. One instructor,
upon viewing SKN data for a course, realized
that although challenges are a desirable
behavior for the course, they were seldom
being used by students. The instructor subsequently
added an activity that explicitly
required challenges as an output of student
work.
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