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Evaluating online discussions is a complex task for educators. Information sys-tems may support instructors and course designers to assess the quality of an asynchronous online discussion tool. Interactivity on a human-to-human, human-to-computer or human-to-content level are focal elements of such quality assess-ment. Nevertheless existing indicators used to measure interactivity oftentimes re-ly on manual data collection. One major contribution of this paper is an updated overview about indicators which are ready for automatic data collection and pro-cessing. Following a design science research approach we introduce measures for a consumer side of interactivity and contrast them with a producer’s perspective. For this purpose we contrast two ratio measures ‘viewed posts prior to a state-ment’ and ‘viewed posts after a statement’ created by a student. In order to evalu-ate these indicators, we apply them to Pinio, an innovative asynchronous video discussion tool, used in a virtual seminar.
Citation preview
Analyzing interactivity in
asynchronous video
discussions
Hannes Rothe
Janina Sundermeier
Martin Gersch Department Business Information Systems
Research Paper Presentation at the International
Human-Computer-Interaction Conference (HCII),
Heraklion, Greece, June 27th 2014
2
I. Problem Definition -- Indicators for interactivity in asynchronous
online discussions
II. Artifact -- Developing of Indicators for a ‚consumer
perspective‘
III. Demonstration -- Measuring interactivity within asynchronous
video discussion in Pinio
IV. Conclusion
Analyzing interactivity in asynchronous video discussions, H. Rothe, J. Sundermeier, M. Gersch, June 27th 2014, HCII2014
Agenda Interactivity in asynchronous online discussions
Identify
problem &
motivate
Define
objectives
of a
solution
Design
&
develop
artifact
Demon-
strationEvaluation
3 Analyzing interactivity in asynchronous video discussions, H. Rothe, J. Sundermeier, M. Gersch, June 27th 2014, HCII2014
I. Problem definition Updating Dringus and Ellis Indicators for interactivity in Online Discussions
Are there key Indicators for measuring
interactivity automatically in Online Discussions?
Active (‚producer perspective‘)
Amount of posts, words, sentences created
Time difference between posts
Amount of reviews or edits
Changes of subjects, Keywords, phrases, topics
Number of responses
Centrality of post, density of a discussion
Passive (‚consumer perspective‘)
Number of posts read or ‚scanned‘
(estimated by time span)
Amount of website hits
Posts marked as ‚read‘
Only few papers mention this
perspective and measure it very
indirectly
‘[T]he associated indicators are found in the literature, but only in piecemail’. (Dringus & Ellis 2005)
4 Analyzing interactivity in asynchronous video discussions, H. Rothe, J. Sundermeier, M. Gersch, June 27th 2014, HCII2014
I. Asynch. Video Discussions The Technology: Pinio
Usage or Pinio
in our course
2nd week:
Mandatory
participation
3rd week:
Discussion
initiated by lecturer
4th week:
No initiation by
lecturer
10th week:
Presentation of
case study with
mandatory
participation
Every person has 30 seconds for a video statement.
Statements are complemented by facial expressions
Replies start with agree or disagree
5 Analyzing interactivity in asynchronous video discussions, H. Rothe, J. Sundermeier, M. Gersch, June 27th 2014, HCII2014
II. Methodology Design Science Research…
Problem: How can we use data mining to evaluate online
discussions against the background of a multifaceted
view on interactivity?
…follows the procedure by Peffers et al. 2007
Identify
problem &
motivate
Define
objectives
of a
solution
Design
&
develop
artifact
Demon-
stration Evaluation
Artifact: Design of indicators for a ‚consumer perspective‘ in
online discussions
6 Analyzing interactivity in asynchronous video discussions, H. Rothe, J. Sundermeier, M. Gersch, June 27th 2014, HCII2014
II. Artifact Quantifiable Indicators for the ‘Consumer Perspective’
viewed comments (v) in a discussion (D) prior to a statement (px) at time (t).
Tt p
Tt v
rva
xtD
xtD
x
1
1
,
,
Ratio of Videos viewed
after a post
1
1
,
,
x
otD
x
otD
x
tt p
tt v
rvp
Ratio of Videos viewed
prior to a post
30s
time
7 Analyzing interactivity in asynchronous video discussions, H. Rothe, J. Sundermeier, M. Gersch, June 27th 2014, HCII2014
III. Demonstration The Case Scenario: Net Economy
In 2013: 140 Students (from Germany, Ukraine, Indonesia)
8 Analyzing interactivity in asynchronous video discussions, H. Rothe, J. Sundermeier, M. Gersch, June 27th 2014, HCII2014
III. Demonstration A ‘Consumer Perspective’ for Video Discussions
270 video statements
6438 videos watched
9 Analyzing interactivity in asynchronous video discussions, H. Rothe, J. Sundermeier, M. Gersch, June 27th 2014, HCII2014
IV. Conclusion Conclusive Remarks and Future Research
There is no either/or between a consumer and
producer perspective (it is a continuum)
A Key Indicator has not been found, yet.
Initial results lead to a more nuanced understanding
of interactivity. Indicators need to be chosen, based
on the context.
Future Research
I currently design a Procedural
model to select indicators from
Learning Analytics for specific
learning scenarios.
Initial results of a cluster
analysis shows three types of
learners.
How does this effect the
learning outcome?
Thank you for your attention. You may find me online on
twitter (@wingsoft) or LinkedIn (Hannes Rothe).
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