analyzing interactivity in asynchronous video discussions

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)


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


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


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


III. Demonstration The Case Scenario: Net Economy

In 2013: 140 Students (from Germany, Ukraine, Indonesia)


III. Demonstration A ‘Consumer Perspective’ for Video Discussions

270 video statements

6438 videos watched


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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