introducing an information system for successful support of selective attention in online courses

S C I E N C E P A S S I O N T E C H N O L O G Y

www.tugraz.at

Introducing an InformationSystem for successfulsupport of selectiveattention in online coursesAndreas Holzinger, Josef Wachtler and Martin EbnerGraz, University of Technology

July 15, 2013

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LIVE Interaction in Virtual learning Environments

Index

1. Goal

2. Motivation

3. Implementation

4. Study

5. Conclusion

Andreas Holzinger, Josef Wachtler and Martin Ebner, Graz, University of TechnologyJuly 15, 2013

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LIVE Interaction in Virtual learning Environments

Graz, University of Technology

Europe, Austria, Graz

http://www.tugraz.at


http://www.tugraz.at

4

Goal

Goal

Development and evaluation

of a web-based information system

to support a live stream of a lecture

with different forms of interactions like anAudience-Response-System.

Sustain and enlarge Students’ attention.


5

Motivation

Attention and Communication

Selective attention is the most crucial resource forhuman learning

Enhances both behavioral and neuronal performance

Interaction and communication between all groups ofparticipants in all sorts and directions

are key features for an increased attention.


6

Motivation

Audience-Response-Systems

ARSs are well known for face-to-face education instandard classroom-situations

presenting questions to studentsanswering with a special handsetanswers are shown to the lecturer

ARS has the power to enhance the attention and theparticipation of the students (reported by manystudies)


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Implementation

Implementation


8

Implementation

Overview


9

Implementation

Lecturer GUI


10

Implementation

Lecturer GUI

1. Metadata of the event

2. Calculated degree of attention of all students

3. Free space for occurring interactions

4. Control-elements to invoke interactions


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Implementation

Student GUI


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Implementation

Student GUI

1. Foreign web-content (e.g. the live-stream)

2. Metadata of the event and calculated degree ofattention

3. Free space for occurring interactions

4. Control-elements to invoke interactions


13

Implementation

Three Interaction-Types

1. Automatically startedThe interactions of an interaction-method of this typeare automatically presented to the attendees in arandom way.

2. Started by the attendeesThis type represents interaction-methods which couldbe started by the attendees.

3. Invoked by the lecturerWith interaction-methods of this type the lecturer isable to invoke them.


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Implementation

Showing Interactions

Three Models are used to schedule interactions

1. showing interactions to students2. presenting interactions to the lecturer3. error messages

If a model reaches its scheduled time

a special view is shown in the reserved space.


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Implementation

Interaction-Methods

Simple QuestionsGeneral questions are automatically shown to thestudents.

Solve CaptchaStudents are prompted to solve a captcha randomly.

Report ProblemA technical problem could be reported to the lecturerby the students.


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Implementation

Interaction-Methods

Set Attention-LevelStudents could set their current level of attentionthrough a slider.

Ask LecturerQuestions could be asked to the lecturer by thestudents.

Ask StudentsAlso the lecturer could ask questions to the students.


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Implementation

Degree of Attention

A value between 0% and 100%

Every interaction-method calculates its own value

Most of them are using a reaction-time basedapproach

Overall attention-level: the mean of allinteraction-methods


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Implementation

Reaction-Time based Attention-Level

For every interaction:

Attention-level of the interaction-method: the mean ofall interactions


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Study

Study


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Study

Setting and Observations

Live broadcasting of the lecture CleanroomTechnology

Five Units

Seven to twelve attendees

Lecture 1 and 2: very low attention-level (less than40%)

Attendees felt very uncomfortable with their lowattention-level and

they liked content-related questions more thangeneral questions.


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Study

Improvements and Observations

Some improvements:

more content-related questionspauses during questions. . .

After that the attention-level stabilized at 75% andmore

Also the attendees felt satisfied with thisimprovements.


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Conclusion

Conclusion

A web-application which provides different methods ofinteraction

Calculation of the degree of attention

Positive effects on the attention under the mentionedcircumstances


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Conclusion

Thanks

for your attention!

Social LearningComputer and Information ServicesGraz University of Technology

[email protected]

http://elearning.tugraz.at

Slides available at http://elearningblog.tugraz.at


[email protected]

http://elearning.tugraz.at

http://elearningblog.tugraz.at

introducing an information system for successful support of selective attention in online courses

Education

martin ebner graz

josef wachtler

interactions andreas

students attention

studies andreas holzinger

conclusion andreas holzinger

graz http

attentionlevel students