1. KIT – University of the State of Baden-Wuerttemberg and
National Research Center of the Helmholtz Association
GMUNDEN RETREAT ON NEUROIS 2014
www.kit.edu
A NeuroIS Platform for Lab Experiments
Marius B. Müller, Anuja Hariharan, Marc T. P. Adam
2. 2 Gmunden Retreat on NeuroIS 201412.03.2015 Institute of Information Systems and Marketing (IISM)
Why yet another platform for experiments?
Many platforms already exist
… and even more one time use and single purpose implementations.
Common missing elements:
Integration of bio sensors (and all its requirements)
Easily adaptable and extendable to individual experiment
Offline and online analyses
Decision to create new platform
3. 3 Gmunden Retreat on NeuroIS 201412.03.2015 Institute of Information Systems and Marketing (IISM)
Agenda
Objectives & Design
Architecture
Use cases/Demonstration
Evaluation
Limitations & Next steps
4. 4 Gmunden Retreat on NeuroIS 201412.03.2015 Institute of Information Systems and Marketing (IISM)
Objectives & Design
Main objectives
Facilitating the creation of lab experiments by reducing development time
Facilitating individual & group interactions in a controlled lab setting
Integrating measurements of bio sensors and logging of physiological data
specific to subject events
Ease of event logging and data storage, enabling experiments to scale in time
and subject size
Meeting emerging technical requirements in the field of IS research and
experimental economics
Design inspiration
Microeconomic System
by Vernon L. Smith (1976, 1982)
Economic environment
Microeconomic institution
Friedman and Sunder (1994)
5. 5 Gmunden Retreat on NeuroIS 201412.03.2015 Institute of Information Systems and Marketing (IISM)
General Platform Architecture
core components
server client
customizablebuilt-in
experimental design
server
(procedure)
client
(visualization)
bio sensors
client
(recording)
server
(control)
6. 6 Gmunden Retreat on NeuroIS 201412.03.2015 Institute of Information Systems and Marketing (IISM)
Demonstration: Auction Fever
Experiment Details
Research question:
Investigate the process of auction fever in
retail auctions and its affects on bidding
behavior
Design:
2x2 factorial between-subjects design
Participants: 216
Sensors:
Measurement of arousal using
ECG, EDA & PPG
Platform support
Three groups of three subjects each interact simultaneously
Integration of individually chosen avatars
Scalability and data preparation
7. 7 Gmunden Retreat on NeuroIS 201412.03.2015 Institute of Information Systems and Marketing (IISM)
Demonstration: Auction Workload
Experiment Details
Research question:
Understand how IS constructs (arousal
and workload) are influenced by auction
types and uncertainty
Impact on bidding behavior
Design:
2x2 factorial within-subjects design
Participants: 54
Sensors:
Measurement of arousal using ECG & EDA
Measurement of workload using EEG
Platform support
Simulate computer agents
Synchronously add triggers to EEG data for various events
HR and SC data transmitted via bluetooth and stored on client
8. 8 Gmunden Retreat on NeuroIS 201412.03.2015 Institute of Information Systems and Marketing (IISM)
Evaluation Process
1) Eeekels(1991) 2) Takeda (1990) 3) Hevner (2004) 4) Cole (2005)
Choose
Evaluation
method
• Observational
and Descriptive (1)
Choose
Evaluation
Type
• Confirmatiory Evaluation (2)
• Step 1 : Confirm the solution
• Step 2 : Evaluate problem in the solution
Define
Metrics
• Utility, Quality, Efficacy (3)
• Simplicity, power (4)
Evaluate the
evaluation
• Feedback from
other IS
researchers
9. 9 Gmunden Retreat on NeuroIS 201412.03.2015 Institute of Information Systems and Marketing (IISM)
Limitations and Next Iteration
Limitations:
Java-APIs not available for other methods (such as fMRIs)
Too rich/not the tool for “simple” surveys
Need to circulate and evaluate tool outside KIT
Combine coding with drag-and-drop UI design methods
• Within own
Research Group
• Tested with diff.
sensors
Iteration 1
• Other research
groups in KIT
• w/o sensors
Iteration 2
• External Research
Groups
• Field Experiments
Iteration 3
10. 10 Gmunden Retreat on NeuroIS 201412.03.2015 Institute of Information Systems and Marketing (IISM)
Summary & Outlook
Contribution:
Stable prototype for implementing experiments with physiological
measurements and strategic interactions
Requirements & Objective of research gap for NeuroIS tool specified and
met through first iteration
Communication:
Distribute as a ready-to-use eclipse workspace
Version controlled source-code repository on Bit Bucket
Tutorials, sample experiments, technical support
Scientific publications
Thank you for your attention!
11. 11 Gmunden Retreat on NeuroIS 201412.03.2015 Institute of Information Systems and Marketing (IISM)
Contacts
marc.adam@kit.edu
marius.mueller@kit.edu
+49 (721) 608 4 8374
anuja.hariharan@kit.edu
+49 (721) 608 4 83 82
12. 12 Gmunden Retreat on NeuroIS 201412.03.2015 Institute of Information Systems and Marketing (IISM)
Literature
Cole, R.; Purao, S.; Rossi, M.; and Sein, M.K. Being proactive: Where action research meets design
research. In D. Avison, D. Galletta, and J.I. DeGross (eds.), Twenty-Sixth International Conference on
Information Systems. Atlanta: Association for Information Systems, 2005, pp. 325–336.
Eekels, J., & Roozenburg, N. F. (1991). A methodological comparison of the structures of scientific
research and engineering design: their similarities and differences. Design Studies, 12(4), 197-203.
Friedman, D. (1994). Experimental methods: A primer for economists. Cambridge University Press.
Hevner, A.R.; March, S.T.; and Park, J. Design research in information systems research. MIS
Quarterly, 28, 1 (2004), 75–105.
Peffers, K., Tuunanen, T., Rothenberger, M. A., & Chatterjee, S. (2007). A design science research
methodology for information systems research. Journal of management information systems, 24(3),
45-77.
Smith, V. L. (1975). Experimental economics: Induced value theory. University of Arizona, College of
Business and Public Administration, Division of Economic and Business Research.
Smith, V. L. (1989). Theory, experiment and economics. The Journal of Economic Perspectives, 151-
169.
Takeda, H.; Veerkamp, P.; Tomiyama, T.; and Yoshikawam, H. Modeling design processes. AI
Magazine, 11, 4 (Winter 1990), 37–48.
Hinweis der Redaktion
Idea is to provide a platform form lab experiments in the context of neurois research and all its unique requirements
No live demo, because live demos (almost) always fail => if some is interested. Happy to show a demo after the talk.
Mention experiments presented that day?
Many single purpose: (at some point most here have implemented some single use ;) )
We conducted an extensive search & comparison of tools
Didn’t find “the one” tool
Most no bio sensors
Very fixed in functionality (only drag-and-drop features)
No Group interaction
No Online & offline analyses
…
Final decision: make our own
What is good for our research requirements, maybe also helpful to others
##############
4
5 not locked in to one specific RQ, Sensor, Experiment idea
Smith paper:
- defines the terminology we use (Environment & Institution)
don’t came up with new
rely on existing literature
- and the general structure (Sessions, Periods, Rounds as well as Groups, Cohorts & their matching)
Friedman
Internal structure of experiments of how experiments are organized
#####################
Facilitate lab experiments on individual & group interaction
Reduce development effort, while still allowing for complex and new-age scenarios
Some existing tools are very fixed in functionality, since they only allow drag-and-drop features.
Integration of sensor measurements & event logging
Most existing sensor based platforms allow for repeated stimuli presentation, but no possibilities for group interaction.
Enable good UI Design to support IS research
Extensible with other sensor processing tools and API’s
################
Goals als Tabelle/ Übersicht
The software itself is generally structured like this after several iterations (always having the objectives in mind)
Although, a very tech-savvy audience, no boring technical details (if anyone interested though, happy to talk about after the talk)
List Features while explaining each component: Core components, Experimental design, Bio sensors
Bio sensors:
Just use for recording
also use the data for the experimen
(biofeedback or real-time analyses influences procedure/ flow of experiment)
Using exactly this Platform, we already conducted two experiments, which I briefly want to show how they looked
photoplethysmograph (PPG)
Group interaction
perfect stranger matching
asynchronously
And the second experiment was about AW which was conducted by anuja
Mention Browser Support
Observational : Case study in business/research environment, Field study – monitor use in multiple projects
Descriptive: Informed Argument : Use info from knowledge base to build convincing argument for artifact’s utility
Scenarios: Construct detailed scenarios around artifact to demonstrate its utility.
Other methods considered : Analytical (static, dynamic, optimization, architecture analysis), Experimental (Controlled study of artifact), Testing (Black box, white box).
2) Step 1: Evaluation to confirm the solution
Step 2: Evaluation to know what is a problem in the solution.
The simulated behavior of the designed product and the desired behavior according to the program of requirements.
3) Utility, Quality and efficacy of a design artifact must be rigorously demonstrated via well-executed evaluation plans.
4) Simplicity and ease of use, power to solve and innovate.
End Remarks:
Please approach us in the break if you would like to view a demo, or if you would like to use the tool for your experiments.
Also, any feedback on the evaluation method is appreciated