Complex Dynamics Lecture SRU 2011

Information Systems Information Systems Dynamics FrameworkDynamics Framework

Maria C. R. Harrington, Ph.D.Faculty Candidate for Assistant Professor, Department of Computer Science, Slippery Rock University's School of Business, as College of Business, Information and Social

Science

© Maria C.R. Harrington, 2011, ALL RIGHTS RESERVED


SEEE Model, 2008SEEE Model, 2008

2© Maria C.R. Harrington, 2011, ALL RIGHTS RESERVED


Background Background

• I am a proven teacher since 1996. As an instructor with over ten years of teaching experience, I am confident that I can teach to your highest standards.

• Since January 2009, (3 years), I have taught Information Systems classes in the Department of Computer Science at Slippery Rock University.

• I am a proven instructor in this environment demonstrating teaching excellence.

• I am committed to excellence in teaching.

3



• Ph.D. in Information Science from the University of Pittsburgho PROGRAM OF INFORMATION SCIENCES AND TECHNOLOGYo Defended and published dissertation in Information Science

• B.S. degree in Economics from Carnegie Mellon Universityo Economics and Art

4



• This combination, a Ph.D. in Information Science and BS In Economics from CMU, along with the ten years of professional information systems experience with international financial companies and software companies, is an ideal background from which to draw both theoretical and practical knowledge.

5


Research FocusResearch Focus• Harrington, Maria, C. R. (2008).

Simulated Ecological Environments for Education (SEEE): A Tripartite Model Framework of HCI Design Parameters for Situational Learning in Virtual Environments. Dissertation Abstracts International. July 17,2008. University of Pittsburgh

• Understanding and modeling the dynamic interaction of the:o Humano Systemo Environment

6

http://etd.library.pitt.edu/ETD/available/etd-08072008-141657/


Research QuestionsResearch Questions• What are the design parameters of these information systems

o How do they impact learning and usability?• What are the subjective emotional reactions to those factors

o Impact user experience, usage rates, and effectiveness• Can we fit data to, and design a priori empirical models to

forecast the effectiveness of such systems prior to construction?

7


Dissertation Dissertation • The Tripartite Model of Simulated Ecological Environments for

Education, and is a conceptual and mathematical framework.

• Empirical Component o Planed Orthogonal Contrast o 2-Way ANOVAo Regression Equationso Markov Model

• Non-parametric Componento Use caseo Surveyso Interviews

8


HypothesesHypotheses• The Two-way ANOVA tests main effects and interaction

effects for all variables under investigation in one system, in a controlled Planned Orthogonal Contrast. o HF= High Fidelity Conditiono LF = Low Fidelity Conditiono HN = High Navigational Freedom Conditiono LN = Low Navigational Freedom Condition

• For each of the Dependent Variables (DV): Salient Events, Fact Inquiry, Time in System, and Knowledge Gain, three statistical tests were possible for each of the Conditionso H01: μ DVHF = μ DVLF

o Ha1: μ DVHF ≠ μ DVLF

o H02: μ DVHN = μ DVLN

o Ha2: μ DVHN ≠ μ DVLN

o H03: No Interactiono Ha3: Interaction

9


10


11


12


13


Results on LearningResults on LearningKnowledge Gained (Test Score Gains)•Visual Fidelity Significantly Impacts

o High Visual Fidelity (Μ = 30.95, SD = 14.76) o Low Visual Fidelity (Μ =19.99, SD = 13.39)o F(1,60) = 10.54, p = 0.0019 (p < 0.05)

•Navigational Freedom Trends an Impact o High Navigational Freedom (Μ = 28.24, SD = 16.51)o Low Navigation Freedom (Μ =22.69, SD =13.06)o F(1,60) = 2.71, p = 0.105

•Strong and Significant Evidence of Interaction between Visual Fidelity x Navigational Freedom

o F(1, 60) = 4.85, p = 0.0315 (p < 0.05)o Highest Learning Gains on tests in the Condition with

Both High Fidelity and High Navigational Freedom (M = 37.44%, SD = 13.88)

14


Results on LearningResults on LearningSalient Events (Evidence of Inquiry) •Visual Fidelity Significantly Impacts

o High Visual Fidelity (Μ = 14.46, SD = 6) o Low Visual Fidelity (Μ =11.31, SD = 6.37)o F(1,60) = 4.35, p = 0.00413 (p < 0.05)

•Navigational Freedom Strong Trend Impacto High Navigational Freedom (Μ = 14.25, SD = 6.99) o Low Navigation Freedom (Μ =11.53, SD = 5.38)o F(1,60) = 3.23, p = 0.0773

•No Evidence of Interaction between Visual Fidelity x Navigational Freedom

o F(1,60) = 1.48, p = 0.2285o Highest Rates of Inquiry in the Condition with Both High

Fidelity and High Navigational Freedom (M = 16.75, SD = 6.27)

15


Transfer EffectsTransfer Effects• Real Compared to Virtual

μ Total Activity (Real) > μ Total Activity (Virtual)

According to the above accepted hypothesis, theReal Environment results in significantly higher Totallearning activity than the Virtual

16


Transfer EffectsTransfer Effects• Real Compared to Virtual

μ Plant-Only Activity (Real) = μ Plant-Only Activity(Virtual)

The Real and Virtual environments are equal when thein-curriculum, Plant-Only learning activity data subset isanalyzed separately

17


Real and VirtualReal and Virtual• Real is better for Learning, but if the Virtual matches

the Real in Content, than the Virtual matches the Real

18


Transfer EffectsTransfer Effects• Transfer Effect

o Virtual Worlds can be used to train for the real world taskso Procedural Knowledge is Transferred

19


Peer ReviewedPeer Reviewed• 1) Harrington, Maria, C. R. (2011).

The Virtual Trillium Trail and the Empirical Effects of Freedom and Fidelity on Discovery-based Learning. Virtual Reality, Springer

• 2) Harrington, Maria, C. R. (2010). Empirical evidence of priming, transfer, reinforcement, and learning in the Real and Virtual Trillium Trails, Journal of IEEE Transactions on Learning Technologies, 28 Jul. 2010. IEEE computer Society Digital Library. <http://doi.ieeecomputersociety.org/10.1109/TLT.2010.20>

• 3) Harrington, Maria C.R. (2009). Meta-ontologies for learning in virtual and augmented realities. ACM-SIGCHI IDC09 The 8th International Conference on Interaction Design and Children Workshop on Children and Mobile Technology: Interface Development for Mobile Touch Devices . June3-5, 2009. Como, Italy.

• 4) Harrington, Maria, C. R. (2009). An ethnographic comparison of real and virtual reality field trips to Trillium Trail: The salamander find as a Salient Event. In Freier, N.G. & Kahn, P.H. (Eds.), Children, Youth and Environments: Special Issue on Children in Technological Environments, 19 (1): [page-page]. http://www.colorado.edu/journals/cye.

• 5) Harrington, Maria, C. R. (2008). Simulated Ecological Environments for Education (SEEE): A Tripartite Model Framework of HCI Design Parameters for Situational Learning in Virtual Environments. Dissertation Abstracts International. July 17,2008. University of Pittsburgh, Pittsburgh, PA.

• 6) Harrington, M.C.R. (2008). A demonstration of virtual trillium trail, a simulation of a fourth grade field trip to a wildflower reserve for ecology education. Open Learning Interplay Symposium 2008. Demos and poster session. March 10-13, 2008. CMU, Pittsburgh, PA USA.

• 7) Harrington, Maria, C. R. (2006). Situational learning in real and virtual space: Lessons learned and future directions. ACM SIGGRAPH’06. July 30-August 3, 2006 Boston, MA, USA. ACM SIGGRAPH

• 8) Harrington, M.C.R. (2006). Trees of life: Models of children's creative processes. ACM DIS’06 Doctoral Consortium. June 28, 2006 State College, PA, USA. Conference Proceedings ACM CHI DIS

• 9) Harrington, M. (2005). Virtual beechwood: Simulated ecological environments for education. Conference on Spatial Information Theory’05. Doctoral Consortium Abstracts. September 14-18, 2005 Ellicottville, New York, USA.

• 10) Gennari, J., Harrington, M., Hughes, S., Manojlovich, M. and Spring, M. (2003). Preparatory observations on ubiquitous knowledge environments: The cyberinfrastructure information ether. NSF Post Digital Library Futures Workshop. Chatham, MA, USA.

21


Future Empirical ModelFuture Empirical Model

Markov Model Regression Equations

22

http://www.sis.pitt.edu/~mariah/phd/Papers/MariaCRHarringtonJVR2011.pdf

http://www.sis.pitt.edu/~mariah/phd/Papers/MariaCRHarringtonIEEETLT2010.pdf

http://doi.ieeecomputersociety.org/10.1109/TLT.2010.20

http://www.idc09.polimi.it/Program.html

http://www.sis.pitt.edu/~mariah/phd/Papers/MariaCRHarringtonCYESICTE2009.pdf

http://www.colorado.edu/journals/cye

http://etd.library.pitt.edu/ETD/available/etd-08072008-141657/

http://telstar.ote.cmu.edu/groups/olisymposium2008/search/?q=virtual+trillium+trail

http://telstar.ote.cmu.edu/groups/olisymposium2008/search/?q=virtual+trillium+trail

http://www.sis.pitt.edu/~mariah/phd/10.1145/1179295.1179344

http://www.sis.pitt.edu/~mariah/phd/10.1145/1142405.1142464


Business Virtual WorldsBusiness Virtual Worlds• Research Interest in Virtual Worlds

o Virtual Reality, Serious Games, Simulationso The next level of Virtualizationo Example; Second Life is used for Meetings, Training,

Collaborative Product Design

IBM, Cisco, Sony, Microsoft and Toyota are one of the Second Life users.

Second Life launched: June 23, 2003

23


Future ResearchFuture Research• How can Virtual Worlds and Serious Games be used

as Business Information Systems?o Soft Skills in Education and Training

• Procedural and Task• Leadership

o Developing Business Acumen o Interpersonal Skillso Motivationo Problem Solvingo Risk Perception and Managemento Ethics under Stress

o Entrepreneurship o Virtual Teams and Collaboration

• ROI -> no travel

24


Future Research Future Research

• Soft Skills in Education and Trainingo Education and Training

• Procedural and Task• Leadership

oDeveloping Business Acumen o Interpersonal SkillsoMotivationoProblem SolvingoRisk Perception and ManagementoEthics under Stress

25


http://www.business-smart.com/products/

26


Future Research Future Research • Risk Management and Ethics

o These are particularly difficult to teach from traditional methodso They require experience to learn

• Difficult to perceive Risk unless you have knowledge of a situation that is not part of your current reality and is in the future and is unlikelyo Financial Crisis o BP Gulf Oil Spill Crisiso Japan Fukushima Nuclear Crisis

27


http://www.traininggames.com/en/index.php?entrepreneurship

28


http://www.goventure.net/VideosENdemo.aspx

29

http://www.goventure.net/VideosENdemo.aspx


• Virtual Teams and Collaboration• Inside a Virtual Meetingo More than 10,000 IBM employees collaborate in virtual worlds. Take a look

inside a meeting in Second Life from the home of IBM V.P. of Innovation, Francoise LeGoues.

• http://www.pbs.org/wgbh/pages/frontline/digitalnation/virtual-worlds/second-lives/inside-a-virtual-meeting.html• Feb 2, 2011

30

http://www.pbs.org/wgbh/pages/frontline/digitalnation/virtual-worlds/second-lives/inside-a-virtual-meeting.html


• Future Information Systems Research• Virtual Worlds and Serious Games

o How are business using them?• Case Studies• Surveys and Interviews

o Test in Classrooms with Students in Learning Environments?• Empirical Studies on Factors that impact learning• Empirical Studies on impacts on motivation and emotional outcomes

o Empirical Model to relate the Factors in such systems to outputs, back to the Design of the Information System

31


ConclusionConclusion• There is great opportunity at Slippery Rock University

for me to bring many interests together, especially in the areas of internet entrepreneurship and the use of virtual simulations for training and education.

• I am a committed and proven teacher in this environment

• I am honored to have worked with you as colleagues over the past few years.

• I cannot imagine a better place to call my professional home

32