About University of Maryland University College

About University of Maryland University College

ssessing the Benefits of Online Scenario mulation Tools in Security-Related Studie at UMUC Irmak Renda-Tanali, DSc. Collegiate Associate Professor Director, Homeland Security & Emergency Management Graduate School of Management & Technology University of Maryland University College Fourteenth Annual Emergency Management Higher Education Conference Federal Emergency Management Agency, U.S. Department of Homeland Security Thursday June 9, 2011 Outline Background Research Objectives Methodology Research Design Tools Results Survey Results Actual Performance Results Conclusions Recommendations Irmak Renda-Tanali 2 Background Why such study? Emergency Management and related fields are best learned through scenario studies Textbooks and lecture-based learning do not effectively teach:

Consensus gathering Collective decision making Decision making under uncertainty Testing and validating assumptions How to manage major crises and emergencies Textbooks and lectures do not capture the dynamic, time-sensitive, contextdependent, multi-disciplinary nature of the emergency/crisis scenarios. Irmak Renda-Tanali 3 Background Why such study (contd)? Course evaluations and teaching experience show: Students want dynamic, hands-on exercises that simulate real world environments, real world thinking. Textbook reading and conference participations need further stimulating tools to enhance student understanding of topics. Students want to be an active part of decision making process as crisis events unfold. They want to learn what are the good AND bad decisions and why, by actively seeing consequences of their decisions in reaction to events that unfold. Case studies looking backward are not so Renda-Tanali interesting as the events andIrmak

consequences are 4 Background Examples of current practice: Multi-media technology Video, audio, web pages, web 2.0 tools: blogs, wikis, social networking sites, podcasts, vodcasts etc. Play2Train, a virtual world platform, uses Second Life software with avatars (intelligent agents) mimicking human behavior. Specific examples related to security studies: A web-based scenario simulation tool used for public health undergraduate students (Spinello & Fishbach, 2004) San Luis Rey town scenario simulation exercise for HS students at UMUC graduate studies (Boubsil & Gayol, 2006) Play2Train, used to replicate tabletop Irmak Renda-Tanali exercises, 5 Background Examples (contd) Specific examples related to security studies (contd) Second Life and Play2Train in Master of Healthcare Administration online programs, used to enhance student discovery, critical thinking, and analytical skills. Irmak Renda-Tanali 6

Research Objectives To capture the effectiveness of online scenario simulation tools used at UMUC, on student learning; To identify the kinds of strengths and weaknesses of those tools; To compare those tools to traditional methods of teaching; Ultimately to enhance student learning in Emergency Management and related fields of study through the findings of the study. Irmak Renda-Tanali 7 Study Tools Subjects: 5 online sections of CCJS 320 145 students in total 3 online sections of CCJS 420 78 students 2 online sections of CCJS 425 45 students 2 online sections of BSBD 641 51 students total 319 students Instructors Developer-instructors Taught in Fall 2010 semester Data Sources Student survey for all sections of the above courses Phone calls to faculty developed and/or use simulation Course statistics measuring student participation and interactionIrmak Renda-Tanali

8 Areas Surveyed Learning: Understanding the material Processing, testing, validating assumptions Decision making skills Getting close to real-life experience Connecting events and objects (or actions) Visualizing, conceptualizing, comprehending Consensus gathering Effective crisis communication Effective use of resources Effective emergency response to large scale crises Student-to-student interaction Irmak Renda-Tanali 9 Areas Surveyed Technology use Workload Student Satisfaction Demographics

Irmak Renda-Tanali 10 Assumptions Learning: Online scenario simulation tools help understand the material better. They help better process, test, validate assumptions Improve decision making skills. Help get close to real-life experience. Help connect events and objects (or actions). Help with visualizing, conceptualizing, and comprehending. Increased student-to-student interaction contributes to learning (Community of Inquiry Theory by Garrison et. al, 2000) Increased student-to-faculty interaction Irmak Renda-Tanali 11 contributes to learning (CoI). Assumptions Technology use: If there are no problems with the technology, student satisfaction is more better learning Workload:

No assumptions about the time spent versus contribution to learning Student Satisfaction: Students who responded favorably performed favorably or did they? Demographics: No assumptions a correlation study may uncover unknown facts Irmak Renda-Tanali 12 Setting CCJS 320 Project Name: Crime Scene Simulation Actions: Students virtually move around a crime scene, examine items, process evidence, place them in an evidence box, interview the witness, and record details in a journal. After all the evidence is collected, students enter into a virtual Crime Lab and request the appropriate tests for each evidence item such as medico-legal autopsy, fingerprint analysis, forensic biology, toxicology, firearm examination, etc. Deliverable: After the tests are performed a detailed Crime Scene Report is generated. Students are graded based on Irmak Renda-Tanali the correctness of the evidence collected 13 Setting CCJS 320 (contd)

Irmak Renda-Tanali 14 Setting CCJS 320 (contd) Irmak Renda-Tanali 15 Setting CCJS 320 (contd) Irmak Renda-Tanali 16 Setting CCJS 320 (contd) Irmak Renda-Tanali 17 Results: Crime Scene Simulation Response Rates (CCJS 320): CCJS 320 No. of Surveys sent No. of Completed Surveys

Response rate 6380 32 12 37.5% 6381 30 9 30.0% 6980 29 14 48.3% 6981 25 11 44.0% 7980

29 5 17.2% Total 145 51 35.2% Irmak Renda-Tanali 18 Results: Crime Scene Simulation Understanding the material This simulation exercise helped me understand the material better. Question understanding material 43% hands-on experience 41% mirroring real-life exper. improve decision making assumption testing making connections visualizing, conceptualizing engaging w/other students

engaging w/faculty 16% approaching faculty technology (no bugs) time spent no. of classes taken so far age Strongly0% Disagree Disagree Agree Q. No. Q2 Q3 Q4 Q5 Q6 Q7 Q8 Q9 Q10 Q11 Q12 Q13 Q19 Q22 Q2 1.000 0.788 0.683

0.747 0.821 0.838 0.746 0.364 0.424 0.247 0.444 -0.026 -0.271 -0.165 Strongly Agree Correlation to itself Large correlation (Pearson Coefficient) Large (strong) correlation Medium correlation Low correlation Irmak Renda-Tanali 19 Pearsons Correlation Coefficient Pearson's correlation coefficient between two variables is defined as the Covariance of the two variables divided by the product of their standard deviations. Simple to do using Excel spreadsheet with the embedded function. Correlation Negative Positive

None 0.09 to 0.0 0.0 to 0.09 Small 0.3 to 0.1 0.1 to 0.3 Medium 0.5 to 0.3 0.3 to 0.5 Large 1.0 to 0.5 0.5 to 1.0 Irmak Renda-Tanali 20 Results Summary: Crime Scene Simulation Learning AGREE CORRELATION 84%

LARGE 84% LARGE 84% LARGE 82% LARGE 80% LARGE It improved my skills about making connections between events and objects. 80% LARGE It helped me visualize, conceptualize, and comprehend situations related to crime scene investigation. 88% LARGE This simulation exercise helped me understand the material better. It gave me a hands-on opportunity to

understand the material. It deepened my understanding of the subject as it mirrored real life situations. It helped to improve my decision making skills. It improved my skills in processing, testing, and validating assumptions. 21 Results Summary: Crime Scene Simulation Interaction AGREE CORRELATION MEDIUM (decision making, The simulation helped me engage with other students. 37% It improved my interaction with the instructor. 76% MEDIUM 78% LOW - MEDIUM It gave me ideas for questions about the

subject matter to approach the instructor. understanding, technology) LOW on all others 22 Results Summary: Crime Scene Simulation Other/Demographics Technology worked Time spent # of classes taken AGREE CORRELATION 74% MEDIUM Diverse (2 to 8 hours) MEDIUM (approaching faculty), low 61% more than 4 LOW NEGATIVE on all, no correlation with otherwise interaction MEDIUM (NEGATIVE: mirroring real-life; Age

49% between 20-30 years, 27% between 30-40 yrs improve decision making; assumption testing; making connections); LOW (NEGATIVE: understanding, hands-on exp., visualizing); LOW (POSITIVE: engaging w/students & faculty, no of classes taken) Gender 69% female N/A 23 Results Summary: Crime Scene Simulation Standard Course Evaluation Results (related questions) (Mean out of 5-point Likert Scale) Technology (such as slide shows, multi-media, streaming audio-video) was effectively used in this course This course helped me develop or improve my computer skills. The lab activities contributed to my learning. I was able to use technology effectively on my own. This course enhanced student-to-student interaction. This course enhanced faculty-student interaction. 4.35 3.85 4.15 4.36 4.17

4.06 24 Setting CCJS 420 CCJS 420 Medical and Legal Investigations of Death Cold Case Simulation Actions: Students begin by examining the reports and evidence from the original investigation. Once they are familiar with the homicide case and the people involved, they proceed to interview persons of interest. As the simulation progresses and student encounter new evidence, they will be able to submit that evidence for various types of forensic testing. As students proceed with their investigation, they gather evidence, test results, reports, and witness statements. These items are placed into their binder as they are created or discovered. Deliverable: Arrest Warrant Report Objectives: Gather enough evidence, secure an indictment from the district attorney, 25 Irmak Renda-Tanali Setting CCJS 420 Irmak Renda-Tanali 26 Results: Cold Case File Simulation Response Rates (CCJS 420): CCJS 420 section

No. of No. of Surveys Responses sent Response rate 6980 7380 7980 27 19 30 12 6 8 44.4% 31.6% 26.7% Total 76 26 34.2% Irmak Renda-Tanali 27 Results Summary: Cold Case File

Simulation Learning AGREE CORRELATION 84% LARGE 88% LARGE 68% LARGE 75% LARGE 75% LARGE It improved my skills about making connections between events and objects. 84% LARGE It helped me visualize, conceptualize, and comprehend situations related to crime scene investigation.

92% LARGE This simulation exercise helped me understand the material better. It gave me a hands-on opportunity to understand the material. It deepened my understanding of the subject as it mirrored real life situations. It helped to improve my decision making skills. It improved my skills in processing, testing, and validating assumptions. 28 Results Summary: Cold Case File Simulation Interaction The simulation helped me engage with other students. AGREE CORRELATION LARGE (making connections; visualizing and conceptualizing; engaging & approaching faculty); 40% MEDIUM (hands-on, mirroring, decision making, assumption testing); LOW (understanding, technology); LOW (negative: time

spent and age) It improved my interaction with the instructor. It gave me ideas for questions about the subject matter to approach the instructor. 44% LARGE (learning) MEDIUM (technology, negative: age); LOW (negative: time spent) LARGE (hands-on, real-life, making connections, visualizing, engaging), 71% MEDIUM (understanding, decision, assumption testing, technology), MEDIUM (negative: age), LOW (negative: time spent) 29 Results Summary: Cold Case File Simulation Other/Demographics Technology worked AGREE 56% CORRELATION LARGE (hands-on, real-life), MEDIUM (understanding, decision-making, assumption testing, making connections, engaging/ approaching faculty),

MEDIUM (NEGATIVE: age); LOW (visualizing, engaging w/students, no. of classes) Time spent Average NEGATIVE LARGE (NEGATIVE: visualizing, age), MEDIUM (NEGATIVE: hands-on, reallife, assumption testing, making connection), LOW (NEGATIVE: understanding, interaction) # of classes taken 92% more than 4 LOW LARGE (time spent), MEDIUM Age Gender 44% between 20-30 years, 44% between 30-40 yrs 88% female (NEGATIVE: understanding, assumption testing, visualizing, interaction), LOW

(NEGATIVE: hands-on, decision-making, making connections, engaging w/other students, no. of classes taken) N/A 30 Results Summary: Cold Case File Simulation Standard Course Evaluation Results (related questions) (Mean out of 5-point Likert Scale) Technology (such as slide shows, multi-media, streaming audio-video) was effectively used in this course This course helped me develop or improve my computer skills. The lab activities contributed to my learning. I was able to use technology effectively on my own. This course enhanced student-to-student interaction. This course enhanced faculty-student interaction. 3.68 4.15 4.04 4.39 4.04 3.50 31 Setting BSBD 641 Irmak Renda-Tanali 32 Results: Biological Attack Simulation

Response Rates (BSBD 641): BSBD 641 section 9040 9041 Total No. of Surveys sent 26 25 51 No. of Responses 9 9 18 Response rate 34.6% 36.0% 35.3% Irmak Renda-Tanali 33 Results Summary: Biological Attack Simulation Learning AGREE This simulation exercise helped me understand the

material better. 100% It gave me a hands-on opportunity to understand the material. 100% It deepened my understanding of the subject as it mirrored real life situations. 89% It helped to improve my decision making skills. 89% CORRELATION LARGE (hands-on, real life, decision making, eff. Crisis comm.., approaching faculty and technology), MEDIUM (eff. Em response, resources) LOW (consensus) LARGE (understanding, real-life, crisis comm..), MEDIUM (decision, eff. EM response, consensus, resources) LARGE (understanding, hands-on, decision-making, eff. Crisis comm.), resources) MEDIUM (eff. EM response, consensus, LARGE (understanding, real-life, consensus, eff. Crisis comm.), MEDIUM (hands-on, eff. EM response,

resources) It improved my knowledge of establishing an effective emergency response structure during bioterrorism attacks. 100% LARGE (hands-on, real life, decision making, eff. Crisis comm.., approaching faculty and technology), MEDIUM (eff. Em response, resources) LOW (consensus) It improved my consensus gathering skills. 100% LARGE (consensus, resources, eff. Crisis comm.), MEDIUM (understanding, hands-on, real-life, decision making) It helped me understand what resources are needed during a public health bioterrorism emergency. 94% It helped improve my understanding of effective crisis communication. 100% LARGE (decision making, eff. EM response, resources, eff. Crisis comm.) MEDIUM (hands-on, real-life), LOW (understanding) LARGE (eff. Em response, consensus, eff. Crisis comm..) MEDIUM (understanding, hands-on, real-life, decision making)

34 Results Summary: Cold Case File Simulation Interaction AGREE CORRELATION LARGE (consensus, eff Crisis comm.) MEDIUM The simulation helped me engage with other students. 94% It improved my interaction with the instructor. 50% (understanding, hands-on, decision making, eff. EM LOW (real-life) LOW (NEGATIVE: time spent, no. of classes taken) LARGE (decision making, consensus gathering, eff. Crisis comm., approaching faculty) MEDIUM (understanding, response, resources, interaction w/faculty), hands-on, real-life, eff. EM response, resources, engaging with students) LOW (age), LOW (negative: no. of classes) It gave me ideas for questions about the subject matter to approach the instructor. LARGE (understanding, real-life, decision making,

consensus gathering, eff. Crisis comm.., engaging with 71% faculty, technology) MEDIUM (hands-on, eff. EM response, resources, engaging with students), LOW (NEGATIVE: time spent) LOW (no of classes) 35 Results Summary: Cold Case File Simulation Other/Demographics AGREE CORRELATION LARGE (understanding, hands-on, real-life, Technology worked Time spent # of classes taken Age 89% 67 % More than 8 hours 89% more than 4 decision making, effective crisis comm.., engaging w/ students, approaching faculty) MEDIUM (consensus, engaging with faculty, time spent) LOW (eff EM response, resources)

LOW (NEGATIVE: age) NEGATIVE MEDIUM (real-life, technology), LOW ON OTHERS MEDIUM (hands-on) LOW on others MEDIUM (negative: understanding), LOW 22% 20-30 yrs, 39% 30-40 yrs, (NEGATIVE: real-life, time spent) LOW 22% 41-50, 17% 50-60 yrs (decision making, eff crisis comm., engaging w/faculty, no of classes) Gender 17% female N/A 36 Results Summary: Cold Case File Simulation Standard Course Evaluation Results (related questions) (Mean out of 5-point Likert Scale) Technology (such as slide shows, multi-media, streaming audio-video) was effectively used in this course This course helped me develop or improve my computer skills. The lab activities contributed to my learning. I was able to use technology effectively on my own. This course enhanced student-to-student interaction. This course enhanced faculty-student interaction. 3.92 3.34 4.22 4.21

4.61 3.71 37 Results Summary Crime Scene Cold case AGREE CORRELATIO AGREE N Understanding material 84% LARGE 84% Bioattack CORRELATION AGREE Learning LARGE 100% CORRELATION LARGE (hands-on, real life, decision making, eff. Crisis comm.., approaching faculty and technology), MEDIUM (eff. Em response, resources) LOW (consensus)

Hands-on experience 84% Mirroring reallife experience 84% LARGE 88% LARGE 100% LARGE (understanding, real-life, crisis comm..), MEDIUM (decision, eff. EM response, consensus, resources) LARGE 68% LARGE 89% LARGE (understanding, handson, decision-making, eff. Crisis

comm.), MEDIUM (eff. EM response, consensus, resources) Improving decision making skills 82% LARGE 75% LARGE 89% LARGE (understanding, real-life, consensus, eff. Crisis comm.), MEDIUM (hands-on, eff. EM response, resources) 38 Results Summary Crime Scene AGREE CORRELATIO N AGREE

Cold case CORRELATION AGREE Bioattack CORRELATION Learning Validating and testing assumptions Making connections between events and objects Helps visualizing, conceptualizing Understanding effective emergency response Improve consensus gathering skills Learn effective use of resources in EM response Improve effective crisis communication skills 80%

LARGE 75% LARGE N/A N/A 80% LARGE 84% LARGE N/A N/A 88% LARGE 92% LARGE N/A N/A 100%

LARGE (consensus, resources, eff. Crisis comm.), MEDIUM N/A N/A N/A N/A (understanding, hands-on, real-life, decision making) LARGE (decision making, eff. EM response, resources, eff. N/A N/A N/A N/A 94% Crisis comm.) MEDIUM (hands-on, real-life), LOW (understanding) LARGE (eff. Em response, N/A N/A N/A

N/A 100% consensus, eff. Crisis comm..) MEDIUM (understanding, hands-on, real-life, decision making) N/A N/A N/A N/A 94% LARGE 39 Results Summary Crime Scene Cold case AGREE CORRELATIO AGREE N Student to student engagement Bioattack

AGREE Interaction LARGE (making MEDIUM (decision making, understanding, technology) LOW on all others 37% CORRELATION LARGE (consensus, eff Crisis comm.) MEDIUM connections; visualizing and conceptualizing; engaging & approaching faculty); 40% MEDIUM (handson, mirroring, decision making, assumption CORRELATION (understanding, hands-on, decision making, eff. EM response, resources, interaction 94% LOW (real-life)

LOW (NEGATIVE: time w/faculty), spent, no. of classes taken) testing); LOW (understanding, technology); LOW (negative: time spent and age) Engaging with faculty MEDIUM LARGE (learning) MEDIUM LARGE (decision making, consensus gathering, eff. Crisis comm., approaching faculty) (technology, negative: 76% 44% age); LOW (negative: time spent) 50% MEDIUM (understanding, hands-on, real-life, eff. EM response, resources, engaging

with students) LOW (age), Approaching faculty LOW MEDIUM 78% 71% LARGE (hands-on, LOW (negative: no. of classes) LARGE (understanding, real- real-life, making connections, visualizing, engaging), life, decision making, consensus gathering, eff. Crisis comm.., engaging with faculty, technology) MEDIUM (understanding, decision, assumption testing, technology), MEDIUM (negative: age), LOW (negative: 71% MEDIUM (hands-on, eff. EM response, resources, engaging with students),

LOW (NEGATIVE: time spent) LOW (no of classes) time spent) 40 Results Summary Crime Scene AGREE CORRELATIO N Technology worked Cold case AGREE CORRELATION Bioattack CORRELATION Other issues LARGE (hands-on, real-life), MEDIUM MEDIUM 74% AGREE 56%

(understanding, decision-making, assumption testing, making connections, engaging/ approaching LARGE (understanding, handson, real-life, decision making, effective crisis comm.., engaging w/ students, approaching faculty) MEDIUM (consensus, 89% faculty), MEDIUM (NEGATIVE: age); LOW (visualizing, engaging w/students, no. of classes) Time spent MEDIUM NEGATIVE LARGE (NEGATIVE: (approaching faculty), low otherwise LOW (eff EM response, resources) LOW (NEGATIVE: age) NEGATIVE MEDIUM

LOW ON OTHERS (real-life, technology), visualizing, age), MEDIUM Uniformly distributed engaging with faculty, time spent) Average (NEGATIVE: handson, real-life, assumption testing, making connection), 67 % More than 8 hours LOW (NEGATIVE: understanding, interaction) # of classes taken LOW 61% more NEGATIVE on 92% more than all, no correlation than 4 4

LOW 89% more than 4 MEDIUM (hands-on) LOW on others with interaction 41 Results Summary Crime Scene AGREE CORRELATIO N Age Cold case AGREE CORRELATION AGREE Bioattack CORRELATION Demographics MEDIUM 44% between LARGE (time spent), 22% 20-30 yrs, 39% MEDIUM (negative: 49% MEDIUM between (NEGATIVE: 20-30 years, 30-40 yrs, 22% 41-50, understanding), LOW mirroring real-life; (NEGATIVE: (NEGATIVE: real-life, time 20-30 17% 50-60 yrs

improve decision 44% between understanding, spent) LOW (decision making, making; years, 27% 30-40 yrs assumption testing, eff crisis comm., engaging assumption visualizing, interaction), w/faculty, no of classes) between testing; making LOW (NEGATIVE: connections); 30-40 yrs hands-on, decisionLOW making, making (NEGATIVE: connections, engaging understanding, hands-on exp., visualizing); w/other students, no. of classes taken) LOW (POSITIVE: engaging w/students & faculty, no of classes taken) Gender 69% female

88% female 17% female 42 Conclusions Online scenario simulations add value to understanding. They help learning through discovery. Provide near real-life, hands-on experience. Help visualize, conceptualize and make connections between events and tools/objects. There is a correlation between student satisfaction and grades. Further studies with control group settings can uncover this or more facts. May or may not increase interaction among students. Further studies should 43 look into this. Conclusions There is evidence of increased studentto-faculty interaction. Technology glitches diminish value and satisfaction. (e.g. dead ends, loops) Information glitches diminish value and satisfaction. Age plays an important role in designing the content for the student audience. A negative correlation between time spent and learning the material was uncovered. Was the time spent on technical problems? Further studies

should look into optimal use of time. 44 Too much time spent may bring Conclusions The more sophisticated (game like) features make the tool more satisfactory. Students would like a sense of achievement at the end (e.g. solving piece of a puzzle, putting pieces together) Caution: Make them game-like but emphasize pedagogy. If designed as a group work with role playing ability may increase communication skills, help build core competencies in crisis management such as consensus gathering, effective resource allocation, understanding 45 Conclusions Recommend a move from low budget productions to sophisticated online simulation tools if budget permits. Expanded studies may show a link between the dollar amount spent for development and the student success outcome (Benefit-Cost Analysis). The tools should allow room for changing/ alternating between multiple scenarios to prevent boredom among professors and student sharing of results. Need buy-in from instructors. Engage

them in designing the tools. 46 Conclusions There are successful applications with proven results about other similar simulations employed by other higher ed instutions. UMUC can emulate on that. The new generation as Digital natives learn better with game-like simulations. 47 Acknowledgments This research was funded by the UMUC Faculty Research Grant Program. Those who contributed to the research include Husein Abdul-Hamid, Susan Blankenship, Howard Krivan, and Howard Dobres. 48

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