2016 INFORMS Annual Meeting Program

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INFORMS Nashville – 2016
319
TC49
211-MCC
Experiential Field Learning
Sponsored: Education (INFORMED)
Sponsored Session
Chair: Benjamin Grannan, Virginia Military Institute, Lexington, VA,
United States,
1 - A Survey Of Issues And Best Practices In Field-based Education
Michael F Gorman, University of Dayton,
There is a growing literature on field-based education in OR/MS. I survey recent
literature and share common benefits, issues and best practices from published
works.
2 - A Toolkit To Facilitate Quality Work In Field Courses
Patrick S. Noonan, Emory University, Atlanta, GA, United States,
Two beliefs about field courses are widely shared: 1. Good field experiences can
greatly boost student ability to apply course concepts & tools to real-world
challenges ahead. 2. Facilitating “good field experiences” is hard... for everyone.
Tackling real-world problems is inherently difficult - that’s the point! But one
central problem that educators can address is that few participants - students,
faculty, TAs - have been trained in the consultative process. Adapting the toolkit
of management consultants can improve the learning experience and the results
for clients/problem-owners, and ease the teaching burden. We share experience &
techniques from Emory’s “Management Practice” program.
3 - Supervising Undergraduate Field Based Analytics Projects
Benjamin Grannan, Virginia Military Institute,
Supervising undergraduate students working on real world analytics projects
results in unique challenges. In this talk we discuss the experience of recruiting
undergraduate students from multiple disciplines, selling the value of analytics to
clients and helping students transition their classroom skills to the often messy
real world project setting. Examples from both a summer five week field based
independent research course and an extracurricular student-led analytics
consulting club are presented.
TC50
212-MCC
SpORts: Sports Analytics I
Sponsored: SpORts
Sponsored Session
Chair: Stephen Hill, University of North Carolina Wilmington, 601
South College Road, Wilmington, NC, 28403-5611, United States,
1 - Do Pitchers Differ on Batting Average on Balls In Play or Defense
Independent Slugging Percentage?
Matthew Hall, University of Alabama, Culverhouse College of
Commerce and Business Administration, Tuscaloosa, AL, 35487-
0226, United States, , James Cochran
Using ANOVA and MANOVA, we systematically examine data for pitchers who
have pitched at least 160 innings in five or more seasons since 1999 to assess
whether they differ on Batting Average on Balls in Play (BABIP - common
Sabermetric wisdom says they do not) or Defense Independent Slugging
Percentage (DISP).
2 - Are You Ready For Some Football? An Analysis Of Monday Night
Football Viewership
Bhupesh Shetty, University of Iowa,
Analyzing data from 1993 to 2014, we conduct a three-pronged analysis of
Monday Night Football (MNF) viewership. First, we present a model using ex
post facto factors that explains over 90% of the variability. Then we present a
model using only factors known in the April preceding the season (when the NFL
schedule is announced). Finally, we use the predictive regression model to
estimate objective function coefficients in an integer program formulation that
maximizes expected MNF viewership. We conduct simulation experiments to
determine the impact of forecast error on the optimal MNF schedule.
3 - A Handicap System For Tennis
Timothy Chan, University of Toronto, Toronto, ON, Canada,
, Raghav Singal
Handicap systems are used in many sports and games to improve competitive
balance and equalize the probability of winning a match between two or more
players. In this paper, we develop a handicap system for tennis using a MDP
model to quantify the appropriate handicap between two players of unequal
ability. We apply the model to real match data to estimate professional handicaps.
We also demonstrate how our handicap can be mapped to a tennis rating system,
which can facilitate broader uptake at a grassroots level.
4 - Does The Current Golf Handicap System Bias Match Play
Outcomes?
Martin L Puterman, Professor Emeritus, University of British
Columbia, Sauder School of Business, 2053 Main Mall, Vancouver,
BC, V6T 1Z2, Canada, , Timothy
Chan, David Madras
In amateur golf, lower handicap players “give strokes” to higher handicap players
on the basis of the difference between handicaps so as to make head-to-head
matches fair. In a match, the “standard way” to allocate handicap strokes is on the
basis of the course hole difficulty ranking. Using a data driven simulation based
on over 600 rounds, we show that standard stroke allocation and hole rankings
favor the superior player. We investigate the simultaneous impact on match
fairness of alternative hole rankings, allocations of handicap strokes to specific
holes and awarding extra strokes to higher handicap players.
TC51
213-MCC
Modeling Complex Systems in Education
Sponsored: Public Sector OR
Sponsored Session
Chair: Roxanne Moore, Georgia Institute of Technology, 1, Atlanta, GA,
30333, United States,
1 - Applying System Dynamics Models To Steam Interventions
Michael Helms, Georgia Tech,
Education researchers implement education interventions in highly complex
systems, where intervention outcomes depend heavily on the system attributes,
actors and interactions over time. We developed a modeling process using system
dynamics principles to better understand the complex interactions and
mechanisms of a STEAM education intervention. In this presentation we will
discuss the resulting causal loop diagram, and the implications of our modeling
process in terms of intervention design, implementation and sustainability.
2 - Education as a Complex System: Opportunities, Challenges, and
Perspectives
Mirsad Hadzikadic, University of North Carolina, Charlotte, NC,
United States,
Education is a large complex systems. It presents many challenges for its full
understanding. However, if done well, it can bring tremendous benefits to people,
society, and industry. It can be simulated and modeled from different perspectives,
including the content of education, the modality of teaching/learning, improving
access to education, school assignments, classroom assignmnents, seating
assignments, within classroom interaction, student-student interaction, or
student-teacher interaction. This talk will present an overview of various
technologies to analyze/simulate/model the previously stated perspectives.
3 - Modeling Interventions In Complex Educational Systems
Britte H Cheng, SRI International, Menlo Park, AL, United States,
The ability of complex social systems to resist policy mandates—to revert to the
norm—has gained increased attention in educational research. This paper
presents a perspective on the reasons behind the policy resistance of education
systems including the lack of approaches for evaluating possible policies before
implementation. We highlight two projects (one around STEM retention in
undergraduate and one on K-12 formative assessment systems) that modeled
educational systems to explore proposed policy implementations before they are
put into practice.
TC51