scholarly journals Minding The Big Picture: Using Discrete Event Process Simulation As A Problem Solving Tool For Students

2020 ◽  
Author(s):  
Susan Scachitti ◽  
Juan Salinas ◽  
Deepthi Karanam
Keyword(s):  
Problem Solving ◽  
Process Simulation ◽  
Discrete Event ◽  
Big Picture

Capacity Decision in Emergency Hospital Operation Rooms

2018 ◽  
pp. 140-155
Author(s):  
Ana Carolina Pereira de Vasconcelos Silva ◽  
Daniel Bouzon Nagem Assad ◽  
Thais Spiegel
Keyword(s):  
Emergency Department ◽  
Problem Solving ◽  
Discrete Event Simulation ◽  
Operations Management ◽  
Discrete Event ◽  
Design Management ◽  
Simulation Tool ◽  
Event Simulation ◽  
Production Distribution ◽  
Capacity Decision

The operations management is a multidisciplinary field that investigates, for instance, the design, management and processes improvement focused on the development, production, distribution and delivery of products and services, encompassing activities such as the implementation of policies, making quota decisions, identification and problem solving, response to uncertainty, among others. Regarding the resources dimensioning in hospitals, the Brazilian scenario is limited to legislative instruments that assume a prior and added sizing. This chapter uses a discrete event simulation tool to set the amount of operation rooms needed for patient care in an emergency department, so that emergency patients have guaranteed compliance, minimizing the cancellation of elective surgeries because of this type of demand. As a result, it was found that the minimum amount established by normative instruments was not appropriate to the specific requirements of the organization.

An Outline of a Series of Diversified Process Simulation (DIPOS) Experiments

1982 ◽  
Vol 26 (11) ◽  
pp. 954-958
Author(s):  
Erik Hollnagel
Keyword(s):  
Problem Solving ◽  
Process Simulation ◽  
Small Scale ◽  
Data Recording ◽  
Series Of Experiments ◽  
Machine Systems

This paper describes a framework for small scale experiments on man-machine systems. Four basic techniques relying on reconstruction, discrimination, prediction and problem solving are discussed together with suggestions for a series of experiments. Finally, the data recording requirements from the various parts of a DIPOS system are discussed in detail.

Problem-Solving Courts

2019 ◽  
pp. 200-210
Author(s):  
David DeMatteo ◽  
Kirk Heilbrun ◽  
Alice Thornewill ◽  
Shelby Arnold
Keyword(s):  
Criminal Justice ◽  
Problem Solving ◽  
Criminal Justice System ◽  
Behavioral Health ◽  
Justice System ◽  
Health Needs ◽  
Research Practice ◽  
Future Directions ◽  
Problem Solving Courts ◽  
Big Picture

This chapter summarizes problem-solving court principles and concepts, provides an overview of the limited reach of problem-solving courts, describes alternatives to problem-solving courts (e.g., diversion, smart sentencing, probation/parole), discusses strategies for incorporating a problem-solving approach in other aspects of the justice system, and examines current innovations for expanding problem-solving justice. This chapter discusses a “big picture” approach that includes a discussion of how reformation of certain aspects of the criminal justice system could effectively address the behavioral health needs of offenders and reduce recidivism. This chapter also discusses future directions within problem-solving justice in terms of research, practice, and policy.

scholarly journals Modeling & Simulation-Based Problem Solving Process in Sustainable Living Lab

2021 ◽  
Vol 13 (7) ◽  
pp. 3690
Author(s):  
Changbeom Choi ◽  
Seungho Yang ◽  
Seon Han Choi ◽  
Sooyoung Jang
Keyword(s):  
Decision Making ◽  
Problem Solving ◽  
Modeling And Simulation ◽  
Citizen Participation ◽  
Scientific Evidence ◽  
Discrete Event ◽  
Modern Society ◽  
Sustainable Living ◽  
Living Lab ◽  
Problem Solving Process

Modern society consists of various groups according to their respective interests. The importance of the citizen participation decision-making process in which such various groups get involved in the numerous decision-making of the society has been emerging. The living lab (LL) can be a sustainable approach in such a modern society because all stakeholders can participate in the problem-solving process. In LL, every group communicates, defines their problems, and discusses with experts to find the best solution. For this process to work effectively, the discussions should be based on clear scientific evidence instead of vague words. This study introduces the modeling and simulation (M&S) process to establish a theoretical basis to help the participants in LL identify problematic situations and analyze the solutions. This process involves discrete event system formalism with a set-theoretical modular form among various modeling and simulation theories and the execution environments. Based on them, participants can reuse or extend the existing simulation model to accelerate the problem-solving process of LL. The case study for multi-modal transit station analysis demonstrates the effectiveness of M&S in LL.

Organizational problem-solving and school discipline: comparing the roles of schoolwide behavior management technologies

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Vincent Cho ◽  
Katrina Borowiec ◽  
Kaitlyn F. Tuthill
Keyword(s):  
Problem Solving ◽  
School Improvement ◽  
Behavior Management ◽  
Classroom Behavior ◽  
Collaborative Problem Solving ◽  
Behavioral Data ◽  
School Level ◽  
Comparative Case Study ◽  
Content Type ◽  
Big Picture

PurposeApplications for tracking and managing classroom behavior have become increasingly commonplace, thus making it possible to incorporate nonacademic data into collaborative problem-solving and school improvement. Whether or how these platforms might support such aims, however, is not known. Accordingly, this study explores practices involving these applications, focusing especially on problem-solving among educators and with students' families.Design/methodology/approachThis comparative case study took place in three schools. In total, 34 semistructured interviews were conducted with teachers and school leaders. Analysis included qualitative coding as well as the development of within- and cross-case summaries.FindingsSchools varied greatly when it came to using behavior management platforms as a part of problem-solving. At a basic level, it was not uncommon for educators to use behavioral data for classroom troubleshooting or check-ins with students and transactional communications with families. However, only two schools attempted to use behavioral data for more systemic, “big picture” problem-solving, such as to make discipline policies more equitable or to improve teacher practices. The richness of collaboration with families seemed especially shaped by how and how frequently data were shared (e.g. automated notifications and paper printouts).Originality/valueEmpirical research about behavior management applications has been limited and focused only at the classroom level. The present study contributes new knowledge about the school-level implications of these platforms, while also expanding conversations about how behavioral data may be incorporated into data-informed problem-solving. Implications for leadership and theory are also discussed.

scholarly journals Analyzing Characteristics of Experts in the Context of Stoichiometric Problem-Solving

2019 ◽  
Vol 9 (3) ◽  
pp. 219
Author(s):  
Ozcan Gulacar ◽  
Alexandra Tan ◽  
Charles T. Cox ◽  
Jennifer Bloomquist ◽  
Okechukwu Jimmy ◽  
...  
Keyword(s):  
Graduate Students ◽  
Problem Solving ◽  
College Graduates ◽  
Coding System ◽  
College Chemistry ◽  
Amount Of Information ◽  
Career Trajectories ◽  
Network Method ◽  
Big Picture ◽  
Problem Solving Strategies

To gauge the variability in expert problem-solving strategies for stoichiometry problems, a set of experts in different career tracks were studied with the cohort including 17 graduate students in chemistry, three college chemistry instructors, and seven college graduates working in the industry. The goal of the study was to determine whether variability would be observed based upon experience and career trajectories. The data were collected using interviews and analyzed qualitatively and quantitatively using the COSINE (Coding System for Investigating Sub-problems and Network) method. Although the method was developed for the analysis of undergraduate problem-solving, it appeared to be effective in examining experts’ problem-solving in chemistry as well. The study revealed similar abilities for succeeding at solving a series of problems, but the strategies were variable for the three cohorts of experts. Specifically, the amount of information used to solve the problems differed across the three cohorts with graduate students focusing more upon each of the specific subproblems within each problem compared to industry chemists utilizing the big-picture approach in lieu of breaking down each problem into respective subproblems. Familiarity with the question types and ability to chunk information were common characteristics observed consistently for the expert participants, which is consistent with existing research.

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