Campus Law Enforcement as a Problem Solver Instructor.

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Presentation transcript:

Campus Law Enforcement as a Problem Solver Instructor

Terminal Objective  Upon completion of this module, the participant will have a basic understanding of five problem solving models and how to apply the models to the role of a school based law enforcement officer.

Enabling Objectives  Identify the four steps of SARA  Apply the SARA model to a scenario  Describe Ockham's Razor  Describe the Problem Analysis Triangle  Recognize the 25 techniques of Situational Crime Prevention  Describe what a decision tree consists of and how it benefits Campus Law Enforcement

Campus Law Enforcement as a Problem Solver  Campus Law Enforcement job consists of solving problems everyday  Reaction to problems  Prevention of problems  What kind of problems are there in schools?  Drugs, violence, bullying, etc.

Problem Solving Models  Problem solving models include:  Ockham’s (Occam’s) razor  SARA model  Problem Analysis Triangle  Situational Crime Prevention  Decision Trees

Ockham’s Razor All other things equal, a simpler explanation is better than a more complex one.  Example:  Crime Prevention Through Environmental Design  Is it easier to install effective lighting, or  Hire multiple individuals to stand watch through rotating shifts at your unlit entrance  What are some examples of Ockham’s Razor being applied in schools?

SARA Model  Overview  S-canning  A-nalysis  R-esponse  A-ssessment

SARA Model (cont.)  Scanning:  Identify recurring problems  Prioritize problems  Analysis:  Identify and understand events and conditions surrounding problem  Narrow the scope of the problem

SARA Model (cont.)  Response:  Brainstorm for intervention  Search how other schools have addressed similar problems  Implement planned response  Assessment:  Analyze pre- and post- response data  Determine whether goals were met

Problem Analysis Triangle

Problem Analysis Triangle (cont.)  Visual aid to determine course of action  Example:  Students are fighting during lunch behind the cafeteria  Having a teacher (handler/manager/guardian) monitor students coming and going from cafeteria removes the availability of the place

Situational Crime Prevention  Problem Triangle helps analyze problem  SCP provides framework for intervention by:  Increasing the effort to commit crime  Increasing the risks for committing crime  Reducing rewards from crime  Removing excuses used to rationalize  Reducing provocations that incite offenders  25 Techniques of Crime Prevention

Situational Crime Prevention (cont.)

Decision Tree  Tool for choosing between alternatives  Useful for dealing with uncommon problems in schools  Problems that Campus Law Enforcement don’t deal with often  Provides a step-by-step process for solution  Ensures Campus Law Enforcement doesn’t miss important steps

Decision Tree (cont.) Is the person a danger to self or others Transport to common ground for assessment Is the person in need of immediate medial attention Is the contact taking place in normal business hours Transport to Common ground for 24/7 observation Transport to nearest hospital ER Choose the most convenient option Transport to Core Provider nearest your location Transport to Common Ground at ….. No Yes No

Practicum  Scenario #1  Sometime during school hours (i.e., between classes/during lunch/etc.) students or outsiders are spraying graffiti around campus. A teacher also reports smelling marijuana when walking to class.  Apply each level of SARA. What steps will you take to solve the problem during each: scanning, analysis, response, and assessment?

Practicum (cont.)  Scenario #2  Your school is experiencing many thefts of the vending machines. Students or outsiders are breaking into the machine for merchandise and cash.  Apply the techniques of Situational Crime Prevention to come up with solutions.

Open Discussion  What specific problems do you face in your ISD?  How may these problems be solved?

References  Popcenter.org  tes_www/node10.html 