Supporting Positive Behaviour in Alberta Schools

Supporting Positive Behaviour in Alberta Schools Dwaine M Souveny Central Alberta Regional Consortium 2010-2011 D.M. Souveny Data Driven Decision Making

Supporting Positive Behaviour in Alberta SchoolsKey Element # 9Data Driven Decision Making May 17, 2011 Dwaine M Souveny Central Alberta Regional Consortium 2010-2011 D.M. Souveny Data Driven Decision Making

Supporting Positive BehaviourIn Alberta Schools (2008) • A School Wide Approach • A Classroom Approach • An Intensive Individualized Approach D.M. Souveny Data Driven Decision Making

Supporting Positive Behaviour in Alberta Schools10 Key Elements Key Element 1: Positive Relationships Key Element 2: Learning Environment Key Element 3: Differentiated Instruction (DI) Key Element 4: Understanding Student Behaviour Key Element 5: Social Skills Instruction Key Element 6: Positive Reinforcement Key Element 7: Fair and Predictable Consequences Key Element 8: Collaborative Teamwork/Leadership and the Wrap Around Process Key Element Nine: Data-driven Decision Making D.M. Souveny Data Driven Decision Making

Key Element #9: Data-driven Decision Making Questions to consider: • How do we know whether the strategy is being effective? • What measurement tools will be used to record the desired/target behavior? • How will the family play a role in this process? D.M. Souveny Data Driven Decision Making

“Schools need reliable evidence that the new actions that they are taking are truly making a positive difference and are resulting in measureable outcomes” School Wide Approach, pp. 74 D.M. Souveny Data Driven Decision Making

Why Collect DataWhat are some reasons for collecting data? • Clarify what problem behaviours are occurring • Understand the purpose and context of specific behaviours • Establish priorities and school wide goals • Identify possible strategies and techniques to use based on • Preventing problems • Reacting to situations when they occur • Evaluate success D.M. Souveny Data Driven Decision Making

Gathering Data to Understand Student Behaviour Functional Behaviour Assessment It is essential to understand the purpose or function the behaviour is serving the individual, as well as the context in which that behaviour occurs. D.M. Souveny Data Driven Decision Making

Functional Behaviour Assessment • Assessment involves examining both antecedents and consequences to understand their effects on behaviour. • Antecedents are any situations, events, demands or expectations that proceed or trigger problem behaviours. • Consequences are any events or conditions which follow behaviour. D.M. Souveny Data Driven Decision Making

AntecedentsWhat came before the behaviour • Who was involved? • When did the behaviour occur? • What are some times when behaviour challenges often occur? • Where did the behaviour occur? • Where do behavioural challenges often occur? • What happened just before? • What are some typical “triggers” for challenging behaviour? D.M. Souveny Data Driven Decision Making

Behaviour What is the behaviour? • How frequently does it occur? • What is it’s intensity? • What is it’s duration? D.M. Souveny Data Driven Decision Making

FrequencyKISS Principle Event Recording The number of times a discreet behaviour occurs • Using • Checklists • Your pockets • Wrist meters Interval recording Record the behaviour if it occurs in a set interval • Time sampling • Yes/no D.M. Souveny Data Driven Decision Making

Intensity How strong was the behaviour? • Loud • Painful On a scale of 1-10… D.M. Souveny Data Driven Decision Making

Duration recording How long did the behaviour last? Use a stop watch …or better yet – your phone! D.M. Souveny Data Driven Decision Making

Consequences What happens following the behaviour? Desired Consequences Undesired consequences Are the consequences actually desired or undesired? D.M. Souveny Data Driven Decision Making

Data Driven Decision Making • Select a problem behaviour • Chose a data system that is effective and efficient • Collect the data • Summarize and assess the data • Use this analysis to • Identify the function of the behaviour • Determine desired behaviours • Select teaching strategies • Develop an effective behaviour support plan D.M. Souveny Data Driven Decision Making

ScenarioWhat are the ABCs According to the teacher, Peter Player is always playing is class. When he was observed it was noted that during math class Peter did 5 of the questions and then started talking with the person behind him. When this occurred his teacher went over and told him to get back to work. This appeared to occur frequently with Peter doing some of his work, then going off task, being told to do his work and so on… Peter was “on task” 15 minutes of the 35 minute class. D.M. Souveny Data Driven Decision Making

Collect Data D.M. Souveny Data Driven Decision Making

Determine Progress D.M. Souveny Data Driven Decision Making

Celebrate success • For the student • For the team: Of the goals/strategies being used • For the school D.M. Souveny Data Driven Decision Making

Using the ABCsFor Success Analyze one of the behaviours within your classroom and from the analysis develop a strategic approach D.M. Souveny Data Driven Decision Making

Supporting Positive Behaviourin Alberta Schools….stay tuned & invite a friend Next time: Making a Plan: Putting it all together Targeting supports Collaborating together IPPs and MAPs June 21, 2011 Email or phone me 403 506 7091 dynamicdevelopment@shaw.ca D.M. Souveny Data Driven Decision Making

Supporting Positive Behaviour in Alberta Schools