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Data informed leadership hortlund
Data informed leadership hortlund
Data informed leadership hortlund
Data informed leadership hortlund
Data informed leadership hortlund
Data informed leadership hortlund
Data informed leadership hortlund
Data informed leadership hortlund
Data informed leadership hortlund
Data informed leadership hortlund
Data informed leadership hortlund
Data informed leadership hortlund
Data informed leadership hortlund
Data informed leadership hortlund
Data informed leadership hortlund
Data informed leadership hortlund
Data informed leadership hortlund
Data informed leadership hortlund
Data informed leadership hortlund
Data informed leadership hortlund
Data informed leadership hortlund
Data informed leadership hortlund
Data informed leadership hortlund
Data informed leadership hortlund
Data informed leadership hortlund
Data informed leadership hortlund
Data informed leadership hortlund
Data informed leadership hortlund
Data informed leadership hortlund
Data informed leadership hortlund
Data informed leadership hortlund
Data informed leadership hortlund
Data informed leadership hortlund
Data informed leadership hortlund
Data informed leadership hortlund
Data informed leadership hortlund
Data informed leadership hortlund
Data informed leadership hortlund
Data informed leadership hortlund
Data informed leadership hortlund
Data informed leadership hortlund
Data informed leadership hortlund
Data informed leadership hortlund
Data informed leadership hortlund
Data informed leadership hortlund
Data informed leadership hortlund
Data informed leadership hortlund
Data informed leadership hortlund
Data informed leadership hortlund
Data informed leadership hortlund
Data informed leadership hortlund
Data informed leadership hortlund
Data informed leadership hortlund
Data informed leadership hortlund
Data informed leadership hortlund
Data informed leadership hortlund
Data informed leadership hortlund
Data informed leadership hortlund
Data informed leadership hortlund
Data informed leadership hortlund
Data informed leadership hortlund
Data informed leadership hortlund
Data informed leadership hortlund
Data informed leadership hortlund
Data informed leadership hortlund
Data informed leadership hortlund
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Data informed leadership hortlund

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  • 1. 16  th  sep  2013   Torbjörn  Hortlund   Center  for  Educational  Management,  Uppsala  university  
  • 2. ¡  Approaching    the  role  of  principals  as  key   persons  in  connecting  the  process  of  generating   and  using  data  to  the  organizational  learning   activieties  in  school.   ¡  A  focus  on  collecting,  analysing,  making  sense  of   data  use  to  plan  action.   ¡  The  specific  school  leader  capacities  for  building   a  culture  of  data  use  and  using  data  to  improve   instructional  practice,  school  improvement  and   professional  accountability.  
  • 3. Information  that  is  collected  and  organized  to   represent  some  aspect  of  schools.     Information  such  as   -­‐  How  students  perform  on  a  test   -­‐  Observations  of  classroom  teaching   -­‐  Surveys  
  • 4. Accountability   Improvement  and   development   Results  of  students   1   3   School   2   4   (1)  from  a  accountability  perspective  with  a  focus  on  results   of  students;     (2)      from  a  accountability  perspective  with  a  focus  on  the    function  of  the  school;     (3)      from  a  improvement  and  development  perspective  with  a    focus  on  results  of  students     (4)      from  a  improvement  and  development  perspective  with  a    focus  on  the  school     Reactive                -­‐                    Proactive                  -­‐                    Interactive    
  • 5. The  growing  request  for  schools´  accountability   implies  also  that  schools,  increasingly,  are   expected  to  inform  their  external  environment   about  many  aspects  of  their  operation,   especially  about  the  results  of  learners.  Schools   –  accountable  for  the  results  of  students  –  must   deliver  data  about  these  results.  
  • 6. ¡  In  many  countries  one  can  see  a  movement   towards  result-­‐orientation  and  accountability.   ¡  New  Public  Management   -­‐  Counterproductive   -­‐  Competition   -­‐  Profit   •  Accountability   •  Audit  society   •  Trust  to  standards   •  Trust  in  numbers  
  • 7. This  movement,  emphasizing  results  and   accountability  is  subject  to  scientific  critics  such   as:     §  narrowing  the  curriculum   §  de-­‐professionalization   §  teaching  to  the  test  
  • 8. ¡  Basic  knowledge  –  Many  competences   ¡  Criteria  –  Creativity   ¡  Standardized  test  –  Assessments  for   learning   ¡  Accountability  –  Development   ¡  Control  –  Trust  the  profession    
  • 9. evalua&on   development       Extarnal   accountability   perspective   Outcomes/results   -­‐goal  achivement   -­‐national  exams   -­‐grades   -­‐surveys   Internal   development   perspective   -­‐Analyctical   knowledge  process     -­‐Reflection     -­‐Understanding     -­‐  Dialouge             Accountability   Control   Development     Culture  and  social  context       National  goals   National  goals   DATA  DRIVEN    -­‐-­‐-­‐  DATA  INFORMED-­‐-­‐-­‐EVIDENCE   INFORMED                                    ”…and  to   balance”  
  • 10. ¡  Develop  the  students  awareness  in  history   ¡  Develop  their  curiosity,  lust  and  ability  to  play   and  learn   ¡  Life-­‐long  learning   ¡  Respect  for  other  people   ¡  Democratic  values   14  
  • 11. ¡  What  do  I  know  about  my  school?   ¡  How  do  I  know  that?  
  • 12.  “Not  everything  that  counts  can  be   counted.    And  not  everything  that  can  be   counted,  counts.”              -­‐  Albert  Einstein    
  • 13. ¡  Input  data  (intake,  home  language,   socioeconomic  status)   ¡  Outcome  data  (data  on  student   achievement,  well-­‐being  surveys)   ¡  Process  data  (observations  and  documents   on  instruction  and  learning  strategies)  
  • 14. Input   • Resources   • Laws   • Competence   • External   conditions   • Schedule   • Teaching   experienc   Process   • Working   methods   • Relations   • Learning   strategies   • Content   Outcome  data   • Results   • Goal   achievement   • Learning   outcome   • Grades   The  pedagogical  evaluation  chain  
  • 15. ¡  Student  demographic:  enrolment,  attendance,  dropout  rate,   ethnicity,  gender,  grade  level,  trends  in  student  population  and   learning  needs,  school  and  student  profiles,  data  disaggregated  by   subgroups   ¡  Perceptions  of  learning  environment,  values  and  beliefs,   attitudes,  observations  .  .  .  (e.g.,  held  by  a  school’s  teachers).   ¡  Student  learning:  standardized  tests,  norm/criterion-­‐referenced   tests,  teacher  observations,  authentic  assessments,  learning  skills   and  work  habits,  student  work  samples.   ¡  School  processes:  descriptions  of  programs,  instructional   strategies,  classroom  practices   ¡  Teacher  characteristics,  behaviour  and  professional  learning:   Teacher  assignment  (grade,  subject  area,  students  served),   qualifications,  retention,  participation  in  professional   development   ¡  Environment  data  such  as  parent/community  surveys.      
  • 16. A  principal  who  wants  to  find  out  whether  parents   understand  the  new  school  report  cards  could  use   following  data:   -­‐  Data  on  parent  characteristics  such  as  home   language  (input  data).   -­‐  Analysis  of  parent  understanding  of  the  reports   through  discussions  and  surveys  with  parents   (outcome  data).   -­‐  Examination  of  the  report  cards  to  see  if  there   are  features  of  the  report  that  aid  or  hinder   parent  understanding  (context  data).    
  • 17. ¡  Purpose   ¡  Data  collection   ¡  Analysis   ¡  Interpretation/conclusions   ¡  Action  
  • 18. Johari  2.0 What we have knowledge about What we have little knowledge about We have data Known field Blind field We have no data Private field Black hole
  • 19. ¡  Data  can  be  used  as  a  tool  for  improvement   ¡  Sceptism  about  data  or  a  tool  for   improvement?   ¡  Data  is  nothing  ”out  there”.  Data  can  be  an   important  part  in  ongoing  process  in  analysis,   insights,  learning  and  improvements  of  the   practice.  
  • 20. ¡  How  do  I  create  a  culture  of  responsibility  outside   the  teacher´s  classroom?   ¡  How  do  I  create  good  conditions  for  teachers´   learning?     ¡  How  do  we  create  curiosity  about  what´s  happening   in  the  colleagues  classrooms?     ¡  How  do  we  create  a  culture  where  teacher  trust   each  other  and  encourage  reflection  on  own   practice  by  using  data?  
  • 21. Categorie   Definition   EExamples   Teaching  and  learning   What  educatots  do  in  their   classrooms  in  instruction   and  assessment.   What  teaching  and   assessment  strategies  are   we  using?   How  might  we  change  out   teaching  and  assessment   practices  to  achieve  the   desired  results?   Parent  Opinion   How  parents  feel  about   and  interact  with  school.   How  well  are  we   connecting  with  the  parent   community?     School  culture   The  assumptions,  beliefs,   and  relationships  that   define  the  organisation´s   view  of  itself  and  its   environment.   What  does  the  staff  of  this   school  believe  about   student  learning?   What  is  the  nature  of  the   professional  relationships?  
  • 22. Categorie   Definition   Questions   Student  attitudes   Descritions  of  how   students  feel  about…   How  engaged  are   students  in  this  school?   Staff   Descriptive  information   about  the  faculty.   What  talents  do  staff   members  hold?   How  are  different  faculty   strenghts  being  utilized   in  the  school?  
  • 23. ¡  Choose  five  different  types  of  data  that  give  you   valuable  information  about  your  school  and  students.     ¡  Write  down  each  data  on  a  post-­‐it  and  put  your  five   notes  on  a  paper.     ¡  Without  talking,  walk  around  and  look  at  each  others   notes.   ¡  Reflection  in  groups.      
  • 24. Control   Internal  needs              External  accountability   Improvement/ Development   Part  2   •  Categorize  your   data!   •  Findings  and   reflections?  
  • 25. ¡  What  do  you  see?   ¡  What  do  you  not  see?  What  do  you  want  to   know  more  about?   ¡  What  do  think/feel?  Speculate!   Individually  and  then  in  small  groups  
  • 26. Different  authentic  examples  of  data  are  exposed  in   the  room.  Work  in  groups  examining  the  data  and   discuss:     -­‐  What  do  data  tell  you?  About  context,  input,  process   and/or  output?  (Use  the  CIPO-­‐model)     -­‐  What  doesn´t  the  data  tell  you?  What  risks  to  be   invisible?   -­‐  What  kind  of  analysis  is  possible  to  make?   -­‐  What    further  data  is  needed  for  wise  decision-­‐making?  
  • 27. ¡  Data  collection  at  the  school   ¡  Working  with  data   ¡  Purpose  of  data  use   ¡  Role  of  the  principal   ¡  Practice  of  the  principal  related  to  data  use   ¡  Attitudes  towards  data  use   ¡  Abilities  of  the  principal  
  • 28. ¡  setting  directions:  (building  a  shared  vision;  fostering  the   acceptance  of  group  goals;  high  performance   expectations);   ¡  developing  people:  (providing  individualized  support/ consideration;  intellectual  stimulation;  providing  an   appropriate  model);   ¡  redesigning  the  organization:  (building  collaborative   cultures;  restructuring;  building  productive  relationships   with  families  and  communities;  connecting  the  school  to   its’  wider  environment);   ¡  managing  the  instructional  (teaching  and  learning)   program:  (staffing  the  program;  providing  instructional   (teaching  and  learning)  support;  monitoring  school   activity;  buffering  staff  from  distractions  to  their  work).    
  • 29. ¡  Practice   -­‐  Katharina  and  Anette   -­‐  Mia  and  Karin   ¡  Theory  –  theoretical  framework  
  • 30. ¡  Learning  communities   ¡  Learning  and  improvement  by  using  data    
  • 31. ¡  Calman  (2010)  found  that  school  effectiveness  is   strongly  associated  with  the  effective  use  of  data   at  both  the  classroom  and  school  levels.  At  the   classroom  level,  in  effective  schools,  teachers   monitor  student  progress  on  a  regular  and  on-­‐ going  basis  in  order  to  provide  both   differentiated  learning  experiences  and   appropriate  support  to  meet  the  needs  of   students.  Assessing  and  tracking  of  progress  are   undertaken  with  rigour,  and  data  are  analysed   with  considerable  care  to  identify  students  or   groups  of  students  who  need  specific  help.      
  • 32. At  the  school  level,  effective  leaders  ensure  that   both  outcome  and  process  data  are  made   available  for  use  by  school  staff  and  that   assessment  data  are  integral  to  monitoring  the   attainment  of  school  goals.  When  data  are  being   used  effectively,  decisions  about  the  focus  of   instructional  programs  and  practices,  professional   learning  needs,  resource  requirements,  intensity  of   support  for  students’  needs  and  placement  of   support  staff  are  grounded  in  data  analysis.    
  • 33. SER  –  skills  in  using,  handling  and   understanding  data  (Calman,  2010  &  Robinson,  2006)     -­‐  Involving  data  in  the  ongoing  process  to   improve  the  instruction.   -­‐  Teaching  students  to  examine  their  own  data.   -­‐  Formulating  a  vision  for  using  data.   -­‐  Create  a  structure  for  a  data-­‐informed   culture.   Hamilton  et  al  (2009)    
  • 34. It  means  not  an  exclusive  appeal  on  scientific   evidence  in  the  process  of  educational  decision-­‐ making,  but  the  integration  of  evidence  with  the   judgement  and  expertise  of  the  practitioner.  It   means  also  an  emphasis  on  professional   conversations:  the  collectively  identifying  of  the   relevance  and  meaning  of  the  evidence  through   cyclical  processes  of  questioning,  interpretation  and   review  by  the  professionals,  involved  in  the  practice   of  making  education  better.     Dixon  (  1999  ),  Nonaka  &  Tackeuchi  (1996),    Crossan,   Lane  &  White  (1999)  Hord  (1997)  and  Verbiest  (2004,   2012).      
  • 35. ¡ Develop  an  inquiry  habit  of  mind.     ¡ Become  data  literate.     ¡ Create  a  culture  of  inquiry.    
  • 36. ¡  Values  deep  understanding   ¡  Reserves  judgement  and  has  a  tolerance  for   ambiguity   ¡  Takes  a  range  of  perspectives  and   systematically  poses  increasingly  focused   questions  
  • 37. ¡  Why  is  this  issue  an  important  area  to  pay   attention  to?   ¡  What  is  prompting  this  decision?   ¡  Who  will  be  influenced  by  it?   ¡  Who  needs  to  be  involved?   ¡  What  is  our  role  in  this  decision?   ¡  Where  are  we  now?   ¡  What  do  we  think  we  know?   ¡  Where  do  we  want  to  go?  
  • 38. ¡  Thinks  about  purpose(s)   ¡  Recognizes  sound  and  unsound  data   ¡  Is  knowledgeable  about  statistical  and   measurement  concepts   ¡  Recognizes  other  kinds  of  data   ¡  Makes  interpretation  paramount   ¡  Pays  attention  to  reporting  
  • 39. ¡  What  are  we  trying  to  understand  better?   ¡  What  is  the  focus  of  this  picture?   ¡  What  do  we  need  to  know  to  capture  the   complexity?   ¡  What  data  do  we  need?  
  • 40. ¡  How  do  we  make  sense  of  these  data?   ¡  What  help  do  we  need  to  analyze  and   interpret  the  data?   ¡  How  much  confidence  do  we  have  in  these   data?   ¡  What  are  the  limitations  of  the  data?   ¡  What  can  we  learn  from  the  data?   ¡  What  other  data  do  we  need?  
  • 41. ¡  Involves  others  in  interpreting  and  engaging   with  the  data   ¡  Stimulates  an  internal  sense  of  ”urgency”   ¡  Makes  time   ¡  Uses  ”critical  friends”  
  • 42. ¡  How  will  we  engage  the  audience?   ¡  How  will  we  share  what  we  have  learned?   ¡  How  do  we  keep  the  appeal  to  data  as  a   routine  part  of  our  planning  and   improvement  process?  
  • 43. ¡  Leadership  that  focuses  attention  and  effort   on  improving  student  learning   ¡  Leadership  that  guide  the  learning  of   individual  professionals   ¡  Leadership  that  guides  what  has  been  called   ”system  learning”  
  • 44. Knapp,  M.,  Copeland,  M..,  &  Talbert,  J..  (2003,  February).  Leading   for  learning:  Reflective  tools  for  school  and  district  leaders.  Seattle,   WA:  Center  for  the  Study  of  Teaching  and  Policy.  Retrieved  7/28/07   from   http://www.dept.washington.edu/cptmail/ Reports.html#WallaceSummary.  
  • 45. ¡  Provide  formal  and  informal  structures  to  support  data  use;  for   example:   §  At  the  district  level,  formal  structures  include  technology,  instructional   vision,  curriculum  and  school  improvement  and  alignment.   §  At  the  school  level,  formal  structures  include  centring  data  initiatives   on  specific  measurable  goals,  building  data  structures  from  already-­‐ existing  structures  and  new  structures  such  as  building  capacity  for   triangulation  of  data.   §  Informal  structures  include  encouraging  collaborative  work  and  using   data  in  a  non-­‐threatening  way.   ¡  Focus  conversations  on  instructional  improvement;  for  example:   §  Engage  in  early  conversations  prior  to  implementation  of  a  data   initiative.   §  Centre  open-­‐to-­‐learning  conversations  on  instruction  and  practice.   §  Foster  collaborative  conversations  that  inspire  teacher  leadership.    
  • 46. ¡  Implement  data  initiatives  purposefully  so  that:   §  Teachers  see  the  connection  between  data  use  and   instruction.   §  Infrastructures  support  data  use  both  in  terms  of   available  hardware  and  data.   §  Professional  development  integrates  existing  learning   opportunities  and  offers  many  different  times  and   ways  for  staff  to  learn  the  data  system.   ¡  Make  time  to:   §  Align  goals  of  data  with  district  instructional  goals.   §  Offer  professional  learning  that  is  tailored  to  teachers’   personal  contexts.  
  • 47. How  do  I  create  a  culture  of  inquiry?     Actions  to  support  a  culture  of  inquiry       Each  group  talk  about  what  you  want  to  know  more   about  –  talk  about  concepts,  perspectives  and  context.   Formulate  two  questions  you  want  to  know  more  about   by  getting  input  from  other  groups  in  the  room.     Select  two  persons  who  will  leave  the  group  as   knowledge  hunters.      
  • 48.     The  knowledge  hunters  leave  the  group  and   bring  one  of  the  two  questions.     The  rest  of  the  group  are  experts  and  will  share   their  knowledge  to  new  knowledge  hunters.      
  • 49. The  knowledge  hunters  go  back  to  their   original  group.    
  • 50. The  original  groups  are  sharing  new  knowledge   and  experiences.     Make  a  summary  on  a  poster:   Write  down  your  question  and  a  short  summary   (concepts,  signs,  pictures).        
  • 51. Repeat  step  2-­‐4  with  the  second  question.    
  • 52. 1)  How  can  you  collect  information  about  teaching   practices  to  test  ideas  about  what  might  explain   students  strengths  and  weaknesses?   2)  How  might  you  encourage/develop  interventions   that  use  data,  and  examine  their  impact?   3)  How  could  you  or  your  organisation  increase   collaboration  around  data  use?   4)  Seven  steps  in  using  data:  receiving  data,  reading  and   discussion,interpretation,    diagnosis,  planning,   implementation  and  evaluation.   a)  What  steps  do  you  think  are  strenghts  in  your   school?  How  do  you  know?   b)  Which  steps  do  your  think  need  to  be  improved?    
  • 53. 1)    Fill  in  the  self  evaluation  paper  individually   ¡  Make  a  first  analysis.  What  do  you  need  to  know  more  about?   Select  an  area  you  need  to  know  more  about!   ¡  What  do  I  know  today  in  this  area?   ¡  What  information/data  do  I  build  my  knowledge  on?   ¡  How  reliable  is  the  data?   ¡  What  risks  to  be  invisible?   §  What  additional  data  is  needed?     2)  Make  a  plan  for  your  inquiry     3)  a)  Discussion  in  groups  concerning  the  self  evaluation  (patterns,   differences,  similarities)            b)  Presentations  of  your  inquiry  plans  –  ”critical  friends”    
  • 54. ¡  Aim  –  why?   ¡  Object  –  what?   ¡  Organization   ¡  Criteria   ¡  Collecting  data   ¡  Analyzing  data   ¡  Communicating  new  knowledge   ¡  Planning  actions  

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