Exploring  alternative  causes  for  learning  outcomes

138   Analysis    

5.7.2. Exploring  alternative  causes  for  learning  outcomes  

In  this  section,  I  explore  whether  removal  of  judgments  or  import  of  behaviour  could  be  effects  of,   or  at  least  impacted  by  factors,  such  as,  years  of  experience  as  a  manager,  years  in  the  current   position,  number  of  employees,  the  time  it  took  the  participants  to  formulate  their  problem  in  the   first  meeting,  which  industry  the  participants  work  in,  whether  the  participants  work  in  the   private,  the  public,  or  a  hybrid  sector,  and  participants  gender.  

In  the  above  analysis,  I  have  found  a  predominance  of  removal  of  judgments  in  G1  and  G2  post-­‐

interviews  and  a  predominance  of  import  of  behaviour  in  G3  and  G4  post-­‐interviews.  I  

interpreted  this  as  evidence  that  these  effects  are  effects  particular  to  the  learning  interventions   (AI  and  MI)  used  in  these  groups.    

However,  it  is  possible  that  the  participants,  by  chance,  were  grouped  in  such  a  way  that  the   predominance  of  removal  of  judgment  in  G1  and  G2  and  the  predominance  of  import  of  behaviour   in  G3  and  G4  were  caused  by  something  other  than  having  gone  through  a  particular  learning   intervention  as  suggested  in  the  above  analysis.    

As  mentioned  in  the  methodology  section,  I  used  randomisation  to  deal  with  possible  

confounding  factors.  However,  as  I  showed  in  the  descriptive  analysis,  certain  factors  were  not   evenly  distributed  across  the  six  groups.  For  example,  in  G3,  all  participants  were  women,  and  G5   had  more  men  than  any  other  group.  Thus,  if  women  are  more  likely  to  import  behaviour  than   men,  then  the  high  degree  of  participants  experiencing  import  of  behaviour  in  G3  might  (at  least   in  part)  be  due  to  the  gender  distribution  and  not  necessarily  due  to  the  MI  intervention  used  in   this  group.    

To  explore  this  in  depth,  I  have  created  a  number  of  population  pyramid  graphs.  In  these  graphs,   the  y-­‐axis  represents  the  factor  I  wish  to  explore,  for  example  years  of  experience  as  a  manager.  

This  axis  is  divided  in  intervals,  for  example,  3-­‐8  years,  9-­‐14  years,  etc.  For  each  interval  a  bar   simultaneously  shows  1)  the  total  amount  of  participants  within  this  interval  (full  length  of  bar),   2)  the  amount  who  did  not  experience  removal  of  judgments  (the  part  of  the  bar  placed  left  of  the   axis),  and  the  number  of  participants,  who  did  experience  removal  of  judgments  (the  part  of  the   bar  placed  right  of  the  axis).  For  categorical  variables,  such  as  industry  or  sector,  each  bar   represents  a  separate  category.    

If  these  population  pyramid  graphs  are  very  symetrical,  the  learning  outcome  is  evenly   distributed  along  the  factor  explored.  This  means  that  this  factor  is  unlikely  to  have  had  any  

Analysis   139   impact  on  the  learning  outcome.  By  contrast,  if  there  is  a  clear  asymetrical  pattern  in  a  graph,  the   factor  represented  on  the  y-­‐axis  of  this  graph  might  have  had  an  influence  on  the  learning  

outcome  explored  in  the  graph.  For  example,  in  the  graphs  exploring  possible  impact  of  sector  on   removal  of  judgment,  the  bar  representing  private  sector  are  much  further  to  the  left  than  the  bar   representing  public  sector.  This  might  mean  that  participants  from  the  private  sector  are  less   likely  to  let  go  of  judgments  about  self  or  others  than  participants  from  the  public  sector  (I   explore  this  further  below).  Similarly,  in  the  graph  exploring  possible  impact  of  length  of   experience  with  management  on  removal  of  judgment  of  self,  the  bars  representing  long  

experience  are  slightly  further  to  the  left  than  the  bars  representing  shorter  total  management   experience.  This  might  mean  that  participants  with  long  experience  in  management  are  less   likely  to  experience  removal  of  judgment  of  self,  than  participants  with  shorter  management   experience  (I  explore  this  further  below).    

When  exploring  the  various  factors  impact  on  the  effects  of  removal  of  judgments  on  self  and   others,  I  have  chosen  to  look  only  at  participants  in  G1  and  G2  where  this  effect  was  predominant.  

When  exploring  the  various  factors  impact  on  the  effects  of  import  of  behaviour,  I  have  chosen  to   look  only  at  participants  in  G3  and  G4  where  this  effect  was  predominant.  I  have  done  this  to  look   at  participants  who  at  least  are  comparable,  in  that  they  have  gone  through  the  same  learning   intervention.  If  I  looked  at  the  entire  sample,  I  would  mix  participants  who  have  gone  through   different  learning  interventions  on  top  of  having  different  demographic  characteristics.  Thus,   looking  at  the  entire  sample  in  the  population  pyramid  graphs  would  make  it  nearly  impossible   to  draw  any  conclusions  due  to  the  amount  of  factors  that  could  impact  the  shape  of  the  graphs.  

However,  this  also  means  that  each  graph  only  looks  at  twenty  participants,  which  is  a  rather   small  number.  Therefore,  the  graphs  cannot  be  taken  as  conclusive  evidence  of  the  impact  of  any   factor  on  the  frequency  of  specific  learning  outcome.  Rather,  the  graphs  can  only  indicate  that   there  could  be  a  ‘risk’  that  a  specific  factor  might  have  had  an  impact  on  a  specific  learning   outcome,  and  that  it  should  be  considered  whether  or  not  this  impact  (if  it  exists)  could  have   weakened  the  findings  of  the  analysis  above.  

I  will  now  look  first  at  the  factors,  which  are  less  likely  to  have  had  an  impact:  Years  of  experience   as  a  manager,  years  in  current  position,  number  of  employees,  and  the  time  it  took  the  

participants  to  formulate  their  problem  in  the  first  meeting.  I  then  look  at  the  factors  that  are   more  likely  to  have  had  an  impact:  industry,  sector,  and  gender.  However,  I  find  that  it  is  unlikely   that  any  of  these  factors  have  had  an  impact  that  weakens  the  findings  from  the  above  analysis.  

140   Analysis    

Years  of  experience  as  a  manager,  years  in  the  current  position,  number  of  employees,  and   the  time  it  took  the  participant  to  formulate  the  problem  in  the  first  meeting:  The  first  eight   graphs  explore  how  removal  of  judgments  on  self  and  others  were  impacted  by  years  of  

experience  as  a  manager,  years  in  the  current  position,  number  of  employees,  and  the  time  it  took   the  participant  to  formulate  the  problem  in  the  first  meeting.  None  of  these  graphs  show  very   clear  assymetrical  patterns  which  would  indicate  possible  influence.  However,  two  graphs  are   worth  mentioning.    

1. The  four  participants  who  have  worked  longest  with  management  (over  15  years)  did  not   experience  removal  of  judgments  of  self  (see  the  first  graph  below).  This  could  indicate  that   participants  with  long  management  experience  (for  whatever  reason)  are  less  likely  to  

experience  this  removal  of  judgments  of  self.  If  this  is  true,  then  the  predominance  of  removal   of  judgments  of  self  in  G1  and  G2  could  be  due  to  a  high  number  of  participants  with  shorter   management  careers  in  these  two  groups,  compared  to  the  participants  in  the  other  groups.  

However,  participants  in  G1  and  G2  had  the  highest  and  the  third  highest  avrage  years  of   experience  as  managers.  If  anything,  this  should  lower  the  amount  of  participants  

experiencing  removal  of  judgments  in  G1  and  G2  –  not  make  this  effect  predominant.    

2. All  the  participants  who  were  new  in  their  current  possition  experienced  removal  of   judgments  of  others.  It  seems  natural  that  the  phase  in  which  one  gets  to  know  new  

coworkers,  would  contain  an  element  of  discovering  that  at  least  some  of  them  are  not  as  bad   as  one  might  have  feared,  i.e.  removal  of  judgments  of  others.  As  in  the  above  case,  if  G1  and   G2  had  had  more  participants  who  were  new  in  their  current  position  than  the  other  groups,   this  might  have  explained  the  predominance  of  participants  experiencing  removal  of  

judgments  of  others  in  these  two  groups.  However,  G1  and  G2  are  among  the  groups  with  the   highest  average  years  in  current  position.  

In  conclusion,  years  of  experience  as  a  manager,  years  in  the  current  position,  number  of   employees,  and  the  time  it  took  the  participant  to  formulate  the  problem  in  the  first  meeting   cannot  explain  the  predominance  of  participants  experience  removal  of  judgments  of  self  or   others  in  G1  and  G2.  Therefore,  assuming  that  this  is  an  effect  of  the  AI  learning  intervention  used   in  these  two  groups  is  still  the  best  explanation.    

Analysis   141  

Table  4:  Removal  of  judgments  of  self  and  other  examined  

142   Analysis    

The  four  graphs  below  explore  how  import  of  behaviour  was  impacted  by  years  of  experience  as  a   manager,  years  in  the  current  position,  number  of  employees,  and  the  time  it  took  the  participant   to  formulate  the  problem  in  the  first  meeting.  None  of  these  graphs  show  clear  asymetrical  

patters.  Thus,  it  is  unlikely  that  these  factors  should  have  had  any  impact  on  whether  participants   experienced  import  of  behaviour  or  not.    

Table  5:  Import  of  behaviour  explored  

Analysis   143  

Industry:  Looking  at  the  graphs  for  industry,  I  choose  to  ignore  industries  with  only  one  

participant  or  industries  where  the  difference  between  the  number  of  participants  who  did  and   did  not  experience  the  particular  learning  outcome  is  one.  Such  asymmetries  are  simply  too  small   to  base  any  speculations  on.    

The  two  first  graphs  below  might  indicate  that  removal  of  judgments  of  self  or  of  others,  occur   more  frequently  for  participants  from  higher  education  or  from  ministries  and  administrations   and  do  not  occur  for  participants  working  as  consultants.    

Thus,  if  G1  and  G2  had  fewer  consultants  than  the  rest  of  the  groups,  this  might  explain  the   predominance  of  the  removal  of  judgments  in  these  groups.  However,  G1  and  G2  have  four  out  of   seven  consultants.  Similarly,  if  G1  and  G2  had  more  participants  from  higher  education  or  from   ministries  and  administrations  than  the  rest  of  the  groups,  this  could  also  explain  the  

predominance  of  removal  of  judgments.  However,  these  participants  are  distributed  evenly   across  groups  with  three  in  G1,  in  G5,  and  in  G6  and  four  in  G2,  in  G3,  and  in  G4.    

Thus,  the  graphs  do  not  provide  evidence  that  the  predominance  of  removal  of  judgments  in  G1   and  G2  could  be  explained  by  referring  to  the  industries  the  participants  in  these  groups  work  in.    

All  bars  in  the  third  graph  are  placed  as  symmetrically  as  possible  (i.e.  one  participant  difference   when  the  total  number  of  participants  represented  by  the  bar  is  uneven).  Thus,  this  graph  does   not  provide  evidence  that  industry  has  any  impact  on  whether  participants  experienced  import   of  behaviour.    

144   Analysis    

Table  6:  Possible  impact  of  industry  

Private,  public,  or  hybrid  sectors:  The  three  graphs  below  might  indicate  that  participants   from  public  sector  organisations  experienced  removal  of  judgments  of  self  and  others  more   frequently  than  participants  from  private  sector  organisations.  They  might  also  indicate  that   participants  from  private  sector  organisations  experienced  import  of  behaviour  more  frequently   than  participants  from  public  sectors.    

It  is  possible  to  imagine  that  a  more  competitive  environment  in  private  sector  organisations   would  make  individuals  more  defended  and,  thus,  less  likely  to  let  go  of  judgments.  Inversely,  the   competitive  environment  in  private  sector  organisations  might  make  individuals  more  likely  to  

Analysis   145   search  in  a  wider  range  of  contexts  for  solutions  to  problems,  and  thus  more  likely  to  experience   import  of  behaviour.  

If  G1  and  G2  have  more  participants  from  public  sector  organisations  than  the  other  groups,  this   could  explain  the  predominance  of  removal  of  judgments  of  self  and  others  in  these  groups.  G1   and  G2  have  11  participants  from  public  sector  organisations,  whereas  G3  and  G4  only  have  9   and  G5  and  G6  also  only  have  9.  However,  two  participants  more  from  public  sector  in  G1  and  G2   cannot  explain  that  these  groups  have  16  participants  experiencing  removal  of  judgments  of  self   or  others  –  against  5  in  G3  and  G4  and  only  1  in  G5  and  G6.    

If  G3  and  G4  have  more  participants  from  private  sector  organisations  than  other  groups,  this   could  explain  the  predominance  of  import  of  behaviour  in  these  groups.  However,  G3  and  G4  only   have  7  participants  from  private  sector  organisations,  against  9  in  both  G1  and  G2  and  in  G5  and   G6.    

In  conclusion,  the  predominance  of  the  learning  outcomes  found  in  the  above  analysis  could  not   be  explained  by  referring  to  the  sectors  the  participants  in  the  various  groups  work  in.  

Table  7:  Possible  impact  of  sector  

146   Analysis    

Gender:  G5  has  more  men  than  any  other  group  (7  out  of  10)  and  G3  consists  of  10  woman  and   no  men.  Therefore,  it  is  worth  checking  if  the  data  show  any  differences  between  men  and   woman  in  terms  of  removal  of  judgments  or  import  of  behaviour.  

In  the  graph  exploring  removal  of  judgments  of  others,  both  the  bar  representing  men  and  the   bar  representing  women  are  placed  as  symmetrically  as  possible  around  the  y-­‐axis.  The  slight   asymmetry  in  the  bar  representing  men  is  simply  due  to  an  uneven  total  number.      

The  other  two  graphs  might  indicate  that  women  are  more  likely  than  men  to  experience  removal   of  judgments  of  self,  whereas  men  are  more  likely  to  experience  import  of  behaviour  than  

women.    

If  G1  and  G2  had  more  women  than  the  other  groups,  this  could  explain  the  predominance  of   removal  of  judgments  of  self  in  G1  and  G2.  G1  and  G2  have  14  women.  This  is  more  than  G5  and   G6,  which  have  only  9  women,  but  it  is  less  than  G3  and  G4,  which  have  17  women.  Thus,  gender   does  not  seem  to  explain  the  predominance  of  participants  experiencing  removal  of  judgments  of   self  in  these  groups.  

If  G3  and  G4  had  more  men  than  the  other  groups,  this  could  explain  the  predominance  of  import   of  behaviour  in  these  groups.  However,  G3  and  G4  only  have  3  men  in  total,  whereas  G1  and  G2   have  6  and  G5  and  G6  have  13.    

Analysis   147   In  conclusion,  there  is  no  evidence  that  gender  can  provide  an  explanation  for  the  predominance   of  either  removal  of  judgment  of  self  or  others  in  G1  and  G2  or  for  the  predominance  of  import  of   behaviour  in  G3  and  G4.  

In  this  section,  I  have  systematically  explored  whether  removal  of  judgments  on  self  or  others  and   import  of  behaviour  could  be  explained  by  referring  to  factors,  such  as,  years  of  experience  as  a   manager,  years  in  the  current  position,  number  of  employees,  the  time  it  took  the  participants  to   formulate  their  problem  in  the  first  meeting,  which  industry  the  participants  work  in,  whether   the  participants  works  in  the  private,  the  public,  or  a  hybrid  sector,  and  participants’  gender.  

This  is  not  the  case.  This  strengthens  my  finding  that  removal  of  judgments  on  self  or  others  and  

import  of  behaviour  are,  in  fact,  effects  of  the  AI  and  the  MI  interventions  respectively.      

148   Analysis