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Longitudinal Analysis of NOSM’s CCC Effectiveness (LANCE) 
•Jeff Bachiu, UME Manager, Curriculum & Planning, NOSM 
•Rachel Ellaway, UME Assistant Dean, Curriculum & Planning, NOSM 
•John Friesen, Director Learner Affairs & UME Administration, NOSM 
•John Dabous, Curriculum Instructional Designer, NOSM
DisclosureSlide 
Presenter: Jeff Bachiu 
Relationships with commercial interests: None 
We work for NOSM and are invested in the success of the CCC program.
CCC sites 
• Fifteen Medium-sized 
population centres 
(pop. 5000 – 75,000) 
outside main 
campuses 
• Family physician 
offices plus hospital 
with basic services 
• But all sites are 
different in: 
Size 
Facilities 
Culture 
Communities 
• Sites: 
• Kenora 
• Dryden 
• Sioux Lookout 
• Fort Frances 
• Sault Ste. Marie 
• Hearst 
• Kapuskasing 
• Timmins 
• Timiskaming Shores 
• Manitoulin 
• North Bay 
• Bracebridge 
• Huntsville 
• Parry Sound 
• Midland
Question 
•Accreditation requires comparability of sites—no negative effect on learning from any site (ED-8) 
•How to ensure that all CCC sites provide a comparable learning experience? 
•Accreditation answer: through common curriculum and assessments 
•But are we sure a community doesn’t effect learning?
Balancing Act 
Comparable learning experience vs. uniqueness of communities
Methods 
Longitudinal review of assessment performance 
Scored (not pass/fail) assessment data (by Theme) for: 
•Phase 2 exams, 
•Phase 3 rotation exams and 
•LMCC scores 
E2007-E2010 in this analysis (CCC in 2009- 2012) 
All scores post remediation (if required) 
To see if patterns might develop over time
Students per site 
0 
1 
2 
3 
4 
5 
6 
7 
8 
9 
10 
E2007 
E2008 
E2009 
E2010 
Different numbers of students per CCC site 
number of students 
cohort
Analysis 
Indices of community student exam performance 
For each exam event: 
MS= (mean score per site) –(mean score all sites) 
SH= count # MS>1 
SL= count # MS<-1 
Site score = Σ(SH-SL)
All sites -Phase 2 (n=12) 
-6 
-4 
-2 
0 
2 
4 
6 
E2007 
E2008 
E2009 
E2010 
site score 
cohort
All sites -Phase 2, 3, LMCC (n=12) 
-15 
-10 
-5 
0 
5 
10 
15 
E2007 
E2008 
E2009 
E2010 
site score 
cohort
Large sites –Phase 2 (n=4) 
-6 
-4 
-2 
0 
2 
4 
6 
E2007 
E2008 
E2009 
E2010 
site score 
cohort
Small sites –Phase 2 (n=4) 
-6 
-4 
-2 
0 
2 
4 
6 
E2007 
E2008 
E2009 
E2010 
site score 
cohort
East sites –Phase 2 (n=8) 
-6 
-4 
-2 
0 
2 
4 
6 
E2007 
E2008 
E2009 
E2010 
site score 
cohort
West sites –Phase 2 (n=4) 
-6 
-4 
-2 
0 
2 
4 
6 
E2007 
E2008 
E2009 
E2010 
site score 
cohort
Discussion 
•Site performance goes up 
•Site performance goes down 
•No stability over more than 3 years 
•Variation in performance between sites more attributable to student differences? 
•One site consistently below par in Phase 2 and falling in overall – need for follow up
Conclusions 
•No major discrepancies 
•One site requiring further investigation 
•The data are indicators of possible problems –may be attributable to many causes including random variations 
•Ongoing monitoring –longitudinal tracking improves over time 
•Tracking and follow-up part of accreditation 
•And of accountability –to students, communities, and Northern Ontario
Questions and Feedback 
•Jeff Bachiu jbachiu@nosm.ca

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117 muster2014 Bachiu

  • 1. Longitudinal Analysis of NOSM’s CCC Effectiveness (LANCE) •Jeff Bachiu, UME Manager, Curriculum & Planning, NOSM •Rachel Ellaway, UME Assistant Dean, Curriculum & Planning, NOSM •John Friesen, Director Learner Affairs & UME Administration, NOSM •John Dabous, Curriculum Instructional Designer, NOSM
  • 2. DisclosureSlide Presenter: Jeff Bachiu Relationships with commercial interests: None We work for NOSM and are invested in the success of the CCC program.
  • 3.
  • 4. CCC sites • Fifteen Medium-sized population centres (pop. 5000 – 75,000) outside main campuses • Family physician offices plus hospital with basic services • But all sites are different in: Size Facilities Culture Communities • Sites: • Kenora • Dryden • Sioux Lookout • Fort Frances • Sault Ste. Marie • Hearst • Kapuskasing • Timmins • Timiskaming Shores • Manitoulin • North Bay • Bracebridge • Huntsville • Parry Sound • Midland
  • 5. Question •Accreditation requires comparability of sites—no negative effect on learning from any site (ED-8) •How to ensure that all CCC sites provide a comparable learning experience? •Accreditation answer: through common curriculum and assessments •But are we sure a community doesn’t effect learning?
  • 6. Balancing Act Comparable learning experience vs. uniqueness of communities
  • 7. Methods Longitudinal review of assessment performance Scored (not pass/fail) assessment data (by Theme) for: •Phase 2 exams, •Phase 3 rotation exams and •LMCC scores E2007-E2010 in this analysis (CCC in 2009- 2012) All scores post remediation (if required) To see if patterns might develop over time
  • 8. Students per site 0 1 2 3 4 5 6 7 8 9 10 E2007 E2008 E2009 E2010 Different numbers of students per CCC site number of students cohort
  • 9. Analysis Indices of community student exam performance For each exam event: MS= (mean score per site) –(mean score all sites) SH= count # MS>1 SL= count # MS<-1 Site score = Σ(SH-SL)
  • 10. All sites -Phase 2 (n=12) -6 -4 -2 0 2 4 6 E2007 E2008 E2009 E2010 site score cohort
  • 11. All sites -Phase 2, 3, LMCC (n=12) -15 -10 -5 0 5 10 15 E2007 E2008 E2009 E2010 site score cohort
  • 12. Large sites –Phase 2 (n=4) -6 -4 -2 0 2 4 6 E2007 E2008 E2009 E2010 site score cohort
  • 13. Small sites –Phase 2 (n=4) -6 -4 -2 0 2 4 6 E2007 E2008 E2009 E2010 site score cohort
  • 14. East sites –Phase 2 (n=8) -6 -4 -2 0 2 4 6 E2007 E2008 E2009 E2010 site score cohort
  • 15. West sites –Phase 2 (n=4) -6 -4 -2 0 2 4 6 E2007 E2008 E2009 E2010 site score cohort
  • 16. Discussion •Site performance goes up •Site performance goes down •No stability over more than 3 years •Variation in performance between sites more attributable to student differences? •One site consistently below par in Phase 2 and falling in overall – need for follow up
  • 17. Conclusions •No major discrepancies •One site requiring further investigation •The data are indicators of possible problems –may be attributable to many causes including random variations •Ongoing monitoring –longitudinal tracking improves over time •Tracking and follow-up part of accreditation •And of accountability –to students, communities, and Northern Ontario
  • 18. Questions and Feedback •Jeff Bachiu jbachiu@nosm.ca