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Statistical analysis of a one-semester general chemistry approach for students entering the pharmacy field

Taylor OwingsMarcy TownsPurdue University

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Goal

•The goal of this research was to evaluate the newly introduced CHM 109 on its effectiveness for preparing students for organic chemistry

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Introduction• Change in the MCAT encourages more

biochemistry for premedical and pre-pharmacy students▫AAMC mandated

• Recommendation for a 1-2-1 format, with inclusion of Biochemistry in place of a second semester of general chemistry

• CHM 109 implemented at Purdue to accommodate the one semester general chemistry requirement▫5 credit hours, 3 lectures a week

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Background on the CHM 109 course• 5 credit hour course

• Created to replace the 2 semester equivalent (CHM 115 and CHM 116)

• Designed to be part of new 1-2-1 chemistry series for students▫1 general chemistry course CHM 109▫2 organic courses (MCMP (Medicinal Chemistry

& Molecular Pharmacology) 204-205)▫1 biochemistry course

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Participants

•Students enrolled in MCMP 204/205 from fall 2002 - fall 2011▫Classified by year enrolled in MCMP 204▫Information collected on all chemistry

classes students had enrolled in

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Data collection

•Data collected included▫Demographic information▫SAT/ACT scores▫Grades in all Purdue chemistry courses

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Research question

•How do students enrolled in MCMP 204/205 perform in organic chemistry based on prior enrollment in CHM 109 and CHM 115-116?

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Statistical analysis

•Analysis to determine if comparisons can be made between student groups

•Analysis to determine if students course outcomes in MCMP 204/205 varied based on prior enrollment in CHM 115-116 or CHM 109

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Explaining differencesSignificant difference Practical difference

• Difference is determined by significance test▫ ANOVA, t-test, etc…

• Answers the question “are they different”

• Degrees of freedom included in equation

• Different tests that accompany significance tests▫ Cohen’s d, eta squared,

etc…• Looks at how different

values are▫ Small, medium, or large

• Answers the question “Does the difference matter”

• Degrees of freedom not included in equation

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Formulas

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SAT test scores

2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012400

450

500

550

600

650

700

SAT Scores by year

VerbalMath

Year in MCMP 204

SA

T S

core

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Preliminary standardized test scores

Mean F-statistic Effect size (η2)

SAT Verbal 576 6.79 .0338

SAT Math 623 10.8 .0524

ACT English 26.4 9.16 .0809

ACT Math 27.9 5.20 .0476

ACT English/Writing 26.0 7.41 .00010

Effect Size: Small ~ .01, Medium ~ .06, Large ~ .14

All listed standardized test scores were significantly different (p <.001)

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Demographics analysis of chemistry GPA

F-Statistic p-value Effect Size (η2)

Gender .852 .427 .00062

Ethnicity 5.46 <.001 .0125Effect size: Small ~ .01, Medium ~ .06, Large ~ .14Significant difference: p < .05

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Average course gradesCourse Mean Standard

deviationF-statistic Effect size (η2)

CHM 109 3.10 .806 16.6 .0342

CHM 115 3.26 .699 12.8 .0556

CHM 116 3.32 .757 19.7 .0768

CHM 109 data is from 2010-2011CHM 115/116 data is from 2002-2011

Effect size: Small ~ .01, Medium ~ .06, Large ~ .14All courses had a significant difference (p <.001)

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Student performance in MCMP 204

Mean Standard deviation

115 Students 2.78 1.11

116 Students 2.84 1.08

109 Students 2.76 1.03

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Student performance in MCMP 204

Effect size: Small = .1, Medium = .25, Large = .4Significant difference: p < .05

t-statistic p-value Effect size (Cohen’s d)

CHM 115 vs. CHM 109

.289 .772 .00001

CHM 116 vs. CHM 109

1.08 .278 .0745

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Student performance in MCMP 205

Mean Standard deviation

115 Students 2.83 1.02

116 Students 2.87 .999

109 Students 2.87 .978

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Student performance in MCMP 205

Effect size: Small = .1, Medium = .25, Large = .4Significant difference: p < .05

t-statistic p-value Effect size (Cohen’s d)

CHM 115 vs. CHM 109

-.372 .711 .0394

CHM 116 vs. CHM 109

.007 .994 .0018

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Conclusion

•Analysis demonstrates no significant or practical differences exist in performance in MCMP 204/205 based upon general chemistry preparation in CHM 109 and CHM 115/116.

•Thus, the new course sequence (one semester general chemistry) supports student success in Purdue’s pre-pharmacy curriculum.

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Implications

•Demonstrates efficacy of one semester gen chemistry course in pre-medical and pre-pharmacy curriculum

•Research finding provide research based support for curriculum augmentation

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Acknowledgements

•HHMI Nexus team at Purdue▫Dr. Marc Loudon▫Dr. Chris Hrycyna

•Research and assessment grant 2011•Towns research group

▫Dr. Marcy Towns

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Participant demographicsN

Male 1059

Female 1707

White Non-Hispanic 1680

Hispanic/ Latino 43

African American 87

Asian American/ Pacific Islander

289

Native American 5

Other 65

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Formulas

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CHM 109Mean Standard Deviation N

2010-2011 3.27 .7387 204

2011-2012 2.97 .8315 266

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CHM 109Mean Standard

DeviationN

Male 3.05 .7986 168

Female 3.12 .8096 302

Other demographics were unavailable for a significant portion of population

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CHM 109F-Statistic P-value Effect Size

(η2)

Gender .922 .337 .00197

Ethnicity N/A N/A N/A

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CHM 115Mean Standard Deviation N

2002-2003 2.99 .718 220

2003-2004 3.13 .716 234

2004-2005 3.17 .632 205

2005-2006 3.15 .696 185

2006-2007 3.28 .729 233

2007-2008 3.51 .623 264

2008-2009 3.36 .650 221

2009-2010 3.38 .665 188

2010-2011 3.80 .422 10

2011-2012 2.33 1.155 3

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CHM 115Mean Standard

DeviationN

Male 3.29 .668 665

Female 3.24 .717 1095

White Non-Hispanic

3.28 .686 1323

Hispanic/ Latino

3.30 .877 30

African American

2.89 .657 73

Asian American/ Pacific Islander

3.16 .735 208

Other 3.50 6.79 40

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CHM 115F-Statistic P-value Effect Size

(η2)

Gender 1.231 .267 .00080

Ethnicity 4.973 .000 .01681

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CHM 116Mean Standard Deviation N

2002-2003 3.04 .788 186

2003-2004 3.33 .746 216

2004-2005 3.08 .806 190

2005-2006 3.15 .762 183

2006-2007 3.25 .763 235

2007-2008 3.44 .739 256

2008-2009 3.56 .604 207

2009-2010 3.68 .556 195

2010-2011 3.4 .894 5

2011-2012 1.5 2.121 2

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CHM 116Mean Standard

DeviationN

Male 3.35 .735 646

Female 3.31 .770 1027

White Non-Hispanic

3.34 .744 1257

Hispanic/ Latino

3.17 .966 29

African American

2.92 .802 61

Asian American/ Pacific Islander

3.28 .774 204

Other 3.53 .726 45

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CHM 116F-Statistic P-value Effect Size

(η2)

Gender 1.036 .309 .00065

Ethnicity 5.734 .000 .01421

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MCMP 204Mean Standard Deviation N

2002-2003 2.33 1.320 222

2003-2004 2.73 1.048 230

2004-2005 2.85 1.152 259

2005-2006 2.75 1.175 238

2006-2007 2.76 1.183 208

2007-2008 3.03 1.013 266

2008-2009 2.69 1.263 270

2009-2010 2.99 .983 238

2010-2011 2.75 1.011 417

2011-2012 2.00 0 2

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MCMP 204Mean Standard

DeviationN

Male 2.80 1.16 896

Female 2.75 1.12 1449

White Non-Hispanic

2.80 1.13 1596

Hispanic/ Latino

2.71 1.20 37

African American

2.43 1.09 81

Asian American/ Pacific Islander

2.63 1.21 280

Other 3.05 1.18 61

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MCMP 204F-Statistic P-value Effect Size

(η2)

Gender 1.749 .186 .00085

Ethnicity 4.141 .002 .0080

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MCMP 205Mean Standard Deviation N

2002-2003 2.65 .894 169

2003-2004 2.79 .983 184

2004-2005 2.76 .978 195

2005-2006 2.75 1.031 175

2006-2007 2.91 .9713 148

2007-2008 3.03 1.043 216

2008-2009 3.07 .897 185

2009-2010 2.69 1.134 188

2010-2011 2.91 1.117 169

2011-2012 2.86 .989 174

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MCMP 205Mean Standard

DeviationN

Male 2.87 1.012 700

Female 2.82 1.018 1098

White Non-Hispanic

2.87 .998 1213

Hispanic/ Latino

2.71 .937 28

African American

2.33 1.203 60

Asian American/ Pacific Islander

2.77 1.048 212

Other 3.14 .833 50

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MCMP 205F-Statistic P-value Effect Size

(η2)

Gender .796 .372 .00059

Ethnicity 5.478 .000 .01387