Steven Forsey, University of Waterloo: Online textbooks provide an incentive through participation grades to motivate students to read the textbook before coming to class—leading to better grades.

1. Using an Online Interactive Textbook to Improve
Student Outcomes in an Introductory Organic
Chemistry Course
Presented by: Dr. Steven Forsey
Statistics: Travis Bender
07/31/2019

2. LMS
2
https://www.mosaicolearning.com/blog/active-learning-improves-educational-results
Active Learning
Metaanalyzed 225 studies and showed that “average
examination scores improved by about 6% in active learning
sections and that students in classes with tradition lecturing
were 1.5 times more likely to fail the course than were
students in classes with active learning.”
Active Learning and Cooperative Learning in the Organic
Chemistry Lecture Class (Donald R. Paulson, 1999)
Active learning increases student performance in science,
engineering, and mathematics (Freeman et al,. 2014)
“The use of active learning strategies and cooperative
learning groups in my organic chemistry lecture classes
has increased the overall pass rate in my classes by an
astounding 20-30% over the traditional lecture mode”

3. LMS
Year Assignments
Course
Notes
In-class
Participation
Extra
online
Text Book
Hard Cover
Exam
average
Number of
students
2013 Sapling Yes Top Hat
780 Practice Q
4 chapters
Yes 59 719
2012 Sapling Yes Top Hat
780 Practice Q
Learning Modules
Yes 57 708
2011 WebAssign Yes Top Hat Demo Animations Yes 57 702
2010 LMS Yes Top Hat Demo Animations Yes 56 645
2009 LMS Yes iClicker Yes 54 626
2008 LMS Yes iClicker Yes 62 681
2007 LMS Yes iClicker Yes 54 592
2005 LMS Yes Yes 56 473
2004
LMS &
Written
Yes Yes 54 684
Student Recourses used in Chem 266
LMS: Learning Management System

4. 4
Organic Chemistry
Interactive
Textbook
Top Hat platform
LMS

5. 5
Reading before the class
Sink or Skim: Textbook Reading Behaviors of
Introductory Accounting Students (Phillips, 2007)
LMS
“Academically strong students appear to read with the primary
goal of understanding assigned material, as evidenced by their
willingness to (1) engage in reading before the related material is
covered in class, (2) persist when material becomes difficult, and
(3) establish defined action plans that promptly resolve confusion.
In contrast, weaker students appear to read with the primary goal
of reducing anxiety, by deferring reading and terminating it when
comprehension becomes difficult.”
Understanding Student Perceptions and Practices for Pre-Lecture
Content Reading in the Genetics Classroom (Gammerdinger, 2018)
“Our results indicate that pre-lecture reading, major, and grade-point average are all significant indicators of
exam average. Once again, the importance of pre-lecture reading cannot be overstated. Not only does it
prepare a student for the lecture they are about to receive, but the fruits of this work are also demonstrated in
improved exam scores. “

6. 6
Year Assign.
In-class
Participation
Extra
online
Comprehensive
course notes
Online
Textbook
Reading
before
lecture
Reading
after
lecture
Final
exam
average
Number
of
students
2018 X X X X 66 676
2017 X X X X 62 654
2016 X X X X X 59 720
2015 X X X X X 60 674
2014 X X X X X 63 740
2013 X X X 59 719
2012 X X X 57 708
2011 X X X 57 702
2010 X X X 56 645
2009 X X 54 626
2008 X X 62 681
2007 X X 54 592
2005 X 56 473
2004 X 54 684
Student Recourses used in Chem 266

7. 7
0
5
10
15
20
25
30
0-29 30-39 40-49 50-59 60-69 70-79 80-89 90-100
2004 2005 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018
Chem 266 Final Exam Grade Distribution
Frequency(%)
Final Exam Grade (%)
Reading before lecture

8. 8
Density
Final Exam Grade (%)
2004
2005
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
Year
2018
2017
2004
Reading before
lecture
2014
Year/Interval 45-55% 75-100%
2004 21% 23%
2009 26% 19%
2013 15% 35%
2018 12% 42%
Chem 266 Final Exam Grade Distribution

9. 9
Chem 266 Final Exam Grade Distribution by availability
of Online Textbook and Comprehensive Course Notes
Density
Final Exam Grade (%)
Resources
2004 – 2013
Not available
2014 – 2018
Available

10. 10
Chem266FinalExamGrade(%)
Chem 123 Grade (%)
Effect of First Year Chem 123 Grades
Chem 123 Final Grade vs Chem 266 Final Exam Grades Chem 266 Final Exam Grade
Distribution by Chem 123 students who
took Chem 123 or where exempted
Chem 123 exempted
Chem 123 taken
Density
Final Exam Grade (%)

11. 11
Is there a relationship between the final exam grades
and the resources provided?
Textbook: 75-100% of the pre-readings
Textbook some of the pre-readings
No online textbook
Textbook: 75-100% of the post readings
Textbook some of the post readings
No online textbook
Textbook and comprehensive course notes
introduced at the same time, therefore are colinear.
Year Assign.
In-class
Participation
Extra
online
Comprehensive
course notes
Online
Textbook
Reading
before
lecture
Reading
after
lecture
Final
exam
average
Chem
123
Grades
2018 X X X X 66 X
2017 X X X X 62 X
2016 X X X X X 59 X
2015 X X X X X 60 X
2014 X X X X X 63 X
2013 X X X 59 X
2012 X X X 57 X
2011 X X X 57 X
2010 X X X 56 X
2009 X X 54 X
2008 X X 62 X
2007 X X 54 X
2005 X 56 X
2004 X 54 X
𝑦 = 𝑏 + 𝑏1 𝑥1 + 𝑏2 𝑥2 + ⋯ 𝑏 𝑝 𝑥 𝑝
Assumes all independent variables
to be correlated with the dependent
variable but not with each other.
𝑦 = Predicted value of the dependent variable
Multiple Linear Regression

12. 12
Multiple Linear Regression with Pre and Post Reading
PreRead: Students completed 75-100% of the pre-readings
ParPreRead: Student completed 0 to 74% of the pre-readings
NoPreRead: No online textbook – but had comprehensive course notes
PostRead: Students completed 75-100% of the pre-readings
ParPostRead: Student completed 0 to 74% of the pre-readings
NoPostRead: No online textbook – but had comprehensive course notes
𝑦 = 𝑏 + 𝑏1 𝑥1 + 𝑏2 𝑥2 + ⋯ 𝑏 𝑝 𝑥 𝑝 𝑦 = Predicted value of the dependent variable
Predicted Grade = b + b1(Chem 123grade) + b2(NoChem123) + b3(PreRead)
+ b4(ParPreRead) + b5(NoPreRead) + b6(Postread) + b7(ParPostRead)
+ b8(NoPostRead)
Base group not shown in equation: no online text and no comprehensive course notes (2004-2013)
Student Participation

13. 13
Multiple Linear Regression Pre and Post Reading
Residual standard error: 14.86 on 9156 degrees of freedom Multiple R-squared: 0.3736, Adjusted R-squared: 0.3731
F-statistic: 682.6 on 8 and 9156 DF, p-value: < 2.2e-16
Predicted Grade = -2.9 + 0.85(Chem 123 grade) + 62.5(NoChem123) + 5.2(PreRead) - 2.3(ParPreRead)
- 3.4(NoPreRead) + 2.5(Postread) - 0.25(ParPostRead) - 2.4(NoPostRead)
Estimate Std. Error t value Pr(>|t|)
Intercept) -2.94034 0.89470 -3.286 0.001019
Chem123 0.84800 0.01239 68.429 < 2e-16
NoChem123 62.51576 1.13911 54.881 < 2e-16
PreRead 5.25260 0.43977 11.944 < 2e-16
ParPreRead -2.31861 0.95297 -2.433 0.014991
NoPreRead -3.40035 0.83804 -4.058 5e-05
PostRead 2.46513 0.65213 3.780 0.000158
ParPostRead -0.25249 0.73667 -0.343 0.731797
NoPostRead -2.43603 0.79499 -3.064 0.002189
Base group not shown in equation: no online text and no comprehensive course notes (2004-2013)

14. 14
Post reading
Prereading
No online text/comp notes
2004-2013
No post reading
No prereading
Partial post reading
Partial prereading
Chem 266 Final Exam Grade Distribution
by Class Resources Used
Density
Final Exam Grade (%)
Resources

15. 15
Maybe the exams got easier?
Density
Final Exam Grade (%)
2012
2017 - Comp. Notes/textbook/PreRead
2014 - Comp. Notes/textbook/PreRead
2018 - Comp. Notes/textbook/PreRead
Density
Final Exam Grade (%)
95% of 2017 questions almost the same as 2012 70% of 2018 questions almost the same 2014

16. 16
Chem 266 Final Exam Grade Distribution by Chem 123 Grade
From 2004-2018
Density
Final Exam Grade (%)
Chem 123 Grade
<= 75
> 75

17. 17
Did strong and weak students benefit by
using the resources?
Density
Final Exam Grade (%)
Density
Final Exam Grade (%)
Final exam grade distribution
Chem 123 Grade > 75%
Final exam grade distribution
Chem 123 Grade <= 75%
Post reading
Prereading
No online text/comp notes
2004-2013
No post reading
No prereading
Partial post reading
Partial prereading

18. 18
Did strong and weak students benefit
by prereading in 2018?
Prereading
No prereading
No online textbook
Partial prereading
Final Exam Grade (%) Final Exam Grade (%)
2018 Final exam grade distribution
Chem 123 Grade > 75%
2018 Final exam grade distribution
Chem 123 Grade <= 75%
Density
Density

19. 19
Did strong and weak students benefit
by post reading in 2016?
Post reading
No post reading
No online textbook
Partial post reading
Final Exam Grade (%)
Final Exam Grade (%)
2016 Final exam grade distribution
Chem 123 Grade > 75%
2016 Final exam grade distribution
Chem 123 Grade <= 75%
Density
Density

20. 20
Summary
• There evidence in this study that the online textbook provides an incentive through participation grades
to motivate students to read the textbook and leads to better grades
• There is a correlation between final exam grades with online textbook/course notes, reading before the
lectures, reading after the lectures and Chem 123 grade
• Having the online textbook, comprehensive course notes and reading before or soon after the lectures
seems to contribute to improved final exam grades over students who did not have these resources.
• Reading before the lectures has a greater influence on the final exam grades than reading the lecture
content soon after the lectures.
• Academically strong students (CHEM 123 > 75%) seemed to benefit more from reading before the
lectures, than students who did partial or no reading.
• Academically strong students (CHEM 123 > 75%) seemed to benefit more from reading after the
lectures than students who did partial or no reading but the increase in final exam grade was not as
large as reading before the lectures.

21. 21
Reference list:
Freeman, S. et al., (2014) Active learning increases student performance in science, engineering, and mathematics, PNAS, 111(23):
8410-8415
Gammerdinger, W. J. and Kocher, T. D. (2018) Understanding Student Perceptions and Practices for Pre-Lecture Content Reading in
the Genetics Classroom, J. Microbiol Biol Educ. 19(2): 1-6
Paulson, Donald R., (1999) Active Learning and Cooperative Learning in the Organic Chemistry Lecture Class, J. Chem. Ed., 76(8):
1136-1140.
Philips, B. J. and Phillips, F. (2007) Sink or Skim: Textbook Reading Behaviors of Introductory Accounting Students. ISSUES IN
Accounting Education 22(1): 21-44