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Using an Online Interactive Textbook to Improve Student Outcomes

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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.

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Using an Online Interactive Textbook to Improve Student Outcomes

  1. 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. 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. 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. 4 Organic Chemistry Interactive Textbook Top Hat platform LMS
  5. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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. 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

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