THE EFFECTS OF COMPUTER ASSISTED INSTRUCTION ON COLLEGE ALGEBRA STUDENTS AT TEXAS TECH UNIVERSITY AMANDA M. KLEIN, B.S. A THESIS MATHEMATICS

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1 THE EFFECTS OF COMPUTER ASSISTED INSTRUCTION ON COLLEGE ALGEBRA STUDENTS AT TEXAS TECH UNIVERSITY by AMANDA M. KLEIN, B.S. A THESIS IN MATHEMATICS Submitted to the Graduate Faculty of Texas Tech University in Partial Fulfillment of the Requirements for the Degree of MASTER OF SCIENCE Approved Jerry Dwyer Chairperson of the Committee George Williams Christopher Monico Accepted John Borrelli Dean of the Graduate School August, 2005

2 2005 Amanda M Klein, B.S.

3 ACKNOWLEDGEMENTS I would like to thank Dr. JoAnne Temple for helping me start this study. I would like to express my deepest gratitude to Dr. Jerry Dwyer for stepping up at the last minute and helping me put everything together, also Dr. Brock Williams and Dr. Chris Monico for their guidance and support. I would like to convey my gratitude to Rachel Backlund, Julia Head, and Kathy Waller for their advice and editing abilities. Finally, I would like to thank Mom, Dad, Pam, and Dustin. Without your constant encouragement and patience this would not have been possible. ii

4 TABLE OF CONTENTS ACKNOWLEDGEMENTS. ii ABSTRACT. v LIST OF TABLES vi LIST OF FIGURES.. vii CHAPTERS I. INTRODUCTION Purpose of Study Research Questions Definitions Need for Study... 2 II. REVIEW OF THE LITERATURE Introduction Background Information on Computer Assisted Learning. 4 III. METHODOLOGY Introduction Research Design Data Collection and Analysis...12 IV. PRE-TEST/POST-TEST ANALYSIS Introduction.. 14 Results.. 14 iii

5 V. PRE-SURUUPPVEY/POST-SURVEY ANALYSIS Introduction Results VI. QUALITATIVE DATA ANALYSIS Introduction.. 28 Results.. 28 VII. CONCLUSIONS Introduction Limitations of Study Conclusions.. 34 Thoughts for Future Research.. 35 BIBLIOGRAPHY.. 36 APPENDICES A. PRE-TEST AND POST-TEST B. BELIEFS ABOUT MATHEMATICS SURVEY. 43 C. QUALITATIVE SURVEY, STUDENT EVALUATION OF COURSE AND INSTRUCTOR, AND COMMENTS D. ADDITIONAL TABLES.. 56 iv

6 ABSTRACT A semester long study was conducted on the effects of the use of MyMathLab, an online computer assisted instruction (CAI) software program, on college algebra students. One section of College Algebra had access to the online CAI supplemental to traditional classroom instruction. The other section received only traditional classroom instruction. The students took a pre-test and post-test, filled out a pre-survey and post-survey, and completed a course evaluation and qualitative survey at the end of the semester. The change in test scores was not statistically different between the two sections. MyMathLab did not influence the students overall attitude toward math, but it did have a negative effect on the students beliefs concerning the time commitments involved in solving math problems. The students thought that entering the answer was too time consuming and frustrating. v

7 LIST OF TABLES 1. Group Statistics for Pre-, Post-, and Change in Test Scores Independent Samples Test on Pre-, Post-, and Change in Test Scores Group Statistics on Change in Test Questions Independent Samples Test on Change in Test Questions Independent Samples Test on Change in Test Questions Group Statistics for Pre-Survey Scores Independent Samples Test on Pre-Survey Scores Group Statistics for Pre-Survey Scores Independent Samples Test on Post-Survey Scores Correlation between the Use of and the Change in Test Score Group Statistics on Course Evaluation Ratings Independent Samples Test on Course Evaluation Ratings Group Statistics on Individual Pre-test Questions Independent Samples Test on Individual Pre-test Questions Independent Samples Test on Individual Pre-test Questions Group Statistics on Individual Post-test Questions Independent Samples Test on Individual Post-test Questions Independent Samples Test on Individual Post-test Questions vi

8 LIST OF FIGURES 1. Histogram of Pre-Test Scores Histogram of Pre-Test Scores Histogram of Post-Test Scores Histogram of Post-Test Scores Most common mistake on question Most common mistake on question 9 22 vii

9 CHAPTER I INTRODUCTION Purpose of Study The purpose of this study is to determine if the use of computer assisted instruction software affects the attitude towards mathematics and grade improvement of students enrolled in college algebra at Texas Tech University. Research Questions 1. How does the use of computer assisted instruction software affect the knowledge gained for a university student enrolled in college algebra? 2. How are the students attitudes towards mathematics affected by the use of MyMathLab, a computer assisted instruction software program? Definitions 1. Quantitative Research Research that focuses on controlling a small number of variables to determine cause-effect relationships and/or the strength of those relationships. (Mills, 2003) 2. Qualitative Research Research that uses narrative, descriptive approaches to data collection to understand the way things are and what it means from the perspectives of the research participants. (Mills, 2003) 1

10 3. Technology Depending on the source, this term can refer to anything from a calculator to high end computer processors. For the purpose of this study, technology refers to computers and online-based instruction. 4. Computer Assisted Instruction Software any form of instruction or tutorial that is performed mainly through a computer program. 5. Computer Assisted Learning See Computer Assisted Instruction. 6. Classroom Instruction Math instruction which involves only lecture and homework/practice problems worked from a textbook and turned in for a grade on a regular basis. 7. College Algebra This class covers inequalities, determinates, theory of equations, binomial theorem, and progressions. Typically the students enrolled in this course are art and science majors fulfilling three of the six required mathematics hours. (Texas Tech University, 2005) 8. College Level Courses for which students may enroll at a college or university to receive credit toward graduation. Need for the Study With the ever advancing technology and the constant need to improve teaching practices, a course that could successfully put the two together efficiently would be very advantageous to today s college students. There are numerous programs like MyMathLab available, but the helpfulness of these programs on the average college student has yet to be determined. Most studies in the past involve either younger students or students that have problems from the start. None have been relevant to a general 2

11 student population. Since each software package is as different as the textbooks that they are designed to supplement, it would be beneficial to the Texas Tech University Mathematics Department to determine if the package that accompanies their chosen college algebra text is worthwhile. 3

12 CHAPTER II REVIEW OF THE LITERATURE Introduction This analysis is to determine if there is a practical advantage to using computer assisted instruction software programs with students enrolled in college algebra at Texas Tech University. The intention is to give the students every feasible advantage to help them learn and enjoy college algebra. Background Information on Computer Assisted Learning There have been many studies conducted on the use of technology in the classroom. They have included qualitative data, quantitative data, and a combination of the two. Most of the qualitative research measures the teachers and administrators attitudes towards and/or reasons for the use of technological components in their math classrooms. The quantitative research focuses mainly on elementary students and the effects the use of technology have on their standardized test scores. A few studies have involved high school students and students enrolled in developmental classes in a community college setting, but there is little information on the effects that these programs have on the average student enrolled in college level courses. Technology is becoming an ever present entity in the lives of students today. As the students of today become the workforce of tomorrow, they will need a variety of skills including problem solving skills that come from the integration of mathematics and technology. For their college education to be successful, they must become comfortable 4

13 with the use of technology (Middleton, 1999). Most students today are more proficient with computers than their parents, but the computer is very seldom used in conjunction with their mathematics lessons (Dickey, 1998). The Principles and Standards for School Mathematics (2000) states technology is essential in teaching and learning mathematics; it influences the mathematics that is taught and enhances students learning. It has been shown that the use of calculators and computers enable students to spend less time on calculations and more time learning the mathematics. Many teachers believe this helps improve student attitudes toward mathematics. (Kersaint, 2003) Gadanidis, et. al. showed students learn best when they have the opportunity to have an active part in their own education and assemble their own personal understanding. Technology in the classroom helps students visualize what is occurring. Because of this improved visualization, students have a deeper understanding of what is happening when they work through a math problem (Thomas, 1996). As with any new idea, there are bumps in the road. The amount of technology that is currently used in the classroom is the main difficulty. The reason most teachers cite as why they do not utilize technology in their classroom is their own lack of training and comfort level (Kersaint, 2003). Kersaint also states teachers often do not feel comfortable engaging students in open-ended uses of technology tools until they are comfortable with exploring mathematics with technology themselves. At first, most instructors are more concerned with the impact the technology will have on them and their teaching and then their apprehension turns to managing the implementation of the technology in their classroom (James, 2000). Conte and Weber reported in 1999 that administration support is the key factor in the success of implementing technology in 5

14 today s classrooms. Teachers need resources and training to be able to effectively use computers to help their students understand mathematics. Therefore, it is vital to provide in-service and professional development opportunities for the teachers, if they are to be expected to implement newer technologies (Middleton, 1999). Studies of how CAI programs compare to other methods of teaching have been conducted since the late nineteen eighties. Though most have involved elementary school students, they help to lay the ground work for this study. In 1987, Beyer, et al. started a three-year study involving second through fifth grade children in three different elementary schools with diverse student make-ups. The project funded the establishment of a computer lab in each school for the use of mathematics and reading tutorial software. The first year of the study showed that two second grade and one forth grade math classes had significant differences in the improvement of the students using the software over those in the control group at the 0.01 level. The second and third years of the study showed that all four grades at all three schools had significant improvement over those in the control classes at the 0.01 level. Another study involving elementary and middle school students in an urban North Carolina public school showed that when students spent at least ten hours throughout the school year using the CAI software only black females in sixth grade had significant differences in progress at the 0.05 level (Brown, 2000). During the school year, an analysis of second through fifth grade students in West Virginia was conducted. The experimental groups spent 4 hours a week in traditional classroom instruction and one hour a week using the CAI software whereas the control group spent the extra hour reviewing and practicing. The students were given a pre- and post-test covering all of the lessons as well as a pre- and post-test 6

15 corresponding to each of the seven lessons. The researchers demonstrated that when the students spent at least an average of 38 minutes a week during the six week long study there was not a significant difference (0.05 level) between the control and experimental groups in any of the pre-/post-test sets. The researchers noted that the computer system did not coordinate well with the text book and it appeared that the presentation was more for the ease of the computer programmers and not for the benefit of the students. (Edgwell, 1998) Students in high school have also been the subjects in CAI analysis. Students in Terry High School in Rosenberg, Texas took part in a study on the effectiveness of a preexisting tutorial program. A group of students who were identified by their teachers as deficient in math were offered an opportunity to receive extra credit by participating in this study. The students had one or two sessions with the software each week. On average the participants improved 2 grade levels. Correlation coefficients were calculated between the students class grade improvement and each of the following; with time spent on the computer, the correlation was low moderate (0.472 at p<0.01); with number of sessions on the computer, the correlation was low (0.376 at p<0.01); and with number of modules mastered, the correlation was high (0.72 at p<0.05). When compared to the number of students passing the math portion of Texas Assessment of Academic Skills before the tutorial program was introduced, 24.9% more students passed during the year of the study. (Brush, 2002) At North Carolina Central University, all students that enroll in College Algebra take a pre-test. If they score below a 70% they are assigned to a self-paced improvement program (SIP) and are given computer based tutorials and assignments to complete. 7

16 Those who attended were the students who completed at least half of what they were assigned. The other students are referred to as those who did not attend. Considering the students that were assigned to the SIP at the beginning of the semester, 59% of those who attended and 25% of those who did not attend passed their class. At mid-semester, students who received a D or F were then assigned to the SIP. Of the students that started the SIP after mid-semester grades, 89.5% of those who attended and 36% of those who did not attend passed their class. (Abraham, 1997) Ford and Klicka performed two separate studies on the use of CAI programs in Bucks County Community College in Newtown, PA. The first in 1994 was a semester long study of the effects of using a CAI supplemental to classroom instruction in Basic and Intermediate Algebra. The students had to have at least an 80% mastery of one module before moving on to the next. If after 3 attempts they do not have 80% mastery, the program locks them out and they have to meet with the instructor for tutoring before they can be reinstated. In Basic Algebra, there was a significant difference (p<0.05) between the experimental and control groups. In the case of the Intermediate Algebra, there was not a significant difference between the two groups; in fact the mean for the control group was slightly higher than the mean for the experimental group. The researchers remarked that the pre-test scores in the Intermediate Algebra were not homogeneous and that there were fewer modules for Intermediate than for Basic Algebra. They also noted that the students had different professors with different midterm tests and grading policies and, therefore, different withdrawal rates. The second study in 1998 was a four-semester analysis of the difference in the achievement of students enrolled in Basic Algebra and Fundamentals of Mathematics between traditional instruction, CAI without a 8

17 lecture component, and CAI with a lecture component. The participants in the CAI classes did not take tests until they had an 85% mastery of the material. If they did not complete enough chapters to receive credit for the class, they could enroll in the class the next semester and start where they left off. Of the students in Fundamentals of Mathematics, there was not a significant difference in the percentage of students who passed their class, passed the final exam, or that passed their next math class between the traditional group and the two CAI groups. Of the students in Basic Algebra, there was a significant difference between the traditional and the two CAI sections in the percentage of students who passed the final with the CAI sections both being higher. There was a significant difference between the traditional and the two CAI sections in the percentages of students who passed the class, but the traditional group had the highest percentage of students passing. There was not a significant difference between the traditional group and the CAI/non-lecture with respect to the percentages of students who passed their next math class. The number of students from the CAI/lecture sections who passed their next class was not available. Technological advances have been in the spotlight for educational research for over 25 years. Qualitative research has shown us that without sufficient administrative support and training, technology will not be used at full capacity in the classroom. The quantitative research in this field has revealed a variety of levels of effectiveness at all grade levels. 9

18 CHAPTER III METHODOLOGY Introduction This study is intended to examine whether the use of computer assisted learning software influences a student s success in college algebra at Texas Tech University. The variables will be assessed using descriptive statistics. Research Design During the Spring Semester of 2005, two sections of college algebra were chosen so that the student populations will be as comparable as possible. The classes met on the same days and at similar times to avoid differences with the time spent in class and student population. The first section, which will be referred to as the online section, was given access to MyMathLab, a computer assisted instruction software, in addition to traditional classroom instruction. In the online section, there were a total of thirty students. Nine of them were male and twenty one were female. There were nine freshmen, eight sophomores, six juniors, and seven seniors. The second section, which will be referred to as the traditional section, received only traditional classroom instruction. The traditional section was made up of twenty nine students including six males and twenty three females. There were eighteen freshmen and eleven sophomores. All students in both sections were what is referred to as traditional college students. This means they were between the ages of seventeen and twenty-five. 10

19 MyMathLab is a CAI software program that can be used in conjunction with many mathematics texts, including Texas Tech University s college algebra text by Robert Blitzer. This program is provided by Pearson Education and is powered by CourseCompass Blackboard Learning and Community Portal System. After a student purchases an access code and is given a course ID by their instructor, they will have access to many valuable tools. These include an announcement board and instructorposted course documents; video/powerpoint lectures; an interactive, electronic copy of the textbook; and access to an 800 number tutoring center open from five o clock pm until midnight Sunday through Thursday. There is also a large question bank for tutorial, homework, and exam exercises. The online homework not only gives immediate feedback to the students, but also includes an option for the computer to help them along. When the students click on the Help me solve this button, a window is displayed that shows step by step how to solve the problem. When they return to the homework, the students are given similar problem to complete. The students can also View an example, by clicking this button and the solution to a similar example will display. If the student wants to know where in the book this material is covered or to read through some of the previous examples, they can click a link that takes them to the appropriate pages in the electronic textbook. If the student still does not understand, they can click on the Instructor button and send an to the instructor. This allows them to type a question or comment as well as send a link to their particular problem. After downloading necessary programs from the 11

20 website, these helpful tools are available on any computer via the internet. To make sure all students were provided equal access, these programs were downloaded on computers in the residence halls, library, and mathematics building computer labs. Even though MyMathLab had many beneficial tools, there is a downside to this program. The program was very particular when it came to the format of the answer. It sometimes wanted a reduced solution, sometimes non-reduced; sometimes it preferred decimals, sometimes fractions. If a student submitted his or her answer and it was considered incorrect, he or she had to start over with a new problem. The students in the online section were required to complete homework assignments that were submitted via MyMathLab. Each assignments covered one or two sections and were made up of ten to twenty exercises. The students had an unlimited number of submissions and up to a week to complete each assignment. Both sections were assigned homework from the text, but for the online section it was only Suggested Problems and was not turned for a grade. Students enrolled in the traditional section were required to turn these assignments in for a grade. Data Collection and Analysis On the second day of class, all students took a pre-test and completed a Beliefs about Mathematics Survey. The pre-test consisted of eighteen problems and was not graded until the end of the semester to avoid difference in the grading procedure. Each problem on the pre-test was worth five points, giving a total pre-test score between The Beliefs about Mathematics Survey consisted of thirty statements in one of six categories. The categories were: 1) time commitments involved in solving math 12

21 problems, 2) ability to solve word problems without using specific steps, 3) understanding the reasons why a math problem works or is correct, 4) importance of word problems in mathematics, 5) attitude toward effort as a way of increasing mathematical ability, and 6) relevance of math to one's life. The students were asked if they strongly agreed, agreed, were uncertain, disagreed, or strongly disagreed with each statement. Depending on the response, the statements were scored on a scale from 0-4. There were five statements on each category, giving a category score between A total survey score was also calculated combining all six categories on a scale from Twenty questions from the final that were similar to those on the pre-test acted as the post-test. Each of these twenty problems was worth 5.5 points, giving a score between After they finished taking the final, students in both classes completed another Beliefs about Mathematics Survey as well as an open ended questionnaire regarding their thoughts on the class and online homework. All students at Texas Tech University are asked to complete an anonymous evaluation sheet regarding their course and instructor. The results of these evaluations pertaining to the course were analyzed. The grades from the pre-test and post-test as well as the scores from the pre- and post- Beliefs about Mathematics Survey were divided by category and recorded. Statistics calculated using SPSS Student Version 11.0 for Windows included histograms on the pre- and post-test scores, Levene s test for equality of variance on the pre- and post-test and survey scores, and t-test statistics on the pre- and post-test and survey scores. 13

22 CHAPTER IV PRE-TEST/POST-TEST ANALYSIS Introduction This section outlines the effects that computer assisted instruction software has on college algebra students success in terms of their pre-test and post-test scores. Results The pre- and post-tests are incorporated in appendix A. Group statistics for the pre-, post-, and change in test scores are presented in Table 1. Histograms depicting the score distribution of the online and traditional pre-tests are presented in Figures 1 and 2, respectively. Histograms depicting the score distribution of the online and traditional post-tests are presented in Figures 3 and 4, respectively. The Levene s Test for equality of variance and t-test for independent samples are presented in Table 2. Table 1. Group Statistics for Pre-, Post-, and Change in Test Scores. Pre Test Post Test Change in Test Section Std. Error N Mean Std. Deviation Mean

23 Std. Dev = 7.85 Mean = 15.8 N = Std. Dev = Mean = 24.0 N = Pretest Score Figure 1. Histogram of Pre- Test Scores. Pretest Score Figure 2. Histogram of Pre- Test Scores Posttest Score Std. Dev = Mean = 75.7 N = Std. Dev = Mean = N = Figure 3. Histogram of Post- Test Scores. Posttest Score Figure 4. Histogram of Post- Test Scores. 15

24 Table 2. Independent Samples Test on Pre-, Post-, and Change in Test Scores. Pre Test Post Test Change in Test not not not Levene's Test for Equality of Variances F Sig. t df t-test for Equality of Means Sig. (2-tailed) Mean Difference 95% Confidence Interval of the Std. Error Difference Difference Lower Upper Since Levene s test for equality of variance significance value on the pre-test (0.001) is less than 0.05, equal variance cannot be. This indicates that the t-test significance value for this data is located on the second row of the t-test statistics for the pre-test. This value (0.008) is less than 0.05; therefore there is a statistically significant difference in the means of the pre-test scores between the online and traditional sections. The mean difference of signifies that the online section was on average 8.23 points lower than the traditional section. Since the Levene s Test significance value for the post-test (0.806) and change in test scores (0.131) are both greater than 0.05, equal variance can be. This means that the t-test significance value is the one on the first rows of t-test statistics. Both the post-test (0.534) and change in test (0.076) t-test significance values are greater than 0.05 indicating that there is not a statistically significant difference between the two sections in terms of post-test or change in test score. 16

25 An analysis of the individual questions was completed and the questions were classified as to the difficulty to enter the answers into MyMathLab. This will be discussed more fully in Chapter VI. The group statistics for the change in each individual question are presented in Table 3 and the corresponding independent samples are in Tables 4 and 5. Table 3. Group Statistics on Change in Test Questions. Q1 Q2 Q3 Q4 Q5 Q6 Q7 Q8 Q9 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 SECTION Std. Error N Mean Std. Deviation Mean

26 Table 4. Independent Samples Test on Change in Test Questions 1-9. Q1 Q2 Q3 Q4 Q5 Q6 Q7 Q8 Q9 not not not not not not not not not Levene's Test for Equality of Variances F Sig. t df t-test for Equality of Means Sig. (2-tailed) Mean Difference 95% Confidence Interval of the Std. Error Difference Difference Lower Upper Since Levene s Test for equality of variance is less than 0.05 for questions 1, 5, 6, and 9, the correct t-test significance is the second row. For the remaining questions, the correct t-test significance value is the first one listed. The t-test significance values are greater than 0.05 for all questions except 6 and 9. This indicates no significant difference between the two sections on these questions. Since the significance value is less than 18

27 0.05 for questions 6 and 9, there is a significant difference on these questions. The group statistics table reveals that the mean score was higher for the online section for both questions. Table 5. Independent Samples Test on Change in Test Questions Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 not not not not not not not not not Levene's Test for Equality of Variances F Sig. t df Sig. (2-tailed) t-test for Equality of Means Mean Difference 95% Confidence Interval of the Std. Error Difference Difference Lower Upper

28 Since Levene s Test for equality of variance is less than 0.05 for questions 12, 14, 15, 17 and 18, the correct t-test significance is the second one listed. For the other questions, the correct t-test significance value is the first one listed. The t-test significance values are greater than 0.05 for all questions. This indicates no significant difference between the two sections on these questions. Statistical tests were run on each individual question on both the pre-test and posttest. These tables are included in appendix D. It was found that there was a statistically significant difference between the two sections on pre-test questions 9 and 14. The mean difference between the two questions was and 1.632, respectively, of 5.5 points. Question 9 covered finding a composite function and question 14 covered solving a system of linear equations with two variables. There were no questions on the post-test for which there was a statistically significant difference. The only questions that had statistically significant differences for the change in test scores were questions 6 and 9. Question 6 covered the objective of solving absolute value inequalities. Twelve students in the online correctly solved the problem, while ten in the traditional section got it right. The most common mistake on the post-test was for the students to just drop the absolute value bars and forget about working both sides, as shown in Figure 5. Nine students in both sections made this mistake. Some student made small arithmetic errors in the problem; seven in online section and five in the traditional section. There were two students in the online section and five in the traditional section who made major errors other than the one described below. 20

29 3( x + 1) ( x + 1) x x 0 x 0 Figure 5. Most common mistake on question 6. For this question, the online section had, on average, a better score. The online section required the solution to this problem in interval notation, starting with the most negative value. This did not make the answers particularly easy to enter into MyMathLab, so it is not likely that the students completed more practice problems than were required. The most plausible reason for the online section performing better is the immediate feedback. The students in the online section knew instantaneously if what they were doing was correct. If they were incorrect, most students would work another similar problem until they received full credit. The students in the traditional section did their homework one night and turned it in the next class period. They then had to wait at least two days for it to be graded and returned, at which time they could have simply looked at the grade and put it in their notebook. Few students really look and try to figure out what they did wrong on a homework assignment. Question 9 involved finding a composite function. Fourteen students in the online section and sixteen in the traditional section got full credit on this problem. The most common mistake was for the student to set the function they got equal to zero and solve for x as shown in Figure 6. Ten students from the online section and seven from the 21

30 traditional section made this mistake. Small arithmetic mistakes were made by two online students and three traditional students. Large errors other than the one below cost four of the online students and three of the traditional students the correct answer. g f( x) = g( 4x+ 8) = 2( 4x + 8) + 9 = 8x = 8x x = 25 x = 25 8 Figure 6. Most common mistake on question 9. Again, the online section had a larger increase in score for question 9. There are two reasonable explanations for why this is true. First is the immediate feedback rationalization. The online section knew right away if their answer was correct. Another excuse is the fact that MyMathLab prompted the answers. For problems that required solving for x, the program would have x =. For this problem, the prompt was given to be f g(x) =. This could have helped the students in the online section know what their answer should have looked like. The students in the traditional section would not have this prompt, and therefore would be more likely to make this mistake. 22

31 CHAPTER V PRE-SURVEY/POST-SURVEY ANALYSIS Introduction The effects MyMathLab had on the students attitudes toward mathematics are included in the following section. Results The survey and scoring guide are included in appendix B. The group statistics for the pre-survey scores are presented in Table 6. The Levene s Test for equality of variance and t-test for independent samples for the pre-survey scores are presented in Table 7. Table 6. Group Statistics for Pre-Survey Scores. Presurvey 1 Presurvey 2 Presurvey 3 Presurvey 4 Presurvey 5 Presurvey 6 Presurvey Total Section Std. Error N Mean Std. Deviation Mean

32 Table 7. Independent Samples Test on Pre-Survey Scores. Levene's Test for Equality of Variances t-test for Equality of Means Presurvey 1 Presurvey 2 Presurvey 3 Presurvey 4 Presurvey 5 Presurvey 6 Presurvey Total Equal variances Equal variances not Equal variances Equal variances not Equal variances Equal variances not Equal variances Equal variances not Equal variances Equal variances not Equal variances Equal variances not Equal variances Equal variances not F Sig. t df Sig. (2-tailed) Mean Difference 95% Confidence Interval of the Difference Std. Error Difference Lower Upper

33 Since the Levene s Test for equality of variance significance values for pre-survey categories 1, 2, 4, 5, 6, and total are all greater than 0.05, equal variance can be and the first row of t-test statistics provide the t-test significance values. Since the Levene s Test for equality of variance significance value for pre-survey 3 is less than 0.05, equal variance cannot be and the t-test significance value is listed on the second row. All of the t-test significance values are greater than This implies that there is not a statistically significant difference between the two sections. The group statistics for the post-survey scores are presented in Table 8. The Levene s Test for equality of variance and t-test for independent samples for the postsurvey scores are presented in Table 9. Table 8. Group Statistics for Pre-Survey Scores. Postsurvey 1 Postsurvey 2 Postsurvey 3 Postsurvey 4 Postsurvey 5 Postsurvey 6 Postsurvey Total Section Std. Error N Mean Std. Deviation Mean

34 Table 9. Independent Samples Test on Post-Survey Scores. Postsurvey 1 Postsurvey 2 Postsurvey 3 Postsurvey 4 Postsurvey 5 Postsurvey 6 Postsurvey Total Equal variances Equal variances not Equal variances Equal variances not Equal variances Equal variances not Equal variances Equal variances not Equal variances Equal variances not Equal variances Equal variances not Equal variances Equal variances not Levene's Test for Equality of Variances F Sig. t df t-test for Equality of Means Sig. (2-tailed) Mean Difference 95% Confidence Interval of the Difference Std. Error Difference Lower Upper

35 Since the Levene s Test for equality of variance significance values are all greater than 0.05, equal variance can be and the first row of t-test statistics provide the t-test significance values. The t-test significance values for post-survey categories 2, 3, 4, 5, 6, and total are greater than This indicates that there is no statistically significant difference between the two sections. For post-survey category 1, the t-test significance value is which is less than This signifies that there is a statistically significant difference between the two means. A mean difference of indicates that the online section was on average 3 (of 20) points lower. This section of the survey dealt with the time commitments involved in solving math problems. To determine if the survey was reliable, Cronbach s alpha coefficient of internal consistency was calculated. This is a value between 0.0 and 1.0 that estimates the probability that if the same survey was given to the same students, then the results would be the same. Anything greater than 0.7 is considered acceptable consistency. The alpha value for the overall survey score is , so this is within the acceptable range. For category 1, the alpha value is , which is suitable. Category 2 has an alpha value of Since this is below 0.7, the reliability of this category is not as high as it should be. For category 3, the alpha value is , which is acceptable. Category 4 s alpha value of is unacceptable because it is below 0.7. The alpha values of for category 5 and for category 6 are in the range of acceptable consistency values. 27

36 CHAPTER VI QUALITATIVE DATA ANALYSIS Introduction The qualitative survey completed at the end of the semester as well as qualitative data collected during conversations with the students throughout the semester is discussed below. Also included are the results of the Student Evaluation of Course and Instructor that are completed at the end of each semester for each class. Results The qualitative survey completed by the students after the final gave some insight as to why the post-survey category 1 scores were different. When asked if they thought MyMathLab was beneficial, most students responded negatively to some degree. Even though half responded with a yes, the majority added it was too difficult, complicated, or frustrating to enter answers. The most recurring reply to the question asking the most beneficial part of MyMathLab was the help me solve this or view an example buttons. However, most students did not utilize the tutor center, video lectures, or tutorial exercises. When asked if they prefer the online homework or the textbook exercises, the students were split down the middle. Those that preferred online liked it because of the immediate feedback, the unlimited attempts, or the examples. Those that preferred the textbook liked it mainly because they were not required to have the answer in a particular format, and it is harder to forget about something that is turned in every day. The surveys 28

37 and actual responses to these questions are included in Appendix C. When asked if they would take a class that incorporated online homework, the online section responded with 14 negatives, 14 positives, and 1 maybe. The traditional section answered with 10 negatives, 15 positives, 3 maybes, and 2 if it was offered, but not required. Two students decided that they did not like the questions asked on the survey. They responded by crossing out the questions and writing their own comments to the side. The first student wrote: math homework is the most absurd idea. Doing math online is comparable to writing a research paper on your calculator. Students have plenty of things to keep them busy without this extra busy work. math homework decreases the amount of math actually learned and increases the wasted time the student spends pecking at the key or looking for the square root button. To conclude, I found nothing helpful or useful about online homework. The second student wrote: My Math Lab in my opinion was a waste of time. All it wanted was answers in the right way, so a person could click enough times to get the answer. So there was no real learning. 29

38 The only MyMathLab service for which there was a variation in the amount of use was My Instructor. The students either always or never used the other services. A correlation was run between the number of times the students used this feature and their change in test score. Table 10 displays this result. The correlation between the use of and the change in test score is 0.237, which indicates a very low positive correlation. This means that about 23.7% of the variance in the change in test score can be attributed to the use of . Table 10. Correlation between the Use of and the Change in Test Score. Change in Test Use of Pearson Correlation Sig. (2-tailed) N Pearson Correlation Sig. (2-tailed) N Change in Test Use of The students made no attempt to hide their feelings about the program. When prompted in class, those who disliked MyMathLab were vocal and very blunt. However, there were students who seemed to enjoy the program. They did not seem to have problems entering answers to the same extent as the other students. Their typical routine was to view an example before working the exercises. This practice had two rewards, it helped refresh the process of solving the exercise and let the student know the answer format the computer required. This procedure was suggested to the students having problems, but was not well received. 30

39 All students at Texas Tech University are asked to complete an evaluation of the course and instructor. The students are given sixteen statements and are asked to rate the statements on a scale from 5 (Strongly Agree) to 1 (Strongly Disagree). All statements are written in a positive manner, so the ideal response is always 5. The first ten statements relate to the instructor s performance and the last six deal with the course. Those statements dealing with the course were incorporated into this study. They are 11) Overall this course was a valuable learning experience, 12) The assignments were relevant and useful, 13) Course materials were relevant and useful, 14) Expectations were clearly stated either verbally or in the syllabus, 15) The testing and evaluation procedures were fair, and 16) The workload was appropriate for the hours of credit. The group statistics for the ratings are described in Table 11 and the independent samples test statistics are in Table 12. The t-test statistics are all less than 0.05, so there is a statistically significant difference between the two sections on all questions. The means given in Table 11 indicate that the online section gave a lower rating than the traditional section in each category. There is a place for the students to include comments. The evaluation sheet and comments that concerned MyMathLab are contained in appendix C. 31

40 Table 11. Group Statistics on Course Evaluation Ratings. Question 11 Question 12 Question 13 Question 14 Question 15 Question 16 Section Std. Std. Error N Mean Deviation Mean Table 12. Independent Samples Test on Course Evaluation Ratings. Levene's Test for Equality of Variances t-test for Equality of Means Question 11 Question 12 Question 13 Question 14 Question 15 Question 16 not not not not not not F Sig. t df Sig. (2-tailed) Mean Difference 95% Confidence Interval of the Difference Std. Error Difference Lower Upper

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42 CHAPTER VII CONCLUSIONS Introduction A limitation of this study is the students could have employed more of the benefits available to them. Additionally, there was a difference in student population that could have lead to the difference in the pre-test scores. Yet, the conclusions drawn are useful in determining the value of this program. Limitations of Study The main limitation of this study was that the students did not utilize many of the services offered to them via MyMathLab. The results could have been considerably different if this was not the case. Mid-way through the semester, the majority of the students were extremely frustrated with the difficulty of entering answers. Therefore, they did not spend as much time working extra problems. The pre-test scores were not homogeneous and there was a statistical difference between the two sections to start out with, particularly with questions 9 and 14. This could be due to the fact that the two sections were not similar in their classification make-up. The traditional section was composed of underclassmen who typically have taken a math class within the past two years, if not less. The online class was composed of a more variety of the student population. Almost half of the class was upperclassmen, most of whom had not taken a 34