Internet classes are being seen more and more as

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1 Internet Approach versus Lecture and Lab-Based Approach Blackwell Oxford, TEST Teaching X Journal Original XXXXXXXXX 2008 The compilation UK Articles Statistics Publishing Authors Ltd 2008 Teaching Statistics Trust for Teaching an Introductory Statistical Methods Course: Students Opinions KEYWORDS: Teaching; Online; Students perspectives; Pedagogical research. H. Dean Johnson, Nairanjana Dasgupta, Hao Zhang and Marc A. Evans Washington State University, USA. Summary The use of the Internet as a teaching tool continues to grow in popularity at colleges and universities. We consider, from the students perspective, the use of an Internet approach compared to a lecture and lab-based approach for teaching an introductory course in statistical methods. We conducted a survey of introductory statistics students. Contradictory to what was hypothesized by the authors, they favoured keeping the lecture and lab-based approach for teaching the class. INTRODUCTION Internet classes are being seen more and more as alternatives to lecture-based classes. There have been several studies to examine the effects of the two approaches on test scores in introductory statistics classes (Utts et al. 2003; Ward 2004; Dutton and Dutton 2005). There has been less research, however, on the opinions of students regarding the use of an Internet approach compared to a traditional approach for teaching statistics. If one is considering using an Internet approach to teaching, it is important for the instructor to understand the attitudes that students have towards Internet classes. This study was conducted to shed some light on the perspectives of introductory statistics students regarding the type of teaching approach they would like to see used for teaching statistics. Being teachers of statistics, we wanted to learn whether students would advocate an Internet approach to teaching an introductory course in statistical methods over the traditional lecture and lab format that we currently use. The popularity of the Internet with students coupled with the perceived dislike that many students have for lecture classes, one perhaps would suspect that students would welcome an Internet class. To investigate whether students would favour an Internet approach over a lecture-based approach to teaching introductory statistics, we surveyed students in STAT212, an introductory algebra-based statistical methods course taught at Washington State University. THE DATA COLLECTION Three sections of STAT212 are offered each semester at Washington State University. This course satisfies a general education requirement for mathematics proficiency at the university. In addition, it satisfies the requirements of many departments. In the class, students use statistical software and they use the Internet for the purpose of printing out class handouts as well as running JAVA applets. Thus, computer and Internet access are important. Students enrolled at Washington State University have access to computer labs on campus, where they can use university software. They also have access to the Internet as the dormitories, libraries and computer labs are connected to the Internet through Ethernet The Authors Teaching Statistics. Volume 31, Number 1, Spring

2 Quantitative variable Minimum 25th percentile Median 75th percentile Maximum Average number of hours on Internet per week Average number of hours on Internet per week for class Math skill Qualitative variable Count Percentage Class Freshman Sophomore Junior Senior Gender Female Male Student type Honours college student Regular university student Table 1. Description of students in STAT212 (Spring 2006) STAT212 consists of 3 hours of lecture and 2 hours of lab per week. In the labs, students participate in hands-on activities, in which they collect their own data and analyse the data using Minitab statistical software (Minitab Inc. 2004). Professors conduct the lectures and graduate students conduct the labs. In the spring of 2006, three different professors taught the three sections of STAT212. Two of the sections each enrolled approximately 125 students and the third section enrolled approximately 75 students. The three sections used the same text and had a similar structure. Each professor required three exams, homework, completion of labs and a project. For the class project, students were asked to complete the survey found in the Appendix and analyse the data resulting from the survey. The instructors purposely made the survey short to make the data analysis more manageable for the introductory statistics students. At the end of the semester, the students were each required to turn in a two- to three-page report in which they discussed the results of their analysis. The authors have observed that having students complete a project, in which they collect and analyse data that are of interest to them, enhances the learning of students in introductory statistics classes. Consequently, the authors will continue to incorporate projects. One difficulty encountered, however, involves the amount of time required to grade the projects. If the reader is considering incorporating such a project in his or her class, the authors would suggest requiring group projects as opposed to individual projects to cut down on the grading time, especially if the class size is large. In our study, we combined the survey responses from the three sections of STAT212, resulting in a sample size of 267. A numerical description of the sample is provided in table 1. ANALYSIS In our analysis, we examined the percentage of all study participants in favour of an Internet approach and then decomposed the preferred teaching approach by each of the following variables: class (freshman, sophomore, etc.), gender and student type. The majority, 75% (95% confidence interval: 69%, 80%), of the students were in favour of the traditional approach. Also, regardless of class, gender and student type (honours college or not), the traditional approach was the preferred choice of students, as shown in figures 1 3. To identify factors that relate to preferred teaching method, we conducted a logistic regression analysis using the variables in table 2. Logistic regression was used here instead of ordinary regression because the response variable (preferred teaching method) is a binary response variable (0 = No, 1 = Yes) as opposed to a quantitative variable as one would encounter in an ordinary regression analysis. If a survey similar to the one described in this study was conducted with question 5 being changed so as to ask students to identify on a continuous scale, say from 0 (strongly disagree) to 10 (strongly agree), how strongly they agree or disagree that they would prefer an Internet class, the results could be analysed using ordinary regression techniques. In a logistic regression analysis, the probability of the occurrence of one of the two outcomes of the 22 Teaching Statistics. Volume 31, Number 1, Spring The Authors

3 Fig. 1. Preferred teaching approach by gender Fig. 3. Preferred teaching approach by student type variables that are good predictors of the response variable. For more information on logistic regression, please refer to Hosmer and Lemeshow (2000). Fig. 2. Preferred teaching approach by class binary response variable is modelled, via the logit transformation, as a function of one or more explanatory variables. One of the purposes of logistic regression, like ordinary regression, is to identify One approach to identifying good predictors is to use a variable selection procedure. We used a stepwise procedure, with the stopping rule being that the p-value of all variables not in the model is > 0.10 (for both entering and leaving the model). We chose this 0.10 cut-off as opposed to the traditional 0.05 cut-off mark because of the exploratory nature of our study. In using stepwise logistic regression procedure, GENDER and AVGINT- CLASS were identified as being statistically significant predictors of PREFERRED TEACHING APPROACH. The results of this stepwise logistic regression analysis are presented in table 3. In our discussion of the results, we interpret them in terms of odds ratios (Hosmer and Lemeshow 2000), holding the other variable constant. In regard to GENDER, we estimated that females are times as likely to prefer an Internet class as males, holding AVGINTCLASS constant. This finding of males preferring computer usage more Variable name Description Response variable PREFERRED TEACHING APPROACH Lecture = 0, Internet = 1 Explanatory Variables: CLASS Freshman = 1, Sophomore = 2, Junior = 3, Senior = 4 GENDER Male = 0, Female = 1 STUDENT TYPE Whether or not student belongs to honours college: No = 0, Yes = 1 AVGINT Average number of hours on Internet per week AVGINTCLASS Average number of hours on Internet per week for class MATH SKILL Student s rating of his or her math skill: 1 (low) to 10 (high) Table 2. Description of explanatory and response variables used in logistic regression analysis 2009 The Authors Teaching Statistics. Volume 31, Number 1, Spring

4 Parameter Odds ratio p-value Table 3. Results of logistic regression analysis 90% lower confidence limit for odds ratio 90% upper confidence limit for odds ratio INTERCEPT GENDER AVGINTCLASS than females is consistent with findings from other studies (Temple and Lips 1989; Whitley 1997). In regard to AVGINTCLASS, for every 1-hour increase in the average number of hours a student spends on the Internet for the class, we estimated that he or she is times as likely to prefer an Internet class, holding GENDER constant. In STAT212, students are required to retrieve class notes and assignments from the Internet. This was not meant to take much time for the students. The professors did observe, however, that for some students retrieving the information was timeconsuming and they became frustrated as a result. The frustration experienced by some students can be used as one possible explanation for an increase in Internet usage for the class being associated with being less likely to prefer an Internet class. The overall concordance for our final model was 54.9%. The Hosmer Lemeshow Goodness of Fit indicates the logistic regression model provides a good fit for the data ( p = 0.456). Two outliers were detected in the logistic regression analysis. For each of these two observations the amount of time spent on the Internet for class purposes was unusually large. Specifically, one student indicated that an average of 15 hours a week was spent on the Internet for class purposes and the other student indicated an average of 10 hours. As mentioned earlier, students in STAT212 are only required to use the Internet for retrieving class notes and assignments. Given this, these two responses were deemed questionable and the decision was made to leave them out of the final analysis. However, it should be noted that when the two outliers were included in the analysis, only GENDER was detected as a significant predictor of preference. DISCUSSION As mentioned earlier, the students in the three sections of STAT212 were required to write a report for their class project. In the write-ups, many students expressed their opinions regarding why they favoured lecture-based classes over Internet classes. Below are some of the comments made by students, which help to shed some light on the preference students have for a lecture-based course over an Internet-based approach. These comments are grouped according to the different themes that emerged from the opinions. Face-to-face interaction Many of the students in this study value the face-to-face learning experience, and thus prefer a lecture-based approach over an Internet-based approach, as illustrated by the comments below. I personally feel that the interaction between students and their teacher/professor is crucial for successful learning. So, the option of an Internet class should be overridden. The social interaction between fellow students, the professor, and the TAs [teaching assistants] is a vital part of the learning process and one would not succeed nearly as easily if they were taking an online-based course. It is my belief that students are better able to learn material when they have the opportunity for face-to-face contact with the instructor and fellow students. In a face-to-face setting students can more easily ask questions and learn from the questions and input of other students. Subject matter It is the belief of some of the students that the most effective teaching approach depends on the subject matter, as discussed below. For a history class that has strictly lecture notes, exams and quizzes could be taken online because you don t have any examples and the information is either read to the class or presented in a way that notes are needed. A math class that has different equations and examples should not be taught online because if there is a misunderstanding, usually the teacher can help explain it another way if you are in class. Science-based classes should not be used for Internet purposes, but classes such as history would be beneficial to students because there are no interactive hands-on activities. Some classes simply must be taught in the classroom such as those with hands-on labs or very detailed subject matter such as calculus. Procrastination According to some of the students, Internet classes have the potential of fostering procrastination, as detailed in the comments below. 24 Teaching Statistics. Volume 31, Number 1, Spring The Authors

5 When a student completes a course online, it is done at his or her own pace and within the comfort of their home, which allows the student to fall behind and fail to learn the material thoroughly. A disadvantage of online courses is the complete lack of supervision. If a person is not motivated to finish what they start, then it is probably not a good idea to take an online course. While there may be deadlines and expectations from the online course instructor, there is no one there to remind him/her to do the assignments or to take the tests. It is difficult for some people to muster the self-discipline to do the homework every day or every week, without a teacher, it becomes easier to procrastinate. Convenience factor Some students expressed inconveniences associated with the use of an Internet-approach and these are mentioned below. Most students I have talked to prefer to have a professor to be able to go talk with when they are having problems, not try to surf the Internet for answers. It is difficult to understand the material on your own and not be able to ask questions directly to your professor when instead you have to correspond through and wait for a response. There are disadvantages to Internet classes. Say for instance, the Internet network on campus was not functioning for a week, then the Internet class could not be held due to technicalities. Internet instruction on performance in statistics classes. In these studies, different conclusions were reached regarding the effect of Internet instruction on course performance. Dutton and Dutton (2005) concluded that students in a Business Statistics class performed better when an online teaching approach is used compared to when a lecture-based approach is used. But Utts et al. (2003) and Ward (2004) concluded that there is no significant improvement in performance when a hybrid- Internet approach is used compared to when a traditional lecture-based approach is used. Our study was conducted to see if students would advocate switching from the traditional lecture-based approach to teaching an introductory course in statistical methods currently used at Washington State University, to an Internet-based approach. We conclude that, at Washington State University, the majority of students favour the lecture-based approach to instruction, and this is true regardless of gender, class and student type. Based on the results of other studies, showing lack of compelling evidence that using an Internet-based approach improves performance, and our results, the authors will continue to use a lecture-based approach in teaching the introductory statistical methods classes at Washington State University. CONCLUSION The Internet enjoys great popularity with college and university students. This was illustrated in this study, with the median number of hours spent on the Internet by the introductory statistics students in this study being 10 hours. The authors anticipated that this popularity would translate into the students preferring an Internet approach to teaching introductory statistics over the lecture/lab approach that is currently used at Washington State University. This was not the case. The majority of the students preferred the lecture/lab approach over an Internet approach and this was true regardless of gender, class (freshman, sophomore, etc.), and student type (honours college or not). We note that our study was on the teaching approach (Internet or lecture) preferred by students and not on the effectiveness of the two approaches. Just because students advocate a lecture-based approach to an Internet-based approach, this does not mean that students will necessarily learn more when such an approach is used. Several studies have been conducted examining the effect of References Dutton, J. and Dutton, M. (2005). Characteristics and performance of students in an online section of business statistics. Journal of Statistics Education, 13(3), amstat.org/publications/jse/v13n3/dutton.html. Hosmer, D.W. and Lemeshow, S. (2000). Applied Logistic Regression (2nd edn). New York: John Wiley & Sons. Minitab Inc. (2004). Minitab, Version 14 (Computer software). State College, PA: Minitab Inc. Temple, L. and Lips, H.M. (1989). Gender differences and similarities in attitudes toward computer. Computers in Human Behavior, 5(4), Utts, J., Sommer, B., Acredolo, C., Maher, M.W. and Matthews, H.R. (2003). A study comparing traditional and hybrid internetbased instruction in introductory statistics classes. Journal of Statistics Education, 11(3), utts.html The Authors Teaching Statistics. Volume 31, Number 1, Spring

6 Ward, B. (2004). The best of both worlds: a hybrid statistics course. Journal of Statistics Education, 12(3), publications/jse/v12n3/ward.html. Whitley, B.E. Jr. (1997). Gender-difference in computer-related attitudes and behavior: a meta-analysis. Computers in Human Behavior, 13(1), Appendix Survey used for STAT212 Project 1. What is your gender? 0 = Male 1 = Female? 2. What year are you in Washington State University? 1 = Freshman 2 = Sophomore 3 = Junior 4 = Senior 5 = Graduate student 3. How often do you access the Internet? (number of hours on an average week) 4. How often do you access the Internet for STAT212 class purposes? (number of hours on an average week): 5. Would you prefer an Internet class as opposed to a face-to-face lecture with lab-type class for STAT212? 1 = Yes 0 = No 6. On a scale of 1 (low) to 10 (high), how would you rate your Math skills? 7. Are you a part of the honours program? 1 = Yes 0 = No XXX Original SHORT AUTHORS Articles TITLE RUNNING HEAD: HEAD: LOOK AHEAD Forthcoming articles include Analyzing the world population: Using population pyramids and If the World Were a Village The binomial distribution in shooting Correlation between coin random variables Experimental probability in elementary school Explaining a positive test result to a patient Hypothesis testing with the Three Stooges An inside look at the two envelopes paradox Madlibs Playing with residuals Statistics online computational resource for education Teaching decision theory with Deal or No Deal Understanding of patterns, streaks, and independence by grade school children A website that provides resources for assessing students statistical literacy, reasoning, and thinking 26 Teaching Statistics. Volume 31, Number 1, Spring The Authors