MAT-125-01, 
MAT-125-02, 
MAT-099-02 and 
MAT-111-01

Spring 2005

Provided will be an overview of the results of assessment in the courses provided by the instructor, Barbara L. Tanzyus. These results assisted this instructor in determining the direction of future courses provided at this institution of higher education. These are preliminary results. Further review of these results will be completed as time progresses.

Barbara L. Tanzyus has been a member of the mathematics faculty since January of 2002. Overall, this instructor has provided on average 6.14 courses per semester excluding summers and 1.50 per summers with an overall average of 4.67. For overall semesters, this instructor has attended the university taking courses at the rate of 1.08 per semester. This instructor is pursuing a PhD in mathematics education at Illinois State University and commutes in order to accomplish that goal. Projected graduation date is Spring of 2007. This instructor has provided 1.33 statistics courses per term, 0.67 elementary education mathematics courses and 0.83 remedial courses. This instructor has provided courses in all undergraduate programs offered by these institutions including the traditional programs and accelerated programs for both schools. With the new masters program, nothing has been provided there to date.

According to the Tenth International Congress on Mathematical Education, enrollment in elementary statistics courses is up 42% nationally (Usiskin & Dossey, 2004). Yet, a survey conducted in 1995 by The Conference Board of the Mathematical Sciences indicated that 94% of sections of statistics at two year colleges were taught by lecture (Loftsgaarden & Watkins, 1998). But, statistics in college is the number one nightmare course for students. According to students, "Statistics is confusing and dull" (Martin, 2003, p. 1). Why? Statistics does not live for them. It is not real. It is a dead group of formulas with no dimension. Why? Textbooks and instructors teach statistics like any other mathematics - axiomatic and theoretically driven. Though students need to know the theory they also need to learn to apply that theory to reality and make that theory live. If students go to work in statistics in their future, their work will not be formula driven. They will need to use what they learned and apply that to the workplace. Within the real world statistics is practical. "Teaching stochastics is teaching problem solving" (Shaughnessy, 1992, p. 467). Statistics is alive. It thrives on real world examples not dead ghosts of mathematicians past. Though statistics needs to give credit to those who contributed the important theoretical pieces to develop the discipline, yet statistics has to live in the hearts and souls of its students so that they can go into the world and share its wonders. Statistics can live in the hearts of students if you make it live in their lives. This was some of the rationale for student survey projects - living statistics.

Students need to experience the data that they use within their analysis. Schafer and Ramsey (2003) reported that before their use of student projects, that "The bungling of data analysis, often by students who received grades of A, indicated to us that we weren't training the students in the full range of skills necessary for successful application of statistics" (p. 1). Schafer and Ramsey (2003) taught introductory statistics in Oregon. When they introduced student projects, they found "understanding and appreciation of data analysis" (Schafer & Ramsey, 2003, p. 2). Their work reported that students found statistics interesting and relevant when the statistics was made a part of their lives. This was what student projects attempted to accomplish - bring life to statistics. Snee (1993) reported "Collection and analysis of data is at the heart of statistical thinking. Data collection promotes learning by experience and connects the learning process to reality" (Tappin, 2000, p. 4). With these ideas in mind, assessment needed to be included.

Though I teach many course types, statistics is my overriding lens of reference. Within my PhD work, my focus is within the area of statistics education. I by no means have read every piece of literature that exists within the field of statistics education, but I am diligently trying to. The focus of my teaching was understanding of the concepts. I attempt to achieve this goal by constantly requesting feedback from students. In my class, we do not move forward unless students understand. Often we step back and question to make sure that understanding is not lost. In mathematics, the building process is significant as concepts build upon each other. In statistics, concepts build on each other and we must also construct upon the experiences of the student from the real world.

Most students enter the realm of statistics with some type of knowledge base whether it is correct or incorrect. Dispelling invalid conclusions and constructing valid ones is a revolving focus of my courses. No course is ever taught identically. Each course revolves around its students and their interests and knowledge that they bring to the course. I constantly look for real world data and examples to bring to the discussions for construction of understanding and relationship of the material to the world around the student. Application of this material is core to my course objectives. Hence, each class is requested to write a survey, seek approval of that document, distribute the survey and analyze the results as one piece of the assigned work of the course. This entity is the source of my current evaluation within my professional project piece for my dissertation work. With this piece, I attempt to wrap all of the course content together and illustrate its usefulness in the world around us.
Additionally, when student do not ask questions, then I begin to quiz students for understanding on a regular basis. This will either determine that they do not know them material or will need further assistance. On average, 1.2 quizzes were given each week to students to assure that understanding was being achieved. This would be yet another positive factor for attendance as students would miss that interaction.

Students start each day providing their input. They are asked to indicate their preparedness for the day's materials. This was seen in whether they read or completed their homework. They are also asked for any questions or concepts that they find difficult for further explanation. Students have three significant pieces of their overall performance in my courses. These included chapter tests, project grades and overall grade. Additionally, included were their attendance and preparedness for the day's materials. Quizzes are also provided as needed based on the number of questions that students ask and the preparedness that the instructor felt that the student had. If students appeared to be not prepared, then more quizzes were provided.

Students for the four courses provided for Springfield College in Illinois were included in this study. These included MAT-125-01, MAT-125-02, MAT-099-03 and MAT-111-01. For MAT-125 this was a statistics course provided for business and social science majors. There were 25 students in each section of this course for a total of 50 and the course met three days a week. Days included for this course were 30 out of the 40 as the others were in taking tests or returning tests. There were 48.0% females in section one and 72.0% females in the second section. In MAT-099, this is a course in the remedial group for those students likely to transfer to college algebra though not required. They will eventually need to take a 100 level mathematics. The course met three days a week. There were eight in that section and also 30 out of 40 days included. There were 75.0% females in this course. The MAT-111 is the second semester of the mathematics for elementary education majors and this section has statistics as its prominent segment. Therefore those students follow much of what the statistics courses study and complete an analytical project. There were 12 in that course and there were 20 days included out of 28 as this course met two days a week. This course was 75.0% female.

Each day students are requested to provide feedback of their questions and overall course status. Additionally, in class, the instructor will ask directed questions in order to determine the student's level of understanding. If students are unable to answer questions, simpler questions are posed. If they are proficient, then harder questions are provided. Student's faces are constantly read to determine their level of confusion. If students look perplexed, then a review of the concepts in a different light will be provided. Students are requested to provide written essay assignments, computer lab assignments, applications assignments where real world examples were to be found, completion of homework or more conventional problem solving, understanding of terminology was explored in assignments and the completion of a survey and its analysis. These items are used along with chapter tests that explore statistics through conventional problems as well as essays. Much of the class was students working on problems posed and the instructor observing their interaction as group work was encouraged. When common problems are found, these are highlighted in the discussion that results after the students have worked on problems for a period of time. The hope was to dispel errors and misconceptions.

For overall attendance of courses, students attended class on average 80% of the time and no student attended every class. Students did not ask questions 94.8% of the time and 41.4% of students never asked any questions. Students read the material prior to class 91.7% of the time with 24.3% of students always reading the materials. Students came to class with their homework completed 90.0% of the time and 24.3% of students came to class daily with their homework completed. The median overall grade for students was a C and their median chapter test grades were a C+. For overall ending grades, 20.0% of students received A's, 15.7% received B's and 24.3% received C's or 60.0% received grades that would transfer to another institution of higher education. 24.3% of students did not pass the course. Of those not passing, 58.8% did not pass due to lack of attendance and hence work completion. The remaining percentage did not complete the final survey project.
Strong positive correlations were determined between attendance and ending grade (r=0.604) and attendance and chapter test grades (r=0.623). There was a midrange positive correlation between homework completion and reading of the materials (r=0.420). Additionally, ending grade had a strong positive correlation to chapter test grades which would be logical as they constitute 30% of that grade (r=0.864). Neither reading nor homework completion significantly impacted overall or chapter test grades. Questions asked did not impact the course or chapter test grades.

Attendance was a strong part of the students overall success in the courses provided by this instructor. What was presented in the course was significant to overall student success. It appeared nature for students to read and complete their homework but not in all cases as this occurred only 42.0% of the time. Questions asked should have been higher as students would often ask questions one on one and those were not included on the assessment instruments. Students indicated that they were prepared for the course, but often this was not the feelings of the instructor. After a point in time, quizzes were provided to assess student understanding and illustrate to the student that lying on the assessment instrument was not assisting them in understanding. Overall student attendance was not positive. The minimum set for the course was 80.0% and for this group 40.0% did not meet this requirement. In the future, attendance standards need to be increased as stronger positive results occurred as a result of attendance and instruction. This instruction could not be replaced by the textbook or a tutor. This would indicate that class time was used to effectively for instruction of essential concepts needed for understanding. This term may have been one of the largest for failing overall grades. Part was due to attendance and part due to poor planning on the long range project.

Attendance policies will be changed for the Spring of 2006 as this study indicated a positive correlation in that area. Since students did not voluntarily attend class as expected or did not see the benefit on their own and instead looked to not attend, this would be an important matter. Additionally, other instruction appeared to not be as effective as that provided in the normal course time allotted. More stress will be placed on recording student's questions on the assessment for a clearer picture on that area. Students ask a great deal of questions that I answer and do not indicate on these instruments. More emphasis will be provided on the survey portion of the course. Too many students did not understand the importance of this piece in their overall performance and did not effectively plan and allocate enough resources to the assignment to insure completion. Many of those with uncompleted projects indicated some sort of work had been done. I conjecture that they did not understand the concepts enough in order to finish the work and as a result had poor overall performance in the course. The direct application of the material to the real world is an important portion of the overall importance of the teaching of statistics to students of other disciplines. I also convey if they do not know how to use the material, they have learned very little. Just following the rules does not insure understanding or applicability. Then statistics does not live in the student but stays dead in the textbook for the next visit by the next student who chooses to open the textbook. Statistics needs to live to be understood. That did not occur for all of these students. More work will be pursued in that area for future class segments and course assignments will be revised to reflect a better application of using statistics in the real world.
This is a preliminary picture at best of the past results on one semester. This process will continue and will be enhanced as time progresses. It is at least a basis for future assessment challenges.

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