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Amy E. Smith and Ignacio J. Martinez-Moyano A variety of strategies have been proposed to address these issues. In general, these strategies can be grouped into three primary categories: teaching techniques, course content revision, and pre-course training. These categories are described next. Teaching Techniques Many have proposed specific teaching techniques or tools to address challenges inherent in teaching statistics. For example, experiential learning has been suggested as a technique for building student beliefs that statistics is valuable, reducing test anxiety for students, and integrating statistics into the lives of students—thus increasing its perceived value (Cobb, 1991; Snee, 1993; Zanakis & Valenzi, 1997). Experiential learning in statistics involves working with real data, solving real problems, and improving real processes (Calderwood, 2002; Snee, 1993). 2 Strasser and Ozgur (1995) suggest the use of case studies, a technique similar to experiential learning. In teaching statistics to social and behavioral science students, humor is favored by instructors as a tool for overcoming math anxiety. Schacht and Aspelmeier (2005) and Forte (1995) use cartoons to reduce student anxiety about math and statistics. These authors contend that students suffering from math anxiety tend to keep these feelings secret and thus avoid seeking help from the instructor or classmates. This can lead to student failure as well as instructor perception that students are lazy or unprepared. Humor and laughter can be used to acknowledge feelings of math anxiety in students and reduce tension. Others have suggested applying statistics to current events by using newspaper articles and other news sources as a way to persuade students that statistics may be valuable in their careers and lives (Peiris, 2002; Strasser & Ozgur, 1995; Zanakis & Valenzi, 1997; Calderwood, 2002). For example, if the government claims in a newspaper article that the unemployment rate is 7% and an opposing group claims otherwise, showing students how this dispute can be resolved by using statistics will help persuade them that statistics does, in fact, have real-life value (Peiris, 2002). For others, making statistics memorable, exciting, and more fun are also ways to increase student interest in, and perceived value of, the subject (Sowey, 1995; Strasser & Ozgur, 1995). Instructor excitement about course materials will affect students in positive ways. When an instructor is passionate about course material, it is easy for students to become excited as well. Students have many different thinking and learning styles. Kolb and Kolb (2005) assert that the way individuals learn, which is influenced by such factors as personality type, education specialization, career choice, and current job role and tasks, shapes the course of their personal development and learning styles. Snee (1993) suggests incorporating a variety of learning methods into the statistics curriculum to accommodate a range of learning styles. While some students learn best by reading books and listening to lectures, others learn 112 Journal of Public Affairs Education
Techniques in Teaching Statistics best by engaging in exercises, writing summaries, and taking part in material review sessions. Still others prefer visual aids, metaphors, and experiments. Incorporating a variety of these tools into a statistics curriculum will allow instructors to reach students in the ways that they learn best. On the basis of the six components of statistics anxiety (Cruise, Cash, & Bolton, 1985), Davis (2003) suggests that instructors begin their statistics courses with a discussion of statistics anxiety. This discussion should include literature on the subject and a chance for students to voice their concerns. The open dialogue acknowledges that statistics anxiety is real and lets students know that the instructor takes their concerns seriously. In addition to the teaching techniques already described, other recommendations for addressing challenges that instructors face in teaching statistics courses include the following: dividing classes into small collaborative groups (Calderwood, 2002; Davis, 2003; Forte, 1995; Peiris, 2002; Zanakis & Valenzi, 1997); incorporating greater use of computer technologies, especially those that are in demand in the market (Forte, 1995; Peiris, 2002; Strasser & Ozgur, 1995); providing lecture notes and study aids (Davis, 2003); and periodically holding class in the computer lab to facilitate software usage (Forte, 1995). Course Content Modifications Beyond specific teaching techniques, others recommend changing the content of statistics courses to address some of the challenges facing statistics instructors. Examples of such changes include reducing methodology coverage (Zanakis & Valenzi, 1997), weighting tests less or modifying grading techniques (Calderwood, 2002; Zanakis & Valenzi, 1997), improving textbooks (Schacht & Aspelmeier, 2005; Sowey, 1995; Strasser & Ozgur, 1995), going into greater depth on fewer topics (such as research design, data collection, and data display; Fitzpatrick, 2000; Snee, 1993; Strasser & Ozgur, 1995), and reducing coverage of such topics as hypothesis testing, probability, and mathematical concepts (Desai, 2008; Snee, 1993; Strasser & Ozgur, 1995). Conversely, Strasser and Ozgur (1995) also report that some instructors wish that more topics were covered. Fitzpatrick (2000) argues that, to become better consumers of research, students must not only understand statistics, but they must also understand how to read existing literature. Thus, course content should include a researchconsumption component that teaches students to read and interpret literature reviews, data and methods, findings, and implications of existing research throughout the course. Calderwood (2002) suggests changing the titles of statistics courses to be more relevant and less intimidating. Students should understand that the purpose of the course is not to transform them into statisticians or mathematicians, but rather to teach them basic statistical concepts and tools and the appropriate ways to use these concepts and tools in data analysis processes. Journal of Public Affairs Education 113
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JPAE VOLUME 18 NUMBER 1 JOURNAL OF
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Journal of Public Affairs Education
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FROM THE EDITOR In the symposium in
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NASPAA Presidential Address Annual
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Leading by Example: Modeling Global
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FROM THE GUEST EDITOR FROM THE GUES
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FROM THE GUEST EDITOR A SYMPOSIUM I
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on other fronts, certainly it can h
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Picasso, P. (1937). Guernica. Pictu
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A View from the 50th Street Gate on
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Reflections of a Working-Class Acad
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Reflections of a Working Class Acad
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Reflections of a Working Class Acad
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Class Rooms Kenneth Oldfield Univer
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Class Rooms although I did, but not
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Class Rooms GRADUATE SCHOOL I was u
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Class Rooms the odds this appointee
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Class Rooms The Great Leveler, too
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Class Rooms of higher learning and
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Didactic Changes Class Rooms Pedago
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Shaw, G. B. (1928). The intelligent
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Analysts also determined the number
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Topical categories. As shown in Tab
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Knowledge and Skills for Policy Mak
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and writing the proposal for the co
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it was achieved. The assessment of
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Fulbright Program for Foreign Stude
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Review of Moral Controversies in Am
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application of those foundations to
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Journal of Public Affairs Education
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Information for Contributors The Jo
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