WINTER 2012 - National Association of Schools of Public Affairs and ...

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Amy E. Smith and Ignacio J. Martinez-Moyano Phase IV: Data Analysis Of those participating in the study, 5 of the 13 instructors were female. These instructors represented five of the six social science disciplines in our original target group. (No instructors from business programs participated in the study.) The colleges and universities with which the responding instructors were affiliated were predominantly public (9), the largest proportion of instructors being from public affairs programs (5). On average, this group of instructors had their PhDs for over 18 years (minimum, 3 years; maximum, 36 years) and had taught statistics for over 16 years (minimum, 8 years; maximum, 31 years). During the idea elicitation stage, an average total of 41 ideas were generated for each challenge. The greater the number of ideas generated, the greater the potential for creativity in the Delphi process (Van de Ven & Delbecq, 1974). On average, for all four questions asked, participants placed more than two ideas in each cluster. The minimum number of ideas placed in a cluster was 1; the maximum was 10. These distributions were relatively right-skewed, and several clusters included only one idea. While only 7 of the original 13 instructors participated in all stages of the Delphi process, we provide summary statistics on all 13 of the instructors here because all 13 provided the initial list of ideas deemed essential for addressing the challenges. This elicitation of ideas formed the core of the remainder of the data collection stages. Identifying Agreement among Participants A major goal of this project was to identify the tools and techniques that instructors agreed are essential for addressing the challenges in teaching statistics to students enrolled in practitioner-oriented master’s degree programs. Participants’ rankings of clustered ideas were divided into three groups using the mean rating for the cluster and a simple majority rule. By using the simplemajority criterion, in conjunction with the mean rating for a cluster, we address potential issues arising from the sensitivity of the mean to outliers. The three groups created are the highest-importance group, the highimportance group, and the average-importance group. These groups capture how essential each cluster is for addressing the challenge in question. Thus, clusters in the highest-importance group are considered by the experienced instructors in our study as the most essential for addressing the challenge. Table 1 summarizes the method used to identify agreement among participants. FINDINGS According to the group of experienced instructors that participated in our research, when designing and/or selecting tools effective for learning, instructors should focus on using real-life, relevant examples; employing computer applications; and emphasizing the process, not the results. Additionally, to 120 Journal of Public Affairs Education
Table 1. Downloads of Papers at Selected Educational Institutions Challenge: Tools Effective for Learning Highest-Importance Group ��Use relevant real-life examples. ��Employ computer applications. ��Emphasize the process, not the results. High-Importance Group ��Use simulation to generate insights about statistical concepts. Challenge: Low Levels of Quantitative Skills ��Apply statistics to real life. ��Require data collection exercises. ��Demonstrate the value of understanding statistics. Challenge: Desire to Memorize Rather than Understand ��Select an appropriate text. ��Use relevant examples. ��Select textbooks that employ practical examples. ��Use “story” problems. Average-Importance Group ��Focus on restructuring how students think. ��Do easy math. ��Use notation early. ��Demonstrate the value of understanding statistics. ��Utilize online discussion groups. ��Reiterate the same problems using different techniques Challenge: Low Levels of Motivation, Participation, and Engagement ��Build knowledge incrementally. ��Emphasize interpretation and understanding, not results. ��Allow memorization Techniques in Teaching Statistics ��Use relevant examples and require students to do the same. ��Provide examples of bad use of statistics. Journal of Public Affairs Education 121
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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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ook (Oldfield & Johnson, 2009). The
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Didactic Changes Class Rooms Pedago
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Admittedly, it will be difficult to
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hooks, b. (2000). Where we stand: C
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Shaw, G. B. (1928). The intelligent
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What’s a Girl Like You Doing in a
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What’s a Girl Like You For exampl
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What’s a Girl Like You and operat
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What’s a Girl Like You captured t
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What’s a Girl Like You full-blown
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What’s a Girl Like You inside). I
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What’s a Girl Like You and collea
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What’s a Girl Like You toward ser
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Blue-Collar Teaching in a White-Col
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Page 111 and 112: REFERENCES Ashwander v. Tennessee V
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Topical categories. As shown in Tab
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negative impact on ARP downloads (
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Knowledge and Skills for Policy Mak
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Stories from Local Public Managers
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and writing the proposal for the co
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Another echoes: Stories from Local
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I think communication is one of the
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Creating Quality Online Course Desi
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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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