There are four exercises that use data from the 2014 General Social Survey to explore topics in religion. These exercises could be used to help students learn the principles of quantitative analysis with a focus on religion. Substantive topics include religious preference, religiosity, and fundamentalism. Methodologically and statistically relevant topics include conceptualization, measurement, reliability, validity, data analysis, hypotheses, and spuriousness. These exercises refer students to the relevant parts of an online introduction to SPSS--the software package used in the exercises. This online introduction is freely available at http://ssric.org/node/582. Each exercise consists of five files – the data set in SPSS format, extended notes to the instructor, the SPSS syntax necessary to carry out the exercise, and the SPSS output for the exercise. The exercise itself is available in both HTML and Microsoft Word (docx) format.
Type of Material:
Assignment, learning object repository.
The learning object is a valuable tool for use in any undergrad social-science methods or statistics class. It would also serve as a great refresher for graduate-level students at the beginning of a intro grad quantitative methods class. It would work well as a series of out-of-class assignments either done by students individually or collectively.
Requires SPSS (any version) and ability to read Microsoft Office (docx) files.
Identify Major Learning Goals:
This learning object provides comprehensive instructions that lead students through key sequential stages of describing and analyzing quantitative data. The exercises relate to responses to a variety of questions about religion, derived from the 2014 General Social Survey. Among quantitative skills addressed are variable construction and reliability, and univariate, bivariate, and multivariate analysis with focus on determining spuriousness. Student knowledge about the causes and consequences of variables related to religious behavior and attitudes will also be enhanced.
Target Student Population:
Social Science Statistics and/or Research Methods courses and substantive courses that deal with religion.
Prerequisite Knowledge or Skills:
Familiarity with navigation in SPSS.
Data rich, high quality set of learning materials. Provides students detailed instructions that simplify the complex task of describing and analyzing quantitative data. Helps students to understand that there is a basic logic and process that, if explicitly followed, will build research competency. Exercises train learners on SPSS operations, tools, and data analysis by using valid, reliable data sets to explore statistical measures.
SPSS software is required.
Potential Effectiveness as a Teaching Tool
The exercise has a number of features making it an excellent teaching tool. First it is explicit in providing detailed instructions to students. It clearly spells out learning objectives, and leads students through much of the quantitative analysis process, which students often find difficult to comprehend. It should also neatly reinforce methods and statistical concepts addressed in text and in class by instructors. Finally, it is highly relevant in that it is based on actual data collected from representative sample of American adults. Student knowledge about the importance of religion as a cause and consequence of various human behaviors will also be expanded. Exercises are self-directed and students may complete at their own pace.
Students must complete or review an SPSS tutorial and research methods to ensure progression and efficiency of learning statistical operations and tools.
Ease of Use for Both Students and Faculty
Usability of exercise is outstanding. It is clearly written, highly detailed, and logically sound in addressing research process. It sets out attainable objectives for students to accomplish. Data sets provide practical applications of statistical measures and learners are introduced to the usefulness of statistical software and significance of social research.
Students must be familiar with SPSS operating procedures.
Other Issues and Comments:
Effective teaching tool for statistics and quantitative research method courses requiring computer data analysis.
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