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New Online Course: Secondary Analysis of Workforce Education & Development Data

Online course announcement, WF ED 571I, spring 2010, David Passmore

The aim of this course is to develop knowledge and skill necessary for organizing, analyzing, and reporting secondary data. This course will be offered entirely at a distance. Students do not need to travel to the University Park Campus to complete this course.

WF ED 597I (Schedule Number 465466), Secondary Analysis of Workforce Education & Development Data, is delivered online entirely, with weekly synchronous class meetings occurring on Monday evenings at a distance supported through Adobe Connect and using general course management and support though ANGEL, Penn State’s online course management system.

Secondary data are data that already were collected by someone else and are re–used for purposes other than those that formed the aim of the primary data collection. Common sources of secondary data for social science and education include censuses, surveys, organizational records and data collected through quantitative methodologies or qualitative research. Secondary data analysis saves time that otherwise would be spent collecting data and provides larger and higher-quality databases than would be feasible for any individual researcher to collect on their own. Secondary data can also be helpful in the research design of subsequent primary research and can provide a baseline with which the collected primary data results can be compared. Over the previous 30 years, I have advised 27 Penn State students who completed theses and research papers using secondary data.

Competency development activities in this course include:
* Reviewing opportunities and methods for secondary data analysis, with a focus on the appropriateness of quantitative aproaches to secondary analysis;
* Configuring and using remotely Hammer, Penn State’s small cluster computing system;
* Uploading data to and downloading output from Hammer;
* Selecting and extracting data and Statistical Analysis System (SAS) control cards from free, publicly–available microdata bases using the National Longtitudinal Surveys (NLS; see using ) as an example;
* Calculating point and interval estimates of statistical parameters and performing tests of statistical hypotheses related to level, variation, and relationship among variables derived from secondary data, with particular attention paid to proper applications of sampling weights, design effects, and missing data treatments;
* Consulting with other researchers to improve research products collaboratively;
* Creating a report of research using secondary data for publication by Penn State’s Institute for Research in Training & Development; and
* Submitting a manuscript based on the IRTD report for publication in a refereed journal.
Although this course promotes secondary analysis of data that will contribute to research in economic and workforce development, students may focus on the development of their secondary data analysis skills on other related topics with any microdata set that interests them.

Possession of advanced statistical skills is not a prerequisite for this course--just a desire to make practical applications of the fundamental knowledge and skills that were the expected outcomes of any introductory statistics course: specification of variables; distributions; distribution theory; estimation; hypothesis testing; and understanding of concepts such as “statistic,” “parameter,” “population,” and “sample.” The analysis techniques that students actually will apply in this course will depend on the types of research questions they will answer with secondary data.

Although the computing conducted in this course might force many students to enter new waters (e.g., high performance computing, UNIX systems, remote computing, secure file transfers), the range of computing tasks required in this course is narrow and the completion of these tasks are not likely to be complex. Instruction in the computing that is required to complete this course is provided.

SAS is the primary data analysis tool that will be emphasized in this course. Students enrolling in this course either without any background in SAS or requiring a SAS refresher will find a book, The little SAS book: A primer, helpful. The third edition of this book is available to the Penn State community as a free electronic resource provided at through the Access Pennsylvania Database project. Students do not need to possess SAS skills prior to enrolling in this course. Instruction in use of SAS is provided in this course.