EAMMi2: The Last Teaching Data Set Any Instructor Will Ever Need
Jon Grahe is a professor of psychology at Pacific Lutheran University.
With help from an APS Teaching Fund Small Grant, I worked with a team of 35 colleagues to administer the project Emerging Adulthood Measured at Multiple Institutions 2: The Next Generation (EAMMi2). The EAMMi2 was designed to benefit science through the generation of survey data to answer important research questions related to emerging adulthood — such as identifying psychometric properties common to emerging adulthood; examining the relationship between disability identity and well-being; and probing the relationships between political events, stress, and health. Because many of the EAMMi2 measures were used in previous research, there are still many other replication and novel questions that could be pursued.
A secondary purpose of the EAMMi2 was to generate a data set that instructors could use to teach statistics and research methods for years to come. Now that the data set is publicly available and the first round of manuscripts are working through the publication process, we wish to invite faculty and students to use our data for learning or future scientific pursuits. We hope instructors will (a) use this data set for their courses, (b) challenge their students to learn with real data, and (c) encourage others to submit more manuscripts answering untapped questions.
From March–December 2016, contributors from 32 locations recruited more than 4,200 respondents (N = 3134 in the cleaned data set). In addition to common demographics, the survey included scales measuring emerging adulthood, preferences in the US presidential election, and 15 other constructs (e.g., need to belong, mindfulness, subjective well-being, disability identity, narcissism, and self-efficacy.)
Data from this project can be used to explore any statistics lesson from the basic introductory level to the advanced graduate level. Further, because EAMMi2 includes so many different scales and measures, instructors can assign homework using unique variables. Whether students practice cleaning and manipulating data or testing hypotheses and writing research papers, they can do so while exploring actual data. Furthermore, students can retest existing questions or explore novel questions. Advanced students might present their work at conferences or submit their work for publication.
Come visit the EAMMi2 project page! While no one needs permission to access the data or to use it, we do ask that potential authors check with us to avoid unintentional redundancy in manuscripts for submission since there are currently a number under review.
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