Statistics – the art and science of learning from data – and data science – the ability to engage with big data in various forms – are two of the fastest growing academic fields, leaving institutes of higher education challenged to meet the demands of teaching skills needed to engage with data of increasing volume, variety and velocity. The Motivational Attitudes toward Statistics and Data Science Education Research (MASDER) group through its DUE #2013392 grant is developing six validated instruments to measure and understand students’ attitudes toward statistics and data science (SDS), instructors’ attitudes toward teaching introductory SDS courses, and the salient learning environment and pedagogical characteristics. The instruments are called the Surveys of Motivational Attitudes toward Statistics (SOMAS) or toward Data Science (SOMADS) with an additional first letter indicating whether the survey is for students (S), or instructors (I), or environment (E). Four of the six instruments, S-SOMAS/DS and I-SOMAS/DS, are guided by Expectancy-Value Theory (EVT) which is a model of motivational attitudes that describes how attitudes lead to certain behaviors and achievements. The decision to use the EVT as the theoretical framework was two-fold: (1) studies have shown that expectancies and values are predictive of achievement and (2) the EVT model is widely used in the mathematics and statistics education literature. The environment framework is guided by a model developed by the MASDER team that includes demographic and characteristic items on the students, instructors, institution, course and learning environment as well as the instructor’s pedagogy and the student-teacher relationship. In order to have maximum impact, a survey-administration website will be created so that instructors and researchers can administer surveys and receive the resulting data beyond the grant. During Year 1 and 2, pilot-versions of the S-SOMAS were administered to 3,134 students (Pilot-1, n=588, Pilot-2, n=2546) and has 72 items measuring 8 constructs: Expectancy, Academic Self-Concept, Goal Orientation, Perception of Difficulty, Costs, Utility Value, Interest/Enjoyment Value, and Attainment Value. Pilot-1, I-SOMAS was administered to over 200 instructors, and Pilot-2 will be administered jointly with the S-SOMAS Fall 2022. The development process includes individual members writing construct items, team review and rewrites of items before and after Subject Matter Experts review the items. As needed, the team uses input from focus groups of students or instructors to inform our item development as well. Since DS is an emerging field, several summer workshops were held with DS instructors and industry people, and these experts developed student models and helped the team write items for the S-, I-, and E-SOMADS. Use of these instruments will lead to better instruction and improved student attitudes toward SDS as well as evidence-based training and professional development material. The instruments and data sets will be freely available for other researchers and teachers to use. This will impact millions of students across the US who are taught SDS annually and lead to improved data literacy and a more competitive workforce with the skills needed to engage with data in its many forms.
Alana Unfried, California State University, Monterey Bay, CA; April Kerby-Helm, Winona State University, Winona, MN; Douglas Whitaker, Mount Saint Vincent University, Halifax, Nova Scotia, Canada; Michael Posner, Villanova University, PA; Leyla Batakci, Elizabethtown College, PA; Wendine Bolon, RSM US, Davenport, IA