Masdering attitude research in statistics and data science education: Instruments for measuring students, instructors, and the learning environment
Year: 2024
Type: conference-paper
Abstract: Research about students’ affective outcomes (such as attitudes) in statistics courses has proliferated over the past three decades, but questions about the impact of instructors and the learning environment on student attitudes remain open. In data science education, research about students’ attitudes is nascent. In many statistics education studies, developing items about individual and course characteristics receives less attention than developing other aspects of the study. Without a reliable way to measure characteristics of individuals and courses we cannot identify barriers to student success in statistics and data science–much less dismantle those barriers. This paper describes the development process that the Motivational Attitudes in Statistics and Data Science Education Research (MASDER) team has used for items measuring individual characteristics to be used across the family of instruments. Further work – including some results from a large data collection in the United States – will be presented at the conference.
Source: IASE Roundtable Conference
Language: English
Subfield: Statistics and Probability
Field: Mathematics
Domain: Physical Sciences
SDG: Quality education
Open Access status: bronze
OpenAlex ID: W4407572063