Predictors of quantitative skills in degree schemes at university

Autor: Partner, Alexander, Lausen, Adi, Vernitski, Alexei, Lausen, Berthold, Saker, Christopher
Rok vydání: 2022
Předmět:
DOI: 10.17605/osf.io/epc3x
Popis: This research will investigate the predictors of quantitative skills at university. The variables that we will measure will be previous education experience in relation to performance accuracy on numeracy and statistics questions, retrospective confidence judgments, mathematics anxiety, mathematics attitudes, personality. We will also measure the perceived impact of COVID-19 on education and learning. We will achieve this by recruiting first-year and foundation year undergraduate students to answer a survey which consists of multiple-choice tests and questionnaires.
Databáze: OpenAIRE