Predicting STEM educational achievement and career pathways from spatial ability and non-cognitive factors
Lead Research Organisation:
Queen Mary University of London
Department Name: Sch of Biological and Chemical Sciences
Abstract
Increasing STEM engagement has been declared a priority
by many governments due to its association with positive
individual outcomes and greater national prosperity. While
there has been an abundance of research elucidating the
aetiology of individual differences in educational
achievement more broadly, there has been less focus on
predicting STEM achievement and career choices
specifically. To that end, recent work has shown that
variation in non-cognitive factors such as attitudes and
emotions are related to variation in maths achievement,
while spatial ability (a domain of general cognitive ability
related to STEM achievement) appears to be
distinguishable from general cognitive ability, both
phenotypically and genetically. Building on this knowledge,
this project will utilize a novel and comprehensive battery
of spatial ability tests alongside measures of non-cognitive
factors to predict STEM achievement and career choice in a
developmental context. By increasing our understanding of
the way the environment and genetics influence individual
differences in STEM outcomes, this research can potentially
inform public policy with regards to increasing STEM
engagement and reducing disparities.
by many governments due to its association with positive
individual outcomes and greater national prosperity. While
there has been an abundance of research elucidating the
aetiology of individual differences in educational
achievement more broadly, there has been less focus on
predicting STEM achievement and career choices
specifically. To that end, recent work has shown that
variation in non-cognitive factors such as attitudes and
emotions are related to variation in maths achievement,
while spatial ability (a domain of general cognitive ability
related to STEM achievement) appears to be
distinguishable from general cognitive ability, both
phenotypically and genetically. Building on this knowledge,
this project will utilize a novel and comprehensive battery
of spatial ability tests alongside measures of non-cognitive
factors to predict STEM achievement and career choice in a
developmental context. By increasing our understanding of
the way the environment and genetics influence individual
differences in STEM outcomes, this research can potentially
inform public policy with regards to increasing STEM
engagement and reducing disparities.
People |
ORCID iD |
Ziye Wang (Student) |
Studentship Projects
Project Reference | Relationship | Related To | Start | End | Student Name |
---|---|---|---|---|---|
ES/P000703/1 | 01/10/2017 | 30/09/2027 | |||
2613396 | Studentship | ES/P000703/1 | 01/10/2021 | 30/09/2024 | Ziye Wang |