Denominators always intrigue me in all data analyses (my main job is data analytics based consulting). In your examples, I wish we could know the *reason* behind the % that say scientists are "welcoming/not welcoming". If only we could know whether it was "because of what you've assumed going into interactions/were told this was the case" or "because of blatant examples you couldn't ignore". I know...so subjective and hard for even the individual to honestly discern.
But this would change the approach to the solution.
You would solve presuppositions by not telling so many black individuals that this is the truth of the world. You would solve the issue of blatant examples by educating the STEM world on how to not continue in this way. Two very different approaches.
Similarly, of the lower representation of non-white groups in STEM, I would love to somehow know "% that were 1. interested and 2. attempted to enter STEM and 3. were not able to do so" (for each ethnicity). Forget the actual % compared to US population...that may confuse the narrowing of the analytics funnel. I would consider it a promising sign if that conversion rate was currently on par with for white or asian populations. Then our focus could appropriately shift on either exposing INTEREST in STEM and then later on we could see why they weren't SUCCEEDING in obtaining careers in STEM. By jumping to the missing population of step 3 as proof, we may continue to be disappointed and continue to hang in neutral.
TL;DR - we may be missing a middle portion of the analytics funnel to know where it's dropping off between population>interest>application>accomplishment and that may be key for where to put resources. Perhaps NSBE is focusing on the issue in this way...but the highlighted stats seem to not suggest that.
Thanks Clifton (for all of your continued studies and publications). Unfortunately the very last sentence alludes to what I was hoping there was a whole study on. Quote: "To increase STEM representation in high school, college and the workforce, efforts by educators and policymakers to support talented students of color may need to begin by the elementary grades."
It seems that the "may need to" phrase is what I'm referring to. This should be looked into and is likely to change to "will need to" if studied thoroughly. Based on other findings I've read from organizations like Girls Who Code and similar organizations, these narrowing-of-the-funnel of eventual careers starts early and it is a bit misleading for any article title to focus on step 3 of this funnel and jump to "X race is underrepresented in Y field".
If found to be true, I look forward to seeing a headline such as "a lack of early interest in STEM leads some groups to be much less likely to pursue STEM later in life...let's fix this" in the future. I do believe nuanced steps like this will lead to the long term success of more marginalized groups in areas such as STEM.
This study is a baby step in the right direction, but I agree with your point that a more definitive prescription is needed. To be fair, the authors acknowledged that while their analysis explained much of the Hispanic-White gap it wasn't as good at determining the factors behind the Black-White gap. More work is needed.
Are there any studies about the success of black STEM students after graduation from HBCUs, State Universities vs more elite colleges? I wonder if a "funnel" is or could be created by older black alum in STEM positions. I don't know much about STEM education, but are there work/study programs(5-6 years) where students can work in STW/STEM jobs while studying? This may help them to be in the real world part of the time. Internships are great, but it may be too late by then. Voc. HS' do something similar for the "trades"; what about STEM at that level?
Sorry, but I didn't learn much from this study. (Granted, I only skimmed it.)
Or, rather, I thought it was already *known* that parents having sufficient time and a lotta books and that kind-a stuff effected early engagement in education. What insights did I miss?
Denominators always intrigue me in all data analyses (my main job is data analytics based consulting). In your examples, I wish we could know the *reason* behind the % that say scientists are "welcoming/not welcoming". If only we could know whether it was "because of what you've assumed going into interactions/were told this was the case" or "because of blatant examples you couldn't ignore". I know...so subjective and hard for even the individual to honestly discern.
But this would change the approach to the solution.
You would solve presuppositions by not telling so many black individuals that this is the truth of the world. You would solve the issue of blatant examples by educating the STEM world on how to not continue in this way. Two very different approaches.
Similarly, of the lower representation of non-white groups in STEM, I would love to somehow know "% that were 1. interested and 2. attempted to enter STEM and 3. were not able to do so" (for each ethnicity). Forget the actual % compared to US population...that may confuse the narrowing of the analytics funnel. I would consider it a promising sign if that conversion rate was currently on par with for white or asian populations. Then our focus could appropriately shift on either exposing INTEREST in STEM and then later on we could see why they weren't SUCCEEDING in obtaining careers in STEM. By jumping to the missing population of step 3 as proof, we may continue to be disappointed and continue to hang in neutral.
TL;DR - we may be missing a middle portion of the analytics funnel to know where it's dropping off between population>interest>application>accomplishment and that may be key for where to put resources. Perhaps NSBE is focusing on the issue in this way...but the highlighted stats seem to not suggest that.
Thanks for your comment. I've seen new research that attempts to address some of the important points you're making. Use this link to see an overview:
https://theconversation.com/disparities-in-advanced-math-and-science-skills-begin-by-kindergarten-191990
Thanks Clifton (for all of your continued studies and publications). Unfortunately the very last sentence alludes to what I was hoping there was a whole study on. Quote: "To increase STEM representation in high school, college and the workforce, efforts by educators and policymakers to support talented students of color may need to begin by the elementary grades."
It seems that the "may need to" phrase is what I'm referring to. This should be looked into and is likely to change to "will need to" if studied thoroughly. Based on other findings I've read from organizations like Girls Who Code and similar organizations, these narrowing-of-the-funnel of eventual careers starts early and it is a bit misleading for any article title to focus on step 3 of this funnel and jump to "X race is underrepresented in Y field".
If found to be true, I look forward to seeing a headline such as "a lack of early interest in STEM leads some groups to be much less likely to pursue STEM later in life...let's fix this" in the future. I do believe nuanced steps like this will lead to the long term success of more marginalized groups in areas such as STEM.
This study is a baby step in the right direction, but I agree with your point that a more definitive prescription is needed. To be fair, the authors acknowledged that while their analysis explained much of the Hispanic-White gap it wasn't as good at determining the factors behind the Black-White gap. More work is needed.
Are there any studies about the success of black STEM students after graduation from HBCUs, State Universities vs more elite colleges? I wonder if a "funnel" is or could be created by older black alum in STEM positions. I don't know much about STEM education, but are there work/study programs(5-6 years) where students can work in STW/STEM jobs while studying? This may help them to be in the real world part of the time. Internships are great, but it may be too late by then. Voc. HS' do something similar for the "trades"; what about STEM at that level?
Sorry, but I didn't learn much from this study. (Granted, I only skimmed it.)
Or, rather, I thought it was already *known* that parents having sufficient time and a lotta books and that kind-a stuff effected early engagement in education. What insights did I miss?