recruiting low-income, disabled, and racially marginalized students into CTE should help diversify cluster pipelines and mitigate tracking.
Certainly a great step that we need to be taking to help get ahead of this potential crisis.
10 Matching Annotations
- Aug 2023
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www.edweek.org www.edweek.org
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Other CTE career-cluster areas have automation risks that are high: Architecture & Construction, Hospitality & Tourism, Manufacturing, and Transportation, Distribution & Logistics.
This is particular concerning for us as Canadians as this makes up a very large sector of our job market.
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a greater number of transferable skills that are less easy to automate.
The question being for how much longer? With how fast technology marches forwards I feel there's strong possibility that these skills too can be automated.
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All this matters because existing research indicates CTE participation can be stratified by race, gender, income, and rurality.
Unfortunate to see how something that could very will help uplift people of lower SES could also stand to create further difficulty.
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And if our efforts to equip these students with automation-resilient, transferable skills are not successful in these clusters, we risk the possibility of, once again, funneling disadvantaged students into low-wage, low-opportunity occupations. CTE’s “dark history” becomes its future.
Really puts more weight on the shoulders of us to equip students for the future. It'd be a shame to see so many more people get trapped in dead-end jobs with no mobility.
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Consequently, states, districts, schools, and teachers take different approaches to academic integration, and some approaches are more successful than others.
Maybe more effort should be put forward in crafting a solid, homogenous solution to this problem.
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the generative artificial intelligence behind ChatGPT can write nearly flawless computer code for a certain syntax-based statistical package commonly used among policy-researcher types, like myself. It was humbling
This is certainly one of the most interesting developments of GPT. Though it should be noted that any programmer that works within proprietary systems you'll be safe (for now).
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These skills include things like two-way communication, critical thinking, creativity, planning, management, and problem-solving. These are transferable skills, not technical skills.
I find focusing some of our resources as teachers to helping students learn these transferable skills would be very valuable in making students lives easier, as well as setting them up for more options as they shift through careers in their life.
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To do this, I merged Bureau of Labor Statistics (BLS) Occupational Employment and Wage Statistics (OEWS) data with an available automation-risk index that assigns each occupation an individual risk score.
Again, quite a dated source. I would call it's validity into question as the landscape has changed dramatically in the past decade of technological evolution.
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To begin, jobs requiring skills that are difficult to automate with available technologies are at lower risk of automation.
These articles are a bit dated now, I'm not sure if they'd hold up following the introduction of the likes of ChatGPT. The general intelligence AI's these articles pertained to were certainly nowhere near it's level.
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