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Students in special education face daily academic challenges in the classroom. For example, a student may have difficulty reading and comprehending a text due to visual impairment or dyslexia.
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Students in special education face daily academic challenges in the classroom. For example, a student may have difficulty reading and comprehending a text due to visual impairment or dyslexia.
The goal of this ETP is to have students practice “Active Listening Skills.” It is part of a unit meant to train students in mentorship skills and with the goal of eventually beginning mentoring younger students to increase participation in STEM classes.
At Facebook Reality Labs, I worked on documenting career expectations for certain roles within Devices. I helped document role expectations as well as help document certain roles by splitting them into Senior and Junior equivalents.
Students are often asked to engage in the practice of code switching both inside and outside the class. Communication with one another is almost second nature to students as they engage in conversation across various mediums and platforms.
Students with special education services, particularly students with learning disabilities, need more opportunities to practice and to develop their soft skills (adaptability, active listening, communication, creative thinking, teamwork, and time management).
The purpose of this ETP is to share with my students the knowledge I have gained during this fellowship on climate action that is being implemented by corporate America to address the climate change crisis.
In this SEMI Foundation lesson plan, students will explore the advantages and challenges of transitioning to electric vehicles by comparing emissions, costs, and incentives through collecting data, graphing data, and writing equations.
A Day in the Life of a Data Scientist is a short term project appropriate for any advisory space that has a college and career focus. Students will learn about non-traditional career paths such as: data scientists, machine learning engineers, program managers, and executive positions.
This lesson series asks students to use a machine learning specialization to explore multiple case studies between various predictive models and analyze an intelligent application that makes predictions from data.
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