As teachers, we get why our lessons about data are important, but do our students? Let's explore ideas that help students become more engaged in lessons about data and help them find relevance in what they are studying.
Dan Greenberg taught in Colorado schools for 25 years, spending 23 years in middle school math classrooms as a classroom teacher and instructional specialist/coach. While Dan primarily taught 6th grade, he also has experience teaching 7th grade math and Advanced HS Geometry for 8th... Read More →
Workshop time will be structured by providing teachers with options for how to use the workshop time productively. The three main options teachers will be directed towards will be reworking existing problems in their own materials, creating their own progression of lessons following the same sequence from their curriculum, or developing a student driven/student centered data unit. Teachers will be able to determine their own starting ppoint and move flexibly among these outcomes. Collaboration with grade level peers and school based teams will be encouraged, but not required.
Dan Greenberg taught in Colorado schools for 25 years, spending 23 years in middle school math classrooms as a classroom teacher and instructional specialist/coach. While Dan primarily taught 6th grade, he also has experience teaching 7th grade math and Advanced HS Geometry for 8th... Read More →
*This is a cohort session. Following one morning session on Monday, July 13, this group will meet every afternoon to continue its exploration and learning.*
In the afternoon sessions participants will continue to examine various problems in applied mathematics and will explore how AI connects disparate mathematical concepts. By attempting challenging problems from various resources (e.g., the Mathematical Association of America, The Art of Problem Solving, and The American Mathematical Society), teachers will again apply a blend of traditional techniques and numerical tools to solve advanced problems; however, unlike the morning session these problems will include examples that current AI models often fail to thoroughly grasp. By discovering more of AI’s limitations, they will be reminded of the value of primary source materials, such as time-tested, multi-edition textbooks. These examples will reinforce the necessity of human oversight and boost professional confidence in identifying "hallucinations" or errors. Additionally, teachers will also be encouraged to research and solve relevant problems of interest to them and their particular course w
Mathematics Instructor, A.I. Faculty Fellow, SC Governor's School for Science and Mathematics
Dr. Stephen Kaczkowski serves as the Mathematics Department Chair and instructor at the South Carolina Governor’s School for Science and Mathematics (SC GSSM). He earned his Ph.D. in mathematics from Rensselaer Polytechnic Institute and has had the opportunity to teach a wide range... Read More →
Workshop time will be structured by providing teachers with options for how to use the workshop time productively. The three main options teachers will be directed towards will be reworking existing problems in their own materials, creating their own progression of lessons following the same sequence from their curriculum, or developing a student driven/student centered data unit. Teachers will be able to determine their own starting ppoint and move flexibly among these outcomes. Collaboration with grade level peers and school based teams will be encouraged, but not required.
Dan Greenberg taught in Colorado schools for 25 years, spending 23 years in middle school math classrooms as a classroom teacher and instructional specialist/coach. While Dan primarily taught 6th grade, he also has experience teaching 7th grade math and Advanced HS Geometry for 8th... Read More →
*This is a cohort session. Following one morning session on Monday, July 13, this group will meet every afternoon to continue its exploration and learning.*
In the afternoon sessions participants will continue to examine various problems in applied mathematics and will explore how AI connects disparate mathematical concepts. By attempting challenging problems from various resources (e.g., the Mathematical Association of America, The Art of Problem Solving, and The American Mathematical Society), teachers will again apply a blend of traditional techniques and numerical tools to solve advanced problems; however, unlike the morning session these problems will include examples that current AI models often fail to thoroughly grasp. By discovering more of AI’s limitations, they will be reminded of the value of primary source materials, such as time-tested, multi-edition textbooks. These examples will reinforce the necessity of human oversight and boost professional confidence in identifying "hallucinations" or errors. Additionally, teachers will also be encouraged to research and solve relevant problems of interest to them and their particular course w
Mathematics Instructor, A.I. Faculty Fellow, SC Governor's School for Science and Mathematics
Dr. Stephen Kaczkowski serves as the Mathematics Department Chair and instructor at the South Carolina Governor’s School for Science and Mathematics (SC GSSM). He earned his Ph.D. in mathematics from Rensselaer Polytechnic Institute and has had the opportunity to teach a wide range... Read More →
