About Dr. Loggins (she/her)
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And, while this is a reply from Cody Vangosen this semester on a different presentation, it’s an ideal presentation of what I’d love to see in your presentation replies:
Great job on your presentation. After viewing your presentation I feel stratified random sampling could prove to be an effective research strategy for exploring my interests in the effects of AI technologies being incorporated in K-12 classrooms. Examining several different school districts in such a manner could prove to provide a valuable dataset to possibly further examine the effects of AI on learning. This could allow for a more random sampling of students of various grade levels from schools with different demographics, thereby creating a sample that could possibly be more representative of more K-12 schools as a whole.
Dan Grimes also had a great presentation reply:
I mentioned in my post how bias had altered a survey I had done in 2020 as part of a business plan. I considered it to be a little unreliable as I didn’t consider any population diversity as part of my sampling. However, after understanding nonprobability sampling a bit more I now realize a new implementation that can be done. By shifting the focus from a whole to the same targeted demographic I took the sample, I can get similar numbers to how the sample was pulled. This will take a bit of extra time to figure out, but in the end the results will be more accurate and reliable to the original sample.