AI in the Classroom

Biases

Machine learning bias, also known as algorithmic bias, is when a system creates unfair outcomes due to assumptions made by the machine learning process (Gillis). These can include algorithm, sample, prejudice, measurement, exclusion, selection, and recall biases. These hidden biases can result in misleading information, misrepresentation, and overall a false perception. 

It’s important to be aware of the biases before using AI. Instead of just accepting what the computer says, we have to be critical of the AI recommendations and sources that we get our information or data from. After all, AI is just a tool, it should not be abused by allowing it to control our thoughts and ideas. Another way to rectify AI is by looking at an AI’s recommendations in regards to race, gender, and age to check for discrimination. Knowing this information and staying alert for red flags such as these, can help determine what AI tools Before introducing AI tools in my classroom, I like to try it out myself by learning how to navigate it, seeing what the expectations are, and deciding how to implement it best. When sharing it with my students, I share the expectations of the AI tool with them, how to use it, and what the objective is. To continually use an AI tool in my classroom, it’s important for me, as a teacher, and my students to see the ways that it will benefit and represent the diverse learners in my classroom. 

TCE Concepts

• Curriculum is co-constructed
  • In order for AI to be executed well in the classroom, teachers have to have a good understanding of it – like anything they teach. It is important to be familiar with the tools that AI can provide that students can use. It’s important for students to be aware of the limits that they can reach while using AI and believing in their capabilities with it. 
• Curriculum is more than standards, textbooks, or courses of study
  • Although AI can assist in meeting standards in the classroom, it can easily go beyond what normal instruction can do by meeting the specific needs of diverse learners and providing tools that can help students take their learning beyond the classroom. With AI meeting these needs, I believe students can feel more successful while in the learning environment which will help give them the confidence and tools that will help them be successful outside of the classroom.

Pros and Cons of AI

Pros: 

• Personalized learning 
• Can provide feedback to teachers, students, and parents
• Can save time and energy for teachers
• Helpful in creating engaging lessons 

Cons 

• Bias
• Plagiarism 
• Possible decrease in social learning

Personalized Learning Through AI

My students have been using Dreambox Math since the beginning of the year as it is a district approved personalized learning app. I have never received training in Dreambox, but I knew of some of its features – including assigning personalized lessons based on objectives I have in our current unit of study and state standards that need to be met throughout the course of the school year. The past few weeks in math, we have been learning about place value. I assigned a lesson on place value for my students to complete when they got onto their chromebooks. With them being in first grade and not knowing how to access assignments on Dreambox, I had to teach them how to do this part. My students seemed to enjoy the assignments and I also really liked knowing that they were working on place value all at once. As I checked in with students around the room, I could see the differentiation among the different learners based on who needed more intervention and who needed enrichment in this area of place value. After my students logged off, I was later able to look at which students were proficient in that area and which still needed more help. I will definitely be assigning more lessons in Dreambox moving forward. It’s a great way to fill in the gaps and provide what each of my learners needs as a supplement to instruction. 

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