Jumping back in in an effort to organize my thoughts, especially around Artificial Intelligence. Future posts will discuss some background, tools, and perils but I thought we’d start with a focus on the promise. Now promises don’t always come true, but I do think there are opportunities here. Let’s start with using AI as an extension of differentiation, assuming a support role in the classroom like an aide.
Blended learning and software offered the first attempts to move from a teacher-driven approach with curriculum and differentiation. There was certainly some forward progress using assessment driven learning programs/algorithms – think Duolingo – I fail a lesson on present tense verbs with irregular endings, the program assigns more practice with those verbs. As a teacher, I saw great growth in this area, especially within the context of remedial skills in math and reading that teachers couldn’t devote instructional minutes to during class time. Likewise, my own son has benefited from the challenges of being offered higher level math concepts within a blended learning software program.
In many cases, Artificial Intelligence is growing out of this success, to provide even more personalized support and doing so in a more “student-friendly” way. Having a chatbot on hand to support students with questions, concerns, misconceptions, or differentiation in a one:one, real-time and conversational manner is a tremendous boon. There is some evidence that this works long-term, but may (like all tutoring) create a crutch effect.
Does the classroom of the near future feature a master teacher utilizing AI as instructional assistants? As voice modes develop (and even video), the ease of use for students, especially those with disabilities, will increase greatly and enable these students to have access to a competent and knowledgeable aide at their fingertips.
This might look similar to the old “ask three before me” rule that I used in group or pair work. It would be great if teachers could then monitor these interactions, receive a report with the most common questions / answers, and then use that data to refine instruction moving forward. A similar flagging system could indicate where teachers would need to meet with students where a chatbot’s support was insufficient, not successful, or too limited to support the student.
These features are already largely available already and could make a difference in large(r) classrooms just as practice books and blended learning software has done for decades.
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