Escuela and AI

As I high school freshman, I knew that I should choose to take Spanish and not French.  However, I was shy and extremely hesitant to speak aloud in class in English, never mind trying to participate in a second language. My high school’s Spanish teacher was known for a no-nonsense classroom that would not have recognized this challenge for me, so I caved to my fear and took French.  In the twenty-something years since then, I have often regretted being unable to speak Spanish.  I’ve picked up enough to get by in a number of situations, but I still wished I had made a different choice all those years ago.

Enter Babbel.  I’ve used language apps before to pick up small amounts of Chinese and Korean but had to depend on boarding students at the school where I taught to let me know if my pronunciation was passable (which was only rarely).  Babbel is the first language app I have used that used voice recognition to provide feedback on spoken language.  The first time I tried this part of the app, I felt self-conscious – a throwback to those days of high school language labs when it seemed that the person in the next cubicle could hear my terrible French and that the teacher would break in at any moment to tell me yet again that my r’s were totally wrong.  However, once I got over the nervousness of speaking a language aloud even though only an AI and my cat could hear me, it was really helpful and affirming to have the instant feedback of knowing whether I was saying a new word correctly during these app-based Spanish lessons.  It’s my first real example as a learner of getting formative feedback from a machine and being able to act on it immediately.

Back in 2013, while a graduate student, attended a fascinating workshop on several new educational software developments.  One software had the same story available in different reading levels and allowed students to move up or down based on not only comprehension, but also choice.  A student could opt to try a more challenging version and tap new words for definitions.  Or if they were having trouble answering comprehension questions, move down a level.  Another, had machine-learning-based tools that could diagnose misunderstanding of math facts and provide different feedback to students based on that misunderstanding.  A student who got the incorrect answer on a subtraction problem would not just be shown the correct answer, but based on their answer given would be given a specific explanation – for example, the importance of order in subtraction if she just subtracted the smaller number from the larger one regardless of the order given in the problem.  This week for MSTU 4029, we read about an experiment with writing software for students that enforced a growth mindset,  which increased students’ persistence at a math game when they struggled with challenging problems.  This is a powerful combination of cognitive science and software, not to mention a far cry from the Apple IIe Number Munchers games that were the hallmark of my own elementary school ed-tech experience.

Our guest speaker in class this week is Andrew Gardner from BrainPop.  Having taught computer programming and spent the better part of my career in education technology, I’m really looking forward to hearing how companies are bringing together what we understand about how people learn, with AI, with good programming.  I’ll also be interested to hear how companies that write the software envision teachers using it.  A game that diagnoses misconceptions in math can be an incredibly powerful tool for teachers, but only if they have the time to analyze the data that it generates and work with individual students or small groups to address their specific learning needs if just playing the game doesn’t do the trick. Do those who create software see themselves as partners with human teachers or providers of an alternative to the traditional classroom?  I deeply hope it is the former, especially since tech companies carry so much weight in our society.

I’ll share any items of interest on this topic here after the next class.  In the meantime, I’m tempted to boot up that old copy of Oregon Train I have and see if dysentery strikes again…



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