Generative Instruction with Linda Berberich, PhD.
Download MP3In this episode of Transformative Principal, Jethro Jones interviews Linda Berberich, a behavioral scientist, about her extensive experience in machine learning before it became a buzzword. They discuss the practical applications of artificial intelligence in education, the pros and cons of using technology like GPT models in learning environments, and the importance of integrating technology thoughtfully based on the specific needs and culture of a school.
- AI is such a buzzword but it’s really just machine learning
- Built many solutions to virtual learning
- What technology is really good at is computing
- Cycle motor learning - good form
- Too much memorizing
- Far transfer vs. Near-transfer (Ruth Clark) and organic vs. mechanistic skills
- Standardizable tasks are mechanistic. The way you perform is how you train.
- Complex and Simple tasks.
- Skewed responses.
- How to know when to use a computer (AI, Machine Learning) for learning.
- Attempts to make the machine more empathetic
- Jethro’s example of writing using two different GPTs to write
- Narrow the field and expand the field.
- Grades have a massive impact on peoples’ lives, so we can’t ditch that.
- Ideas around what school looks like.
- Use the time for kids to be together pro-socially.
- Generative Instruction
- Teachers know this stuff!
- Using Technology to get kids interested in
- Don’t be afraid of technology or of letting kids lead.
About Linda Berberich, PhD.
Behavioral scientist specializing in innovative, impactful, and immersive learning and intelligent, intuitive technology product design. Extensive background in data analysis, technical training, behavior analysis, learning science, neuroscience, behavior-based performance improvement, and sport psychology/performance enhancement.
Passionate lifelong learner who is constantly up-skilling, most recently in the areas of:
solopreneurship, technology-based networking, writing business cases for corporate-wide initiatives, design thinking, agile/scrum methodology, data science, deep learning, machine learning, and other areas of artificial intelligence, particularly as they intersect with human learning and performance.
Follow her newsletter at Linda Be Learning.
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