Human learning is a complex, sometimes mysterious process. Most of us have had experiences where we have struggled to learn something new, but also times when we’ve picked something up nearly effortlessly.
What if a fusion of computer science and psychology could help us understand more about how people learn, making it possible to design ideal lessons?
That long-range goal is moving toward reality thanks to an effort led by professors in the University of Wisconsin-Madison departments of computer sciences, psychology and educational psychology. Their collaborative research aims to break new ground in what computer scientist Jerry Zhu calls “machine teaching” — a twist on the more familiar concept of machine learning.
“My hope is that machine teaching has an impact on the educational world. It’s quite different from how people usually think about education,” says Zhu. “It will give us optimal, personalized lessons for real, human students.”
Machine learning is a well-established subfield of computer science in which experts develop mathematical tools to help computers learn from data and detect patterns. The machine learner (the computer) is like a student. The goal of machine learning is to develop models that will prove useful in the future when dealing with large, often unwieldly data sets. Practical tasks like speech recognition are aided by machine learning.
Machine teaching turns this concept on its ear. Rather than dealing with pools of data and not knowing at the outset what patterns might be revealed through analysis, the researcher in a machine teaching arrangement already knows what knowledge he or she wants to impress upon the learner.
Machine teaching uses sophisticated mathematics to allow researchers to model actual human students and devise the best possible lessons for teaching them. While the definition of “best” in a particular setting is up to the teacher, one example could be identifying the smallest number of exercises needed for a particular student to grasp a concept. Or, as Zhu puts it, “Can five really good questions teach the material, rather than 20?”
While this work is still in its early stages, it has immense potential to impact education.
Timothy T. Rogers, a professor of cognitive psychology at UW-Madison and one of Zhu’s collaborators, explains how computer science and psychology come together.
“In order for the machine teaching approach to work, it needs a good model of how the learner behaves — that is, how the learner’s behavior changes with different kinds of learning or practice experiences,” Rogers says. “Also, the model needs to be computational; it has to be able to make concrete, quantitative predictions about the learner’s behavior.”
The Latest on: Machine teaching
via Google News
The Latest on: Machine teaching
- Microsoft Research: Machine Teaching, Optical Computing, Machine-Human Interaction, and Moreon November 13, 2019 at 9:58 am
She focused on what she called major paradigm shifts—artificial intelligence, computing power, In various talks, researchers drilled down into research into "machine teaching," optical computing, and ...
- Developing efficient machine teaching, technologieson July 17, 2019 at 5:00 am
He predicts that the field of machine teaching will advance further to make this reinforcement learning process more efficient. “That is why we acquired Bonsai last year, a startup established in the ...
- Microsoft Research explores ‘Machine Teaching’on July 12, 2019 at 5:00 pm
Microsoft announced it has formed the Machine Teaching Group, a research project to advance “Machine Teaching.” Machine Teaching is described by Microsoft as the next evolution of machine learning (ML ...
- Machine teaching: How people's expertise makes AI even more powerfulon April 24, 2019 at 4:16 am
But as the desire to use AI for more scenarios has grown, Microsoft scientists and product developers have pioneered a complementary approach called machine teaching. This relies on people's expertise ...
- “Machine teaching” is a thing, and Microsoft wants to own iton April 23, 2019 at 6:01 am
Microsoft is rallying behind a new buzzword as it tries to sell businesses on artificial intelligence. It’s called “machine teaching,” and it’s loosely defined by Microsoft as a set of tools that ...
- Microsoft wants to shortcut AI’s usefulness with ‘machine teaching’on March 26, 2019 at 1:32 pm
REDMOND, Wash. – Businesses around the world have already seen the impact of AI technology in digital services such as chatbots and virtual assistants. But how could this technology be implemented to ...
- Machine Teaching Will Drive Crowdsourced Cognition into the AI Pipelineon June 24, 2018 at 5:00 pm
This is the essence of an emerging feature-engineering approach known as “machine teaching.” As discussed in this Microsoft Research paper and this heavy-going academic research paper, this relies on ...
- Machines Teaching Each Other Could Be the Biggest Exponential Trend in AIon January 21, 2018 at 8:02 am
“But this one is potentially the biggest.” According to Lipson, what we might call “machine teaching”—when devices communicate gained knowledge to one another—is a radical step up in the speed at ...
- Machine Teaching A New Paradigm for Building Machine Learning Systemson September 23, 2017 at 5:00 pm
and fast discipline which they called Machine Teaching (MT). This paper laid out the position of machine teaching discipline and articulated the fundamental machine teaching principles. The supply-and ...
- AI Explainability: Machine Teaching & Recomposabilityon September 17, 2017 at 5:00 pm
Integrating both together results in a new technique — Machine Teaching. Machine Teaching is used to build a conceptual hierarchy. It’s a fuzzy hierarchy; it’s not like old expert systems with very ...
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