Technique 2: Right is Right

"Right is Right" means that partial answers aren't good enough: only a 100% correct answer is the correct answer. As the author says,

Many teachers respond to almost-correct answers their students give in class by rounding up. That is, they'll affirm the student's answer and repeat it, adding some detail of their own to make it fully correct even though the student didn't provide (and may not recognize) the differentiating factor. ... When answers are almost correct, it's important to tell students that they're almost there, that you like what they've done so far, that they're closing in on the right answer [...]. In holding out for [R]ight, you set the expectation that the questions you ask and their answers truly matter.

The author suggests 4 techniques for holding out for the 100% right answer:

1. Praise what the student said, but ask for more. E.g., "Can you develop that further?", or "I like where you're going. Can you take us the rest of the way?"

2. Make sure the student answers the actual question you asked, not some other question. E.g., sometimes students will give an example when they are asked to define something. That's good, but it isn't an answer to the actual question.

3. Similarly, make sure the student doesn't get ahead of you, and answer a subsequent question. Sometimes you want to lead students down a path, but some students want to jump right to the end of the path. Don't allow that.

4. Use technical vocabulary, and insist students learn to use it, too.


My response:

I like this a lot, but I'm really bad about fixing student's answers myself. I need to work on getting the students to give the correct answers. I find it hard to formulate good questions to prompt a student to get to the point where they give the 100% correct answer.

Regarding the "Use Technical Vocabulary" point: This is so applicable for teaching computer science. I've been using this technique in FIT and it really works. I insist that students answer questions using the technical terms we've defined earlier in the lecture: "algorithm", "volatile memory", etc. I feel that by using the technical terms, they get a better feeling for their meaning.