Type I versus Type II Errors
May 23rd, 2007 by Frank LaBanca, Ed.D.

I’ve read numerous definitions of Type I versus Type II errors. Written by statisticians, these definitions are convoluted and hard to understand. Type I errors are false positives and Type II errors are false negatives. Listen to this gobbly gook from an Applied Statistics text:

Type I error is when we reject a true null hypothesis. Type II error is when we do not reject a false null hypothesis. Although we cannot eliminate the possibility of making an error in hypothesis testing, we can control the criterion for rejecting the null hypothesis . . .

I’ve struggled with what this actually means and how to explain it well until a recent science fair experience.

At the fair, on the first day of judging, the scientific posters are evaluated without the students present. The top 25% are identified and these students are called back for finals. This year, eight of my ten students were called for finals. One of the eight was called just for a category award. That basically left three in the lower 75%. One was not surprising to me. His project “a” was weak, poorly conceived, and poorly presented. The other two, however, were a bit surprising.

As I was traveling home from a graduate stats review I was conducting, I had a student “b” call me very upset about her results in the science fair. She did not make finals. I was surprised, because she was a finalist the previous year and her project this year was far stronger. She had, only the week before, won first place at a different science symposium for her work. The other student, “g,” who had not made finals also placed first in her category at yet a third event. Student g failed to heed my advice about her poster – I informed her that it was convoluted and difficult to follow. Without her present, the judges might have a hard time evaluating it. And so it goes – that project was not selected as a fair finalist. However, that student was named a finalist for a special award category. Unfortunately b’s ride ended at that phone call. However, g ’s trip continued on. She wound up winning many special awards, even though she was not recognized as a finalist:

Xerox Computer Science Awards – Medallist
United Technologies Corporation Award
Quinnipiac University ScholarshipConnecticut Academy for Education DeRocco Award for Excellence
IEEE, Connecticut Section Award
Meyerand Young Woman Scientist Award
The Howard Lessoff Award for Excellence

As g received these awards, I thought to myself. Surely a mistake was made in the preliminary judging. I know why it was made – the judges couldn’t get past the poster and see the great science that was there. And then it hit me . . .

This is a Type II error. B and g were false negatives. They should have been there but they weren’t. This was a pretty bad error, because there was no way to correct it. If a project was selected in the prelims but wasn’t good, it would have made it to finals, but would have been weeded out there – the false positive. Not as bad here, because a correction can take place at a later time.

The false positive – the student who was recognized, but should not have been.
The false negative – the student who had the great project, but wasn’t recognized.

Big Idea #2: Levels of Research Excellence
May 23rd, 2007 by Frank LaBanca, Ed.D.

I have recently been considering what makes a great science research project great. There certainly have been some common characteristics – long term involvement, metacognitively recognizing that the problem is significant to an authentic audience, working with an experienced and well-versed mentor. However, after having a talk with Ed Schmidt, science research director at Brewster High School, I realized that there is a very critical component which differentiates a good project from a great project.

A good project often will observe and analyze phenomena. However a great project offers a novel solution to a problem.

This is a very important distinction. I have had absolutely wonderful projects that have been observations of phenomenon – Igor’s mummichog study, Drew’s mummichog study, Aman & Caitlin’s ribbed mussel studies – many of the wonderful environmental projects I have done have focused on observing phenomena and reporting environmental impact. These have been very successful, however, the trick to take it to the next level is the novel solution aspect – Dayton’s coliform detector, Rebecca’s neural nets, Sara’s microwave strategy, Wesley’s fuel cell. These projects have an important distinction. Their contribution is not only reporting authentic information, but also includes a potential method or solution to evaluating or fixing the problem.
The challenge, therefore, is to get students thinking about new challenges and new solutions. Ones that are original, unique, and valuable.

Differentiated Swim Lessons
May 7th, 2007 by Frank LaBanca, Ed.D.
I had the pleasure of taking my daughters to their first swim lessons today. Anna (4 [almost 5]) and Maggie (3) have been so excited for the past several days in anticipation. We got to the class early and we ran for a bit outside of the pool area.
When it was time to start, the instructor called the class over “Pikes?” To my surprise, only three students. That seems like some quality one-on-one. I’m quick to notice that Anna is older than the other two students. As I speak to the other boy’s mom, I find out that he is a month younger than Maggie. So I think to myself – here’s Anna – much older and more mature. How will she handle the situation and also, how will she be handled?

To my pleasant surprise, the instructor adapted each activity for each child. When it was Anna’s turn to jump in the water from the pool deck, the instructor moved much further back in the pool than with the other two children. Conversely, when Maggie tried to get out of the pool and was struggling, she got a little boost. Depending on comfort level, the instructor would provide additional support for floatation for each child and could quickly identify strengths.

The instructor quickly changed the routine to accommodate the individual needs of each child. As a teacher, it was wonderful to see differentiated instruction taking place – and it was so easily observed by me, yet totally unnoticed by the children.

I guess that’s the point of a high school science research experience. Each student is completing a project, but at the level that is appropriate for that student. High-quality learning takes place and it is different for each person involved. It is so nice to see differentiated instruction take place and more exciting to observe and recognize it so easily. Just a little forethought goes a long way!
A Chat with Carol
May 2nd, 2007 by Frank LaBanca, Ed.D.

I recently stopped in to the Art Dept at NHS to distribute some informed consent sheets for one of my colleague’s dissertation. I had the chance to talk with Carol and we discussed the similarities between art and science. I quickly retold the story of a recent interview I conducted. Here is the excerpt from the transcript:

Me: How are scientists different/similar from artists/musicians?

Student: I think that the only difference is the medium from which they work. You know, a musician is working with an instrument – a musical instrument which is going to produce music. An artist works with paintbrushes. That’s their instrument that produces artwork. A scientist is working with a microscope, a telescope – and that’s producing the art of science. It’s just the medium for which they conduct their artwork.

Me: How are scientists different/similar from Journalists?

Student: Well journalists report on various things, and so do scientists. They report on their various findings and their data. I see scientists being closer to artists, though, and not as close to journalists.

Then our conversation continued. I, the scientist, talked about the creativity in art and science. She, the artist, talked about problem solving in art and science.

Wow! Most people take [>>science = problem solving<<] and [>>art = creativity<<] at face value. I, as a science educator, want to inform others of the creative processes necessary to conduct authentic research. She, as the art educator, wants to inform others of the problem finding processes necessary to produce art.

I find it interesting that we both were trying to demonstrate that our domains take into consideration the others “apparent” strength. We didn’t need to convince each other – but it is clear that we thing others need convincing.
Big Idea #1
May 1st, 2007 by Frank LaBanca, Ed.D.

Although this is not the first big idea I’ve come up with, it is the one that I’ve worked on this morning. I have been compiling the student descriptive adjectives from my interviews on a spreadsheet. The question reads:

Name three adjectives that describe you as a person in terms of your science project.

I’ve been struggling with thinking of ways to group this data. I’ve also been struggling with getting up in the morning. This morning, my alarm went off at its usual 5:50. I snoozed once, then turned it off. I started thinking about the adjective data again as I faded back and forth from consciousness. I was thinking, how do I axially code (group) this data . . . I know I have some creative behaviors and I know I have some work-ethic ideas. And then it hit me . . . work ethic is like task commitment a la Renzulli’s (1986) three-ring conception of giftedness. Perhaps I can categorize the data into these three groups.

And so it has been done (thus far). I am not surprised to see that the high achieving students describe their projects with more “creativity” words, while the low achieving students use more “task commitment” words.

I think this grouping will be an interesting way to look at the data (perhaps a x2 is in the works?)
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