Congratulations to all of the teacher-presenters at NSTA—to those who were willing to share their ideas and experiences. It’s a quantum leap from the classroom to the national stage, but in the sessions I attended, my colleagues rose to the occasion.

For example, Greg Benedis-Grab from The School at Columbia University (NY) shared ideas he uses for sharing digital data in the elementary science classroom. (Greg does more than presentations—look for more of his ideas in an upcoming issue of Science & Children.)

I was blown away by the work of chemistry teacher Tanya Katovich (from Shaumberg IL). She is working with Northwestern University to create remote online laboratories. These are different from simulations, in that students manipulate actual devices. She demonstrated (live) an investigation that uses a Geiger counter located in Australia. The students get real data in tables and graphs. Check out the iLabCentral site for more information about this free resource.

Who would think that a session on Friday afternoon at 5:00 would be packed? Those who managed to squeeze into Using Interactive Notebooks for Inquiry-Based Science were treated to a dynamic presentation by LaTonya Walker, Helena Easter, and Leslie Hayes from Richmond VA. They showed the audience how to help middle school students organize and use notebooks. They also showed how to scaffold activities through several levels of inquiry.

The deadline for proposals for next year’s conference in Indianapolis is April 15, 2011.

I’m a new teacher at a new school. I’m applying for a spot on the principal’s cabinet. One of the questions he’s asking is “What data should we review when we are planning and checking in on existing plans?” I can think of test scores and attendance, but can you suggest other data sources?
—Anar, Jamaica, NY

Schools already have a wealth of data, but the challenge is how schools can use these data to inform and guide the decision-making and planning processes. As a science teacher, your skills with problem solving strategies and the role of evidence (data) would be very valuable to the cabinet.

From the notes accompanying your question, it appears two of your school’s goals are related to project-based learning and improving student reading skills. I assume your principal will want to focus on data regarding your school’s attempt to meet these goals. I’ve often used Deb Wahlstrom’s four-step process:

1.     Collect. The data you use should come from a variety of sources in order to get a more complete picture of what it happening at your school. I’d recommend using four types of data (suggested by the work of Victoria Bernhardt):

• Student learning. In addition to standardized tests, measures of student learning could include report card grades, common assessments (e.g., unit tests or semester exams used in all sections of a subject), project scores based on a rubric, and examples of student work such as notebooks or portfolios. If you have access to data from the middle schools your students attended, this could be helpful as baseline data, especially in reading and math.

• Demographics. The demographics of the students and teachers include characteristics such as gender, race/ethnicity, socio-economic status, special education status, English language learner (ELL) status, feeder schools attended, neighborhood characteristics, years of experience (for teachers).

• Perceptions. Some researchers might consider attitudes and beliefs as “soft” data. But sometimes these perceptions become part of a school’s reality. Surveys, questionnaires, and interviews can tell you what students, teachers, administrators, and parents believe about the school and each other. (Bernhardt’s books have examples of surveys and questionnaires on attitudes toward learning and the school.)

• School processes. The day-to-day activities and school climate can also have an impact on student learning. This data would include class schedules, enrollment in remedial and advanced courses, instructional strategies being used, extracurricular opportunities, availability of tutoring (and which students take advantage of it), discipline records, attendance, school facilities, class size, professional development opportunities. These data, along with observations from walkthroughs, provide a glimpse into what happens in the school.

The real value of considering multiple kinds of data is in looking at how the data sets intersect. As a result of NCLB, you get student achievement data disaggregated by several demographic characteristics. You can also look at differences in project quality or reading achievement by gender, the quality of projects in various subject areas, the attitude of students in remedial classes, the types of reading instruction that take place in different content area classes, or the relationship between attendance and learning.

2.     Organize. Looking at spreadsheets, printouts, and surveys can be daunting. Organizing the data into consistent formats and using graphic displays can help people make sense of the data. Spreadsheets or other electronic tools are essential to this process, especially if you’re aggregating data from a variety of sources.

3.     Analyze. In a smaller school, you can learn a lot simply by looking at the data and highlighting trends, patterns, or anomalies. Some numeric data can also be analyzed statistically. It’s helpful if the data team can produce summaries and displays to communicate with the rest of the faculty.

4.     Use. The next step is to use the results of the data analysis for identifying needs, decision-making, planning, monitoring your progress toward the goals, and celebrating your success.

There is no “last step” in the process, because you’ll use the results to revise your goals and identify additional needs. In addition to answering questions, you’ll find that your data analysis leads to more questions.

It’s easy to focus on the tables, charts, statistics, and summaries. But behind the numbers and descriptions, there are real people—students, teachers, parents, and administrators—with variables and stories that make data-informed processes challenging (and fascinating).

You mentioned your school currently has ninth grade and will add a grade each year. You have a wonderful opportunity to study your ninth graders longitudinally. As additional grades are added, you’ll have teachers new to your school also. It would be important for the cabinet to develop a way to bring them up to speed with your processes.

Decision-making can be stressful, especially if the decisions result in changing the status quo. You’re fortunate that, as a new school, you don’t have an entrenched status quo. Your school is evolving, and data-informed processes can become an accepted part of the school culture.

For more information:

Deb Wahlstrom: Using Data to Improve Student Achievement
Victoria Bernhardt: Data Analysis for Continuous School Improvement

Photo: http://www.flickr.com/photos/jenmaiser/2171791257/

I like to think of science as the process of discovering or creating knowledge. Sure it has many other definitions, but to me, in its most basic form science generates information, and that information is understood and communicated by humans as knowledge.

An engine, on the other hand, is often described as a machine for converting any of various forms of energy into mechanical force and motion. But further definitions include an engine as something used to effect a purpose or computer software that performs a fundamental function especially of a larger program.

It is this latter definition that was the likely use of naming Wolfram Alpha a “Knowledge Engine.” However, it is the second one, something used to effect a purpose, that I particularly like.

An oldie but a goodie: Wolfram Alpha shows data in a way Google can’t.

Reading the above story about the so-called knowledge engine named Wolfram Alpha (abbreviated W|A), it made me wonder about the pros and cons of of what I like to call recreational data mining.

The classic web search engines of the past decade and a half gave anyone using the net access to a huge number of resources about almost any subject. The read-write web of the past few years allowed one to fill in the gaps with known information thus adding to the overall body of net-based knowledge. Image databases and mapping interfaces further pushed the level of information mashing. But Wolfram Alpha is yet another leap forward.

Having played with W|A on and off since it went live on online, I’ve found it an interesting way to explore subjects, or rather the intersection of subjects. Considering the potential of recreational data mining, it would be interesting to have a place where curious results could be published. The danger, of course, is there might not be a useful or even rational connection between the searched subjects that were forced together possibly against their will. But if science is the creation or discovery of knowledge, then using W|A is, in fact, science.

Like all emerging tech, early adopting educators test-drove the tech then posted their adventures and observations online. W|A is no exception. Here’s a W|A education discussion board: The Education Community Forum for Wolfram Alpha.

Even as science educators get up to speed with W|A, the next generation of products is already on the way. Given Wolfram’s origins within mathematics software, math was the natural place to start, but science topics are on the list as well. What am I talking about? Why Wolfram Course Assistant Apps of course.

But like many of our digital dilemmas—including spell check, electronic calculators, digital balances, GPS, and GO-TO telescopes—that all rudely displaced their ancestors, questions arose that directly addressed the very nature of why we do what we do. For instance: Wolfram education apps raise teaching dilemma.

Another definition of an engine is “something that produces a particular and usually desirable result.” Hopefully the future of relational databases will pursue this definition as well. But alas, there is yet another definition for engine, and although an obsolete usage of the word, its etymology might be something to keep in mind—”engine: a torture implement.”

Click here for the Table of Contents

Everyone talks about the weather, but the articles in this issue show students doing more than talking. Just look at the action words in the titles: blog, cruise, teach, make, watch, look, learn.

The differences between weather and climate can be challenging for younger students. The author of Making the Climate Connection suggests a “progression” topics for grades K–5 and recommends some online resources (many of which are in SciLinks). The lesson described in Dress for the Weather uses actual data to help students differentiate between weather and climate. The lesson uses the 5E learning cycle with a real-life focus.

Talk about a real-life focus—the students in the article Blogging About the Weather combine their experiences in weather instruments, storm studies, cloud formations, and weather fronts to prepare their forecasts and share them with other students via a blog. In a class I visited, the fourth-grade students used their weather station to prepare forecasts that they shared every day with the principal to help her make the decision about whether to have outdoor recess. And in a related news article, check out how fourth grade weather watchers are creating forecasts that are telecast on the Internet as well as on the school’s Web site.

Cruising the Climate with Spreadsheets shows how elementary science methods teachers found local weather data online, created Excel spreadsheets to organize the data, and interpreted the data from both local and international sites to learn about climates. This activity could be used as a purposeful workshop to brush up (or introduce) skills in spreadsheets. The author includes a list of online spreadsheet tutorials and tips for inserting or deleting symbols. I was not aware of this feature, so I learned something new, too. (Note: I use the Mac 2008 version where inserting symbols is part of the Object Palette under the View menu or in the Toolbox.)

NSTA’s Early Years blog has detailed ideas and resources on exploring the concept of evaporation with younger students, related to the article Where Did the Water Go?

If you’re looking for lesson ideas or sites for students on topics related to this theme, check out these K–4 SciLinks keywords:

• Forecasting the Weather
• Collecting Weather Data
• What Causes Earth’s Seasons?
• Clouds and Fog
• Storms
• Tornadoes
• What Makes Up the Atmosphere?

At the 5–8 level, there are many keywords leading to websites on weather and climate. In SciLinks, use the basic keywords “weather” or “climate” to access them.

In this issue, all of the articles deal with the theme of weather. I’m going to continue reading and in the next post, I’ll share more resources on seasons, clouds, and instrumentation.

Check out the Connections for this issue. Even if the article does not quite fit with your lesson agenda, this resource has ideas for handouts, background information sheets, data sheets, rubrics, etc.

Ted Koehn with his arsenal of inexpensive/free materials

Last year in New Orleans, I attended the session Sixty Labs You Can Do with Little or No Budget (see related posts below). Last year, so many people were there that some had to stand and some of us had to sit on the floor. I decided to go again this year because I was curious: Who would come this time? How many, given the late time slot of 5 p.m. on Saturday afternoon? What would I learn that I missed last time?

Ted literally describes his 60 high school physics and chemistry activities in a fast-paced, one-hour session. All of the materials he uses are either free or very inexpensive, and he even will tell you the exact amount–to the penny–he spent to acquire them (“at least in Lincoln,” Nebraska—his hometown—he adds). He provides each audience member with a packet containing guides for doing each of the labs, and the hour was filled with the sounds of pages turning as the teachers followed along.

He covered chemistry labs on moles, acids and bases, the periodic table, solubility curve… (the clock was ticking: 1 lab…10 labs…15 labs…)

…using gumdrops and toothpicks to create models of molecules…buying 100 chromatography strips for $3…10 vials of pH paper for $10…using eyedroppers as titration tubes…(20 labs…30 labs…)

Then came the physics labs. How to construct four inclined planes using inexpensive plywood…getting free ball bearings (from a truck repair shop) that students can roll down the inclined planes…checking garage sales for bargain supplies…propping a curtain rod on some books to create another inclined plane…(35 labs…40 labs)

…getting softballs from the PE department to use to teach projectile motion…”Ohaus gave out free spring balances in the Exhibition Hall; did you get one?”…having students use old film canisters and loading them with different amounts of pennies to see whether they would sink or float in water…(50 labs…60 labs! Hooray!) The audience applauded enthusiastically!

As you can see, the 5:00 start time did not deter science teachers from showing up for Sixty Labs. One teacher commented, “He’s amazing. I’m exhausted—but it was great!” (You can find Ted’s e-mail address online in the Saturday/Sunday program.)

Longtime readers of NSTA Reports, NSTA’s monthly newspaper, may recall the headline of this post was once the name of a popular column in the paper. (And hello to the former Reports editors reading the blog, who will remember the fun we had coming up with the names for the newspaper’s columns.)

Improving Your Students' Graphing and Graph Interpretation Practices

Tony Bartley (from Thunder Bay, Ontario) and Mike Bowen (from Halifax, Nova Scotia) discussed how to improve students’ data literacy. They reviewed types of data (nominal, ordinal, and integer/ratio) and the type of graph that would be appropriate for each.

Using simple materials such as marbles, paper cups, and a ruler, they engaged the participants in an activity that incorporated concepts such as data types, graphing, variables, line of fit, and interpreting data. By the end of our marble-rolling trials, we had the beginnings of a great bar graph.

How far does a marble push a cup?

They noted that “science is a probabilistic endeavor. It doesn’t make absolute deterministic statements; it makes statements of probability.” They also shared a booket they created on data literacy for students (and teachers).

Karen Wood

I’ve been hearing a lot about science notebooks lately, so I went to the Education Development Center’s Pathway Session on Establishing Science Notebook Habits and Skills. It was interesting to hear each presenter’s unique take on the science notebook and see all of the student examples they displayed.

Fifth-grade teacher Karen Wood said structured journals work best with her fifth graders, who typically don’t have a lot of exposure to science. I was shocked to hear that only a handful of her students each year have had any science at all.

Dean Martin

Dean Martin, science specialist for grades 3-5 in the Boston Public Schools, uses a “dual notebook structure” combining free writing with specific questions to explore. With students who have difficulty expressing themselves in writing, he adapts the notebook by letting them take digital photos and write captions. To help kids who think they can’t draw, he provides a few simple drawing lessons to build their confidence, while assuring them that their drawings need not be perfect.

Lori Fulton

Lori Fulton of Jay Jeffers Elementary School in Las Vegas, Nevada, says many of her kindergarteners are English Language Learners, so writing is hard for them. So they work on creating pictures for their notebooks first, then learn how to label the pictures. With older students, she advises not overemphasizing conclusions and encouraging students to describe their observations.

Audience members asked the presenters about how they helped their students make real-world connections using their notebooks and how to determine whether what students put in the notebook represented accurate understanding.

Photo uploaded to Flickr.com’s Creative Commons by marcusrg

In the award-winning documentary A Private Universe, education researchers from the Harvard-Smithsonian Center for Astrophysics sought to answer this question: Why don’t even the brightest students truly grasp basic science concepts? Teachers and teacher educators alike continue to search for ways to overcome students’ science misconceptions and to determine how they develop in the first place.

Get some insight on students’ “Private Universe” in Philadelphia. You’ll find sessions addressing misconceptions at all grade levels, in a range of science fields. Use the session browser with the keyword misconception to find them. Here’s a sample:

• Centering Around the Science Standards, Grades K–2 (March 18). Find out how hands-on centers incorporate the learning cycle to address common misconceptions.
• Everyone Knows That Heavier Things Fall First (March 19). Use misconceptions to teach intermediate-level physical science? You can do it with these classroom demonstrations and activities.
• Using Diagnostic Assessment to Address Preservice Teachers’ Science Misconceptions (March 20). It’s never too late to identify these deep-seated incorrect beliefs. Learn how to create inquiry-based lessons to improve scientific understanding.

And picking up where A Private Universe left off, Neil Comins—astrophysicist, astronomer, and professor of physics and astronomy at the University of Maine—has identified nearly 2,000 commonly held misconceptions about astronomy and physics and has figured out “their origins, why we develop them, how to avoid them in the future, and how to get rid of old ones (which is the hard part).” Hear how he conquers them on March 20 at the Shell Science Seminar.

The word “data” for some people conjures up pages of numbers or a dreadful experience in statistics class. But get rid of the deer-in-the-headlights look and dig into lessons focused on forensics, snow, fruit flies, and Down syndrome. The protocols, rubrics, and examples can help you work with students in this critical inquiry process.

I’ve been trying to learn more bird songs, from CDs and other media. So I was blown away by the idea of learning insect sounds as described in Exploring Sound with Insects. It was fascinating to read how the authors combined the physics of sound with an investigation in biology. I downloaded the software Raven Lite (free!) from Cornell University and spent an entire evening “playing around” with it and with the sound resources listed at the end of the article. The authors describe how to use the software to record and analyze insect songs, but it seems like the software could be used to record and analyze musical sounds or environmental sounds, too. The whole lesson looks fascinating, and if you’re concerned about learning the software, perhaps a few students could become familiar with it and do a demonstration for the class? (For background resources on sound, check out SciLinks with the keywords “sound” and “communication”)

With many of us in the grips of winter weather, perhaps a virtual exploration of Hawaii would be interesting. The lesson described in Predicting the Timing and Location of the Next Hawaiian Volcano shows students how to extract data from maps, diagrams, and tables and how to analyze the data by looking for trends and patterns. For background information for this lesson, check out SciLinks with the keywords “volcano” and “ring of fire” – a great way to integrate concepts in earth science and geography.

As someone who actually enjoys statistics, I was intrigued by the article Is Knowledge Random? Introducing Sampling and Bias Through Outdoor Inquiry. My state includes statistics in the math standards, so this lesson could be a way to show students some practical connections between science and math. I’ll share this with a math colleague.

Our students may be used to using evidence to answer questions, but in Elk Habitat: A Case Study of Scientific Inquiry, the authors describe an activity in which students ask questions, examine evidence, ask new questions, and design potential research studies. If elk studies are not relevant for your students, look at the resources of the National Center for Case Study Teaching in Science for more examples and resources. Wouldn’t it be interesting for older students to design case studies for younger grades?

The articles Argument-Driven Inquiry and A New Twist on Mystery Boxes both describe the value of argumentation in science. If argumentation is a new concept for your students, look at this month’s issue of Science and Children for ideas on how to introduce this type of discussion. Although “Mystery Boxes” have been used by many teachers, this could be a good activity for the beginning of the year, helping students to differentiate between evidence and inferences (and opinions). There is also a rubric for assessment.

Although there are many ways to measure temperature (use the code TST110901 in SciLinks,) The Sound of Crickets looks at whether the temperature can be estimated by counting cricket chirps. The process that the author used to figure out how to collect the evidence would be interesting for students to read about.

Students aren’t the only ones to engage in inquiry. Examining Student Work describes a process in which groups of teachers meet to examine student work in detail to examine student thinking and learning. Rather than looking only at the summative data from standardized tests, these teachers followed a systematic inquiry process to examine evidence of student learning throughout the school year. The authors provide many of the resources in the NSTA Connections, including an outline of a 55-minute study session. This month’s issue of Educational Leadership is devoted to the theme “Multiple Measures.” Many of the articles look at various types of assessments as examples of student work. Although most articles can be read online by nonmembers, unfortunately Looking at Student Work does require a fee for nonmembers. Perhaps a colleague who is a member of ASCD can get a copy for you.

Give a copy of Data, Data Everywhere to anyone in your school who analyzes data or transforms data into graphical representations. The author differentiates between types of data and describes the kinds of graphs that are appropriate for each, including how to graph the relationships between independent and dependent variables. To help students (or other teachers) communicate evidence graphically, check out the Create a Graph website from the National Center for Education Statistics. The Tutorial (which can be downloaded as a pdf file) also has an explanation of when to use various types of graphs and a discussion of independent and dependent variables. The tool itself can be used to make, save, and print graphs.