Sunday, December 08, 2013

Smart Science® Labs Go Mobile

In a major new release of Smart Science® online hands-on labs, they're now mobile with HTML 5.  Using the Google Web Toolkit, the new software is more accessible for the handicapped and available on a long list of devices.

The world's only online hands-on labs and best way to learn science are now available on a long list of web devices including:
  • Android tablets
  • Android phones
  • iPad
  • iPhone
  • Chromebook
  • Laptops and desktops
    • Linux
    • Windows
    • Mac OS X
    • various Unix systems
In fact, any system that supports the CANVAS and VIDEO tags of HTML 5 will run Smart Science labs now. Just be sure that Javascript is enabled.

For a quick preview and check of compatibility, see our home page and click on the "TRY OUR NEW HTML 5 LITE DEMO NOW"  link in the upper right corner.

Smart Science online hands-on labs have been bringing real science to the online world for over a decade.  With more than 150 labs and different reading and math levels for content, these labs will meet your science learning goals, including NGSS and America's Lab Report.

Finally, you can have the world's best science learning at your students' fingertips anywhere they have Internet access and on their own devices.

© 2013 by Smart Science Education Inc., U.S.A. www.smartscience.net
Follow this author on ETC Journal

California State University to Use Smart Science Labs

I am very proud to announce that Smart Science Education Inc. has a contract to supply our online hands-on science labs to the 23 campuses of the California State University, the largest university system in the United States with over 400,000 students enrolled.

Smart Science® labs are the only virtual labs developed outside of the CSU system to be chosen for use in the program to add virtual labs to science courses at CSU campuses.  This action comes as a result of a mandate by the state's governor to remove system bottlenecks in all state colleges, including the University of California and the California Community College system.  With rising enrollments, available lab seats have held back many students from graduating on time because of the necessity of fulfilling a laboratory science requirement.

The Smart Science approach to online labs differs from all others in that it uses real experiments, video recorded, and has sophisticated software that allows students to take their own data using their care and judgment just as in typical classroom labs.  This approach is patented, and more patents are in process.

The point of science labs should be to do real science, to inquire,  investigate, and discover.  In general education classes, there's no real necessity for learning laboratory technique.  It is, however, crucial to have an understanding of the nature of science, to develop scientific thinking skills, and to appreciate the complexity and ambiguity of empirical data.  In many instances, Smart Science explorations fulfill these goals better than the traditional lab experiences.

© 2013 by Smart Science Education Inc., U.S.A. www.smartscience.net
Follow this author on ETC Journal

Thursday, February 07, 2013

Remote Robotic Labs and Smart Science® Explorations

Recently, someone asked about the differences between remote robotic labs and the Smart Science® exploration online hands-on labs. This question may arise in the minds of many.

The various remote robotic labs (RRL), including MIT's iLab, are different in some important aspects. Because our approach is so different, educators often have trouble understanding the differences compared to approaches with which they may be familiar.  This explanation should help to clear up any questions.

A RRL provides data automatically. You set up your parameters, whatever those may be, and push a virtual button. Often, you see nothing transpire at the remote site. After a brief pause, you're handed a sheaf of data electronically. For advanced students, that may be just fine, but for ordinary students, all of the trouble of setting up the RRL has been wasted. You might as well have stored the data from yesterday (or last year) along with any imagery and provided that. In that event, you could have just provided this information locally. The students wouldn't know the difference and probably wouldn't even care.

RRLs have limited range. They cannot do Sordaria crossing over or seed germination experiments. You can imagine doing tides, but the real-time aspect is lost because students are not there in real time the entire time that data are being captured. And so it goes. You cannot base an entire biology or chemistry course on just RRLs.

RRLs have limited access. If you attempt to scale RRLs, you must have more pieces of expensive or unique equipment. Depending on the precise experiment being run, the time that the machine is available controls how many students can use it during a given hour-long period. It's not unlimited. You know that you cannot deliver to a million students per hour and probably not even to a thousand.

Our approach takes the online hands-on lab (OHOL) path. We toss out the pretense of real-time experiments. (I say pretense because there's always a delay between data capture and arrival at the student workstation.) In its place, we open up entire new vistas of learning science.

The OHOL way does not deliver data automatically. Students truly must interact to take their own data. As in the tides example, those data are different for different students doing the same experiment with the same parameters.

With OHOL, you have a visual experience. With tides, you watch the actual tides and then measure them yourself.

An OHOL can be created for any experiment you can record on video and take data from. The data may be quantitative, semi-quantitative, or qualitative. They are your data, not those of a machine. The experiment videos may be from a high-speed camera or from a time-lapse camera. They may even combine multiple cameras as with the shadows lab where one camera follows the Sun with a fish-eye lens and the other tracks the path of a shadow.

What do OHOLs and RRLs have in common? None of the data are invented. They all come from the real world. The various forms of real wet labs also have this feature. However, only manual wet labs and OHOLs are truly hands-on in the sense that you take your own data point by point.

Our technology allows for an unlimited number of scenarios. We're only limited by our imagination and our resources. We have done as many as 100 experiments to create one lab. The number of experiments available is also a function of the pedagogy. Students can be confused by having 30 experiments available. Some will think that they must do every one rather than exercise judgment (actually think) despite our telling them otherwise. It becomes the instructor's task to handle this issue because instructors control grades, and students who do every single experiment available are doing so because they think they'll improve their grades. The instructor must convince them that lack of thought will reduce their grades. Our best efforts cannot do so because we do not hand out grades.

There's much more to this picture. For example, we insist on students making predictions before beginning experiments. We provide introductory (pre-lab or formative) assessments and summary (post-lab or summative) assessments. We provide extensive background resources and an online lab report that can be customized for your classes.

The above is not to say that RRLs have no value. On the contrary they are the go-to labs of the future for college engineering courses. They open up the use of expensive equipment that many schools cannot afford to undergraduate engineering students. They have limited use for college science courses. The limitations are those of the medium that requires complete automation and relatively quick experiment completion. They're of little value in K-12 education. You can find better ways to learn any science concept at that level, with the possible exception of advanced or honors courses and then, as with college science, only with a very few investigations.

© 2013 by Smart Science Education Inc., U.S.A. www.smartscience.net
Follow this author on ETC Journal

Wednesday, January 23, 2013

NGSS Have Problems

You can read a review of NGSS at http://etcjournal.com/2013/01/22/next-generation-science-standards-fall-flat/.  However, that's not the entire story.  Here's the rest of the story.

In the NGSS, "crosscutting concepts" are concepts that span all disciplines of science and engineering and help, according to the authors, to tie the standards together.  As a chemist, I look at those associated with chemistry standards.  I also look most closely at high school standards to see what the highest level of the standards do.

The crosscutting concepts in high school chemistry (Structure and Properties of Matter and Chemical Reactions) are listed as follows:

  • Cause and Effect
  • Systems and System Models
  • Energy and Matter
  • Structure and Function
  • Stability and Change
  • Patterns
The one crosscutting concept I see missing here is Obtaining First-Hand Data from the Real World.

Science is about exploring the real world and is an open exercise that explores what really happens, not what should happen in an ideal system.  While ideal systems are used as models against which to compare real data, scientists don't really care about models except as a tool.

Here's one sample standard that exemplifies the approach of the NGSS.

Analyze and interpret provided data about bulk properties of various substances to support claims about the relative strength of the interactions among particles in the substance.
 The standard does not specify whether the provided data are to be real or manufactured.  In this instance, you might infer that data are real.

In the section on Forces and Interactions, you'll find the following standard that is much less clear.

Analyze data to support the claim that Newton’s second law of motion describes the mathematical relationship among the net force on macroscopic objects, their mass, and acceleration.
 From where do these data arise?  Is it from student experiments, from teacher experiments or demonstrations, or from a formula?  Very often, the data will come from a simulation, e.g. a formula.  You can expect teachers, when allowed by their state and local standards, to resort to this easier and more "reliable" approach whenever possible.

What does it mean to analyze manufactured data?  Here, you're using F=ma to generate data, and those data are then used to infer that the model they represent is F=ma.  This sort of thing is ludicrous.  I'd use stronger language but refrain out of respect for the reader.

This is a closed cycle.  A formula generates data that are used to verify the same formula.  In science, however, it's always an open system.  Data come from the real world, or as America's Lab Report  (ALR) says, "the material world."  Indeed, ALR insists that data originate in the material word in order for an activity truly to be a science investigation.  Ultimately, these data are analyzed and may result in a model of the real world.

The difference is as night and day.  Where ALR focuses on student actually obtaining their own data for the most part, NGSS has students working with provided data.  Is there no hope?

Later on, the following standard provides some relief.

Design and conduct an investigation to support claims about how electric and magnetic fields are created.
Here, students must do experiments and collect their own data.  However, there's one minor problem as the Clarification Statement shows.
Qualitative observations only.
So, here is the one actual piece of lab work in HS.Forces and Interactions, and it's entirely qualitative.   You cannot do much with purely qualitative data.

Finally, under Energy, you can find a real lab.

Design and conduct an investigation to support the claim that the transfer of thermal energy between components results in a more uniform energy distribution among the components of a closed system
In this standard, students are requested to "[use] mathematical thinking to describe the energy changes both quantitatively and conceptually."

That's it for the physical science portion of the standards.  One quantitative investigation and one qualitative one -- for an entire year of physical science or for two years of chemistry and physics.

To be fair, these are "core concepts," and states, districts, and teachers are free to add to them and extend them.  However, if the states and districts do not mandate laboratory investigations, then teachers will tend to avoid the extra time and budgetary stress of true lab investigations.

I find these standards to be rather shallow for leaving out important concepts (e.g. the mole) and for failing to insist on more first-hand quantitative investigations.

They've become so enamored of their cross-cutting concepts and of integrating engineering into science that they've lost the very essence of science.

© 2013 by Smart Science Education Inc., U.S.A. www.smartscience.net
Follow this author on ETC Journal