What you are describing is known (in eduspeak terms) as "discovery based learning."
My school experimented with this some years ago. It was an unmitigated disaster.
The primary problem is that students simply can't put together all the pieces of the puzzle in the 3-hour time period, and accreditation requirements of 10 experiments per semester don't allow us to spend 3 or 4 weeks on each lab.
In the end, we basically had to tell the students how to run the experiment, which meant we were back to the same "cookbook" chemistry we've been teaching for the past 100 years.
I wouldn't recommend Spartan to high-school students. They can't possibly understand what the software is calculating without a thorough understanding of quantum mechanics, thus relegating the software to a toy with no practical application.
I offer this advice:
Teach them to graph experimental data, either with Excel or any other software. However, only do so AFTER they have learned to graph the old fashioned way (pencil & paper).
I am often frustrated by my students' complete lack of understanding of (1) what constitutes a proper scientific graph and (2) what information that should be able to glean from the results.
If you want to do them an even larger favor, teach them how to perform a manual linear regression of their hand-drawn graph (see http://easycalculation.com/statistics/learn-regression.php for an example). Linear regression isn't that difficult: once you get past all of the fancy symbols, it's really just arithmetic. Only then should they progress to Excel.
A sample lesson plan would look something like this:
1. Perform an easy experiment to collect data (P-V data from a Boyle's law experiment would be a good example). You only need four or five data points.
2. Have the students graph the data by hand. Emphasize the components of a proper scientific graph (descriptive title, properly labeled axes that include units, etc.).
3. Have them draw an "eyeballed" best-fit line through the data and then teach them to calculate the equation of that line.
4. Now have them perform a manual linear regression and compare this new straight-line equation with their estimated equation. This is an excellent opportunity to teach them the usefulness of linear regression.
5. Now teach them to construct the same graph in Excel or other graphing software and have the software perform the linear regression. Again, they should compare their results to the computer's results.
The idea is to teach them that tools like Excel or ONLY TOOLS. Software is not a magic black box that miraculously spits forth meaningful numbers. They are simply tools that save scientists time, and scientists must understand what the software is doing before he/she can "trust" the results.
Best of luck to you.
I'm a college faculty member and I pitched Moodle at a college-wide meeting last year when the Admin types were looking for cost-saving ideas.
The idea was quickly shot down on the basis that our college has "tens of thousands of man hours" invested in developing Blackboard content that cannot be directly imported into Moodle.
This is what the suits call "sunk costs."
It's what the rest of us call "good money after bad."
And it never occurred to any of them that the lack of portability of Blackboard content is 100% deliberate---for the sole purpose of preventing migration to other platforms.
I'll move away from the Gulf Coast as soon as everyone in Kansas and California are stripped of their homeowner's insurance.
Oh, and also residents of New York, because only fools would live in a known terrorist target.
Slashdot Mirror
...Microsoft's reputation is so bad that people won't believe them even when they're right...
Bill Maher once said, concerning the OJ Simpson case, that "the LAPD is so incompetent they couldn't frame a guilty man."
I think MS and the LAPD have more in common than meets the eye.
What you are describing is known (in eduspeak terms) as "discovery based learning." My school experimented with this some years ago. It was an unmitigated disaster. The primary problem is that students simply can't put together all the pieces of the puzzle in the 3-hour time period, and accreditation requirements of 10 experiments per semester don't allow us to spend 3 or 4 weeks on each lab. In the end, we basically had to tell the students how to run the experiment, which meant we were back to the same "cookbook" chemistry we've been teaching for the past 100 years.
I wouldn't recommend Spartan to high-school students. They can't possibly understand what the software is calculating without a thorough understanding of quantum mechanics, thus relegating the software to a toy with no practical application.
I offer this advice: Teach them to graph experimental data, either with Excel or any other software. However, only do so AFTER they have learned to graph the old fashioned way (pencil & paper). I am often frustrated by my students' complete lack of understanding of (1) what constitutes a proper scientific graph and (2) what information that should be able to glean from the results. If you want to do them an even larger favor, teach them how to perform a manual linear regression of their hand-drawn graph (see http://easycalculation.com/statistics/learn-regression.php for an example). Linear regression isn't that difficult: once you get past all of the fancy symbols, it's really just arithmetic. Only then should they progress to Excel. A sample lesson plan would look something like this: 1. Perform an easy experiment to collect data (P-V data from a Boyle's law experiment would be a good example). You only need four or five data points. 2. Have the students graph the data by hand. Emphasize the components of a proper scientific graph (descriptive title, properly labeled axes that include units, etc.). 3. Have them draw an "eyeballed" best-fit line through the data and then teach them to calculate the equation of that line. 4. Now have them perform a manual linear regression and compare this new straight-line equation with their estimated equation. This is an excellent opportunity to teach them the usefulness of linear regression. 5. Now teach them to construct the same graph in Excel or other graphing software and have the software perform the linear regression. Again, they should compare their results to the computer's results. The idea is to teach them that tools like Excel or ONLY TOOLS. Software is not a magic black box that miraculously spits forth meaningful numbers. They are simply tools that save scientists time, and scientists must understand what the software is doing before he/she can "trust" the results. Best of luck to you.
I'm a college faculty member and I pitched Moodle at a college-wide meeting last year when the Admin types were looking for cost-saving ideas. The idea was quickly shot down on the basis that our college has "tens of thousands of man hours" invested in developing Blackboard content that cannot be directly imported into Moodle. This is what the suits call "sunk costs." It's what the rest of us call "good money after bad." And it never occurred to any of them that the lack of portability of Blackboard content is 100% deliberate---for the sole purpose of preventing migration to other platforms.
I'll move away from the Gulf Coast as soon as everyone in Kansas and California are stripped of their homeowner's insurance. Oh, and also residents of New York, because only fools would live in a known terrorist target.
to the "federal pound-me-in-the-ass prison" scene from Office Space? This is meant as humor, right?
Don't forget THE most important lesson: When in doubt---cast chain lightning.