Do these students identify the same colors as the students without visual impairments?
Are their lab results correct?
Students were able to accurately describe colors.
I have had some students in class have a hard time identifying colors (flame tests, solution color, acid-base indicators, etc.) because of a visual impairment. There are many cell-phone apps that are helpful in aiding these students. "Pixel Picker" allows the students to load a picture from a device (cell phone, ipad). This is helpful because students are now dealing with a "frozen" image. Moving the cross-hair to different parts of the picture changes the R-G-B values. The "Color Blind Pal" app uses a more qualitative approach. It names the color in the cross-hair using various color scales. There are also different options for different types of color blindness.
Both of these apps are free and availble in the App Store.
A student should be able to correctly identify an unknown metal by the color of its flame.
A student should be able to correctly identify the endpoint in a titration by the indicator's color change.
A student should be able to correctly describe the physical properties (color) of a sample.
A student should be able to correctly predict the visible absorbance spectrum of a solution based on correctly identifying the color of the solution.
Have the students with visual impairments practice using the app ahead of time to better prepare them to use the app for the first time in class/lab. Students would also need to understand the additive nature of light colors. For example, high R and G values will appear yellow/orange. I would give these students a 1-page handout for their lab notebook with the addative color wheel and various colored circles labeled with their names and RGB values so that students could practice and reference in the lab.
Our lab safety contract actually has students indicate whether they are color blind. This is a good time to introduce these students to the apps.
This exercise takes longer than a 50 minute class period, so we get as far as we can in one class and the students complete the exercise as homework. Students write their answers to the questions directly on the handout. Tables are provided for recording numerical results, but because of some (simple) required mathematical manipulations, it is easier if students set up a spreadsheet and record their numerical results there. The handouts with their answers and printed copies of their spreadsheet are collected in the next class.
In Exercise 1, the vibrational spectrum of formaldehyde is calcuated by three different methods. Because the vibrational modes come out in a different order, energy-wise, in one of the methods, students have trouble keeping track of which vibration is which. Each mode is labeled with the correct symmetry label, which should help them. Plus, they can click on each mode and visualize it.
Exercise 2 involves calcuating delta H for an "isodesmic" reaction: one in which the total number and type of bonds is the same in reactants and products. This helps cancel any systematic errors in the calculations. If this is one of the first time that students have worked in "hartrees," it is helpful to explain that unit to them. Students compare semi-empirical calculations with HF and DFT, and in this example, the HF and DFT calculations give much more accurate results.
Exercise 3 is about calculating UV-Vis spectra, but more importantly it walks students through drawing more complicated molecules. The CIS/ZINDO approach is used for the UV-Vis calcuation, which may not be highly accurate, but is very fast, so students get rapid results that they can compare.
In Exercise 4, students calculate NMR spectra for three different molecules. It teaches students about chemical shifts, but it does not cover coupling constants. If students are experienced with NMR, the averaging of proton resonances (such as the three protons in a methyl group) has become second nature to them. This exercise forces them to think about how those resonances are averaged.
This is the fifth in a series of exercises used to teach computational chemistry. It has been adapted, with permission, from a Shodor CCCE exercise (http://www.computationalscience.org/ccce). It uses the WebMO interface for drawing structures and visualizing results. WebMO is a free web-based interface to computational chemistry packages (www.webmo.net).
In this exercise, students perform infrared, thermochemistry, UV-Vis, and NMR calculations. They compare the results from different methods and basis sets to experimental values.
The exercise provides detailed instructions, but does assume that students are familiar with WebMO and can build molecules and set up calculations.
Students will be able to:
- Calculate an IR spectrum. Visualize the normal modes. Use appropriate scale factors to “correct” the calculated values.
- Calculate NMR spectra and average the chemical shift values for the static structures (in 1H NMR) to approximate the experimental spectrum.
- Calculate UV-Vis spectra.
Students need access to a computer, the internet, and WebMO (with Mopac and Gaussian).
I use this as an in-class exercise. Students bring their own laptops and access our institution's installation of WebMO through wifi.
I am really unsure at this point. I may use the 1FLO version of this as a series of exam quesitons, or I may have the students work on this literature discussion in class. Either way, I am excited to see what they will do with it.
This is the full literature discussion based on a communicaiton (J. Am. Chem. Soc. 2011, 133, 9278). This paper describes a redox-switch yttrium catalyst that is an active catalyst for the polymerization of L-lactide in the reduced form and inactive in the oxidized form. The catalyst contains a ferrocene-based ligand that serves as the redox active site in the catalyst. This full literature discussion is an extension of the one figure literature discussion that is listed below. In addition to presenting all of the same questions as that learning object, this includes interpretation of the XANES spectra presented in the paper. It also asks the students to identify the monomer and polymer in the reaction of interest. A possible extension of this learning object would be to have students examine and take measurements from the crystal structure presented in the paper in order to support the apparently low electron count on the yttrium catalyst. The Covalent Bond Classification system for counting electrons is used in this learning object.
A student should be able to apply their knowledge to
- describe and interpret a plot of conversion vs. time
- count electrons and determine valence states in organometallic compounds
- determine if an organometallic compound is an oxidizing or reducing agent
- decipher a first-order kinetic plot
- interpret XANES spectra to determine the valence of iron in the catalyst