# WPI's Learning Object Repository

## Add Your Learning Objects

If you are a WPI faculty member and would like to have your learning objects included in this repository for use by the WPI community, please contact us at atc-ttc@wpi.edu.

Learning objects are small digital chunks of learning content that are self-contained and reusable. They are often used in education to supplement course materials and to demonstrate concepts that are difficult for students to grasp with traditional teaching methods.

The learning objects in this collection were developed by WPI faculty members and are available for public use. Many were developed as part of the Teaching Technology Fellowship, a joint venture sponsored by the Division of Academic Affairs and Information Technology here at WPI.

If you require assistance with using a learning object, please contact us at atc-ttc@wpi.edu.

We hope that you find these learning objects useful in your teaching and learning endeavors.

### Biomedical Engineering

**Series 1**: This series of tutorials, developed in 2005 by professors Kristen Billiar and Allen Hoffman, detail the use of TestWorks 2.03 and X machine. The first two clips demonstrate the proper technique for running a uniaxial tensile test. Subsequent clips demonstrate the necessary steps to use the testing software, TestWorks 2.03.

Mantling the Grips

Running a Uniaxial Tensile Test

TestWorks 2.03: Using the Handset, Extension Meter, and Load Meter

Logging into TestWorks 2.03

Plotting Specimen Data in Excel

Running a Cyclic Test using TestWorks 2.03

Running a Tensile Test using TestWorks 2.03

Saving Test Data in TestWorks 2.03

Exporting Test Data from TestWorks 2.03

Transferring Data to Excel from a Text File

**Series 2**: This series of tutorials, developed in 2004 by professor Ross Shonat and WPI student Ryan Carey, detail the use of Biopac and several other software applications relevant to biomedical engineering.

Physiology/Data Acquisition Equipment Overview

Acquiring Data with Biopac

Conducting an EEG Lab with Biopac

Conducting an ECG Lab with Biopac

Lab 1: Animal Care and Anesthesia

Lab 2: Muscle and Nerve Physiology

Lab 3: Electrophysiology

Lab 4: Circulatory Physiology

Lab 5: Respiratory Physiology

Lab 6: Acid-Base Physiology

Statistical Analysis Using Excel

Data Analysis with AcqKnowledge

### Civil & Environmental Engineering

**Series 1**: The following two simulations were developed in 2005 by professor Jeanine Plummer. The first simulation is a virtual tour of a wastewater treatment plant. The second simulation is an interactive simulation that provides students with the opportunity to input several variables into an interface to test air pollution.

Wastewater Treatment Plant Tour

Air Pollution Simulation

**Series 2**: This series of video clips, developed in 2003 by professor Guillermo Salazar, details a series of functions in Primavera’s project management software.

Creating a File

Entering Activities

Creating Network Logic

Running the Schedule

Exporting to a Spreadsheet

Inserting a Graphic Object into a PowerPoint File

Creating an Image File of a Project Schedule

Creating an Image File of a Project Schedule – Option 2

Creating an HTML Version of the Project Schedule

### Fire Protection Engineering

This video, created by professor Robert Zalosh at an FM Global test site, shows a warehouse fire and a selection of data that were superimposed on top of the footage, including heat transfer rate, temperature, number of sprinklers actuating, and time. Permission to use the video was granted by FM Global.

### Computer Science

The following two simulations were developed by Dr. Karen Lemone. The first simulation demonstrates the principle of mathematical induction. The second simulation demonstrates the principle of mathematical induction being used to show that the natural numbers are infinite.

Principle of Mathematical Induction

Principle of Mathematical Induction in Use

### Mathematical Sciences

The following animations and interactive applets were developed by Dr. Jacob Gagnon and his student, Anh Do. These applets require the Java plugin for your web browser. Some are available in 2 sizes in order to better fit the size of your computer screen.

- Applet #1
- The first interactive applet demonstrates the law of large numbers. Choose a density and let the number of terms get large. According to the law of large numbers, what value will the sample mean approach as n gets large?

Law of Large Numbers Applet: [1920x1080] [1280x720]

*GeoGebra source code*: [1920x1280] [1280x720]

- The first interactive applet demonstrates the law of large numbers. Choose a density and let the number of terms get large. According to the law of large numbers, what value will the sample mean approach as n gets large?
- Applet #2
- Applet #3
- A third applet demonstrates the relative frequency interpretation of probability using coin flips.

Coin Flip Animation (Hosted on MIT's web space)

- A third applet demonstrates the relative frequency interpretation of probability using coin flips.
- Applet #4
- The next animation shows the Central Limit Theorem applied to an uniform density. According to the central limit theorem, what do we expect to occur?

Central Limit Theorem Animation

- The next animation shows the Central Limit Theorem applied to an uniform density. According to the central limit theorem, what do we expect to occur?
- Applet #5
- Applet #6
- This applet shows an application of probability to video gaming.

Video game applet (Hosted on MIT's web space)

- This applet shows an application of probability to video gaming.
- Applet #7:

- The following applet shows the relationship between density histograms and density functions

Link: DensityHist

- The following applet shows the relationship between density histograms and density functions
- Applet #8:

- The following applet is a quiz of the relationship between density histograms and density functions

Link: Guess

- The following applet is a quiz of the relationship between density histograms and density functions
- Applet #9:

- The following applet shows the relationship between sample size, confidence level, and the confidence interval

Link: CIapp

- The following applet shows the relationship between sample size, confidence level, and the confidence interval
- Applet #10:

- This applet demonstrates the relationship between sample size, confidence level, and the prediction interval

Link: PIapp

- This applet demonstrates the relationship between sample size, confidence level, and the prediction interval
- Applet #11:

- In the next applet, we visualize common sampling strategies such as simple random sampling, cluster sampling, and stratified sampling

Link: SamplingApp

- In the next applet, we visualize common sampling strategies such as simple random sampling, cluster sampling, and stratified sampling
- Applet #12:

- The following applet allows us to visualize the bivariate normal density

Link: Sagetest

If the first link doesn't work try: Sagetestv2

- The following applet allows us to visualize the bivariate normal density
- Applet #13:

- Next, we have an interactive tutorial for the confidence interval for mu

Link: CItutorapp

- Next, we have an interactive tutorial for the confidence interval for mu
- Applet #14:

- The following applet gives us an interactive introduction to hypothesis testing for mu

Link: HypoApp

- The following applet gives us an interactive introduction to hypothesis testing for mu
- Applet #15:

- The next applet provides us with an interactive tutorial for forming prediction intervals

Link: PItutor

- The next applet provides us with an interactive tutorial for forming prediction intervals
- Applet #16:

- The following applet allows us to visualize the common mass functions and common density functions

Link: Density

Backup server: Density v2

- The following applet allows us to visualize the common mass functions and common density functions
- Applet #17:

- Here we have an interactive tutorial for forming the confidence interval for a population proportion

Link: CIptutorapp

- Here we have an interactive tutorial for forming the confidence interval for a population proportion
- Applet #18:

- The following applet gives students practice in using a t-table to calculate p-values

Link: Ttopapp

- The following applet gives students practice in using a t-table to calculate p-values
- Applet #19:

- Applet #20:

- This applet gives students practice in using the z-table.

Link: ztopapp

- This applet gives students practice in using the z-table.
- Applet #21:

- The following applet gives us an interactive introduction to hypothesis testing for a population proportion

Link: PropHypo

- The following applet gives us an interactive introduction to hypothesis testing for a population proportion
- Applet #22:

- This applet shows us an example of cluster sampling

Link: NewYork

- This applet shows us an example of cluster sampling
- Applet #23:

- The next applet quizzes the student on confidence intervals for mu

Link: CIquiz

- The next applet quizzes the student on confidence intervals for mu
- Applet #24:

- The following applet quizzes the student on confidence intervals for a population proportion

Link: CIpquiz

- The following applet quizzes the student on confidence intervals for a population proportion
- Applet #25:

- Here we have a quiz on prediction intervals

Link: PIquiz

- Here we have a quiz on prediction intervals
- Applet #26:

- The following applet quizzes the student on hypothesis testing for mu

Link: HypoQuiz

- The following applet quizzes the student on hypothesis testing for mu
- Applet #27:

- The next applet quizzes the student on hypothesis testing for a population proportion

Link: PropHypoQuiz

- The next applet quizzes the student on hypothesis testing for a population proportion
- Applet #28:

- The final applet illustrates the principle of blocking in experimental design

Link: Blocking

- The final applet illustrates the principle of blocking in experimental design

Last modified: Sep 25, 2012, 15:40 EDT