I have come to believe that a syllabus should be a dynamic learning tool. To that end on the first day of class I randomly select some students to download my syllabus. Using the classroom projection system, they explore in the syllabus embedded links to such things as a paper I wrote about how I teach and they begin using a tool (Research Randomizer) for drawing random samples and for randomly assigning participants to conditions.
Here is the syllabus I use in my PSY205 “Statistics and Experimental Design Course.”
I am moving towards requiring that all my students demonstrate to me minimal mastery of my technology enhanced teaching and the learning tools which I introduce into the classroom.
Here is an example of a Quizlet benchmark: Example 1: Quizlet.
How helpful are these links? How might they be improved?
I also am increasingly incorporating screencasts made by me (or by my students) into the class as additional instructional support—especially as I teach SPSS. Though I realize that there are an abundance of such resources on YouTube (and even on LinkedIn!), I still see some value in my personally producing them (or having my students do so).
Here are some screen casts that Simpson research assistants Tia and Ariana made for me to demonstrate their mastery of using screen casting software tools:
And here is one of my SPSS screen casts made at home with the help of Leo the Dog:
Should I continue to produce these even though their production quality may not be “professional”?
Below is a first draft outline of an ebook I am contemplating writing. I share it at this time welcoming feedback. I shall use this draft as part as a review for my PSY205 students. Here is a brief description of HOW I teach the course.
Each hyperlink is a “module. Thanks to Arianna, Tia, and Lizzy for helping me create this draft (while I was away from the office).
What data analysis should I use?: Test your knowledge by clicking on the link. Eventually I shall incorporate a flow chart / decision tree here.
- Teaching Tools: SPSS, inStat, starQuiz, Camtasia and Research Randomizer.
- Augmenting My Teaching Capabilities: Top Technology Learning Tools Revisited.
- On Engaging Students (Part 2): Adventures with StarQuiz and SPSS
- Changes: How much tinkering should one do with a course that seems to work well?
- Learning by Teaching: Alison and Lizzy’s Guide to Using SPSS Data Analysis for Simple Linear Regression
- Retrospective Thinking: How much tinkering should one do with a course that seems to work well?
- Two-way Between Subjects ANOVA Using SPSS (Part 1)
- What Questions can you Answer with your Data? Using SPSS to guide you.
- Review of One-way Between Subjects ANOVA using SPSS
- t-Time: Three Short SPSS Screencasts for PSY205
- Still Looking for ways to Improve Courses After 36 Years of Teaching (Part 1 of 2)
- Retooling and Sharpening the Saw
- Something Old and Something New: A brief Introduction to Effect Size Statistics
I’m glancing at a research article “The Pandora Effect: The Power and Peril of Curiosity” by Christopher K. Hsee and Bowen Ruan recently published in the journal Psychological Science. Since my Oberlin undergraduate days I’ve been interested in the topics of curiosity and intrinsic motivation. Hence, my nom de plume “Curious David.” I wonder how many of my students are familiar with the Greek myth of this first human woman created by the gods. I suspect that more of them are familiar with the radio streaming service by that name.
I’ll probably use the article in my PSY205 course “Statistics and Experimental Design” in several ways. The studies are methodologically simple. They use data analyses I teach in the course. They illustrate the so-called “New Statistics“. In addition, they are amenable to plausible alternative hypotheses. My quick reading suggests additional studies which could be done—-here by my students..
The first and third experiments’ results sections lend themselves well to illustrating how to check the reported effect sizes using the effect size calculators I introduced in an earlier blog piece. I’ll “borrow” and modify the theme of these studies when I create the exam over one-way between subjects ANOVA which I am scheduled to give tomorrow. That is, I’ll in essence propose a study that could/should be done here at Carroll.
I’ll probably have to defer until this summer mastering the intricacies of “The New Statistics” championed by Geoff Cumming. I want to avoid throwing the baby out with the bath water as I attend to blend the revolution in data analysis into my courses. However, here is a first attempt to introduce the concept, calculation, and interpretation of effect sizes into my teaching. Below the screen cast are five very useful effect size online calculators.
Here are five effect size calculators I have found useful enough to share with my students in Psychology 205.
Effect Size Calculators
- Becker: http://www.uccs.edu/~lbecker/
- Hong Kong http://www.polyu.edu.hk/mm/effectsizefaqs/calculator/calculator.html
- Campbell Collaboration: http://www.campbellcollaboration.org/resources/effect_size_input.php
- Psychometrica http://www.psychometrica.de/effect_size.html
- Cognitive Flexibility http://www.cognitiveflexibility.org/effectsize/
I’ve been so busy lately that yesterday I almost didn’t have time to change out of my academic regalia before beginning my PSY205 Statistics and Experimental Design course. Thanks to Jenny Percy for capturing this “precious moment”.
My social media day usually begins at 5:30 a.m. with a quick look at my Carroll email, my Twitter feed, my Facebook and LinkedIn accounts. If I see an article from the Chronicle of Higher Education or Inside Higher Education worth sharing, I pass it on to Twitter, LinkedIn and Facebook followers. My restricted “Twitter feed” often appears on the left of the window of applications I am using like this WordPress software.
Here is what I mean (courtesy of my Snagit capturing software and Screencast.com).
Twitter primarily serves me as a personal professional development tool. Facebook is a rich source for my staying in touch with alumni (NO, Kim and Ryan, I DO NOT WANT a party in 2019). LinkedIn has proven to be a wonderful way to reconnect and stay connected to Alumni —So great reconnecting with you recently, Dave Verban!—, Members of the Board of Trustees, and Schneider Consulting Clients.
Time to meet with my colleague and FB “friend” Peggy Kasimatis.
Carroll has become a special place to me. I have been influenced greatly by its students, faculty, staff, administration, and alumni. By its traditions, theater productions and its music.
There are lots of changes these days occurring at Carroll. Some of them are physical, others organizational. Some things never change (read between the lines:); some things never should change.
I asked research assistants Alison and Lizzy to document some of the physical changes. Here is what they produced:
I continue to experiment with my “best” course (Statistics and Experimental Design) to make it better by finding the right balance of technology-assisted and personally- delivered instruction. Here is how I have taught it in the past. I have been pleased at the helpfulness, useful feedback and receptiveness of students past and present as I experiment.
This semester I was influenced in what did the during the first week of class by a Chronicle of Higher Education thought piece about making best use of the first class day.
I began the class wanting to test the sound systems so I shared this amazing tribute to David Bowie:
Instead of calling out the class list to take attendance I give a quiz every day with immediate feedback which goes into a student portfolio. I also call upon a random group of students (selected by students using random sampling software to select the lucky students). Two students won free copies of my workbook!
Since then I have introduced them to SPSS and InStat (i.e. that the latter software exists) and to Survey Monkey.
Here is something Lizzy and Alison produced illustrating one of these tools:
I have also shown them Quizlet, started urging them to read germane articles from the Chronicle of Higher Education, and attempted to alert them to ethical issues about research by sharing lessons I have learned from Diederik Stapel.
To date, I seem to have highly engaged students learning and eager to learn. The first exam is February 10.
I am now invite their feedback and yours.
One of the many lessons I’ve learned from many years of teaching is how much I learn through the act of teaching. It recently occurred to me that one way to facilitate my students’ learning of statistics is to position them to teach it. Below is a video created by two of my students illustrating how to use and interpret SPSS’s procedures for creating a scatter plot, calculating Pearson’s r, and, if warranted, performing a simple linear regression. Here is what they wrote and did:
This video was designed to help demonstrate an SPSS analysis for a simple linear regression. This video helps to show the steps to obtain an analysis of data, but the steps are also printed below for further assistance.
Step 1) Enter the names of the data into the variable view. For our data, the first name is Global Awareness which is the “independent variable” while the second name is “Satisfaction” which is the dependent variable. The data will come up automatically as numeric, but change the decimals to 0. Once complete hit the data view.
Step 2) Enter data under the appropriate name.
Step 3) To see if several of Pearson r’s assumptions are met first create a scatter plot. To create the scatter plot, go underneath graphs, legacy dialogues, and then click on scatter/dot. Then a pop up menu will appear and select simple scatterplot, which is the first option. Then SPSS will ask you for the x and y axis. The X is the independent variable while the Y is the dependent variable.
Step 4) When the scatter plot appears, notice the direction (positive or negative), the strength of the scatter plot, and if the scatter plot is linear. If the scatter plot is linear, calculate Pearson’s r.
Step 5) To calculate Pearson’s r, go under Analyze, Correlate, than select bi-variate, and a pop up menu will ask you for the independent and dependent variable. Make sure the Pearson box is selected as well as the two tailed box.
Step 6) To calculate the linear regression, go under Analyze, Regression, and select linear. A pop up menu will ask for the independent and dependent variable.
To understand the data:
Pearson’s r indicates how strong the two variables are correlated.
r squared is the coefficient of determination which communicates how much of the Y variable is explainable by knowing the X variable.
The standard error of estimate is the range around a predicted score within which you are sure with a specified degree of certainty that the predicted score will indeed fall.
Underneath the coefficients table in the B column, one is able to see the y predicted equation (Ypredicted = Bx + A). B is going to be the next to the independent variable while the A is going to be next to the constant.
I continue to experiment with my “best” course to make it better by finding the right balance of technology-assisted and personally- delivered instruction. I have been pleased at the helpfulness, useful feedback and receptiveness of students as we “experiment.”
I just made a Screenflow screencast of what I taught in lab this week (using SPSS to create a scatterplot, calculate Pearson’s r, and do simple linear regression).
This time I published it on YouTube rather than on Vimeo.
I also, in response to student feedback, created some Quizlet study materials. Click the Quizlet link to try them.
A next step will be to involve students in the creation of such materials—rather than my doing so. That may wait until next year, however, since I want to introduce this year’s students to instruction in using Survey Monkey survey creation software.
Please go here to evaluate the video shown above
It would be fun to teach an entire course on these topics.