Why doesn't anyone tell me these things?

One of the frustrating things about getting my degree at a big research school, and now being in a department of people who are (mostly) more interested in research than teaching, is that I often feel like I'm on my own when it comes to finding resources that would be helpful for teaching economics. Because my institution is relatively teaching-oriented (just not really my department), I do feel like there are people around I can turn to for help with certain pedagogy-related issues in general (SDSU has a particularly awesome ITS crew!) but when it comes to teaching economics, not so much. I do pester the tch-econ list-serv when I have a specific question (and if any economists reading this are not subscribers, go sign up NOW), and there are the obvious sources like the Journal of Economic Education and the RFE teaching resources, and now Starting Point too, but I've also had to find a lot of resources on my own (and of course, one of the reasons I started this blog was to share what I find with others so we don't all have to re-invent the wheel!).

Occasionally, I come across something that just makes me feel dumb for not having known about it before. That happened this weekend, when I discovered the "Recommendations for Further Reading" section in the Journal of Economic Perspectives. Technically, I guess I 're'-discovered it, since I think that at one point in time, I did know what this section was about but I stopped getting a hard copy of the JEP years ago, and just never thought about how useful this would be for teaching. In case I'm not the only clueless one, this section specifically "will list readings that may be especially useful to teachers of undergraduate economics, as well as other articles that are of broader cultural interest. In general, the articles chosen will be expository or integrative and not focus on original research." Looking at the last several issues, many of the readings are reports or policy briefs from think tanks or government agencies (like the CBO, regional Feds, World Bank, etc.). Since I've been looking for "non-technical but still quantitative" articles to assign in my data class, and for "non-technical but still written by economists" articles to assign in my writing class, this is a godsend. There are also suggestions for more mainstream news articles, as well as interviews and conversations with prominent economists. 

 

Just wish someone had told me sooner...

Economists are such positive people...

As I have been developing this data course, I have been trying to keep in mind that this is an economics course, and the focus is supposed to be (as the title of the course states) the Collection and Use of Data in Economics. From a data standpoint, that means exposing students to the types of data that economists use (which is not quite the same thing as 'economic data' but that's a topic for another post). From an analysis standpoint, that means that we have to talk about inference from observational data, issues with identifying causation vs. just correlation, multiple regression, etc.

But I think it also means that we need to talk about the larger issue of what types of empirical questions do economists use data for? I'm planning to start the semester with a discussion of what is, and what isn't, an empirical question, and get the students thinking about what kinds of questions can and can't be answered with data. In economics, we talk about this in terms of positive and normative questions; most economists try to stay in the realm of positive analysis when we are doing data work but usually, our empirical analysis is still driven by normative questions (I usually refer to this as the 'why do we care' part of any research project). My plan is to have students first consider how values affect the trade-offs we are willing to make, and then we'll look at how data can inform those normative decisions. I think this will lead pretty naturally into a discussion of bias and how our normative values affect what data we are willing to believe, but I want students to think about how that goes both ways (i.e., prior beliefs may affect whether you accept some new piece of data but beliefs can also be affected by new data, and that's where a lot of social research comes in).

All of my students will have already taken two Principles courses in which they should have at least been exposed to the concepts of positive and normative analysis; however, most intro classes do little more than define positive as "what is" and normative as "what should be", which sort of drives me nuts because that seems so simplistic as to be pretty useless. I'm trying to find a simple paper or chapter that discusses these concepts more in the context of what economists do but haven't had any luck. If anyone out there knows of something that I could use, please let me know!

Choosing a textbook

I always think it's a bit odd when textbook reps come by my office in the middle of the semester - I listen politely and then tell them (every single time), "I won't be thinking about this until the summer." It puzzles me because they never seem to come at a time of year that actually makes sense; I mean, does anyone ever decide to adopt a new textbook in the middle of the term? I sort of assume most professors are like me in that even if they are considering switching textbooks (or they are prepping a new course for which they need to choose a text), they wait until summer to sit down and think about it. Which is probably why I've seen at least a couple blog posts on the subject lately - the Teaching Professor had a post about the role of the text in course planning, pointing out that many faculty design their courses around the text, which can lead to too much focus on content, and Lisa Lane has a post about her personal experience finding an exceptional text that has led her to re-think the focus of her course.

Like Lisa, I resist the idea of a textbook shaping my pedagogy. It has been years since I have taught to, or 'out of', a textbook; instead, I start with what and how I want to teach and I've generally just tried to find a book that matched what I wanted to do as closely as possible, though never with perfect success. I have learned that students don't like it if I assign a textbook and don't use it, or seem to be skipping around too much, so I've experimented with not requiring a textbook at all (though students still had an online text through Aplia). Students didn't seem to like that either so then I tried using a custom text; student complained that they couldn't sell it back to the bookstore but since the cost was so much lower in the first place, I don't have a ton of sympathy for that...

Anyway, I've spent the last several weeks looking at textbooks for the data and stats class. At first, I was mostly reading in order to re-acquaint myself with the content; now I'm starting to get serious about deciding on a specific book and I'm having a tough time (not to mention that my bookstore is not happy with me). Previous instructors haven't even used one text but simply pointed students to a few different books they might want to use to review stats and Excel, and I am beginning to understand that strategy; every book I've looked at has either been way more than needed for this course (and ridiculously expensive), or only covers one aspect (either stats, Excel or data) and not the others. It's feeling like it's going to be a long summer... 

Glutton for punishment

OK, someone really needs to save me from myself... Just to make life more interesting, I've decided that it would be cool to teach this new data course using team-based learning (TBL). For those not familiar with TBL, the basic idea is that students are organized into 5-7 person teams that stay together through the entire semester and then as much of the course as possible is built around team activities. So now, on top of trying to figure out the basic content and topics for a course I've never taught before, I'm also trying to figure out how to structure assignments and assessments using a method I've never used before.* Fun!

Actually, it's not quite as crazy as it sort of seems (at least, that's what I keep telling myself) - designing a team-based learning course basically requires backward design, which I was doing anyway, and in a TBL course, the instructor doesn't really do traditional lectures, which I really don't want to do. Instead, students acquire a lot of the basic content knowledge outside of class and then classes are built around simple assessments of that basic knowledge (to make sure students are really prepared), followed by application exercises. Since this is a course where the students are supposed to have already acquired much of the basic knowledge previously anyway (i.e., a lower-division stats class is a prerequisite), and the point is for students to get experience using that knowledge in the ways that economists do, I think the TBL structure actually is a good fit. Instead of me talking, students will spend almost all of the class time doing. Plus, the teams will mean I can give more complex assignments without a corresponding increase in time spent grading (one section will have 70 students and the other will have 60 - yes, I know that's totally nuts). I've still got a ton of things to figure out, and I have serious concerns about how this is going to go over with the students, but as I have been thinking about the types of activities I want students to do and how these will work in groups, I have to say that I'm pretty excited!

* I blame Bill Goffe for this - he mentioned TBL to me in an email a few months ago and then recently posted this link on the tch-econ listserv, showing TBL in action in a large lecture. If you're not familiar with the technique, I highly recommend checking out the video and the website.

Economics Education sessions at the Westerns

For those who will be in Portland, I went through the program and tried to find the econ ed sessions. Also, as the Western regional rep for CSWEP, I'll be 'hosting' the CSWEP breakfast on Thursday, July 1, 7-9am, so feel free to stop by and say hi!


Wednesday, June 30, 12:30–2:15 p.m.
CREATING UNDERGRADUATE RESEARCH AND FIELD EXPERIENCES (ROUNDTABLE)
Organizer: Melanie Fox Kean, Austin College, and Eric Dodge, Hanover College
Chair: Melanie Fox Kean, Austin College, and Eric Dodge, Hanover College
Papers: Elizabeth Perry-Sizemore, Randolph College, Mary O. Borg, University of North Florida, Stephen B. DeLoach, Elon University, and Sheila Kennison, Oklahoma State University
Creating Quality Undergraduate Research Programs in Economics
C. Beth Haynes, Brigham Young University Hawaii
One for the Money, Two for the 'Know,' Three to Get Ready, and Four to Go: Facilitating Undergraduate Research in Developing Countries
Eric Dodge, Hanover College
Dam Economics: A Dam Good Field Experience in the Pacific Northwest
Melanie Fox Kean, Austin College
Undergraduate Research Conferences as a Model for Fostering Research at All Phases of Student Learning


June 30, 2:30-4:15pm
TEACHING MONETARY POLICY: RESOURCES FOR EDUCATORS
Organizer: Yelena F. Takhtamanova, Federal Reserve Bank of San Francisco
Chair: Yelena F. Takhtamanova, Federal Reserve Bank of San Francisco
Papers: Jody Hoff, Federal Reserve Bank of San Francisco
Federal Reserve's Response to Crisis
Yelena F. Takhtamanova, Federal Reserve Bank of San Francisco
Experiential Learning Tools
Gary Zimmerman, Federal Reserve Bank of San Francisco
FRBSF Online Resources for Educators
Jeffrey A. Parker, Reed College
Educators' Perspective
Discussants: Sarah E. Tinkler, Portland State University
Peter Wilamoski, Threshold Group
Jenny Liu, Portland State University

June 30, 4:30–6:15 p.m.
TOPICS IN ECONOMIC EDUCATION
Organizer: Robert C. Dolan, University of Richmond
Chair: Robert C. Dolan, University of Richmond
Papers: Dean D. Croushore, University of Richmond, and Robert M. Schmidt, University of Richmond
RIDIT Analysis of Student Course Evaluations in Economics
Jeffrey A. Parker, Reed College, Jan Crouter, Whitman College, James Grant, Lewis and Clark College, and Jon Rivenburg, Reed College
Peer Effects: Evidence from Core Courses at Three Colleges
David H. Dean, University of Richmond, and Robert C. Dolan, University of Richmond
The Capstone Course in Economics
Discussants: Arthur H. Goldsmith, Washington & Lee University
Garrett Milam, University of Puget Sound
Nicholas Shunda, University of Redlands

Friday, July 2, 8:15–10:00 a.m.
TEACHING METHODOLOGY I
Chair: James P. McCoy, Murray State University
Papers: Gareth Paul Green, Seattle University, John C. Bean, Seattle University, and Dean Peterson, Seattle University
Using Public Policy Issues to Teach Quantitative Analysis in Economics
Martin I. Milkman, Murray State University, and James P. McCoy, Murray State University
Exemplary Programs in Preparing Graduate Assistants to Teach Economics
Paul R. Johnson, University of Alaska, Anchorage
A Classroom Business Cycle Experiment
Discussants: from above participants

July 2, 10:15 a.m.–12:00 n.
TOPICS IN ECONOMICS EDUCATION
Organizer: Sarah E. Tinkler, Portland State University
Chair: Sarah E. Tinkler, Portland State University
Papers: Clifford Nowell, Weber State University, and Lewis R. Gale IV, Weber State University
Correcting Student Evaluations of Teaching for Missing Data: Online versus Face-to-Face Evaluations
James Woods, Portland State University
Online and In-Class Exams as a Method of Assigning Course Grades: Are They Equivalent?
Sarah E. Tinkler, Portland State University
Can Students Read College-Level Economics Textbooks?
Discussants: James Woods, Portland State University
Clifford Nowell, Weber State University
Martin I. Milkman, Murray State University
Tim Anderson, Portland State University

July 2, 2:30–4:15 p.m.
STARTING POINT ECONOMICS: A SOURCE FOR PEDAGOGICAL RESOURCES
Organizer: KimMarie McGoldrick, University of Richmond
Chair: KimMarie McGoldrick, University of Richmond
Papers: KimMarie McGoldrick, University of Richmond
Starting Point---Teaching and Learning Economics
KimMarie McGoldrick, University of Richmond
Cooperative Learning in Economics
Andrea L. Ziegert, Denison University
Service-Learning in Economics
Mark H. Maier, Glendale Community College
Interactive Lecture Demonstrations
Discussants: Samuel K. Allen, Virginia Military Institute
Genevieve Briand, Eastern Washington University
Elizabeth Perry-Sizemore, Randolph College
Steven J. Balassi, St. Mary's College of California

July 2, 4:30–6:15 p.m.
ASSESSMENT TOOLS AND THE TEACHING INNOVATIONS PROGRAM
Organizer: KimMarie McGoldrick, University of Richmond
Chair: Steven J. Balassi, St. Mary's College of California
Papers: William B. Walstad, University of Nebraska
An Assessment of the Teaching Innovations Program for Economics Faculty
Lee Erickson, Taylor University
Comparing Formative Assessments: Daily In-class versus Weekly On-line
Felix B. Kwan, Maryville University
An Innovative Course-Assessment Tool: Letters to Incoming Students
Geetha Rajaram, Whittier College
Teaching Econometrics with Summative and Formative Assessment
Discussants: Thomas White, Assumption College
Beth Wilson, Humboldt State University
Hisaya Kitaoka, Franklin College
Julie K. Smith, Lafayette Colleg

Saturday, July 3, 10:15 a.m.–12:00 n.
TEACHING METHODOLOGY II
Chair: Mark W. Frank, Sam Houston State University
Papers: Genevieve Briand, Eastern Washington University, and R. Carter Hill, Louisiana State University
Teaching Basic Econometric Concepts Using Excel Monte Carlo Simulations
David F. Kauper, University of the Pacific
Teaching Profit Seeking as the Source of Growth
Satyajit Ghosh, University of Scranton, and Sarah Ghosh, University of Scranton
Spreadsheet Based Interactive Teaching Strategies and Assessment of Learning Outcomes
Sean Jasso, Pepperdine University
Demystifying the Pedagogy of Globalization: A Contemporary Approach to Effective Learning
Discussants: Mark W. Frank, Sam Houston State University
Satyajit Ghosh, University of Scranton
Sean Jasso, Pepperdine University
David F. Kauper, University of the Pacific

How much weight do you give evaluations?

By now, a lot of academics (or at least academic economists) have heard about Scott Carrell and James West's paper on professor quality. They use data from the Air Force Academy (where students are randomly assigned to core courses and take common exams) and find that the 'value-added' of professors in intro courses is both positively correlated with student evaluations and negatively correlated with 'value-added' in follow-on courses (which the authors talk about as evidence of 'deep learning'). Basically, professors who seem to be better at inducing 'deep learning' in their intro students are also more likely to get lower evaluations from those students.

On the one hand, I have to say that this feels kind of validating for people like me - that is, I care a lot about helping my students learn to think critically and I think I put a lot of effort into trying to foster deep learning, rather than allowing my students to just memorize stuff, but I rarely get stellar evaluations (at least in my Principles course) and I've often told myself that my focus on deeper learning is one of the reasons why my evaluations aren't as high as some of my colleagues. Certainly, some of the open-ended comments from students on the anonymous department evaluations could be interpreted as them resenting that I ask them to actually think.

But on the other hand, I can't be quite so cynical as to blame it all on my students. I think about teachers, like those in Ken Bain's What the Best College Teachers Do, and I know that they are able to not only promote deep learning but they are able to do so in a way that students appreciate and respond to. So clearly, I have work to do...

But I have to say, one of the best things about tenure is that I don't really have to care about my teaching evaluations. I know that is exactly the kind of thing that makes a lot of people think tenure is a bad thing, and I do realize that for some people, the 'threat' of bad evaluations is the only thing motivating them to care about their teaching at all. But a) I don't think anyone could seriously argue that me not caring about my evaluations is equivalent to me not caring about teaching and b) since I'm going to keep working on my teaching regardless, the anonymous student evaluations done for my department tend to just stress me out without giving me much useful feedback. I get much more useful information from the end-of-course surveys I have students do that are tailored to the individual courses, which I will be talking more about soon...

Quantitative methods in economics

I should clarify something I said last week about how this data and statistics course I'm prepping isn't really a standard course: I do know there are lots of econ departments that offer an economic statistics course that is a step below econometrics. I guess what I was thinking is that the intention behind this course was specifically to give students tangible skills working with data, so there is supposed to be a heavy emphasis on finding and accessing economic data and using Excel to manipulate that data, rather than on formulas and statistical theory (which students presumably should have already had anyway, in a lower-division required statistics course). But my impression is that a lot of econ statistics courses for majors at other schools are really more stats courses, just with econ-related examples*.

The interesting thing is that the Siegfried, et al, report ("The Status and Prospects of the Economics Major, JEE, Summer 1991) discusses this very situation (emphasis mine):

Originally conceived as a means of providing students with a sufficient empirical foundation to enrich their understanding and facilitate their active participation in applied courses, the [quantitative methods] requirement all too often fails to fulfill this purpose. Although this requirement presupposes the development of skills in working with real data, contrived numerical examples are more common in these courses... These courses are often overloaded and taught at too fast a pace to adequately prepare students for the empirical dimension of elective courses. Frequently, data appraisal (e.g., survey design, sampling procedures, data accuracy) is squeezed out of the course, and some quantitative methods courses fail to cover adequately the philosophy, appropriate use, and limitations of hypothesis testing and regression analysis. Sophistication in empirical work requires more than just training in statistics. It requires attention to observation skills, measurement problems, and empirical judgment. Students need guidance on how to judge the quality of data, and how to identify evidence that would help to resolve an empirical dispute.

I think that this is what my department was likely striving for when we originally adopted this course. Over the years, instructors have tried to retain the emphasis on data but the content seems to be more along the lines of 'contrived numerical examples'; students use lots of real data and have assignments to make graphs and charts in Excel but from what I can tell, there is still more focus on formulas and statistical concepts than the 'art' of using data to resolve economic questions.

As I plan this course, I am definitely striving for something more along the lines of what Siegfried, et al, suggest:

Rather than view this as a matter of learning statistics, we need to ask what it is that student must know to function as economists. The foundation of empirical methods depends on (1) knowing something about the measurement of economic variables (methods of data collection, reliability, etc.); (2) being able to organize, work with, and manipulate data for purposes of comparison; (3) the capacity to test hypotheses with empirical data; and (4) knowing how to interpret the results of various statistical procedures.

In the framework of backward design, that pretty much lays out my learning outcomes (what I want my students to be able to do). Now I just have to figure out how to achieve this...

* If I am wrong about this, I would really love to hear from people who teach more data- and application-driven courses. As an undergrad advisor, I've seen a lot of requests from transfer students who want to take an econ stats course somewhere else and have it count the same as our course but they rarely look comparable (or at least, they don't look like the course that we think we have, though now that I'm taking a closer look at what my colleagues have been teaching, I think the courses at other schools may be closer than we thought).