Nabamita Dutta and James Murray
Supported by a Lesson Study Project 2013-2014 Grant by the UWL Center for Advancing Teaching and Learning
January 28, 2015
Abstract: In introductory economics classes, we emphasize graphical modeling, which for many students is a new way of framing problems, thinking about them, and solving them. We have learned in past years by assessing these courses that students struggle with modeling. We have made some improvement in this area, but we recently learned that even when students correctly set up and solve a graphical modeling problem, they fail to connect the result to the real world economic problem. For example, students are often able to correctly model and solve a problem involving taxes, but when in a separate question they are asked to describe the implications of the same tax policy, their answers are inconsistent with the results they had just found. Often answers showed little relationship to the previous analysis.
We created a lesson that challenges students to integrate graphical modeling and economic reasoning in the context of an authentic scenario. Students present their case in a manner appropriate to a non-expert audience while still using economic reasoning based on graphical modeling. In our lesson, the instructor demonstrates this thought process with a few examples. Then we give in-class group exercises that ask the students to do the same. In this report, we present our lesson, some findings on our students' thought processes, and identify some common challenges in student learning and hurdles we still face as instructors.
Taggert Brooks, Elizabeth Knowles, Bryan Kopp, James Murray, and Laurie Strangman
Supported by a Lesson Study Project 2012-2013 Grant by the UWL Center for Advancing Teaching and Learning
August 1, 2013
Abstract: We developed and implemented a systematic and efficient approach to give feedback on student writing in a business research methods course. In this lesson study, we investigate how students respond to this feedback. The lesson takes place at mid-semester, after students have spent some time developing their research question and reviewing the literature. At the time of our classroom observation, the students receive the first feedback of their first draft of the introduction section of their final paper. We observed their conversations upon receiving the feedback and noted how it influenced their revision plans. We conducted our lesson study over two semesters, Fall 2012 and Spring 2013.
To make the process of giving feedback efficient, we developed a database of comments on student writing which were specific to the objectives of the assignment. There are seven goals of the introduction assignment, some of which are specific to an introduction section of a research project, such as “State the purpose of your research project”, and some of which are very general, such as “Communicate in a clear and meaningful way.” Using these goals as the traits for a rubric, we developed a set of feedback comments that align to each goal suggesting improvements or noting when the objective was met. While the comments are specific enough to address specific goals of the assignment and common writing problems, they were general enough so that they could be used for any student’s writing for the given assignment. We use text-expanding software (Breevy for Windows, Text-Expander for Mac) that allows the instructor to quickly populate a letter to each student with a set of comments appropriate for their submission.
Our classroom investigation revealed some challenges in giving feedback that effectively guides students on how to revise their work. One significant example concerns how students communicate purpose. While students may have attempted to communicate a specific purpose in one part of their introduction, often the introduction as a whole lacked focus. Even after receiving feedback, students were largely unable to recognize this problem or understand what kind of revision was appropriate.
Elizabeth Knowles and James Murray
Supported by a Lesson Study Project 2011-2012 Grant by the UWL Center for Advancing Teaching and Learning
August 23, 2012
Summary: Introductory statistics classes typically emphasize computation and implementation procedures for a number of statistical tests. While it is essential to build these skills before achieving higher-order critical thinking skills, students often struggle in subsequent research methods courses when expected to select appropriate statistical tests to answer research questions. This requires an understanding of how statistical methods are related to one another; and to achieve this, students must develop a more advanced organization of knowledge. We designed a lesson to help students build a knowledge organization to achieve this outcome, and observed students to better understand their thought processes. We share our thought process map for selecting a statistical test, report on the impact it had for our students, and offer suggestions for improving the lesson. In addition, we describe the thought processes students used, both before and after being exposed to the thought process map, and identify sources of confusion revealed through the lesson study process. These include: when to apply an independent-samples test versus a paired-samples test, how the identification of scale of measurement led students to choose the wrong statistical method, the difficulty students had recognizing or defining what the variables in a problem were, and the lack of understanding of the difference between statistical language and colloquial language.
Summary: This assessment tool measures students' ability to use models to predict the short-run effects of a change in international conditions on a country's macroeconomy and exchange rate. The task measures students' abilities to think about multiple dimensions of the situation using multiple macroeconomic models. One challenge students face is deciding what model to use to answer each aspect of the situation. I document below my teaching strategies prior to assessment, student performance on the task, my reflection and conclusions from the assessments, and strategies to improve student learning.
Summary: The assessment tool measures students' ability to use multiple models to evaluate the impact of a shock on financial markets and the macroeconomy. Students also use these models to prescribe monetary policy to counteract the effects of the shock. One challenge students face in this task is deciding what model to use for addressing each aspect of the situation. I document below my teaching strategies prior to assessment, my students' performance on the task, my reflection and conclusions from the assessment, and strategies to improve student learning.
Summary: This assessment exercise is a follow-up from the Economics Department Competency in the Major (CITM) assessment processes conducted in Spring 2011, of which a major component included a class-embedded assessment exercise in ECO 305: Intermediate Macroeconomics, at the time taught by another instructor. The general findings from that assessment were that students did not understand well the assumptions behind various theories for economic growth and they had difficulty applying different models to the same scenario and understanding the different conclusions that would be reached.
The present assessment task extends the Spring 2011 CITM assessment task to three models of economic growth (CITM only looked at two), and asked students to list all the strengths, weaknesses, and implications of each model. While the present task asks much more from the students, the task was also part of a take-home exam, so students had access to their textbook and class notes and they had more time to answer the questions. Still, successfully answer these questions requires students to have a full understanding of each model. Lists of these answers do not appear anywhere in the notes or textbook, but instead would need to be pieced together based on an understanding of the larger picture. I document below my teaching strategies prior to assessment, my students' performance on the task, my reflection and conclusions from the assessment, and strategies to improve student learning.
Fall 2009 - Spring 2011
Summary: I administered similar assessment tasks in my introductory macroeconomics classes over four semesters from Fall 2009 to Spring 2011. The assessment task targeted a task and topic many introductory students find challenging: applying the supply and demand models for foreign currency exchange to make predictions for relative currency appreciation or depreciation. I document below my teaching strategies prior to assessment, my reflection and conclusions from previous assessments, student performance on the task, and updated teaching strategies to improve student learning. By the end of the two year assessment process, I had developed teaching strategies that involved interleaving exchange rate models throughout the semester and practice problem strategies that improved my students understanding of graphical modeling more generally.
John Nunley and James Murray
Supported by a 2013 Kazanjian Economic Foundation Grant
Summary: The Pencasts on this website over most of the content that is commonly taught in six college-level economics courses that typically form the core of the curriculum for a major in economics. A 'Pencast' is a video of someone writing on a notebook page, while describing what they are writing. It is made with a special ballpoint pen, called a SmartPen and made by LiveScribe, that has a small video camera looking at the tip and a microphone to record audio. Each course on this site has between 8-15 major units which coincide roughly with a chapter of a textbook. Each unit has several Pencasts, most between 3-5 minutes, covering most of the content that would typically appear in such a chapter in an economics textbook. The collection of Pencasts in each course should be able to complement most of the core content in a face-to-face class or online class, or facilitate an independent study in the given course.
Summary: This work in progress is a collection of applied statistics tutorials for business research methods, using the R statistical software package. These tutorials are more than just directions on using software. The focus is on teaching statistics with a hands-on approach and real data. Each tutorial is short, focused, and self-contained. They are designed so that students and business professionals engaged in conducting data analysis can quickly learn the statistical concepts and technological tool to produce their own applied statistics research.