Pedagogy in Action > Library > Developing Quantitative Reasoning > QR Across the Curriculum Profiles > Jim Yih-Jin Young, Sociology

Jim Yih-Jin Young, Sociology

Jim Young is a professor of Sociology at Nassau Community College, a public 2-year institution that is part of the State University of New York (SUNY) system. Information for this case study was obtained from an interview conducted on September 6th, 2013. This page is part of a collection of profiles about a variety of techniques for integrating Quantitative Reasoning (QR) across the curriculum.

Jump down to Design and Implementation of QR Goals | Key QR Assignment of the Course | Challenges | Advice | Documents

Overview and Context

About the Course

Sociology of Health and Illness is an upper-level course that I have taught for about 15 years. The students are a very diverse group in terms of their academic backgrounds, and usually number around 30-33. The students come mostly from different disciplines because we do not have a sociology major. Many are from health-related departments. Some students are enrolled in four-year nursing programs at other institutions. All of the students will have had an introductory sociology course, as this is a prerequisite.

Key QR Assignment Description (links to section in this page)

How Quantitative Reasoning (QR) and Literacy are Approached

I teach both quantitative literacy and quantitative reasoning. In my mind, these two cannot exist without one another. Quantitative literacy is more basic, but it is needed in order to be able to function at a higher reasoning level. An example of quantitative literacy is understanding summary statistics. An example of quantitative reasoning is being able to interpret numbers in a table and place them in context. By having this higher level reasoning ability, students are able to consider quantitative information and make viable arguments.

Design and Implementation of QR Goals

Motivation to integrate QR

I want students to be able to interpret quantitative information because the world is now organized largely with numbers. Every time we read a newspaper or watch TV, we are presented with them. Students will need to be able to understand quantitative information throughout their lives.

Another motivation was that in about 2009 the State University of New York (SUNY) administration implemented a quantitative literacy requirement, meaning that it had to be incorporated into all courses. Part of my role at my college has been to help other teachers incorporate quantitative literacy and reasoning into their classes.

QR goals

My main goal is for students to learn how to do research in the social sciences, so that they will be able to answer questions and solve problems. I want students to learn how to conduct research in such a way that they will be able to apply it in other disciplines, such as political science or economics. The principles of finding information, creating knowledge, and interpreting data are all the same, although the subject areas may be different.

My quantitative reasoning goals fit well with my goals for teaching the subject matter of the course, because in order to understand the substance, it is important to be able to interpret quantitative information. The textbook, for example, is full of tables and I do not want students to skip over these in their readings.

Pedagogic approaches used

I believe it is important to build an openly communicative and encouraging relationship with the students from the start. On day one, I explain my expectations and the course goals. By being explicit about these things up front, students are better informed about what to expect and this affects their motivational level. Another way I build their confidence is by explaining how to do well in the class: attend regularly and take good notes.

Quite a few of our students tend to have a math phobia, and so I try to be encouraging; so that they believe that they can handle it. I let them know that the quantitative aspects will not be harder than addition and subtraction, which can be done with a basic calculator. I explain why they should focus on this now–that knowing the quantitative material will help them in more advanced classes, and that without it, those courses will be more challenging.

Knowing the course is successful

The key assignment is a semester-long research project that culminates in a final paper. By reading these student papers, I know whether or not they understand and can interpret information correctly. As an example, students must present their findings on three variables for the assignment described below. They must present data in a frequency distribution and interpret what it says. In the illustration below, they would need to be able to interpret how the variation in health status is due to one's social class using percentage difference analysis. Assessing their success in these areas is straightforward.

I can also tell how the course is going by interacting with the students in classroom exercises and during their presentations. We create some of the tables for their final paper during class. I walk around helping students and find out how they are doing. I ask that they verify having done the calculations correctly before leaving for the day when we analyze the data in class. If they get data interpretation wrong during their presentation a week before they turn in the paper, then I correct them at that time so that they have a chance to interpret it correctly in the paper. In this way I can see what students are struggling with and what is going well.

Key QR Assignment of the Course

The key assignment is a semester-long research project where students design the project, collect data, interpret it, and report their findings in a research paper. The topics are chosen by the students, and are related to the sociology of health.

This research paper assignment involves students designing and administering a 3-question survey, analyzing the data, and writing about the results. Since the focus of the class is Sociology of Health and Illness, an example topic would be, "How does health vary by social class and level of education?" Each student selects their own topic, but I provide guidance and ideas.

In this project, students learn how to do research in the social sciences. Students select a topic early in the course, conduct a literature review, design a survey based on 3 variables, collect survey data throughout the semester, analyze the data together in class, make a presentation, and write their paper.

For the survey collection, students interview 50 to 60 people and ask them a series of questions based on the variables they elected to study. So in the above example, students would ask questions pertaining to health, social class, and level of education. Due to the time involved, students often interview people in a variety of informal settings such as in parking lots, on the bus, or on campus. The students receive instruction about random sampling, and about being careful about writing up the results given that their survey data will not be random or representative of a specific population.

For the data analysis, students first look at two variables, such as social class and health. They create a cross-tabulation with a chi-square statistic, and learn how to interpret that statistic. Then they are asked to think deeply about why these two variables might be related. In order to explore that question, they bring in their third variable, such as education. They do other crosstabs tables, for instance comparing the level of education—high education vs. low education–to social class and to health status. Once they have analyzed their data, they write up their report, which includes an introduction, literature review, discussion of the data source, a hypothesis, data tables, methods, and interpretations of the results.

They must use quantitative reasoning to interpret the final results. They must analyze whether the relationship between social class and health can be explained by educational level. This helps them see that while there may be a relationship between X and Y, we often must dig deeper to understand the relationship. Why does X affect Y? What is the mechanism?

In order to help them with the statistics, I spend 2 or 3 hours per semester going over basic statistics. I do not go into the depths of statistical theory as a methods course would since this is not the course's purpose. We don't go into the details, for example, as to why the chi-squared statistic is determined, but we talk about the criteria for assessing a relationship between two variables.

For a few years, I asked students to use Stata to analyze the data, but then I realized that it is better for them to do this by hand. I want them to know how to compute the statistics from scratch. It does not take them too long because they are only analyzing 50 surveys. This experience calculating the statistics by hand is very valuable for the students.

For the structure of the research paper (Microsoft Word 2007 (.docx) 14kB Oct15 13), students visit a website I created that shows details of the assignment, including the important sections they must include. The papers must be 8 to 10 pages long including tables and citations.

The paper is 15% of their grade. They have to also make an oral presentation, which is about 5% of their total grade. So in total this project constitutes about 20% of their overall grade.


  • The level of student preparation varies greatly. It is challenging to teach a very diverse set of students with regards to quantitative preparation. For example, some students don't know how to use a calculator and need lots of help with basic skills. Other students are very good at using a calculator and don't need much instruction. Nearly all students know how to surf the Internet, and are computer savvy, but that does not necessarily help them in dealing with quantitative materials.
  • Student push-back. Some students simply do not like doing quantitative work. Some do, but many do not. Good communication with students at the beginning of the course helps to ease this resistance.


  • Expect to enjoy teaching QR. I find it very enjoyable to teach quantitative literacy and reasoning. I think that if faculty members are ready, they should go ahead and do it.
  • Learn from others and ask for feedback. Talk to colleagues or others with more experience teaching quantitative reasoning. Present your materials to them and ask for feedback. In this way you can benefit from what they have learned.
  • Start simple. Start with materials that are reasonable and not too complicated. If you present materials that are too hard, it will not work. For example, at the sophomore level, you do not want to teach regression. You have to start with something basic, and work up from there.


Syllabus for Sociology of Health and Illness (See link on this page to "Soc 225 Syllabus")

Resources for the research paper assignment from the course web page (see link to "Group Project".)

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