Summit-P Case Studies: Initiating a Student Exchange Program and Creating a Faculty Learning Community
Bryan D. Poole, Associate Professor of Psychology & Caroline Maher-Boulis, Professor of Mathematics, Lee University
Part I: Initiating a Student Exchange Program
Intended Audience: Teachers who want to create interdisciplinary collaboration opportunities to improve learning.
OVERVIEW
This case study describes how to create and sustain a student-focused, interdisciplinary collaboration opportunity to improve student learning. Practical advice is provided to help readers create similar opportunities at their institutions.
KEY POINTS
The Student Exchange Program (SEP) was designed to give mathematics and social science majors opportunities to collaborate and learn from one another. Creating such a program involves:
- Intentional recruitment
- Appropriate incentives
- Learning-focused goals and activities
- Frequent assessment and program revision
CASE STUDY
As someone who frequently teaches research methods and statistics courses for psychology majors, I have watched countless students struggle to recall material from their prerequisite mathematics courses and apply that knowledge in my classes. Standard deviation? “Never heard of it.” Normal distribution? “Isn’t that the curve with percentages to memorize?” Readers of this case study may not teach research methods or statistics, but I wager that many faculty have experienced similar issues with students’ knowledge recall, transfer, and application.
In 2017, while working within a National Consortium for Synergistic Undergraduate Mathematics via Multi-institutional Teaching Partnerships (SUMMIT-P), I helped establish an interdisciplinary collaboration experience for undergraduate students to begin addressing this problem. This experience came to be known as the Student Exchange Program (SEP), a name borrowed from programs that allow foreign exchange students to learn while living in a completely different culture. As part of a grant funded by the National Science Foundation, the SEP was designed to help students majoring in mathematics to better understand how statistics are used by students majoring in social science, and to help social science majors understand the mathematical side of statistics.
The purpose of this case study is to provide a brief overview of the SEP. However, because details about the SEP have been published by Poole, Turner, and Maher-Boulis (2020), this case study will primarily focus on how to run a similar program at other institutions.
Intentional Recruitment
Each semester we recruited 4-6 students majoring in mathematics and social sciences by contacting students who demonstrated interest or expertise in statistics. Our ability to recruit additional students was limited by grant funds, student interest, and by how much time faculty could devote to supervising students. Regardless of how many students we recruited, we paired one student majoring in one discipline with at least one student majoring in a different discipline to ensure interdisciplinary crosstalk. Having more than two students on a team is possible, but oftentimes there is an imbalance of student contributions when the teams are uneven or too large.
Faculty at other institutions could easily recruit students majoring in disciplines other than mathematics and social sciences to achieve similar goals. For example, students majoring in nursing would benefit from collaboration with students majoring in psychology, and vice versa. In any case, it is important to keep the program small to allow a faculty supervisor to pay careful attention to each project, and to protect faculty time.
Appropriate Incentives
When interviewing and recruiting students, we indicated that participants would be paid a minimum of $10 per hour for their time. In addition, we indicated that students would be working together for 2-4 hours for 10-12 weeks. We were fortunate to have the ability to pay SEP participants through grant funds for several years.
Understandably, many institutions may not have funding options to compensate students or faculty for participating in a similar program. If an institution is unable to pay students, faculty may consider a variety of incentives to encourage participation. For example, faculty could embed similar opportunities within a course or practicum, offering course credit or extra credit to collaborate with other students. In the absence of incentives, students may be willing to participate simply to gain relevant experience that may appear on a resumé.
Learning-focused Goals and Activities
After recruiting participants, we outlined our goals for the program and for the students. Although we hired new students each year and emphasized goals differently with each new cohort, our primary goals always included (1) facilitating interdisciplinary crosstalk, (2) helping students transfer mathematical knowledge from one context to another, and (3) improving students’ conceptual understanding of specific statistical concepts.
Similar to backwards course design, faculty should first identify the goals of the program before pairing students to complete activities. Using the goals listed above may not work for every institution or discipline. Instead, consider interviewing faculty to identify relevant skills that students need to develop through the program. In addition, interviewing students about their needs and knowledge is a helpful way to develop goals and involve students in program creation.
After we identified our program goals, students worked in pairs to complete a variety of tasks related to our goals. For example, students interviewed one another about their knowledge of mathematics and statistics; designed a resource website to aid other students in statistics courses; and worked together to tutor students enrolled in a freshman-level statistics course. After assigning myriad activities over multiple semesters, we eventually narrowed the list of student activities to retain only the most effective ones.
Faculty should always keep the program goals in mind when selecting activities for students. Consulting publications, conferences, and colleagues may help faculty generate ideas for tasks that are relevant to the program’s goals. Further, not all activities are equally impactful, so faculty should regularly edit or remove the ones that do not seem to be maximizing students’ time and effort.
Frequent Assessment and Program Revision
Frequent assessment of our students helped determine the effectiveness and direction of the SEP. Specifically, we assessed students at the end of each semester using both qualitative and quantitative items, which included preexisting scales and homegrown prompts. Students’ responses indicated features of the program that worked and did not work, and what they learned through the program. Our assessments revealed many benefits of participating in the SEP, such as applying knowledge in unexpected ways and encouraging knowledge transmission from one domain to another.
Although it may take extra time and effort, faculty should measure the outcomes of each student team using relevant assessments. Such assessments can be derived from past research or designed from scratch, depending on the program’s established goals. Disseminating assessments at the beginning and end of a semester is also an effective way to demonstrate student growth through the program. Similarly, faculty should use students’ performance and responses to demonstrate the impact of program activities, and to revise the program (e.g., selecting effective activities, revising goals) as needed.
Summary
The SEP was designed to improve student learning and crosstalk by creating opportunities for interdisciplinary collaboration. More specifically, it was designed to help social science students understand the mathematical processes of and language related to statistics, and to help mathematics students understand various applications of statistics. Maintaining such a program is not without its challenges (e.g., participation incentives, faculty time, student commitment), but the benefits of knowledge transfer and collaboration far outweigh these issues. Broadly, it is my hope that this case study can serve as a model for faculty who wish to encourage collaborative opportunities between students majoring in different disciplines, such as nursing, business, and education.
Resources
Poole, B. D., Turner, L., & Maher-Boulis, C. (2020). Designing a “Student Exchange Program:” Facilitating interdisciplinary, math-focused collaboration among college students. Journal of Mathematics and Science: Collaborative Explorations, 16(1). Available at https://scholarscompass.vcu.edu/jmsce_vamsc/vol16/iss1/13/
Part II: Creating a Faculty Learning Community
Intended Audience: Faculty from different departments.
OVERVIEW
This case study describes how to create cross-disciplinary faculty learning communities (FLCs), specifically between mathematics and other departments, and how to use the FLC to create meaningful interventions that can be used in a mathematics classroom. The case study describes the collaboration between mathematics and other departments to inform the instruction of specific mathematics courses. The procedure, however, can be implemented by any different department.
KEY POINTS
The key points to creating a FLC start with discussions between faculty from different departments, sharing knowledge of course-specific content and examples from the disciplines to develop classroom instructional tools.
- Identify a mathematics course that serves other departments.
- Talk with faculty from the disciplines that require the mathematics course you identified. Find out why the partner discipline requires their students to take this specific mathematics course. What skills do they expect students to obtain from the mathematics course? What other courses build on the knowledge and skills gained in the math course?
- Share the mathematics course syllabus with the faculty from the partner discipline(s) so that they know what is being covered in that class.
- Get the partner discipline faculty to share with you examples of when they use the mathematical content, or skills, of the mathematics course.
- Work together to develop interventions, activities or projects to be implemented in the mathematics course.
- Invite the partner discipline faculty to talk to the students in your mathematics course about how what they learn will be needed in future courses.
CASE STUDY
Students taking mathematics courses often wonder why they need to take that math course; where would those mathematical concepts turn up in real life? Cross-disciplinary discussions can be very effective to answer such questions, and even more. They always reveal new things. Since 2017 faculty members in four departments at Lee University have been collaborating to understand the mathematical needs of students in different majors as part of the NSF-funded project, a National Consortium for Synergistic Undergraduate Mathematics via Multi-institutional Teaching Partnerships (SUMMIT-P). Mathematics faculty created faculty learning communities with the Department of Natural Sciences, Department of Behavioral and Social Sciences, and the College of Education. The focus has been to inform the mathematics courses required of students in these majors with emphasis on the needs of the partner disciplines. These courses have been Algebra for Calculus (for science majors), Introduction to Statistics (for social science majors), and Concepts of Mathematics (for education majors).
Faculty from the above-mentioned departments first participated in numerous discussions and “fishbowl” activities creating faculty learning communities aiming at understanding each other’s discipline and creating interventions that would be implemented in the mathematics courses. In the “fishbowl” activities partner discipline faculty discussed among themselves what content knowledge and skills they wanted their students to acquire in the relevant mathematics course. The mathematics faculty sat down listening to these discussions. The partner faculty in each discipline came up with a “wish list,” a list of content knowledge and skills they agreed the students should acquire after completion of the mathematics course.
As a result of these activities, mathematics faculty became aware of why students need to take the specific math course for their major discipline. Partner discipline faculty also became aware of the content of the mathematical curriculum. In addition, faculty from all four disciplines realized that the mathematical language used by different faculty from the different departments was different.
Subsequently, faculty collectively continued the discussions to make appropriate curriculum changes. One example of an impactful result of these discussions was the realization of the science faculty that some algebra topics that were assumed to be covered in the course were actually not covered due to lack of time. This resulted in a curriculum change of the Algebra for Calculus course from a 3-credit hour course to a 4-credit hour course. The faculty from all four departments further collaborated in creating classroom tools to address the needs of the departments.
One of the items on the “wish list” of faculty in the College of Education was that prospective teachers enrolled in Concepts of Mathematics should know how to use manipulatives in delivering instruction. We thus collaborated to conduct professional workshops to train mathematics faculty on the use of manipulatives in content delivery in Concepts of Math courses, such as Base 10 Blocks, Snap Cubes, Cusienaire Rods, and Fraction Towers. Examples of activities that we created with these manipulatives can be found in the first resource listed in this Case Study.
Mathematics and science faculty worked together to create biology and health science activities to be used in the Algebra for Calculus course. The activities delve into the concept of functions, reading and interpreting graphs, and how to make conclusions from graphs. Students practice manipulating equations algebraically, rearranging and interpreting them, and analyzing data. The interventions are introduced according to the level of difficulty, concept(s), and skills covered in the course. For instance, activities that introduce students to the terminology of functions, such as independent and dependent variables, domain, and range, are assigned at the beginning of introducing the topic. After the students become comfortable using function terminology, an intervention on population dynamics is assigned. The intervention uses the simplest of functions, linear functions. Students are given a table of values showing population changes in light and dark moths over a period of time. They are asked to plot the data points and find lines of best fit. They are then asked to calculate and interpret the slopes of the lines and the intercepts in the context of the problem. More detailed information about and copies of the interventions can be obtained by contacting the authors.
Mathematics and psychology faculty worked together to create activities with a social science context to be used in the Introduction to Statistics course. These activities addressed major concepts in the statistics course, such as the normal distribution, central tendency, and data visualization, and could be used in a variety of formats. For example, faculty designed prompts for small-group discussions that required students to discuss and agree on a solution before presenting it to the class. In one case, students are given a series of bar graphs, only one of which accurately represents a small sample of consumer satisfaction ratings, and must collectively decide which graph best represents the data. Faculty also designed debate topics for teams of students who were required to argue opposing sides of an argument (e.g., when it is appropriate to report the mean vs. median when reviewing census data). It is worth noting that as a result of the FLC created with the College of Education and the need to use manipulatives, this idea was extended to the use of manipulatives in Introduction to Statistics. For example, using a resource developed by Sledjeski (2006), students are given bags of poker chips that represent individuals within a population. Each poker chip contains a label that indicates the person’s age, gender, income, and happiness level. When students draw poker chips from a bag, they are simulating real-world data collection and can analyze those data using whatever statistics are being taught at the time.
These faculty learning communities provide a possible solution to departments working in silos across campus. It also helps make course content relevant to students’ majors and provides a means to answer the question: “when will I ever use this?”
Challenges
Some of the challenges faced with our initiative include receiving faculty buy-in. The cross-disciplinary collaborations worked well in the Algebra for Calculus and Concepts of math courses: not so well in Introduction to Statistics. Faculty who saw the benefit of these collaborations were open to making changes, learning new techniques, and listening to the needs of the partner disciplines.
Another challenge faced was measuring the effect of the project on student learning. For example, some students started their science program being exempt from taking the Algebra for Calculus course in our institution. In addition, the course’s enrollment was mostly low to draw any significant conclusions. We did receive, occasionally, verbal comments from the students that the interventions with the science context we used were helpful to them.
Successes
In addition to the curriculum changes that were implemented as described above, this project enabled faculty to exit their discipline-specific silos and create a collaborative network that has an impact on their instruction. These learning communities will last beyond the lifespan of the NSF-funded project.
Resources
Cornett, Jennifer, Beth Fugate, Patricia McClung, Caroline Maher-Boulis and Jason Robinson (2020). Counting on Collaboration: A Triangular Approach in the Education Preparation Program (EPP) for Teachers of Mathematics. Journal of Mathematics and Science: Collaborative Explorations, 16(1), 107-119. Available at: https://scholarscompass.vcu.edu/jmsce_vamsc/vol16/iss1/10
Hofrenning, Stella K.; Hargraves, Rosalyn Hobson; Chen, Tao; Filippas, Afroditi Vennie; Fitzgerald, Rhonda; Hearn, John; Kayes, Lori J.; Kunz, Joan; and Segal, Rebecca (2020) “Fishbowl Discussions: Promoting Collaboration between Mathematics and Partner Disciplines,” Journal of Mathematics and Science: Collaborative Explorations: Vol. 16 : No. 1 , Article 3. Available at: https://scholarscompass.vcu.edu/jmsce_vamsc/vol16/iss1/3
Sledjeski, E. M. (2016). Poker chip people: Using manipulatives in a college level statistics Course. https://teachpsych.org/resources/Documents/otrp/resources
For interventions created for use in Algebra for Calculus or Introduction to Statistics, please email the author at cmaherboulis@leeuniversity.edu.
