Sophomore Bioengineering Final Project
Summary
Description: As a final project, students apply their knowledge of mass conservation to develop computational models of ligand-receptor signaling. Students systemically examine how signals enter cells (ligand-receptor binding), how signals generate cellular response (second-messenger signaling), and how signals can be controlled by drugs (monoclonal antibodies, small molecules, etc.). Students work in teams to: (1) Choose a disease to treat that depends on ligand-receptor binding, (2) Create a mathematical model simulating ligand-receptor signaling in this disease, (3) Determine which molecule or molecules they would like to target to control signaling in the disease (e.g., drug), (4) Use the model to quantitatively evaluate the relative effectiveness of their signaling control (e.g., drug) strategy, and (5) Demonstrate the value of their quantitative analytical framework by comparing their treatment scheme to current therapies.
Students derive equations based on conservation principles taught in class, allowing students to fully synthesize course material. Students create a plan to complete the project. Students present their work at mid-semester and at the end of the semester to obtain both instructor and peer feedback using an established rubric. Students are required to address critiques (in a similar format to "a response to reviewers") in their final products.
Students derive equations based on conservation principles taught in class, allowing students to fully synthesize course material. Students create a plan to complete the project. Students present their work at mid-semester and at the end of the semester to obtain both instructor and peer feedback using an established rubric. Students are required to address critiques (in a similar format to "a response to reviewers") in their final products.
CollapseLearning Goals
MATLAB is utilized in this activity to input equations, run simulations, and analyze parameter effects.
Utilizing MATLAB in this activity improves student learning in several ways:
1. Students learn how the equations that they have solved either by hand or by matrix algebra techniques can be solved computationally. This is an essential transition for the engineers, because it allows them to see how computational tools can help them solve engineering problems quickly.
2. It inspires students to consider pursuing research in computational modeling. Indeed, several students have continued on as researchers in my laboratory after successful completion of the project. Other students have participated in Systems Biology + Computational Modeling REUs during the summer, as a direct result of doing this project.
With regards to higher-order thinking skills and outcomes, there are several:
This project aims to stir interest in systems biology research, motivate students to perform independent research, and impart the well-documented benefits of undergraduate research. More specifically, by delineating and analyzing the complexities of ligand-receptor signaling, students engage each of the six major Bloom's Taxonomy of cognitive processes—ultimately improving their learning of Bioengineering fundamentals. Many students should be inspired to take additional courses in systems biology. To enable motivated sophomores to pursue their systems biology interest, we modified pre-requisites of my advanced systems biology course (BIOE498/598) to allow continuation into the spring semester. I expect students to display several learning gains attributed with undergraduate research, including an ability to read and understand primary literature, learning to work independently, readiness for further research, and an ability to analyze data. Ultimately, their engagement in systems biology research will generate new knowledge while opening several opportunities that will inevitably enhance their undergraduate and future engineering careers.
Other skills:
(1) Writing - Students prepare a proposal of their work and a final report. Each report is graded via an established rubric. So students obtain writing practice and critique.
(2) Oral Presentation - Students present their proposal and final product in class. Presentations are critiqued by instructional staff and all students in the course, using an established rubric. Students must respond to critique, updating their reports accordingly. Therefore, students are able to develop and improve their presentation skills through the project.
Utilizing MATLAB in this activity improves student learning in several ways:
1. Students learn how the equations that they have solved either by hand or by matrix algebra techniques can be solved computationally. This is an essential transition for the engineers, because it allows them to see how computational tools can help them solve engineering problems quickly.
2. It inspires students to consider pursuing research in computational modeling. Indeed, several students have continued on as researchers in my laboratory after successful completion of the project. Other students have participated in Systems Biology + Computational Modeling REUs during the summer, as a direct result of doing this project.
With regards to higher-order thinking skills and outcomes, there are several:
This project aims to stir interest in systems biology research, motivate students to perform independent research, and impart the well-documented benefits of undergraduate research. More specifically, by delineating and analyzing the complexities of ligand-receptor signaling, students engage each of the six major Bloom's Taxonomy of cognitive processes—ultimately improving their learning of Bioengineering fundamentals. Many students should be inspired to take additional courses in systems biology. To enable motivated sophomores to pursue their systems biology interest, we modified pre-requisites of my advanced systems biology course (BIOE498/598) to allow continuation into the spring semester. I expect students to display several learning gains attributed with undergraduate research, including an ability to read and understand primary literature, learning to work independently, readiness for further research, and an ability to analyze data. Ultimately, their engagement in systems biology research will generate new knowledge while opening several opportunities that will inevitably enhance their undergraduate and future engineering careers.
Other skills:
(1) Writing - Students prepare a proposal of their work and a final report. Each report is graded via an established rubric. So students obtain writing practice and critique.
(2) Oral Presentation - Students present their proposal and final product in class. Presentations are critiqued by instructional staff and all students in the course, using an established rubric. Students must respond to critique, updating their reports accordingly. Therefore, students are able to develop and improve their presentation skills through the project.
Context for Use
Educational Level: Sophomore
Class Size: 30-40 students
Institution type: R01
College: Engineering
Technical skills needed: The students must understand conservation principles, which we teach in class. This allows the students to input the equations that they derive into MATLAB's Simbiology toolbox.
MATLAB experience: Brief training in Simbiology is also needed
Other disciplinary skills needed: calculus, biology, chemistry, physics
How is the activity situated in course: team final project that is performed during the latter third of the semester.
Mastery prior to beginning activity: The students must have mastered deriving mass balance equations.
Class Size: 30-40 students
Institution type: R01
College: Engineering
Technical skills needed: The students must understand conservation principles, which we teach in class. This allows the students to input the equations that they derive into MATLAB's Simbiology toolbox.
MATLAB experience: Brief training in Simbiology is also needed
Other disciplinary skills needed: calculus, biology, chemistry, physics
How is the activity situated in course: team final project that is performed during the latter third of the semester.
Mastery prior to beginning activity: The students must have mastered deriving mass balance equations.
Description and Teaching Materials
Students synthesize knowledge via the BIOE201 final project. Here, we expose students to the use of computational modeling in Bioengineering research and inspire them to continue as undergraduate researchers. Piloting these efforts has led to significant undergraduate student research engagement in my laboratory and in summer REUs. Moreover, this project allows students to synthesize the knowledge of conservation principles that we teach throughout the term.
Student Handout for Final Project (Microsoft Word 2007 (.docx) 28kB Sep29 16)
Peer critique rubric (Microsoft Word 2007 (.docx) 21kB Sep29 16)
Powerpoint presentation introducing the team final project (PowerPoint 2007 (.pptx) 17MB Sep29 16)
Instructor-Assessment rubric (Microsoft Word 2007 (.docx) 16kB Sep29 16)
Student Handout for Final Project (Microsoft Word 2007 (.docx) 28kB Sep29 16)
Peer critique rubric (Microsoft Word 2007 (.docx) 21kB Sep29 16)
Powerpoint presentation introducing the team final project (PowerPoint 2007 (.pptx) 17MB Sep29 16)
Instructor-Assessment rubric (Microsoft Word 2007 (.docx) 16kB Sep29 16)
Teaching Notes and Tips
Students often find it difficult to find computational model parameters. It is not expected that the students do this. Once the students have submitted their project proposals, I provide them with published examples of the modeling that they propose to do. This allows them to compare their derived equations to established equations, and it provides them the data that they need to complete their project.
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Assessment
The attached rubrics show student/peer-based assessment and instructor assessment
References and Resources
http://www.mathworks.com/products/simbiology/