Work in Progress: Fault-Finding in the Statistical Analysis of Scientific Research Papers to Help Reinforce and Improve Training from a Biostatistics course for Engineers

Bilal Ghosn

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Conference: 2022 ASEE Annual Conference & Exposition
Location: Minneapolis, MN
Publication Date: August 23, 2022
Start Date: June 26, 2022
End Date: June 29, 2022
Conference Session: Biomedical Engineering Division Poster Session
Page Count: 5
DOI: 10.18260/1-2--41623
Permanent URL: https://peer.asee.org/41623
Download Count: 213

Paper Authors

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Bilal Ghosn Rice University

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Bilal Ghosn is a lecturer in the Department of Bioengineering at Rice University. He earned his Ph.D. from the University of Texas at Austin in Biomedical Engineering (2009). He also earned his M.S. (2004) and B.S. (2002) degrees in Biological Engineering from Louisiana State University. His teaching interests have included a variety of areas such as needs finding and development, service learning, digital design, engineering design, molecular techniques, global health and statistics.

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Abstract

For all engineers, the ability to make decisions through the iterative process based on real and meaningful information is critical for continual success. One key way that engineers make valid and supported decisions is through the use of statistical analysis., which is an essential element used in design and decision-making at numerous levels of the design process. In the case of biomedical engineers, the importance often holds even more weight given the nature of the work undertaken in the field. Thus, it is critical for students to receive adequate training and experience in their undergraduate curriculum. Training in biostatistics varies greatly from program to program, ranging from simply incorporating small elements within various courses throughout the curriculum to full stand-alone statistics courses. While our curriculum incorporates both approaches, there is still a need for reinforcement of the skills following initial training to improve retention. We have aimed to improve this through the incorporation of an open-ended fault-finding assignment for our students to help reinforce the teachings in our biostatistics course.

As overall credit requirements limit many of our biomedical engineering and bioengineering programs to use 1-credit hour course offerings for statistics, the need for creative and innovative approaches to reinforce the lecture material is crucial. Our current course structure includes a full semester, once per week lecture, which was recently supplemented with a paired weekly discussion session. In the lectures, students are taught on fundamentals of parametric statistical analysis with applications in biomedical engineering problems. Students were assigned weekly homework assignments linked to our lectures, and built around preparing them for the two exams in the course. Although student performance in the course demonstrated effective mastery of the material, evaluation of student performance in subsequent courses in the curriculum have noted less retention than expected.

In an attempt to provide improve the retention of the learned skills in statistics, we have incorporated an additional assignment into our second-year, one credit our biostatistics course. One key objective has been to improve students’ abilities to read and understand relevant scientific literature in the field. Our second objective was to improve the ability of students to recognize faulty versus sound science and engineering analysis. To meet both objectives, the creation of a fault-finding assignment was added in the Fall of 2020 as part of the course. In the assignment, students were tasked with identifying three scientific research papers where inappropriate statistical analysis was performed, and explain the reason. Further, the students were also required to provide the more appropriate statistical analysis approach in each case and their justification. It is believed that application of their understanding and training in this manner will help reinforce their newly developed statistics skills.

To evaluate the efficacy of this method, we will be assessing the students across a multi-course sequence. Following completion of each course, students will be surveyed using a 5-point Likert survey and open-ended response questions on the value of the assignment towards their understanding and ability to continue applying statistical analysis tools. Further, assessment of their performance on statistical analysis assignments in the subsequent lab courses will also be evaluated to determine if improvement over previous cohorts can be determined. It is hypothesized that by incorporating this assignment, we should see improvements in skills retention and application later throughout the program. This is particularly important with the importance of statistics as a skill for bioengineers throughout the field.

Citation
Format

Ghosn, B. (2022, August), Work in Progress: Fault-Finding in the Statistical Analysis of Scientific Research Papers to Help Reinforce and Improve Training from a Biostatistics course for Engineers Paper presented at 2022 ASEE Annual Conference & Exposition, Minneapolis, MN. 10.18260/1-2--41623

TY - CPAPER
AB - For all engineers, the ability to make decisions through the iterative process based on real and meaningful information is critical for continual success. One key way that engineers make valid and supported decisions is through the use of statistical analysis., which is an essential element used in design and decision-making at numerous levels of the design process. In the case of biomedical engineers, the importance often holds even more weight given the nature of the work undertaken in the field. Thus, it is critical for students to receive adequate training and experience in their undergraduate curriculum. Training in biostatistics varies greatly from program to program, ranging from simply incorporating small elements within various courses throughout the curriculum to full stand-alone statistics courses. While our curriculum incorporates both approaches, there is still a need for reinforcement of the skills following initial training to improve retention. We have aimed to improve this through the incorporation of an open-ended fault-finding assignment for our students to help reinforce the teachings in our biostatistics course.

As overall credit requirements limit many of our biomedical engineering and bioengineering programs to use 1-credit hour course offerings for statistics, the need for creative and innovative approaches to reinforce the lecture material is crucial. Our current course structure includes a full semester, once per week lecture, which was recently supplemented with a paired weekly discussion session. In the lectures, students are taught on fundamentals of parametric statistical analysis with applications in biomedical engineering problems. Students were assigned weekly homework assignments linked to our lectures, and built around preparing them for the two exams in the course. Although student performance in the course demonstrated effective mastery of the material, evaluation of student performance in subsequent courses in the curriculum have noted less retention than expected.

In an attempt to provide improve the retention of the learned skills in statistics, we have incorporated an additional assignment into our second-year, one credit our biostatistics course. One key objective has been to improve students’ abilities to read and understand relevant scientific literature in the field. Our second objective was to improve the ability of students to recognize faulty versus sound science and engineering analysis. To meet both objectives, the creation of a fault-finding assignment was added in the Fall of 2020 as part of the course. In the assignment, students were tasked with identifying three scientific research papers where inappropriate statistical analysis was performed, and explain the reason. Further, the students were also required to provide the more appropriate statistical analysis approach in each case and their justification. It is believed that application of their understanding and training in this manner will help reinforce their newly developed statistics skills.

To evaluate the efficacy of this method, we will be assessing the students across a multi-course sequence. Following completion of each course, students will be surveyed using a 5-point Likert survey and open-ended response questions on the value of the assignment towards their understanding and ability to continue applying statistical analysis tools. Further, assessment of their performance on statistical analysis assignments in the subsequent lab courses will also be evaluated to determine if improvement over previous cohorts can be determined. It is hypothesized that by incorporating this assignment, we should see improvements in skills retention and application later throughout the program. This is particularly important with the importance of statistics as a skill for bioengineers throughout the field.

AU - Bilal Ghosn
CY - Minneapolis, MN
DA - 2022/08/23
PB - ASEE Conferences
TI - Work in Progress: Fault-Finding in the Statistical Analysis of Scientific Research Papers to Help Reinforce and Improve Training from a Biostatistics course for Engineers
UR - https://peer.asee.org/41623
DO - 10.18260/1-2--41623
ER -