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BIOENGINEERING SUMMER CAMPS

INSPIRING TOMORROW’S ENGINEERS2 0 1 6 A N N U A L R E P O RT

University of PittsburghSwanson School of EngineeringDepartment of Bioengineering

2 SWANSON SCHOOL OF ENGINEERING | DEPARTMENT OF BIOENGINEERING

BIOENGINEERING SUMMER CAMPS | 2016 ANNUAL REPORT 1

MISSION STATEMENT

Since 2007, the faculty and staff members of the University of Pittsburgh Department of Bioengineering in the Swanson School of Engineering have been addressing deficiencies in youth science, technology, engineering, and math (STEM) education by offering Bioengineering Summer Camps. The camps are now the signature outreach program of the department and one of the most successful K–12 outreach initiatives at the University.

The goal of the program is to engage young minds in the wonders of science, bioengineering, and the potential to benefit the human condition while also showing them that STEM can be a fun and exciting field of learning with promising career opportunities. We seek to engage diverse groups of students, particularly those who come from backgrounds that are largely underrepresented in STEM fields, namely minorities and women.

Building on our nationally-ranked department’s partnerships with the University of Pittsburgh Medical Center, the camp curriculum utilizes regenerative aspects of the natural world and current research topics in bioengineering to explore how state-of-the-art research can be applied to human medicine and treatment. Our “near-peer” mentorship strategy integrates excellent undergraduate bioengineering students from Pitt’s Swanson School of Engineering as content creators and camp counselors. Each year, we aim to provide middle and high school students who have burgeoning interests in science with an exceptional opportunity to learn about bioengineering and regenerative medicine through hands-on experiences with new technologies, experimental strategies, and ethical considerations in the diverse fields of bioengineering and regenerative medicine.

THE GOAL OF THE PROGRAM IS TO ENGAGE YOUNG MINDS IN THE WONDERS OF SCIENCE, BIOENGINEERING, AND THE POTENTIAL TO BENEFIT THE HUMAN CONDITION … .


2016 SUMMARY

We had a record-breaking year! Thanks to support from charitable gifts and grants, we were once again able to offer a week of Bioengineering Summer Camp at no charge for Pittsburgh-area students from backgrounds that are underrepresented minorities (URMs) in STEM fields. We were able to achieve an amazing 37.6 percent URM student participation in 2016 (32 out of 85 total students). To put this accomplishment in perspective, 2015 was the first year that we were able to implement our URM outreach efforts, and URM student participation that year was 26.6 percent, which also was an incredible improvement from our 2014 and earlier percentages that were typically just 3–5 percent. The 37.6 percent participation rate also exceeds the national demographic profile of URM versus non-URM individuals, so this is a tremendous achievement indeed! Currently at the Swanson

School of Engineering, 7 percent of undergraduate students are from URM groups, a number that’s consistent with other major engineering degree programs. Some have speculated that these low numbers can be attributed to URM students’ lack of interest in STEM fields, perhaps because they have too few role models in such careers and STEM disciplines are perceived as academically “too hard.” However, our data demonstrates, in stark contrast with such reports and speculation, that there is a clear interest in STEM careers among URM youths in Pittsburgh. That interest needs to be cultivated and enriched so that more underrepresented students will enroll in STEM-focused degree programs and pursue related career opportunities in the future. This is a primary mission of our Bioengineering Summer Camps: to nurture and develop these students’ interests, skills, and potential.

Unfortunately, the playing field in education is certainly not level. For example, recent data show that only 23 percent of high schools with a primarily URM student population offer calculus versus 55 percent of high schools with a primarily non-URM student population. Because many URM students lack strong academic preparation in STEM subjects, we wanted to place greater emphasis on understanding how well we were recruiting students from underserved versus nonunderserved school districts and how these factors, along with differing racial backgrounds, impacted performance in our camps. Thus, our evaluation, performed by Jennifer McCoy, was much more in depth than in previous years.

The detailed report is provided in the following pages. Much of the data confirms that students from underserved schools are indeed coming into our camps with less knowledge than those from

UNDERREPRESENTED MINORITIES STUDENT PARTICIPATION IN 2016

32 OUT OF 85 TOTAL STUDENTS 37.6%


nonunderserved schools. Excitingly, the data also show that posttest scores on most topics covered in the camps were equivalent between students from underserved and nonunderserved schools. These data suggest that while there may be differences in the opportunity to learn throughout the Allegheny County schools, the capacity for these students to learn is the same. In fact, it shows that many of the URM and underserved students are successfully climbing a higher learning curve during their week with us compared to non-URM and nonunderserved students. These are powerful findings, and nothing demonstrates to us more that there is a tremendous need to invest in these students!

For 2017, we are excited to announce that the University of Pittsburgh has established an initiative to invest more in our communities (news.pitt.edu/news/pitt-reimagines-community-partnerships). This began with the

establishment of a center for technology in the Jeron X. Grayson Community Center, located in Pittsburgh’s Hill District. The University renovated one of the rooms of that building to make a technology classroom complete with more than 20 computers and a 3D printer. Our Bioengineering Summer Camp (CampBioE) program director, Steven Abramowitch, PhD, has been teaching and conducting activities there on Thursday afternoons since the spring of 2017. His plan is to use this opportunity to develop a technology-focused camp during the summer to complement the bioengineering-focused camps that we already offer. With the same hands-on “flavor” of CampBioE, the focus of this new camp would be to introduce middle and high school students to the use of 3D technology in science and industry. With the University’s investment in the Jeron X. Grayson Community Center, we have the perfect opportunity to make this additional camp a reality.

In addition, in 2017, we plan to:

1. continue local recruiting initiatives within underrepresented communities, which have resulted in a more than 800 percent increase in underrepresented student participation since 2013;

2. continue to offer a free fourth week of CampBioE for underprivileged and underrepresented students at Central Catholic High School’s new state-of-the-art Zupanic Family STEM Center, a location that can accommodate a larger cohort of students and is easily accessible via public transportation;

3. provide 40 registration-free scholarships to underrepresented students in the Pittsburgh area, an increase over last year, when we were able to provide 32; and

4. develop an all new one-week camp program focused on 3D technology to be launched at the Jeron X. Grayson Community Center in Pittsburgh’s Hill District.

We hope you can appreciate the impact that your donations have had in the success of our program and will continue to support us and our goals moving into 2017 and beyond. We are already developing some exciting activities based on microfluidics for this summer.


SELECTED FEEDBACK FROM PARENTS

“My husband and I have both done research at different points in our career(s) and we were amazed at what our daughter was doing. She was literally learning about techniques that I did during my postdoc time!”

“[THE CAMP] HAS INCREASED HIS CONFIDENCE AND WAS SUCH A POSITIVE EXPERIENCE!”

“Having teaching experience myself and a background in psychology, I think (wittingly or not) the program took advantage of Vygotsky’s principles of learning in adolescents perfectly.”

“Great camp and great staff! Definitely looking forward to next year.”

“I really enjoyed the opportunity to send my daughter to the camp to broaden her horizons as far as careers and education. It was good to see young people, close to my daughter’s age and African American, who were in college and achieving so much.”

“He came home every day and was excited about something—dissecting a brain, designing a bone to withstand weight, performing surgery on a cockroach. The hands-on learning was great!”

“He mostly enjoyed the experi-mentation and topics chosen. I believe this was enhanced by several factors. One, that instruction was by a knowl-edgeable non-adult, but that adults were around more so as guideposts. Two, that the work effort was collaborative and therefore with a built-in support structure. Lastly, that he was grouped with peers.”


2016 KEY PERSONNEL

Sanjeev ShroffDistinguished Professor and Gerald McGinnis ChairDepartment of BioengineeringSwanson School of EngineeringUniversity of Pittsburgh

Steven AbramowitchAssociate ProfessorDepartment of BioengineeringSwanson School of EngineeringUniversity of PittsburghCamp Director

Juel SmithAssociate Professor of BiologyCommunity College of Allegheny CountyCamp Mentoring and Education Specialist

Mark KrotecBiology Teacher Central Catholic High SchoolCamp Master Educator

Alicia KempUndergraduate Program AdministratorDepartment of BioengineeringSwanson School of EngineeringUniversity of PittsburghCamp Coordinator

“I had two children attend. They both enjoyed the atmosphere, where they were in a positive group of people who also enjoy learning about science. They got to do things that we aren’t able to in our school district. Your team also understands that they are kids, and from the Facebook posts, it looks like everyone had fun getting up and moving around—inside or outside! Thank you all so very much for finding time in your full schedules to take this program on and reach out to so many kids.”


NEW ACTIVITIES DEVELOPED AND IMPLEMENTED IN 2016

Each year, the theme of the camp focuses on a distinct area of bioengineering research. To complement our standard bioengineering and tissue engineering-related activities, 2016’s focus was on the brain and neuronal activity. We trained five or six undergraduates that served as senior counselors to develop these activities and taught them to our campers. Our senior counselors worked for six to seven weeks, with each counselor allotted a $1,000 budget to bring new content to the camp. They then served as the primary educators during the four weeks of our camp, with support from high school junior counselors. This is an outstanding educational opportunity for our undergraduates and high school junior counselors, and the campers love the near-peer mentorship that they provide. This year, the camp included the following activities:

RoboRoach: Stimulating Neurons and Neuroplasticity: Makes use of technology to control the motility of the Descoid roach; developed/implemented by Ryan Nguyen

Mind Games: An activity that examined the concept of mind control to operate video games; developed/implemented by Robert Donahoe

Makey Make-Me—You’re Grounded: An activity in which the students physically simulated a piano keyboard through electrical conductivity; developed/implemented by Mia Baker

Cyborg: This activity related the nervous system to computer science. It used electrical engineering to control a 3D-printed hand construct. Developed/implemented by Ross Tedder

Memory—Use It or Lose It: An activity that looked into human memory and modern research progress on increasing mental capacity and intelligence; developed/implemented by Patricia Donehue

Fast as Lightning: A series of small activities that tested campers’ reaction times to different types of stimuli; developed/implemented by Chris Ford

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6


Clockwise from top right: 1. Mind Games, 2. Fast as Lightning, 3. Makey Make-Me, 4. Memory, 5. Cyborg, 6. RoboRoach

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3

4

5


SENIOR COUNSELORS

Ryan Nguyen Chris Ford

Patricia Donehue Rob Donahoe

Mia Baker Ross Tedder

JUNIOR COUNSELORS

Adam Parrish Luke Barrante

Reed Rankin Taniya Parnell


Pictured from left to right are Patricia Donehue, Chris Ford, Ryan Nguyen, Mia Baker, Steven Abramowitch, Ross Tedder, Rob Donahoe, and Juel Smith.


PROGRAM EVALUATION OF A BIOENGINEERING CAMP FOR MIDDLE SCHOOL AND HIGH SCHOOL STUDENTSPrepared by Jennifer McCoy, Research Technician, Pittsburgh Institute for Neurodegenerative Diseases

DISCUSSION REPORT

The bioengineering department at the University of Pittsburgh Swanson School of Engineering has hosted four weeklong bioengineering camps called CampBioE for a number of years. This past summer, one camp was devoted to middle schoolers, two weeks were composed of high schoolers, and the final week consisted of both middle and high school students from potentially lower socio-economic status schools in the Pittsburgh area and predominantly underrepre-sented minorities (URMs).

The overarching goal of CampBioE is to engage participants in experiencing science and bioengineering and the potential to benefit the human condition. In evaluating the success of the summer camps, three general objectives were tackled:

• to increase students’ process skills across disciplines,

• to enhance students’ appreciation of science and technology, and

• to increase students’ awareness of educa-tional and career opportunities.

A CampBioE manual was given to each student for the duration of the camp. The manual provides an introduction to the camp with the outlined goals as well as challenges to complete, laboratory safety information, and the questions and directions for the activities. The activities of the camp are outlined according to each branch of STEM with the example questions or directions seen in Table 1. The activities and challenges were group based, with each group creating a “company.” The company would receive fake money based on the success of each activity and challenge applicable to stakeholder rewards. The activities provided directions that were applicable to real-world problems in STEM fields, such as “the contract requires that a specific bone be created for implantation in the legs of injured athletes.” Over the course of the week, the group companies were provided with challenges focused on researching the McGowan Institute for Regenerative Medicine scientists and their research, top engineers, and identifying neurotransmitters to help a “client” in healing.

The targeted sample was 85 students who participated in CampBioE. The program consisted of four identical camps that were one week long.

CampBioE has been in existence since 2004, with slight adjustments to the camp from year to year based on how the camp counselors organized and presented the activities. For 2016, three of the four weeks were open to the public and had a fee of $300 to attend the camp to cover the costs of the supplies for activities and food. The last week was targeted toward underrepresented minorities living in urban areas, and they attended with no fee in order to possibly increase participation. The first week was specifically for middle schoolers, while the next two weeks were a mix of middle school and high school students. The fourth week for underrepresented minority students also was a mix between middle school and high school students. Promotional information for the camp was provided online, and students voluntarily participated.

Out of the 85 students, 47 were male (54.8 percent) and 38 were female (45.2 percent). Students had completed grades 5–11, with more students participating as middle schoolers. There were 61 total middle school students (72.6 percent) and 23 high school students (27.4 percent), for one student, these data were not provided. A middle school student was classified


Table 1: CampBioE activities for the STEM components

Topic Activity Examples Example Questions/Directions

Science

Metric conversions; tissue extract challenge— spectrophotometry

How would the absorbance readings on the spectrophotome-ter compare if you have two samples, one with very little cell growth and one with a lot of cell growth?

Stem cell culturingUse a cell line to determine the effects of a variable on cell replication and survivorship, extracellular matrix production, and general responses to injury.

Cell Staining Perform a toluidine blue dye stain.

Polymerase chain reaction Prepare a polymerase chain reaction.

DNA extraction Follow a protocol for DNA extraction using Qiagen spin columns.

Roach surgery Follow protocol to perform surgery for inserting an electrode for electrical stimulus of a live roach.

Reflex activities Six different games to understand how reflexes work

Neuroplasticity activity Use a disk and Nerf gun to gain faster reaction times.

TechnologyMind games with Arduino Follow a protocol to build an Arduino headset and answer a

series of questions.

Memory activities Use given technology to learn about iconic, short-term, episodic, semantic, and procedural memories.

Engineering

Vessel fluid dynamics activity Synthesize a vessel scaffold to test its fluid retention and flow properties.

Tissue-engineered blood vessel construction

Was your scaffold compressible, elastic, and resistant to shock forces and did it support adequate fluid flow?

Bone strength competition Test the strength of an engineered bone with given supplies.

Bioethics as related to tissue engineering Examine the ethics, choices, and consequences that tissue engineering raises from an informed perspective.

Scaffold degradation activity Determine the legal dose 50 percent of a scaffold product being degraded.

Stem cell seeding efficiency experiment Determine which group has the highest stem cell seeding efficiency.

Origami nanobots Use origami pieces to create nanobot structures for collecting beads in water.

Makey Make-Me kit Use a printed circuit board that runs Arduino code to learn a song.

Mathematics Metric conversions and calculations Complete the brain teasers.


as having completed fifth through eighth grade, whereas a high school student was classified as having completed grades 9–11. More than half of the students were encouraged to register their parents, and 70 percent of students reported having a parent with a job in STEM. The students were then categorized for the analyses: underrepresented minority (URM) versus non-underrepresented minority (non-URM) and attend an underserved school district categorized by having at least 50 percent of the students eligible for free and reduced price lunch (FRPL) versus attending a nonunderserved school district categorized by having less than 50 percent of the students eligible for FRPL. One male student

was excluded from the data set due to not including identifiers, not having

response sets, and not answering all of the

open-ended questions.

Figure 2 is a depiction of middle school and high

school students combined broken into URM students versus non-URM stu-

dents and the categorization of school district groups (underserved versus a nonunderserved school district by the categorization of 50 percent FRPL eligibility, which are nonmutually exclusive. There were 46 middle school and high school students who attended a nonunderserved school district, with 41 of those students identified as non-URM and five students as URM. There were 38 middle school and high school students who attended an underserved school district, with 11 of the students identified as non-URM and 27 as URM students.

Students were then further categorized, separating middle school students and high school students for both URM verses non-URM and underserved versus nonunderserved For middle school students, there were 25 non-URM

students attending nonunderserved school districts, nine non-URM students attending underserved school districts, five URM students attending nonunderserved school districts, and 22 URM students attending underserved school districts. For high school students, there were 16 non-URM students attending nonunderserved school districts, two non-URM students attending underserved school districts, five URM students attending underserved school districts, and no URM students attending nonunderserved school districts.

There were no students missing for the first day of camp, however there was a student who took only one of the precamp surveys. Due to the technological issues for the first year using electronic tablets, a few of the students took one survey and not the other (knowledge versus evaluation). Therefore, it may appear that the student was missing from the camp when he or she was not. The specific student totals are found in Table 2 for both middle school and high school students combined.


0

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40

50

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40

50Figure 1. Students categorized by URM or non-URM and underserved or nonunderserved by 50 percent FRPL eligibility

Figure 2. Students separated by middle school and high school for the group categorizations

Table 2: Total number of students for the pre- and postsurveys categorized by URM, non-URM, underserved, and nonunderserved

Preknowledge Postknowledge Preevaluation Postevaluation

URM students (N ) 31 30 32 30

Non-URM students (N ) 52 47 52 46

Total (N ) 83 77 84 76

Categorization of students attending underserved school districts (N )

38 34 38 34

Categorization of students attending nonunderserved school districts (N )

45 43 46 42

Total (N ) 83 77 84 76

Middle and high school non-URM

Middle and high school URM

Middle and high school nonunderserved

Middle and high school underserved

Middle school non-URM 0

10

20

30

40

50

0

10

20

30

High school non-URM

Middle school URM

High school non-URM

Middle school nonunderserved

0

10

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40

50

0

10

20

30

High school nonunderserved

0

10

20

30

40

50

0

10

20

30

Middle school underserved

High school underserved

0

10

20

30

40

50

0

10

20

30


Pretest Posttest

Open-ended non-URM vs URM X X

split MS/HS non-URM vs URM X X

non-US vs US X

split MS/HS non-US vs US X

Words non-URM vs URM X X

split MS/HS non-URM vs URM X

non-US vs US X

split MS/HS non-US vs US

Research Question 1: Will underrepresented minority students and students who are categorized as attending an underserved school district by having at least 50 percent of the students eligible for FRPL gain a signif-icant amount of knowledge outlined by the learning objective from pretest to posttest as nonunderrepresented minority students and students who attend nonunderserved school districts with less than 50 percent of their students eligible for FRPL?

The learning objective assessed information on the knowledge survey. A total score was computed for both bioengineering and tissue engineering constructed response questions and familiar words. The total score for the constructed response questions was analyzed first. Both non-URM and nonunderserved students had significantly higher scores than URM and underserved students on the posttest. However, URM students had significant increases in scores from pretest to posttest, whereas underserved students had increases in mean scores but were not significant. When students were split between middle school and high school for both groups, results were similar between URM students based on categorization of school districts. Middle school non-URM and nonunderserved students were compared to middle school URM and underserved students. High school non-URM and nonunderserved students were compared to high school URM and underserved students. Non-URM

middle school students had higher scores on both the pretest and the posttest than URM middle school students. High school non-URM students had higher scores on the posttest than high school URM students but not on the pretest. Nonunderserved middle school students had higher scores on the posttest than under-served middle school students, but not on the pretest. There were no significant differences on either the pretest or the posttest between high school nonunderserved and underserved students.

As for familiar words, non-URM and nonunder-served students had higher scores on the posttest than URM and underserved students. Non-URM students had higher scores on both the pretest and the posttest compared to URM students. Both non-URM and URM students had increases from pretest to posttest. There also were differences when middle school students were compared to each other as well as when high school students were compared to each other. Middle school non-URM students had higher scores on the posttest than middle school URM students but not on the pretest. High school non-URM students had higher scores on both the pretest and the posttest than URM students. As for groups based on the categorization of school districts, there were no differences between middle school students or high school students for both the pretest and the posttest. Both nonunderserved and under-served students had increases in scores from pretest to posttest.

(MS = middle school; HS = high school; US = underserved)

Differences on pretest and posttest

Differences on pretest and posttest middle school only

Pretest Posttest

Open ended MS non-URM vs URM X X

MS non-US vs US X

Words MS non-URM vs URM X

MS non-US vs US

Differences on pretest and posttest high school only

Pretest Posttest

Open ended HS non-URM vs URM X

HS non-US vs US

Words HS non-URM vs URM X X

HS non-US vs US


Overall, there were increases from pretest to posttest for the racial groups and groups based on categorization of school districts. Splitting the students into two groups with middle school and high school combined produced different results than when the students were split into four groups for post hoc comparisons for the pretest or posttest. This is due to both middle school and high school nonunderserved and non-URM students’ having higher mean scores than both middle school and high school undeserved and URM students. Typically, middle school non-URM and nonunderserved students had mean scores for the knowledge questions close to the mean scores from high school non-URM and nonunderserved students. However, middle school URM and underserved students had scores well below the mean scores of high school URM and underserved students. The analyses based on the two groups for URM and underserved students with middle school and high school students combined are lower due to the differences in middle school mean scores. Interestingly, nonunderserved middle school students had higher mean scores than nonunderserved high school students on the con-structed response scores pretest and the familiar words pretest. Other than those patterns, high school non-URM and high school nonunderserved students had the highest mean scores for both constructed response and familiar words for both pretest and posttest. When splitting the students

into four groups and comparing middle school students to each other and high school students to each other across groups, specific differences can be seen.

The differences between groups could be due to a number of things. The known achievement gaps and opportunity gaps between these groups could be a relevant factor. The constructed response questions are specific to defining bioengineering and tissue engineering, which are more advanced topics likely not taught in a standard curriculum. In order to increase scores on the open-ended questions, the definitions of the terms should be better targeted during the camp. Scores for the familiarity of words could be misleading due to differences in individual confidence levels or differences in producing results that reflect social desirability. For example, nonunderserved middle school students had the highest mean scores out

of nonunderserved and underserved students for the total word scores. These students may be checking the boxes irrespective of whether they were actually familiar with explaining the tissue engineering and bioengineering words. The students also may have thought that the survey was a test and were to check as many words as possible. Each word should be reevaluated to ensure that the context of the word is discussed at the camp. The question that asked the students to rank the bioethical analysis steps was omitted from the final analysis. There were no patterns of student responses. This question could be short-ened for easier test taking and grading. A more concrete coding system should be implemented for the grading of the question, which would allow for greater leniency of the order of the bioethical analysis steps without taking away the validity.

OVERALL, THERE WERE INCREASES FROM PRETEST TO POSTTEST FOR THE RACIAL GROUPS AND GROUPS BASED ON CATEGORIZATION OF SCHOOL DISTRICTS.


Research Question 2: Will underrepresented minority students and non-underrepresented minority students, as well as students attending school districts categorized as underserved by having at least 50 percent of the students eligible for FRPL and nonunder-served school districts with less than 50 percent of the students eligible for FRPL, have equal process skills, appreciation and interest, and awareness on the evaluation surveys outlined by the general objectives?

Process skills were assessed with self-reported experience and confidence levels on 11 different items related to STEM. For the 11 items related to STEM, there were a fewer number of differences between racial groups on the posttest than the pretest for the students’ self-reported level of experience, with four differences on the pretest and two on the posttest. As for groups based on the categorization of school districts, there were the same number of differences on the pretest as the posttest, with two each. Overall, the students reported a similar level of experience on a majority of the STEM items after participating in the camp. As for confidence levels, non-URM students had higher levels of confidence than URM students on more STEM items on the posttest compared to the pretest. Interestingly, URM students had higher levels of confidence than non-URM students for two items on the pretest but had the same level

of confidence by the posttest. Gel electrophoresis was the only STEM item that non-URM students had both higher self-reported experience and confidence levels compared to URM students. As for the groups based on the categorization of school districts, there were no differences on the pretest for any of the items, but nonunderserved students had higher confidence than underserved students for the STEM item of making solutions.

Score increases from pretest to posttest also were analyzed for each of the STEM items individually, and the total score for both experience and confi-dence levels are shown in the tables to follow.

The correlations between pretest and posttest were fairly low for both experience and confidence levels. This is because students answered disagree response options for the pretest and agree response options for the posttest. The camp increased the self-reported levels of experience and confidence on a six-point scale.

In order to improve the experience and confidence differences, a shorter scale could possibly be introduced. However, there still may be little variability in responses leading to few differences for the analyses. A frequency scale could be asked with the response options being an estimation of how many times or how often the student participated in the STEM items. The confidence scale could be asked in addition to this scale.

EXPERIENCE

The 11 STEM items were analyzed for differences and are reported on pages 68–75 of the results section for experience levels. For an easy comparison, differences in the tables below were labeled with an N for no difference and a Y for a difference. The groups that were compared for each item were middle school and high school combined non-URM and URM students, middle school and high school split for non-URM and URM students, middle school and high school combined nonunderserved and underserved students, and middle school and high school split for nonunderserved and underserved students. Overall, there were more differences between the groups on the pretest than the posttest. There were 14 out of 44 differences on the pretest and only five differences on the posttest. This indicates that student groups that had a lower level of experience compared to other student groups on the pretest increased their level by the end of the camp.

When middle school and high school students were split, groups were compared across their respective educational level (i.e., middle school compared to middle school and high school com-pared to high school). There were only differences across high school students, with non-URM and nonunderserved having higher self-reported levels of experience than URM and underserved students on the posttest for gel electrophoresis. For the



Pretest PosttestSpectrophotometry non-URM vs. URM N N split MS/HS non-URM vs. URM N N non-US vs. US N N split MS/HS non-US vs. US N NPipetting non-URM vs. URM Y N split MS/HS non-URM vs. URM Y N non-US vs. US N N split MS/HS non-US vs. US Y NHandling science equipment non-URM vs. URM N N split MS/HS non-URM vs. URM N N non-US vs. US N N split MS/HS non-US vs. US N NMaking solutions non-URM vs. URM N N split MS/HS non-URM vs. URM N N non-US vs. US N N split MS/HS non-US vs. US N NLab safety non-URM vs. URM N N split MS/HS non-URM vs. URM N N non-US vs. US N N split MS/HS non-US vs. US N NTotal score non-URM vs. URM Y N split MS/HS non-URM vs. URM Y N non-US vs. US N N split MS/HS non-US vs. US N N

Pretest PosttestCell culture non-URM vs. URM N N split MS/HS non-URM vs. URM N N non-US vs. US N N split MS/HS non-US vs. US N NGel electrophoresis non-URM vs. URM N Y split MS/HS non-URM vs. URM Y Y non-US vs. US N Y split MS/HS non-US vs. US N YStaining cells non-URM vs. URM N N split MS/HS non-URM vs. URM N N non-US vs. US N N split MS/HS non-US vs. US N NResearch non-URM vs. URM N N split MS/HS non-URM vs. URM Y N non-US vs. US N N split MS/HS non-US vs. US Y NDissection non-URM vs. URM Y N split MS/HS non-URM vs. URM Y N non-US vs. US Y N split MS/HS non-US vs. US Y NMetric measurements non-URM vs. URM Y N split MS/HS non-URM vs. URM Y Y non-US vs. US Y N split MS/HS non-US vs. US Y N

Differences on pretest and posttest high school only—racial groups—split MS/HS

Pretest Posttest

Gel electrophoresis non-URM vs. URM N Y

nonunderserved vs. underserved N Y

Dissection non-URM vs. URM Y N

Pipetting non-URM vs. URM Y N

nonunderserved vs. underserved Y N

pretest, non-URM high school students had higher scores than URM high school students for the item dissection. Also, for the pretest, both non-URM

The analyses were then simplified for the signifi-cant increase in scores from pretest to posttest for middle school and high school students combined and separate. For the URM students, there were significant increases for 10 out of the 11 items. Non-URM students had increases for all items. When the students were separated by middle school and high school, URM middle school students did not have increases for four items and URM high school students did not have increases for two items. Non-URM students had increases for all 11 items.

and nonunderserved students had higher levels of experience than URM and underserved students for pipetting.


Increases combined URM and non-URM

Increase from pretest to posttest

Cell culture non-URM X

URM X

Gel electrophoresis non-URM X

URM X

Staining cells non-URM X

URM X

Research non-URM X

URM X

Dissection non-URM X

URM X

Metric measurements non-URM X

URM X

Spectrophotometry non-URM X

URM X

Pipetting non-URM X

URM X

Handling science equipment non-URM X

URM X

Making solutions non-URM X

URM X

Lab safety non-URM X

URM

Total score non-URM X

URM X

Increases split MS/HS URM and non-URM


Cell culture MS non-URM X

MS URM X

HS non-URM X

HS URM X

Gel electrophoresis MS non-URM X

MS URM X

HS non-URM X

HS URM X

Staining cells MS non-URM X

MS URM X

HS non-URM X

HS URM X

Research MS non-URM X

MS URM

non-URM X

URM X

Dissection MS non-URM X

MS URM X

HS non-URM X

HS URM X

Metric measurements MS non-URM X

MS URM X

HS non-URM X

HS URM X

Spectrophotometry MS non-URM X

MS URM X

HS non-URM X

HS URM X

Pipetting MS non-URM X

MS URM X

HS non-URM X

HS URM X


Handling science equipment MS non-URM X

MS URM

HS non-URM X

HS URM X

Making solutions MS non-URM X

MS URM

HS non-URM X

HS URM

Lab safety MS non-URM X

MS URM

HS non-URM X

HS URM

Total score MS non-URM X

MS URM X

HS non-URM X

HS URM X

As for the groups based on categorization of school districts, underserved students had increases for 10 out of the 11 items. Nonunderserved students had increases for all items. When the students were separated by middle school and high school, both underserved middle school students and under-served high school students did not have increases for two items. For the last item, lab safety, both middle school and high school nonunderserved students did not have significant increases from self-reported experience levels.


Increases combined MS/HS nonunderserved and underserved


Cell culture nonunderserved X

underserved X

Gel electrophoresis nonunderserved X

underserved X

Staining cells nonunderserved X

underserved X

Research nonunderserved X

underserved X

Dissection nonunderserved X

underserved X

Metric measurements nonunderserved X

underserved X

Spectrophotometry nonunderserved X

underserved X

Pipetting nonunderserved X

underserved X

Handling science equipment nonunderserved X

underserved X

Making solutions nonunderserved X

underserved X

Lab safety nonunderserved X

underserved

Total score nonunderserved X

underserved X

Increases split MS/HS US vs. non-US


Cell culture MS nonunderserved X

MS underserved X

HS nonunderserved X

HS underserved X

Gel electrophoresis MS nonunderserved X

MS underserved X

HS nonunderserved X

HS underserved X

Staining cells MS nonunderserved X

MS underserved X

HS nonunderserved X

HS underserved X

Research MS nonunderserved X

MS underserved

HS nonunderserved X

HS underserved X

Dissection MS nonunderserved X

MS underserved X

HS nonunderserved X

HS underserved X

Metric measurements MS nonunderserved X

MS underserved X

HS nonunderserved X

HS underserved X


Spectrophotometry MS nonunderserved X

MS underserved X

HS nonunderserved X

HS underserved X

Pipetting MS nonunderserved X

MS underserved X

HS nonunderserved X

HS underserved X

Handling science equipment MS nonunderserved X

MS underserved X

HS nonunderserved X

HS underserved X

Making solutions MS nonunderserved X

MS underserved X

HS nonunderserved X

HS underserved

Lab safety MS nonunderserved

MS underserved

HS nonunderserved

HS underserved

Total score MS nonunderserved X

MS underserved X

HS nonunderserved X

HS underserved X

Pretest Posttest

Cell culture non-URM vs. URM N N

split MS/HS non-URM vs. URM N N

non-US vs. US N N

split MS/HS non-US vs. US N N


split MS/HS non-URM vs. URM Y Y

non-US vs. US N Y

split MS/HS non-US vs. US Y Y

Staining cells non-URM vs. URM N N

split MS/HS non-URM vs. URM Y Y

non-US vs. US N N

split MS/HS non-US vs. US N Y

Research non-URM vs. URM N N

split MS/HS non-URM vs. URM Y N

non-US vs. US N N

split MS/HS non-US vs. US Y N

Dissection non-URM vs. URM N N


non-US vs. US N N


Metric measurements non-URM vs. URM N N


non-US vs. US N N


Spectrophotometry non-URM vs. URM N N


non-US vs. US N N


CONFIDENCE

The 11 STEM items were then analyzed for differences and reported on pages 76–84 of the results for confidence levels. The groups that were compared for each item were middle school and high school combined non-URM and URM students, middle school and high school split for non-URM and URM students, middle school and high school combined nonunderserved and underserved students, and middle school and high school split for nonunderserved and underserved students. Overall, there were the same number of differences between the groups on the pretest and posttest: seven out of 44. Gel electrophoresis had the most number of differences, with differences in all of the student group combinations.

Pretest Posttest

Pipetting non-URM vs. URM N N

MS/HS non-URM vs. URM Y N

non-US vs. US N N

split MS/HS non-US vs. US Y N

Handling science equipment non-URM vs. URM N N


non-US vs. US N N


Making solutions non-URM vs. URM N N


non-US vs. US N Y


Lab safety non-URM vs. URM N N


non-US vs. US N N


Total score non-URM vs. URM N N


non-US vs. US N N

non-URM vs. URM Y N



Middle school students and high school students were compared across groups. Among middle school students, URM students had a higher level of agreeability on the pretest than non-URM students but were on the same level for the posttest for gel electrophoresis. As for high school students, non-URM students had a higher level of agreeability than URM students on the posttest. As for the pretest, non-URM students had a higher level of agreeability than URM students for both staining cells and pipetting. Nonunderserved students also had a higher level of agreeability than underserved students for pipetting. There were no differences between the racial groups or groups based on the categorization of school districts for the posttest.

Differences on pretest and posttest middle school only—racial groups

Pretest Posttest

Gel electrophoresis non-URM vs. URM Y N

Differences on pretest and posttest high school only—racial groups

Pretest Posttest


Staining cells non-URM vs. URM Y N

Pipetting non-URM vs. URM Y N

Pipetting nonunderserved vs. underserved Y N

The analyses were then simplified for the signifi-cant increase in scores from pretest to posttest for middle school and high school students combined and separate. URM students had significant increases in scores from pretest to posttest for eight out of the 11 items. Non-URM students had increases for all items. When the students were separated by middle school and high school, URM middle school students had increases from pretest to posttest for one item and URM high school students had increases for eight of the items. Middle school non-URM students had increases for all of the items, and high school non-URM students had increases for 10 of the items.

Increases combined URM and non-URM


Cell culture non-URM X

URM X

Gel electrophoresis non-URM X

URM X

Staining cells non-URM X

URM X

Research non-URM X

URM X

Dissection non-URM X

URM X

Metric measurements non-URM X

URM

Spectrophotometry non-URM X

URM X

Pipetting non-URM X

URM X

Handling science equipment non-URM X

URM X

Making solutions non-URM X

URM

Lab safety non-URM X

URM

Total score non-URM X

URM X


Increases split URM and non-URM


Cell culture MS non-URM X

MS URM

HS non-URM X

HS URM X

Gel electrophoresis MS non-URM X

MS URM

HS non-URM X

HS URM X

Staining cells MS non-URM X

MS URM

HS non-URM X

HS URM X

Research MS non-URM X

MS URM

HS non-URM X

HS URM X

Dissection MS non-URM X

MS URM

HS non-URM X

HS URM X

Metric measurements MS non-URM X

MS URM

HS non-URM

HS URM

Spectrophotometry MS non-URM X

MS URM

HS non-URM X

HS URM X


Pipetting MS non-URM X

MS URM X

HS non-URM X

HS URM X

Handling science equipment MS non-URM X

MS URM

HS non-URM X

HS URM X

Making solutions MS non-URM X

MS URM

HS non-URM X

HS URM

Lab safety MS non-URM X

MS URM

HS non-URM X

HS URM

Total score MS non-URM X

MS URM X

HS non-URM X

HS URM X

As for the groups based on categorization of school districts, underserved students had increases for nine out of the 11 items. Nonunderserved students had increases for all items. When the students were separated by middle school and high school, middle school underserved students had increases for four items and high school underserved students had increases for nine items. As for nonunderserved students, middle school students had increases for all of the items and high school students had increases for nine of the items.


Cell culture nonunderserved X

underserved X

Gel electrophoresis nonunderserved X

underserved X

Staining cells nonunderserved X

underserved X

Research nonunderserved X

underserved X

Dissection nonunderserved X

underserved X

Metric measurements nonunderserved X

underserved X

Spectrophotometry nonunderserved X

underserved X

Pipetting nonunderserved X

underserved X

Handling science equipment nonunderserved X

underserved X

Making solutions nonunderserved X

underserved

Lab safety nonunderserved X

underserved

Total score nonunderserved X

underserved X

Increases combined MS/HS nonunderserved and underserved


Increases split nonunderserved and underserved


Cell culture MS nonunderserved X

MS underserved

HS nonunderserved X

HS underserved X

Gel electrophoresis MS nonunderserved X

MS underserved X

HS nonunderserved X

HS underserved X

Staining cells MS nonunderserved X

MS underserved

HS nonunderserved X

HS underserved X

Research MS nonunderserved X

MS underserved X

HS nonunderserved X

HS underserved X

Dissection MS nonunderserved X

MS underserved

HS nonunderserved X

HS underserved X

Metric measurements MS nonunderserved X

MS underserved

HS nonunderserved

HS underserved X

Spectrophotometry MS nonunderserved X

MS underserved X

HS nonunderserved X

HS underserved X


Pipetting MS nonunderserved X

MS underserved X

HS nonunderserved X

HS underserved X

Handling science equipment MS nonunderserved X

MS underserved

HS nonunderserved X

HS underserved X

Making solutions MS nonunderserved X

MS underserved

HS nonunderserved X

HS underserved

Lab safety MS nonunderserved X

MS underserved

HS nonunderserved

HS underserved

Total score MS nonunderserved X

MS underserved X

HS nonunderserved X

HS underserved X


ADDITIONAL QUESTIONS—CAMPBIOE

Students were asked how many science and math classes they had taken, with options of zero to one, two to three, four to five, and six or more (Table 80). Overall, the highest percentage of number of classes students had taken was six or more. When the students were split between middle school and high school for racial group and groups based on categorization of school districts, an approximately equal amount of middle school non-URM and middle school URM students had taken six or more classes. However, a higher percentage of middle school non-URM students had taken four to five classes compared to middle school URM students. For both middle school non-URM and middle school URM, the highest frequency had taken two to three classes. As for high school students, almost half of non-URM students had taken six or more classes, whereas roughly a quarter of URM students had taken the same amount. The highest frequency of high school URM students had taken two to three classes. The results were similar when the students were broken into nonunderserved and underserved categories. High school underserved students had an equal number and percentage of two to three classes and six or more classes.

However, this question appeared to be too vague. The question was not clear on which grades were included for the question. Some middle school students may have included elementary science and math classes. It would be helpful to ask students, especially high schoolers, if they have

taken specific classes. The survey also could ask separately how many science classes and how many math classes were taken that were not required.

Students also were asked if either parent has a job in STEM (Table 81). Racial groups and groups based on the categorization of school districts had similar patterns. A majority of middle school non-URM, high school non-URM, and middle school URM students had a parent with a job in STEM. However, almost half of high school URM students did not have a parent with a job in STEM. As for groups based on the categorization of school districts, all four groups had a majority of students with a parent that had a job in STEM.

Students were asked if they had ever worked on an ungraded science project outside the classroom and/or participated in a science fair like the Pittsburgh SciTech Festival (Table 82). As for racial groups, middle school non-URM and high school non-URM students had the highest percentage out of the groups that had participated. A little more than half of middle school URM students had participated, and slightly less than half of high school URM students had participated. As for groups based on the categorization of school districts, interestingly, an equal percentage of all four groups had and had not participated, with the majority reporting that they had participated.

Table 80. Number of science and math classes taken

0–1 2–3 4–5 6 or more

n % n % n % n %

All students 10 12.0 28 33.7 16 19.3 29 34.9

Middle school non-URM 2 7.1 10 35.7 7 25.0 9 32.1

High school non-URM 4 16.7 5 20.8 4 16.7 11 45.8

Middle school URM 3 18.8 7 43.8 1 6.3 5 31.3

High school URM 1 6.7 6 40.0 4 26.7 4 26.7

Middle school nonunderserved 1 4.0 9 36.0 7 28.0 8 32.0

High school nonunderserved 3 15.0 5 25.0 3 15.0 9 45.0

Middle school underserved 4 21.1 8 42.1 1 5.3 6 31.6

High school underserved 2 10.5 6 31.6 5 26.3 6 31.6


0

10

20

30

40

50

0

10%

20%

30%

40%

50%

Table 81. Percent of students with at least one parent who had a job in STEM

Yes No I’m not sure

n % n % n %

All students 58 69.0 20 23.8 6 7.1

Middle school non-URM 22 78.6 4 14.3 2 7.1

High school non-URM 20 83.3 4 16.7 0 0

Middle school URM 10 58.8 5 29.4 2 11.8

High school URM 6 40.0 7 46.7 2 13.3

Middle school nonunderserved 21 80.8 2 7.7 3 11.5

High school nonunderserved 17 85.0 3 15.0 0 0

Middle school underserved 11 57.9 7 36.8 1 5.3

High school underserved 9 47.4 8 42.1 2 10.5

How many science and math classes have you taken?

0–1 2–3 4–5 6 or moreMiddle school non-URM

High school non-URM

Middle school URM

High school URM

0

10

20

30

40

50

0

10%

20%

30%

40%

50%

How many science and math classes have you taken?

0–1 2–3 4–5 6 or moreMiddle school nonunderserved




0

20

40

60

80

100

0

20%

40%

60%

80%

100%

Parent has a job in STEM

Yes No I’m not sureMiddle school non-URM

High school non-URM

Middle school URM

High school URM

0

20

40

60

80

100

0

20%

40%

60%

80%

100%

Parent has a job in STEM





Yes No I’m not sure


Table 82. Percent of students who had worked on an ungraded science project or participated in a science fair Yes No

n % n %

All students 48 57.1 36 42.9

Middle school non-URM 17 60.7 11 39.3

High school non-URM 15 62.5 9 37.5

Middle school URM 9 52.9 8 47.1

High school URM 7 46.7 8 53.5

Middle school nonunderserved 15 57.7 11 42.3

High school nonunderserved 11 55.0 9 45.0

Middle school underserved 42.1 57.9 8 42.1

High school underserved 11 57.9 8 42.1

EVALUATION SURVEYS

Each of the evaluation questions was analyzed individually. The questions were grouped together based on the appropriate camp goal. There were no differences on level of agreeability between the racial groups or groups based on the categorization of school districts for the goal of “increase stu-dents’ process skills across disciplines” on either the pre- or postevaluation survey. Based on these results, all students had the desire to participate in activities related to process skills and equally agreed that they learned how to conduct a STEM project and had a lot of hands-on experience.

As for the second goal of “enhance students’ appreciation of science and technology,” out of the four preevaluation questions, there was a relationship between racial group and level of agreeability for the question “I am interested in science and engineering,” with non-URM students having a higher interest than URM students. As for the matching postevaluation question “Since participating in the Bioengineering Camp, my interest in science, engineering, and medicine has increased,” there were no differences between the student groups. Therefore, URM students had a lower interest in STEM at the start of camp but equally agreed with the non-URM students at the end of camp that their interest in STEM increased by participating in the camp. When the students were broken down into middle school nonunder-served, high school nonunderserved, middle school underserved, and high school underserved

0

10

20

30

40

50

60

70

80

0

20%

40%

60%

80%

Have you ever worked on an ungraded science project outside the classroom and/or participated in a science fair like the Pittsburgh SciTec Festival?

Yes NoMiddle school non-URM

High school non-URM

Middle school URM

High school URM

0

10

20

30

40

50

60

0

10%

20%

30%

40%

50%

60%





Have you ever worked on an ungraded science project outside the classroom and/or participated in a science fair like the Pittsburgh SciTec Festival?

Yes No


students, the middle school underserved students had a higher level of agreeability compared to high school underserved students and middle school nonunderserved students for the question “I want to interact with instructors/students with the same interest in science and engineering.” There were no differences between the groups for the other questions on the preevaluation survey. As for the postevaluation survey, there were no differences between the racial groups or groups based on the categorization of school districts for any of the questions. All students equally agreed that their interest in STEM increased by participating in the camp, they enjoyed participating in the camp, they want to learn more about bioengineering in the coming years, they would like to attend another tissue engineering summer camp or program, and the camp was not only educational but also fun.

The third goal was “increase students’ awareness of educational and career opportunities in STEM.” There were no differences between the groups when students were combined middle school and high school. However, when students were separated, high school non-URM students had a higher level of agreeability than middle school URM students for the question “I expect to gain some ideas on whether bioengineering is appropri-ate for me to pursue in the future.” It makes sense that high school students would have higher expec-tations for thinking about bioengineering in the future compared to middle school students. There

were no differences between the groups based on the categorization of school districts for any of the four questions. As for the postevaluation survey, out of the four questions, the only question that had differences between groups was “I plan to take more science classes in the future even if they are not required.” Non-URM students had a higher level of agreeability than URM students for this question. Specifically, high school non-URM students had a higher level of agreeability than URM students for the desire to take more science classes in the future that are not required. There were no differences between nonunderserved and underserved students for any of the questions. By participating in the camp, all students equally experienced what it’s like to be a bioengineer, learned how bioengineers influence our life, gained ideas on whether bioengineering is suitable to pursue in the future, and were inspired to pursue a career in STEM by taking appropriate classes.

By participating in the camp, all students had the same level of agreeability on the postevaluation survey. The results indicate that the camp was effective in attaining its goals of increasing stu-dents’ process skills across disciplines, enhancing students’ appreciation of science and technology, and increasing students’ awareness of educational and career opportunities in STEM.

It is suggested that the evaluation survey be altered for future years to capture true differences

from pretest to posttest. The same questions will be asked for both surveys. The Attitudes Related to STEM Survey addresses dimensions measured for behaviors and attitudes related to STEM, which are perceived potential in STEM, perceived under-standing of the research process related to STEM, attitudes of appreciation for and interest in STEM, and attitudes of awareness of educational and career opportunities in STEM. A total score as well as scores for each of the dimensions will be pro-vided. Perceived potential is a narrowed element of self-efficacy and can be defined as the perceived ability to perform in STEM. If students have an increase in perceived ability by participating in the camp, this would be a significant finding. The second construct is perceived understanding of the research process related to STEM. This construct closely aligns with definitions of manipulative skills and science process skills in the literature. The third dimension measures attitudes of appreciation for and interest in STEM. Appreciation and interest are related due to value. Students will select and persist in activities that are valuable to them. Appreciation implicates perceiving and recognizing value. The fourth dimension is attitudes of aware-ness of future educational and career opportunities in STEM. This construct is necessary to gauge the increased levels of awareness from participation in the camp. The 46-question survey was piloted with approximately 15 middle school and high school students and took five to 10 minutes to complete.


SUMMARY POINTS RECOMMENDATIONS

• Make sure the presurveys and postsurveys are combined. There were technical difficulties with students clicking multiple links.

• Construct the knowledge questions around activities from the camp. The rank order ques-tions need to be simplified. A knowledge test with 10 multiple choice questions, for example, could be developed for a more concrete grading system and simplicity.

• Add the Attitudes Related to STEM Survey.

• Reword the current evaluation questions if they are to be kept in for the following year’s survey, such as double-barreled questions.

• For the question “Where do you see your future career?,” specific jobs and descriptions would be helpful to enable students to understand the career clusters better.

• It would be helpful to follow the participants longitudinally to see if the camp helped in decision making for a career or advanced education in STEM.

• A parent survey also could be developed in order to see if the camp had an effect at home. The survey also could be used to collect information such as the students’ typical grades in school and general interest in STEM.

• An activity performed during the camp could be graded for an additional achievement measure.

• Overall, there were still differences on the postknowledge survey questions with non-URM and nonunderserved students having higher scores than URM and underserved students. URM and undeserved students did, however, have increases from pretest to posttest.

• As for experience and confidence levels for the STEM items, there were more differences between the groups on the pretest than the posttest. Most of the STEM items had increases in experience and confidence levels from pretest to posttest for both of the racial groups and groups based on the categorization of school districts.

• There were few differences between the groups for the pre- and postevaluation survey questions directed toward the three general camp goals of process skills, appreciation and interest, and awareness of educational and career opportunities.

THANK YOU TO OUR SPONSORS:

Advanced Controls & Distribution

ALung Technologies Inc.

CardiacAssist, Inc.

Mr. and Mrs. Theodore D. and Amy B. Clineff

Computer Enterprises, Inc.

The Grable Foundation

InCube Labs, LLC

Innovation Works

LANXESS

Mr. and Mrs. Gerald E. and Audrey L. McGinnis

Philips Respironics

Pittsburgh Life Sciences Greenhouse

Thermo Fisher Scientific Inc.

University of Pittsburgh

Center for the Neural Basis of Cognition

Clinical and Translational Science Institute

Innovation Institute

Office of the Provost

Vascular Medicine Institute

Dr. Elizabeth Woo

University of PittsburghSwanson School of Engineering Department of Bioengineering

302 Benedum Hall3700 O’Hara StreetPittsburgh, PA 15261

engineering.pitt.edu

The University of Pittsburgh is an affirmative action, equal opportunity institution. Published in cooperation with the Department of Communications Services. DCS110457-0517

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