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1 Biomedical Engineering Key Content Survey - Results from Round One of a Delphi Study David W. Gatchell and Robert A. Linsenmeier VaNTH ERC for Bioengineering.

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Presentation on theme: "1 Biomedical Engineering Key Content Survey - Results from Round One of a Delphi Study David W. Gatchell and Robert A. Linsenmeier VaNTH ERC for Bioengineering."— Presentation transcript:

1 1 Biomedical Engineering Key Content Survey - Results from Round One of a Delphi Study David W. Gatchell and Robert A. Linsenmeier VaNTH ERC for Bioengineering Educational Technologies and Northwestern University Whitaker Foundation Biomedical Engineering Educational Summit March, 2005 Supported by NSF EEC

2 2 Why conduct a BME key content survey? Motivation and potential benefits  Motivation  Establish an identity for undergraduate Biomedical Engineers  Improve communication between academic BME programs and industry  Academia – Inform industry of the knowledge, skills and training of BMEs  Industry – Inform academia of the knowledge, skills and training expected  Benefits  More industrial positions for BMEs  Each graduate does not have to explain curriculum  Recognition that BME degree is ideal preparation for at least some industrial positions.

3 3  In General:  An iterative process for collecting knowledge from, and disseminating results to, a group of experts  Four steps (repeat steps #2 and #3 to attempt to reach consensus) 1.Develop a set of questions on a topic. 2.Experts give opinions on topics; suggest new ideas that were missed 3.Explore and evaluate inconsistencies uncovered in step 2 4.Disseminate findings, or revise questions and go back to 2  Key point is that experts remain anonymous  Our Study: A set of three surveys  Round 0: Select concepts from VaNTH taxonomies; reviewed by domain experts  Round 1: Survey BME industrial representatives and faculty. Asked participants to rate relevance of concepts important for ALL undergrads in BME, and make suggestions of concepts missed  Round 2: Refine and update list of concepts and resubmit to the above groups for further evaluation  Round 3: Question proficiencies expected (e.g., using Bloom’s Taxonomy) Delphi study - Overview

4 4  Utilized an online survey tool to query ~274 concepts:  Eleven bioengineering domains (including design)  Physiology, cellular biology, molecular biology and genetics, biochemistry  Mathematical modeling, statistics, general engineering skills (e.g., computer programming)  Survey divided in two parts, each with half the domains:  Total number of participants, n = 136  Part one: Academia – 42, Industry – 25  Part two: Academia – 35, Industry – 23  Participants were asked to:  Provide demographic information  Employer, Job Title, Responsibilities, Years of Experience  Self-assess level of expertise in each domain (e.g., Biomechanics)  Rate the importance/relevance of each concept to a BME core curriculum  Suggest concepts that had not been included Overview of the key content survey, round one

5 5  Concepts rated on 5 point Likert Scale  1- very unimportant for all BMEs  5 – very important for all BMEs  Mean ratings across concepts similar for industry and academia  Academia (n=77) mean and SD rating: 3.71 ± 0.52  Industry (n=48) mean and SD rating: 3.75 ± 0.41  Domains Investigated:  Bioinformatics, bioinstrumentation, biomaterials, biomechanics, biooptics, biosignals and systems, medical imaging, thermodynamics, transport (fluid, heat, mass)  Cell biology, biochemistry, molecular biology and genetics, physiology  Statistics, general engineering Overview of the key content survey

6 6 Some concepts included as “Ringers” - Expected to have low rating ConceptRating (Academia) Rating (Industry) Statistical Physics (e.g., Bose-Einstein statistics; Fermi-Dirac statistics) Statistical Physics (e.g., Partition function; statistical representation of entropy; population of states) Comparative Genomics (e.g., ortholog and paralog genes; gene fusion events) Dynamical Instability and Chaos Unsteady state mass diffusion equation (e.g. Fick’s second law; production and consumption; boundary conditions; different geometries; multiple layers) All except unsteady state mass diffusion equation met expectations

7 7 Some concepts included in more than one domain to check consistency of response  Two values shown are ratings when concepts are included in different domains  Generally good agreement, but rating sometimes depended on context ConceptRatings (Academia) Ratings (Industry) Databases - Interfaces and Structures (e.g., MySQL, relational tables, simple queries, PERL, CGI, DBI) 2.29/ /3.68 Signal Processing to Reduce Noise (e.g., signal-to-noise ratio; signal averaging) 4.24/ /4.14 Properties of Systems (e.g., boundary, surroundings, universe) 3.88/ /3.88 Electrochemical Potential, Nernst Potential, Fick's Law 4.09/ /4.00

8 8 ConceptRating Hypothesis Testing (e.g., paired and un-paired t-tests; chi-square test) 4.69 Principles of Statics (e.g., forces; moments; couples; torques; free- body diagrams) 4.68 Descriptive Statistics (e.g., mean, median, variance, std deviation) 4.63 Circuit Elements (e.g., resistors, capacitors, sources, diodes, transistors, integrated circuits) 4.56 DC and AC circuit analyses (e.g., Ohm's and Kirchoff's laws) 4.56 Mathematical Descriptions of Physical Systems (e.g., functional relationships, logarithmic, exponential, power-law; ODEs; PDEs) 4.54 Strength of Materials (e.g., stress, strain; models of material behavior) 4.53 Pressure-Flow Relations in Tubes and Networks (e.g., flow rate = [change in pressure]/resistance; Poiseiulle relation; Starling resistor) 4.51 Measurement concepts (e.g. accuracy, precision, …4.50 Regression analysis4.49 Forces and pressures in fluids (e.g. shear, normal, surface tension…4.49 Results: Highest rated eng’g concepts – Academia Orange concepts are from statistics and general engineering

9 9 Results: Highest rated eng’g concepts – Industry Orange concepts are from statistics and general engineering Concept Rating Descriptive Statistics (e.g., mean, median, variance, standard deviation) 4.76 Measurement Concepts (e.g., accuracy, precision, sensitivity; error analysis - sources, propagation of error) 4.71 Hypothesis Testing (e.g., paired and un-paired t-tests; chi-squared) 4.65 Probability Distributions (e.g., normal, Poisson, binomial) 4.62 Strength of Materials (e.g., stress, strain; models of material behavior) 4.57 Fundamental Properties of Polymers, Metals and Ceramics 4.50 Product Specification (e.g., requirements, design, reliability, evolution/tracking of the product) 4.45 Principles of Statics (e.g., forces; moments; couples; torques; free- body diagrams) 4.43 Mechanical Properties of Biological Tissues (e.g., elastic; viscoelastic, hysteresis, creep, stress relaxation) 4.43 Data Acquisition (e.g., sampling rates and analog-digital conversion; Nyquist criterion; aliasing) 4.39

10 10 Results: lowest rated concepts some from “Ringers” Academia Databases - Interfaces and Structures (e.g., MySQL, relational tables, simple queries, PERL, CGI, DBI) 2.29 Statistical Physics (e.g., Bose-Einstein and Fermi-Dirac statistics)2.32 Artificial Intelligence (e.g., artificial neural networks, fuzzy logic)2.33 Analysis of Phylogenetic Trees, Molecular Evolution2.47 Comparative Genomics (e.g., ortholog and paralog genes; gene fusion events) 2.50 Structural Prediction and Molecular Design2.53 Industry Statistical Physics (e.g., Partition function; statistical representation of entropy; population of states) 2.58 Statistical Physics (e.g., Bose-Einstein; Fermi-Dirac statistics) 2.58 Artificial Intelligence (e.g., artificial neural networks, fuzzy logic) 2.78 Storage Instruments and their properties (e.g., tape, disk, memory) 2.89 Comparative Genomics 2.94 Root Locus Plots (e.g., definition, properties, sketching) 2.95

11 11 Results: Industry - Academia agreement Distribution of mean ratings of all concepts  Most concepts rated highly. Few ringers in survey.  All traditional domains had some highly rated concepts.  Cutoff level for inclusion in recommended undergrad curriculum still to be determined on basis of further analysis and round two.

12 12 Results: Industry – Academia Agreement Differences in means (A-I) Design

13 13 Results: Discrepancies in design concepts

14 14 Results: A comparison of general engineering concepts

15 15 Results: Biology Domains  Good agreement on the whole  All biology areas important, but industry sees molecular biology as being more important than academia  Bioinformatics generally scored low, but industry feels that it is more important than academia does

16 16 ConceptsAcademiaIndustryAcademia - Industry Flow of Genetic Information (i.e., DNA to RNA to Protein) Methods for Determining Macromolecular Structure (e.g., NMR...) DNA Microarrays Biological Networks (e.g., genetic networks...) Structural Prediction and Molecular Design (e.g., homology modeling and prediction of macromolecular structures and interactions) Results: Largest biology discrepancies

17 17 Results: Physiology (82 concepts)  Very large span within domain  Generally good agreement  Cardiovascular, neural, cellular physiology concepts rated highly  Digestive, renal, parts of endocrine rated low

18 18 Results: Largest physiology discrepancies between academia and industry ConceptsAcademiaIndustryAcademia - Industry Cellular Anatomy (e.g...) Membrane Dynamics (e.g....) Processes of the Kidney (e.g....) Renal Filtration (e.g...) Homeostasis of Volume and Osmolarity Water Balance and Urine Concentration Platelets and Coagulation (e.g....) Sodium Balance and the Regulation of ECF Volume (e.g....)

19 19 Results: Should the following foundational courses be required? Agreement that second semester organic chemistry is not universally required; some uncertainty about one semester

20 20 Universities represented in round one of the survey 1.Arizona State University* 2.Binghampton University 3.Boston University* 4.Columbia University 5.Devry Institute of Tech 6.Duke University* 7.Florida International University 8.IIT 9.Johns Hopkins University* 10.Marquette University* 11.Milwaukee SOE* 12.MIT 13.NJIT 14.NC State University* 15.Northwestern University* 16.RPI* 17.RHIT 18.Stanford University 19.Syracuse University* 20.SUNY – Stony Brook 21.Tulane University* 22.University of Akron* 23.University of Cincinnati 24.University of Illinois – UC* 25.University of Iowa* 26.University of Memphis 27.University of Michigan 28.University of Minnesota* 29.University of Pittsburgh* 30.University of Rochester* 31.University of Texas – Austin* 32.University of Toledo* 33.Vanderbilt University* 34.VCU* *ABET Accredited – 21 of 37 Accredited Programs Participated

21 21 Companies and industrial expertise represented in round one of the survey  Companies Represented  Abbott Laboratories  AstraZeneca  Baxter Healthcare  Boston Scientific  Cardiodynamics  Cleveland Medical Devices  Datasciences, International  Dentigenix, Inc.  Depuy, a Johnson and Johnson Co.  ESTECH Least Invasive Cardiac Surgery  GE Healthcare  Intel, Corp.  Materialise, Inc.  Medtronic, Inc.  Tyco Healthcare  Underwriter Laboratories  Areas of Expertise  Biomaterials  Biomechanics  Bioinformatics  Bioinstrumentation  BioMEMS  Biotransport  Cellular Biomechanics  Computational Modeling  Control Systems Engineering  Fluid Mechanics  Medical Devices  Medical Imaging  Medical Optics  Signal Processing

22 22 Conclusions  More analysis is required to:  Investigate variation of opinions for individual topics  Correlate ratings with expertise levels  Eliminate contextual bias  Incorporate concepts omitted from first round  BUT, preliminary results have shown that:  “Consistency checks” validate data  Generally good agreement between industry and academia  Industry and academia disagree on a significant number of Design concepts  Industry highly values knowledge of statistics and probability  Core biology should include all domains assessed

23 23 Conclusions  Remaining issues  Determine level of significance for deciding what concepts can be dropped from core curriculum  Determine significance of differences between industry and academia  Launch second round – by summer  Full matrix of results by concept will be posted on


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