The University Senate of Michigan Technological University
Proposal 19-09
(Voting Units: Academic)
“Proposal for a Ph.D. Program in
Applied Cognitive Science and Human Factors and M.S. in Applied
Cognitive Science and Human Factors”
Summary
This is a formal proposal
to establish a Doctor of Philosophy and M.S. degree in Applied Cognitive Science & Human Factors in the
Department of Cognitive and Learning Sciences at Michigan Technological
University. The proposed program will help meet strong demand for Human Factors
professionals, will build on Michigan Tech’s existing strengths in science and technology,
and will enable Michigan Tech to develop a nationally recognized program in an
emerging discipline critical to technology. This document provides the
rationale for, and details about the program.
Applied Cognitive Science
- Human Factors
Applied cognitive science
addresses a diverse array of contemporary human phenomena, resulting in
practical solutions for many real world problems. Through the application of cognitive
psychology’s principles, applied cognitive scientists investigate diverse
topics such as effective modes for the delivery of instruction, eyewitness
memory, artificial intelligence, and human factors considerations in the design
of systems.
Human Factors (HF) is the
multi-disciplinary science within the purview of cognitive science that focuses
on the needs of the human in the design of products, work processes, and
technology systems in an effort to optimize human well-being and overall system
performance. HF is concerned with the design and evaluation of technological
systems from the perspectives of human needs, abilities, and limitations. HF
professionals may examine human-machine interactions from cognitive, social,
biological, physical, or other perspectives.
From an Applied Cognitive
Science perspective, Human Factors is involved in conducting research regarding
human cognitive abilities and limitations with respect to the design,
operation, or use of products or systems. It is a subfield of applied cognitive
science that focuses upon human-machine interactions. Overall goals include
optimizing human performance, health, safety, and/or habitability. Thus, the
proposed program in Applied Cognitive Science and Human Factors will integrate
the knowledge of human experts (psychology and cognitive science) and built
systems experts (for example, technology and engineering).
Human Factors is a
critical area of research because of (a) human safety concerns, (b) market forces,
and (c) environmental sustainability. Human operators are often critical
contributors to lapses in overall system safety. Human errors, for example,
have been attributed as the cause of up to 98,000 preventable patient deaths a
year in US medical practice. Despite our desire for automated, faultless
systems, our current technological knowledge is not capable of foolproof technological
fixes to problems of human error. Substantial funding has been allocated to research
on machine intelligence, pattern-recognition technologies, and expert systems,
but there is only one alternative for many complex systems: human operators.
Although they have limitations, humans are excellent pattern recognizers and,
unlike current automated systems, are immensely flexible. HF is concerned with
understanding human abilities and limitations, information critical to the
prevention of human-related errors and the preservation of human life and
well-being.
Critical to understanding
market forces, HF researchers are motivated to assess customer needs and
desires in order to increase customer satisfaction by improving the usability
of products. User-centered design is a
widespread paradigm in information technology and consumer products. The
success of a human factors perspective in improving customer satisfaction in these
industries suggests wider application.
Human Factors is not only
important for human safety, well-being, and the economy, but it is also a
critical component in forming a sustainable society. Many environmental
disasters, such as the Exxon Valdez incident, are due to poor HF design, task
design, and working conditions. Good HF
design not only prevents human casualties, it also prevents environmental
catastrophes. In addition, HF leads to better consumer products. Customers will
discard poorly-designed products as they seek products they can actually use.
Throwing away products because of poor user design is not a sustainable
practice. Therefore, HF design is sustainable design.
There is increasing need
for personnel trained in Human Factors in industry, government, and academia.
According to the US Dept. of Labor Occupational Outlook handbook (2008-09 edition),
employment for all psychologists (including all specialty areas) is expected to
grow 15 percent from 2006 to 2016, faster than the average for all occupations.
Further, they state “Job prospects should be the best for people who have a
doctoral degree from a leading university in an applied specialty…Psychologists
with extensive training in quantitative research methods and computer science
may have a competitive edge…” A survey of three doctoral programs in Human
Factors revealed that 90-95% of their graduates have secured positions prior to
graduation, and 99% obtained employment after graduation, typically in the exact
sub-discipline they desired. Clearly, Human Factors is a growth field with
immense potential that offers great career opportunities. Moreover, salaries
for human factors specialists are the highest among all subfields within
psychology and cognitive science. According to a 2005 salary survey conducted by
the Human Factors and Ergonomics Society, the mean annual base salary is
approximately $92K for a master’s level profession and $105K for persons
holding a doctorate. Doctoral-level consultants are reported as earning an
average of $175K annually.
Opportunities exist and
are expanding in all major employer groups: government, not-for-profit institutions,
consulting firms, private industry, and academic institutions. Work settings
range from classroom, to laboratory, to the industrial design team. Applied
Experimental and Engineering Psychology is increasingly employed in litigation
involving product and workplace safety. Salaries are competitive with those of
engineers and other professionals who work in similar settings. In industry,
there has been explosive growth in the HF job market with the development of
increasingly complicated consumer products, network-centric business (electronic
commerce), and more stringent product liability laws. With new technology, businesses
are increasingly capable of customizing products for individual users. Jobs in
this area of industry are often titled cognitive engineer, customer
experience specialist, ergonomist, human factors engineer, knowledge
engineer, usability specialist, usability engineer, user
experience specialist, and/or user interface
designer. There has also been a surge of employment in the government
sector for personnel trained in HF. For example, employment opportunities exist
in the Department of Defense, Department of Homeland Security, Federal Aviation
Administration, National Aeronautic and Space Agency, transportation, and
intelligence services. The military, for example, has a number of career tracks
for Ph.D.-level HF specialists, including the US Navy’s aviation experimental
psychologist, surface research psychologist, and subsurface research
psychologist, the US Army’s research psychologist, and the US Air Force’s aerospace
research physiologist. In terms of government support, the Department of
Defense’s broad agency announcements consistently identify HF research as one
of the most critical areas of research. HF careers are also available in
academia, in particular in psychology, which is currently the second largest
undergraduate major in the United States, and in interdisciplinary programs
housed in colleges of engineering, science, and medicine.
Rationale
This graduate program
focuses on the application of cognitive science to understanding human use of
and interaction with technology. The Human Factors interdisciplinary field
builds upon psychology, engineering, and computer science/information
technology. Emphasis is on using the methods and theories of cognitive science
to create interventions designed to enhance safety and performance.
Implementation of a graduate program in Human Factors is a key component in the
development of a technological university. This facet, currently underdeveloped
at Michigan Tech, builds upon existing strengths in the Department of Cognitive
and Learning Sciences and in other academic units of the university, integrates
behavioral science research with expertise in engineering and natural sciences,
and is consistent with Michigan Tech’s current strategic plan to “offer
programs in new and emerging areas, particularly interdisciplinary areas.”
More specifically, the proposed program addresses the following areas of Michigan
Tech’s strategic plan:
Goal 2: Deliver a distinctive and rigorous discovery-based
learning experience grounded in science, engineering, technology,
sustainability, and the business of innovation.
2.2 Develop undergraduate and graduate programs in new and
emerging areas.
Goal
3: Establish world-class research, scholarship and innovation in science,
engineering,
and technology that promotes sustainable economic development in
Michigan
and the nation.
3.1 Increase interdisciplinary initiatives to expand knowledge and
address societal needs.
…develop and support
superior graduate programs.
This program will
contribute significantly to the goals of 500 enrolled Ph.D. students at the university
by 2012, and the conferring of 60 Ph.D. degrees annually.
Michigan Tech faculty
members possess considerable expertise in cognitive science and applied cognitive
psychology and in science and engineering fields which study the interaction of
human and technological systems. Current expertise in the Department of
Cognitive and Learning Sciences is in the areas of human memory, perception,
attention, and cognition. Current research projects include work in human-robot
interaction, interface design, multi-modal display design, data visualization,
cognitive-perceptual performance assessment, transportation systems, computer
automated systems, covert communication strategies, detection of deception (polygraph),
human performance modeling, and STEM education. Affiliated faculty in the departments
of Computer Science, Civil and Environmental Engineering, Electrical and Computer
Engineering, Exercise Science, Health, and Physical Education, Mechanical Engineering-Engineering
Mechanics, and Biomedical Engineering have expertise in human computer interaction,
simulations, robotics, biomechanics, and work physiology.
By integrating cognitive
and HF psychologists and STEM education researchers with science and engineering
faculty, this program merges cognitive science research with applications in a wide
range of STEM fields. By combining faculty expertise in human subjects research
with scientific and engineering expertise, the program will enhance
interdisciplinary research at Michigan Tech and strengthen the university’s competitiveness on complex projects at the interface
of human and technical systems.
This program responds to
the national need to better understand how technological systems are limited by
human operators. The modern world is increasingly being integrated with
advanced, although very complicated, communication equipment. While this speeds
up the pace of transactions, it also introduces new risks for designers who may
make products unsuitable for the intended users. The business world is shifting
to fast, lean, agile, just-in-time production methods. There will increasingly
need to be a tight integration between usability-consumer research and
manufacturing. Transportation systems are becoming more complex. Without seriously
considering human operators and their limitations, modern society is setting
itself up for catastrophic loses. Many disasters can be attributed to poor
human-machine interaction or systemic design errors. Our graduates will be well
prepared to rectify this situation, and the skills the program will provide are
in very high demand by industry and government.
1. Program Description
The proposed program will
be offered by the Department of Cognitive and Learning Sciences. Affiliated faculty in other academic units
will also be directly involved as adjunct faculty in the program. The program
provides a strong scientific basis in human subjects research and in the core
areas of cognitive science necessary to skillfully undertake research on the
interface of human behavior and technological systems. The program is a
research-intensive curriculum, which includes a core in psychology and research
methods. Students will select an area of specialization in which to focus their
elective coursework and their dissertation research.
Course Requirements
The doctoral program in
Applied Cognitive Science and Human Factors (ACSHF) will require a minimum of
72 credit hours. This consists of 32 hours from the core courses and required research,
30 hours of electives, and 10 dissertation research hours. Although most Michigan
Tech Ph.D. programs require only 60 credits, nationally, most Human Factors and
related programs require between 80 and 90 credits. A sampling of such programs
yielded an average of 83 credits required. Likewise, many Michigan Tech
programs have limited course requirements; however, Applied Cognitive Science
and Human Factors is a field in which students rarely have much undergraduate
preparation, so considerable work in basic subject matter is necessary to
prepare students to conduct appropriate research. Below is a list of required
and potential elective courses; a list of which faculty may teach each course
is listed in Appendix A.
Core Courses and Required Research (32 credits)*
PSY 5100 Applied Cognitive Science (3 hrs)
PSY 5850 Human Factors I (3 hrs)
PSY 5860 Human Factors II (3 hrs)
PSY 5210 Advanced Statistical Analysis and Design I (4 hrs)
PSY 5220 Advanced Statistical Analysis and Design II (4 hrs)
PSY 5010 Cognitive Psychology (3 hrs)
PSY 5160 Sensation and Perception (3 hrs)
PSY 5060 Behavioral Neuroscience (3 hrs)
PSY 5900 Graduate Research Project (6 hours)
*Depending upon background of individual students, some of these
courses may be waived.
Electives (30 credits)**
PSY 5300 Human Performance (3 hrs)
CS 5760 Human-Computer Interaction and Usability Testing (3 hrs)
PSY 5400 Ergonomics and Biomechanics (3 hrs)
ED 5510 Educational Technology (3 hrs)
PSY 5500 Supervised Teaching Practicum (3 hrs)
PSY 5610 Automation (3 hrs)
PSY 5620 Displays and Alarms (3 hrs)
PSY 5910 Independent Research (3 hrs)
PSY 5880 Current Issues in Human Factors (1-3 hrs)
PSY 5190 Special Topics in Cognitive Science (3 hrs)
PSY 5890 Special Topics in Human Factors (3 hrs)
* At least 9 credits must be from coursework; students will
select courses in consultation with the advisor. Additional courses not listed here may be
accepted as electives (see Section 7, Other Courses). Up to 21 credits of
independent research may be applied towards the 30 required elective hours. A
minimum of 9 elective hours must come from coursework, which comprises a
student’s area of specialization within ACSHF.
Dissertation (10 credit hours)
PSY 6999 Dissertation Research (10 hrs)
72 Credit Hours Total
M.S. degree requirements. Students who wish to
terminate their studies after two years may acquire a M. S. degree by completing
the core courses and six credits of required research for a 32-credit master’s
degree in Applied Cognitive Science and Human Factors. It is not our intention
to admit students to a terminal master’s degree program, however utilizing
standard practice in graduate programs at Michigan Tech, students who are
unable to complete the Ph.D. may be allowed to earn a M. S. degree upon
completion of the core courses and required research.
2. Rationale
See pp. 2-4, above.
3. Related Programs at Michigan
Tech and Elsewhere
The proposed Doctorate of
Philosophy in Applied Cognitive Science and Human Factors will complement other
programs at Michigan Tech and will be interdisciplinary in nature. There are no
related programs at the university, although faculty in the Department of
Cognitive and Learning Sciences has established a collaborative network for
research in Human Factors with researchers in numerous science, engineering,
and related departments. The Department of Cognitive and Learning Sciences
offers a B.S. degree in Psychology.
There are no doctoral
programs in Human Factors in Michigan. Central Michigan University offers a
Ph.D. in applied experimental psychology, which potentially overlaps with
Cognitive Science and Human Factors when applied to technological systems.
Several Michigan universities offer graduate programs in Industrial Engineering
or Industrial Design, somewhat related yet distinct disciplines that typically
offer a single course pertaining to Human Factors. Michigan State University offers an
interdisciplinary specialization in Cognitive Science, but not a degree.
In the upper Midwest, only
the University of Minnesota-Twin Cities has a comparable degree program. They
offer a graduate minor in Cognitive Science or in Human Factors for
Ph.D. or M.A./M.S. programs. Additionally, they offer a Human Factors emphasis
as part of their Kinesiology Ph.D. program.
The Human Factors and
Ergonomics Society lists 120 graduate programs related to human factors in the Directory
of Human Factors/Ergonomics Graduate Programs in the United States and Canada.
Forty-three percent are doctoral programs, most of which are housed either in Industrial
Engineering (41%) or Psychology (39%) departments. The remaining doctoral programs
reside in departments such as Cognitive Science, Environmental Medicine, Design
and Environmental Analysis, or Kinesiology; other programs are of an
interdisciplinary nature and are housed in the graduate school. Of the
Industrial Engineering programs, the majority (61%) offer concentrations
through optional coursework rather than specific degrees in human factors or
cognitive science.
Only two of Michigan Tech’s
benchmark universities offer doctoral programs in Cognitive Science or Human
Factors: Rensselaer (Cognitive Science) and Georgia Tech (Human Factors).
Georgia Tech offers a Human Factors concentration at the bachelor degree level.
None of our benchmark universities offers an interdisciplinary program
combining both fields.
4. Projected Enrollment
We anticipate that two
students will enter the program by Fall, 2010. Thereafter, we expect 3 new
students per year. Within 6-7 years the program will have between 12 and 15
students and an average of 3 new Ph.D. students will complete the program
annually.
HF Ph.D.
Enrollment |
2009-10 |
2010-11 |
2011-12 |
2012-13 |
2013-14 |
2014-15 |
2015-16 |
2016-17 |
Attrition
= 25%>yr.3 Planning |
Planning
& Recruiting |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
New
Students |
|
2 |
2 |
3 |
3 |
4 |
4 |
4 |
Returning
Students |
|
|
2 |
4 |
6 |
7 |
10 |
11 |
Total
Enrollment |
|
2 |
4 |
7 |
9 |
11 |
14 |
15 |
Ph.D.s
Awarded |
|
|
|
|
1 |
1 |
2 |
3 |
Three students will be
supported as GTAs; ten students will be supported by external research funds;
the remainder will be self-supported. External funding is anticipated to come
primarily from US Department of Defense (see page 2), but also the National
Science Foundation and National Institutes of Health. The result will be
approximately two Ph.D. students per full-time graduate faculty member.
5. Scheduling Plans
The program will be a
regular on-campus offering, with inception planned for Fall, 2010. The 2009-2010
academic year will be used for student recruiting. All core courses will be
offered regularly (either annually or biennially), beginning Fall, 2010.
6. Curriculum Design
The core courses in the
program (see Program Description, above) are designed to provide students,
particularly from engineering and computer science, with fundamental
understanding of human behavior, expertise in conducting research with human
subjects, and an overview of the concepts, tools, and applications of Human
Factors psychology. These eight core courses will be taken during the first 3
semesters in the program and will be taught by Cognitive and Learning Sciences
faculty.
Areas of Specialization
Upon completion of the
core courses, students will identify an area of specialization, from which they
will select at least 18 credits to ensure sufficient depth and expertise to
conduct dissertation research. Potential areas of specialization include the
following:
• Human Performance
• Human-Computer
Interaction
• Adaptive
Automation/Biosensors
• Educational Technology
• Environmental Design
•
Transportation/Geospatial Systems
• Manufacturing Systems
• Construction
Comprehensive Exam
To obtain doctoral
candidacy status, students must pass a comprehensive written examination. The comprehensive exam is taken after all
required courses and course-based electives are completed. It must be passed
within five years of starting the ACSHF program and at least two semesters
prior to the dissertation defense. The exam will consist of four sections with
questions covering the following topics: 1) applied cognitive science/cognitive
psychology, 2) human factors/human performance, 3) research
methodology/statistics, and 4) a specialty topic within ACSHF. Each section may
contain multiple questions evaluating whether the student is capable of concept
integration and application at the doctoral level. Questions for the first
three sections will be provided by ACSHF faculty. A committee comprised of
three faculty members of the student’s choosing will supply questions for the
specialty area. The student’s answers will be graded by a minimum of two
faculty members. Passage is required on all four sections to be considered a
doctoral candidate. If a student fails one section, a remediation project to compensate
for an area deficiency will be developed by relevant faculty in coordination
with the student’s advisor. If a student fails two or more sections, the exam
is considered failed en toto. The
student must retake and pass the entire exam at the next scheduled
administration. If a student fails to pass all sections of the exam upon
retaking it, he/she may be asked to withdraw from the program and may be
awarded a master’s degree in lieu of the doctorate, if the requirements for the
master’s degree have been met.
Doctoral Dissertation
Dissertation Committee and Proposal Process
Once a student has doctoral candidacy status, he/she may
officially form a dissertation committee. Students must submit a form signed by
all committee members declaring the make-up of the committee. Any changes to
committee membership must be made in writing. The committee should have four
members, two of whom must be faculty within the Department of Cognitive and
Learning Sciences and one faculty member from outside the ACSHF Program. One
committee member must be designated as the committee chair. Once the chair is
satisfied with the student’s dissertation proposal, a proposal defense may be
scheduled. The defense consists of an oral presentation before the committee.
All committee members must sign-off on the proposal indicating their approval
before the student may begin any data collection.
Oral Dissertation Defense
When the research is complete and the committee chair is satisfied
with the manuscript, the student should send the dissertation to all other
committee members to prepare for the defense. The dissertation defense is
public, in that any member of the university committee may attend. The defense
must be advertised a minimum of two weeks in advance of the scheduled defense
date. All committee members must be present at the defense. After the defense
presentation and a period of questioning from committee members, the committee
will hold a private vote on two items. The first is whether the defense was
passed (yea or nay). The second item is the status of the dissertation manuscript
(accepted without revisions, accepted with minor revisions, or not accepted/needs
extensive revisions).
7. New Course Descriptions
PSY 5860 Human Factors II (3) – An overview of the tools and
techniques used by human factors researchers and practitioners. Topics include
task analysis, link analysis, human error in systems, workload analysis, and
physiological assessment techniques.
PSY 5210 Advanced Statistical Analysis and Research Design I (4) –
An overview of research ethics, experimental design, proposal writing, and
univariate statistics such as tests and ANOVA.
PSY 5220 Advanced Statistical Analysis and Research Design II (4)
– A continuation of PSY 5210 covering multivariate and nonparametric statistics
such as MANOVA, ANCOVA, Multiple Regression, factor analysis, and Chi Square.
PSY 5300 Human Performance (3) – An overview of factors
contributing to human performance in human-machine systems. Topics include
cognitive workload, attention, fatigue, aging, stress, and perceptual
limitations.
PSY 5400 Ergonomics and Biomechanics (3) – An overview of the
physical aspects of user-centered design. Specific topics include
anthropometry, repetitive strain injuries, and physical workload evaluation.
PSY 5610 Automation (3) – An overview of the changing role of
human users in
automated systems. Topics include levels of automation, automation
trust issues,
automation uses and misuses, and the role of automation in human
performance.
PSY 5620 Displays and Alarms (3) – An overview of display and
alarm display design principles for human-machine systems. Topics include
visual, auditory, and tactile display design, masking and alarm detection, and
the cry wolf effect and alarms.
PSY 5910 Independent Research (3) – Study of a specific cognitive
science or human factors problem.
PSY 5880 Current Issues in Human Factors (1) – An overview of the
state of the field of human factors, trends, ethics for human factors
practitioners, and career development.
PSY 6991 Special Topics in Human Factors (3) – Study of special
topics in human factors as designed by section title.
PSY 6990 Special Topics in Cognitive Science (3) – Study of
special topics in cognitive science as designed by section title.
PSY 5998 Research Project I (3) – Proposal and data collection
phases of an independent research project.
PSY 5999 Research Project II (3) – A continuation of PSY 5998,
analysis and public presentation of research results.
PSY 6999 Dissertation Research (10) – Fundamental and applied
research in cognitive science and human factors psychology. Taken by doctoral
students in partial fulfillment of the PhD research requirement.
Other Courses (catalog descriptions are
in Appendix B)
PSY 5010 Cognitive
Psychology
PSY 5100 Applied Cognitive
Science
PSY 5060 Behavioral
Neuroscience
PSY 5160 Sensation and
Perception
PSY 5850 Human Factors I
BE 5110 Neuroengineering
BE 5700 Biosensors
BL 4470 Analysis of
Biological Data
CE5404 Transportation
Planning
CE 5410 Intelligent
Transportation Systems
CS 4760 Human-Computer
Interactions
CS 4811 Artificial
Intelligence
CS 5811 Advanced
Artificial Intelligence
ED 5510 Special Studies in
Educational Technology
EE 4250 Communication
Theory
EE 4257 Digital Image
Processing
EE 5530 Wireless Digital
Communication
EH 4400 Motor Control
EH 4420 Motor Learning and
Development
EH4500 Biomechanics of
Human Movement
EH 5350 Special Topics in
Kinesiology
FW 4130 Biometrics
MA 4720 Design and
Analysis of Experiments
MEEM 4660 Data Based
Modeling & Control
MEEM 4705 Introduction to
Robotics and Mechatronics
MEEM 5602 Process and
Product Design and Improvement
8. Library and Other
Learning Resources
Access to scholarly
materials is absolutely essential at a research institution such as Michigan Tech,
particularly for faculty mentoring doctoral students through high-quality,
funded research. The Van Pelt library
currently subscribes to 23 journals that are core to the Applied Cognitive Science
and Human Factors program. In addition, the library has supporting journal
holdings in engineering, computer science, exercise science, general
psychology, and teacher education.
Enhancing our electronic
database search engine PsychFirst is required. Michigan Tech currently offers database
search access to psychology publications from only the preceding three years.
Access to a more complete database and subscriptions to additional journals
beyond our current holdings will be essential for both faculty and graduate
students. This will require the availability of PsycINFO and PsycARTICLES.
Subscriptions to nine
additional journals is essential to the program (see Appendix C).
New library costs include
(costs were estimated in consultation with Ellen Seidel):
$3000.00 one-time
allotment for the library to purchase core monographs in the area of cognitive
and
human factors psychology, allowing the
purchase of approximately 90 hard and softcover items.
$5782.00 for nine
additional journals.
$7200.00 (annual cost)
provides full database search capability of the psychology literature (through
PsycINFO in journal, book, and book
chapter, and dissertation records, 1887– present, and
PsycARTICLES records, 1988–present, to
all faculty and students.
Additional Interlibrary
loan costs will be generated for the library.
9. Computing Access Fee
Graduate students in the
program will pay the standard Computing Access Fee to utilize the current
undergraduate computing lab for Psychology majors.
10. Faculty Curriculum
Vitae (complete vitae provided upon request)
Cognitive & Learning Sciences Faculty:
Susan L. Amato-Henderson, Ph.D.
Associate Professor of Psychology
PhD, University of North Dakota
Psychology and law (eyewitness memory, credibility assessment,
field sobriety testing); career and educational interests and decision making;
self efficacy (your belief in your ability to do well in a given situation or
setting); service learning as a teaching tool; outcome assessments;
experimental design and statistical analysis
J. Christopher Brill, Ph.D.
Assistant Professor of Psychology, Cognitive & Learning
Sciences
PhD, University of Central Florida
Tactile communication, mental workload, cognitive resource theory,
multi-modal display and alarm design, spatial audio, human performance
assessment, motion and simulator sickness, Sopite Syndrome (motion-induced drowsiness)
William S. Helton, Ph.D.
Assistant Professor, Department of Cognitive & Learning
Sciences
PhD, University of Cincinnati
Engineering (human factors) psychology, environmental psychology, neurophysiological
measures of cognition, psychometrics (stress and workload), skill acquisition
in humans and working dogs
Kedmon N. Hungwe, Ph.D.
Assistant Professor, Cognitive & Learning Sciences
PhD, Michigan State University
Learning and development; educational policy & practice;
educational media/technology
Rosalie P. Kern, Ph.D.
Associate Professor of Psychology, Department of Cognitive &
Learning Sciences PhD, Central Michigan University
Emotion, attention, and memory; decision making; perceptions of
sexual harassment; psychology and law (trial consulting); experimental design
and statistical analysis
Adjunct Faculty:
Jason Carter, Ph.D.
Chair & Assistant Professor of Exercise Science, Health and
Physical Education Adjunct Assistant Professor, Cognitive & Learning
Sciences
Adjunct Assistant Professor, Biological Sciences
PhD, Michigan Technological University
Regulation of arterial blood pressure, the vestibulosympathetic
reflex in humans, autonomic and cardiovascular adaptations to microgravity and
exercise
Michele Miller, Ph.D.
Associate Professor of Mechanical Engineering
PhD, North Carolina State University
Precision engineering, microelectromechanical systems, engineering
education
Amlan Mukherjee, Ph. D.
Assistant Professor of Civil Engineering
Member, Michigan Tech Transportation Institute
Engineering-Environmental (inter-disciplinary program)
PhD, University of Washington
Planning and decision making in construction management using
situational simulations, information visualization, transportation
infrastructure management, simulations of complex systems, system dynamics,
expert novice cognition (especially among construction managers)
Michael Neumann, Ph.D.
Professor & Chair of Biomedical Engineering
Adjunct Professor of Electrical Engineering
PhD Case Institute of Technology, MD Case Western Reserve
University Biomedical instrumentation, biomedical sensors, microfabrication
technology and perinatal medicine
Robert Pastel, Ph.D.
Assistant Professor, Computer Science
PhD, University of New Mexico
Human-computer interaction and human-robot interaction
Jindong Tan, Ph.D.
Assistant Professor of Electrical and Computer Engineering
PhD, Michigan State University
Computer engineering, mobile robotics
11. Available/Needed
Equipment Facilities
The department of
Cognitive and Learning Sciences operates or has access to seven dedicated laboratories.
Human-Robot Interaction Laboratory in Advanced Technology
Development Center equipped with unmanned aerial and ground robot vehicles,
including 6 ground active-robots, 10 ground Romba robots (Irobot), and 2
remote-controlled helicopters, sensors (laser range finders, sonar systems,
visual capture systems), computers, and a wide-scale sensor network for environmental
sensing.
Virtual Reality Laboratory in Rehki equipped with a
GeoWall 3-d projection system, World Viz virtual reality system, magnetic and
optical tracking equipment, head-up displays, computers, and interface
equipment (joysticks, steering wheels, data-gloves).
Human Fatigue and Vigilance Laboratory in Chemical Sciences
equipped with MindWare Technologies Biomedical Signal Processing Systems,
Respironics Actigraphy System, Companion III Transcranial Doppler Sonography
Unit, Seeing Machines Eye-tracker, Arrington Eye-tracker, and computers
programmed with Superlab software.
Multimodal Interface Laboratory in Chemical Sciences
equipped with a 24 Channel Vibrotactile Laboratory Display System, a 8 Channel
Vibrotactile Laboratory Display System, a 8 Channel Wireless Vibrotactile
Display System, and computer programmed with SuperLab software.
Emotion and Memory Laboratory in Chemical Sciences
equipped with computers programmed with SuperLab software and other specialized
programs.
Detection of Deception Laboratory in Chemical Sciences equipped
with video recording equipment, computers, and a polygraph unit.
Educational Technology Laboratory in Academic Office
Building equipped with computers, Vernier Software and Technology, including
sensors for use with our Vernier interfaces.
No additional equipment will be necessary to initiate the program.
Additional space needs are addressed below in Section 13.
12. Program Costs
Additional recurring costs
are associated with implementation of this program (Appendix A). Three new graduate assistant lines to support
teaching of introductory psychology courses will be necessary during the first
five years of the program. New human factors faculty will be necessary to
support existing faculty with undergraduate teaching obligations and to teach
the required core courses in the program. New faculty should have expertise in
the following areas:
Applied
Cognitive Science - Cognitive Ergonomics or Human-Computer Interaction
Human
Factors Psychology - Visual Performance and Display
Quantitative
Psychology; I/O Psychology: Simulation and Training or Team Performance
Two new faculty members
will be needed when the program is initiated (Fall, 2010). The third faculty
member (in Quantitative Psychology) will be added in the third year of the
program, as externally funded research funds result in greater demands on the
time of existing faculty.
Additional ongoing funds
for library journals and online journal access will also be needed (see #8,
above). The addition of these faculty members will enable the program to
accommodate up to 15 students (approximately 2 Ph.D. students per full-time
faculty member).
13. Space
Currently, each faculty
member has an office and a 100 square foot room for research. The department
also rents a 1000 square foot high bay facility for HF research. Other Human
Factors programs typically provide approximately 1000 square feet of lab space
per faculty member, with space increasing to nearly 2000 square fee for faculty
with external funding. In addition, nearly all programs at other institutions
have a dedicated teaching laboratory averaging 700 square feet (Appendix B).
We currently have 1438
square feet consisting of faculty offices, laboratories, a reception area, and
a small conference room. This space is satisfactory for an undergraduate
program with modest research activity, but additional space is essential if the
program is to be successful. The Department of Cognitive and Learning Sciences
has no excess space. New faculty will require office space and research
facilities in order to carry out their research and scholarship obligations.
Graduate students will also need office space. Without additional space, the
Ph.D. program cannot be implemented. We are requesting approximately 10,000
square feet of space.
A breakdown of this space
request is provided in the table below:
Allocated
Use Approximate
Size (Sq Ft)
7 Faculty Offices (144
sq ft each) |
1008 |
7 Laboratory Suites
(1000 sq ft each) |
7000 |
2 GTA Offices (250 sq ft
each; 2-3 students in each) |
500 |
Reception/Common Area |
400 |
Seminar/Conference Room |
500 |
Graduate Teaching
Laboratory |
600 |
Total:
10,008
14. Policies, Regulations
and Rules
No additional policies, regulations, or rules
beyond those mandated by the Graduate School.
15. Accreditation
Requirements
Accreditation is not necessary for this
program.
16. Internal Status of
Proposal
Dept. of Cognitive &
Learning Sciences, _March 24, 2008____,Date Approved_______
Dean, College of Sciences and
Arts, __April 14, 2008_______,Date Approved_______
Provost, ____________________,Date
Approved_______
Graduate Faculty Council __November 4, 2008___,Date Approved_______
University Support Units, ____________________,Date Approved_______
University Senate, ____________________,Date Approved_______
Academic Affairs Officers,
____________________,Date Approved_______
Board of Control, ____________________,Date
Approved_______
17. Planned Implementation
Date
Fall, 2009, for planning, faculty recruiting,
and student recruiting. First students begin Fall, 2010.
APPENDIX A Courses and Potential Faculty
Assignments
Course Number |
Course
Title |
Amato |
Brill |
Helton |
Hungwe |
Kern |
Adjunct Faculty |
New Hires |
PSY 5100 |
Applied Cognitive Science |
|
|
x |
|
x |
|
x |
PSY 5850 |
Human Factors I |
|
x |
x |
|
|
|
|
PSY 5860 |
Human Factors II |
|
x |
x |
|
|
|
|
PSY 5210 |
Advanced Statistical
Analysis and Design I |
x |
x |
x |
|
x |
|
x |
PSY 5220 |
Advanced Statistical Analysis and Design II |
|
|
x |
|
|
|
x |
PSY 5010 |
Cognitive Psychology |
|
x |
|
|
x |
|
x |
PSY 5160 |
Sensation and Perception |
|
x |
|
|
|
|
|
PSY 5060 |
Behavioral Neuroscience |
x |
x |
x |
|
|
x |
x |
PSY 5300 |
Human Performance |
|
x |
x |
|
|
x |
x |
CS 5760 |
Human-Computer
Interaction and Usability |
|
|
|
|
|
x |
|
PSY 5400 |
Ergonomics and Biomechanics |
|
|
|
|
|
x |
x |
ED 5510 |
Educational Technology |
|
|
|
x |
|
|
|
PSY 5610 |
Automation |
|
|
x |
|
|
|
x |
PSY 5620 |
Displays and Alarms |
|
x |
|
|
|
|
|
PSY 5880 |
Current Issues in Human Factors |
|
x |
x |
|
|
|
x |
PSY 6991 |
Special Topics in Human Factors |
|
x |
x |
|
|
|
x |
PSY 6990 |
Special Topics in Cognitive Science |
|
|
x |
|
x |
|
x |
Note: Required courses are listed in italics;
elective courses are in plain text. An “x” indicates the person is qualified
and may teach the course. Actual course assignments will be determined at the
time of implementation.
APPENDIX B Existing Courses with
Catalog Descriptions
PSY 5010 Cognitive
Psychology
A systematic survey of classical and
contemporary research topics in human information processing and
learning. Topics include models of cognition,
perception/pattern recognition, attention, the nature of
mental representation and processing; the architecture
of memory, imagery, concepts, and prototypes;
reasoning, decision making, problem solving,
and cognitive development.
PSY 5100 Applied
Cognitive Science
Survey of applied human information
processing literature, detailed review of recent developments in
applied cognitive science, and exaination of
the purposes, role and scope of cognitive engineering.
PSY 5060 Behavioral
Neuroscience
Advanced topics in the field of behavioral
neuroscience and neuroergonomics. Topics may include motor
and sensory systems and complex motivated
behaviors such as vigilance, attention, adaptive automation, and fatigue
countermeasures.
PSY 5160 Sensation
and Perception
Examination of basic sensory mechanisms and
perceptual phenomena. Sensory mechanisms reviewed
will include vision, audition, olfaction,
gustation, vestibular system and touch.
PSY 5850 Human
Factors I
Advanced concepts critical to the design of
human-technological systems, such as capitalizing upon
human capabilities and compensating for human
limitations. Topics may include perceptual and motor
abilities, human error and cognitive
engineering.
BE 5110 Neuroengineering
Brief overview of neuroanatomy,
neurophysiology, and neurobiology followed by introductions of more
advanced topics including neural tissue
engineering, neural/electrode interfaces, and functional electrical
stimulation.
BE 5700 Biosensors
This course introduces the student to the
fundamentals of biosensor development and applications. It
provides an understanding of biological components,
immobilization methods, transducers, and
fabrication techniques.
BL 4470 Analysis
of Biological Data
Methods and techniques of analyzing
quantitative biological data and of designing biological
experiments.
CE5404 Transportation
Planning
Introduction to urban transportation
planning, travel characteristics, demand forecasting techniques,
corridor studies, traffic impact studies, and
public transit planning and operations.
CE 5410 Intelligent
Transportation Systems
Introduction to ITS, concepts, technologies,
activities, and deployment issues. Topics include advanced
traffic management, traveler information
systems, commercial vehicle operations, vehicle control
systems, ITS applications in public transit,
and rural ITS.
CS 4760 Human-Computer
Interactions
Principles of design and implementation of
user interface (UI). Topics include: UI design principles,
evaluation, tools and theory. Students
receive direct experience with designing, implementing, and
evaluating UIs. Requires completion of a
group project.
CS 4811 Artificial
Intelligence
Fundamental ideas and techniques that are
used in the construction of AI problem solvers. Topics include knowledge
representation, problem solving, heuristics, search heuristics, inference
mechanisms, expert systems, and language understanding.
CS5760 HCI
Evaluation and Usability Testing
Current issues in human-computer interaction
(HCI), evaluation of user interface (UI) design, and
usability testing of UI. Course requires
documenting UI design evaluation, UI testing, and writing and
presenting a HCI survey, concept or topic
paper.
CS 5811 Advanced
Artificial Intelligence
Course topics include current topics in
artificial intelligence including agent-based systems, learning,
planning, use of uncertainty in problem
solving, reasoning, and belief systems.
ED 5510 Special
Studies in Educational Technology
Individual or group studies of specially
selected issues or problems in educational technology. Credit may be granted
for scholarly work under the supervision of departmental-approved, authorized
University
faculty members that results in an acceptable
scholarly product_research reports, curricula, computer
program, or other.
EE 4250 Communication
Theory
Introduces the mathematical theory of
communication science. Topics include baseband and digital
signaling, bandpass signaling, AM and FM
systems, bandpass digital systems, and case studies of
communication systems.
EE 4257 Digital
Image Processing
Image formation, enhancement and
reconstruction. Applications in medical imaging, computer vision,
and pattern recognition.
EE 5525 Wireless
Digital Communication
Principles of wireless communications
systems. Projects may include cell phones, computer networks,
paging systems, satellite communications, radio,
television and telemetry.
EH 4400 Motor
Control
Designed for upper level undergraduates or
graduates with a basic neuroscience background. Students
learn the basics of how the neural and
muscular systems coordinate human movement. This will require
an integration of biomechanics, molecular and
cellular neurophysiology, cognitive neuroscience, and
sensory motor skills.
EH 4420 Motor
Learning and Development
Designed for upper level undergraduates or
graduates with a basic neuroscience background. Students
learn the basics of how humans learn to
control muscles and coordinate movement (motor learning), and
how motor behavior progressively changes
throughout a life cycle (motor development).
EH4500 Biomechanics
of Human Movement
An in-depth view of the biomechanical
properties of the musculoskeletal system. The course provides
detailed analyses of the kinetics of human
movement, material properties of the component tissues, and
dynamic processes of adaptation to stress and
strain of the system.
EH 5350 Special
Topics in Kinesiology
Selected additional topics in kinesiology for
advanced students based on interests of faculty and students. Interested students should contact the
Exercise Science, Health and Physical Education department.
FW 4130 Biometrics
Application of statistical and mathematical
methods to ecological issues. Subjects include exploratory
data analysis, monitoring programs and
development of prediction equations.
MA 4720 Design
and Analysis of Experiments
Covers construction and analysis of
completely randomized, randomized block, incomplete block, Latin
squares, factorial, fractional factorial,
nested and split-plot designs. Also examines fixed, random and
mixed effects models and multiple comparisons
and contrasts. The SAS statistical package is an integral
part of the course.
MEEM 4660 Data
Based Modeling & Control
System modeling from observed data for
computer-aided design and manufacturing, providing
differential equation models. Analysis of
manufacturing and dynamic systems, computer routines for
modeling, forecasting with accuracy
assessment, and minimum mean-squared error control. Underlying
system analysis, including stability and
feedback interpretation, periodic and exponential trends.
Illustrative applications to real-life data.
MEEM 4705 Introduction
to Robotics and Mechatronics
Cross-discipline system integration of
sensors, actuators, and microprocessors to achieve high-level
design requirements, including robotic
systems. A variety of sensor and actuation types are introduced,
from both a practical and a mathematical
perspective. Embedded microprocessor applications are
developed using the C programming language.
MEEM 5602 Process
and Product Design and Improvement
System modeling and analysis from observed
data for computer-aided design and manufacturing,
providing differential equation models.
Computer routines for modeling, forecasting with accuracy
assessment and minimum mean-squared error
control. Underlying system analysis, including stability and feedback interpretation,
periodic and exponential trends. Uses illustrative applications to real-life
data, including team projects.
APPENDIX C Library Holdings and Needs
Journals in J. R. Van Pelt
Library
Accident Analysis and Prevention
Applied Cognitive Psychology
Applied Ergonomics
Behavioral and Brain Sciences
Cognition
Cognitive Psychology
Cognitive Science
Emotion
Ergonomics
Journal of Environmental Psychology
Journal of Experimental Psychology: Applied
Journal of Experimental Psychology: General
Journal of Experimental Psychology: Human
Perception and Performance
Journal of Experimental Psychology: Learning,
Memory and Cognition
Journal of Mind and Behavior
Journal of Occupational and Environmental
Hygiene
Medicine and Science in Sports and Exercise
Memory and Cognition
National Academies in Focus / National
Academy of Sciences
Physiology and Behavior
Psychological Bulletin
Psychological Science
Research Quarterly for Exercise and Sport
Journals Needed: Essential
Aviation Space & Environmental Medicine $ 215
Cognition and Emotion $1,
395
Human Computer Interaction $ 619
Human Factors $ 457
International Journal of Human-Computer
Interaction $ 940
Perception and Psychophysics $ 365
Total $3,
991
Journals Needed: Important
International Journal of Aviation Psychology $ 645
Mind, Culture and Activity $ 375
Theoretical Issues in Ergonomics Science $ 771
Total $1,
791
Other Needs: Essential
Online Search Database $7,
000
Total $7,
000
APPENDIX D Costs and
Revenue
Program Costs
One-time start-up costs:
Marketing and Recruiting $10,000
Library monographs $ 3,000
Total
one-time costs $13,000
Continuing costs:
Beginning Year 1 (2010-11)
New faculty (salary + fringes) $164,000
New journals $ 5,782
Library online search $ 7,000
Graduate assistantships (2) $ 40,000
Beginning Year 2
Graduate assistantship (1) $ 20,000
Beginning Year 3
New faculty (salary & fringes) $ 82,000
Total annual costs, as of
2012-13 $319,000
Program Revenue
Continuing revenue:
Beginning Year 1 (2010-11)
External research funding $ 75,000
By Year 5 (2014-15, with 8
CLS faculty) $300,000
Indirect cost return $168,000
Part-time instructional
costs assumed by GTAs $ 27,000
Total annual revenue, as
of 2014-15 $327,000
By year three, the investment in the new
program of about $300K annually (3 faculty lines and 3GTA-ships) will result in
an increase of external research funding by approximately the same amount. Enrollment
in the program will have increased by three PhD students per year. By year five (2014-15), the program is
projected to become revenue neutral, if not profitable. By year seven, the program will produce three
PhD graduates annually, while remaining profitable.
APPENDIX E Space Needs
Research Space Survey Summary
Office
Space Lab
per Faculty Rooms per
Member Faculty Lab Space per Faculty Dedicated Teaching Lab
Institution (Sq
Ft) Member Member (Sq Ft) (Sq Ft)
Univ. of Central Florida |
144-180 |
1-3 |
420-700
(unfunded); increase
to 1500-3500 for funded
projects |
2 labs,
each with 45 computers
(1972 sq ft total) |
Old
Dominion University |
168-180 |
1-2 |
500-600
(unfunded); increase
to 1500-2000 for funded projects |
Info Not
Available |
Clemson Univ. |
144-180 |
3-5 |
1000-2000
(regardless of funding) |
Info Not
Available |
Univ. of Cincinnati |
240-280 |
4-6 |
1000-2000
(regardless of funding) |
1 lrg
room 400 sq ft, plus 5-6
rooms 120 sq ft each (approx.
1000-1200 total) |
Univ. of West Florida |
144-180 |
1-3 |
400-600
(regardless of funding) |
1200 sq ft |
George Mason Univ. |
300 |
1-3 |
200-400;
plus shared lab spaces
(e.g., simulation rooms, neuroergo testing) |
500 sq
ft |
Virginia Tech |
144 |
1-3 |
300-400
(regardless of funding),
plus shared spaces |
300 sq
ft with 25 computers |
Georgia Tech |
360 |
3-6 |
1500-3000;
plus shared spaces
(regardless of funding) |
800 sq
ft with 30 computers |
Average
for Institutions
Surveyed: 226 Sq Ft 3 Rooms 1030 Sq Ft (unfunded); 717
Sq Ft
1928 Sq Ft (with funding)