HCI Graduate Program

1620 Howe Hall

Ames, IA 50010

515-294-2089

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Our Announcements

News

• Bernard named interim dean of Iowa State University College of Engineering
— ISU News Service: 07/23/2008

• Car manufacturing: Vehicle makers appreciate the virtues of virtual design
— Financial Times: 05/28/2008

• Top Schools, Top Programs: ISU Human Computer Interaction graduate program ranked #7 among top performing individual Information Science/Information Systems programs.
— Academic Analytics, LLC: 05/02/2008

• The Virtual Becomes Reality at Iowa State University
— Embedded Technology: 05/01/2008

Coursework in HCI

The following courses are the core (required) courses for the MS, PhD, and Graduate Certificate programs. Additional courses may be added at the direction of the Program of Studies Committee.

Required Courses

HCI 575X Computational Perception.
MIS 655 Organizational and Social Implications of Human Computer Interaction
Psych 521 The Cognitive Psychology of HCI.

In addition to the core courses, PhD students are required to take one or more research methods courses satisfy the Research Methods Requirement. The courses listed below courses satisfy the requirement:

Stat 401 Statistical Methods for Research Workers.
Psych 508 Research Methods in Applied Psychology.
Psych 522x Scientific Methods in Human Computer Interaction.
Psych 540 Psychological Measurement II.
Psych 586 Research Methods in Social Psychology.
Stat 430X Empirical Methods for Computer Science.

Electives

In selecting electives, students work with their Program of Study Committee. The following list of courses may be taken as electives for both the MS and PhD programs. The Program of Study Committee makes the final decision about whether a course can apply to a student's Program of Study.

General courses:

IMPORTANT: The list of courses on this page is NOT exhaustive. Many other courses may also apply to your course of study in HCI.

The accuracy of the information on this page cannot be guaranteed. Check the ISU catalog and with the offering department for full details on pre-requisites, availability, instructors and times.

Architecture

Arch 534. Advanced Computer-aided Architectural Design, 3 Cr.
*Can take more than once, for up to 6 Cr. total
Spring 2008 (offered alternate years)
Instructor: Chiu-Shui Chan

Prereq: Arch 434, permission of instructor.
Emphasis on concepts, algorithms, data structures and data base development, evaluation and development of software for complex data management, and applications in architectural design.

Instructors Notes
This class focuses on:

Introduction to virtual reality in arts and design.
Creating 3D stereoscopic images.
Creating geometric models through MAX for the Web display,
Testing methods to get the best realism in the model
View the model in virtual reality facilities.

ISU Catalog

Art: Graphic Design

ArtGr 570. Advanced Studies in Visual Communication, 3cr.
Fall 2007
Instructor: Alan Mickelson

Prereq: Graduate classification in College of Design.
Theory and investigation of systems, structures, principles of visual organization, and typography for communication. Studio problems will be influenced by social, cultural, environmental, or technological factors. (ISU Catalog)

ArtGr 574. Exhibition Design

Visual communication applied to exhibition design focusing on educational or interactive museum exhibitions, trade show booth design, and modular unit design for traveling exhibitions. Translation of graphic information to a three-dimensional space.

ArtGr 672. Graphic Design and Human Interaction, 3cr.
Fall 2007
Instructor: Debra Satterfield.

This class will focus on creating a series of human interaction design projects based on the principles of emotion, cognition, motivation, and design for behavioral change. The following learning objectives will be addressed via the studio projects:

Sensory Languages
The sensory systems of the body will be researched and analyzed. Students will be given the opportunity to study research from other fields such as perceptual psychology, occupational therapy, and neurology in order to understand and identify those concepts which affect human interaction, graphic design, and sensory communication.

Communication Via Multiple Sensory Channels
A method of evaluating and analyzing sensory experiences will be developed and utilized for creating user experiences. Students will synthesize information from various fields and formulate a process of utilizing this information in practical applications.

Micro and Macro Sensory Experiences
Communication experiences will be evaluated in terms of their use of fine and gross motor involvement for the user. Research in body movement, spatial orientation and tactile response will be used as a basis for developing a method of analyzing and evaluating the effectiveness of these experiences.

Multiple Learning Styles
Students will research various learning models in order to understand how people gain information.

The Role of Emotion in Human Interaction Design
Students will research ways of identifying and utilizing emotion in the design of user experiences.

Primary Motivating Factors in Human Behavior
Learn how behavioral principles work and why they need to be incorporated into many types of human computer interaction situations.

The Role of Human Interaction in Communication
Learn how human interaction influences human emotions and behaviors. Students will then research how design can be used as a catalyst or facilitation tool for human interaction. ISU Catalog

ArtGr 699. Research. Credit varies. (catalog)

Computer Engineering

ME/CprE 557. Computer Graphics and Geometric Modeling, 3cr.
Fall 2007
Delivered Online (EDE)
Instructor: Tsung-Pin Yeh

Prereq: M E 421, programming experience in C.
Fundamentals of computer graphics technology. Data structures. Parametric curve and surface modeling. Solid model representations. Applications in engineering design, analysis, and manufacturing. (ISU catalog)

Computer Science

Com S 309. Software Development Practices, 3cr.
Fall 2007
Instructor: Simanta Mitra

A practical introduction to methods for managing software development. Process models, requirements analysis, structured and object-oriented design, coding, testing, maintenance, cost and schedule estimation, metrics. Programming projects. Nonmajor graduate credit. (ISU Catalog)

Com S 401. Projects in Computing and Business Applications, 3cr.
Fall 2007
Instructor: Alex Stoytchev

Prereqs: Engl 250, Sp Cm 212, Com S 309, and Com S 362 or Com S 363
The theme for the class will be: designing an intelligent house. We will focus on hardware and software solutions that sense, detect, recognize, and react appropriately to the actions of humans inside their homes. The Computer Science department has a prototype intelligent room that we will use as a test platform. An ideal follow-up class for students who have taken HCI/CS 575X. (ISU Catalog)

Com S 572. Principles of Artificial Intelligence, 3cr.
Fall 2007
Instructors: Vasant Honavar, Jin Tian.
Course website

Prereq: ComS 311, 331, Stat 330, ComS 342 or comparable programming experience.
Specification, design, implementation, and selected applications of intelligent software agents and multi-agent systems. Algorithmic models of problem solving, knowledge representation, reasoning, planning, decision making, learning, perception, action, communication and interaction. Reactive, deliverative, rational, adaptive, learning and communicative agents. Artificial intelligence programming. Graduate credit requires a research project and a written report. Oral and written reports. (ISU Catalog)

Com S 573. Machine Learning, 3cr.
Spring 2007

Prereq: ComS 311, 362, Stat 33.
Algorithmic models of learning. Design, analysis, implementation and applications of learning algorithms. Learning of concepts, classification rules, functions, relations, grammars, probability distributions, value functions, models, skills, behaviors and programs. Agents that learn from observation, examples, instruction, induction, deduction, reinforcement and interaction. Computational learning theory. Data mining and knowledge discovery using artificial neural networks, support vector machines, decision trees, Bayesian networks, association rules, dimensionality reduction, feature selection and visualization. Learning from heterogeneous, distributed, dynamic data and knowledge sources. Learning in multi-agent systems. Selected applications in automated knowledge acquisition, pattern recognition, program synthesis, bioinformatics and Internet-based information systems. Oral and written reports. (ISU Catalog)

Com S 574. Intelligent Multiagent Systems, 3cr.

Prereq: Stat 330, ComS 331, ComS 572 or ComS 573 or ComS 472 or ComS 474
Specification, design, implementation, and applications of multi-agent systems. Intelligent agent architectures; infrastructures, languages and tools for design and implementation of distributed multi-agent systems; Multi-agent organizations, communication, interaction, cooperation, team formation, negotiation, competition, and learning. Selected topics in decision theory, game theory, contract theory, bargaining theory, auction theory, and organizational theory. Agent based distributed computing. Agent-oriented software engineering. Applications in distributed intelligent information networks for information retrieval, information integration, inference, and discovery from heterogeneous, autonomous, distributed, dynamic information sources.

The course aims to provide a rigorous yet accessible introduction to intelligent multiagent systems. Course projects will provide experience with designing, implementing intelligent multi-agent systems and their application to data mining, information integration, mobile, agile, distributed intelligent information networks. (ISU Catalog)

Com S 575x. Computational Perception, 3cr.
Cross-listed with HCI 575X.
Spring 2008
Instructor: Alex Stoytchev
* Overview: Spring 2007
* Overview: Spring 2006

Prereq: See Syllabus, p.2.
This class covers statistical and algorithmic methods for sensing, recognizing, and interpreting the activities of people by a computer. This semester we will focus on machine perception techniques that facilitate and augment human-computer interaction. The main goal of the class is to introduce computational perception on both theoretical and practical levels. You will work in small groups to design, implement, and evaluate a prototype of a human-computer interaction system that uses one or more of the techniques covered in the lectures.

At the end of this class you will have an understanding of the current state of the art in computational perception and will be able to conduct original research. In addition to that, you will have the skills to design novel human-machine interfaces that push the limits of current interfaces which, in general, are deaf and blind to the human user.

This course requires programming knowledge of C/C++. It also uses Matlab, and the instructor gives tutorials on Matlab during the course.

Com S 577. Problem Solving Techniques for Applied Computer Science, 3cr.
Fall 2007
Instructor:

Prereq: Com S 228, either 330 or Cpr E 310, Math 166, either Math 307 or Math 317, or consent of the instructor.
Selected topics in applied mathematics and modern heuristics that have found applications in areas such as geometric modeling, graphics, robotics, vision, human machine interface, speech recognition, computer animation, etc. Polynomial interpolation, roots of polynomials, resultants, solution of linear and nonlinear equations, approximation, data fitting, fast Fourier transform, linear programming, nonlinear optimization, Lagrange multipliers, genetic algorithms, integration of ODEs, curves, curvature, Frenet Formulas, cubic splines, and Bezier curves. Programming components. (ISU Catalog

Com S 610 AS (seminar). Developmental Robotics, 3cr.
Fall 2006
Instructor: Alex Stoytchev.
Class web page

The class will focus on representations and algorithms for robot learning that facilitate and/or benefit from a developmental period. At the end of this class you will have an understanding of the current state of the art in developmental robotics and will be able to conduct original research. In addition to that, you may also gain a deeper understanding of the development of human intelligence.

Curriculum and Instruction

C I 503. Theories of Designing Effective Learning and Teaching Environments, 3cr.
Summer 2008
More information
Delivered Live and Online
Instructor: Dr. Ana-Paula Correia

Prereq: C I 501, convenient access to the Web.
In this class, students will work in small groups to solve instructional problems. They will engage in the design, development, implementation and evaluation of instruction. Students will also have the opportunity to engage in community service learning if they want to work in such a project. This will be a great opportunity to not only learn instructional design, but also to develop a high quality product to include in a professional portfolio. (ISU Catalog)

C I 504. Managing and Evaluating Instructional Technology Programs, 3cr.
Spring 2008
More Information
Instructor: Dr. Ana-Paula Correia

This is a graduate course on how to plan, design, and conduct effective evaluation studies (formative, summative, usability). Students will have the opportunity to engage in real or simulated evaluation projects of substantial scope. Students will design the instruments and methods with which to evaluate a product (e.g. usability testing) or program (e.g. formative evaluation), conduct try-outs or usability sessions, analyze the data, report the findings and write-up the recommendations. (ISU Catalog)

C I 507. Principles and Practices of Flexible and Distance Learning, 3cr.
Fall 2007
Delivered Live and Online
Instructor: Dr. Niki Davis

Prereq: C I 501, convenient access to the Web.
Review of flexible and distance learning (FDL) cases in a variety of contexts and pedagogic styles, research into relevant topics. Identification of underlying principles and frameworks for best practice in this field. Offered in FDL modes, utilizing telecommunications and the Internet.

The classroom experience is blended with online experiences in WebCT and Moodle. Although you will not be attending campus each week, it is important to set aside time for this challenging and rewarding class. All students will facilitate, teach, and create part of an online course and be able to add to their portfolio of accomplishments. In addition, considerable support is provided to students who wish to focus on flexible and distance learning in their work and/or research. (ISU Catalog)

C I 511. Technology Diffusion, Leadership and Change, 3cr.
Spring 2007, M 5:10-8pm
Instructor: Dr. Niki Davis

This course is designed to examine strategic change in education and aspects of technology diffusion in education. In this course, students will discover principles and approaches that prompt complex changes affecting society and education today and explore their roles in leadership and change. Perspectives covered include that of the individual, the organization and educational systems. This on campus offering will have a complementary WebCT learning environment. Students will lead seminars, conduct field observation and engage in project work to prompt and understand change within their own contexts. This course aims to help each student gain experience as a change agent using technology reflectively and responsibly to support educational change. It is suitable for both masters and doctoral students’ programs.

Course text: Rogers, E.M. (2003). Diffusion of innovations. (5th ed.). New York, NY: The Free Press, will be complemented with a list of online reading in WebCT, and ISU e-Library. (ISU Catalog)

C I 512. Research Trends in Technology & Education, 3cr.
Spring 2008, Mon 5:10-8pm
Location: CTLT Labs N047, Lagomarcino
Instructor: Dr. Niki Davis

CI 512 will be taught by Dr Niki Davis in spring 2008 on Monday evenings 5.10 – 8 pm in CTLT Labs N047 Lagomarcino Hall, starting Monday January 14. In addition to learning about the trends of research into curriculum and instructional technology in the U.S. and around the world, this course will support each student to craft a literature review, preferably on the topic of their thesis or dissertation. These papers have often turned into early drafts for proposals and occasionally published papers.

In addition, the course will start with collaboration to create a literature review for submission to a scholarly journal, such as the Review of Educational Research. That exemplary literature review process will be led by Dr Davis, probably on the topic of technology and teacher education, which is a major focus of the Center for Technology in Learning and Teaching directed by Dr Davis. Students may earn a place as an author in this literature review. This mainly on campus course will have a blended online component in Moodle to support student learning and collaboration.

Although this is the capstone course for Curriculum & Instructional Technology (CIT) MS and PhD programs in Education, it is also relevant and open to students in other programs when they are nearing thesis or dissertation with a curriculum aspect, including Human Computer Interaction (HCI), Computer Assisted Language Learning (CALL), and Agricultural Education. Please note that this course is ONLY taught every other year. (ISU Catalog)

C I 593-B. Instructional Design Workshop, 2cr.
Spring 2007, T 5:10-7pm [ More Information ]
Instructor: Dr. Mi Ok Cho

In this course, students will gain knowledge of self-managed learning and instructional design based on adult learning theory. With this knowledge, students will develop instructional design skills that are mostly used in higher education and corporate HRD (Human Resource Development). Students also will design on line learning academy based on adult learning philosophy.

Topics include:

Understanding the concept of self-managed learning
Discuss adult learning theory and compare/contrast self-directed learning with self-managed learning
Use an andragogy (adult learning theory) based learning design process with the concept of self-managed learning
Hands-on experience with developing learning resources and tasks
Collect information / human resources to develop self-managed learning kits
Design on line learning academy for future use for training with the concept of self-managed learning
Design student activities and a manual for self-managed learning or (ISU Catalog)

C I 603. Advanced Instructional Systems Design, 3cr.
Spring 2008
Course Web Page
Class Flyer
Instructor: Dr. Ana-Paula Correia

This course focuses on the design and use of instructional technology for learning and teaching. This class requires application of principles of analysis, design, development & production, evaluation, implementation, and project management. This will be a great opportunity to develop a high quality product to include in a professional portfolio, and serve the community at the same time.

Students will work in small groups to solve real instructional problems with real-world clients (e.g. local organizations & businesses). Potential clients are: City of Ames, Story County Emergency Management, Phasient Learning Technologies, Thomas B. Thielen Student Health Ctr., Mid-Iowa Community Action, Inc., Edwards Elementary School, Beyond Welfare, Inc., ISU College for Seniors, and ISU Extension to Families. Lecture and hands-on activities on entrepreneurship by inviting guest speakers to the class with strong business and/or entrepreneurship backgrounds will also be offered. (ISU Catalog)

Economics

Econ 308. Agent-based Computational Economics (ACE), 3cr.
Spring 2007
Instructor: Leigh Tesfatsion.

A modern market-based economy is an example of a complex adaptive system, consisting of a decentralized collection of autonomous adaptive agents interacting over time in various market contexts. These massively parallel local interactions give rise to global regularities such as trade networks, socially accepted monies, market protocols, business cycles, and the common adoption of technological innovations. These global regularities feed back in turn into the determination of local interactions.

The recent advent of powerful computational tools, particularly object-oriented programming, permits new approaches to the study of this complex two-way feedback between microstructure and macrostructure. The primary objective of this course is to introduce, motivate, and explore through concrete applications the potential usefulness of one such approach -- agent-based computational economics (ACE) -- the computational study of economies modeled as evolving systems of autonomous interacting agents. (ISU Catalog)

Electrical Engineering

EE 528. Digital Image Processing, 3cr.
Spring 2007
Delivered Live and Online (EDE)
Instructor: Namrata Vaswani

Image representation, sampling, and formats. Edge models, histograms, intensity enhancement, and image statistics. Image transforms and multi-resolution signal processing. Image restoration. Compression and coding techniques. Mathematical morphology. Object recognition and computer vision concepts. Current applications. (ISU Catalog)

English

Stat/Engl 332X. Visual Communication of Quantitative Information, 3cr.
Spring 2007, MWF 11:00-11:50am
Instructor: Heike Hofmann, Dianne Cook, Charlie Kostelnick
Course web page

Prereq: Statistics 101, 104, or 226; English 104 and 105
Communicating quantitative information using visual displays: visualizing data, interactive and dynamic data displays, evaluating current examples in the media, color/perception/representation in graphs, interpreting data displays. (ISU Catalog)

ENGL 520. Computational Analysis of English, 3cr.
Not offered Spring 2007
Delivered Live and Online(EDE)
Instructor: Nick Pendar

This course is an introduction to computational linguistics and natural language processing with emphasis on symbolic approaches to language. Throughout the course, students will familiarize themselves with the field of computational linguistics in general and learn some of the basic ideas and techniques used to enable computers to “understand” language and/or use it intelligently otherwise. Students will also build simple natural language processing systems using Python programming language. They will also discuss their completed projects in the class periodically. Evaluation is based on a final take-home examination and the course projects/presentations. No background in Python programming is assumed.

Required Text:

Jurafsky, D. and J. H. Martin (2000). Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics and Speech Recognition. Upper Saddle River, N.J.: Prentice Hall.

Extra Reading:

Downey, A., J. Elkner and C. Meyer (2002) How to Think Like a Computer Scientist: Learning with Python. Wellesley, MA: Green Tea Press.
Available online at http://www.greenteapress.com/thinkpython/
Bird, S., J. Curran, E. Klein and E. Loper (2006) NLTK-Lite Tutorial.
Available online at http://nltk.sourceforge.net/lite/doc/en/.

ISU Catalog

LING/ENGL/HCI 515X. Statistical Natural Language Processing
Cross-listings: LING 515x, HCI 515x
Offered Fall 2007
Instructor: Nick Pendar
Course web page

Prerequisites:: ComS 207, Stat 330 or equivalent. Recommended LING 219 or LING 511.
Download detailed course description [.pdf]. Automatic processing of natural languages has always been a great challenge for researchers in linguistics, computer science, and artificial intelligence. Since its inception, computer science has been preoccupied with natural language, and has sought input from a variety of disciplines, such as linguistics, logic, philosophy, mathematics, and statistics. This course introduces students to one of the most successful approaches to natural language processing (NLP). Statistical NLP is a rapidly growing field with many realworld applications and has become an integral part of computational linguistics. The course introduces students to the fundamental ideas and problems in the field.

The students will understand the fundamental theoretical infrastructure of natural language processing and the contributions of its underlying fields: computer science, linguistics, machine learning and statistics. They will also learn about the existing, emerging and possible real-world computer applications involving natural language interfaces. Some of topics covered in this course include: Text & Corpora, Automatic Text Categorization, Maximum likelihood models of language, N-gram models and statistical smoothing, Word Prediction, Hidden Markov Models for NLP, Part-of-Speech Tagging, Word-Sense Disambiguation, Document & Text Retrieval, Automatic Text Summarization.

Geology

Geol 552. Geographic Information Systems (GIS) for Geoscientists I, 3cr.
Fall 2007
Instructor: Chris Harding

Geographic information systems (GIS) are a rapidly growing area of computer application that will benefit many graduate students in Geology, Water Resources, Environmental Science, Soil Science and related earth and life sciences. GIS for Geoscientists I is an introduction to GIS operations and analyses of geospatial data and will prepare students for more advanced GIS courses. We will use ESRI&39;s ArcGIS 9.x Desktop Software on PCs in the Durham GIS lab. This hands-on course will be taught at a senior undergraduate (400) level, students taking the course at the graduate (500) level will also work on additional exercises and projects. (ISU Catalog)

This course is one of the foundation courses for the GIS certificate administered by the department of Community and Regional Planning (CRP). More information about this certificate can be found at www.design.iastate.edu/CRP/giscertificateprogram.php

Human Computer Interaction

LING/ENGL/HCI 515X. Statistical Natural Language Processing
Cross-listings: LING 515x, ENGL 515x
Offered Fall 2007
Instructor: Nick Pendar
Course web page

Psych/HCI 521. Cognitive Psychology of HCI, 3cr.
Offered Fall 2007
Delivered Live and Online (EDE)
Instructor: Stephen Gilbert

Prereq: Graduate classification or instructor approval.
Sensation, perception, memory, decision making, the biological basis of behavior, models of cognitive thought processes, and design strategies for human computer interfaces. (ISU catalog)

ME/HCI 525x. Mechanical System Optimization, 3 cr.
Offered Spring 2007
Delivered Live and Online (EDE)
Instructor: Eliot Winer

Prereq: ME 415, Engr 160.
Please see ME 525x for more information.

HCI 558x. Introduction to the 3D visualization of scientific data, 3cr.
Cross-listings: GEOL 558x, COM S 558x
Spring 2007
Instructor: Chris Harding

(Spring 2006 class page)

3D visualization is now used in many scientific and engineering disciplines to investigate and comprehend large amounts of complex multi-dimensional data. This course will introduce the major concepts used in visualizing scientific information with 3D computer graphics, will show how visualization techniques relate to concepts in human visual perception and will teach with a mixture of lecture and practical, hands-on examples of 3D visualization.

Course Objectives include: Basic understanding of the major principles and workflows of 3D scientific visualization and how they relate to human visual perception; Application of this understanding to analyze, comprehend and criticize existing 3D visualizations; Practical experience in creating small interactive scientific 3D visualizations with a data set from the student’s scientific domain using either the higher level visualization software open DX or a programming API such as VTK. (ISU Catalog)

HCI 575x. Computational Perception, 3cr.
Cross-listings: COM S 575x
Spring 2007
Instructor: Alex Stoytchev
* Overview: Spring 2007
* Overview: Spring 2006

This course requires programming knowledge of C/C++. It also uses Matlab, and the instructor gives tutorials on Matlab during the course.

HCI/ME 580x. Virtual Worlds and Applications, 3cr.
Fall 2007
Delivered Online (EDE)
Course page (hosted at odu.edu)
Instructor: Mark Bryden/Doug McCorkle

Prereq: Senior or Graduate status.
A systematic introduction to the underpinnings of Virtual Environments (VE), Virtual Worlds, advanced displays and immersive technologies; and an overview of some of the applications areas particularly virtual engineering.

This course begins by introducing the topic historically. An examination of human perception related to VEs follows. After describing the essential characteristics of VEs, the course will systematically cover the hardware needed to produce a useful VE. Special attention is given to interactions with the VE since this forms the basis for most successful VE applications. The software needed to create VEs is then discussed. After dealing with a number of applications the course concludes by describing advanced displays and immersive technologies. (ISU catalog - see HCI 580x)

HCI 591. Seminar in Human Computer Interaction, 1cr.
Offered each Fall and Spring semester
Instructor: James Oliver

A weekly seminar open to all faculty and students in HCI related disciplines. Each week we will read and discuss one or more articles on the latest research in Human Computer Interaction from a multi-disciplinary perspective.

HCI 592X. Entrepreneurship Workshop, 1cr.
Instructor: James Oliver

Students will be taken step-by-step through activities that must be undertaken when attempting to commercialize a technology or start their own company. Speakers will be brought in to introduce relevant topics, provide resources, answer questions, and provide working examples.

Students will be able to recognize opportunities for entrepreneurial activities and then know the steps that they need to take when attempting to commercialize a technology or start their own company. Topics discussed will include:
1. Developing a Business Plan: Marketing; Patents/Intellectual Property; Costing; Promotion
2. Generating Capital: Proposals (SBIR, STTTR, Federal, State, Local sources); "Bootstrapping" your business
3. Setting up Shop: Labor; Management; Salaries & Benefits; Globalization; Outsourcing

HCI 697. HCI Internship
*Can take more than once, for up to 6 Cr. total
Offered each Fall, Spring and Summer semester
Instructor: Varies

Internship experience in an HCI related field. One semester and one summer maximum per academic year.

Industrial Engineering

IE 699. Research. Credit varies.
ISU catalog

Journalism & Communication, Greenlee School of

JLMC 574/T SC 574. Communication Technologies and Social Change, 3cr.
Cross-listings: T SC 574
Fall 2007
Instructor: Daniela Dimitrova
T 2:10 - 3:25p in Rm 5 Hamilton Hall
R 2:10 - 3:25p in Rm 5 Hamilton Hall

New communication technologies are affecting traditional media both in the United States and abroad. New media forms, new distribution channels and new delivery systems are emerging. The course will focus on several key aspects of the Internet and other new media technologies through the lens of diffusion of innovations theory. We will discuss new media trends, regulatory and digital divide issues, impacts of new technologies on the telecommunications industry and the broader society. A premise in this course is that technology is partly a cause of and partly a response to larger social changes. We will discuss such changes at the individual, organizational and societal level. (ISU Catalog)

JLMC 598A/HCI 598. Audiences and Effects
Fall 2006
ISU catalog

JLMC 598P/HCI 598. Communication Technology – Philosophy and Ethics
Spring 2007
Instructor: Chad Harms

Linguistics

LING/ENGL/HCI 515X. Statistical Natural Language Processing
Cross-listings: ENGL 515X, HCI 515X
Offered Fall 2007
Instructor: Nick Pendar
Course web page

Mechanical Engineering

ME 484/584 (also WLC 484/584). Technology, Globalization & Culture.
Offered Fall 2008
Instructors: Jim Bernard (ME) and Mark Rectanus (WLC)
Delivered Live and Online (EDE)
(ME Web Listing)

Prereq: Senior Classification for 484; Grad Classification and permission of instructor for 584.
Download detailed course description [.pdf]. This course will provide a cross-disciplinary examination of the present and future impact of globalization with a focus on preparing students for leadership roles in diverse professional, social, and cultural contexts. We will examine the threats and opportunities inherent in the globalization process as they are perceived by practicing professionals and articulated in debates on globalization. Students will be expected to contribute critical analyses and debate through threaded discussions and will work collaboratively on final projects. Non-major graduate credit.

ME/HCI 525x. Mechanical System Optimization, 3 cr.
Offered Spring 2007
Delivered Live and Online (EDE)
Instructor: Eliot Winer

Prereq: ME 415, Engr 160.
Optimization involves finding the 'best' according to specified criteria. In Engineering Design, this might typically be minimum cost or weight, maximum quality or efficiency, or some other performance index pertaining to a disciplinary objective. Realistic optimal design involves not only an objective function to be minimized or maximized, but also constraints, which represent limitations on the design space. Numerical programming requires the mathematical representation of the design space (objective function and constraints) in terms of 'design variables' (parameters that signify some potential for change). Generally, the problems of interest in engineering are of a nonlinear nature, in that the dependence of the objective function and constraints on the design variables is nonlinear.

This course looks at a range of optimization methods from traditional nonlinear ones to modern evolutionary methods such as Genetic algorithms. The course will explore how these methods can be used to solve a wide variety of design problems across disciplines, including mechanical systems design, biomedical device design, biomedical imaging, and interaction with digital medical data. By the end of the semester, the student will have gained a basic knowledge of numerical optimization algorithms and will have sufficient understanding of the strengths and weaknesses of these algorithms to apply them appropriately in engineering design. Students will write code as well as use off-the-shelf routines to gain this experience. Students will also be exposed to numerous case-studies of real-world situations in which problems were modeled and solved using advanced optimization techniques.

Application Areas: Design optimization is key to the development and implementation of current design methods such as Multidisciplinary Design Optimization and Concurrent Engineering being used in top companies. The next generation of products and processes are using these design methods and it is critical that new engineers understand these concepts. These methods enable complex systems designs, whether in traditional mechanical engineering or other fields such as those with biological implications, to be performed within not only physical constraints (i.e. stress, deformation) but other impact areas as well (e.g., cost and time). (Syllabus)

IE/ME/CprE 557. Computer Graphics and Geometric Modeling, 3cr.
Fall 2006
Delivered Online (EDE)
Instructor: Tsung-Pin Yeh

HCI/ME 580x. Virtual Worlds and Applications, 3cr.
Fall 2007
Delivered Online (EDE)
Course page (hosted at odu.edu)
Instructor: Mark Bryden/Doug McCorkle

Management Information Systems

MIS 437x. Project Management, 3cr.
Spring 2007
Delivered Online (EDE)
Instructor: Gary Hackbarth

Designed for the project team environment, this course will equip students to support team activities in the general project management environment and better manage their careers. Students will gain practical experience using project management techniques, including the use of software tools such as MS Project, MS Excel, and SIMPROJECT. Course topics include project initiation, risk assessment, estimating and contracts, planning, human factors, project execution, and standard methods. Case studies, personal experience and real-world projects will be used to demonstrate tools and techniques. Nonmajor graduate credit. (ISU Catalog)

MIS 533. Data Management for Decision Makers, 3cr.
Offered Spring 2007
Delivered Live and Online (EDE)
Instructor: Brian Mennecke

Prereq: 503.
Databases are mission critical resources because these systems power the information technologies that are used to run modern organizations. The course will address the data needs of organizations in functional areas such as marketing, finance, production, engineering, systems design, etc. The course will focus on skills, knowledge, and technologies focused on database development, management, and use. The course will also cover emerging topics and applications such as e-commerce databases, XML, data warehousing, data mining, and decisions support systems. The role of contemporary technologies and procedures will be stressed. (ISU Catalog)

MIS 534. Electronic Commerce, 3cr.
Offered Summer 2007
Delivered Live and Online (EDE)
Instructor: Brian Mennecke

Prereq: 503.
Overview of how modern communication technologies including the internet and world wide web have revolutionized the way we do business. It will provide an understanding of various internet technologies and how companies are using the internet for commercial purposes. The course will also explore future scenarios on the use of these technologies and their impact on various industries and the society. (ISU Catalog)

MIS 537. Information Resource Management, 3cr.
Offered Spring 2007
Delivered Live and Online (EDE)
Instructor: Tony Townsend

Prereq: 503.
(IRM) is a popular concept of viewing information systems resources from a strategic resource perspective. This course will present and discuss the IRM concept as well as provide pragmatic tools for implementing this approach within the organization. Topics will include: IS outsourcing, total cost of ownership, IS planning and strategic analysis, justifi cation for IT investment, management of IT human resources, traditional project management theory, and project management techniques derived from the Theory of Constraints (TOC). (ISU Catalog)

MIS 655. Organizational and Social Implications of Human Computer Interaction, 3cr.
Fall 2007
Delivered Online (EDE)
Instructor: Anthony Townsend

Prereq: Graduate Classification
Examine opportunities and implications of information technologies and human computer interaction on social and organizational systems. Explore ethical and social issues appurtenant to human computer interaction, both from a proscriptive and prescriptive perspective. Develop informed perspective on human computer interaction. Implications on research and development programs. (ISU Catalog)

Psychology

Psych 508. Research Methods in Applied Psychology, 3cr.
Spring 2007

Prereq: Psych 440, Stat 401
Methods and issues in applied psychological research. Role of theory in research, fidelity of measurement, selection of subjects, sampling, ethical issues, experimenter bias, data collection methods, power analysis, meta-analysis, and professional standards for writing research articles. Emphasis on research methodological issues, not statistical issues. (ISU catalog)

Psych/HCI 521. Cognitive Psychology of HCI, 3cr.
Fall 2007
Delivered Live and Online (EDE)
Instructor: Stephen Gilbert

Psych 522X. The Scientific Methods of HCI, 3cr.
Spring 2007
Instructor:Derrick Parkhurst

Prereq: Psych 521.
This course will be a three hour per week graduate level seminar offered bi-annually and is intended to complement the pre-requisite course Psych 521. Psych 522X will satisfy the research methods course requirement for PhDs.
Students seeking a terminal Masters degree in HCI are encouraged to take this course as an elective. The course will be an advanced treatment of the following topics:

Philosophy of Science Experimental Design Experimental Ethics
Observational Methods Correlational Methods Experimental Design and Control
Descriptive Statistics Inferential Statistics Literature Review Techniques
Hypothesis Testing Scientific Writing Presenting Research Results

The treatment of these topics will be focused on HCI related research and examples. Grades will be based upon an experimental design project, a statistical analysis project, an oral presentation and a final project. The final project in the course will require the design, execution, analysis, and write-up of the results of an HCI related behavioral experiment.

Psych 550. Advanced Industrial and Organizational Psychology, 3cr.

Prereq: Psych 440, Stat 402.
Critical examination of theories, methods, and applications in industrial and organizational psychology. History and legal issues, predictor and criteria relationships, employee attitudes and behaviors, employee training and motivation, and human factors. ISU catalog)

Psych 580. Advanced Social Psychology: Psychological Perspectives, 3cr.
Fall 2007

Prereq: 4 courses in psychology, including 280.
Current theories, methods, and research in social psychology with an emphasis on cognitive and interpersonal processes such as attribution, social cognition, attitude change, attraction, aggression, and social comparison. (ISU Catalog)

Psych 581. Applications of Social Psychology Theories, 3cr.
Spring 2007

Prereq: 12 credits in psychology, including 280.
Application of social psychological theory to various applied topics, including physical and mental health, stress, and coping. (ISU catalog)

Psych 586. Research Methods in Social Psychology, 3cr.
Spring 2007

Prereq: Stat 402 and permission of instructor.
Ethical issues, generating testable hypotheses, operationalizing independent and dependent variables, sampling and design issues, laboratory procedures, and interpretation of results in experimental research. Issues in analysis of variance, Bayesian reasoning, and effect size estimation will be emphasized, as will writing and publication strategies. (ISU catalog)

Psych 699. Research

Offered on a satisfactory-fail grading basis only.

Sociology

Soc 515. Sociology of Technology, 3cr.
Fall 2007
Offered Online through (CDE)
Instructor: Stephen Sapp
Textbook: Rogers, Everett. Diffusion of Innovations. 5th ed. Free Press.

(Off-campus and nonmajors only. Offered as demand warrants.)
Prereq: 3-6 hours of social science.
Linkages among science, technology, and society. Physical, life, and social science approaches to technology evaluation. Public responses to complex and controversial technologies. Strategies for gaining adoption/rejection of technology. Required in the Master of Agriculture program. (ISU Catalog)

Statistics

Stat/Engl 332X. Visual Communication of Quantitative Information, 3cr.
Spring 2007, MWF 11:00-11:50am
Instructor: Heike Hofmann, Dianne Cook, Charlie Kostelnick
Course web page

Stat 401. Statistical Methods for Research Workers, 4cr.
Fall 2007

Prereq: Stat 101 or 104 or 105 or 226
Graduate students without an equivalent course should contact the department. Methods of analyzing and interpreting experimental and survey data. Statistical concepts and models; estimation; hypothesis tests with continuous and discrete data; simple and multiple linear regression and correlation; introduction to analysis of variance. Nonmajor graduate credit. (ISU Catalog)

Stat 430x. Empirical Methods for Computer Science, 3cr.
Spring 2007

Prereq: Stat 330 or an equivalent course.
Students will be introduced to the statistical concepts and methodologies that can be used for studying performance of complex computer programs and systems: fundamentals of experimental design, estimation and hypothesis testing procedures, exploratory tools to find patterns in data and modeling tools to help distinguish systematic patterns from random variation and make predictions.

Students entering this course should be familiar with elementary matrix algebra and some basic probability theory and statistical concepts covered in Stat 330 (or a similar course) sampling variation and bias, uniform, normal, and binomial distributions, bar charts, estimation of means, proportions and standard deviations, simple regression analysis. These topics will be briefly reviewed in the beginning of the course, but it is recommended that the students have seen most or all of the topics listed above.

This course will cover as many topics as possible from the following list of topics: basic concepts in experimental design and associated analysis of variance, hypothesis testing (including chi squared test, t tests, confidence intervals) and estimation of parameters, simulation techniques, bootstrap methods, prediction models (including diagnostics and sensitivity analysis), logistic and Poisson regression and basics of exploratory data analysis. These techniques will be applied to situations that are relevant for computer science or computer engineering researchers. Laboratory assignments will require students to familiarize themselves with and use R (a popular statistical software package). In addition to the usual exams, problem sets, and laboratory assignments, students may be required to do a small project applying one or some of the techniques discussed in this course to their own area of research (or to any other area of interest to the student). (ISU Catalog)

Technology & Social Change

JLMC 574/T SC 574. Communication Technologies and Social Change, 3cr.
Cross-listings: JLMC 574
Fall 2007
Instructor: Daniela Dimitrova
T 2:10 - 3:25p in Rm 5 Hamilton Hall
R 2:10 - 3:25p in Rm 5 Hamilton Hall

World Languages & Cultures

WLC 484/584 (also ME 484/584). Technology, Globalization & Culture.
Offered Fall 2008
Instructors: James Bernard (ME) and Mark Rectanus (WLC)
Delivered Live and Online (EDE)
(ME Web Listing)