Muutke küpsiste eelistusi

E-raamat: Research Methods in Human-Computer Interaction

(Professor, Computer and Information Sciences, Towson University, and Shutzer Fellow, Radcliffe Institute for Advanced Study, Harvard University), , (Professor, Computer and Information Sciences Department, Towson University, Maryland)
  • Formaat: EPUB+DRM
  • Ilmumisaeg: 28-Apr-2017
  • Kirjastus: Morgan Kaufmann Publishers In
  • Keel: eng
  • ISBN-13: 9780128093436
  • Formaat - EPUB+DRM
  • Hind: 75,06 €*
  • * hind on lõplik, st. muud allahindlused enam ei rakendu
  • Lisa ostukorvi
  • Lisa soovinimekirja
  • See e-raamat on mõeldud ainult isiklikuks kasutamiseks. E-raamatuid ei saa tagastada.
  • Formaat: EPUB+DRM
  • Ilmumisaeg: 28-Apr-2017
  • Kirjastus: Morgan Kaufmann Publishers In
  • Keel: eng
  • ISBN-13: 9780128093436

DRM piirangud

  • Kopeerimine (copy/paste):

    ei ole lubatud

  • Printimine:

    ei ole lubatud

  • Kasutamine:

    Digitaalõiguste kaitse (DRM)
    Kirjastus on väljastanud selle e-raamatu krüpteeritud kujul, mis tähendab, et selle lugemiseks peate installeerima spetsiaalse tarkvara. Samuti peate looma endale  Adobe ID Rohkem infot siin. E-raamatut saab lugeda 1 kasutaja ning alla laadida kuni 6'de seadmesse (kõik autoriseeritud sama Adobe ID-ga).

    Vajalik tarkvara
    Mobiilsetes seadmetes (telefon või tahvelarvuti) lugemiseks peate installeerima selle tasuta rakenduse: PocketBook Reader (iOS / Android)

    PC või Mac seadmes lugemiseks peate installima Adobe Digital Editionsi (Seeon tasuta rakendus spetsiaalselt e-raamatute lugemiseks. Seda ei tohi segamini ajada Adober Reader'iga, mis tõenäoliselt on juba teie arvutisse installeeritud )

    Seda e-raamatut ei saa lugeda Amazon Kindle's. 

Research Methods in Human-Computer Interaction is a comprehensive guide to performing research and is essential reading for both quantitative and qualitative methods. Since the first edition was published in 2009, the book has been adopted for use at leading universities around the world, including Harvard University, Carnegie-Mellon University, and the University of Washington. Chapters cover a broad range of topics relevant to the collection and analysis of HCI data, going beyond experimental design and surveys, to cover ethnography, time diaries, physiological measurements, case studies, and other essential elements in the well-informed HCI researcher's toolkit. Continual technological evolution has led to an explosion of new techniques and a need for this updated 2nd edition, to reflect the most recent research in the field and newer trends in methodology.

This revision contains updates throughout, including more detail on statistical tests, coding qualitative data, and data collection via mobile devices and sensors. Other new material covers research with children, older adults, and people with cognitive impairments.

  • Comprehensive and updated guide to the latest research trends and tools
  • New to this edition: o Expanded discussion of research involving online datasets and crowdsourcing o Techniques for expanding the influence of your research to reach developers, policymakers, and educators o Advice for involving participants with cognitive impairments o Discussions of regulations and laws around the world relating to the use of human participants in research

Arvustused

"This book is an outstanding contribution to HCIs pedagogical and reference literature, reviewing and explaining the numerous research methods in common use. It motivates with numerous examples the methods in terms of posing questions and designing research to answer those questions. It covers well both quantitative and qualitative methods. The treatment is accessible and lively. The book should be considered for adoption by all HCI instructors." --Ron Baecker, Member of the CHI Academy, Founder and Co-Director, Technologies for Aging Gracefully lab (TAGlab), and Emeritus Professor of Computer Science, University of Toronto

"This is the research methods book I recommend to my students and colleagues. And it's a time-saver: my students make fewer methodological mistakes and we can now engage in deeper and more insightful discussions about specific challenges of their research work. With this improved and updated edition, the bar is even higher! With increasing traces of our lives online and availability of Big Data in many research projects, the new chapter on online and ubiquitous HCI research was a welcome addition to the already comprehensive, multi-method research book. Every HCI student, researcher, and practitioner must read it!" --Simone Barbosa, Professor, PUC-Rio, Brazil, and co-Editor-in-Chief of ACM Interactions

"Research Methods in HCI is an excellent resource for newcomers and seasoned HCI professionals alike. Covering all the basic methods for conducting research in HCI, concepts are explained clearly and brought alive through case studies and examples. In addition to offering how-to details, the text offers detailed rationale for why and when to use different methods. Some historical context and controversial viewpoints are also offered. Clear discussions around how to select participants and work with different populations are offered, as are ethical issues in conducting research. The attention to these kinds of details makes this a truly engaging, readable text. The extensive list of references offers plenty of scope for follow-up for those wishing to deepen their knowledge even further. The 2nd edition offers new and refreshed content, updated examples and case studies, and new references and resources." --Elizabeth Churchill, Member of the CHI Academy, Secretary/Treasurer of ACM, currently Director of User Experience at Google, formerly Director of Human Computer Interaction at eBay

"This book by Lazar, Feng, and Hochheiser is a must read for anyone in the field of Human-Computer Interaction. Their multi-discipline approach, housed in the reality of the technological world today, makes for a practical and informative guide for user interface designers, software and hardware engineers and anyone doing user research" --Mary Czerwinski, Principal Research Manager, Microsoft Research, Recipient of the ACM SIGCHI Lifetime Service Award, Member of the CHI Academy, and ACM Fellow

"This is a superb book for all researchers, practitioners, and students interested in the investigation of anything related to HCI. This new edition has much needed information on research methods in HCI that have become prevalent, including crowdsourcing as well as new creative ways to collect and analyze qualitative data, two examples of essential skills for today's HCI students! Highly recommended!" --Vanessa Evers, Full Professor and Chair of Human Media Interaction, Scientific Director of the DesignLab, University of Twente, the Netherlands

Muu info

Revised second edition of the leading textbook on quantitative and qualitative methods for conducting Human-Computer Interaction research
About the Authors xix
Foreword xxi
Preface xxiii
Acknowledgments xxv
Chapter 1 Introduction to HCI Research
1(24)
1.1 Introduction
1(1)
1.1.1 History of HCI
1(1)
1.2 Types of HCI Research Contributions
2(1)
1.3 Changes in Topics of HCI Research Over Time
3(1)
1.4 Changes in HCI Research Methods Over Time
4(3)
1.5 Understanding HCI Research Methods and Measurement
7(2)
1.6 The Nature of Interdisciplinary Research in HCI
9(2)
1.7 Who is the Audience for Your Research?
11(2)
1.8 Understanding One Research Project in the Context of Related Research
13(5)
1.9 Inherent Trade-offs in HCI
18(1)
1.10 Summary of
Chapters
19(6)
References
22(3)
Chapter 2 Experimental Research
25(20)
2.1 Types of Behavioral Research
26(1)
2.2 Research Hypotheses
27(5)
2.2.1 Null Hypothesis and Alternative Hypothesis
28(2)
2.2.2 Dependent and Independent Variables
30(1)
2.2.3 Typical Independent Variables in HCI Research
30(1)
2.2.4 Typical Dependent Variables in HCI Research
31(1)
2.3 Basics of Experimental Research
32(3)
2.3.1 Components of an Experiment
32(1)
2.3.2 Randomization
33(2)
2.4 Significance Tests
35(4)
2.4.1 Why Do We Need Them?
35(1)
2.4.2 Type I and Type II Errors
36(2)
2.4.3 Controlling the Risks of Type I and Type II Errors
38(1)
2.5 Limitations of Experimental Research
39(2)
2.6 Summary
41(4)
References
43(2)
Chapter 3 Experimental Design
45(26)
3.1 What Needs to be Considered When Designing Experiments?
46(1)
3.2 Determining the Basic Design Structure
47(1)
3.3 Investigating a Single Independent Variable
48(8)
3.3.1 Between-Group Design and Within-Group Design
49(3)
3.3.2 Choosing the Appropriate Design Approach
52(4)
3.4 Investigating More Than One Independent Variable
56(3)
3.4.1 Factorial Design
56(1)
3.4.2 Split-Plot Design
57(1)
3.4.3 Interaction Effects
58(1)
3.5 Reliability of Experimental Results
59(6)
3.5.1 Random Errors
59(1)
3.5.2 Systematic Errors
60(5)
3.6 Experimental Procedures
65(1)
3.7 Summary
66(5)
References
68(3)
Chapter 4 Statistical Analysis
71(34)
4.1 Preparing Data for Statistical Analysis
71(3)
4.1.1 Cleaning Up Data
72(1)
4.1.2 Coding Data
73(1)
4.1.3 Organizing Data
74(1)
4.2 Descriptive Statistics
74(2)
4.2.1 Measures of Central Tendency
74(1)
4.2.2 Measures of Spread
75(1)
4.3 Comparing Means
76(1)
4.4 t Tests
77(3)
4.4.1 Independent-Samples t Test
78(1)
4.4.2 Paired-Samples / Test
78(1)
4.4.3 Interpretation of t Test Results
79(1)
4.4.4 Two-Tailed t Tests and One-Tailed t Tests
80(1)
4.5 Analysis of Variance
80(7)
4.5.1 One-Way ANOVA
80(2)
4.5.2 Factorial ANOVA
82(1)
4.5.3 Repeated Measures ANOVA
83(2)
4.5.4 ANOVA for Split-Plot Design
85(2)
4.6 Assumptions of t Tests and F Tests
87(1)
4.7 Identifying Relationships
88(5)
4.7.1 Correlation
88(3)
4.7.2 Regression
91(2)
4.8 Nonparametric Statistical Tests
93(7)
4.8.1 Chi-Squared Test
94(2)
4.8.2 Other Nonparametric Tests
96(4)
4.9 Summary
100(5)
References
103(2)
Chapter 5 Surveys
105(30)
5.1 Introduction
105(1)
5.2 Benefits and Drawbacks of Surveys
106(2)
5.3 Goals and Targeted Users for Survey Research
108(1)
5.4 Probabilistic Sampling
109(4)
5.4.1 Stratification
111(1)
5.4.2 Response Size
112(1)
5.4.3 Errors
113(1)
5.5 Nonprobabilistic Sampling
113(6)
5.5.1 Demographic Data
114(1)
5.5.2 Oversampling
115(1)
5.5.3 Random Sampling of Usage, Not Users
116(1)
5.5.4 Self-Selected Surveys
116(1)
5.5.5 Uninvestigated Populations
117(2)
5.6 Developing Survey Questions
119(3)
5.6.1 Open-Ended Questions
119(1)
5.6.2 Closed-Ended Questions
120(1)
5.6.3 Common Problems With Survey Questions
121(1)
5.7 Overall Survey Structure
122(2)
5.8 Existing Surveys
124(1)
5.9 Paper or Online Surveys?
124(2)
5.10 Pilot Testing the Survey Tool
126(2)
5.11 Response Rate
128(1)
5.12 Data Analysis
129(1)
5.13 Summary
130(5)
References
131(4)
Chapter 6 Diaries
135(18)
6.1 Introduction
135(3)
6.2 Why do we Use Diaries in HCI Research?
138(3)
6.3 Participants for a Diary Study
141(2)
6.4 What Type of Diary?
143(2)
6.4.1 Feedback Diary
143(1)
6.4.2 Elicitation Diary
144(1)
6.4.3 Hybrid Feedback and Elicitation Diary
145(1)
6.5 Data Collection for the Diary Study
145(3)
6.6 Letting Participants Know When to Record a Diary Entry
148(1)
6.7 Analysis of Diaries
149(1)
6.8 Summary
150(3)
References
151(2)
Chapter 7 Case Studies
153(34)
7.1 Introduction
153(1)
7.2 Observing Sara: A Case Study of a Case Study
154(2)
7.3 What is a Case Study?
156(3)
7.3.1 In-Depth Investigation of a Small Number of Cases
156(1)
7.3.2 Examination in Context
157(1)
7.3.3 Multiple Data Sources
157(2)
7.3.4 Emphasis on Qualitative Data and Analysis
159(1)
7.4 Goals of HCI Case Studies
159(6)
7.4.1 Exploration
160(1)
7.4.2 Explanation
160(2)
7.4.3 Description
162(2)
7.4.4 Demonstration
164(1)
7.5 Types of Case Study
165(5)
7.5.1 Intrinsic or Instrumental
165(1)
7.5.2 Single Case or Multiple Cases
165(4)
7.5.3 Embedded or Holistic
169(1)
7.6 Research Questions and Hypotheses
170(2)
7.7 Choosing Cases
172(2)
7.8 Data Collection
174(2)
7.8.1 Data Sources and Questions
174(1)
7.8.2 Collecting Data
175(1)
7.9 Analysis and Interpretation
176(2)
7.10 Writing Up the Study
178(2)
7.11 Informal Case Studies
180(2)
7.12 Summary
182(5)
References
184(3)
Chapter 8 Interviews and Focus Groups
187(42)
8.1 Introduction
187(1)
8.2 Pros and Cons of Interviews
188(1)
8.3 Applications of Interviews in HCI Research
189(7)
8.3.1 Initial Exploration
189(4)
8.3.2 Requirements Gathering
193(2)
8.3.3 Evaluation and Subjective Reactions
195(1)
8.4 Who to Interview
196(2)
8.5 Interview Strategies
198(6)
8.5.1 How Much Structure?
198(2)
8.5.2 Focused and Contextual Interviews
200(4)
8.6 Interviews vs Focus Groups
204(2)
8.7 Types of Questions
206(4)
8.8 Conducting an Interview
210(6)
8.8.1 Preparation
210(1)
8.8.2 Recording the Responses
211(1)
8.8.3 During the Interview
212(4)
8.9 Electronically Mediated Interviews and Focus Groups
216(3)
8.9.1 Telephone
217(1)
8.9.2 Online
217(2)
8.10 Analyzing Interview Data
219(5)
8.10.1 What to Analyze
220(1)
8.10.2 How to Analyze
221(2)
8.10.3 Validity
223(1)
8.10.4 Reporting Results
223(1)
8.11 Summary
224(5)
References
226(3)
Chapter 9 Ethnography
229(34)
9.1 Introduction
229(2)
9.2 What is Ethnography?
231(2)
9.3 Ethnography in HCI
233(2)
9.4 Conducting Ethnographic Research
235(13)
9.4.1 Selecting a Site or Group of Interest
236(1)
9.4.2 Participating: Choosing a Role
237(4)
9.4.3 Building Relationships
241(1)
9.4.4 Making Contact
242(1)
9.4.5 Interviewing, Observing, Analyzing, Repeating, and Theorizing
243(4)
9.4.6 Reporting Results
247(1)
9.5 Some Examples
248(8)
9.5.1 Home Settings
248(1)
9.5.2 Work Settings
249(1)
9.5.3 Educational Settings
250(1)
9.5.4 Ethnographies of Mobile and Ubiquitous Systems
251(1)
9.5.5 Virtual Ethnography
252(4)
9.6 Summary
256(7)
References
258(5)
Chapter 10 Usability Testing
263(36)
10.1 Introduction
263(1)
10.2 What is Usability Testing?
263(2)
10.3 How Does Usability Testing Relate to "Traditional" Research?
265(2)
10.4 Types of Usability Testing or Usability Inspections
267(4)
10.4.1 Expert-Based Testing
268(2)
10.4.2 Automated Usability Testing
270(1)
10.5 The Process of User-Based Testing
271(22)
10.5.1 Formative and Summative Usability Testing
271(3)
10.5.2 Stages of Usability Testing
274(1)
10.5.3 How Many Users are Sufficient?
275(1)
10.5.4 Locations for Usability Testing
276(10)
10.5.5 Task Lists
286(2)
10.5.6 Measurement
288(2)
10.5.7 The Usability Testing Session
290(2)
10.5.8 Making Sense of the Data
292(1)
10.6 Other Variations on Usability Testing
293(1)
10.7 Summary
294(5)
References
296(3)
Chapter 11 Analyzing Qualitative Data
299(30)
11.1 Introduction
299(1)
11.2 Goals and Stages of Qualitative Analysis
300(1)
11.3 Content Analysis
301(2)
11.3.1 What is Content?
301(1)
11.3.2 Questions to Consider Before Content Analysis
301(2)
11.4 Analyzing Text Content
303(17)
11.4.1 Coding Schemes
303(8)
11.4.2 Coding the Text
311(3)
11.4.3 Ensuring High-Quality Analysis
314(6)
11.5 Analyzing Multimedia Content
320(2)
11.6 Summary
322(7)
References
325(4)
Chapter 12 Automated Data Collection Methods
329(40)
12.1 Introduction
329(1)
12.2 Existing Tools
330(9)
12.2.1 Web Logs
330(8)
12.2.2 Stored Application Data
338(1)
12.3 Activity-Logging Software
339(7)
12.3.1 Web Proxies and Interaction Loggers
340(4)
12.3.2 Keystroke and Activity Loggers
344(1)
12.3.3 Interaction Recording Tools
345(1)
12.4 Custom Software
346(7)
12.4.1 Instrumented Software
346(3)
12.4.2 Research Software
349(4)
12.5 Hybrid Data Collection Methods
353(1)
12.6 Data Management and Analysis
354(4)
12.6.1 Handling Stored Data
354(1)
12.6.2 Analyzing Log Files
355(3)
12.7 Automated Interface Evaluation
358(1)
12.8 Challenges of Computerized Data Collection
358(3)
12.9 Summary
361(8)
References
365(4)
Chapter 13 Measuring the Human
369(42)
13.1 Introduction
369(1)
13.2 Eye Tracking
370(6)
13.2.1 Background
370(1)
13.2.2 Applications
371(5)
13.3 Motion and Position Tracking
376(5)
13.3.1 Muscular and Skeletal Position Sensing
377(2)
13.3.2 Motion Tracking for Large Displays and Virtual Environments
379(2)
13.4 Physiological Tools
381(5)
13.4.1 Physiological Data
381(5)
13.5 Data Collection, Analysis, and Interpretation
386(8)
13.5.1 Data Collection
387(2)
13.5.2 Data Analysis
389(1)
13.5.3 Data Interpretation
390(4)
13.6 Examples
394(2)
13.7 Summary
396(15)
References
399(12)
Chapter 14 Online and Ubiquitous HCI Research
411(44)
14.1 Introduction
411(1)
14.2 Online Research
412(13)
14.2.1 Observational Online Studies
412(2)
14.2.2 Online Data Collection
414(2)
14.2.3 Online Activity
416(6)
14.2.4 Online Research Design Challenges
422(3)
14.3 Human Computation
425(11)
14.3.1 Introduction to Human Computation
425(4)
14.3.2 Conducting Human Computation Studies
429(6)
14.3.3 Future of Human Computation
435(1)
14.4 Sensors and Ubiquitous Computing
436(5)
14.4.1 History and Examples
437(2)
14.4.2 Ubiquitous Computing Research Methods
439(2)
14.5 Summary
441(14)
References
443(12)
Chapter 15 Working With Human Subjects
455(38)
15.1 Introduction
455(1)
15.2 Identifying Potential Participants
455(8)
15.2.1 Which Subjects?
456(2)
15.2.2 How Many Subjects?
458(2)
15.2.3 Recruiting Participants
460(3)
15.3 Care and Handling of Research Participants
463(21)
15.3.1 Risks and Concerns of Research Participants
464(4)
15.3.2 Protecting Privacy
468(1)
15.3.3 Institutional Review Boards
469(3)
15.3.4 Informed Consent
472(4)
15.3.5 Respecting Participants
476(2)
15.3.6 Additional Concerns
478(5)
15.3.7 International Concerns
483(1)
15.4 Human Subjects Research and the Public Trust
484(1)
15.5 Summary
485(8)
References
487(6)
Chapter 16 Working With Research Participants With Disabilities
493(30)
16.1 Introduction
493(2)
16.2 Participants
495(9)
16.2.1 Inclusion Criteria
495(2)
16.2.2 Differing Levels of Ability
497(2)
16.2.3 Recruitment of Participants With Disabilities
499(2)
16.2.4 Communicating With People Who are Deaf or Hard of Hearing
501(1)
16.2.5 Communicating With People With Moderate to Severe Speech Impairments
502(1)
16.2.6 Proxy Users
503(1)
16.3 Methodological Considerations
504(4)
16.3.1 Small Sample Sizes
504(1)
16.3.2 Distributed Research
505(1)
16.3.3 In-Depth Case Studies
506(1)
16.3.4 Consistent Technical Environment or Best Case Scenario?
507(1)
16.3.5 Interventions
508(1)
16.4 Logistics
508(10)
16.4.1 Communicating With Potential Participants
508(1)
16.4.2 Pilot Studies
509(1)
16.4.3 Scheduling Data Collection Involving Users With Disabilities
510(1)
16.4.4 Involving Participants With Cognitive Disabilities/Intellectual Impairments
511(2)
16.4.5 Documentation for Users With Disabilities
513(3)
16.4.6 Bringing Extra Computer Parts
516(1)
16.4.7 Payment
517(1)
16.5 Summary
518(5)
References
520(3)
Index 523
Jonathan Lazar is a professor in the Department of Computer and Information Sciences at Towson University and has served as director of the Undergraduate Program in Information Systems since 2003. He also founded the Universal Usability Laboratory at Towson University and served as director from 2003 to 2014. In the area of human-computer interaction, Lazar is involved in teaching and research on web accessibility for people with disabilities, user-centered design methods, assistive technology, and law and public policy related to HCI. He has previously authored or edited 10 books, including Ensuring Digital Accessibility Through Process and Policy (coauthored with Dan Goldstein and Anne Taylor), Disability, Human Rights, and Information Technology Accessibility (coedited with Michael Stein), Universal Usability: Designing Computer Interfaces for Diverse User Populations, and Web Usability: A User-Centered Design Approach. He has published over 140 refereed articles in journals, conference proceedings, and edited books, and has been granted two US patents for his work on accessible web-based security features for blind users. He frequently serves as an adviser to government agencies and regularly provides testimony at federal and state levels, and multiple US federal regulations cite his research publications. His research has been funded by the National Science Foundation; National Institute on Disability, Independent Living, and Rehabilitation Research (NIDILRR); American Library Association; and TEDCO. He currently serves on the executive board of the Friends of the Maryland Library for the Blind and Physically Handicapped and the State of Maryland Work Group on Increasing the Teaching of IT Accessibility Concepts in State Universities. He has served in multiple roles in the Association for Computing Machinery Special Interest Group on Computer-Human Interaction (ACM SIGCHI), most recently, adjunct chair of public policy (201015) and Digital Accessibility Chair (CHI 2014). Lazar has been honored with the 2017 University System of Maryland Board of Regents Award for Excellence in Research, the 2016 SIGCHI Social Impact Award, given annually to an individual who has promoted the application of human-computer interaction research to pressing societal needs, the 2015 AccessComputing Capacity Building Award (sponsored by the University of Washington and the National Science Foundation) for advocacy on behalf of people with disabilities in computing fields, the 2011 University System of Maryland Board of Regents Award for Excellence in Public Service, and the 2010 Dr. Jacob Bolotin Award from the National Federation of the Blind, for working towards achieving the full integration of the blind into society on a basis of equality. In 2012, Lazar was selected to be the Shutzer Fellow at the Radcliffe Institute for Advanced Study at Harvard University, where he investigates the relationship between human-computer interaction for people with disabilities and US disability rights law. Jinjuan Heidi Feng is a professor in the Department of Computer and Information Sciences at Towson University. She conducts research in the areas of human-computer interaction, universal accessibility, health informatics, and usable and accessible security. She works closely with national and local communities to improve the quality of life for people with disabilities through information technology. Her current research projects focus on assistive technologies for people with cognitive disabilities in educational and professional settings, mobile applications for health related activities, and accessible security techniques for individuals with visual or cognitive disabilities. Her research has been funded by various national and state agencies such as the National Science Foundation (NSF), the National Institute on Disability, Independent Living, and Rehabilitation Research (NIDILRR), and TEDCO. Her work has been published in various top-notch journals and presented at conferences such as Human-Computer Interaction, ACM Transactions on Computer-Human Interaction, and ACM Transactions on Accessible Computing. She has received the Maryland Daily Record's Innovator of The Year Award” twice, in 2009 and 2016. Dr. Feng was appointed as the director for the School of Emerging Technologies in Fall 2015 and is leading the effort to promote interdisciplinary collaboration across the Towson University campus. She currently serves on the editorial board of ACM Transactions on Accessible Computing. She also served as the general conference chair for the 18th ACM SIGACCESS International Conference on Computers and Accessibility (ASSETS 2016). Harry Hochheiser is currently a faculty member in the Department of Biomedical Informatics and the Intelligent Systems Program at the University of Pittsburgh, where he is actively involved in the Biomedical Informatics Training Program. Previously, Hochheiser served as an assistant professor at Towson University, and worked at Massachusetts General Hospital, Tufts University School of Medicine, AT & T Bell Labs, IBM T.J. Watson Labs, and the National Institutes on Aging. Working at the intersection of human-computer interaction and healthcare informatics, his research has covered a range of topics, including human-computer interaction, information visualization, bioinformatics, clinical informatics, universal usability, security, privacy, and public policy implications of computing systems. His research has been funded by the National Cancer Institute, National Library of Medicine, the Centers for Disease Control and Prevention, and the Baobab Health Trust, among others. Hochheiser has taught and developed several courses at both undergraduate and graduate levels, including introductory computer science, introduction to algorithms, information visualization, advanced web development, and human-computer interaction. He is a member of the US Public Policy Committee of the Association of Computing Machinery, and of the American Medical Informatics Association (AMIA) public policy committee. Hochheiser is co-recipient of the 2009 Maryland Daily Record's Innovator of the Year Award” with Lazar and Feng, for the development of improved web-based security features for blind users.