Information Course Schedule fall 2014

Lower Division Courses

How can we critically think about emergent phenomena of the Internet? Is the Internet a democratic medium for political action (a "networked public sphere") or a surveillance apparatus of centralized control? Who has access to digital information and what techniques are used to make information artificially scarce? How do trade group lawsuits against digital "piracy" affect a generation's perception of the law? Should we look at the growing sphere of copyright as a public interest problem, or celebrate the expansion of creators' rights? Can free software thrive independently from ideological backing? Why are peer production communities like Wikipedia and Linux affected by extreme gender disparity?

In this course, we will examine the societal implications of computer networks from critical and technical perspectives. We will collectively engage with issues of intellectual property, access to information, privacy, freedom of speech, representation, and peer production. We will be discussing provocative texts and media, doing hands-on exploration of emerging technologies, and practicing ethnographic fieldwork in online communities. We will also offer opportunities for field trips and guest speakers to provide us with different perspectives. Additionally, students will engage in a semester-long collaborative project in a flexible format.

This is a student-initiated group study course (DE-Cal). Please contact the student coordinator(s) for specific questions.

Must be taken on a passed/not passed basis.

Th 3:30-5 | 254 Dwinelle
Instructor(s): Paul Duguid Rodrigo Ochigame, Tony Chen
CCN:
41503

Upper Division Courses

Three hours of lecture per week. With the advent of virtual communities and online social networks, old questions about the meaning of human social behavior have taken on renewed significance. Using a variety of online social media simultaneously, and drawing upon theoretical literature in a variety of disciplines, this course delves into discourse about community across disciplines. This course will enable students to establish both theoretical and experiential foundations for making decisions and judgments regarding the relations between mediated communication and human community.

Students will receive no credit for Sociology C167/Information C167 after taking Sociology 167.

Also listed as Sociology C167.

W 5-8 | 10 Evans
Instructor(s): Marc Smith, Alexy Khrabrov
CCN:
41505

How can we critically think about emergent phenomena of the Internet? Is the Internet a democratic medium for political action (a "networked public sphere") or a surveillance apparatus of centralized control? Who has access to digital information and what techniques are used to make information artificially scarce? How do trade group lawsuits against digital "piracy" affect a generation's perception of the law? Should we look at the growing sphere of copyright as a public interest problem, or celebrate the expansion of creators' rights? Can free software thrive independently from ideological backing? Why are peer production communities like Wikipedia and Linux affected by extreme gender disparity?

In this course, we will examine the societal implications of computer networks from critical and technical perspectives. We will collectively engage with issues of intellectual property, access to information, privacy, freedom of speech, representation, and peer production. We will be discussing provocative texts and media, doing hands-on exploration of emerging technologies, and practicing ethnographic fieldwork in online communities. We will also offer opportunities for field trips and guest speakers to provide us with different perspectives. Additionally, students will engage in a semester-long collaborative project in a flexible format.

This is a student-initiated group study course (DE-Cal). Please contact the student coordinator(s) for specific questions.

Must be taken on a passed/not passed basis.

Th 3:30-5 | 254 Dwinelle
Instructor(s): Paul Duguid Rodrigo Ochigame, Tony Chen
CCN:
41506

Core Courses

8 weeks; 3 hours of lecture per week. This course introduces the intellectual foundations of information organization and retrieval: conceptual modeling, semantic representation, vocabulary and metadata design, classification, and standardization, as well as information retrieval practices, technology, and applications, including computational processes for analyzing information in both textual and non-textual formats.

This is a required introductory course for MIMS students, integrating perspectives and best practices from a wide range of disciplines.

NOTE: Before Fall 2017, Info 202 was offered as a full-semester course for 4 units.

MW 9-10:30 | 210 South Hall
Instructor(s): Robert Glushko
CCN:
41566

7 weeks - 4 hours of laboratory per week. This course introduces software skills used in building prototype scripts for applications in data science and information management. The course gives an overview of procedural programming, object-oriented programming, and functional programming techniques in the Python scripting language, together with an overview of fundamental data structures, associated algorithms, and asymptotic performance analysis. Students will watch a set of instructional videos covering material and will have four hours of laboratory-style course contact each week.

NOTE: Before Fall 2017, Info 206 was titled “Distributed Computing Applications and Infrastructure” and was offered as a full-semester course for 4 units.

TuTh 9-10:30 | 210 South Hall
Instructor(s): Doug Tygar
CCN:
41584

General Courses

Three hours of lecture per week. User interface design and human-computer interaction. Examination of alternative design. Tools and methods for design and development. Human- computer interaction. Methods for measuring and evaluating interface quality.

This course covers the design, prototyping, and evaluation of user interfaces to computers which is often called Human-Computer Interaction (HCI). It is loosely based on course CS1 described in the ACM SIGCHI Curricula for Human-Computer Interaction (Association for Computing Machinery, 1992).

HCI covers many topics including:

  1. Human capabilities (e.g., visual and auditory perception, memory, mental models, and interface metaphors);
  2. Interface technology (e.g., input and output devices, interaction styles, and common interface paradigms); and,
  3. Interface design methods (e.g., user-centered design, prototyping, and design principles and rules), and interface evaluation (e.g., software logging, user observation, benchmarks and experiments).

This material is covered through lectures, reading, discussions, homework assignments, and a course project. This course differs from CS 160 primarily in two ways:

  1. There is an emphasis on interfaces for information technology applications; and,
  2. There is less emphasis on programming and system development, although some simple prototyping (for example, in visual basic or using JAVA GUI development tools) may be required. (CS 160 has a big programming project.)
TuTh 10:30-12 | 210 South Hall
Instructor(s): Tapan Parikh
CCN:
41590

This course focuses on managing people in information-intensive firms and industries, such as information technology industries. Students who seek careers in these industries will soon be asked to manage people, teams, departments, and units. They need to learn how to manage. However, managing is sometimes very different in these settings: Employees are highly educated; work is more fluid; teamwork and collaboration are essential; and external situations and strategies change rapidly. For these reasons several management principles born in a traditional manufacturing era no longer apply. In particular, the old style of “command and control” needs to give way to more distributed ways of work, with significant consequences for how managers need to manage. Of course, some universal management principles apply no matter what circumstance.

While we will cover these universal management principles in this course, we will pay particular attention to management issues that are highly relevant in information-intensive settings. Topics to be covered will likely include: managing knowledge workers; managing teams (incl. virtual ones); collaborating across disparate units, giving and receiving feedback; managing the innovation process (incl. in eco-systems); managing through networks; and managing when using communication tools (e.g., tele-presence). The course will rely heavily on cases as a pedagogical form.

This course satisfies the Management of Information Projects & Organizations requirement.

F 9-12 | 210 South Hall
Instructor(s): Morten Hansen
CCN:
41591

"Behavioral Economics" is one important perspective on how information impacts human behavior. The goal of this class is to deploy a few important theories about the relationship between information and behavior, into practical settings — emphasizing the design of experiments that can now be incorporated into many 'applications' in day-to-day life. Truly 'smart systems' will have built into them precise, testable propositions about how human behavior can be modified by what the systems tell us and do for us. So let's design these experiments into our systems from the ground up! This class develops a theoretically informed, practical point of view on how to do that more effectively and with greater impact.

Previously offered as Info 290. Applied Behavioral Economics for Information Systems.

TuTh 2-3:30 | 210 South Hall
Instructor(s): Steven Weber
CCN:
41592

Three hours of lecture per week. This course will provide an overview of the intellectual property laws with which information managers need to be familiar. It will start with a consideration of trade secrecy law that information technology and other firms routinely use to protect commercially valuable information. It will then consider the role that copyright law plays in the legal protection of information products and services. Although patents for many years rarely were available to protect information innovations, patents on such innovations are becoming increasingly common. As a consequence, it is necessary to consider standards of patentability and the scope of protection that patent affords to innovators. Trademark law allows firms to protect words or symbols used to identify their goods or services and to distinguish them from the goods and services of other producers. It offers significant protection to producers of information products and services. Because so many firms license intellectual property rights, some coverage of licensing issues is also important. Much of the course will concern the legal protection of computer software and databases, but it will also explore some intellectual property issues arising in cyberspace.

MW 10:30-12 | 202 South Hall
Instructor(s): Brian Carver
CCN:
41593

This course is a survey of Web technologies, ranging from the basic technologies underlying the Web (URI, HTTP, HTML) to more advanced technologies being  used in the the context of Web engineering, for example structured data  formats and Web programming frameworks. The goal of this course is to provide an  overview of the technical issues surrounding the Web today, and to provide a  solid and comprehensive perspective of the Web's constantly evolving landscape.

Students will receive no credit for 253 after taking 290. Web Architecture.

F 2-5 | 210 South Hall
Instructor(s): Jim Blomo
CCN:
41599

This course examines the state-of-the-art in applied Natural Language Processing (also known as content analysis and language engineering), with an emphasis on how well existing algorithms perform and how they can be used (or not) in applications. Topics include part-of-speech tagging, shallow parsing, text classification, information extraction, incorporation of lexicons and ontologies into text analysis, and question answering. Students will apply and extend existing software tools to text-processing problems.

Restrictions for non–I School students interested in taking Info 256.

MW 10:30-12 | 210 South Hall
Instructor(s): Marti Hearst
CCN:
41602

Three hours of lecture per week. This course is concerned with the use of Database Management Systems (DBMS) to solve a wide range of information storage, management and retrieval problems, in organizations ranging from large corporations to personal applications, such as research data management. The course combines the practical aspects of DBMS use with more theoretical discussions of database design methodologies and the "internals" of database systems.

A significant part of the course will require students to design their own database and implement it on different DBMS that run on different computer systems. We will use both ACCESS and ORACLE.

In the theoretical portion of the course, we will examine the major types or data models of DBMS (hierarchical, network, relational, and object-oriented). We will discuss the principles and problems of database design, operation, and maintenance for each data model.

TuTh 12:30-2 | 210 South Hall
Instructor(s): Ray Larson
CCN:
41605

This course will explore the theory and practice of Tangible User Interfaces, a new approach to HCI which focuses on the physical interaction with computational media. The topics covered in the course include:

  • Theoretical framework of Tangible User Interfaces
  • Design examples of Tangible User Interfaces
  • Enabling technologies for Tangible User Interfaces

Students will design and develop experimental Tangible User Interfaces, applications, underlying technologies, and theories using concept sketches, posters, physical mockups, working prototypes, and a final project report. The course will have 3 hours of lecture and 1 hour of laboratory per week.

Note:  Previously listed as Info 290: Theory and Practice of Tangible User Interfaces. Students who completed INFO 290 section 4 in Fall 2008 will receive no credit for Info 262.

This course is cross-listed as New Media C262.

MW 2-3:30 | 210 South Hall
Instructor(s): Kimiko Ryokai
CCN:
41608

The goal of this course is to provide students with an introduction to many different types of quantitative research methods and statistical techniques. This course will be divided into two sections: 1) methods for quantitative research and, 2) quantitative statistical techniques for analyzing data. We begin with a focus on defining research problems, theory testing, causal inference, and designing research instruments. Then, we will explore a range of statistical techniques and methods that are available for empirical research. Topics in research methods include: Primary and Secondary Data Analysis, Sampling, Survey Design, and Experimental Designs. Topics in quantitative techniques include: Descriptive and Inferential statistics, General Linear Models, and Non-Linear Models. The course will conclude with an introduction to special topics in quantitative research methods.

TuTh 3:30-5 | 210 South Hall
Instructor(s): Coye Cheshire
CCN:
41614

This course will focus upon the use of qualitative methods for research about information technologies. Methods including interviewing, focus groups, participant observation and ethnography will be taught and practiced. Significant qualitative research findings about the social impact of information technologies will be read, to analyze what we know about IT thus far, how we know it, and as models of theories and methods for future research. Frequent field exercises will be assigned to develop qualitative research skills and best practices, but the primary assignment will be to engage in a substantial fieldwork project. Methods covered will include video if grant support or other budget resources are found.

TuTh 12:30-2 | 205 South Hall
Instructor(s): Jenna Burrell
CCN:
41617

This seminar reviews current literature and debates regarding Information and Communication Technologies and Development (ICTD). This is an interdisciplinary and practice-oriented field that draws on insights from economics, sociology, engineering, computer science, management, public health, etc.

TuTh 2-3:30 | 202 South Hall
Instructor(s): Isha Ray
CCN:
41620

Special Topics Courses

The ICTD group seminar will discuss topics of current interest in the emerging multidisciplinary field of Information and Communications Technologies and Development, or ICTD. Each semester will be focused on a particular topic or set of topics, under the direction of appropriate faculty from the I School's ICTD group. The course content will consist of paper discussions, invited lectures from both within and outside the class and a some relatively short written assignments. Students will also be responsible for presenting during at least on class session, either on their own research, ideas or on a selected set of papers relevant to the semester's chosen topic.

Section: 10
W 11-12 | 107 South Hall
Instructor(s): Tapan Parikh
CCN:
41638

What insights about student learning can be revealed from data, and how can those insights be used to improve the efficacy of educational technology? This course will cover computational approaches to the task of modeling learning and improving outcomes in Intelligent Tutoring Systems (ITS) and Massive Open Online Courses (MOOCs). We will cover theories and methodologies underpinning current approaches to knowledge discovery and data mining in education and survey the latest developments in the broad field of human learning research.

This course will be project based, where teams will be introduced to online learning platforms and their datasets with the objective of pairing data analysis with theory or implementation. Literature review will serve to add context and grounding to projects.

Suggested background includes one programming course and familiarity with one statistical/computational software package.

The study of learning in online environments is an interdisciplinary pursuit, and therefore all majors are welcomed and encouraged to bring complimentary backgrounds.

Undergraduates with the appropriate background and motivation are encouraged to enroll but must contact Associate Director of Student Affairs Catherine Cronquist Browning for enrollment permissions.

NOTE: This course is cross-listed as Education 290A. Formative Assessment in Virtual Learning Environments.

(Currently offered as Info C260F.)

Section: 7
TuTh 2-3:30 | 205 South Hall
Instructor(s): Zachary Pardos
CCN:
41631

Students in this course will expand on their knowledge of techniques for exploratory data analysis (EDA) and collaborate on and contribute to a research project whose goal is to create a new framework for the EDA process.

Topics and goals overview:

Exploratory data analysis is an approach to examining data that emphasizes visually describing and interactively and iteratively inspecting data. EDA is the first step in data analysis, prior to performing confirmatory statistical analysis (such as conducting statistical tests or fitting statistical models; this topic is taught in Info 271B Quantitative Research Methods, which is a terrific complement to this course). This distinction between exploratory and confirmatory statistics was originally championed by mathematical pioneer John Tukey, who said of EDA, “1. It is an attitude, and  2. a flexibility, and  3. some graph paper.”

Exploratory data analysis should be conducted before other types of analysis, in order to:

  • evaluate data quality and identify additional data to collect, if necessary,
  • suggest questions and hypotheses to pursue, or
  • assess assumptions on which later analysis will be based.

Exploratory data analysis techniques include:

  • visualization techniques (histograms, scatter plots, parallel coordinates, etc.)
  • projection methods (principal component analysis, multidimensional scaling, projection pursuit, t-SNE, etc.)
  • unsupervised machine learning (clustering, pattern mining, anomaly detection, etc.)

One challenge is that while there are a multitude of tools for data exploration, there is no established systematic understanding of or rules for guiding such exploration. Instead, data analysts learn how to do this work by slow trial and error or in an apprentice model from other analysts. Therefore, guidelines are needed to allow measurement of the amount of progress made in exploring a data set, to ensure complete coverage in exploration, to allow different sets of people to collaborate in exploring a data set individually and later combine their results, and to develop automated and intelligent assistance algorithms for data analysis interfaces.

Students in this course will expand their knowledge of and practice with exploratory data analysis techniques and at the same time will develop a repository of EDA case studies to be used to further our understanding of the EDA process. The first part of the course will consist of developing data sets and scenarios of use that can be used as examples, both for instruction and research, of best practices for EDA. The last few weeks of the course will be to help convert those examples into a systematic framework or theoretical model that characterizes the EDA process or processes, in order to guide future practice as well as to inform the design of new interactive data analysis tools.

Students will be expected to work together in teams and with the instructor to reach these goals. This is a research seminar, therefore students must be comfortable with open-ended problems, self-directed work and with setting their own goals.

The primary EDA tool used will be Tableau, but other programming abilities will be needed, e.g., for parsing and analyzing the Tableau log files, for wrangling data sets to get them into the right format, and so on. Students who are interested in the more analytic side of EDA (projection methods, clustering, etc) and who already have background in this area will be allowed to work on these problems, but must come to the course with strengths in those methods, as they will not be the focus of classroom work.

Requirements:

Course is open to graduate students from all fields, at discretion of the instructor. Students should have taken either:

  • Info 247 (Information Visualization and Presentation), or
  • CS 294-10 (Information Visualization)

Students will be expected to have:

  • Enjoyed the EDA aspects of their infoviz course
  • Familiarity with Tableau
  • Proficiency in programming and the use of software engineering tools like the unix command line, databases, version control, some scripting language (Python, MATLAB or R will be useful)
  • Ability to comfortably pick up new programming languages and software tools with minimal guidance
Section: 9
Th 10:30-12:30 | 107 South Hall
Instructor(s): Marti Hearst
CCN:
41637

Just as the web browser brought us click-stream data and the mobile phone brought us geo-location data, ubiquitous low-cost sensors integrated with wearable and Internet-of-Things devices will bring us a new torrent of user data to collect, analyze, and exploit. The course takes a hands-on approach to exploring the possibilities and limitations of consumer-grade sensing technologies for physiological and contextual data.

We will survey the intellectual foundations and research advances in ubiquitous computing, physiological and affective computing, with applications in health and wellness, social computing, information security, novel user interfaces, etc. We will cover temporal and spectral techniques for time-series data analysis. We will consider data stewardship issues, including data ownership, data privacy, and research ethics. The class lending library will provide access to a variety of devices that can be used for data collection and application prototyping.

Project work can be undertaken in a variety of application domains, such as affective computing, ambient assisted living, biometric authentication, privacy by design, quantified self, smart cars and homes, social robotics, and virtual and augmented reality.

Section: 8
M 3:30-5:30 | 202 South Hall
Instructor(s): John Chuang
CCN:
41632

Network studies have been described as “a terminological jungle in which any newcomer may plant a tree.” Since J.A. Barnes wrote that in 1972, newcomers have proliferated, the jungle flourished, and the ecosystem diversified dramatically. This growth is particularly evident in the region of “social networks” — though it can sometimes be hard to envisage anything social that could not be called a network. The aim of this course, then, is to try to understand what has been described as the “modern obsession” with networks, to try to decide what might be valuable and what ephemeral, and to see if we can justify such decisions. For this, we will attempt to set some recent accounts in both disciplinary and historical context. Consequently, we will look at contributions from different fields and different periods. In particular, this seminar will seek to encourage dialogue among its participants by examining the implicit dialogue among the texts we shall be reading and the fields they represent, while keeping an eye on cases where, despite the shared terminology, the works seem to have nothing to say to each other.

Section: 1
Tu 3:30-5:30 | 107 South Hall
Instructor(s): Paul Duguid
CCN:
41623

Health and health care have profound impact on a society's well being and economic productivity. Health care reform and ongoing economic forces are placing unprecedented pressure on the health care system to provide consumers and payers with value. Patients, purchasers, regulators, and other key stakeholders are demanding that care be readily accessible, proactive, and focused on improving health while containing costs. The health care system, policy makers, and key stakeholders are responding by developing new care models that focus on patient and customer centricity, novel information practices, and the seamless integration of care.

Following a review of the current trends in health care, the course will explore the relationship between health care and the information economy. We will also delve into information strategies being utilized by health care providers, patients, payers, and other key stakeholders to improve care while controlling costs. Health care leaders from Kaiser Permanente will serve as guest lecturers, providing tangible perspective to our discussions.

Section: 2
F 1-3 (September 5 - October 24) | 202 South Hall
Instructor(s): Scott Young, Sean Hennessey
CCN:
41644

Mass communications technologies have been profound influencers of human identity, from the printing press and the rise of vernacular political cultures to television and the power of celebrity. While the Web is still a work in progress, salient characteristics such as the collapse of distance, the discovery of like-minded groups, and information delivered in short bursts are already affecting the way people see themselves and the way they consume information. Following an overview on the relationship of technology with identity and communications, the course will look at the uses of narrative in news, public relations, advertising, entertainment, and online gaming.

Section: 1
M 3:30-6:30 (September 8 - October 6) | 210 South Hall
Instructor(s): Quentin Hardy
CCN:
41641

Free communication has changed the world, including the expectations and work and play. The class begins with the two data revolutions--the first about passively collected clicks on the web, the second about actively contributed data, as platforms like Facebook empower individuals to contribute a variety of quantitative and qualitative data (transactions, social relations, attention gestures, intention, location, and more.) With active student participation, we explore the far-reaching implications of the consumer data revolution for individuals, communities, business, and society.

This course was previously offered for 1 unit; in Fall 2016, the course increased to 2 units.

Section: 3
Tu 3:30-6:30 (September 30 - November 25) | 202 South Hall
Instructor(s): Andreas Weigend
CCN:
41647

Every business depends on information — about customers, competitors, trends, performance, etc. Entire curricula have been focused on the technological, systems, strategic, and management challenges associated with that dependency. This course, however, looks at a different intersection between information and business. Specifically, it will explore how entrepreneurs across the world are developing ventures fundamentally centered on new and emerging information technologies and the business models and strategies they make possible. These include not only the Googles, Amazons, and Facebooks of the world, but also ventures like Comat and Samasource. In some cases, these are efforts on the proverbial cutting edge of technology; more often they involve creative application and/or integration of existing information technologies in innovative ways.

We will first examine the key elements of business models and the entrepreneurial process, before looking in more detail at a variety of ventures leveraging information-based technologies and strategies in an array of markets. Using of mix of case-study discussion, short lectures, and focused conversations with active entrepreneurs, this will be a highly interactive and collaborative course — not a sit-listen-take-notes type of class.

Expect to be actively involved in a series of in-class and outside assignments, both individual- and team-based, that will help you develop an understanding of how entrepreneurs are using information-centric technologies to create new markets and redefine old ones, and the lessons learned along the way. You may also explore your own ideas for new ventures along the way.

NOTE: This course was previously offered as 290. Information-Centric Entrepreneurship & Startup Strategies.

Th 3:30-5:30 | 202 South Hall
Instructor(s): Kurt Beyer
CCN:
41653

Students will work on the full-stack web development process while applying concepts taught in INFO 202, “Information Organization and Retrieval,” which is a pre- or co-requisite for the course. Students will apply concepts and techniques for information architecture, resource description and transformation, categorization, and interaction design.  Individual and team assignments will enable students to develop skills in data modeling, API design, responsive front-end design, version control, and deployment using Python, XML, jQuery and other tools and frameworks.

This course satisfies the technology requirement for the MIMS degree.

TuTh 10:30-12 | 205 South Hall
Instructor(s): Alex Miłowski, Ramit Malhotra
CCN:
41659

Seminars & Colloquia

One hour colloquium per week. Must be taken on a satisfactory/unsatisfactory basis. Colloquia, discussion, and readings are designed to introduce students to the range of interests of the school.

M 12-1:30 | 205 South Hall
Instructor(s): Jenna Burrell
CCN:
41665

The seminar explores selected advanced topics relating to 'digital libraries' with special emphasis on:

  • Access to networked resources
  • Use of two or more resources in conjunction
  • Combined use of two or more retrieval systems (e.g. use of pre- or post-processing to enhance the capabilities)
  • The redesign of library services

It is expected that these issues will require attention to a number of questions about the nature of information retrieval processes, the feasibility of not-yet-conventional techniques, techniques of making different systems work together, social impact, and the reconsideration of past practices. More generally, the seminar is intended to provide a forum for advanced students in the School. Anyone interested in these topics is welcome to join in — and to talk about their own work. This is a continuation of the previous Lynch/Buckland seminars.

Section: 1
F 3-5 | 107 South Hall
CCN:
41668

Individual & Group Study

This course is intended for graduate student instructors (GSIs) and is meant to be taken simultaneously with teaching as a GSI and to satisfy the Graduate Council's 300-level pedagogy course requirement. The practicum may include discussion, reading, preparation, and practical experience under faculty supervision in teaching, with a focus on topics within information management and systems.

Course may be repeated for credit as topic varies. Four hours of work per week per unit. Must be taken on a satisfactory/unsatisfactory basis. Does not count toward a degree.

Spring 2014: Info 375 will be offered for 2 units.

M 2-4 | 205 South Hall
Instructor(s): Brian Carver
CCN:
41736