Major/Minor Areas
Code | Title | Units |
---|---|---|
Human-Computer Interaction | ||
Introduction to User Experience Design | 4 | |
User Experience Research | 3 | |
Human-Computer Interaction (HCI) Research | 3 | |
Information Visualization and Presentation | 4 | |
Theory and Practice of Tangible User Interfaces | 4 | |
Interface Aesthetics | 3 | |
Special Topics in Information (Advanced HCI Research and Interaction Design only) | 1-4 | |
Special Topics in Technology (Biosensory Computing only) | 2-4 | |
Plus outside courses upon approval of your advisor | ||
Information Economics and Policy | ||
Information Technology Economics, Strategy, and Policy | 3 | |
Plus outside courses upon approval of your advisor | ||
Information Law and Policy | ||
Information Law and Policy | 3 | |
Technology and Delegation | 3 | |
Public Interest Cybersecurity: The Citizen Clinic Practicum | 3 | |
Special Topics in Social Science and Policy (Introduction to Politics of Information and Seminar in the Politics of Information only) | 2-4 | |
Plus outside courses upon approval of your advisor | ||
Information Organization and Retrieval | ||
Information Organization and Retrieval | 3 | |
Information Visualization and Presentation | 4 | |
Applied Machine Learning | 4 | |
Applied Natural Language Processing | 3 | |
Data Engineering | 4 | |
Natural Language Processing | 4 | |
Plus outside courses upon approval of your advisor | ||
Information Systems Design | ||
Introduction to Programming and Computation | 2 | |
Introduction to Data Structures and Analytics | 2 | |
Applied Machine Learning | 4 | |
Front-End Web Architecture | 3 | |
Back-End Web Architecture | 3 | |
Privacy Engineering | 3 | |
Data Engineering | 4 | |
Applied Natural Language Processing | 3 | |
Natural Language Processing | 4 | |
Plus outside courses upon approval of your advisor | ||
Social Aspects of Information | ||
Research Design and Applications for Data and Analysis | 3 | |
Social Issues of Information | 3 | |
User Experience Research | 3 | |
Concepts of Information | 3 | |
Leadership and Management | 3 | |
Social Psychology and Information Technology | 3 | |
Experiments and Causal Inference | 3 | |
Quantitative Research Methods for Information Systems and Management | 3 | |
Qualitative Research Methods for Information Systems and Management | 3 | |
Big Data and Development | 3 | |
Plus outside courses upon approval of your advisor | ||
Information and Communication Technologies and Devleopment | ||
Social Issues of Information | 3 | |
Introduction to User Experience Design | 4 | |
User Experience Research | 3 | |
Information and Communications Technology for Development | 3 | |
Big Data and Development | 3 | |
Plus outside courses upon approval of your advisor |
Info 201 research design and applications for data and analysis 3 units.
Terms offered: Fall 2024, Spring 2024, Fall 2023 Introduces the data sciences landscape, with a particular focus on learning data science techniques to uncover and answer the questions students will encounter in industry. Lectures, readings, discussions, and assignments will teach how to apply disciplined, creative methods to ask better questions, gather data, interpret results, and convey findings to various audiences. The emphasis throughout is on making practical contributions to real decisions that organizations will and should make. Course must be taken for a letter grade to fulfill degree requirements. Research Design and Applications for Data and Analysis: Read More [+]
Hours & Format
Fall and/or spring: 15 weeks - 1.5 hours of lecture per week
Additional Format: One and one-half hours of lecture per week.
Additional Details
Subject/Course Level: Information/Graduate
Grading: Letter grade.
Research Design and Applications for Data and Analysis: Read Less [-]
Terms offered: Fall 2024, Fall 2023, Fall 2022 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. Information Organization and Retrieval: Read More [+]
Rules & Requirements
Prerequisites: Students should have a working knowledge of the Python programming language
Fall and/or spring: 15 weeks - 3 hours of lecture per week
Additional Format: Three hours of lecture per week.
Information Organization and Retrieval: Read Less [-]
Terms offered: Spring 2024, Spring 2023, Spring 2022 This course is designed to be an introduction to the topics and issues associated with information and information technology and its role in society. Throughout the semester we will consider both the consequence and impact of technologies on social groups and on social interaction and how society defines and shapes the technologies that are produced. Students will be exposed to a broad range of applied and practical problems, theoretical issues, as well as methods used in social scientific analysis. The four sections of the course are: 1) theories of technology in society, 2) information technology in workplaces 3) automation vs. humans, and 4) networked sociability. Social Issues of Information: Read More [+]
Social Issues of Information: Read Less [-]
Terms offered: Spring 2024, Spring 2023, Spring 2022 This course uses examples from various commercial domains—retail, health, credit, entertainment, social media, and biosensing/quantified self—to explore legal and ethical issues including freedom of expression, privacy, research ethics, consumer protection, information and cybersecurity, and copyright. The class emphasizes how existing legal and policy frameworks constrain, inform, and enable the architecture, interfaces, data practices, and consumer facing policies and documentation of such offerings; and, fosters reflection on the ethical impact of information and communication technologies and the role of information professionals in legal and ethical work. Information Law and Policy: Read More [+]
Prerequisites: Consent of instructor required for nonmajors
Instructor: Mulligan
Information Law and Policy: Read Less [-]
Terms offered: Fall 2024, Fall 2023, Fall 2022 This course introduces the basics of computer programming that are essential for those interested in computer science, data science, and information management. Students will write their own interactive programs (in Python) to analyze data, process text, draw graphics, manipulate images, and simulate physical systems. Problem decomposition, program efficiency, and good programming style are emphasized throughout the course. Introduction to Programming and Computation: Read More [+]
Fall and/or spring: 7.5 weeks - 4 hours of lecture per week
Additional Format: Four hours of lecture per week for seven and one-half weeks.
Instructor: Farid
Introduction to Programming and Computation: Read Less [-]
Terms offered: Fall 2024, Fall 2023, Fall 2022 The ability to represent, manipulate, and analyze structured data sets is foundational to the modern practice of data science. This course introduces students to the fundamentals of data structures and data analysis (in Python). Best practices for writing code are emphasized throughout the course. This course forms the second half of a sequence that begins with INFO 106. It may also be taken as a stand-alone course by any student that has sufficient Python experience. Introduction to Data Structures and Analytics: Read More [+]
Prerequisites: INFO 206A or equivalent, or permission of instructor
Credit Restrictions: Course must be completed for a letter grade to fulfill degree requirements.
Formerly known as: Information 206
Introduction to Data Structures and Analytics: Read Less [-]
Terms offered: Fall 2024, Fall 2023, Fall 2022 This course will provide an introduction to the field of Human-Computer Interaction (HCI). Students will learn to apply design thinking to User Experience (UX) design, prototyping, & evaluation. The course will also cover special topic areas within HCI. Introduction to User Experience Design: Read More [+]
Introduction to User Experience Design: Read Less [-]
Terms offered: Spring 2024, Spring 2023, Spring 2022 This course addresses concepts and methods of user experience research, from understanding and identifying needs, to evaluating concepts and designs, to assessing the usability of products and solutions. We emphasize methods of collecting and interpreting qualitative data about user activities, working both individually and in teams, and translating them into design decisions. Students gain hands-on practice with observation, interview, survey , focus groups, and expert review. Team activities and group work are required during class and for most assignments. Additional topics include research in enterprise, consulting, and startup organizations, lean/agile techniques, mobile research approaches, and strategies for communicating findings. User Experience Research: Read More [+]
Additional Format: Three hours of Lecture per week for 15 weeks.
User Experience Research: Read Less [-]
Terms offered: Fall 2024, Fall 2023 This course will give participants hands-on digital product design experience oriented around current industry practice. The course will be project-based with an emphasis on iteration, practice, and critique. During the course, participants will work on a series of design projects through a full design process, including developing appropriate design deliverables, gathering feedback, and iterating on designs. Product Design Studio: Read More [+]
Objectives & Outcomes
Course Objectives: The course objective is to provide students interested in web and mobile Product Design with skills, practice, and experience that will prepare them for careers in product design and design-related roles.
Prerequisites: DES INV 15 or COMPSCI 160 or INFO 213 AND INFO 214; or permission of the instructor. Students can take INFO 214 and INFO 215 concurrently, but students may not drop INFO 214 and remain in INFO 215
Formerly known as: Information Systems and Management 215
Product Design Studio: Read Less [-]
Terms offered: Spring 2024, Fall 2021, Fall 2020 This course is a graduate-level introduction to HCI research. Students will learn to conduct original HCI research by reading and discussing research papers while collaborating on a semester-long research project. Each week the class will focus on a theme of HCI research and review foundational and cutting-edge research relevant to that theme. The class will focus on the following areas of HCI research: ubiquitous computing , social computing, critical theory, and human-AI interaction. In addition to these research topics the class will introduce common qualitative and quantitative methodologies in HCI research. Human-Computer Interaction (HCI) Research: Read More [+]
Instructor: Salehi
Human-Computer Interaction (HCI) Research: Read Less [-]
Terms offered: Spring 2024, Spring 2022, Spring 2020 As it's generally used, "information" is a collection of notions, rather than a single coherent concept. In this course, we'll examine conceptions of information based in information theory, philosophy, social science, economics, and history. Issues include: How compatible are these conceptions; can we talk about "information" in the abstract? What work do these various notions play in discussions of literacy, intellectual property, advertising, and the political process? And where does this leave "information studies" and "the information society"? Concepts of Information: Read More [+]
Prerequisites: Graduate standing
Instructors: Duguid, Nunberg
Concepts of Information: Read Less [-]
Terms offered: Fall 2024, Fall 2023, Fall 2021 This course focuses on the practice of leadership, collaboration, and people management in contemporary, distributed, information and technology-rich organizations. Not just for potential people managers, this course is derived from the premise that a foundation in leadership, management, and collaboration is essential for individuals in all roles, at any stage of their career. To build this foundation we will take a hybrid approach, engaging literature from disciplines such as social psychology, management, and organizational behavior, as well as leveraging case studies and practical exercises. The course will place a special emphasis on understanding and reacting to social dynamics in workplace hierarchies and teams. Leadership and Management: Read More [+]
Leadership and Management: Read Less [-]
Terms offered: Fall 2024, Spring 2013, Spring 2011 This class is for graduate students interested in getting an advanced understanding of judgments and decisions made with predictive algorithms. The course will survey the vast literature on the psychology of how people arrive at judgments and make decisions with the help of statistical information, focused mostly on experimental lab evidence from cognitive and social psychology. Then study the burgeoning evidence on how people use statistical algorithms in practice, exploring field evidence from a range of settings from criminal justice and healthcare to housing and labor markets. Special attention is paid to psychological principles that impact the effectiveness and fairness of algorithms deployed at scale. Decisions and Algorithms: Read More [+]
Course Objectives: Help students understand systematic human errors and explore potential algorithmic solutions.
Decisions and Algorithms: Read Less [-]
Terms offered: Spring 2024, Spring 2023, Spring 2022 Discusses application of social psychological theory and research to information technologies and systems; we focus on sociological social psychology, which largely focuses on group processes, networks, and interpersonal relationships. Information technologies considered include software systems used on the internet such as social networks, email, and social games, as well as specific hardware technologies such as mobile devices, computers , wearables, and virtual/augmented reality devices. We examine human communication practices, through the lens of different social psychology theories, including: symbolic interaction, identity theories, social exchange theory, status construction theory, and social networks and social structure theory. Social Psychology and Information Technology: Read More [+]
Instructor: Cheshire
Social Psychology and Information Technology: Read Less [-]
Terms offered: Spring 2024, Spring 2022, Spring 2021 This course applies economic tools and principles, including game theory, industrial organization, information economics, and behavioral economics, to analyze business strategies and public policy issues surrounding information technologies and IT industries. Topics include: economics of information goods, services, and platforms; economics of information and asymmetric information; economics of artificial intelligence, cybersecurity, data privacy, and peer production; strategic pricing; strategic complements and substitutes; competition and antitrust; Internet industry structure and regulation; network cascades, network formation, and network structure. Information Technology Economics, Strategy, and Policy: Read More [+]
Course Objectives: INFO234 is a graduate level course in the school's topical area of Information Economics and Policy, and can be taken by the masters and doctoral students to satisfy their respective degree requirements.
Student Learning Outcomes: Students will learn to identify, describe, and analyze business strategies and public policy issues of particular relevance to the information industry. Students will learn and apply economic tools and principles to analyze phenomena such as platform competition, social epidemics, and peer production, and current policy issues such as network neutrality and information privacy. Through integrated assignments and project work, the students will apply the theoretical concepts and analytic tools learned in lectures and readings to develop and evaluate a business model, product, or service of their choosing, e.g., a start-up idea they are pursuing.
Instructor: Chuang
Information Technology Economics, Strategy, and Policy: Read Less [-]
Terms offered: Fall 2021, Fall 2019, Fall 2018 The introduction of technology increasingly delegates responsibility to technical actors, often reducing traditional forms of transparency and challenging traditional methods for accountability. This course explores the interaction between technical design and values including: privacy, accessibility, fairness, and freedom of expression. We will draw on literature from design, science and technology studies, computer science, law, and ethics, as well as primary sources in policy, standards and source code. We will investigate approaches to identifying the value implications of technical designs and use methods and tools for intentionally building in values at the outset. Technology and Delegation: Read More [+]
Technology and Delegation: Read Less [-]
Terms offered: Fall 2024, Spring 2024, Fall 2022 This course introduces students to experimentation in data science. Particular attention is paid to the formation of causal questions, and the design and analysis of experiments to provide answers to these questions. This topic has increased considerably in importance since 1995, as researchers have learned to think creatively about how to generate data in more scientific ways, and developments in information technology has facilitated the development of better data gathering. Experiments and Causal Inference: Read More [+]
Experiments and Causal Inference: Read Less [-]
Terms offered: Spring 2023, Spring 2022, Spring 2021 The design and presentation of digital information. Use of graphics, animation, sound, visualization software, and hypermedia in presenting information to the user. Methods of presenting complex information to enhance comprehension and analysis. Incorporation of visualization techniques into human-computer interfaces. Course must be completed for a letter grade to fulfill degree requirements. Information Visualization and Presentation: Read More [+]
Prerequisites: INFO 206B or knowledge of programming and data structures with consent of instructor
Fall and/or spring: 15 weeks - 3 hours of lecture and 1 hour of laboratory per week
Additional Format: Three hours of lecture and one hour of laboratory per week.
Instructor: Hearst
Information Visualization and Presentation: Read Less [-]
Terms offered: Spring 2024, Spring 2023, Spring 2022 Provides a theoretical and practical introduction to modern techniques in applied machine learning. Covers key concepts in supervised and unsupervised machine learning, including the design of machine learning experiments, algorithms for prediction and inference, optimization, and evaluation. Students will learn functional, procedural, and statistical programming techniques for working with real-world data. Applied Machine Learning: Read More [+]
Student Learning Outcomes: • Effectively design, execute, and critique experimental and non-experimental methods from statistics, machine learning, and econometrics. • Implement basic algorithms on structured and unstructured data, and evaluate the performance of these algorithms on a variety of real-world datasets. • Understand the difference between causal and non-causal relationships, and which situations and methods are appropriate for both forms of analysis. • Understand the principles, advantages, and disadvantages of different algorithms for supervised and unsupervised machine learning.
Prerequisites: INFO 206B , or equivalent course in Python programming; INFO 271B , or equivalent graduate-level course in statistics or econometrics; or permission of instructor
Fall and/or spring: 15 weeks - 3 hours of lecture and 1 hour of discussion per week
Additional Format: Three hours of lecture and one hour of discussion per week.
Instructor: Blumenstock
Applied Machine Learning: Read Less [-]
Terms offered: Fall 2024, Fall 2023, Fall 2022 This course is a survey of technologies that power the user interfaces of web applications on a variety of devices today, including desktop, mobile, and tablet devices. This course will delve into some of the core Front-End languages and frameworks (HTML/CSS/JS/React/Redux), as well as the underlying technologies enable web applications (HTTP, URI, JSON). The goal of this course is to provide an overview of the technical issues surrounding user interfaces powered by the web today, and to provide a solid and comprehensive perspective of the Web's constantly evolving landscape. Front-End Web Architecture: Read More [+]
Prerequisites: Introductory programming
Fall and/or spring: 15 weeks - 2 hours of lecture and 1 hour of laboratory per week
Additional Format: Two hours of lecture and one hour of laboratory per week.
Formerly known as: Information 253
Front-End Web Architecture: Read Less [-]
Terms offered: Spring 2024, Spring 2023, Spring 2022 This course is a survey of web technologies that are used to build back-end systems that enable rich web applications. Utilizing technologies such as Python, Flask, Docker, RDBMS/NoSQL databases, and Spark, this class aims to cover the foundational concepts that drive the web today. This class focuses on building APIs using micro-services that power everything from content management systems to data engineering pipelines that provide insights by processing large amounts of data. The goal of this course is to provide an overview of the technical issues surrounding back-end systems today, and to provide a solid and comprehensive perspective of the web's constantly evolving landscape. Back-End Web Architecture: Read More [+]
Back-End Web Architecture: Read Less [-]
Terms offered: Spring 2024, Spring 2023 The course overviews a broad number of paradigms of privacy from a technical point of view. The course is designed to assist system engineers and information systems professionals in getting familiar with the subject of privacy engineering and train them in implementing those mechanisms. In addition, the course is designed to coach those professionals to critically think about the strengths and weaknesses of the different privacy paradigms. These skills are important for cybersecurity professionals and enable them to effectively incorporate privacy-awareness in the design phase of their products. Privacy Engineering: Read More [+]
Course Objectives: Critique the strengths and weaknesses of the different privacy paradigms Describe the different technical paradigms of privacy that are applicable for systems engineering Implement such privacy paradigms, and embed them in information systems during the design process and the implementation phase Stay updated about the state of the art in the field of privacy engineering
Credit Restrictions: Students will receive no credit for INFO 255 after completing INFO 255 . A deficient grade in INFO 255 may be removed by taking INFO 255 .
Privacy Engineering: Read Less [-]
Terms offered: Fall 2024, Fall 2023, Fall 2021 This course examines the use of natural language processing as a set of methods for exploring and reasoning about text as data, focusing especially on the applied side of NLP — using existing NLP methods and libraries in Python in new and creative ways. 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. Applied Natural Language Processing: Read More [+]
Prerequisites: INFO 206A and INFO 206B or proficient programming in Python (programs of at least 200 lines of code). Proficient with basic statistics and probabilities
Instructor: Bamman
Applied Natural Language Processing: Read Less [-]
Terms offered: Spring 2024, Fall 2022 This course will cover the principles and practices of managing data at scale, with a focus on use cases in data analysis and machine learning. We will cover the entire life cycle of data management and science, ranging from data preparation to exploration, visualization and analysis, to machine learning and collaboration, with a focus on ensuring reliable, scalable operationalization. ensuring reliable, scalable operationalization. Data Engineering: Read More [+]
Prerequisites: INFO 206B or equivalent college-level course in computer science in Python with a C- or better AND COMPSCI C100/ DATA C100 / STAT C100 or COMPSCI 189 or INFO 251 or DATA 144 or equivalent college-level course in data science with a C- or better
Instructors: Hellerstein, Parameswaran, Jain
Data Engineering: Read Less [-]
Terms offered: Spring 2024, Spring 2023, Spring 2022 This course introduces students to natural language processing and exposes them to the variety of methods available for reasoning about text in computational systems. NLP is deeply interdisciplinary, drawing on both linguistics and computer science, and helps drive much contemporary work in text analysis (as used in computational social science, the digital humanities, and computational journalism). We will focus on major algorithms used in NLP for various applications (part-of-speech tagging, parsing, coreference resolution, machine translation) and on the linguistic phenomena those algorithms attempt to model. Students will implement algorithms and create linguistically annotated data on which those algorithms depend. Natural Language Processing: Read More [+]
Prerequisites: Familiarity with data structures, algorithms, linear algebra, and probability
Natural Language Processing: Read Less [-]
Terms offered: Fall 2024, Fall 2023, Fall 2022 This course explores the theory and practice of Tangible User Interfaces, a new approach to Human Computer Interaction that focuses on the physical interaction with computational media. The topics covered in the course include theoretical framework, design examples, enabling technologies, and evaluation of Tangible User Interfaces. Students will design and develop experimental Tangible User Interfaces using physical computing prototyping tools and write a final project report. Theory and Practice of Tangible User Interfaces: Read More [+]
Instructor: Ryokai
Also listed as: NWMEDIA C262
Theory and Practice of Tangible User Interfaces: Read Less [-]
Terms offered: Spring 2024, Spring 2023, Spring 2022 This course will cover new interface metaphors beyond desktops (e.g., for mobile devices, computationally enhanced environments, tangible user interfaces) but will also cover visual design basics (e.g., color, layout, typography, iconography) so that we have systematic and critical understanding of aesthetically engaging interfaces. Students will get a hands-on learning experience on these topics through course projects, design critiques , and discussions, in addition to lectures and readings. Interface Aesthetics: Read More [+]
Also listed as: NWMEDIA C265
Interface Aesthetics: Read Less [-]
Terms offered: Fall 2024, Fall 2023, Fall 2022 Introduction to many different types of quantitative research methods, with an emphasis on linking quantitative statistical techniques to real-world research methods. Introductory and intermediate topics include: defining research problems, theory testing, casual inference, probability, and univariate statistics. Research design and methodology topics include: primary/secondary survey data analysis, experimental designs, and coding qualitative data for quantitative analysis. Quantitative Research Methods for Information Systems and Management: Read More [+]
Prerequisites: Introductory statistics recommended
Quantitative Research Methods for Information Systems and Management: Read Less [-]
Terms offered: Fall 2024, Fall 2023, Fall 2022 Theory and practice of naturalistic inquiry. Grounded theory. Ethnographic methods including interviews, focus groups, naturalistic observation. Case studies. Analysis of qualitative data. Issues of validity and generalizability in qualitative research. Qualitative Research Methods for Information Systems and Management: Read More [+]
Instructor: Burrell
Qualitative Research Methods for Information Systems and Management: Read Less [-]
Terms offered: Spring 2024, Spring 2023, Spring 2022 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. Information and Communications Technology for Development: Read More [+]
Fall and/or spring: 15 weeks - 3 hours of seminar per week
Additional Format: Three hours of seminar per week.
Instructor: Saxenian
Formerly known as: Information C283
Information and Communications Technology for Development: Read Less [-]
Terms offered: Spring 2024, Spring 2021, Spring 2019 As new sources of digital data proliferate in developing economies, there is the exciting possibility that such data could be used to benefit the world’s poor. Through a careful reading of recent research and through hands-on analysis of large-scale datasets, this course introduces students to the opportunities and challenges for data-intensive approaches to international development. Students should be prepared to dissect, discuss, and replicate academic publications from several fields including development economics, machine learning, information science, and computational social science. Students will also conduct original statistical and computational analysis of real-world data. Big Data and Development: Read More [+]
Prerequisites: Students are expected to have prior graduate training in machine learning, econometrics, or a related field
Big Data and Development: Read Less [-]
Terms offered: Fall 2024, Spring 2024, Fall 2023 This course provides students with real-world experience assisting politically vulnerable organizations and persons around the world to develop and implement sound cybersecurity practices. In the classroom, students study basic theories and practices of digital security, intricacies of protecting largely under-resourced organizations, and tools needed to manage risk in complex political, sociological, legal, and ethical contexts. In the clinic , students work in teams supervised by Clinic staff to provide direct cybersecurity assistance to civil society organizations. We emphasize pragmatic, workable solutions that take into account the unique needs of each partner organization. Public Interest Cybersecurity: The Citizen Clinic Practicum: Read More [+]
Repeat rules: Course may be repeated for credit with instructor consent.
Public Interest Cybersecurity: The Citizen Clinic Practicum: Read Less [-]
Terms offered: Fall 2024, Spring 2024, Fall 2023 Specific topics, hours, and credit may vary from section to section, year to year. Special Topics in Information: Read More [+]
Repeat rules: Course may be repeated for credit when topic changes. Students may enroll in multiple sections of this course within the same semester.
Fall and/or spring: 8 weeks - 2-8 hours of lecture per week 15 weeks - 1-4 hours of lecture per week
Summer: 10 weeks - 1.5-6 hours of lecture per week
Additional Format: One to four hours of lecture per week. One and one-half to six hours of lecture per week for 10 weeks. Two to eight hours of lecture per week for 8 weeks.
Special Topics in Information: Read Less [-]
Terms offered: Fall 2024, Spring 2024, Fall 2023 Specific topics, hours, and credit may vary from section to section and year to year. Special Topics in Management: Read More [+]
Additional Format: One to four hours of lecture per week. Two to eight hours of lecture per week for 8 weeks.
Special Topics in Management: Read Less [-]
Terms offered: Fall 2024, Fall 2023, Spring 2023 Specific topics, hours, and credit may vary from section to section and year to year. Special Topics in Social Science and Policy: Read More [+]
Fall and/or spring: 8 weeks - 4-8 hours of lecture per week 15 weeks - 2-4 hours of lecture per week
Additional Format: Two to four hours of lecture per week. Four to eight hours of lecture per week for 8 weeks.
Special Topics in Social Science and Policy: Read Less [-]
Terms offered: Spring 2024, Fall 2023, Spring 2023 Specific topics, hours, and credit may vary from section to section and year to year. Special Topics in Technology: Read More [+]
Special Topics in Technology: Read Less [-]
Terms offered: Prior to 2007 Specific topics, hours, and credit may vary from section to section, year to year. Special Topics in Information: Read More [+]
Repeat rules: Course may be repeated for credit when topic changes.
Fall and/or spring: 15 weeks - 1-4 hours of lecture per week
Additional Format: One to four hours of lecture per week.
Grading: Offered for satisfactory/unsatisfactory grade only.
Instructor: Hoofnagle
Terms offered: Fall 2016, Summer 2016 10 Week Session, Spring 2016 This course is designed to help School of Information graduate students maximize their internship, practicum, or independent research experiences. Information Management Practicum: Read More [+]
Course Objectives: Experience the practical application of your academic knowledge to real-world professional contexts; Gain insight into an organization and how one might make a valuable contribution; Reflect on the information the experience has provided, to see if it fits within one’s personal value set and work/life manifestos. Try out various professional activities to see when you are in ‘flow’;
Student Learning Outcomes: Assess the organizational culture of a company, governmental body, or non-governmental organization Connect academic knowledge about information management to real-world professional contexts Evaluate the effectiveness of a variety of information science techniques when deployed in organizational situations Integrate the student's own individual professional goals with the organization's needs relevant to the internship or practicum Reflect critically on the internship or practicum experience
Prerequisites: Consent of a Head Graduate Adviser for the School of Information
Repeat rules: Course may be repeated for credit without restriction.
Fall and/or spring: 15 weeks - 1 hour of internship per week
Summer: 10 weeks - 1.5 hours of internship per week
Additional Format: One hour of internship per week. One and one-half hours of internship per week for 10 weeks.
Information Management Practicum: Read Less [-]
Terms offered: Spring 2024, Spring 2023, Spring 2022 An intensive weekly discussion of current and ongoing research by Ph.D. students with a research interest in issues of information (social, legal, technical, theoretical, etc.). Our goal is to focus on critiquing research problems, theories, and methodologies from multiple perspectives so that we can produce high-quality, publishable work in the interdisciplinary area of information research. Circulated material may include dissertation chapters , qualifying papers, article drafts, and/or new project ideas. We want to have critical and productive discussion, but above all else we want to make our work better: more interesting, more accessible, more rigorous, more theoretically grounded, and more like the stuff we enjoy reading. Doctoral Research and Theory Workshop: Read More [+]
Prerequisites: PhD students only
Fall and/or spring: 15 weeks - 2 hours of workshop per week
Additional Format: Two hours of workshop per week.
Doctoral Research and Theory Workshop: Read Less [-]
Terms offered: Fall 2024, Fall 2023, Spring 2023 Colloquia, discussion and readings designed to introduce students to the range of interests of the school. Doctoral Colloquium: Read More [+]
Prerequisites: Ph.D. standing in the School of Information
Fall and/or spring: 15 weeks - 1 hour of colloquium per week
Additional Format: One hour of colloquium per week.
Doctoral Colloquium: Read Less [-]
Terms offered: Fall 2024, Spring 2024, Fall 2023 Topics in information management and systems and related fields. Specific topics vary from year to year. Seminar: Read More [+]
Prerequisites: Consent of instructor
Fall and/or spring: 15 weeks - 2-4 hours of seminar per week
Additional Format: Two to Four hours of Seminar per week for 15 weeks.
Seminar: Read Less [-]
Terms offered: Fall 2019, Spring 2016, Fall 2015 Group projects on special topics in information management and systems. Directed Group Study: Read More [+]
Credit Restrictions: Students will receive no credit for INFO 298 after completing INFOSYS 298.
Fall and/or spring: 15 weeks - 1-4 hours of directed group study per week
Summer: 8 weeks - 1.5-7.5 hours of directed group study per week
Additional Format: One to four hours of directed group study per week. One and one-half to seven and one-half hours of directed group study per week for 8 weeks.
Directed Group Study: Read Less [-]
Terms offered: Spring 2022, Spring 2016, Spring 2015 The final project is designed to integrate the skills and concepts learned during the Information School Master's program and helps prepare students to compete in the job market. It provides experience in formulating and carrying out a sustained, coherent, and significant course of work resulting in a tangible work product; in project management, in presenting work in both written and oral form; and, when appropriate, in working in a multidisciplinary team. Projects may take the form of research papers or professionally-oriented applied work. Directed Group Work on Final Project: Read More [+]
Prerequisites: Consent of instructor. Course must be taken for a letter grade to fulfill degree requirements
Additional Format: One to four hours of directed group study per week.
Directed Group Work on Final Project: Read Less [-]
Terms offered: Fall 2023, Summer 2016 8 Week Session, Spring 2016 Individual study of topics in information management and systems under faculty supervision. Individual Study: Read More [+]
Fall and/or spring: 15 weeks - 1-12 hours of independent study per week
Summer: 8 weeks - 2-22.5 hours of independent study per week
Additional Format: Format varies.
Individual Study: Read Less [-]
Terms offered: Spring 2024, Fall 2021, Fall 2020 Discussion, reading, preparation, and practical experience under faculty supervision in the teaching of specific topics within information management and systems. Does not count toward a degree. Teaching Assistance Practicum: Read More [+]
Fall and/or spring: 15 weeks - 2 hours of lecture per week
Additional Format: Two hours of lecture per week.
Subject/Course Level: Information/Professional course for teachers or prospective teachers
Instructor: Duguid
Teaching Assistance Practicum: Read Less [-]
School of information.
102 South Hall
Phone: 510-642-1464
Siu Yung Wong
Julia Sprague
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This program consists of six three-hour major courses:
In addition to the major, information systems doctoral students are required to choose a minor field (normally 3 to 4 courses, or 9 to 12 credit hours). Most students in this area choose minors such as organizational behavior, cognitive psychology, social psychology, and management. Students without prior teaching experience also take one short course ( X630 ) on teaching, prior to teaching their first course, which may be before or after the comprehensive exam.
All information systems doctoral students are required to take S600 in the first semester of the program. S600 is a prerequisite for the topics-based courses and provides the fundamental background in information systems. The topics-based courses are organized around major research topic areas in information systems research. The elective course could be another information systems major course, an independent study course, an IS-related course in another discipline, or a research methods course.
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General information.
The Department of Information Systems & Operations Management (ISOM) supports two areas for doctoral study: Information Systems (IS) and Operations Management (OM). Both areas are designed for persons seeking academic and research careers.
The area of Information Systems deals with the management of development, use, and impact of information systems and technologies in organizations. It is an interdisciplinary area, combining the study of information technologies and systems with other areas such as economics, operations research, decision theory, and psychology. Information systems have impact on all aspects of a modern organization — from providing solution to current problems to new business models and opportunities. With the rapid growth and globalization of businesses, information systems have taken on a more important role.
Department web site Information Systems Faculty
Applicants must have completed an undergraduate degree at an accredited university and should have a reasonable training in mathematics and economics. An admission committee of faculty members in the Information Systems & Operations Management Department reviews all completed applications. While the committee considers all relevant factors in its recommendations, important factors include past academic performance, GMAT scores (which are usually above 650 for successful applicants), and previous work experience. The GRE exam can be substituted for the GMAT but the GMAT is strongly preferred. In some cases we may request a personal interview.
It is assumed that students entering the information systems area are knowledgeable in advanced calculus, linear algebra, basic statistics, and a high level programming language. Any student who is deficient in these areas should consider taking appropriate coursework prior to entering the program.
Asst. Prof. Mingwen Yang, Information Systems Area Faculty Coordinator, would be glad to answer your questions. Contact her by email at [email protected] .
The Department’s Doctoral Review Committee will guide new students until they establish a Supervisory Committee. Students are required to establish a Supervisory Committee by the end of their first year. The Supervisory Committee assists the student in choosing appropriate courses, approves course of studies, and monitors the student’s progress.
The following courses are required for the IS major area. The number of credits for each course is indicated in parentheses after the course number.
I S 580 (4) | Advanced Research Topics in Information Systems I |
I S 581 (4) | Advanced Research Topics in Information Systems II |
I S 582 (4) | Advanced Research Topics in Information Systems III |
OPMGT 587 (4) | Advances Topics in Inventory Management |
OPMGT 590 (4) | Stochastic Models for Business |
QMETH 592 (4) | Stochastic Models: Queueing and Simulation |
I S 599 (1,1,1) | Doctoral Seminar |
All IS students must enroll in the doctoral seminar (IS 599) until all coursework is completed and the IS area examination is successfully completed; after this milestone, we strongly encourage all students to continue participating in the doctoral seminar.
Additionally, the following are strongly recommended courses for IS majors.
QMETH 580 (4) | Mathematical programming |
CSE 546 (4) | Machine Learning |
CSE 417 (4) | Natural Language Processing |
Research Methods Minor Area Requirements All students majoring in Information Systems must select Research Methods as one of their minor areas. The Research Methods area is designed to ensure that all students are knowledgeable with research tools needed to conduct high-level research in Information Systems.
The requirements below are viewed as minimal preparation for conducting doctoral level research; we strongly recommend that students expand their research methods area beyond the courses listed below. Certain substitutions of courses, upon approval from the chair of the supervisory committee may be allowed.
Microeconomics
ECON 500 (4) | Microeconomic Analysis I |
ECON 501 (4) | Microeconomic Analysis II |
ECON 508 (4) | Microeconomic Analysis III |
Econometrics
ECON 580 (4) | Econometrics I |
ECON 581 (4) | Econometrics II |
ECON 582 (4) | Econometrics III |
Other Minor Area Requirements In addition to Research Methods, IS students must select one additional minor area depending on the student’s interest. Possible minor areas include:
Assuming adequate background preparation, students are expected to complete the following coursework in their first and second years. The normal schedule is as follows but course offerings and quarter offerings might change depending on faculty availability.
Autumn | Winter | Spring | Summer |
ECON 500 Microeconomics I | ECON 501 Microeconomics II | ECON 508 Microeconomics III | Internship / Independent Research |
ECON 580 Econometrics I | ECON 581 Econometrics II | ECON 582 Econometrics III | |
OPMGT 590 Stochastic Model | QMETH 580 Math Programming | QMETH 592 Queuing Theory | |
IS 599 Doctoral Seminar | IS 599 Doctoral Seminar | IS 599 Doctoral Seminar | |
Teaching Effectiveness Seminar |
Second Year
Autumn | Winter | Spring | Summer |
IS 580 Ad. Research Topics I | IS 581 Ad. Research Topics II | IS 582 Ad. Research Topics III | Area Exam |
OPMGT 587 Topics in Inventory Management | Elective | Elective | Second year paper |
Elective | Elective | Elective | |
IS 599 Doctoral Seminar | IS 599 Doctoral Seminar | IS 599 Doctoral Seminar |
Students who select Information Systems as a minor area must take all three courses in Group I and two courses from Group II.
Group I. MBA level courses:
I S 545 (4) | Database Management |
I S 560 (4) | Information Systems Development |
I S 570 (4) | Business Data Communications |
If an MBA course in the above list is not offered, students may take a corresponding undergraduate course with permission.
Group II. Doctoral level courses:
IS 580 (4) | Advanced Research Topics I |
IS 581 (4) | Advanced Research Topics II |
IS 582 (4) | Finance Research Workshop |
Written Area or Qualifying Examination After completing all coursework in his or her major area, each student will take a written area examination consisting of questions contributed by all appropriate area faculty and administered by the chair of the student’s Supervisory Committee. The exam is graded on a high pass, pass, low pass, or fail basis; if appropriate, the departmental faculty members in the Supervisory Committee may require additional work and/or classes as a condition for passing the exam. If the student fails the exam, he or she can take the exam one additional time after satisfying deficiencies.
Second Year Paper At the end of the second year, in order to demonstrate competency and ability to conduct research in IS, each student is required to write a paper. The work is to be supervised by the chair of the student’s Supervisory Committee and then graded by the departmental faculty members in the student’s Supervisory Committee on a high pass, pass, low pass, or fail basis. The departmental faculty members in the Supervisory Committee may require additional work as a condition for passing the paper.
General Examination After successfully completing the written area exam, each student takes a general (oral) examination. Members of the Supervisory Committee which includes a representative of the Graduate School and any other interested faculty and students, administer this examination. Typically, this exam involves a defense of the student’s dissertation proposal; however, the chair of the Supervisory Committee determines the precise format of the general exam.
Dissertation After successfully completing the general examination, the student is admitted to Candidacy and continues work on his/her dissertation research. A Reading Committee guides the student in working with the dissertation. It is also expected that the student will present his or her research to the Information Systems and Operations Management Department at the doctoral seminar.
Final Examination When the dissertation is completed, the Supervisory Committee administers a final defense of the dissertation.
Current Ph.D. faculty research programs span a wide range of technology management topics. Examples include:
Our doctoral students work with faculty members on many intriguing topics. Here are some research projects involving faculty and either current Ph.D. students or graduates:
“Understanding User Participation in Crowdsourced Mobile Apps: A Geo-Spatial Analysis” ( Tae Hun Kim, graduated 2018 ) “Dynamics of Online Word of Mouth Spillover Effects” ( Yen-Yao Wang, graduated 2017 ) “The Effect of Mergers and Acquisitions on Firm Performance: Evidence from Digital Industries” ( Kangkang Qi, graduated 2016 ) “Community Engagement and Collective Evaluation in Crowdfunding” ( Eun Ju Jung, graduated 2015 ) “A Process Theory of Technology Trust Change” ( Peng Liu, graduated 2013 ) “Technology, Humanness and Trust: Rethinking Trust in Technology” ( John Tripp, graduated 2012 ) “The (N)Ever-Changing World: Stability and Change in Organizational Routines” ( Derek Hillison, graduated 2009 ) “How Peripheral Developers Contribute to Open-Source Software Development” ( Pankaj Setia, graduated 2008 ) “Team Documentation Influences Clinic Complexity and Patient Satisfaction” ( Inkyu Kim and Dr. Brian Pentland )
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PhD in IS Program Flyer Meet Current Students Explore FAQs
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The Information Systems (IS) doctoral program is a research-based program where students work with world-renowned scholars to build skills that will prepare them for impactful careers as professors in information systems at business schools.
Overall, the doctoral program places a heavy emphasis on training students through active engagement in the research process. Students develop a strong foundation in research methods and statistics, while closely collaborating with multiple faculty members on research projects.
General details about the curriculum, requirements, and structure of the program can be found here . Please be aware this document is not an exhaustive list of the requirements for the program.
Program Faculty
Our renowned, award-winning IS faculty are published experts on topics like:
Artificial Intelligence and Deep Learning
Cybersecurity, Text Analytics and Face Recognition
Emerging Digital Technologies
Large Language Models (LLMs)
Machine Learning and Semantic/Lexical Analytics
Natural Language Processing
Tools and Methods for Making Sense of Large Data
Tandean Rustandy Esteemed Endowed Chair
Assistant Professor
Associate Professor
Assistant Professor • Information Analytics PhD Program Director
Program Graduates
The PhD program prepares students to be researchers and teachers at major universities. See where our graduates started their careers and published research.
Management Information Systems Quarterly ( WITS 2016 Best Prototype Award ) Unlocking Knowledge Inheritance of Behavioral Research: A Design Framework and an Instantiation (Conditional acceptance) Jingjing Li—University of Virginia (PhD 2013) Kai Larsen –University of Colorado Boulder Ahmed Abbasi –University of Virginia
Information Systems Research Don’t Mention It? Analyzing User-generated Content Signals for Early Adverse Event Warnings (2019) Ahmed Abbasi –University of Virginia Jingjing Li—University of Virginia (PhD 2013) Donald Adjeroh –West Virginia University Marie Abate—West Virginia University Wanhong Zheng –West Virginia University
MIS Quarterly Information technology use as a learning mechanism: The impact of it use on knowledge transfer effectiveness, absorptive capacity, and franchisee performance (2015) Kishen Iyengar - University of Colorado at Boulder Jeffrey R Sweeney - Maastricht University (PhD 2016) Ramiro Montealegre - University of Colorado at Boulder
MIS Quarterly Can online wait be managed? The effect of filler interfaces and presentation modes on perceived waiting time online (2012) Younghwa Lee - University of Northern Iowa (PhD 2005) Andrew N.K. Chen - University of Kansas Virgina Ilie - California Luthern University
Learn more about
Research requirements
Teaching Requirements
PhD Research Topics in Information Technology is our prime research service. Moreover, we will offer ‘ top grade guidance’ for all future PhD/MS scholars. We also help you to achieve greater heights in your career by considering all the things.
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An effective process of Memory Leakage-Resilient Dynamic and Verifiable Multi-keyword Ranked Search based on Encrypted Smart BSND merthod
A framework process of Intelligent Home Security Monitoring System Based on Android system
An original mechanism for Dynamic Degenerative Neural Network used Classification of Images by Live Network Data
An inventive process of Deep Abstraction and Weighted Feature Selection intended for Wi-Fi Impersonation Detection
An effeicent mechanism for Anomaly Detection of Cyber Physical Network Data used by 2D Images
An inventive research mechanism for Data Fusion based on Predicting Novel Activity in Enterprise Cyber-Security system
An effectual functkion of Detecting Hidden User Behavior for Network Data Stream method
The novel technology for Rapid Malware Analysis and Reverse Engineering by Visual Analytics
An effective mechanism for Identification of heavy hitters for network data streams with probabilistic sketch scheme
An kinnovative technique for Detection of super nodes based on connection metrics for network data streams
A fresh competent process of fast multi-pattern matching algorithm for mining big network data
A design and development of new research based LoRa network for cities Private and complete secured by information system
A novel technology for Attacker Behavior-Based Metric for Security Monitoring Applied to Darknet Analysis scheme
Design methodology function of Security Analytics forWBAN/WLAN Healthcare Network
An effective mechanism for Evaluation and Cluster Analysis of E-Businesses with Perishable Products and Cold Supply Chain
An innovative function of Security in Modern Smart Cities by Information Technology Perspective
Design a new methodology of Application in Natural Language Processing in Machine Translation method
An effective process of Enhancing Cloud-Based on IoT Security through Trustworthy Cloud Service
An effective function of Integrated Cloud Storage based on Paperless Thesis Examination by information technology
Effectual process of Research for Security Situational Awareness and Visualization Approach in Cloud Computing
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We associated with 200+reputed SCI and SCOPUS indexed journals (SJR ranking) for getting research work to be published in standard journals (Your first-choice journal).
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The objectives of the PhD specialization in Information Systems (IS) are to promote theoretical and applied research on topics related to information systems practice with a combined focus on scientific rigour and relevance.
Faculty in the IS Area conduct research on diverse topics including the business value and impacts of information technology, managing resistance to information systems implementation, Coordination in fast response organizations, Knowledge management, management of information security, predictive analytics, adoption and impact of healthcare IT, online search and advertising, and social media, by using a variety of methodologies. IS faculty members are funded by external agencies and also enjoy a fruitful working relationship with the business community that provides a rich environment for field research.
Fall semester
INSY 704 Organizational Impacts of Information Technology MGSC 706 Management Research Statistics ECON 662 Econometrics I
Winter semester
INSY 706 IT Acceptance and Usage MGMT 709 Designing for Causal Inference ECON 663 Econometrics II
INSY 709 IT & Digital Economy INSY 705 Seminar in IS - AI Applications in Information Systems Elective
INSY 705 Seminar in IS - Decision Making with IT EDPH 689 Teaching and Learning in Higher Education Elective
MGPO 704 Organizational Theory Seminar MGPO 705 Seminar in Policy MGPO 706 Perspectives on Innovation ORGB 708 Social Network Analysis for Social Science Research POLI 666 Causal Inference for Political Science ECON 706 Selected Topics ECON 742 Empirical Microeconomics MPHE 742 HEC80774411 Theory Building MPHE 743 HEC80109A Textual Analysis and Psychophysiological Measures MPHE 745 HEC80-724A Research Methods IT MPHE 746 HEC8062917A Machine Learning I: Large-Scale Data Analysis and Decision Making
Phd thesis defense presentation:, related content.
Prof. Taha Havakhor Information Systems Area PhD Representative
Desautels faculty of management mcgill university.
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An active and collegial group of senior and junior academics is the distinguishing feature of the MIS faculty at UBC. These researchers investigate a wide variety of topics, including electronic commerce, economics of information systems, systems analysis, intelligent systems, strategic and organizational issues, and planning for MIS. Their methods include laboratory experiments, field studies, survey methods, econometrics, conceptual modelling, and computational simulation. This rich portfolio of topics and research methods allows substantial flexibility for our PhD students in selecting a research topic.
For specific program requirements, please refer to the departmental program website
The PhD Program in MIS in terms of its reputation, research record and research grants received, stands at the top of Canadian business schools and at the very top rank in the international arena. A recent assessment of research productivity showed that the UBC MIS program ranks 6th in the world among public universities, and 9th overall, in terms of publications in top MIS journals.
Program enquiries, admission information & requirements, 1) check eligibility, minimum academic requirements.
The Faculty of Graduate and Postdoctoral Studies establishes the minimum admission requirements common to all applicants, usually a minimum overall average in the B+ range (76% at UBC). The graduate program that you are applying to may have additional requirements. Please review the specific requirements for applicants with credentials from institutions in:
Each program may set higher academic minimum requirements. Please review the program website carefully to understand the program requirements. Meeting the minimum requirements does not guarantee admission as it is a competitive process.
Applicants from a university outside Canada in which English is not the primary language of instruction must provide results of an English language proficiency examination as part of their application. Tests must have been taken within the last 24 months at the time of submission of your application.
Minimum requirements for the two most common English language proficiency tests to apply to this program are listed below:
Overall score requirement : 100
Overall score requirement : 7.0
Some programs require additional test scores such as the Graduate Record Examination (GRE) or the Graduate Management Test (GMAT). The requirements for this program are:
The GRE or a comparable test is required. Please check the program website.
September 2025 intake, application open date, canadian applicants, international applicants, deadline explanations.
Deadline to submit online application. No changes can be made to the application after submission.
Deadline to upload scans of official transcripts through the applicant portal in support of a submitted application. Information for accessing the applicant portal will be provided after submitting an online application for admission.
Deadline for the referees identified in the application for admission to submit references. See Letters of Reference for more information.
Transcripts.
All applicants have to submit transcripts from all past post-secondary study. Document submission requirements depend on whether your institution of study is within Canada or outside of Canada.
A minimum of three references are required for application to graduate programs at UBC. References should be requested from individuals who are prepared to provide a report on your academic ability and qualifications.
Many programs require a statement of interest , sometimes called a "statement of intent", "description of research interests" or something similar.
Students in research-based programs usually require a faculty member to function as their thesis supervisor. Please follow the instructions provided by each program whether applicants should contact faculty members.
Citizenship verification.
Permanent Residents of Canada must provide a clear photocopy of both sides of the Permanent Resident card.
All applicants must complete an online application form and pay the application fee to be considered for admission to UBC.
Fees | Canadian Citizen / Permanent Resident / Refugee / Diplomat | International |
---|---|---|
$114.00 | $168.25 | |
Tuition * | ||
Installments per year | 3 | 3 |
Tuition | $1,838.57 | $3,230.06 |
Tuition (plus annual increase, usually 2%-5%) | $5,515.71 | $9,690.18 |
Int. Tuition Award (ITA) per year ( ) | $3,200.00 (-) | |
Other Fees and Costs | ||
(yearly) | $1,116.60 (approx.) | |
Estimate your with our interactive tool in order to start developing a financial plan for your graduate studies. |
Applicants to UBC have access to a variety of funding options, including merit-based (i.e. based on your academic performance) and need-based (i.e. based on your financial situation) opportunities.
We provide a financial package that includes tuition plus $30,000 per year for the first five years of the PhD Program.
All applicants are encouraged to review the awards listing to identify potential opportunities to fund their graduate education. The database lists merit-based scholarships and awards and allows for filtering by various criteria, such as domestic vs. international or degree level.
Many professors are able to provide Research Assistantships (GRA) from their research grants to support full-time graduate students studying under their supervision. The duties constitute part of the student's graduate degree requirements. A Graduate Research Assistantship is considered a form of fellowship for a period of graduate study and is therefore not covered by a collective agreement. Stipends vary widely, and are dependent on the field of study and the type of research grant from which the assistantship is being funded.
Graduate programs may have Teaching Assistantships available for registered full-time graduate students. Full teaching assistantships involve 12 hours work per week in preparation, lecturing, or laboratory instruction although many graduate programs offer partial TA appointments at less than 12 hours per week. Teaching assistantship rates are set by collective bargaining between the University and the Teaching Assistants' Union .
Academic Assistantships are employment opportunities to perform work that is relevant to the university or to an individual faculty member, but not to support the student’s graduate research and thesis. Wages are considered regular earnings and when paid monthly, include vacation pay.
Canadian and US applicants may qualify for governmental loans to finance their studies. Please review eligibility and types of loans .
All students may be able to access private sector or bank loans.
Many foreign governments provide support to their citizens in pursuing education abroad. International applicants should check the various governmental resources in their home country, such as the Department of Education, for available scholarships.
The possibility to pursue work to supplement income may depend on the demands the program has on students. It should be carefully weighed if work leads to prolonged program durations or whether work placements can be meaningfully embedded into a program.
International students enrolled as full-time students with a valid study permit can work on campus for unlimited hours and work off-campus for no more than 20 hours a week.
A good starting point to explore student jobs is the UBC Work Learn program or a Co-Op placement .
Students with taxable income in Canada may be able to claim federal or provincial tax credits.
Canadian residents with RRSP accounts may be able to use the Lifelong Learning Plan (LLP) which allows students to withdraw amounts from their registered retirement savings plan (RRSPs) to finance full-time training or education for themselves or their partner.
Please review Filing taxes in Canada on the student services website for more information.
Applicants have access to the cost estimator to develop a financial plan that takes into account various income sources and expenses.
102 students graduated between 2005 and 2013. Of these, career information was obtained for 100 alumni (based on research conducted between Feb-May 2016):
Sample employers outside higher education, sample job titles outside higher education, phd career outcome survey, career options.
Our graduates have academic positions in Canada, the USA, Asia, and Europe. Students in our program work closely with faculty and other students in a stimulating intellectual environment to create outstanding research.
Job Title Assistant professor
Employer Kuwait University
These statistics show data for the Doctor of Philosophy in Business Administration in Management Information Systems (PhD). Data are separated for each degree program combination. You may view data for other degree options in the respective program profile.
2023 | 2022 | 2021 | 2020 | 2019 | |
---|---|---|---|---|---|
Applications | 27 | 26 | 36 | 30 | 26 |
Offers | 2 | 0 | 1 | 5 | 3 |
New Registrations | 2 | 0 | 1 | 3 | 1 |
Total Enrolment | 7 | 6 | 7 | 6 | 7 |
This list shows faculty members with full supervisory privileges who are affiliated with this program. It is not a comprehensive list of all potential supervisors as faculty from other programs or faculty members without full supervisory privileges can request approvals to supervise graduate students in this program.
Year | Citation |
---|---|
2016 | Dr. Saghafi studied business information modelling. He investigated approaches that could improve the performance of users in business analytics, and enhance their overall understanding of the application requirements. His research has important implications for both researchers and practitioners in the area of information systems development. |
Same academic unit.
Specialization.
Management Information Systems covers information on systems analysis, databases, telecommunications, electronic commerce, economics of information systems, intelligent systems, strategic and organizational issues, and planning for MIS.
Program website, faculty overview, academic unit, program identifier, classification, social media channels, supervisor search.
Departments/Programs may update graduate degree program details through the Faculty & Staff portal. To update contact details for application inquiries, please use this form .
Here, you can choose from more than 300 graduate degree program options and 2000+ research supervisors. You can even design your own program.
If you are interested in pursuing a PhD with the School of Information Systems and Technology Management (UNSW Business), then you will need to receive an Invitation to Apply from the school’s Postgraduate Research Coordinator in charge of Admissions ( Dr. Eric Lim ).
To receive an Invitation to Apply, you should 1) self-assess your eligibility, and 2) then submit an Expression of Interest (EOI) . Details of what to include in your EOI can be found here .
UNSW’s Doctor of Philosophy (PhD) Information Systems & Technology Management (Program code 1525) will prepare you to become a globally focused and socially engaged research leader. You’ll join a cohort of high-achieving research students and benefit from interdisciplinary engagement with your cohort. This is your opportunity to become integrated into the UNSW Business School’s community of scholars.
You’ll first undertake rigorous coursework covering research methods and theoretical foundations of information systems and operations management. As part of the program, you’ll also be involved in research projects from an early stage. This research training will equip you with the skills required to identify, analyse and solve problems in the field.
You’ll then pursue full-time research under the supervision of high-profile UNSW academics, culminating in a doctoral thesis. There will also be exciting opportunities to develop your teaching portfolio. There will also be exciting opportunities throughout to interact with industry leaders. The training is geared toward preparing you for a career in academia, although other career paths (e.g., consulting, government, industry, non-profit) are also enabled.
Your PhD thesis will showcase your research skills and enable you to make an original contribution to knowledge in your field.
Year one: master of pre-doctoral business studies (mpdbs).
The first year of study is designed to provide a rigorous foundation to conduct independent research. You’ll learn a range of methodologies and build your communication and presentation skills.
Your first year of coursework study will cover fundamental qualitative and quantitative research methods. You’ll also start developing key research skills such as identifying, framing, presenting, and writing academic contributions. You’ll work as a research assistant on faculty research projects and start working on your own research as your skills develop.
The first year will help you identify your potential thesis supervisor for the PhD component of the program. Upon successful completion of the first year, you’ll be awarded a Master of Pre-Doctoral Business Studies. A brief overview of the first year is presented below. Please visit the UNSW Handbook for full course structure details.
During the second year, you’ll continue in the Information Systems & Technology Management stream with a further year of advanced coursework.
You’ll choose up to eight additional research courses from a range of electives in consultation with your supervisor and PGRC, with an opportunity to take several courses outside of your specialised discipline to prepare you for interdisciplinary collaborations.
Your second year is also when you’ll identify your thesis topic with your supervisor. You’ll engage in literature review and research design, and present your research proposal to the School at the end of the year.
The final two years of the program are focused on conducting full-time research and completing your doctoral thesis. This is your opportunity to address some of the biggest challenges in Information Systems & Technology Management and make a significant contribution to knowledge in your field. Your research will offer new critical thinking and withstand critical analysis from expert researchers in the area.
As with most other OECD countries, the number of PhD completions in Australia has grown dramatically – more than doubling in the last two decades.
An increasing number of PhD graduates find employment in business, government, and the non-profit sector. Nineteen of the largest ASX companies have PhD graduates on their senior executive teams.
Your PhD thesis will set you on the path to a career in a premier research institution, anywhere in the world. Throughout your research degree, you’ll also have many opportunities to develop your teaching portfolio.
Beyond academia, there is also significant demand in the private and public sectors for people with deep knowledge and sound research and analytical skills*.
Whether you’re looking to pursue a career in academia, or take your research skills out to industry, a PhD in Information Systems & Technology Management from UNSW will get you there.
* Source: 2019 Advancing Australia’s Knowledge Economy Report
Postgraduate Research
4 years full-time, 5-8 years part-time
Term 1 – February
Delivery mode, domestic / international.
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As the name depicts, information systems dissertation topics revolve around the information technology sphere of organizations and industries. Information systems research topics include both primary as well as secondary levels of research studies and their complexities differ in accordance with the academic and degree levels at hand.. Other Related Post
The program offers a Ph.D. in Business with an Information Systems and Technology Management (ISTM) Area of Focus, which explores diverse research topics in information systems and digital transformation. The program requires 45 credits and can be completed in four to five years, with a summer research paper and a dissertation.
Learn how to apply for the doctoral program in information systems at NYU Stern, which offers tracks in technical, economic, and organizational perspectives. The program requires 3-4 years of coursework, research apprenticeship, and thesis writing.
Information Systems Research Topic ideas for MS, or Ph.D. Degree. I am sharing with you some of the research topics regarding Information Systems that you can choose for your research proposal for the thesis work of MS, or Ph.D. Degree.
First- and second-year Research Papers meeting current Ph.D. requirements; Dissertation focused on Information Systems topic as per judgment of Ph.D. committee; While fulfilling these requirements, you'll work closely with the faculty to develop individualized programs of study and research that meet your goals.
W. P. Carey faculty and PhD students present their research at leading national and international conferences, and publishing academic journals. Research topics include: Business analytics/big data ... Social media/e-commerce and mobile platforms; In addition to information systems, our PhD students are often published by leading journals in ...
Learn about the PhD program in Information Systems at the Naveen Jindal School of Management, ranked #1 worldwide in research based on publications in three journals. The program prepares students for academic or industry careers in information systems research and teaching.
Learn how to become a researcher and scholar in information systems and technologies at Baylor University. The program offers four years of funding, diverse faculty and student backgrounds, and a STEM-designated degree.
The Information Systems and Technology Management (ISTM) program investigates behavioral, design, and economic issues related to the use and impact of information technology. ... Katz offers a breadth of research topics-many students can find a home here. Recent PhD dissertation topics have included e-commerce, online communities, project ...
We've taken a few ideas of the information technology topics for research paper off the surface, but we think you'll find a starting point for your subject matter here. Resourceful List of Ideas for PhD in Information Technology. In this resourceful list, information systems research topics touch on various areas.
Learn about the PhD program in Information Systems at Simon Business School, which focuses on the business aspects of IT use and management, and the analytic and quantitative tools to address them. The program requires courses, papers, exams, and a dissertation in the first three years.
Learn about the research-oriented PhD program in Information Science at UC Berkeley, which covers various fields of specialization and requires original dissertation research. Find out the admission requirements, program design, breadth and major/minor courses, and faculty contact information.
All information systems doctoral students are required to take S600 in the first semester of the program. S600 is a prerequisite for the topics-based courses and provides the fundamental background in information systems. The topics-based courses are organized around major research topic areas in information systems research.
Learn about the interdisciplinary area of Information Systems (IS) at the Foster School of Business, which deals with the management of development, use, and impact of information systems and technologies in organizations. Find out the admission requirements, course requirements, and faculty coordinator for the IS PhD program.
Learn about the PhD program in Management Information Systems at the University of Georgia, a top-ranked and internationally renowned department. The program prepares future academics with a problem-focused, theory-based, and method-inclusive approach to research.
Learn about the current and past research programs of Ph.D. faculty and students in IT management at MSU Broad. Explore topics such as analytics, adoption, trust, IT capabilities, and more.
Browse the list of graduate theses and dissertations from the Information Systems department at the University of Arkansas, Fayetteville. Find research topics, authors, and publication years from 2011 to 2023.
Learn how to become a researcher and teacher in information systems at business schools with a PhD from the Leeds School of Business. Explore the curriculum, faculty, program graduates, and placements of this research-based program.
One of the oldest Information Systems (IS) PhD programs in the world, the PhD in MIS is a four-to-five-year program consistently ranked among the best IS PhD programs globally. It provides flexibility to pursue individual research interests while ensuring a strong foundation in conceptual and methodological skills.
Get to know about latest interesting PhD research topics in information technology. Research Topics FAQ Contact +91 94448 29042 [email protected]. Menu Home. Logo/Motto; Confidential; Trust; Proposal; ... A design and development of new research based LoRa network for cities Private and complete secured by information system.
The objectives of the PhD specialization in Information Systems (IS) are to promote theoretical and applied research on topics related to information systems practice with a combined focus on scientific rigour and relevance. Faculty in the IS Area conduct research on diverse topics including the business value and impacts of information technology, managing resistance to information systems ...
An active and collegial group of senior and junior academics is the distinguishing feature of the MIS faculty at UBC. These researchers investigate a wide variety of topics, including electronic commerce, economics of information systems, systems analysis, intelligent systems, strategic and organizational issues, and planning for MIS. Their methods include laboratory experiments, field studies ...
How to apply. If you are interested in pursuing a PhD with the School of Information Systems and Technology Management (UNSW Business), then you will need to receive an Invitation to Apply from the school's Postgraduate Research Coordinator in charge of Admissions (Dr. Eric Lim).. To receive an Invitation to Apply, you should 1) self-assess your eligibility, and 2) then submit an Expression ...