Who We Are
From the Dean
Know the Libraries
This course is for prospective Purdue undergraduate researchers who are
interested in conducting undergraduate research or creative endeavors. Purdue
students who have not already started an independent research project with a
research mentor will learn valuable skills to market themselves to individuals
and research programs. Throughout the course, students will develop components
for a final application packet to submit to a research team or program they
This course provides an introduction to Ethical, Legal Social Issues (ELSI) in
Data Science. Students will be introduced to interdisciplinary theoretical and
practical frameworks that can aid in exploring the impact and role of Data
Science in society. This is a writing intensive course. Students will work
individually and on collaborative assignments.
This course is for current Purdue undergraduate researchers to hone skills
necessary for successfully reflecting on and completing the experience. During
this course, students will utilize their research experience to apply skills
such as managing time with a research project, communicating your research,
utilizing Purdue Libraries' resources, and providing feedback to peer
researchers. Students will deliver research pitches about their own project
and provide critiques to others’ pitches.
This course examines concepts of trust and authority and uses them to promote
critical thinking and assessments regarding credibility. Authoritative
information sources, evaluative criteria, and technical tools will be
enumerated and discussed as students work through a research issue of personal
interest. Topics include: what is trust and why is it significant, what types
of authority exist and what specifically is cognitive authority, how is
in-person trust and authority different from digital trust, when does
credibility matter and what are criteria for determining credibility, how and
where is quality information found, techniques of the nefarious (cons, scams,
spam, phishing etc.), considerations of a skeptical consumer (research
project). This course is designed to help lower-level undergraduate students
think deeply about trust, authority, evaluation, and quality, topics that they
may not have consciously considered or studied previously.
This course is for current Purdue undergraduate researchers to build upon the
previous course and focus on research data collection, presentation, and
communication for current Purdue undergraduate researchers. During this
course, students will learn and discuss various forms of data and collection
practices. Students will develop their own academic poster to present their
research project's data and implications. Students are encouraged to present
their poster at one of Purdue’s undergraduate research conferences near the
end of the semester.
We live in a technologically complex time, a time in which our access to and
experience with technology has dramatic effects on our lifeworld. Digital
cultural studies is an interdisciplinary and creative approach to
understanding, theorizing, building, and critiquing the human experience of
technology. In this course, students will encounter the theories, topics, and
artifacts that constellate our technological world, including films, books,
art, scholarship, media artifacts, games, social media, interfaces, and
platforms. Students will think critically about a variety of topics, engage in
thoughtful discussions, respond creatively, and build original projects.
Any time information is used for a particular means conflict is inevitable.
This seminar course examines historical and current societal issues and
challenges related to the consumption and production of information. The
course delves into how the use and misuse of information has resulted in
historical and contemporary challenges, including ethical concerns in the
dissemination of science, technology, engineering and mathematics (STEM)
information, the capturing and sharing of surveillance and privacy
information, the creation and sharing of disinformation and ‘fake’ news, and
information on social media that takes on a life of its own (i.e., going
viral). New issues will be examined weekly and students will be able to
introduce topics of interest as well. The cumulative final project will allow
students to select and explore their own topics on an evolving information
practice and its influence on culture or society.
This course is for current Purdue undergraduate researchers to build on
previous courses and focus on continuing their education in graduate or
professional school. During this course, students will learn and discuss the
various phases of identifying, selecting, applying to and funding graduate or
professional school programs. Students will also gain a deeper comprehension
of the qualities and skills that make research mentors effective while
developing skills they will need to be successful mentees and peer mentors.
Students will conduct research to identify potential programs of interest and
develop a statement of purpose.
So you want to go to medical school or veterinary school, or become a
chiropractor, dentist, public health specialist, osteopath, occupational
therapist, physical therapist, physician’s assistant, or get a PhD and do
clinical research. Take this course to develop critical information skills to
support your professional goals and prepare you for graduate or professional
school. Show up on day one of professional or graduate school knowing how to
navigate PubMed and other databases, differentiate between various types of
research articles, and save and organize articles so you can easily locate
them, “cite while you write,” and share articles with your classmates or
Intensive study of selected topics varying from semester to semester, from the
practice of information and data sciences. Topics may include data management
and organization, digital scholarship, data visualization, computer languages
for data and information science, information literacy, archival literacy, and
emerging trends in information and data science. Permission of the instructor
is required for undergraduates.
This course focuses on information strategies for successful research in science, engineering, and technology disciplines. Students will learn about how scholarly information and discipline relevant grey literature (e.g., patents, technical standards) are created, organized, disseminated, retrieved, and managed. In addition, students will learn strategies to critically evaluate information and present their research effectively and ethically.
This course is designed to help you learn fundamental Python programming
concepts, get introduced to the Python scripting environment within ArcGIS
Pro, perform data visualization and advanced analytical skills using Python
libraries for GIS and spatial data science, automate GIS tasks, learn to use
version control with Git and practice basics of sharing code using GitHub.
These topics will be taught in the context of solving geoscientific problems.
The course consists of readings, quizzes, and laboratory exercises about
programming concepts and techniques and a final term project. You will be
encouraged to research concepts, examples, and content from online resources
such as esri.com, stack overflow, GIS StackExchange, etc.
Emphasizes the importance and role of strong information and communication
skills (written, oral, graphical, and interpersonal) in a successful
engineering or technology career. Search, evaluate, access, use, and
synthesize technical information in order to present information clearly,
ethically, and effectively in a variety of professional formats.
This course offers an interdisciplinary introduction to data management and
curation with a focus on the use, value, and organization of data, materials,
infrastructure, tools, and scholarly communication in qualitative research.
The course will introduce literature concerning ethical and legal
considerations of data management and curation, and will provide opportunity
for hands-on digital, data literacy, and data manipulation skills development.
Computational analysis of textual data has become increasingly important in
the world of digital humanities, digital history, data science, and
computational social science. This course provides an introduction to the
methods, debates, controversies, and tools of computational text analysis
(CTA) specifically crafted for the humanities and social science graduate
student. Students will explore the central theoretical debates in CTA while
also learning practical hands-on skills in corpus creation, OCR, text mining,
topic modeling, sentiment analysis, and other methods. They will learn how CTA
relates to established interpretative practices in the larger histories of the
humanities and social sciences and the broader context of their own
disciplines, and will consider both the possibilities and the limitations of
CTA in their own work. While the course is designed for a beginner with little
technical training, students will become familiar with the basic elements of
coding/scripting using the programming language R and other tools. Upon
completion of this course, students will understand the challenges of CTA, be
conversant with major theoretical discussions around CTA, and have a
foundational understanding of the steps required to incorporate CTA into their
regular research practices and particular projects.
This course walks students through the process of preparing a dataset for
sharing with both internal and external audiences. Students wil select
authoritative datasets for sharing and publication, apply metadata to those
datasets, create documentation for end-users of the datasets, and publish the
datasets to internal or external data repositories or storage as appropriate.