Description

Introduces concepts of the management of data throughout its lifecycle. Understanding different types of data and their functions. Managing data in the context of a particular discipline or profession. Finding and evaluating data purposefully. Using data ethically and responsibly. Creating and sharing data for reuse, accountability, and enhancement. Making decisions and communicating using data, including data analysis and visualization. Protecting and archiving data. This course is currently required for and restricted to the Engineering in the World of Data LC. Additional sections are offered for students not in the LC.

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Instructors

• JJ Sadler
• Amy Childress

Description

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 choose.

Instructors

• Victoria Dawkins
• JJ Sadler

Description

Google and other search platforms are common resources for gathering information. Information literacy instruction prepares students to connect search strategies, contextualize authority and successfully navigate both the popular search engines, such as Google, as well as more scholarly/academic resources. These skills are key for students to participate successfully as scholars at Purdue and beyond in the workforce. This course will familiarize students with online databases and reference sources to efficiently research, evaluate source material, and document sources. Course information will consider student research interests, searching for available opportunities and mentors, and applying to undergraduate research opportunities. This course is open to all students in their first or second year in college and includes active-learning experiences that will support the course objectives.

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Instructors

• Melissa Chomintra

Description

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.

Instructors

• Jerilyn Tinio

Description

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.

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Instructors

• JJ Sadler
• Amy Childress

Description

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.

Instructors

• Spencer Stewart

Description

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.

Instructors

• JJ Sadler
• Amy Childress

Description

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.

Instructors

• Melissa Chomintra
• Heather Howard

Description

This course will provide students with an understanding of feminist research by introducing a range of feminist epistemologies, methodologies, and emergent research methods that have had a significant impact on feminist research practice and women's studies scholarship. The course will examine myriad feminist methodologies and approaches to the formal construction of knowledge. Additionally, it will survey the major methods of research in diverse fields presented in the context of feminist critique and epistemology. Androcentric information bias, feminist epistemology, information ethics and power are central themes of the course.

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Instructors

• JJ Sadler
• Wei Zakharov

Description

ILS 395 is offered as a complement to GS 395, Understanding Your Undergraduate Research. This course provides an introduction to principles of data management and organization, data analysis and visualization, and ethical and social implications of data science, providing a strong foundation for subsequent coursework. This course focuses on proper organization, management, visualization, preservation, communication, and ethical use of data. Students will apply their own research experiences in data management topics through readings, videos, discussion, lectures, guest speakers, and hand-on activities in class. They will develop an ability to locate, access, transform, and evaluate data to answer research questions. Students will communicate the results of their data searches, and format the data for sharing.

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Instructors

• JJ Sadler
• Amy Childress

Description

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.

Instructors

• Andrea Hayes

Description

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 research group.

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Instructors

• Adriana Harmeyer
• Kristin Leaman

Description

This seminar will introduce students to the exciting world of rare books and the endless research possibilities they provide. The co-instructors will cover the many methods necessary in understanding and successfully researching rare books primarily published between the 15th and 19th centuries. Students will engage with multiple rare books from the Purdue University Archives and Special Collections as part of in-class activities and assignments. Applying what they learn from reading and discussion to real-life examples will create hands-on, active-learning experiences that will enhance their own critical thinking skills when researching a rare book.

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Instructors

• Amy Childress
• JJ Sadler

Description

This course is for current Purdue undergraduate researchers who want to learn how to serve as peer mentors to undergraduate researchers early in their careers. This course will train students on how to create mutually beneficial and productive mentorships. This course will provide research-based best practices for mentoring newer student researchers while developing as a cohort of new research mentors. This course is especially useful for those students who enjoy supporting peer researchers or plan to continue into more formal mentorship roles as a senior undergraduate researcher, graduate student, or research supervisor in academia or industry. Must be a current undergraduate researcher.

Instructors

• Gang Shao

Description

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, stack overflow, GIS StackExchange, etc.

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Instructors

• Matt Hannah
• Gang Shao

Description

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.

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