printer friendly pageDLCL 103: Future Text: AI and Literatures, Cultures, and Languages (ITALIAN 103)
How do AI language models work and what is their impact on education? In this course we will: Experiment with translation; Experiment with textual analysis of specific texts from different contexts and historical periods and cultures; Experiment with large data questions that are very hard to do by a single person; Experiment with ways to fact-check an AI generated work: we know AI creates false assertions, and backs them up with false references; Experiment with collaborating with AI to write a final paper, a blog, a newspaper article, etc.
Terms: Aut
| Units: 4
| UG Reqs: WAY-A-II, WAY-EDP
DLCL 201: Digital Humanities Practicum
Interested in applying digital tools and methods to text, images, or other humanities research materials? This hands-on course will support you in planning and implementing your own digital project, using materials in any language. Working directly with a digital humanities expert, you will identify your own research question that can be addressed by digital methods, define a reasonable scope, and learn how to implement the methods you need to answer your research question. The course will include workshops on topics including data management, project management, and how to talk about your work both in academic contexts, and as part of your portfolio for applying to jobs in other fields.
Terms: Win, Spr
| Units: 1-5
| Repeatable
3 times
(up to 5 units total)
Instructors:
Dombrowski, Q. (PI)
DLCL 203: Data Visualization With Textiles
How does something become "data", and how can we understand our data better through visualization and physicalization? This 1-credit course will explore data creation and methods for representing that data using textiles, which have a long history as a medium for capturing data. Students will get hands-on experience with different tools at the Textile Makerspace (sewing, knitting, embroidery, spinning, weaving) and create a data physicalization final project that uses skills developed during the class.
Terms: Spr
| Units: 1-3
Instructors:
Dombrowski, Q. (PI)
DLCL 205: Project Management and Ethical Collaboration for Humanists (DLCL 305)
What does it look like to manage a collaborative project in a way that's both effective and ethical, taking into account the needs of people as well as the task? This class will cover project management and collaboration as they are practiced in digital humanities, "alt-ac" (alternative academic) jobs, and similar environments outside academia. In addition to readings and discussion, students will participate in a simulation of one year in the life of a digital humanities project (in the style of Dungeons and Dragons and similar role-playing games), with each student playing the role of a member on the project team.
Terms: Win
| Units: 3-5
Instructors:
Dombrowski, Q. (PI)
DLCL 305: Project Management and Ethical Collaboration for Humanists (DLCL 205)
What does it look like to manage a collaborative project in a way that's both effective and ethical, taking into account the needs of people as well as the task? This class will cover project management and collaboration as they are practiced in digital humanities, "alt-ac" (alternative academic) jobs, and similar environments outside academia. In addition to readings and discussion, students will participate in a simulation of one year in the life of a digital humanities project (in the style of Dungeons and Dragons and similar role-playing games), with each student playing the role of a member on the project team.
Terms: Win
| Units: 3-5
Instructors:
Dombrowski, Q. (PI)
ITALIAN 103: Future Text: AI and Literatures, Cultures, and Languages (DLCL 103)
How do AI language models work and what is their impact on education? In this course we will: Experiment with translation; Experiment with textual analysis of specific texts from different contexts and historical periods and cultures; Experiment with large data questions that are very hard to do by a single person; Experiment with ways to fact-check an AI generated work: we know AI creates false assertions, and backs them up with false references; Experiment with collaborating with AI to write a final paper, a blog, a newspaper article, etc.
Terms: Aut
| Units: 4
| UG Reqs: WAY-A-II, WAY-EDP
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