From Data to Narrative via Computational Communication Science - Interaktive Studienpläne der TU Ilmenau
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| Modulinformationen zu From Data to Narrative via Computational Communication Science im Studiengang Master Digital Business – Medienwirtschaft und digitale Märkte 2025 | |
|---|---|
| Modulnummer | 201336 |
| Prüfungsnummer | 2500659 |
| Fakultät | Fakultät für Wirtschaftswissenschaften und Medien |
| Fachgebietsnummer | 2559 (Kommunikationswissenschaft mit Schwerpunkt Computational Communication Science) |
| Modulverantwortliche(r) | Prof. Dr. Emese Domahidi |
| Turnus | Sommersemester |
| Sprache | Englisch |
| Leistungspunkte | 5 |
| Präsenzstudium (h) | 22 |
| Selbststudium (h) | 128 |
| Verpflichtung | Wahlmodul |
| Abschluss | alternative Prüfungsleistung |
| Details zum Abschluss | Part 1: |
| Link zum Moodle-Kurs | |
| Lehrende | Prof. Dr. Emese Domahidi, Dr. Jingyuan Yu |
| Anmeldemodalitäten für alternative PL oder SL | <p style="-qt-block-indent: 0; text-indent: 0px; margin: 0px;">Enrolment in the course takes place by registering in the Moodle room, latest until one week after the first class. Registration for the exam is done directly by the Examination Office based on the list of participants.</p><p> </p> |
| max. Teilnehmerzahl | |
| Vorkenntnisse | Basic knowledge of R programming, prior attendance to "Introduction to Computational Communication Science" is encouraged |
| Lernergebnisse und erworbene Kompetenzen | By the end of this course, students are able to craft data-driven news articles by collecting, analyzing, and visualizing real-world data using R. They have learned to extract and interpret meaningful, newsworthy insights from datasets such as those from the German Federal Statistical Office and the United Nations Statistics Division. Students have developed the ability to interpret descriptive and statistical analyses in a non-technical manner and effectively communicate their findings to the public. They also gained hands-on experience in building interactive dashboards (e.g., via R Shiny) to facilitate discussion and engagement with both their peers and the public. Beyond technical skills, the course enabled students to critically examine social, economic, and political issues from a quantitative and computational perspective. Finally, students have refined their journalistic writing skills, learning how to convey complex data-driven narratives in a clear and compelling way. |
| Inhalt | This course introduces students to the principles and practices of data journalism, emphasizing the role of data in storytelling and investigative reporting. Students will learn how to source, clean, and analyze datasets to create news reports. They will also acquire skills in data visualization to effectively present their findings. As part of the course, students will produce a report that combines their data analysis, visualizations, and written insights. Students will also defend their work in an oral examination, demonstrating their ability to communicate complex findings. By the end of the course, students will have a portfolio of work showcasing their ability to use data to tell stories. |
| Medienformen und technische Anforderungen bei Lehr- und Abschlussleistungen in elektronischer Form | Reading work, moodle, lecture script, course materials |
| Literatur | Will be announced each semester |
| Lehrevaluation | |