Program Overview

Introduction to the Digital Methods Module

The Digital Methods module is a comprehensive program designed to equip students with the knowledge and skills necessary to navigate the complexities of digital methodologies. This module is part of the broader curriculum offered by Aalborg University, aiming to foster a deep understanding of digital tools, their applications, and the critical thinking required to effectively utilize them in various contexts.

Module Content, Progression, and Pedagogy

Through this module, students acquire knowledge about new digital methods and gain practical experience with computational techniques such as machine learning, pattern recognition, and network analysis. The curriculum is structured to enable students to collect, analyze, and visualize large amounts of unstructured data from digital media, such as texts or images from the internet. Furthermore, students learn to critically assess the possibilities and challenges of digital method projects and to communicate effectively with technical specialists.

Learning Objectives

Knowledge

• Techniques for collecting and curating large amounts of unstructured data from digital media, including scrapers, crawlers, and APIs.
• Techniques for machine processing and exploratory analysis of large amounts of unstructured data, including visual network analysis, natural language processing, and various forms of machine learning.
• Central methodological discussions, problems, and concepts from the digital method literature, such as questions about ethics, online grounding, algorithmic bias, or the relationship between quantitative and qualitative methods.

Skills

• Collecting large amounts of unstructured data from digital media.
• Investigating relationships in data through visual network analysis.
• Applying tools based on machine learning to analyze text and images.
• Applying relevant data visualization tools to convey qualitatively deep stories with data.

Competencies

• Planning a digital method project and critically evaluating its possibilities and challenges.
• Collaborating with relevant technical specialists in fields such as computer science or information design.
• Translating between qualitative, humanistic questions and insights from machine analysis of large data quantities.

Teaching Methods

The teaching methods for this module are outlined in the study regulations, section 17. The specific weighting of different teaching elements will be detailed in the semester description for the module, which is published in Moodle before the semester starts.

Examination

Exams

The exam for the Digital Methods module is a group project where students, in groups of at least 2 and no more than 4, produce a minor demonstration project over the course of the semester. The project consists of a series of visualizations with accompanying descriptions of the methods used, insights gained, and considerations for potential future work.

• Group size: 2-4 students.
• Scope: Minimum 5 and maximum 8 standard pages per student in the group.
• Exam period: As specified in the study regulations, section 17, paragraph 4.
• ECTS: 5.
• Assessment form: 7-point scale.
• Evaluation criteria: As stated in the University's examination regulations.

Facts About the Module

• English title: Digital Methods.
• Module code: BAOLA.
• Module type: Project.
• Duration: 1 semester.
• Semester: Spring.
• ECTS: 5.
• Language of instruction: Danish.
• Place of instruction: Campus Aalborg.
• Module responsible: Lone Krogh.

Organization

• Study board: Study Board for Learning, IT, and Organization (LIO).
• Department: Department of Culture and Learning.
• Faculty: The Faculty of Humanities.

Conclusion

The Digital Methods module at Aalborg University offers a comprehensive and practical approach to understanding and applying digital methodologies. With a focus on both theoretical knowledge and practical skills, this module prepares students to navigate the complexities of digital data analysis and to contribute meaningfully in their future careers.