Topic outline

  • General

    Overview: This course introduces the foundations of scientific research in the area of human-computer interaction. Students carry out an end-to-end research project during the course of a semester. In 2024, research topics will be hosted by AI researchers at the Finnish Center for AI.

    Topic: In 2024, the course focuses on LLMs and their use for assisting in design. LLMs have shown their competencies in many Natural Language Processing (NLP) tasks, such as summarizing text, synthesizing ideas, and generating human-like responses, but it is an open question how to apply them in design. During the course, students will plan and implement LLM-based interactive applications and investigate them with human experts. The techniques we cover go beyond prompt engineering. Students will document their work in academic paper styles, demonstrate their prototypes, and release their course code in Github.

    Requirements: We strongly recommend taking ELEC-E7852 (Computational Design and Interaction) prior to this course. If you have not taken this course, please consult Dr. Shin in advance about eligibility.

    Schedule and attendance: The course starts in January and continues until mid-May when final presentations take place. A maximum of 5 absences is permitted during the course.

    Learning objectives: 

    • Formulation of research problems  

    • Research planning 

    • Research strategy

    • User research methods

    • User testing; Experimental design; Statistical testing; Reporting empirical results

    • Representations of user research data

    • Data analysis and visualization methods for HCI data

    • Design space analysis, task analysis

    • Sketching techniques

    • Modeling workflows

    • Scientific reporting and presentations; pitching 

    Organization: One weekly meeting is organized until May, with the exception of April, when there's a break for independent research work. The beginning half of the course focuses on defining research problems and methods; the second on implementation and reporting.

    Learning in small groups: The number of students has historically ranged between 4 and 12. The small group size of the course ensures engaging meetings with plenty of feedback, iteration, and a collaborative atmosphere. The maximum number of students is limited to 12. In case there are more students wanting to join the course, selection will be based on the study program and study success.

    CHI student research competition: Best student projects will be submitted to the CHI student research competition or similar. 

    Teacher: Dr. Joongi Shin (cbl.aalto.fi)