623.405 (22S) Experiments in Human-Computer Interaction

Sommersemester 2022

Anmeldefrist abgelaufen.

Erster Termin der LV
03.03.2022 14:00 - 16:00 S.2.69 - Bitmovin On Campus
... keine weiteren Termine bekannt

Überblick

Bedingt durch die COVID-19-Pandemie können kurzfristige Änderungen bei Lehrveranstaltungen und Prüfungen (z.B. Absage von Präsenz-Lehreveranstaltungen und Umstellung auf Online-Prüfungen) erforderlich sein.

Weitere Informationen zum Lehrbetrieb vor Ort finden Sie unter: https://www.aau.at/corona.
Lehrende/r
LV-Titel englisch Experiments in Human-Computer Interaction
LV-Art Vorlesung-Kurs (prüfungsimmanente LV )
LV-Modell Präsenzlehrveranstaltung
Semesterstunde/n 2.0
ECTS-Anrechnungspunkte 4.0
Anmeldungen 7 (30 max.)
Organisationseinheit
Unterrichtssprache Englisch
LV-Beginn 03.03.2022
eLearning zum Moodle-Kurs

Zeit und Ort

Beachten Sie bitte, dass sich aufgrund von COVID-19-Maßnahmen die derzeit angezeigten Termine noch ändern können.
Liste der Termine wird geladen...

LV-Beschreibung

Intendierte Lernergebnisse

Upon successful completion of the course, a student will know how to:

  • plan and design HCI-experiments,
  • conduct HCI-experiments,
  • analyse quantitative data and qualitative data collected through HCI-experiments, and
  • document/present HCI-experiments and results.

Lehrmethodik

lecture • discussions • example project • reading/writing assignments

Based on an example project, we will together discuss and exercise through the necessary steps required to convincingly answer an HCI-research question using an experiment.

Inhalt/e

The research area Human-Computer Interaction (HCI) deals with phenomena surrounding humans interacting with computing devices or digital environments, such as desktop computers, smartphones, and smart homes. This course provides knowledge, skills and techniques necessary to conduct purposeful experiments (a.k.a. user studies) in Human-Computer Interaction. 

Topics include:

  • empirical research motivation,
  • HCI-research questions and experiments,
  • internal/external validity of experiments,
  • repeatability, replicability, and reproducibility of experiments,
  • experiment terminology and design considerations,
  • ethics and working with human participants,
  • measurement scales and statistics,
  • hypothesis testing / inference statistics,
  • describing HCI-experiments, and
  • presenting results from HCI-experiments.

Link auf weitere Informationen

https://www.aau.at/en/isys/ias/teaching/master-specialization-hci/

Prüfungsinformationen

Im Fall von online durchgeführten Prüfungen sind die Standards zu beachten, die die technischen Geräte der Studierenden erfüllen müssen, um an diesen Prüfungen teilnehmen zu können.

Prüfungsmethode/n

discussions • assignments • course example project

Prüfungsinhalt/e

See Course overview above.

Beurteilungskriterien/-maßstäbe

The final grade is based on the results of the following work items: participation in discussions, completed assignments, and contributions to the course example project. The scores on these work items depend on their overall quality, completeness, and correctness according to the following grading scheme.

Grade 1 – Excellent: 89 – 100 percent points
The work item is complete and of superior quality. The work item is very well written, has a professional touch, and is profound. The student is very reflective and insightful. The work item may contain very few clarity, structure, or presentation problems.
Grade 2 – Good: 76 – 88 percent points
The work item is complete and of high quality. The work item is well written and in-depth. The student is reflective and insightful. The work item may contain few clarity, structure, or presentation problems.
Grade 3 – Satisfactory: 63 – 75 percent points
The work item is complete and of good quality, but several points could be better articulated, be more insightful, or more thorough. The work item may contain some clarity, structure, or presentation problems.
Grade 4 – Sufficient: 50 – 62 percent points
The work item is mostly complete and of satisfactory quality, but most points could be better articulated, be more insightful, or more thorough. The work item contains clarity, structure, or presentation problems.
Grade 5 – Failed: 0 – 49 percent points
The work item is incomplete or of lower quality. The points are not well articulated or thorough enough. The work item may contain significant clarity, structure, or presentation problems.

Beurteilungsschema

Note Benotungsschema

Position im Curriculum

  • Masterstudium Informatics (SKZ: 911, Version: 19W.2)
    • Fach: Human-Computer Interaction (Wahlfach)
      • Weitere LVen aus dem gewählten Spezialisierungsfach ( 0.0h XX / 12.0 ECTS)
        • 623.405 Experiments in Human-Computer Interaction (2.0h VC / 4.0 ECTS)
          Absolvierung im 1., 2. Semester empfohlen

Gleichwertige Lehrveranstaltungen im Sinne der Prüfungsantrittszählung

Sommersemester 2024
  • 623.405 VC Experiments in Human-Computer Interaction (2.0h / 4.0ECTS)
Sommersemester 2023
  • 623.405 VC Experiments in Human-Computer Interaction (2.0h / 4.0ECTS)
Sommersemester 2021
  • 623.405 VC Experiments in Human-Computer Interaction (2.0h / 4.0ECTS)