Schlagwortarchiv für: MA-IAS

Universität Klagenfurt gewinnt den Global Student Satisfaction Award in der Kategorie „Student Diversity“

Nachdem die Universität Klagenfurt schon 2021 einen der begehrten Preise gewonnen hatte, war sie nun auch bei der diesjährigen Award-Verleihung erfolgreich. Sie gewann die Auszeichnung im Bereich Student Diversity und konnte sich in der globalen Endrunde gegen die University of West Florida aus den USA und die Prince of Songkla University aus Thailand durchsetzen. Damit ist die Universität Klagenfurt die einzige Universität weltweit, die zweimal hintereinander einen Global Student Satisfaction Award gewinnen konnte.

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Selection of Moving Screen Targets

In many appli­cations – such as in air-traffic con­trol, in video sur­veill­ance, and in com­puter games – the user needs to quick­ly and accu­ra­te­ly select ob­jects that are mov­ing across the screen. Several pre­vious re­search pro­jects have pro­posed vari­ous tech­ni­ques that can assist the user when click­ing on mov­ing screen objects. The aim with this pro­ject is to com­pare such tech­niques and to build a theo­re­ti­cal model that mathe­ma­ti­cally de­scri­bes and pre­dicts how fast users can se­lect tar­gets that are mov­ing across the screen (de­pend­ing on the size of the tar­get and its moving speed).

A first version of a Java appli­ca­tion that pro­vi­des the necess­ary func­ti­on­ality to con­duct user ex­peri­ments on selec­tion of moving screen objects has al­ready been de­vel­oped. In this pro­ject you will first ex­tend this app­li­ca­tion with addi­tional func­tion­ality and then de­sign and con­duct a user ex­peri­ment that allows you to 1) veri­fy pre­vi­ously re­ported re­search re­sults on the effect­ive­ness of var­ious tech­niques that support the selec­tion of mov­ing screen ob­jects, and 2) empi­ri­cally build and veri­fy a pre­dictive per­for­mance model that ex­plains how fast users can select mov­ing screen objects.

Accordingly, with this pro­ject you have the oppor­tu­nity to deepen your pro­gramming skills (using Swing, Java’s GUI tool­kit) and you will gain ex­peri­ence in how to de­sign, conduct, and eva­luate user ex­peri­ments, and in theo­re­ti­cal modell­ing of user per­for­mance.

Technologies & Tools: Java, SPSS (for statistical analysis)

Contact: Dr. David Ahlström