Assessing the evidence: Student response system versus computer based testing for undertaking multiple choice question assessment in undergraduate nursing education

There is a dearth of evidence focusing on student preferences for computer-based testing versus
testing via student response systems for summative assessment in undergraduate education.
This quantitative study compared the preference and acceptability of computer-based testing
and a student response system for completing multiple choice questions in undergraduate
nursing education. After using both computer-based testing and a student response system to
complete multiple choice questions, 192 first year undergraduate nursing students rated their
preferences and attitudes towards using computer-based testing and a student response system.
Results indicated that seventy four percent felt the student response system was easy to use.
Fifty six percent felt the student response system took more time than the computer-based testing
to become familiar with. Sixty Percent felt computer-based testing was more users friendly.
Seventy Percent of students would prefer to take a multiple choice question summative exam
via computer-based testing, although Fifty percent would be happy to take using student response
system. Results are useful for undergraduate educators in relation to student’s preference
for using computer-based testing or student response system to undertake a summative
multiple choice question exam

Using bar-code technology to capture clinical intervention data in a hospital with a stand-alone pharmacy computer system

The use of barcode technology to capture data on pharmacists' clinical interventions is described.

Common-sense knowledge for a computer vision system for human action recognition

This work presents a novel approach for human action recognition based on the combination of computer vision techniques and common-sense knowledge and reasoning capabilities. The emphasis of this work is on how common sense has to be leveraged to a vision-based human action recognition so that nonsensical errors can be amended at the understanding stage. The proposed framework is to be deployed in a realistic environment in which humans behave rationally, that is, motivated by an aim or a reason. © 2012 Springer-Verlag.

Evaluating a Computer System that Converses Fluently with People

The SAL system embodies a new kind of human-computer interaction, where a person and a computer carry out a fluent, emotionally coloured conversation. Because that kind of capability is new, evaluating systems that have it is a new challenge. This paper outlines techniques that have been developed to evaluate SAL interactions, and uses the case to highlight the range of variables that become relevant in dealing with systems of this order of complexity.