8/11/2019 media_123993_en

1/1

Engineers must learn to self-check answers in order tohave confidence in their predictions and designs. It is

often too expensive and dangerous to proceed by trial

and error. Multichoice testing neglects to stress the disc-

pline of self checking - if your answer is listed, you chooseit.

In this work we re-implement and extend the existing,

simple, numerical answer support for the Universityselectronic voting systems to include confidence values,

complex numbers and improved display routines.

onventional multichoice Open ended numerical question

1*431 111 2

he advantage of electronic voting systems is that they allow a class to receive immediate feedback. The better targeted the

edback, the more effective the learning experience. For example, feedback can be worked out in advance of the presenta-

on for each of the wrong multiple choice answer. Enabling open-ended question types makes the task of preparing feed-ack appear to be equally open ended. By using the numerical question types, confidence metrics, and display routines devel-

ped here, we propose that the tension can be somewhat relieved by allowing the presenter to quickly and easily focus on the

ajority of the answers without being unduly distracted by spurious answers.

Numeric responses shown in asimple stacked bar chart, where

confidence is more quickly and

easily picked out.

XYBarChart graph to allow easy

manipulation of a wide range ofresponses in context to the range.

Number of votes indicated via size of bubblewith colour indicating an average confidence

value for that response. Scaling provided for

large sample sizes.

Complex questions can also be viewed asthree pie charts, with two separate charts

for real/imaginary parts only

Red indicates low confidence re-

sponse, green a high confidence.

chart shows responses to a multiple

choice question.

Or you can view confidence as a com-bined bar chart with confidence

values appearing underneath.