Goodness of communication

This page is a knowledge crystal of subtype method. The page identifier is Op_en5441
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Question

How to measure the performance or goodness of communication about an open assessment?

Answer

Failed to parse (SVG (MathML can be enabled via browser plugin): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\displaystyle GC = \frac{Re*Av*Us*Ac}{Ef} }

Explanations:

• Calibration, Informativeness, and Coherence: These are not relevant for the assessment of communication methods and are therefore not used.
• Relevance (Re): P(receiver is interested in the content of communication)
• Availability (Av): number of people hearing the content N(people)
• Usability (Us): utility of content (in onors) to a user finding it interesting U(content)
• Acceptability (Ac): P(content and production are acceptable in user's context)
• Efficiency (Ef): Sum of costs (in working hours): Sum(talking, reading, using content)
• Goodness of communication (GC): overall outcome divided by resources used

Rationale

Drafts of estimates for calculations. The idea is to test whether a quantitative approach makes sense, i.e. whether it is possible to give plausible answers as parameters in the calculation.

Goodness of communication: Difference between revisions(P,o,h)

Obs	Method	Situation	Property	Result
1	Mouth-to-mouth communication	Between scientists	Calibration	0
2	Mouth-to-mouth communication	Between scientists	Informativeness	0
3	Mouth-to-mouth communication	Between scientists	Coherence	0
4	Mouth-to-mouth communication	Between scientists	Relevance	0.1
5	Mouth-to-mouth communication	Between scientists	Availability	5
6	Mouth-to-mouth communication	Between scientists	Usability	1
7	Mouth-to-mouth communication	Between scientists	Acceptability	0.5
8	Mouth-to-mouth communication	Between scientists	Efficiency	0.5
9	Opasnet	Between scientists	Calibration	0
10	Opasnet	Between scientists	Informativeness	0
11	Opasnet	Between scientists	Coherence	0
12	Opasnet	Between scientists	Relevance	0.1
13	Opasnet	Between scientists	Availability	100
14	Opasnet	Between scientists	Usability	1
15	Opasnet	Between scientists	Acceptability	0.005
16	Opasnet	Between scientists	Efficiency	0.5
17	Opasnet	Within society	Calibration	0
18	Opasnet	Within society	Informativeness	0
19	Opasnet	Within society	Coherence	0
20	Opasnet	Within society	Relevance	0.01
21	Opasnet	Within society	Availability	50000
22	Opasnet	Within society	Usability	1
23	Opasnet	Within society	Acceptability	0.05
24	Opasnet	Within society	Efficiency	0.5

+ Show code- Hide code library(OpasnetBaseUtils) library(xtable) data <- op_baseGetData("opasnet_base", "Op_en5441")[, -c(1,2,7)] data <- reshape(data, timevar = "Property", idvar = c("Method", "Situation"), v.names = "Result", direction = "wide") colnames(data) <- c("Method", "Situation", "Calibration", "Informativeness", "Coherence", "Relevance", "Availability", "Usability", "Acceptability", "Efficiency") data$GC <- data$Relevance * data$Availability * data$Usability * data$Acceptability / data$Efficiency print(xtable(data), type = 'html')