Goodness of communication

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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{Av*Re*Ac*Us}{Ef} }

Explanations:

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

Rationale

Open assessment framework. The roles of different participants lead to different kinds of communication and information work.

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(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')