mpia-package: Meaningful Purposive Interaction Analysis (MPIA)
In mpia: Meaningful Purposive Interaction Analysis

Description Details Author(s) References See Also Examples

'Learning' is building competence through (targeted) conversation between an aspirant and a typically more experienced other. Such conversation, – particularly when born digital in form of messages, essays, articles, or books available online –, can be subjected to analysis, looking into both developed conceptual structures as well as the social interaction leading to them.

Meaningful Purposive Interaction Analysis (MPIA) was developed to facilitate the analysis of social semantic relations. It uses conceptual spaces built from the conversational content collected from networked learning activity to represent persons and their competence demonstrated.

MPIA is dervied from the same mathematical foundation as latent semantic analysis and (social) network analysis, sharing their advantages, while at the same time overcoming some of their shortcomings.

The package provides routines to construct and investigate representations of social semantic performance networks.

The community knowledge expressed digitally in a larger amount of unstructured text (such as a collection of messages, essays, articles, or books) can be used to derive its specific 'conceptual graph' of (both generic as well as professional language) terms and their associative proximity relations.

Such conceptual graph provides a projection surface on which it is possible to investigate social as well as semantic relations of persons, their performance, and the underlying competence.

The package additionally provides visual analytics to support the analyst.

Fridolin Wild <wild@brookes.ac.uk>

Fridolin Wild (2016): Learning Analytics in R with SNA, LSA, and MPIA, Springer:Berlin.

lsa, sna, network

# load domain

dmgr=DomainManager()
data(generic.domain)
dmgr$add(d, title="generic")

#d=dmgr$get("generic")

# visualise terminology map
plot(d)
toponymy(d)

# the virtual HR manager
ppl = HumanResourceManager(dmgr)

# add a learner
fridolin = ppl$add(name="fridolin")
fridolin$write("risk management is crucial for preventing
   a business from failure.", label="risk")
fridolin$write("shareholders can maximize their profits, if the price
   level is increased: most shareholders appreciate such performance
   management oriented approach to business", label="profits")
fridolin$write("in management, it is the role of the ceo in business
   to appreciate the contributions of the panel members and to balance
   risk", label="control")
fridolin$write("donor development in fundraising is all about ensuring
   that you and your donors get the most you can from your relationship
   in ways which are mutually agreeable and beneficial", label="donors")
terms(fridolin)
terms(position(fridolin))

# visualise
plot(position(fridolin), col="red")
plot(path(fridolin), col="red")

# add a second learner
max = ppl$add(name="maximilian")
max$write("advertising includes the activity in the media such as
   running newspaper ads, direct marketing, cold calling",
   label="advertising")
max$write("marketing management, however, is a wide field: this
   basically boils down to comparing investment into advertising
   with the return on investment and making decisions",
   label="marketing")

# visualize
plot(position(max), col="yellow")

# check for competence profile identity
max == fridolin
near(max, fridolin)
competences(fridolin)