A computational model is a mathematical model in computational science that requires extensive computational resources to study the behavior of a complex system by computer simulation.

They provide a base for comparison similar to a control group?

Maybe I missed something in our previous readings/videos, but can someone explain to me what is meant by the term "artifacts"?

This whole concept is a huge part of what I want to get out of my data set! This is exciting and also terrifying because I will have to figure out how to actually get these measurements....

I had not thought of that until they spelled this out. that actually makes a lot of sense.

I think this also applies in financial sectors, right? good explanantion linking centrality and structural holes; I also like the breakdown in the bottom paragraph with five specific roles shown in fig. 7.7

density + pattern of relations among alters = constraints

wow. entropy sounds awesome. I want to be able to use this in my analysis just because it sounds so cool and I think it was one of the few concepts that really made sense when I was introduced to entropy in physics and chemistry!

focus of questions that try to examine individual entities across different networks and/or patterns of interaction within groups.

ego's social capital in the hood

It is easy to see why node level centrality and network-level centralization are mistakenly treated as the same. This is my third or fourth time through this and I'm still not completely clear.

These are two terms that are commonly used in literacy in regards to acquisition of emerging readers and two different theories as to which is the best way to help young readers become successful in reading. Spoiler - bottom-up won...

Although I already determined I needed to add a cut-off value to my data in order to make some of it meaningful it's reassuring to read about here.

Nice definition

I'm interested to learn more about this.

In ELT, "Top Down" refers to getting learners to make predictions about reading/listening activities before they actually do them. For example showing students a magazine article and asking to predict what they the article might be about, based on pictures or titles. This seems to be similar here, looking at readily available information without getting into the details first.

so is this directly correlated to structural cohesiveness?

component definition; the graphic from Bodong's video clip is helpful in getting a (mental) picture of this definition.

1. Would it be right to say that a decentralized network would mean that more actors have a say in the evaluation process?
2. Could a measure like high transitivity indicate more equitable practices in evaluation?
3. Would high reciprocity mean that there was healthier communication (not just directed "at" the new teachers, but feedback loops and supportive avenues of communication)?
4. And finally, what would high density scores indicate -- that resources are more accessible and basically better connections overall - so a more well-connected network, with fewer actors in isolated or peripheral positions?

centralization: power in the hands of a few

small world phenomenon

clustering: tendency towards shared interactions based on homophily

examples of forms of relationships (16 dif kinds according to Holland&Linehardt, 1979)

reciprocity: appears in many studies and seems highly relevant in educational fields

size: affects structure of relations, reflects network's boundary, and measure of number of nodes in network

How were the data changed from 1,2,3 to 1,0?

From my understanding of this, structural holes differ from triads since triads generally indicate that all three actors are connected in some way. Is this correct?

I like the explanation of effective density. I think it will be useful for my own "potential" research

Interesting. I am unfamiliar with this type of sampling. I have heard of it before, but I have not seen many studies that utilize this sampling approach.

useful in "empirically locating network boundaries" but not used widely

positional different from relational because there could be structural holes

I like this definition of SNA

This is my first time learning about cultural capital. It makes sense so I am surprised that I have not come across it before.

Human Capital is a big deal in the field of Human Resource Development. Supporters of the human capital theory argue that humans are the best asset of any organization. It's nice to see the theory mentioned in literature outside of business and HR fields.

While I can make an educated guess as to what these terms mean, I am not very familiar with them.

This is the easiest definition to work with, in my opinion!

I find this interesting because it is being described as "classical theory of capital"... even though it is still used to this day as the dominant definition of capital, and fits well within contemporary applications of capital theory, including social capital theory.

Patterned social relations are structural relations that exist only at a specific time-place and either disappear or recede when actors are elsewhere. Relations vary significantly across contexts and condition the social actors apart from their attributes.

These graphs are powerful tools, very similar to concept maps.

Interesting

Here is a better explanation of the SNA terms Arcs and Edges. Arcs represent those relations that are directed from one student to another, meaning that the friendship nomination has not necessarily been reciprocated. Edges, on the other hand, are those lines that do not have arrowheads (since friendships are directed, there are no edges in Figure 3.1), which are appropriate when the relation is by definition reciprocated (e.g., “studies with”).

I am unfamiliar with the term "arc" in this context since I am unsure what is meant by "directed lines".

This has come up a couple times now with no definition (that I've seen), so I looked it up on dictionary.com: the measurement of attitudes of social acceptance or rejection through expressed preferences among members of a social grouping

I think this will occur a lot in SNA

This is a really great SNA term/phrase. Generating big ideas from small observations is a nice description of SNA. It reminds me of the grounded theory approach in qualitative research.

I really appreciate how the term diffusion is used in SNA to describe the natural spread of knowledge through a network.

I'm curious about this concept, as I suspect it's been the basis for other technologies we use today.

I think the idea of research as therapy is really interesting. Beyond that, though, a major concept within LT is the idea of bringing theory into practice; this seems like a different application of that process.

Is this ontology inherently incompatible with relational realism? If different educational researchers operate under each ontological paradigm and describe the same scenario in unique ways, what value would each bring to our understanding of the world? Is one inherently more valuable than the other?

SNA is not just a methodology, rather an informed perspective that should affect every area of research.

This seems to somewhat reflect a similar evolution in education theory (not directly, but somewhat), tying into the newer theory of connectivism, as I see it. Though this doesn't necessary indicate a progression (maybe though?)

A collection of actors on which ties are to be measured.

The collection of the ties between actors, taken as a whole.

Ties are connections between actors

Diffusion--as I understand it--is tracking how a particular phenomenon moves through a social network. This reminds me of a TEDTalk on how to start a movement: https://www.youtube.com/watch?v=RXMnDG3QzxE

I am curious about a few things packed in this sentence: network phenomena, and their antecedents and consequences.