3. Research Methods
3.4 Variables
A large number of relational variables are defined to correspond to the ego-centric network interviews and surveys. They represent the raw network data and are computed for research variables of analytical models.
3.4.1. Variables of Study 1
3.4.1.1. Relational Variables of Personal Relationships
CTKASize and CTKCSize represent variables of network size of ICT knowledge acquisition and the contribution of each STC in first layer.
ATKASize and ATKCSize represent variables of network size of ICT knowledge acquisition and the contribution of each STC in second layer
CIKASize and CIKCSize represent variables of network size of ICT-in-Education knowledge acquisition and the contribution of each STC in first layer.
AIKASize and AIKCSize represent variables of network size of ICT-in-Education knowledge acquisition and the contribution of each STC in second layer.
DISCSIze represents variable of network size of discussions for ICT-in-Education knowledge in first layer.
CKADen and CKCDen represent variables of network densities of ICT knowledge
acquisition and contribution of each ego in work layer.
AKADen and AKCDen represent variables of network densities of ICT knowledge acquisition and the contribution of each ego in second layer.
CIKADen and CIKCDen represent variables of network densities of ICT-in-Education knowledge acquisition and the contribution of each ego in first layer.
AIKADen and AIKCDen represent variables of network densities of ICT-in-Education knowledge acquisition and the contribution of each ego in second layer.
CKAStr and CKCStr represent variables of tie strength of ICT knowledge acquisition and the contribution of each ego in first layer.
AKAStr and AKCStr represent variables of tie strength of ICT knowledge acquisition and the contribution of each ego in second layer.
CIKAStr and CIKCStr represent variables of tie strength of ICT-in-Education knowledge acquisition and the contribution of each ego in first layer.
AIKAStr and AIKCStr represent variables of tie strength of ICT-in-Education knowledge acquisition and the contribution of each ego in second layer.
IKCSize represents variable of number of networks spanning online knowledge contribution.
The Table 3.1 summaries these relational variables.
Table 3.1. Summaries of Relational Variables in Two Layers
Direction of Knowledge Sharing Relational Properties
IKAEffSize Network Size CTKCSize ATKGSize
CIKCSize AIKGSize Network Density CTKCDen ATKGDen
CIKCDen AIKGDen Network Strength CTKCStr ATKGStr
CIKCStr AIKGStr Effective Sizes TKGEffSize
Knowledge Contribution
IKGEffSize
Knowledge Contribution (Internet) IKCSize DISCSize DISCDen Discussion
DISCStr Note: 1. Code TK and IK represent ICT-practice and ICT-in-Education-practice respectively.
3.4.1.2. Research Variables
The research variables derived from hypotheses 1 to 8 are illustrated in Figure 3.3.
Figure e
Variables ATKCSize and IKC sent the degree measurements of know
3.3 Research Variables and Hypotheses of Prestige and Knowledge Exchang Size repre
ledge contribution for ICT practice and IK practice respectively. Variables CSize, CDen and CTKCStr: represent variables of personal network size, network density, and tie strength of knowledge exchange, respectively.
The research variables derived from hypotheses 9 to 11 are illustrated in Figure 3.4.
Figure 3.4 Research Variables and Hypotheses of Structural Holes
Variable ledge
cont
ledge Acquiring
ariables of network size, network density and tie s
SWDen, and SWStr represent variables of network size, network density, and tie s
Size, NWDen, and NWStr represent variables of network size, network density, and tie strength of each STC’
e, PRODen, and PROStr represent variables of network size, network s TKCEffSize and IKCEffSize represent effective size of know ribution of each STC. Variables ATKCDen and AIKCDen represent network densities of knowledge contribution of each STC. ATKCStr and AIKCStr represent effective size of knowledge contribution of each STC.
3.4.2 Variables of Study 2
3.4.2.1. Variables of Know
HWSize, HWDen, and HWStr represent v
trength of each STC’s knowledge acquisition with regard to computer hardware maintenance.
SWSize,
trength of each STC’s knowledge acquisition with regard to computer software usage.
NW
s knowledge acquisition with regard to computer networking.
PROSiz
dens
DMSize, DMDen, and DMStr represent variables of network size, network density, and
bles
coordinator (CO), gatekeeper (GT), representative (RP), and consultant (CN)
knowledge brokerag
Table 3.2 Variables of Knowledge Brokerage and Friendship
ity, and tie strength of each STC’s knowledge acquisition with regard to ICT procurement.
tie strength of each STC’s knowledge acquisition with regard to digitalizing instructional materials.
3.4.2.2. Research Varia
We examined four brokerage scores:
of STCs’ knowledge acquisition and five types of practices requiring knowledge acquisition: computer hardware maintenance (HW), software usages (SW), network techniques (NW), ICT procurement (PRO) and digitalizing materials (DM). Brokerage variables are described in the following.
Variable Friendships (FR) was the other variable used for comparison.
Variables HWCO, HWGT, HWRP, and HWCN represent four variables of e of each STC’s knowledge acquisition in relation to computer hardware maintenance. Variables SWCO, SWGT, SWRP, and SWCN represent four variables of knowledge brokerage of each STC’s knowledge acquisition in relation to computer software usage. Variables NWCO, NWGT, NWRP, and NWCN represent four variables of knowledge brokerage of each STC’s knowledge acquisition in relation to computer networking. Variables PROCO, PROGT, PRORP, and PROCN represent four variables of knowledge brokerage of each STC’s knowledge acquisition in relation to ICT procurements. Variables DMCO, DMGT, DMRP, and DMCN represent four variables of knowledge brokerage of each STC’s knowledge acquisition in relation to digitalizing instructional materials. FRCO, FRGT, FRRP, and FRCN represent four variables of brokerage of each STC’s friendship, which will be used as references.
Types of knowledge Coordinator Gatekeeper Representative Consultant
Computer Networking NWCO NWGT NWRP NWCN Procurement PROCO PROGT PRORP PROCN Digitalizing Materials DMCO DMGT DMRP DMCN Friendship FRCO FRGT FRRP FRCN
3.4.3. Other variables
and R) of the personal characteristics (variations of gender and scho
k effects are compared relative to other facto
ges, interviewers recorded relationship data, according to nam
Two matrices (G
ol district) are constructed in study 1. Each element of matrix G indicates the gender difference between any two STCs of the networks. The number 1 indicates that two STCs have the same gender, and 0 indicates that they have different genders. The elements of matrix R indicate whether the school districts of any two STCs are similar (indicated by 1) or different (indicated by 0).
The impacts of the hypothesized networ
rs known to affect prestige. The variables considered are the size of the school of subjects (represented by the number of classes: NUMofClass), seniority (represented by number of years in STC work: STCAge), and exemplary nature of the school (whether this school implemented the ICT integrated instruction projects: E-School).