Research Direction of Study 1

This study proposed that subjects who were identified more often by other subjects in a knowledge-acquisition network were more prestigious. Degree prestige (out-degree) measurement (Wasserman and Faust, 1994) by objective STCs (i.e., knowledge contributors) was used as the prestige score.

3.1.1. Hypotheses

Theories of social practices and researches of network benefits, gift-giving attitudes, and positional advantages for knowledge sharing sustain the hypotheses of this study. Based on the arguments of network analyzers, this study uses ICT practices and ICT-in-education as the essence of knowledge sharing and proposed that prestigious persons take on central roles in knowledge dissemination. It explores the usefulness of prestige as an indicator in CoP and argues that modes of knowledge sharing can be clarified by analyzing the relational properties. The author develops assumptions to explain the positive effects of social resources on knowledge sharing.

3.1.1.1. Mediation Effects of Knowledge Contribution

This study first seeks to verify the usability of prestige as an indicator of knowledge exchanges in a sparsely connected CoP. Then it seeks to identify whether gift-giving attitudes can mediate between limited informal personalization and prestige.

It hypothesizes that STCs who engage in greater knowledge contribution to STCs at

other schools will have higher prestige. It also hypothesizes that STCs who are devoted to contributing knowledge to online communities could gain prestige. The range of a network refers to a degree of range that contains socially engaged network members.

Hypothesis 1 (H1): Knowledge contribution to STCs at other schools has mediation effects for STCs leading to their gaining higher prestige scores.

Hypothesis 2 (H2): Knowledge contribution to online communities has mediation effects for STCs leading to their gaining higher prestige scores.

3.1.1.2. Features of Personal Social Networks

Features of personal social networks (PSNs)—e.g., number of contact ties, network density, and tie strength within organizations or among inter-organizations—affect the effectiveness of informal personalization as a knowledge-exchange mechanism. In a school context, a knowledge-exchange PSN within or outside of school would reflect an STC’s informal personalization in seeking out support when encountering problems. The various features of PSNs’ underlying knowledge exchange would depict the varied status in CoPs.

In the exchange process, network ties are created that consist of ties of knowledge acquisition and reciprocation. This study assumed that STCs with large knowledge-exchange PSNs both within and outside of school would thus have more resources for contributing knowledge to STCs at other schools. STCs with large knowledge-exchange PSNs would also tend to contribute more to online communities of related competency.

Hypothesis 3 (H3): Size of STC’s personal knowledge-exchange network correlates with knowledge contribution to STCs at other schools.

Hypothesis 4 (H4): Size of STC’s personal knowledge-exchange network correlates with knowledge contribution to online communities.

Network density is calculated by counting the number of ties that connect members

of the network and dividing it by the total number of possible pairs in the network (Wasserman & Faust, 1994). This study argues that contributions to STCs of other schools depend more on a gift-giving attitude than trust. This study assumed that dense knowledge-exchange PSNs might not facilitate knowledge contribution to STCs at other schools.

Hypothesis 5 (H5): Density of STC’s personal knowledge-exchange network does not correlate with knowledge contribution to STCs at other schools.

This study assumed that an STC with a dense knowledge-exchange PSN engages in online knowledge exchange with community members because that STC prefers secure relationships.

Hypothesis 6 (H6): Density of STC’s personal knowledge-exchange network positively correlates with knowledge contribution to online communities.

Previous studies have used frequency of contact to represent tie strength. Because exchanges of tacit knowledge and complicated practices require frequent contact and greater effort to contribute to STCs at other schools, we assumed STCs with stronger knowledge-exchange ties might tend not to contribute knowledge to STCs of other schools.

Hypothesis 7 (H7): Tie strength of STC’s personal knowledge-exchange network negatively correlates with knowledge contribution to STCs at other schools.

STCs with weaker knowledge-exchange ties presumably possess more heterogeneous information. Since contributing to an online community is easier than dealing with individuals and relatively heterogeneous enquiries from non-acquaintances, STCs that have PSNs with weak tie strength are assumed to be more likely to engage frequently in online relationships.

Hypothesis 8 (H8): Tie strength of STC’s personal knowledge-exchange network negatively correlates with knowledge contribution to online communities.

3.1.1.3. Effects of Structural Holes

The following hypotheses investigated the chance of good practice being transferred across school boundaries. This study inspected the efficiency of informal personalization of prestigious STCs by constructing a predictive model. The results provided the basis for discussing the discrepancies found between STCs’ PSNs in disseminating ICT practices and those in disseminating ICT-in-education practices

Burt (1992) has proposed that a network with “structural holes” is efficiently effective. Greater effective sizes increase the efficiency of knowledge sharing and work performance. In contrast, high network density is hypothesized to have more constraints.

That is, higher network density would decrease the effects of the knowledge transmittal to more people. This model hypothesizes that STCs who have larger effective network sizes of knowledge contribution will have higher prestige. It also hypothesizes that a lower density network with structural holes has fewer constraints and is positively linked to knowledge prestige.

Hypothesis 9(H9): Effective network size of STC’s personal knowledge contribution network has positive effects on knowledge prestige.

Hypothesis 10(H10): Density of STC’s personal knowledge contribution network has negative effects on knowledge prestige.

Researches have shown that people with strong ties belong to cliques and strong ties tend to be located in or develop into cliques (Travers & Milgram, 1969).

Contrastingly, weaker or irregular contacts are better sources of new information or are bridges to distant information networks. Weak ties are often more important for the dispersion of information than strong ties.

Hypothesis 11(H11): The tie strength of STC’s personal knowledge contribution

network has negative effects on knowledge prestige.

3.1.2. Instruments

This study developed a two-layer interview structure (Figure 3.1) with a two-layer interview protocol (see appendix A, Table A.1). The first interview regarding informal personalization was designed to examine the relational variables of each STC’s personal knowledge exchange. Correlates of informal personalization were colleagues with whom the subjects exchanged knowledge. The second interview regarding inter-school interaction was designed to record relationships of knowledge contribution to and acquisition from STCs of other schools. Researchers have indicated that workers’ recall of some specific interactions occurred at specific time intervals and has lower reliability than more general measures of typical interactions (Cross, Rice and Parker 2001). With this in mind, questionnaire items with general wording (not specific wording) were prepared for the two studies.

Figure 3.1 Two-layer Interview Structure