Share and succeed: the development of knowledge sharing and brokerage in data teams’ network structures

Figures & data

Figure 1. The data team intervention (Schildkamp and Ehren 2013, p. 56).

Figure 2. Three different types of knowledge brokerage.

Note: The middle rectangle represents the broker. The arrows represent the diffusion of knowledge.

Table 1. School characteristics.

School^1	N Locations	Educational^2 level	School size: N students	Relative size**	Denomination^3	N Data team members	Response data team members (%)	N Colleagues	Response Colleagues (%)
Fairview	2	Low/low	543/464*	–/–	Religious	7	100	16/14*	36/38
Highland	1	Interm. – High	1079	=	Public	9	89	20	28
Jefferson	4	Interm. – High	2752	=	Religious	5	100	***	***
Lincoln	1	Low – High	1261	+	Religious	6	100	49	49
Maple Grove	1	Low – High	1223	–	Public	5	80	33	34
Oak Grove	1	Low – High	1185	+	Religious	6	83	42	55
Pine Grove	1	Interm. – High	1007	–	Religious	6	83	31	43
Roosevelt	1	Low – High	964	–	Public	6	100	34	47

^* Data on Fairview 1 and Fairview 2, respectively

^** School size in relation to the educational level. + above average, = average, – below average

^*** This school was excluded from the second part of the study.

^1. School and participant names are pseudonyms.

^2. In the Netherlands, there are three main educational tracks. The lowest track (4 years) prepares students for vocational education. The intermediate track (5 years) prepares students for college/higher education. The highest track (6 years) prepares students for university education. These tracks are quite segregated, which means that most students who enter a track stay within that track until graduation.

^3. A school is considered public when it does not have a religious denomination.

Table 2. Participants’ characteristics for the four cases.

Name	Location	Years of experience	Function	Subjects
Fairview
Mr. Anderson	1	20	Teacher, school leader	Dutch
Mr. Johnson	1	12	Assistant principal	–
Ms. Smith	1	9	Teacher	English
Mr. Williams	1	8	Teacher, quality manager	Science, Chemistry
Mr. Jones	2	35	Teacher, school leader	Mathematics
Ms. Lee	2	10	Teacher	History, Geography
Mr. Miller	2	31	Teacher, school leader	Mathematics
Highland
Mr. Adams	–	5	Teacher	Mathematics
Mr. Bell	–	22	Teacher	Dutch
Mr. King	–	30	School leader, teacher	Geography
Ms. Morgan	–	11	Educational specialist	–
Ms. Murphy	–	15	Teacher	PE
Mr. Roberts	–	8	Teacher	PE
Ms. Stewart	–	7	Head ICT & Education*	–
Mr. Taylor	–	20	School leader	–
Mr. Turner	–	15	Teacher	History, Civics
Lincoln
Ms. Brown	–	32	Teacher	Music, Arts
Ms. Clark	–	13	Support staff	–
Ms. Harris	–	30	School leader	–
Mr. Martinez	–	15	Teacher	Mathematics
Mr. Wilson	–	9	Teacher	Chemistry
Ms. Young	–	20	Teacher	Mathematics
Roosevelt
Mr. Barnes	–	27	Teacher	French
Ms. Collins	–	20	School leader	–
Mr. Evans	–	20	Assistant principal, Teacher	Chemistry
Ms. Jenkins	–	14	Teacher	Arts
Mr. Myers	–	30	School leader	–
Ms. Powell	–	32	Teacher	Biology

^* Abbreviation of Information and Communication Technology.

Table 3. Descriptive statistics for the network structure measures.

	Data use				Educational problem
	T1		T2		T1		T2
	Mean	St. dev.	Mean	St. dev.	Mean	St. dev.	Mean	St. dev.
Knowledge sharing
Density	31.90	7.25	23.41	3.74	43.98	6.27	50.54	3.63
Reciprocity	19.31	4.78	15.79	5.01	25.42	6.72	37.52	8.34
Centralisation	27.40	5.12	33.62	5.52	33.30	8.33	34.29	4.70
Knowledge brokerage
Outward	2.96	0.85	1.51	0.47	5.62	1.96	5.14	1.31
Inward	2.21	0.64	0.95	0.34	3.08	0.66	3.43	0.59
Forward	0.63	0.11	0.38	0.12	1.73	0.79	1.29	0.53

Figure 3. Changes in network measures of knowledge sharing over time.

Figure 4. Relationships for exchanging data within four teams.

Note: Data team members from Fairview 1 are represented by the darker boxes, whereas members from Fairview 2 are represented by the lighter boxes.

Figure 5. Relationships for discussing the educational problem within four teams.

Note: Data team members from Fairview 1 are represented by the darker boxes, whereas members from Fairview 2 are represented by the lighter boxes.

Figure 6. Changes in types of knowledge brokerage over time.

Schildkamp, K., and M. Ehren. 2013. “The Netherlands: From ‘Intuition’- to ‘Data’-driven Decision Making in Dutch Secondary Schools?” In Data-Based Decision Making in Education, edited by K. Schildkamp, M. K. Lai, and L. Earl, 49–67. Dordrecht: Springer.10.1007/978-94-007-4816-3

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