Unpacking the motivational variables which impact engagement in Lesson Study: Mathematics teaching self-efficacy and attitudes towards self-development

Figures & data

Table 1. Phases of lesson study within one cycle (Clivaz and Ni Shuilleabhain 2019).

0	Consider issues and formulate general goals
1	Study curriculum and formulate content specific goals
2	Collaboratively plan a research lesson (select or revise content, consider elements of the research lesson, detail the conduction of the lesson etc.)
3	One member of the group conducts the research lesson, with other members of the group observing and recording data on student learning
4	Reflect on the data from the research lesson and document the lesson study cycle

Figure 1. Hypothesised model of key study variables.

Table 2. Descriptive statistics for study variables.

Sex	Variables	n	mean	95% CI [LL,UL]	SD	Min	Max	Skew	Kurtosis	SE
Male	Age	18	37.78	[32.31,43.25]	10.07	22.00	59.00	0.12	−0.94	2.37
Male	Years teaching	18	14.11	[9.06,19.16]	9.30	2.00	37.00	0.64	−0.23	2.19
Male	ALS	18	36.40	[32.73,40.07]	6.73	19.21	44.00	−1.13	0.49	1.59
Male	MTSE	18	85.60	[80.94,90.26]	8.58	71.00	98.79	−0.01	−1.46	2.02
Female	Age	46	35.96	[32.48,39.44]	10.25	23.00	65.00	0.89	0.39	1.51
Female	Years teaching	46	12.91	[9.59,16.23]	9.74	1.00	42.00	0.86	0.56	1.44
Female	ALS	46	37.20	[35.61,38.79]	4.65	27.00	45.00	−0.12	−0.85	0.69
Female	MTSE	46	82.06	[79.48,84.64]	7.60	68.00	98.79	0.47	−0.13	1.12

Note. Note: CI = confidence interval; LL = lower limits of 95% CI; UL = upper limits of 95% CI; SD = standard deviation; SE = standard error; ALS = attitudes towards self-development in Lesson study; MTSE = Mathematics teaching self-efficacy.

Figure 2. Attitudes towards self-development in Lesson Study plotted across cycles of participation.

Figure 3. Predicted probabilities for attitudes towards self-development on participation in Lesson Study. Note. Career stages in current study are based on quartiles of years teaching experience recorded for study sample; NQT = Newly qualified teacher (<5 years); Est. = established teacher (5-11.5 years); Senior = Senior teacher (11.5-19 years); End = End quarter of career (>19 years).

Table 3. Results of bootstrapped non-parametric mediation analysis.

	0 cycles			1 cycle			2 + cycles
Effect	Value	95% CI [LL, UL]	p	Value	95% CI [LL, UL]	p	Value	95% CI [LL, UL]	p
ACME	−0.002	[−.009, .001]	0.11	0.001	[−.001, .005]	0.13	0.0003	[−.0006, .004]	0.11
ADE	−.003	[−0.01, 0.002]	0.10	0.003	[−.0001, 0.007]	0.06	0.001	[−0.002, 0.005]	0.10
Total effect	−0.005	[−0.01, 0.002]	0.04	0.004	[.00001, 0.008]	0.02	0.001	[0, 0.006]	0.04

Note. ACME = Bootstrapped average causal mediation effect; ADE = Bootstrapped average direct effect (with mediator held constant); Total effect = Bootstrapped direct effect of the independent variable on the outcome without mediator included; 95% CI [LL, UL] = Bootstrapped 95% confidence intervals for mediation effects [LL = lower limits, UL = upper limits]; p = Bootstrapped p-values associated with the type of effect; Sample size used = 64; Simulations = 1000.

Table 4. Comparison of fit parameters for mediation models.

	Model [95% CI]	Mediated model [95% CI]
ALS	0.12*	0.09
	[ 0.02; 0.22]	[−0.01; 0.18]
MTSE	-	0.11**
		[ 0.04; 0.18]
AIC	139.35	131.15
BF	-	20.48
LRT	-	10.20***
Num. obs.	64	64

Note. ALS = Attitudes towards self-development in Lesson Study. MTSE = Mathematics teaching self-efficacy. AIC = Akaike information criterion. BF = Bayes factor. LRT = Likelihood ration test. Num. obs. = Number of observations.

*p < .05. **p < .01. ***p < .001.

Clivaz, S., and A. Ni Shuilleabhain. 2019. “What Knowledge Do Teachers Use in Lesson Study? A Focus on Mathematical Knowledge for Teaching and Levels of Teacher Activity.” In Theory and Practice of Lesson Study in Mathematics: An International Perspective, edited by R. Huang, A. Takahashi, and J. P. da Ponte, 419–440. Cham: Springer International Publishing. https://link.springer.com/chapter/10.1007978-3-030-04031-4_20.

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