Original data from the Gardner and Williamson (2004) study are converted from EXCEL to
Stata 9.2 using Stat/Transfer 4. The initial analyses extract descriptive statistics and other
related cross-tabulations. Ordinary least squares (OLS) regressions are run to estimate the
number of activities undertaken by teachers, and capture the parameters of simple time
budget equations across activities and days of the teaching week. For ease of managing the
data, deriving important variables as suggested by theory and past empirical findings, and
using software that allows econometric estimations of relationships, the equations used in the
thesis are estimated using STATA 9.2. Additional qualitative variables are obtained, in the
form of dummy variables, using STATA. The econometric estimations based on time-budget
and time-share expenditures are conducted in STATA. The prevalence of dummy variables is
obviously noticeable, and represents an extensive use of qualitative dependent variables. The
prominence or prevalence of dummy variables, and qualitative dependent variables in the
qualitative research software such as NVIVO, and attempting to use key capabilities within
the STATA environment.
4.8 Conclusion
In this chapter, an empirical framework for modelling teacher time-use has been presented.
The framework supports the metaphor of the teacher’s thumbprint and recognises the impact of external and internal factors on teachers’ work. A system of equations and their derivations is provided to show the link among recorded diary data variables, expected and contractual
school times, weekend work and the extent of overload. The individual teacher has been
emphasised as the unit of analyses. The need to use qualitative and quantitative variables, a
suite of techniques, and several estimable equations has been put forward.
This thesis has so far added to the suite of theoretical models undertaken to contribute to an
understanding of time allocation behaviour of Tasmanian teachers. Two key concepts: time budgets and time shares are used; these two concepts are used to investigate time allocation to activities and days of the week. The equations relating time allocation to teacher and
school characteristics are estimated using the equation structure detailed above in sections 4.2
through 4.6, and summarised by equation 4.11, and its variations. Total weekly time
expenditure also is estimated. It is realised that weekly expenditures tend to be above the
required, official weekly outlay. As a result, the extent of teacher’s overload also is estimated. So, what is next? Clearly, the stage has been set to report some empirical findings in the next
chapter, Chapter 5. The technical aspects of the results have been pushed to the Appendices
in order to help with clarity, readability and interpretation of the results (see Appendices A
through H). A discussion of the empirical findings in the context of past evidence, new
evidence, and likely policy is deferred to Chapter 6. Concluding remarks relating to the
CHAPTER 5 RESULTS 5.1 Introduction
Time plays a crucial role in shaping society, and more specifically the teachers’ workloads.
The types of activities undertaken by teachers as they make their time allocation decisions are
important also in shaping societal outcomes and the realities of teachers’ work lives. In
Chapter 5 results of time allocation between and/or across teachers’ activities are reported.
The results are from a suite of econometric techniques developed and described in Chapter 4,
that are used for estimating the structural equations of the conceptual framework (teacher’s thumbprint) developed and presented in Chapter 3. Two key concepts are used: (i) the actual
allocation of time across activities, days, the teaching week and weekends; and, (ii) the
proportioned allocation of time across activities, days, the teaching week and weekends.
These two key concepts are referred to as the time budgets and time shares, respectively.
As developed in Chapter 1, time budgets measure actual hours of time expended on activities,
days, or typical week. The time shares are the relative use of time as part of the time budgets
in a typical day or week, and therefore time shares simply reflect the proportion of time
allocated by a teacher to a day’s activities relative to the weekly activity time budget
(endowment/expenditure). In that regard, the relative share of the daily time budget is
measured by the proportion of daily time budget in total time budget for the week. These
relative shares will be referred to, throughout the thesis, as time shares. Similarly, the amount of time allocated to an activity, by a teacher, will be referred to as an activity time budget.
The proportion of time allocated to each activity, expressed as a fraction of total activity time
budget will be referred to as the activity time share. The activity time share measures,
therefore, the proportion of the total time budget for the week that is allocated to each activity
a typical week, and time shares depend on the total time allocated to all activities on a given
day. Therefore, daily time shares are not activity-specific, whereas activity time shares are
activity-specific. This reminder assists in the linking of the results presented in this chapter
with earlier theoretical work on the teacher’s thumbprint, in Chapters 1 through 4. Therefore,
consistent with the framework of the teacher’s thumbprint provided in earlier Chapters – the
results of the empirical, inferential analyses of time budgets and time shares are presented in
this chapter.
In the analyses of activity patterns of teachers, descriptive and inferential analyses of time
allocation and activity budgets and time shares are presented. Differences in time allocation
and activity times across selected demographic variables are also examined, empirically.
Tetrachronic correlations are employed to ascertain any linear correlations between selected
variables that may influence the allocation of time. The tetrachronic correlations are used to
identify variables that are related linearly instead of the usual Pearson correlations because
several dummy variables for categorical variables (limited dependent variables) have been
constructed (see Stata 9.2). The results of the correlation analyses are used to guide the
choice of variables that are suitable for inclusion in the empirical model of time allocation.
The empirical model of time allocation then uses ordinary least squares (OLS), multivariate
regressions (MVREG), seemingly unrelated regressions (SUREG), instrumental variable
regressions (IVREG), and errors in variables (EIV) regressions to establish the extent of the
dependence of time allocation on a host of selected variables. The results thereof address the
key research objectives and questions of the thesis.
The results reported in this Chapter are presented as follows: A list of selected variables used
in this thesis, and summary statistics thereof, are presented in Section 5.2. This list includes
variables describing teacher demographics, activities of teachers, school factors, teacher
Gardner and Williamson (2004). These derived variables are mainly in the form of dummy
variables and other selected aggregates such as the number of hindering factors identified by
the teacher.
Analyses of actual and relative daily hours expended by primary school teachers during a
typical week are presented in Section 5.3. The analyses of time allocation focuses only on
teachers’ time allocation (expenditure) – time budgets, time shares and the number of activities performed by the teacher. The time shares of relative use of actual daily hours
expended by primary school teachers during a typical week also are presented. Time spent on
activities during a typical week, and the relative time spent by teachers on various activities,
reflect, therefore, the allocation of time across activities and across days.
Section 5.3 presents also the descriptive analysis of actual daily hours spent by primary
school teachers during a typical week, as well as the share of daily time allocation relative to
the total hours expended by each teacher during a typical week. The analysis of daily time
budgets and time shares is presented in Section 5.3.1. The type and number of activities
performed by teachers are presented in Section 5.3.2. How these activities are performed by
teachers in different age groups is presented in Section 5.3.3. Similarly, the statistical
dependence of the size of class taught by a teacher and the number of activities undertaken by
the teacher is examined and presented in Section 5.3.4. Clearly the number of statistically
dependent connections that can be established between teachers’ activity patterns and school
variables, in this study, is extensive. For the sake of brevity, Section 5.3.5 presents a
summary of tests of various statistical dependences or likely connections between teacher
activity, and school variables and teacher variables. The tests for these connections are
Section 5.3 is followed by Section 5.4. Section 5.4 reports the results of the analysis of
primary teachers’ time budgets and time shares. This analysis is based on actual time spent on each activity undertaken by the teacher. These activity times are then re-examined by looking
at the relative shares of time spent on each activity.
It is noteworthy that the results presented in Section 5.2 through 5.4 have so far focused
mainly on univariate analyses and limited bivariate analyses, in the form of chi-square tests
of statistical independence. These results give a general picture of primary teachers’ time
allocation across days, and also across activities. The results presented in Section 5.2 through
5.4 show variations in hours allocated over the days of the week and activities, and also
variations in time shares across days of the week, and across activities. It is, therefore,
imperative to conduct, inferential analysis of the observed variations in primary school
teachers’ time allocation. To that end, results on the inferential analysis of time allocation behaviour of primary school teachers are presented in Section 5.5, by examining differences
in allocation of time budgets and time shares. In Section 5.5, pair-wise differences in daily
time budgets and time shares are computed and presented for all teachers, as well as for full-
time, and other full-time equivalent (FTE) teachers (0.5 and 0.8).
In Section 5.6, differences in teacher time allocation by key teacher variables, such as age,
employment status, and teaching experience, as covered in the literature, are considered. The
results highlight any significant differences in time allocations by teachers’ in different age
categories (Section 5.6.1), employment status (Section 5.6.2), kindergarten teaching only
(Section 5.6.3), primary teaching only (Section 5.6.4), length of teaching experience (Section
5.6.5), and teaching out of area of expertise (Section 5.6.6). Section 5.7 reports results on the
variation of time allocation by teachers under different selected school characteristics. The
selected school characteristics include school size (Section 5.7.1), small versus large schools
Tetrachronic correlations are presented in Section 5.8. Only those correlations that are
significant at the 5 percent level are reported. These correlations are between: the number of
teaching activities and time budgets and time shares (Section 5.8.1), respective time budgets
are presented (Section 5.8.2), and respective daily shares are presented (Section 5.8.3).
Sections 5.8.1 through 5.8.3 are followed by an examination of correlations between time
budgets and time shares, in Section 5.8.4. The correlations between time shares and selected
activity variables are reported in Section 5.8.5. The correlations between time shares, school
variables, and variables that capture how teacher perceive school management and education
reforms are reported in Section 5.8.6. The correlations in Section 5.8.1 through Section 5.8.6
set the scene for investigating the determinants of: (i) the number of activities undertaken by
teachers, (ii) activity time budgets and activity time shares, (iii) daily time budgets and time
shares, (iv) weekly time-use, and (v) the extent of teacher overload.
Determinants of the number of activities undertaken by teachers are then presented in Section
5.9. These determinants of the number of activities undertaken by teachers are examined
using the set of explanatory variables identified from correlation analyses and Ordinary Least
Squares (OLS) estimation. Determinants of time budgets and time shares identified using
OLS, MVREG, SUREG and IVREG regression techniques are reported in Section 5.10.
Determinants of teacher overload are reported in Section 5.11. The reported results are based
only on the EIVREG estimation technique. A reliability factor that is useful in comparing and
contrasting the results of EIVREG to those obtained from OLS is presented also. The impact
of uninterrupted breaktime (UBT) on teachers’ time allocation behaviour is presented in Section 5.12. Concluding remarks are drawn in Section 5.13.
5.2 Descriptive Statistics of the Sample of Primary School