International aid and education reform and the paradox of implementation: a case study of the Philippines.
Reyes, Vicente, Jr.
INTRODUCTION
The Philippine Department of Education (DepEd) is the biggest
bureaucracy in the nation (Abad, 2005). Its sheer size makes it unwieldy
and complemented by an even bigger demand from a burgeoning population,
DepEd becomes highly inefficient and ineffective (Chua, 1999; Reyes,
2009b). The clamour for reform particularly in devolving and
decentralizing powers to those that could make the most impact have been
made about highly centralized education systems that have proven to be
ineffective in delivering their mandated services (Cuban, 1990; Tyack
& Cuban, 1997). Alongside the need to decentralize is the equally
important question about the readiness (or the lack of it) among
stakeholders in education who have received devolved and decentralized
powers. To this end, there is a growing body of literature both
Philippine-based and international that points towards the promise of
empowered stakeholders (Bautista, 2000, 2003; Reyes, 2015). Chua's
journalistic expose, about the scandals surrounding textbooks and other
learning materials, validated what had been described by textbook
publishers, DepEd officials, parents and Non-Government Organization
(NGO) watchdogs about resources and procurement procedures at the
Department: inefficient, ineffective and exacerbated with irregularities
and oftentimes blatantly corrupt (Chua, 1999, 2001, 2003; Reyes, 2009a).
More studies about the allegations of corruption and faulty governance
about DepEd followed, further confirming and validating the issues
raised by Chua (Carino, Iglesias, & Mendoza, 1998; Reyes, 2010), for
example:
The persistence of issues for much of the 20th century and into the
first decade of the 21st century highlight a distressing paradox--with
its long tradition of critical assessments and reform-oriented planning,
DepEd actually incubated, tested and proved the effectiveness of
numerous reform initiatives, some of them ahead of the discourses of
their time. Yet, at the start of every school-year, print and broadcast
media project without fail, a perpetual education crisis that the
mainstreaming of successful reform initiatives could have addressed
(Bautista, Bernardo, & Ocampo, 2008, p. 5).
One of the contemporary examples of 'successful' reforms
has been the Strengthening Implementation of Visayas Education (Project
STRIVE), a joint initiative of DepEd and the Australian Aid Agency
(AusAID). This inquiry is designed to interrogate the issues of
implementation that can be derived from the experience of STRIVE. Using
available data on a population of all the participating schools and
focusing on the levels of 'pilot implementation' of the STRIVE
components several discussion and thinking points are raised. This
inquiry is divided into three main sections. The initial part outlines
the research premise which is an elaboration of the variances in the
project outputs of STRIVE components in all the participating schools.
The second section presents the succinct findings from cross-tabulations
analyses of key dependent and independent variables in an effort to
detect relationships between project inputs and outcomes. The third and
final part presents a discussion and reflection of the findings with a
critique of the success of STRIVE implemented reforms.
Reform in the Philippines
Scholars and practitioners involved in Philippine education have at
their disposal a repository of critical studies that identify the most
serious challenges facing reforms of Philippine education. The
pioneering 1991 Education Commission (EDCOM) study, the equally
influential 1999 Presidential Commission on Education Reform (PCER), and
the landmark 2006 Basic Education Sector Reform Agenda (BESRA) have
comprehensively identified the obstacles that have perennially plagued
Philippine education--and have even suggested possible paths to
transformation. Using findings from a reform initiative formed through a
partnership between the Philippine government and AusAID, this inquiry
focuses on implementation paradoxes that accompany education reform.
AusAID, the Paris Declaration and reform in the Philippines
International organisations undertaking development work in the
Philippines including AusAID have categorically declared that their
programmes are aligned with the Paris Declaration. Five key principles
underpin this statement: (1) ownership, (2) alignment, (3)
harmonization, (4) managing for results and (5) mutual accountability.
The Organisation for Economic Cooperation and Development (OECD) argues
that the Paris Declaration is not merely a statement of good intentions
but actually can make a difference (OECD, 2006, p. 50). AusAID is a
signatory to the Paris Declaration. In an independent evaluation of
AusAID's Aid Effectiveness, it has been determined that all
programmes are implementing the principles of the Paris Declaration in
some form (AusAID Office of Development Effectiveness, 2010, p. 6).
Australia and the Philippines have had formal diplomatic relations
since 1946 (Carter, Funnell, & Rogers, 2012). Official Development
Assistance (ODA) from Australia to the Philippines commenced in 1983
with the establishment of the Australian Centre for International
Agricultural Research (ACIAR) designed to improve the attractiveness of
Philippine agricultural products (Carter et al., 2012, p. 8). Starting
in mid-2000, AusAID's ODA to the Philippines saw a significant
increase in education aid. During that time, education was the best
performing sector of Australia's aid engagement in the Philippines
as evidenced by the success of education reform projects such as the
Basic Education Assistance in Mindanao (BEAM) in coordination with the
Philippine's DepEd (Carter et al., 2012, p. xii). Independent
scholars have acknowledged the achievements that AusAID has experienced
particularly in the area of policy focus and engagement in education
reform:
Policy engagement occurs through the continued assistance of the
Support to Philippine Basic Education Reform (SPHERE), engagement in the
Philippine Development Forum (PDF), and through a 6-monthly BESRA
Review, that is jointly undertaken by DepEd and education donors. AusAID
contends that its projects contribute to the implementation and
framework of BESRA, and that the SPHERE Trust Fund supports policy
development, resources, for schools and classroom construction, and
financing of activities for resource management and mobilization of
BESRA. These aims are consistent with the Paris Declaration Alignment
indicator of donors using strengthened country systems, particularly
through reviews conducted through BESRA. This policy focus makes clear
endeavours to meet the Alignment target of the Paris Declaration, and
specifically through the indicator of aligning with partners'
strategies (Cassity, 2010, p. 515)
However scholars and practitioners of international development
assistance are more circumspect in declaring that education
reforms--including those of AusAID--have indeed been successful. One of
the phenomenon that dampens declarations of success is
'projectisation'. AusAID's efforts in the Philippines
manifests this when a pilot project to support national education reform
becomes the most outstanding feature of AusAID's education program
(Cassity, 2010, p. 510). Projectisation becomes problematic when scaling
up or sustaining reforms wanes when external support dries up or when
the actors involved in the project no longer sustain the implementation
after the completion of the project (Malana, 2009, p. 5). In the
Philippine case, a more serious criticism of Australian ODA appears when
despite AusAID's policy discourse confirming its commitment to
Paris and other processes what happens instead is that a large portion
of its education program funds scholarships hinting that the Australian
higher education lobby has an undeniable influence in ODA use and the
nation's international education policy (Cassity, 2010, p. 511).
For the year 2013/14 for example, education received the second highest
allotment (21%) in Australia's aid framework. A closer examination
of the breakdown of this education assistance reveals that for 2013/14,
close to AUS$310 million of the AUS$978 million (or 33%) of the
education budget went into the Australia Awards programme (Department of
Foreign Affairs, 2015). The Awards programme essentially consists of
tertiary scholarships at Australian higher education institutions. It is
worth noting that for the year 2014/15, education will be receiving the
highest allocation (23%) in Australia's aid framework (Department
of Foreign Affairs, 2015). This inquiry argues that the success of the
aid programme embodied in STRIVE, as seen from the lens of rural
Philippines is complex and needs a more nuanced perspective.
STRENGTHENING IMPLEMENTATION OF VISAYAS EDUCATION (STRIVE)
STRIVE Stage 1 was an 18 month project between October 2005 and
July 2007 costing about AUS$3.9 million dollars (AusAID, 2006, p. 1).
STRIVE was targeted to address the dire education needs of the
predominantly rural provinces found in the Visayas region of the
Philippines. Visayas--a collection of islands within the
Philippines-which has a population of 11.3 million (National Statistics
Office., 2010) contains roughly a tenth of the entire population of the
country. These islands consist of three main regions: Central (Region
VII), Western (Region VI) and Eastern (Region VIII) Visayas. Central
Visayas has a total population of 6.4 million people and a population
density of 345 people per square kilometer. Almost half of the
population in Region VII live in urban areas. The incidence of poor
families in Central Visayas is 24 per cent higher than the national
average (De la Paz & Colson, 2008). Western Visayas, where 70 per
cent of the population resides in rural areas, and Eastern Visayas, with
80 per cent of its population found in rural settings are two other
regions whose poverty rates are considerably higher than the national
average (Albert & Collado, 2004).
STRIVE attempted to improve basic education in these impoverished
and predominantly rural regions. One of the indicators identified as
evidence of improved education outcomes was the National Achievement
Test (NAT). Interestingly, these three regions have contrasting
performances in relation to the NAT. In 2009, out of a total of 205
School Divisions distributed nationwide, three school divisions from
Region VIII were in the top five NAT performers. In the same year, two
school divisions each from Region VI and Region VII were in the bottom
10 NAT performers (Department of Education., 2010)
The NAT is a 'Philippine-made standardized test' created
to measure achievement levels, strengths and weaknesses of students in
five subject areas (Benito, 2010, p. 6). These five areas are: (1)
Science, (2) Mathematics, (3) English, (4) Filipino and (5)
Geography-History-Civics (for elementary) (1) or Social Studies (for
high school) (2) (Benito, 2010). The DepEd considers NAT as a timely
device for assessing students' learning:
The NAT, which is a system-based assessment, was specifically
designed to gauge learning outcomes across target levels in identified
periods of basic education. In particular, it spans from mid-assessment
of elementary education which falls on the third grade, and then to a
terminal exit assessment which falls on the sixth grade. The test
results in NAT-Grade Six can likewise serve as measurement of incoming
first year students' readiness for high school. On the other hand,
the NAT for Second Year high school serves as mid-assessment of the
secondary level. (Benito, 2010, p. 12)
The STRIVE project was designed as a flexible and responsive
mechanism to assist the DepEd in improving access to and the quality of
basic education in the Visayas and in so doing improve education
outcomes for the regions' young people. Stage 1 was implemented
from October 2005 to July 2007 and focused on Bohol (Region VII) and
Northern Samar (Region VIII) divisions. Activities were undertaken in
two main components, the Leadership and Management Development and
Programs for Out of School Children, Youth and their Families with a
view to implementing two other components (Teacher Training and
Teaching/Learning Materials Development) (Leonardo-Ong, 2005).
STRIVE Stage 2 was designed as a vanguard initiative which aimed to
develop and test support systems for School-Based Management (SBM),
Human Resources Development (HRD) specifically In-Service Education and
Training (INSET) and the equitable provision of Learning Resource
Materials (LRM). STRIVE Stage 2 was estimated to cost AUS$15 million to
Australia with the Republic of the Philippines matching this with a Ps
128 million peso counterpart funding (AUS$3.6 million) (AusAID, 2006, p.
28). The initiative was intended to be the precursor to widespread
implementation of the Basic Education Sector Reform Agenda (BESRA)
reforms by DepEd. STRIVE Stage 2 was envisioned to contribute to the
improvement in the quality of and access to basic education in the
Visayas. These goals would be achieved through the development, support
and strengthening of education management and learning support systems
for improved access to quality basic education. One of the intentions of
DepEd was to learn from the experience of key support systems developed
in the Visayas through STRIVE paving the way for these to be replicated
in other regions of the country and thus serving as a platform to
support BESRA implementation.
Starting Point: Variances in the Outputs of STRIVE Components in
Schools
Table 1 provides a snapshot of the variances in the levels of
'pilot implementation' of STRIVE components in all the schools
participating in STRIVE Phase 2.
Plans for Professional Development (Individual Professional Plans
and School Improvement Plans) are overwhelmingly present in the schools
(98%), followed by components pertaining to Quality Assurance (50%). It
must be pointed out that all Philippine schools starting from 2006 have
been mandated to complete School Improvement Plans (SIPs) as part of the
BESRA initiative (Department of Education, 2012). Professional
Development plans as well as initiatives to improve quality are integral
parts of the SIPs, these components effectively antedate the STRIVE
Programme. This could explain why these two components appear to be more
advanced in terms of implementation. Availability of SOBE funds,
Learning Resources, Training and Development and the start of
Information Systems are in 'pilot implementation' mode in
about 15 per cent of all the schools. Project Management has the lowest
'pilot implementation' exposure with eight per cent of all the
schools. One can argue that the dispersal of 'pilot
implementation' components of STRIVE in the schools can be argued
as evidence of the fragmented nature of the level of effectiveness of
the program
Intuitive Assumptions.
The overarching goal of STRIVE Phase 2 is to 'strengthen basic
education in the Visayas'. One of the indicators used to ascertain
improvements in basic education through the implementation of STRIVE is
the NAT performance of the specific regions. The goal is for the
components of School-based Management, Training and Development,
Learning Resources, Quality Assurance, Project Management, and
Information Systems to be intervening factors in ensuring that basic
education improves in the target areas. Therefore it may be posited that
'holding everything constant' the ideal scenario would be for
all the different STRIVE components to be operational in the
participating schools. Such an approach, complemented by the notion that
STRIVE is seen as the implementing catalyst for the BESRA of DepEd could
then be described--albeit in a simplistic fashion--as a trickle-down
approach in education reform (Ginsberg & Wimpelberg, 1987, p. 346).
There are two key facets to this approach: (1) BESRA as the
rational/prescription element and (2) STRIVE as the symbolic/ceremonial
element (Ginsberg & Wimpelberg, 1987, p. 358). The trickle-down
approach posits that these two elements give rise to an 'enabling
environment' where education reforms cascade down for eventual
implementation.
ANALYSING THE IMPLEMENTATION PERFORMANCE OF STRIVE:
CROSS-TABULATIONS
A Short Note on the Analytical Approach
In order to undertake this analysis, a non-experimental
correlational study (employing cross-tabulations) will be pursued as the
methodological approach of this inquiry. It can be argued that the
'rational/prescription' or the policy of different and
multiple STRIVE Components piloted in schools determines whether
specific sub-components of STRIVE reach the stage of 'pilot
implementation'. This 'trickle-down' education reform
approach is tested in the subsequent sections of this paper with the use
of contingency tables also referred to as cross-tabulations analysis
based on the entire population of STRIVE participating schools (N=308)
in Region VI, VII and VIII. In the subsequent cross-tabulations, the
columns are treated as the independent variables and the row is seen as
the dependent variable. The universal hypothesis tested in the
cross-tabulations is that both variables are independent and have no
relation with each other. Moreover, these subsequent analyses
interrogate 'measures of association'--describing the strength
of dependence between two variables. In cross-tabulations, one of the
most powerful ways of interpreting measures of association is through
the Proportional Reduction of Error (PRE): quantifying the extent to
which the independent variable helps in predicting the dependent
variable (Liebetrau, 1993). Essentially the analyses establish
'correlation' among variables and therefore no attempt is made
to define causal relationships.
Analysis: STRIVE Components and Availability of SOBE Funds
The cross-tabulations produced statistically significant results
(approx. sig. for Gamma y is less than .05). An examination of the
absolute value of Gamma y (.54) means that there was a 54 per cent
reduction in error in predicting the dependent variable when the
independent variable was taken into account. In other words, the
statistically significant relationship between the dependent and the
independent variable is moderate. An interpretation of this could be
that information about the number of STRIVE components piloted in
schools greatly helps in improving the prediction of the outcomes of
'Availability of SOBE funds' ('No action' or
'Pilot implementation') by about 54 per cent.
Analysis: STRIVE Components and Training and Development
The statistically significant value of Gamma (.97) means that there
was a 97 per cent reduction in prediction error. One can argue that the
relationship between the dependent and the independent variable is very
strong and that information about the number of STRIVE components
piloted in school greatly helps in improving the prediction of
'Training and Development' ('No action' or
'Pilot implementation') by about 97 per cent. More STRIVE
components implemented correlates with the high incidence of Training
and Development carried out in schools.
Analysis: STRIVE Components and Learning and Resources
The statistically significant value of Gamma (.98) signifies a 98
per cent reduction in prediction error of the dependent variable
(Learning and Resources) taking into consideration the independent
variable (Number of STRIVE Components piloted in schools) revealing a
very strong relationship between the variables. Furthermore it can be
postulated that the number of STRIVE components piloted in school
greatly helps in improving the prediction of the 'learning and
resources' ('No action' or 'Pilot
implementation') by about 98 per cent.
Analysis: STRIVE Components and Project Management
Gamma (.61) reveals a statistically significant 61 per cent
reduction in predictive error of the dependent variable (Project
Management) pointing out a moderate relationship between the variables.
Furthermore it can be claimed that the number of STRIVE components
piloted in school greatly helps in improving the prediction of
'project management' ('No action' or 'Pilot
implementation') by about 61 per cent. More STRIVE components
implemented translates to project management promulgated in schools at
an average pace.
Analysis: STRIVE Components and Quality Assurance
Gamma (.94) signifies a 94 per cent reduction in prediction error
of the dependent variable (Quality Assurance) taking into consideration
the independent variable (Number of STRIVE Components piloted in
schools). It can be argued that the statistically significant
relationship between the dependent and the independent variable is very
strong; it can even be suggested that the number of STRIVE components
piloted in school greatly helps in improving the prediction of the
'Quality Assurance' ('No action' or 'Pilot
implementation') by about 94 per cent.
Analysis: STRIVE Components and Information System
The statistically significant value of Gamma (.87) signifies an 87
per cent reduction in prediction error as well as a strong relationship
between the dependent and the independent variables. It can even be
suggested that the number of STRIVE components piloted in school greatly
helps in improving the prediction of the 'Information System'
('No action' or 'Pilot implementation') by about 87
per cent.
Analysis: STRIVE Components and Plans for Professional Development
Cross-tabulations produced statistically significant results
(approx. sig. for Gamma [gamma] is less than .05). For this particular
factor, the results produce a negative value of Gamma (-.59) signifying
a moderate negative association as opposed to all the other preceding
factors that have registered positive associations. According to this
data, when the 'Number of strive components piloted in school'
goes higher, 'Pilot implementation' for Plans for Professional
Development is lower due to the negative association. This moderate
negative interaction is useful in predicting the inverse relationship
between 'Plans for Professional Development' ('No
action' or 'Pilot implementation') in schools by about 59
per cent. As explained earlier in Table 1, Plans for Professional
Development form part of the SIPs in all Philippine schools when it was
introduced in the BESRA roll-out in 2006. This component antedates the
implementation of the STRIVE reform initiative and could be one of the
explanations for the negative interaction.
DISCUSSION AND REFLECTION POINTS
The preceding preliminary cross-tabulations analyses provide
insightful perspectives on how policy prescription represented as
'Different STRIVE components piloted in schools' determine
whether specific sub-components reach 'Pilot implementation'
stage. Using data from the population of STRIVE participating schools in
rural contexts located in Regions VI, VII and VIII and the foregoing
analyses which exclusively used 'Measures of association', it
can be argued that the policy prescription of piloting multiple STRIVE
components predict (i.e. 'is correlated') to a statistically
significant level (i.e. 'not to chance') the actual
'Pilot implementation' of individual STRIVE sub-components.
The explanations up to this point may seem extremely tautological;
what must be noted though is that the levels of 'measures of
association' (i.e. represented by Gamma y between the different
variables produced interesting and varied results).
Relevance
These findings support to some extent the issue of relevance of the
STRIVE program. Using the current approach of making available the
different components of STRIVE does have a positive impact on the
eventual implementation of sub-components. Assuming that the STRIVE
components have been identified as those that would address the
education demands of the predominantly rural regions, one can argue that
the programme's attempts to address the key needs in the Visayas
appears to be on-track.
Effectiveness
On School-based Management (SBM). Two of the STRIVE components
could very well be identified as indicators of SBM, namely: (1)
Availability of SOBE Funds--represented as the knowledge and skill of
the school management to be able to tap into, source and generate funds
and (2) Plans for Professional Development--that are included in the
respective School Improvement Plans (SIPs) prepared by the STRIVE
participating schools. Table 9 indicates that 'Availability of SOBE
Funds' has a moderate association (54%)--but the lowest among all
the other measures in relation with the independent variable:
'Number of STRIVE Components Piloted in Schools'. Moreover,
'Plans for Professional Development' (-59%) has a moderate
relationship but more importantly a negative association with the same
independent variable--'Number of STRIVE Components Piloted in
Schools'.
What the findings reveal is that 'Availability of SOBE
Funds' is only moderately associated with the other STRIVE
components. It could mean therefore that other objectives--not within
the specific parameters of STRIVE--are targeted by the school leaders
when they pursue SOBE funds. The findings also reveal that the
'Plans for Professional Development' has a moderate but
negative association with the other STRIVE components. In other words,
presence of these 'plans' do not contribute in increasing the
number of piloted STRIVE components in schools. Similar to the SOBE
funds one can assume that these plans do not specifically target the
objectives within the STRIVE parameters, moreover in the case of Plans
for Professional Development, these have already been set in motion even
before the implementation of STRIVE. These findings indicate that SBM
within STRIVE merits a more careful analysis.
On Training and Development (T&D) and Learning Resources (LR).
From the results in Table 9 one can glean that the T&D component
(98%) registered the highest measure of association with the independent
variable. This is closely followed by Learning Resources (97%). Both
factors have very strong positive associations with the independent
variable. According to the data, this means that an increase in the
'Number of STRIVE components' is accompanied by increases in
T&D and LR pilot implementation. In other words the objective of
promoting T&D and LR in schools is greatly supported by allowing an
enabling environment where all the STRIVE components are pushed towards
pilot implementation.
On Project Management (PM), Information Systems (IS) and Quality
Assurance (QA). Results compiled in Table 9 indicate that Project
Management (94%), Information Systems (87%) and Quality Assurance (61%)
had strong to moderate positive associations with the independent
variable. Similar to T&D and LR, these components of STRIVE are
promoted to a great extent when a policy that enables these elements to
be piloted is vigorously pursued.
Impact of STRIVE
A very difficult criterion to address in implementation reviews
deals with the question on the impact of programmes. Evaluating impact
becomes even more complex when projects under review are in a bridging
phase where the outputs are very much interrelated to inputs and
therefore concrete indicators of outcomes are usually elusive. Perhaps
the most important question to ask about evaluating impact would be
attributing success or failure due mainly to the implemented programme.
In other words, counterfactual conditions or factors that could have an
impact on implementation need to be properly accounted for in order to
clearly establish the contribution attributed solely to specific
programs (Ferraro, 2009). In order for this to happen careful planning
and groundwork in terms of specific program goals, precise
implementation phases and well-calibrated monitoring tools should have
been established during the conception and early stage program
execution. Another possible way is to review current outputs and conduct
analyses using quasi-experimental approaches. The following tables
attempt to do these analyses by hypothesizing a relationship between
National Achievement Test (NAT) scores (an ordinal variable) and Region
(a polytomous-ordered variable).
Cross-tabulations produced statistically significant results
(approx. sig. for Gamma y is less than .05). An examination of the
absolute value of Gamma (.90) signifies a 90 per cent reduction in
prediction error of the dependent variable taking into consideration the
independent variable. It can be argued that the statistically
significant relationship between the dependent variable (NAT scores) and
the independent variable (Region) is very strong. It can even be
suggested that Region greatly helps in improving the prediction of the
'NAT Scores' ('Low'; 'Average',
'High') by about 90 per cent.
Table 10 highlights that the greatest proportion of NAT scores in
the STRIVE target regions belong to the 'Low' category (64 and
below) accounting for 51.4 per cent. NAT scores in the
'Average' category (65-79) constituted 33.7 per cent. This is
completed by the NAT scores in the 'High' category (80 and
above) which make up 14.9 per cent.
In terms of determining impact what would be more insightful would
be to add STRIVE Components (as a controlling variable) to the existing
variable Region and see how this addition makes an impact on the NAT
scores. In order to arrive at a 'neater' table, the STRIVE
Components variable was recoded into three categories: Limited (1-2
STRIVE components piloted); Moderate (3-4 STRIVE components piloted) and
WIDE (5-6 STRIVE Components piloted).
Performing cross-tabulations between NAT scores and Region plus the
controlling variable STRIVE components produced statistically
significant results where approx. sig. for Gamma [gamma] is less than
.05. Examining the absolute values of Gamma [gamma] for Limited Pilot of
STRIVE Components (.90) and Moderate Pilot of STRIVE Components (.90)
signifies a 90 per cent reduction in prediction error of the dependent
variable (NAT scores) taking into consideration the controlling effect
of the additional variable (STRIVE). The more significant figures to pay
attention to would be the differences in percentage scores from the
zero-order table 10 and the three partial tables (Table 11).
Table 11 indicates that Limited STRIVE pilot implementation in the
target regions does not have an impact on the NAT scores distribution
since the total column scores are almost identical to those found in the
zero-order table 10. However, inspecting the partial table for Moderate
STRIVE pilot implementation (particularly the epsilon [epsilon] or
Percentage Point change) reveals a small impact. The partial scores
improved with the controlling variable of Moderate STRIVE pilot
implementation: 'Low' NAT scores decreased by 4.2 per cent;
'High' NAT scores increased by 5.9 percent. The
'Average' NAT scores decreased slightly by 1.8 per cent. An
inspection of the partial table for Wide STRIVE pilot implementation
reveals across the board deterioration in the epsilon [epsilon] scores:
'Low' NAT scores increased by 11.8 per cent,
'Average' NAT scores decreased by 7.4 per cent and
'High' NAT scores also decreased by 4.4 per cent.
In other words, Table 11 reveals that the impact of the program on
NAT scores, vary according to the degree of pilot implementation of the
STRIVE components. The data suggests that Limited STRIVE pilot
implementation has almost no impact; Moderate STRIVE pilot
implementation, has a marked positive impact on the outcome
variable--NAT scores while for Wide STRIVE pilot implementation the
impact seems to be negative.
An essential point that needs to be considered in interpreting
these results is the life-cycle of STRIVE Phase 2. Bearing in mind, that
STRIVE Phase 2 has reached a post-bridging period; the findings in table
11 would seem quite reasonable. Where the components of STRIVE are
merely at the start-up phase, the impact is negligible. In situations
where the STRIVE components have been rolled out; the figures indicate
positive impact. And more importantly, where STRIVE components are at
the verge of 'wider implementation', this critical transition
point seems to be represented by negative impact on the outcome
variable--deteriorating NAT scores. These key discussion points
naturally beg the question of the sustainability of implementing such a
project.
Sustainability of STRIVE as Education Reform and the implementation
paradox
Tables 10 and 11 provide illumination in addressing the question of
sustainability. Recognizing the epsilon e or Percentage Point changes
between the zero-order table and the partial tables reveal that
'Number of STRIVE Components piloted in schools' creates an
interaction effect. This inquiry argues that an implementation paradox
emerges upon closer examination of the experience of STRIVE. The
progress that is expected of a more widespread implementation of STRIVE
components follows an almost counterintuitive path. The data reveals
that Moderate pilot implementation is a condition that strengthens the
original relationship: Region determining NAT scores. Conversely, the
data also indicates that Wide pilot implementation is a condition that
weakens the original relationship. The analyses also points to the fact
that Limited implementation is a condition that neither strengthens nor
weakens the original relationship.
[FIGURE 1 OMITTED]
Recalling the principles of the Paris Declaration that prescribes
an almost linear perspective of effectiveness: Ownership (developing
countries set their own targets)--Alignment (donor countries align
behind these targets)--Harmonisation (donor countries coordinate to
simplify and avoid duplication--Results (developing countries and donors
shift focus to development results) and Mutual accountability (donors
and partners are accountable for results) (OECD, 2006), the non-linear
implementation trajectory of STRIVE does not fit this paradigm. The
international development community which includes AusAID as signatories
of the Paris Declaration have adopted Managing-for-development-results
(MfDR) as an overarching means to assure improved development
effectiveness (Armytage, 2011, p. 266). One of the biggest critiques
against MfDR is that it is built on managerial logical frameworks of
evaluation. Reflecting on the experience of STRIVE and using the
benchmark of MfDR implied in the Paris Declaration, one recognises an
implementation paradox and one may even conclude that such a project
would be ineffective (i.e. increased inputs for implementation translate
to negative outcomes) and thus not sustainable. One important argument
that this inquiry raises is the need to recognise possible limitations
of development models in attempts to address highly-contextualised
issues found in developing countries with large rural populations such
as the Philippines. Moreover, the empirical analyses conducted in this
inquiry were based on quantitative results. Qualitative data in the form
of the actual practices that various stakeholders of the STRIVE project
such as AusAID staff and educators from the three diverse regions were
not included in this inquiry. This inquiry acknowledges that it suffers
from a lack of systemic documentation of the compromises, solutions and
efforts exerted by various stakeholders in pushing the STRIVE project
forward. This could be an area for further study that can be pursued by
scholars and practitioners keen on interrogating the implementation of
development aid and education reforms. In a way, this article engages
with an ongoing debate about the search for the so-called
'right' modes of implementation:
Despite the enormous energy devoted to generating the right policy
models, however, there is surprisingly little attention paid to the
relationship between these models and the practices and events that they
are expected to generate or legitimize in particular contexts (Mosse,
2004, p. 640)
This inquiry set out to provide a comprehensive empirical review of
the performance outputs of STRIVE. In so doing, a seeming implementation
paradox where additional inputs generate negative results was unearthed.
This article proposes a careful re-examination of implementation
analysis of education reforms in highly-complex contexts such as the
rural regions of the Visayas in the Philippines. This article also
problematises a fundamental ethos of the Paris Declaration of Aid
Effectiveness that may be limited due to its adherence to MfDR--a
managerial results-based paradigm built on logical frameworks of
evaluation.
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(1) This is referred to as Heografiya, Kasaysayan at Sibika or
HEKASI in the Philippines.
(2) This is referred to as Araling Panlipunan in the Philippines.
Table 1. Table of Frequencies STRIVE Components in Schools
Count % No action Pilot implementation
Availability of Support Options for 85.1 14.9
Basic Education (SOBE) Funds
Learning Resources 83.8 16.2
Training and Development 83.8 16.2
Plans for Professional Development 1.9 98.1
Quality Assurance 50.0 50.0
Project Management 91.9 8.1
Information System 82.5 17.5
Source: Information provided by STRIVE Project
Table 2: STRIVE Components and Availability of SOBE Funds
Count %
Number of STRIVE Components
piloted in School
Availability No action 111 75 39 19 15 3 262
of SOBE Pilot 0 20 16 6 2 2 46
implementation
Funds Total 111 95 55 25 17 5 308
[gamma] = .54; p = .000
Source: Information provided by STRIVE Project
Table 3: STRIVE Components and Training and Development
Count %
Number of STRIVE Components
piloted in School
Training and No action 111 93 46 8 0 0 258
Development Pilot 0 2 9 17 17 5 50
implementation
Total 111 95 55 25 17 5 308
[gamma] = .97; p = .000
Source: Information provided by STRIVE Project
Table 4: STRIVE Components and Learning and Resources
Count %
Number of STRIVE Components
piloted in School
Learning No action 111 94 46 7 0 0 258
Resources Pilot implementation 0 1 9 18 17 5 50
Total 111 95 55 25 17 5 308
[gamma] = .98; p = .000
Source: Information provided by STRIVE Project
Table 5: STRIVE Components and Project Management
Count %
Number of STRIVE Components
piloted in School
Project No action 111 85 49 23 13 2 283
Management Pilot 0 10 6 2 4 3 25
implementation
Total 111 95 55 25 17 5 308
[gamma] = .61; p = .000
Source: Information provided by STRIVE Project
Table 6: STRIVE Components and Quality Assurance
Count %
Number of STRIVE Components
piloted in School
Quality No action 111 35 5 2 1 0 154
Assurance Pilot implementation 0 60 50 23 16 5 154
Total 111 95 55 25 17 5 308
[gamma] =.94; p = .000
Source: Information provided by STRIVE Project
Table 7: STRIVE Components and Information System
Count %
Number of STRIVE Components
piloted in School
Information No action 111 91 31 16 5 0 254
System Pilot 0 4 24 9 12 5 54
implementation
Total 111 95 55 25 17 5 308
[gamma] = .87; p = .000
Source: Information provided by STRIVE Project
Table 8: STRIVE Components and Plans for Professional Development
Count %
Number of STRIVE Components
piloted in School
Plans for No action 0 1 4 1 0 0 6
Professional Pilot 111 94 51 24 17 5 302
implementation
Development Total 111 95 55 25 17 5 308
[gamma] = -.59; p = .000
Source: Information provided by STRIVE Project
Table 9: Summary of Measures of Association
Factors (Dependent variable/s) * Independent Measures of
variable - Number of STRIVE Components Association %
(represented by
gamma [gamma])
Availability of SOBE Funds * No. of STRIVE 54
Components
Learning Resources * No. of STRIVE Components 97
Training and Development * No. of STRIVE 98
Components
Plans for Professional Development * No. of -59
STRIVE Components
Quality Assurance * No. of STRIVE Components 61
Project Management * No. of STRIVE Components 94
Information System * No. of STRIVE Components 87
Table 10: Zero Order Table: National Achievement Test (NAT)
Scores * Regions
Name of Region
Count % Region VI Region VII
within Region
Scores in the Low 91 42
National 91.9% 54.5%
Achievement Average 8 33
Test (NAT) 8.1% 42.9%
High 0 2
0% 2.6%
Total 99 77
100.0% 100.0%
Name of Region
Region VIII Total
Scores in the Low 9 142
National 9.0% 51.4%
Achievement Average 52 93
Test (NAT) 52.0% 33.7%
High 39 41
39.0% 14.9%
Total 100 276
100.0% 100.0%
[gamma] = .90; p = .000
Table 11: Partial Tables: (NAT) Scores * Regions * STRIVE Components
Name of Region (%)
Region VI Region VII
Limited: 1-2 Scores in the Low 90.6 55.2
STRIVE NAT Average 9.4 43.1
Components High 0 1.7
Total 100.0 100.0
Moderate 3-4 Scores in the Low 92.3 61.5
STRIVE NAT Average 7.7 30.8
Components High 0 7.7
Total 100.0 100.0
Wide 5-6 Scores in the Low 100.0 33.3
STRIVE NAT Average 0 66.7
Components High 0 0
Total 100.0 100.0
Name of Region (%)
Region VIII Total
Limited: 1-2 Scores in the Low 9.5 51.9
STRIVE NAT Average 54.0 35.1
Components High 36.5 13.0
Total 100.0 100.0
Moderate 3-4 Scores in the Low 6.1 47.2
STRIVE NAT Average 51.5 31.9
Components High 42.4 20.8
Total 100.0 100.0
Wide 5-6 Scores in the Low 25.0 63.2
STRIVE NAT Average 25.0 26.3
Components High 50.0 10.5
Total 100.0 100.0
