Dissertation locked

Tom Lake PI: B280823X May 2015
Is the GCSE National Curriculum
Appropriate for Disengaged
Students?
A Quantitative Study
K316- ExploringPractice

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CONFIDENTIALITY DISCLOSURE
This report was produced in 2015, in a Secondary School in South-West England. To
respect anonymity, the school involved will be identified as ‘the school’, whilst staff and
students identities will remain anonymous.
Word Limit Report: 5000 - Actual 5116
Action Plan: 2000 – Actual 1992
EXECUTIVE SUMMARY
A disengaged student can loosely be defined as one who ‘will do all they can to avoid
learning’ (Cooksley, 2014). This could be detrimental at a time where Year 9 students
are currently choosing their General Certificate of Secondary Education (GCSE)
qualifications that they will study in Key Stage Four (KS4).
Three groups of fifteen Year 9 pupils were randomly-sampled; those with behavioural
difficulties (disengaged), Special Educational Needs (SEN) (nurture) and a randomly-
sampled group (control), then questioned on subject preferences and justifications for
their choices. Current subject attainment levels were measured against mid-year
attainment grades from Year 7. The Year 7 to 9 difference was then added to create
predicted attainment scores for Year 11, then converted from National Curriculum 1-8
levels into predicted GCSE grades.
These predicted grades were compared to GCSE grades achieved by ex-Year 11s from
2013-2014, using the same randomly-sampled disengaged, nurture and control groups.
Results revealed GCSE grades of ex-Year 11 disengaged students were higher in subjects
with examinable practical components than academic-based subjects. Nurture students
exhibited a similar but reduced practical trait. Control students performed better in
academic subjects.

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Year 9 students’ projected GCSE grades mirrored these results, with disengaged
students predicted to achieve better in practical-based subjects. This report suggests
that current curriculum provision is failing disengaged students, recommending:
 Offering more vocational subjects and qualifications.
 Introducing more cross-curricular activities in academic subjects.
 Rotating teachers termly to avoid detrimental student-teacher relationships.
This report also acknowledges that both the data collected and subsequent analysis
have limitations. These include:
 All grades, bar actual GCSE results, are subjective and although moderated can
only act as guidelines to performance.
 Predicted grades cannot incorporate outside influences including health,
behavioural or lifestyle changes.
 Ninety students from one school in one geographical area is a low sample,
which cannot be generalized to represent demographic or national populations.
These limitations demonstrate that although results are fairly conclusive, the study
needs replicating on a wider scale to evaluate whether similar trends occur regionally
and nationally.

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TABLE OF CONTENTS
Executive Summary..................................................1
List of Figures and Tables.........................................4
Introduction .............................................................5
Literature Review.....................................................7
Methodology..........................................................13
Findings ..................................................................17
Discussion...............................................................21
Action Plan .............................................................22
Reference List:........................................................29
Appendix A – GCSE Subject Assessment Criteria...39
Appendix B – Year 9 Questionnaire.......................40
Appendix C – Monitoring Report Cover Letter ......42
Appendix D – Year 7-9 Monitoring Form Example 43
Appendix E - Year 7 to 9 Monitoring Data & predictions 44
Appendix F - Predicted and Actual GCSE Grades per Subject per Category 47

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LIST OF FIGURES AND TABLES
1. National Curriculum Levels to GSCE Conversion…p15
2. Predicting Grades Comparison…p16
3. Cumulative Subject Scores of Year 9 Students…p17
4. Year 9 Average Monitoring Grades, Winter 2014…p18
5. Mean Levels of Progress from Year 7-9…p19
6. Predicted GCSE A*-C Grades in Academic Subjects…p20
7. Predicted GCSE A*-C Grades in Practical Subjects…p20
8. Actual GCSE A*-C Grades Achieved in Academic Subjects…p20
9. Actual GCSE A*-C Grades Achieved in Practical Subjects…p20
10. Four Principles of Best Value…p28

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INTRODUCTION
In England, students in Year 11 undertake GCSE’s, the final assessments in Secondary
School before moving on to Tertiary Education or Apprenticeships. This report analyses
the relationship between prospective KS4 students informally classed as disengaged and
both their enjoyment and educational performance of both academic and practical-
based subjects.
It is hypothesised that:
‘Disengaged students prefer and perform better in practical-based subjects than
academic subjects’
Data was collected between December 2014 and April 2015. All monitoring data is grey
literature, based on subjective teacher opinion although cross-moderation provides
objectivity making it acceptable for use. The exception is the 2013-2014 GCSE results
used which are publicly available, albeit in an overview not individualised fashion.
Literature was researched between October 2014 and May 2015, using both systematic
and Boolean search techniques (The Open University, 2014a) in research articles, plus
other media sources including reports, books and news articles. Seventy-four articles
were reviewed, reduced to fifty-one after measurement against Walsh and Wigens’
critical evaluation model (2003, in the Open University, 2014b) based on validity,
funding and author credibility. International articles were used, demonstrating the
validity of intervening on a worldwide issue and acknowledging multi-national ideas on
both causes and subsequent techniques for tackling disengagement.
STUDENT DEFINITIONS
As students are a generalised population, creating explicit categories of students can
add clarity (vom Brocke and Rosemann, 2014, p580) and present different types of
student to analyse:
DISENGAGED STUDENTS

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Students exhibiting ten or more separate behavioural incidents, recorded on SIMS.net
(Capital Business Services, 2015), the school’s administrative management system.
These have occurred since the start of the 2014-2015 academic year (2013-2014 for ex-
students whose GCSE results have been used). Using ten or more separate behavioural
incidents increases the validity and dismisses the possibility of unfairness, providing
allowances for isolated incidents.
NURTURE STUDENTS
Pre-identified SEN students receiving additional support due to social, academic,
physical or emotional difficulties which impair their learning at the rate of their peers
(Makin, 2014, p3). Although sometimes students display characteristics of both learning
and behavioural difficulties, defining them separately can help to further explore the
demands of those with ‘behaviour that challenges’ and those with learning disabilities
or difficulties (National Institute for Health and Care Excellence, no date, p3).
CONTROL STUDENTS
Students with no SEN or behavioural support, randomly-sampled by an independent
body, offering the ability to compare against general populations. The random
allocation of control students also satisfies the requirements of true experiment
strategy (Robson, 2002, in The Open University, 2014, p12) further adding credibility
and reliability to the research.
SUBJECT CLASSIFICATION
For clarity, subjects have been categorised as either academic or practical subjects.
Whilst there are undoubtedly some hands-on elements in academic subjects, they have
been defined as:
PRACTICAL SUBJECTS
Subjects containing practical assessment components, such as performances,
coursework and production creation.

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NON-PRACTICAL SUBJECTS
Subjects of which assessment is in written terminal examinations only.
A comprehensive list of each KS4 qualification currently offered by the school and their
assessment criteria can be found in Appendix A.
LITERATURE REVIEW
The concept of disengaged behaviour was developed over thirty years ago (Natriello,
1984, pp14-24), collectively grouping individuals who for numerous reasons are not
engaged or involved in their work to the same degree as peers.
Relating specifically to children, disengagement can occur for several reasons, including
but not limited to academic ability, behaviour, emotional detachment and cognitive
development (Fredricks et al, 2004, in Foliano et al, 2010, p7; Jensen and Tuten, 2012,
p93). These can all contribute to a child’s social and academic development.
The availability of resources exploring the issue of student disengagement has increased
during the last decade, resulting in greater understanding and acceptance, although a
lack of understanding as to the causes. This lack of understanding (NHS Choices, 2013;
Kettlewell et al, 2012, p5) correlates to the lack of appropriate recommendations to aid
re-engagement, with evidence suggesting no universal response (Gray et al, 1994, p7).
More recently, practitioners have begun to further research disengagement (Kemp,
2008; Kettlewell et al, 2012, pp1-3; Tamvakis, 2014, p12), supporting the idea of a lack
of identifiable causes and universal intervention strategies.
BEHAVIOUR
Focussing on behaviour, an identified cause of disengagement, presents difficulties.
Both Trust (in House of Commons Education Committee, 2011, pp15-16) and Watkins
(2011, pp8-10) explained that qualitative behavioural analysis presents potential bias
and subjectivity; without clear grading or behavioural parameters it is difficult to assess
whether behaviour is improving or getting worse. The media exacerbate notions of
teenage behaviour getting worse (Elliott, 2013) however this can be attributed to

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several factors, including increased media coverage and social media emergence; less
accessible to previous generations.
Davidson (2007, pp18-19) summarised the problem with behaviour categorisation,
explaining:
‘One must assume that the matter of unacceptability is subjective, and that
subjectivity is mitigated by professional judgement, which in turn is the corollary
of professional training’.
The Department for Education (DfE) (2012, p10) even recognised difficulties in defining
behavioural issues due to the many definitions and acceptations of behaviour. With this
message coming from the educational governing body it is evident that this is a deep-
rooted flaw in behavioural management and therefore without objectivity, defining
classifications of behaviour and subsequent expectations presents unreliability.
Behaviour is heavily identified as a contributory factor to disengagement. Black et al
(2012, p.ii-iii) explained that 97% of teachers see low-level disruption each week, whilst
Education Scotland (2010, p4) identified low-level disruption as something that needed
management. The DfE (2012, p20) explained most of the literature they have
researched stated low-level disruption is the main cause of behavioural issues, creating
the link to behavioural disengagement. The idea of disruptive behaviour was given
further credibility by Hung (2014, pp72-75) who suggests behaviour worsens between
Primary and Secondary Schools, indicating possible links between adolescent
development and behavioural changes. A serious weakness with this argument is again
the issue of subjectivity, and the lack of clarity between disruptive and passable
behavioural traits.
When incorporating the change of schools and additional factors such as puberty and
hormonal development, Cavanagh et al (2007, pp186–198), supported the idea of
external factors being a large part of behavioural changes and subsequently possible
disengagement. Therefore; it seems that when one considers the extraordinary changes

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young people experience during adolescence irrational behaviour should be expected,
although not to a degree where it becomes tolerated.
Despite this, McCluskey et al (2013, p296) explained a proportion of labelled disengaged
students stated they enjoyed school and had generally positive experiences, suggesting
that school environments are not the cause of disengaged behaviour. A small sample
size means caution must be applied, as results may vary per demographical area and
cannot represent teenagers as a whole. Other studies (Sullivan et al, 2012, pp43-56;
Education Scotland, 2006) tried to attribute behaviour to outside sources such as
parental influences and behavioural trends, yet whilst outside influences
unquestionably affect behaviour these studies focussed on generalised behaviour rather
than school life and academic engagement.
RELATIONSHIPS
Research indicated that domestic relationships are crucial to enjoyment and
engagement in school. Those with the ability to nurture and support, or conversely
turbulent households which created unhappy environments, were seen as pivotal to
young people’s well-being and engagement (The Office for Standards in Education,
Children's Services and Skills (OFSTED), 2008, pp13-18). Laosa (1982, p796) exhibited
how research into domestic relationships discovered a more stressful home
environment resulted in unsuccessful adaptations to school environments and therefore
lower school performance.
Despite this study taking place in Los Angeles over thirty years ago, worldwide evidence
supports this ideology. More recent studies in Pakistan demonstrated peaceful domestic
environments were more conducive for academic achievement (Suleman et al, 2012,
p245) while Mooney et al (2009, p10) suggested parent-child relationships in the United
Kingdom were paramount to child development, although suffer from variables such as
financial hardship and inter-parental conflict.
Another prominent concept in research was the importance of student/teacher
relationships and the pitfalls of negative relationships. The idea that improved

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connections between staff and pupil is a popular concept (Kemp, 2008; Lumby, 2013;
Schlosser, 1992, pp128-140) with the focus on understanding issues children potentially
encounter, for example domestic or friendship issues.
Despite its age, Schlosser’s study (1992, pp128-140) on thirty-one ethnically diverse
students identified as potential dropouts still remains relevant, concluding that
exhibiting a greater understanding and appreciation of outside influences on a student’s
life can create a better working environment. Lumby (2008, pp2-4) also explored
student/teacher relationships from a communicative angle; suggesting whilst school
isn’t fit for purpose for some students with greater needs, developing positive
relationships, ensuring every child matters and avoiding hostility are all elements that
students valued.
A common research theme clearly identified that relationships could be a barrier to
engagement yet few recommendations were actually made. Schlosser (1992, pp128-
140) explained a greater understanding through communication can help, however
there is little evidence to endorse other techniques for adults working with children.
Communication could even be detrimental; Rogers (2000, pp9-12) countered the idea of
greater understanding and communication by suggesting too much can have the
adverse effect and leave students feeling victimised, further damaging any bond.
Another potential barrier to effective student/teacher relationships was found to be the
workload of the teacher, with Secondary School teachers on average working 55.7 hours
per week (DfE, 2014, p11). This further supports William’s (2012, pp299-313) evidence
that teacher’s workloads prohibit change, with staff possibly too pressurised or busy to
spend time developing positive relationships with students. These figures were
produced from just 1,004 responses from over 6,000 invitations, a limited sample size
perhaps ironically re-emphasising teachers’ heavy workloads.
CURRICULUM:
Student curriculums vary per school, with evidence suggesting that individuals struggle
because of a lack of knowledge or understanding of a subject (Cooksley, 2014), leading

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to disengagement through frustration. Vasagar (2011) supported this concept,
suggesting an ability-focus exists where more gifted students are less disengaged. Such
explanations however tend to overlook the fact that it cannot be assumed that all
disengaged students have learning disabilities.
The approach of Gordon (2015, pp30-31) and Spruce (2003, p224) was that curriculums
should stimulate, suggesting that if students enjoyed their tasks set; they were less likely
to become disengaged. Gordon’s work, despite being based on creative writing with
Primary School students, offered insights into the benefits of less formal teaching styles
and the benefits student’s experienced, particularly the respite from formality and the
rigours of a full curriculum. Expressing caution, these findings cannot be extrapolated to
all students because of the subjectivity of observed behavioural characteristics and the
variety of behavioural traits; curriculums could be outstanding but if students don’t
want to engage, they won’t. Jaffe et al (2015, pp95-101) further illustrated this,
explaining that forcing someone to work isn’t conducive for development, possibly
further damaging the student/teacher bond by continual persecution.
Several studies demonstrated that students respond to practical elements in the school
curriculum (Enright and O’Sullivan, 2010, pp203-210; Lord and Jones, 2006, p33;
National Foundation for Educational Research, 2011, pp5-8), yet this is not a universal
opinion. Osborne (1998, in Millar, 2009, pp1-3) stated practical work offers ‘little
educational value’ further indicating the subjective and divisive opinions the educational
sector present.
Maitland (2013) stated that music-based interventions in Secondary Schools improved
the behaviour of 87.5% of children, also improving non-cognitive skills like focus and
confidence which can both assist future engagement. Whilst this is just one example of
a practical intervention, it improved behaviour for that group of students, although
would need repeating on a broader scale to see if results were replicated. There also
may be suggestions of bias that students previously enjoyed music, whereas another
group may not. These factors must be included and further researched before a clear
intervention strategy is recommended.

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Lord and Jones (2006, p33) endorsed that subjects with the ability to offer practical
elements should do so, because of the positive responses from children. This research
had further credibility due to the sample sizes, with some elements of the research
involving more than fifty schools. This offered a broader response yet still cannot be
generalised to describe the views of every child. Lord and Jones (2006, p9) presented an
explicit weakness that the study focussed mainly on four key subjects – Science, English,
Mathematics and Physical Education, not other subjects with practical elements such as
Information Technology, The Arts and Geography. This presented an area where current
knowledge is limited and more research is needed.
CONCLUSION:
In conclusion, categorising the subjective nature of children behaviour and relationships
is difficult, with prior research largely acknowledging the limitations that subjectivity
brings. There is worldwide acceptance that disengagement is a real issue (Suleman et al,
2012, p245; Laosa 1982, pp791-827) yet solutions to combat the threat of
disengagement are scarce.
A set of perceived ideologies for effective learning exist, including positive
student/teacher relationships (Kemp, 2008; Lumby, 2013), non-turbulent home-lives
(Sullivan et al, 2012, pp43-56) and an enjoyment of school (McCluskey et al 2013, p296).
These can all assist the development of an engaged student, however are based on the
main limitation of disengagement research – the notion of subjectivity.
With behaviour and relationships difficult to quantify, the general acceptance of
children having fewer coping strategies than adults (Lumby, 2008, p3; (KidsMatter 2012,
p2) has created an era where mindfulness and well-being (Kuyten et al, 2013, pp126-
131; Drabble, 2013) are being introduced, benefitting future students but possibly too
late to affect currently disengaged students. Whether these new initiatives work will be
a question only answerable in due course, although again the lack of quantifiable
evidence highlights the difficulty of managing disengagement.

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Relating back to the hypothesis on students’ improved performance in practical-based
subjects, there seems to be a lack of research that this is correct, demonstrating that
research is necessary. With a form of quantitative results obtainable from GCSE grades,
this research focusses on both enjoyment and school exam performance, an area
seemingly only Kettlewell et al (2012, p21) have explored.
As Hek et al (2000, in The Open University, 2014c) states, a full systematic review of all
literature is unrealistic and that is a limitation of this literature review, with time a
restrictive factor in searching the plethora of articles both on and offline. Due to the
difficulty in exploring all available literature, it is problematic to summarise the concept
of disengaged behaviour. Additional reading and research however, both quantitatively
and qualitatively will further raise awareness of educational disengagement, helping to
produce coping strategies to re-engage students and give them opportunities to achieve
their learning potential.
METHODOLOGY
SAMPLING METHODS
Samples were both selected and randomised, with disengaged and nurture students
targeted specifically because of their academic characteristics to create a comparison.
The 23 disengaged students (D), 27 nurture students (N) and 204 remaining eligible for
the control group (C) were then numbered and, similarly to The Open University (no
date), independently drawn from separate hats to create three sets fifteen of randomly-
sampled students. This was repeated for the Ex-Year 11s, ensuring randomisation and
ethical awareness, creating fairness and transparency in the sampling process. The
sample size of two sets of forty-five students was chosen for two main reasons; to
investigate whether the difference of three years in age affected results and also to
make a fair representation of the year group, with 65% of disengaged and 55% of
nurture students represented.
The principles of the Human Research Ethics Committee (2014, in the Open University,
no date, p2) were adhered to in the form of consent, with verbal consent used as

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opposed to signed consent. The rationale for this was that forcing a thirteen year-old to
sign a waiver document may be interpreted as too intense and perhaps create worry,
which could affect the validity of results. Consent was also extended to the Ex-Year 11s,
despite their data coming from the school-produced GCSE results. Due to logistical and
geographical issues consent was given via telephone conversations, with de Vaus (2013,
p61) explaining the continuation of phone calls is a strong indicator of consent.
YEAR 9 DATA COLLECTION
Year 9 data was collected using voluntary and involuntary methods. Voluntary
questionnaires (Appendix B) were given to forty-five Year 9 participants asking them to
rank subject 1-11, with 11 their favourite and 1 their least favourite and then
justifications why using predefined reasons, with two ‘other’ boxes for customised
reasons. This was similar to Dantzker and Hunter’s self-administered surveys, (2010, in
The Open University, 2014f, p3), except students had one lesson to complete it
individually. Questionnaires were completed in classrooms during lessons, in a natural
environment (Hämäläinen and Rautio, 2013, p10) rather than a formal interview
environment which could intimidate and skew results. One control participant refused
to take part, so their place was re-allocated using the same random-sample method.
Monitoring grades provided involuntary data, a process where staff assess both
behavioural and attainment progress termly (Appendix C). This was presented using
National Curriculum 1-8 Levels (DfE, no date,) the current method of analysis. Despite
levels being phased out from 2015 (Lilly et al, 2014, p35) their validity and reliability
merited their inclusion.
Figure 1 offers a comparison between Year 9 levels and current raw GCSE grades if taken
now, not factoring in external influences on attainment.

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Year 9 Level Current GCSE Grade
3 G
4 F
5 E
6 D
7 C
8 B
9 A
10 A*
Figure 1 - National Curriculum levels to GSCE Conversion, adapted from eMaths (2013)
The original table can be criticised for not looking further than a GCSE grade B, therefore
the addition of levels 9 and 10 allowed greater precision when predicting the GCSE
grades Year 9’s might achieve.
YEAR 7 DATA COLLECTION
Student’s Year 7 monitoring data from winter 2012 was used to demonstrate the
progress made between December 2012 and December 2014, similar to methods shown
by Dantzker and Hunter (2012, in The Open University 2014f, p11). This showed current
rates of progress, challenging the DfE’s view (2010) that every child will show three
levels of progress in the Secondary School lives. With the large range of data, subject
averages were taken from all fifteen children per group, creating mean levels of
progress per subject for each group of students.
YEAR 11 DATA PREDICTION
These Year 7 to 9 rates of progress clearly demonstrated that students’ progress
differently both collectively and in individual subjects, allowing more personalised
predictions of future performance. Whereas current indicators include KS2 performance
and the three levels of progress (Appendix C) this method showed a more valid and
trustworthy method of progress, following Robson’s advice (2002, in The Open
University, 2014e, p4) of collecting additional data to further answer research questions.

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Student Subject
Year 7
Grade
Year 9
Grade
Doubled Rate
of Progress
(Yr11)
3 Levels of
Progress
Score (Yr11)
D15 English 3.66 4.66 5.66 E 6.66 D
N15 English 5.66 5.99 6.33 D 8.66 B
Figure 2 – Predicting Grades Comparison
As Figure 2 reveals, using the three levels of progress advocated by the DfE (2010) can
extremely distort predictions, showing why the method used in this report is more
reliable. With predicted grades wrong as often as 52% (Coughlan, 2013), using this
method to compare future and previous GCSE grades offered more accuracy, however is
unable to predict future health, social or domestic ramifications on academic
performance.
With the complexity of the data difficult to evaluate, success is compared by GCSE A*-C
grades, the criteria which School Performance Tables (DfE, 2015c) measure. Rather than
focus on specific subject grades, the number of A*-C grades for the five academic
subjects were added together and subsequently divided by five to create a mean
average, whilst the same process occurred with the six practical subjects, divided by six
to create the second mean average. This didn’t include PE, as current Year 9 students do
not study GCSE PE and Core PE is not quantifiable by grades.
PREVIOUS YEAR 11 GCSE GRADES
Predicted grades generated using the alternative prediction method were compared to
GCSE results of 2013-2014 of selected students, again using the consistent random-
sampling method to identify three sets of fifteen students. This allowed comparison
across three years, showing trends and rates of changes (European Commission, 2005)
but also enough time between the two, to offer direct comparisons under similar, if not
exactly replicated academic conditions. Comparing years in a short space of time
increased the reliability and repeatability of the research, as well as providing greater
representation by using a wider sample which can be generalised further (The Open
University, 2004, in The Open University, 2014g, p41). The ex-Year’s 11 data was

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calculated in the same fashion as the predicted grades, using mean averages of
academic and practical subjects across the three categories of students.
Due to the wide range of modules taken at GCSE level in each subject, some subjects
were grouped together, for example individual Languages and Mathematics modules, as
some in KS3 only study these subjects as a whole and not singularly. The same principle
was afforded to ICT and Computing, whilst GCSE PE, Business and Child Development,
not studied in KS3, were excluded. It is also conceivable that GCSE’s chosen may differ
from those studied in Year 9, however this is a natural variable where limiting choice
would be unethical.
FINDINGS
Firstly, Figure 3 demonstrates disengaged student’s preference for practical subjects,
with PE, Technology and Science the highest scoring subjects, proving the first part of
the hypothesis correct.
Figure 3 - CumulativeSubject Scores of Year 9 Students

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Justifications given for this were varied; 22.2% of disengaged students stated they enjoy
the practical elements of their top three subjects, whilst 17.78% stated that positive
relationships with teachers are paramount for their subject enjoyment. Nurture
students follow a similar pattern, with 44.4% stating that either their student/teacher
relationship or interest in topics makes them enjoy the subject. Control group results
were more varied, bar the 31% who stated they enjoy subjects they find easy.
Reasons for dislike were clearer; disengaged students stated subject difficulty, poor
student/teacher relationships and lack of subject interest accounted for over 60% of the
entire justification, whilst 33% of nurture students disliked subjects due to their
difficulty.
Year 9 monitoring data demonstrated that control students generally perform better,
however differences in ability in practical subjects between all groups (on the right of
the graph) are smaller than academic subject differences. Figure 4 explains this;
although group averages don’t take into account starting levels.
Figure 4 – Year 9 Average Monitoring Grades,winter 2014
As expected, the progress from Year 7 to 9 varied greatly per student, indicating the
three levels of progress over five years (DfE, 2010) is unattainable for some students, as

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shown in Figure 5. Indeed, in Mathematics disengaged students on average improved by
0.25% of a level, far less than the two levels the DfE (2010) suggest in Key Stage 3.
Figure 5 – Mean Levels of Progress from Year 7-9
This demonstrates the mean levels of progress shown across each subject, showing that
control groups generally learn quicker than their peers. Nurture groups tend to learn
quicker than disengaged students, although this could be attributed to one-on-one
support for children with SEN statements and smaller booster classes replacing subjects
they do not take, such as Languages. Figure 5 also suggests that progress rates are fairly
evenly distributed between academic and practical-based subjects, although this
doesn’t take into account starting levels.
The Year 7 and 9 data allowed Year 11 predictions, with Figures 6 and 7 predicting that
disengaged students will perform better in practical subjects rather than academic
subjects, showing the biggest mean average improvement from 3.2 academic A*-C’s to
6 practical A*-C’s.

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Figures 6 & 7 - Predicted GCSE A*-C Grades in Academic and Practical Subjects
Actual GCSE grades achieved by Ex-Year 11s (Figures 8 & 9) also show the improvement
made by disengaged students in practical-based subjects over academic subjects.
Figures 8 and 9 – Actual GCSE A*-C grades achieved in academic and practical subjects
In both predicted and actual GCSE grades, disengaged students show the greatest rate
of mean A*-C grade improvements from academic to practical, increasing from 3.2 to 6
and 2.2 to 5.5 respectively. Nurture students also performed higher in practical subjects
in both predicted and actual GCSE grades, whilst conversely control students varied;
scoring higher in practical predictions, yet in actual GCSE results their share of A*-C
grades dropped from 59% to 44%.

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DISCUSSION
Results are fairly conclusive, demonstrating that disengaged students do, and are
predicted to achieve higher grades in practical-based subjects in comparison to
academic subjects.
There are limitations to this research, perhaps the biggest being the sample size which
doesn’t allow generalisations, however the sample size of thirty from each category of
students is above the recommendation of twenty-five that Houston (1983, in Springate,
2011, p163) advocates for bias-free and reliable research, justifying it’s use.
Using just one school is also a limitation, although time constraints and data protection
issues of using different school’s results means that research will never be as reliable as
Lord and Jones (2006, p33) who collected data from over fifty schools. The use of two
contrasting years do offer an interesting analysis of trends which are powerful means of
comparison (van Mosseveld and van Son, 2012, p294). A second strand of GCSE results
would have provided further comparison, yet with these students now in Further
Education and beyond obtaining consent would have been difficult and certainly
unethical without consent obtained.
The practical GCSE subjects studied at KS4 but not included in analysis hinders results as
some Year 11 students may perform best in subjects such as GCSE PE or Child
Development, although comparing subjects that Year 9’s do not have access to could be
considered unethical and provide unreliable data. The Year 9 data does show students
do prefer practical subjects such as PE, satisfying the criteria of part one of the
hypothesis about the enjoyment of practical subjects.
Year 7 data used was relevant due to being produced in the same environment,
however was produced when teachers had only known the students for barely three
months. Data received from Primary Schools is often portrayed as unreliable (Curtis,
2009) and should teachers have little contact time to evaluate attainment they may
resort to KS2 grades, which may not indicate true progress.

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Year 8 grades could be used in future, however this presents just a year’s worth of
progress which subsequently is less reliable. Hek et al (2000, in The Open University
2014c, p11) state one-year interventions don’t offer completeness; yet conversely three
or more year comparisons may allow too many variables to be unaccounted for. The
short-termism of education, already demonstrated by the phasing out of levels (Lilly et
al, 2014, p35) also doesn’t lend itself to long-term comparisons.
In conclusion, this research does prove the hypothesis true that disengaged students
prefer and perform better in practical-based subjects, following similar patterns to
worldwide literature researched. Interestingly, both disengaged and nurture students
appeared to perform better in practical-based subjects, giving scope for additional
research on the elements of education that suit both groups of students, which further
emphasises findings from Kemp (2008) and Tamvakis (2014, p12 that the issued is
accepted, yet with real lack of understanding as to why.
These results offer comparisons between disengaged, SEN and control students of two
different age groups, something existing research doesn’t do. It also accepts the
subjectivity of grades and the small sample size of one school means generalisations
cannot be made, but its strong replicability can set foundations for future research.
ACTION PLAN
Having successfully explored the hypothesis that disengaged students enjoy and
perform better in practical-based subjects, the report suggests three recommendations
to improve the success of disengaged students in school life.
RECOMMENDATION ONE: ROTATING TEACHERS TERMLY IN KEY STAGE FOUR
TO AVOID DETRIMENTAL STUDENT/TEACHER RELATIONSHIPS:
From the data collected, it appears that rotating teachers in subjects in KS4 may help to
re-engage students. In the questionnaire completed, 17.78% of disengaged students
exclaimed the student/teacher relationship is the cause of their dislike for a subject.

23
In more popular subjects for disengaged students, such as Science and Technology, the
school currently offer staff rotations termly which may be a cause of their enjoyment of
the subject. Data suggests that 37.5% of disengaged students and 18.2% of nurture
students who chose the teachers as a factor in their enjoyment of the subject did so in
Science and Technology, possibly suggesting rotation of teachers assisted their learning.
Rotation and collaboration is commonplace in many establishments; Leavitt (2006, p2)
explains that team teaching and rotations allows teachers to teach their specialist topics
and this should be explored, particularly in multifaceted, modular subjects. School
subjects cover a variety of topics; such as Biology, Chemistry and Physics in Science and
Shakespeare and Poetry in English. This could allow staff to teach to their strengths,
ensuring they are more comfortable which should present a more positive learning
experience for students.
There are limitations to this idea of rotating teachers. In smaller departments such as
The Arts and Child Development, rotation may not be feasible, particularly if only one or
two teachers are able to teach the subject. Smaller departments may result in teachers
having to teach their second or third subject, creating the argument of whether a child
would rather have a non-specialist who they like, or a specialist who they do not, as
their teacher. Whilst a disengaged student may want to be taught by a teacher they
enjoy a better relationship with, there must be a consideration that the recessive
economy and increased admissions result in teachers having to teach second or third
subjects (Ratcliffe, 2013) thus increasing their workload. The frequency of rotations can
vary but this report recommends termly rotations, allowing students to get used to a
teaching style and providing amounts of continuity whilst still delivering change.
As with any intervention; participants will judge the success based on their own
experiences. There is a possibility of it seeming unfair that a student who get has forged
a successful educational relationship with a teacher then has that teacher replaced; yet
similarly a student who doesn’t have a good relationship with their current teacher will
feel happy when they experience the rotation. There may also be differing viewpoints in

24
each class; children will inevitably have wide-ranging opinions of each member of staff
and there is a high possibility that multiple opinions will exist in the same classroom.
With this dilemma, it is important to remember that this action plan aims to re-engage
students. There will always be unintentional consequences however it is also ethical to
give each student a chance to re-engage, which isn’t possible if a disengaged student
stays with a teacher they dislike for the whole year. It is important that any
interventions provide equality, following the idea of Eby and Gallagher (2008, in The
Open University, 2014d) that interventions must be equal and cannot make people feel
less valued, which might cause further and maybe even irreversible disengagement.
RECOMMENDATION TWO: OFFER MORE VOCATIONAL SUBJECTS AND
QUALIFICATIONS IN KEY STAGE FOUR
From the results produced, there is a clear observation that disengaged children do
perform better in practical subjects. Using the assumption that this is due to the
practical elements of the subject, the school could implement more practical-based
subjects or vocational qualifications into the curriculum to play to the strengths of these
children.
Currently, student’s GCSE grades are published annually in the school and college
performance tables (DfE, 2015c) which give readers the ability to view both simple and
detailed statistics about, amongst other data, percentages of A*-C grades and the ‘Best
8’ measure (Moorse, 2013). The Best 8 measure does exactly this, judging pupil
performance on their eight best grades from qualifications they have studied.
This measure allows greater vocational content to be included, yet the Best 8 can only
include subjects approved by the DfE (2013, pp2-6), making other subjects
disadvantageous for schools as the grades will not appear in the performance tables.
These subjects range from Construction and Engineering to Health and Social Care,
which should offer students a greater choice in finding a qualification that suits them,
hopefully re-engaging them into education which may spread to other subjects.

25
There are of course several feasibility issues in the implementation of a new curriculum;
including staffing, costing and facilities, all of which can affect the types of qualifications
offered. Firstly however, there needs to be the demand from the students, yet too much
choice can conversely have a negative effect; offering too many new courses will spread
interest too wide to make any feasible majority decision, therefore creating more
anxiety that students cannot pick their first choice subjects. This is further supported by
Iyengar (1995, in Tugend, 2010) who states that providing more choice can actually
cause more harm than good.
Another limitation is facilities; the school in question is a large school but doesn’t have,
for example, a salon which lends itself to Hair and Beauty courses. The lack of facilities
would therefore result in required investment, a dangerous route for a State School
particularly if the demand for these courses drops after the investment in facilities. This
investment also includes staff; existing staff will need to be assessed for the necessary
skillsets however if these are unavailable then there will be a need to employ, which will
involve additional careful budgeting to safeguard the school’s fiscal health.
Should introducing vocational qualifications be too problematic, the school could look
into the funding of stand-alone qualifications, which will allow students to gain
additional non-academic qualifications which may increase their employability in later
life. Qualifications such as the Level 2 Sports Leader Award (Sports Leaders UK, 2015), or
practical challenges like the Ten Tors Challenge (British Army, 2015) can both improve
personal skills and be looked upon favourably by future employers.
The viability of these standalone qualifications is a lot simpler, with demand being the
only real stumbling block to achievement. The teaching of these qualifications could be
done in both curriculum time or after school, with the relatively small expense of tutor-
training much more manageable for the school in comparison to the hiring of new staff
and developing new facilities, in an era where schools in the area are struggling
financially (Taffs, 2015). This also demonstrates good ethical practice, acknowledging
that the limitations of the school environment and curriculum legislation are not

26
conducive for universal development, offering students alternative methods for
continual professional development.
RECOMMENDATION THREE: INTRODUCE PRACTICAL ELEMENTS TO ACADEMIC
SUBJECTS
Should new qualifications and alternative curriculums not be a feasible option, then the
third recommendation from this action plan will be to explore methods of delivery
which allow an increased amount of practical-based elements in traditionally academic
subjects.
The data collected during the study demonstrated that practical elements of subjects
was the favourite reason for enjoyment, contributing 22.2% of the overall enjoyment of
the subject from disengaged students, with the use of technology contributing a further
13.3%. This shows that at least one in three disengaged students respond in a better
fashion to practical elements in subjects, demonstrating the need for change.
The feasibility of practical elements varies by subject, the benefits of techniques such as
role play in subjects such as English and History are both confidence-boosting and
stimulate learning (LeFever, 1995, p117) yet more difficult in subjects such as
Mathematics which doesn’t naturally lend itself to interactivity. This could be countered
with creative ideas such as using cooked spaghetti to measure graphs (Pumphrey, 2013,
in Drabble, 2013) or increased ICT Mathematics lessons (O’Donnell, 2014) to help
engage those who find just writing and reading uninspiring. As Mathematics was the
least favourite subject by disengaged students in the study, these techniques could
prove invaluable in making the subject both more enjoyable and popular with students.
Some subjects lend themselves to collaboration much more easily; GCSE Physical
Education has strong links to GCSE Science, where blood pressure, heart rate and sprint
speed can all be measured in either subject and analysed in both, presenting a more
interactive way of learning. With both PE and Science both deemed popular with
disengaged students, finding ways of incorporating them into other subjects should help
them to both understand the topic better and become further engaged.

27
Of course, when working with the general public and especially children, there is a need
to follow the ‘Every Child Matters’ ideology (DfE, 2003, pp14-18) that education should
be, if possible, enjoyable for all and allow each child to succeed. It is unrealistic to say
that lessons should be planned for the specific needs of every child which would take
more of the limited time teachers have free (DfE, 2014, p11), however there should be a
variety of active learning styles to suit all children. Although an issue in the ‘rotation of
teachers’ action point, having teachers delivering second or third subjects may actually
help to bring additional ideas to lessons and to introduce further cross-curricular links
using their expertise from other subjects.
Whilst time is a limitation in terms of extra planning and collaboration between
departments, there are few other obvious limitations to implementing this
recommendation. Timetables would not need to be changed and curriculums subjects
could stay the same, allowing curriculum continuity, a trait that the DfE and
Qualifications and Curriculum Authority (2004, p12) state is important to ensure
progression in pupils learning.
ACTION PLAN CONCLUSION
In summary, the three recommendations offer a varied response to assist students to
become re-engaged with their educational careers and give them an improved chance
to achieve in education.
There must also be a solid structure to any intervention, in this case incorporating the
‘Four Principles of Best Value’ (Figure 10) to ensure that all parties involved are
maximising the benefits of the intervention.

28
Challenge To re-engage students into educational well-being and increased
attainment
Compare Would the intervention improve academic performance for disengaged
students in comparison to current provision?
Consult Liaise with curricular, pastoral and financial decision-makers for
feasibility and students to determine demand/interest
Competition Are there any better existing ideas or are any similar ideas being
developed?
Figure 10 - ‘Four Principles of Best Value’ adapted from: Department of Environment, Transport and the
Regions, 1998,in Harris,2007,p24)
As the next academic year starts in September, this report recommends a consultancy
and feasibility study to be undertaken from now until January 2016. This allows eight
months for the analysis of current staff skillsets and the collaboration of school partners,
Governors and existing staff to determine the best way forward, with adequate time for
implementation in to the 2016/2017 academic year. This also provides ample time for
staff to plan and prepare lessons in different subjects, as well as time to survey
student’s opinion on future courses or curriculums.
This report recommends once implemented, any intervention should be continuously
evaluated by all participants involved, using an evaluation model similar to that of Eby
(2000, in Finlay 2008, p5). This model, or a hybrid model of self-awareness, reflection
and critical thinking can help to ensure the best quality education is delivered to young
people in the school.
Finally, a major consideration must be the state of the education system in England,
currently going through a transitional phase of leadership and priorities (Ministry of
Justice, 2015; Harrison, 2013) which could hamper any attempt at intervention. The
move to more terminal exams (DfE, 2015d) already harms those who struggle
academically, demonstrating the difficulty in delivering change in a vastly autocratic
education system.

29
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https://learn2.open.ac.uk/pluginfile.php/1259156/mod_resource/content/1/EK310_key
_research_terms.pdf (Accessed 28th May 2015) p41
The Open University (no date) ‘Simple random sampling’ [online] Available at:
http://www.open.edu/openlearnworks/mod/oucontent/view.php?id=233&section=1.5.
1 (Accessed 23rd May 2015)
Tugend, A. (2010) ‘Too many choices: a problem that can paralyze’ [online] Available at:
http://www.nytimes.com/2010/02/27/your-money/27shortcuts.html (Accessed 19th
May 2015)
Van Mosseveld, C. P. J. M. and van Son, P. (2012) ‘International comparison of health
care data: methodology development and application’ New York, United States,
Springer, p294

38
Vasagar, J. (2011) ‘Academic curriculum may worsen discipline problems say MPs’
[online] Available at: http://www.theguardian.com/education/2011/feb/03/academic-
path-will-worsen-behaviour (Accessed 14th February 2015)
vom Brocke, J. and Rosemann, M. (2014) ‘Handbook on business process management
1: introduction, methods, and information systems’ New York, United States, Springer,
p580
Watkins, C. (2011) ‘Managing classroom behaviour’ London, Association of Teachers
and Lecturers, pp8-10
Williams, H. (2012) ‘Fair pairs and three part praise – developing the sustained use of
differential reinforcement of alternative behaviour’ in ‘Educational psychology in
practice: theory, research and practice in educational psychology’ Volume 28, Issue 3,
pp299-3

39
APPENDIX A – GCSE SUBJECT ASSESSMENT CRITERIA
Green = All Written Assessment
GCSE
Subject
Controlled
Assessment
Terminal
Exam
GCSE
Subject
Controlled
Assessment
Terminal
Exam
Blue = Some Practical Assessment
GCSE
Subject
Controlled
Assessment
Terminal
Exam
Religious
Studies
√ x 2 Textiles
Practical Creation&
Design Folder
√
English √ √ Biology
Individual
Skills
Assessment
(ISA)
√ x 2 GCSE PE
4 x Physical
Assessments
√
English
Language
√ √ Chemistry
Individual
Skills
Assessment
(ISA)
√ x 2
Child
Development
Child Resource &
Design Folder
√
English
Literature
√ √ Physics
Individual
Skills
Assessment
(ISA)
√ x 2 Geography
Fieldwork
Controlled
Assessment
√ x 2
Further
Maths
√
Science A
(Route 1)
Individual
Skills
Assessment
(ISA)
√ x 2
Food/
Catering
Practical Creation&
Design Folder
√
Maths
Linear
F/H
√ x 2
Additional
Science
Individual
Skills
Assessment
(ISA)
√ x 2
Design and
Technology
(SC)
Practical Creation&
Design Folder
√
Methods
in Maths
√ x 2
Business
Studies
ICT-Based
Assessment
√ x 2
GCSE PE
Short
Course
2 x Physical
Assessments
√
Sociology √ x 2 Art
10 Hour
Practical
Assessment
Drama
Practical
Performance
√
French
Oral, Listening, Reading
and WritingAssessments
BACS
ICT-Based
Assessment
√ x 2
OCR
Nationals
ICT-Based
Coursework
German
Music
Performing,
Composing
and Listening
Assessments
√
OCR
Nationals 1st
Grade
ICT-Based
Coursework
Spanish
Electronics
Practical
Creation &
Design Folder
√
OCR
Nationals
2nd Grade
ICT-Based
Coursework
History √ √ x 2 Graphics
Practical
Creation &
Design Folder
√
OCR
Nationals
3rd Grade
ICT-Based
Coursework
Statistics √
Product
Design
Practical
Creation &
Design Folder
√ Astronomy
Controlled
Telescope
Assessment
√

40
APPENDIX B – YEAR 9 QUESTIONNAIRE
Dear Student,
This questionnaireis partof a study Mr Lake has been asked to do about what children enjoy and don’t
enjoy at school to see if the school is doingwhat it can to support you.
Pleaseanswer the followingquestions honestly and on your own. Your name will notbe used and there
will beno penalties for writingwhat you feel. If you areunsure of a question, Mr Lake will explain itmore
clearly to you to help you understand it. Once finished,pleaseput in the envelope that came with the
questionnaireand seal the envelope.
Thank you,
Mr Lake.
Questions
1) Please listyourfavouritesubjectsinorder,with11 beingyourfavourite and1 being
your leastfavourite.Eachsubjectmusthave a unique value (e.g. 1,2,3,4,5,6,7,8,9,10,11
and not1,1,2,3,4,4 etc.).Inthis,‘Expressive Arts’counts as Music/Drama/Art, as not all
studentstake all three subjectsseparately.
English Maths Science ICT Geography History RE Languages
(one or two)
PE Technology Ex.
Arts
Subject 11 (My
Favourite)
Subject 7 Subject 3
Subject 10 Subject 6 Subject 2
Subject 9 Subject 5 Subject 1 (Least
Favourite)
Subject 8 Subject 4
2) Now, pleasegive the most important reason for each of your top three subjects, tickingthe
reasons in the boxes below. You can put the same answer for as many of the three choices as
you like.If you likethe subjectfor another reason,pleasecomplete the ‘other’ box explaining
why.
Reason Subject 11 (Fav) Subject 10 Subject 9
Please name subject here -
Example - I get on well with the teacher √ √
I get on well withthe teacher
The subject interests me
I find the subject easy
My friends are in the same class
I like the practical parts rather thanjust writing
I enjoythe use of computers or technologyinthe subject
I am proudof the workI produce inthe subject
Other (Please Explain)-

41
3) Finally,pleasedo the same for your leastfavouritethree subjects,usingthe options in the table
below to pick the most important reason per subject. Again, if you feel your reason is not
already covered in one of the given options,pleaseuse the ‘other’ box and write your reason(s)
next to it.
Reason Subject 3 Subject 2 Subject 1
(Least Fav)
Please name subject here -
Example - I find the subject too difficult √
I do not get onwell with the teacher
I have no interest inthe subject
I find the subject toodifficult
None of myfriends are inmyclass
There is too much writtenwork inthe subject
I don’t like the amount of computer work in the subject
I onlydo the subject because it is compulsory
Once you have completed all three questions,pleasedouble-check your answers and once happy, please
placeinsidethe envelope provided and then seal the envelope and hand back to your teacher or Mr Lake.
PLEASE DO NOT PUT ANY NAME OR TUTOR GROUP ON YOUR QUESTIONNAIRE
Thank you,
Mr Lake.

42
APPENDIX C – MONITORING REPORT COVER LETTER
Year 9 Monitoring December 2014
Dear Parent/Carer,
Pleasefind enclosed your son/daughter’s monitoring report from The School Named. We have made
several changes to the format and information provided in order to make it clear to you as to whether
your child is makingtheprogress we expect of them.
Pleasefind a range of information belowto help guide you through the monitoring report.
Attendance: Research indicates that achievement is directly related to attendance. Every child has his/her
own target for attendance but we expect a minimum of 95% attendance. Even missing5%of school
means that a child would miss nearly 10 weeks of education over fiveyears at Secondary School;this is
very difficultto catch up.
‘Behaviour for Learning’: A teacher will assign a grade,A-D, in this column. They have to consider many
factors – completion of homework, meeting deadlines,contribution in the lessons,concentration,
relationshipswith others and behaviour. Pleasesee the criteria atthe bottom of the monitoringreport.
Progress to Target: This column has been added this year to show you clearly if your son/daughter is
makingthe progress we would expect to achievetheir End of Key Stage 3 Target. The three options
teachers can selectare: Below Expected Progress (red), Expected Progress (yellow) or Above Expected
Progress (blue).
End of Key Stage 3 Target: This target indicates thelevel that should be achieved at the end of year 9 if
your child is on courseto make the progress we expect of them. This target is based on a range of data
and information includingKey Stage 2 results and teacher judgements.
 Targets are on a scalefrom Level 2 up to Level 8 and then on to E for Exceptional Performance
(beyond Level 8). Each level is divided up into 3 sub-levels;A (high), B (middle) and C (low).
 In most subjects,you would expect a child who is attaininga level 7 by the end of Year 9 to
achievea Grade C in their GCSE if they continue to work hard and make similar progress.
 The sub-levels also indicateGCSE grades; one would expect a 7B to get a comfortable GCSE
Grade C if continuingat the same level of progress, whilstsub-levels such as 7Aor 7C indicate
borderlineperformance of either the grade above or below respectively.
Hopefully, this monitoringreport will help you build a pictureof the progress your child is making.It
should enableyou to have the discussions you need with his/her teachers to ensure we are all working
collaboratively and students arebeing appropriately challenged and supported to do their very best.
Should you wish to discussany aspectfurther (includingthe new monitoringformat) pleasefeel free to
contact men. If you have a query about a specific subject,pleasecontactyour child’s teacher (of Head of
Department).
Yours Sincerely,
Name Withheld

43
APPENDIX D – YEAR 7-9 MONITORING FORM EXAMPLE
Year 9 Monitoring Report
December 2014
Name: ---------------
House: ---------------
Tutor: Mrs. ----------
Attendance: 96.5%
Subject Teacher
Behaviour for
Learning
Current
Attainment
Progress to Target
End of KS3
Target
English C 5c Expected Progress 5a
Maths B 4a Above Expected Progress 4a
Science B 5b Expected Progress 5a
Technology B 4b Expected Progress 5a
Art C 4a Expected Progress 5c
Computing B 3a Below Expected Progress 4b
Geography B 4a Expected Progress 5b
History A 4a Expected Progress 5c
Music C 4a Expected Progress 5b
PE B 5c Expected Progress 5b
Philosophy C 4b Expected Progress 5c
Spanish C 4b Expected Progress 4a
Behaviour for Learning (BfL)
A = Excellent. Your behaviour for learningis always excellent andthis helps you to make real progress in your lessons.
You are sensible, cooperative, helpful andthoughtful;you set a reallygoodexample to other students.
B = Good. Your behaviour for learning is usuallygoodandthis helps youto make pleasing progress inyour lessons.
Veryoccasionallyyou needto be remindedabout aspects of your behaviour but you always accept advice sensibly.
C = Adequate. Generallyspeaking your behaviour for learning is satisfactoryinlessons andyou make progresswith
the tasks youare set. Sometimes youneed to be remindedabout aspects ofyour behaviour byyour teacher but you
generallyunderstand the needto be well behaved.
D.= Unsatisfactory. Your behaviour for learningis not always acceptable. The things you do inlessons caninterfere
with your learning andthe learning ofother students. Making positive changesto the wayyou behave is a very
important area for you to target if you are to make anyrealprogress.
(Please complete and return this slip to your child’s tutor)
I have read this report and discussed itwith my child.
Student Name…………………………………………………………………………….. Tutor ………………………………….
Parent/Carer Signature………………………………………………………………..

44
APPENDIX E - YEAR 7 TO 9 MONITORING DATA & PREDICTIONS
ENGLISH MATHEMATICS HISTORY PHILOSOPHY/ETHICS LANGUAGES
1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4
D1 4.7 5.3 0.7 6-D 3.3 5 1.7 6.7-D 2.7 5.3 2.7 8-B 2.7 4.7 2 6.7-D 2.7 4.7 2 6.7-D
D2 6 6.7 0.7 7.3-C 3.7 4.7 1 5.7-E 3.3 5 1.7 6.7-D 3.3 5 1.7 6.7-D 3.3 4.3 1 5.3-E
D3 6 5.7 -0.3 5.3-E 4 4.3 0.3 4.7-F 3 5 2 7-C 3 4.3 1.3 5.7-E 3 4.7 1.7 6.3-D
D4 3.7 4.3 0.7 5-E 3.7 4.3 0.7 5-E 2.3 3.3 1 4.7-F 3 3.3 0.3 3.7-G 3 DOESNT TAKE
D5 5 6 1 7-C 4 5.3 1.3 6.7-C 2.7 4.3 1.7 6-D 2.7 4.3 1.7 6-D 2.7 4.3 1.7 6-D
D6 4.7 5.7 1 6.7-D 3.7 4 0.3 4.3-F 3 4 1 5-E 3 4.3 1.3 5.7-E 3 4.3 1.3 5.7-E
D7 5.7 6.3 0.7 7-C 5.3 6.3 1 7.3-C 3.3 5.7 2.3 8-B 3.3 6 2.7 8.7-B 3.3 5.7 2.3 8-B
D8 6.3 7.7 1.3 9-A 6.3 8 1.7 9.7-A 3.7 6 2.3 8.3-B 3.7 5.3 1.7 7-C 3.3 5.3 2 7.3-C
D9 5.3 6.3 1 7.3-C 5.7 5.3 -0.3 5-F 3.3 4.7 1.3 6-D 3.3 5 1.7 6.7-D 3.3 4.3 1 5.3-E
D10 3.3 4 0.7 4.7-F 4.7 4 -0.7 3.3-U 2.7 3.7 1 4.7-F 2.7 4.3 1.7 6-D 2.7 3.7 1 4.7-F
D11 3.3 4.3 1 5.3-E 5 4.7 -0.3 4.3-F 3.3 4.3 1. 5.3-E 3.3 4.7 1.3 6-D 3.3 DOESNT TAKE
D12 4.3 5.7 1.3 7-C 5 4 -1 3-G 3.3 4.7 1.3 6-D 3.3 4.7 1.3 6-D 3.3 4.7 1.3 6-D
D13 4 4.7 0.7 5.3-E 5 4 -1 3-G 3 4.7 1.7 6.3-D 3 3.7 0.7 4.3-F 3 4 1 5-E
D14 4.7 6 1.3 7.3-C 4 4.7 0.7 5.3-E 3 4.3 1.3 5.7-E 3.3 4.7 1.3 6-D 3 5.3 2.3 7.7-C
D15 3.7 4.7 1 5.7-E 5 4.3 -0.7 3.7-G 2.3 4.3 2 6.3-D 2.7 5 2.3 7.3-C 3 DOESNT TAKE
SCIENCE TECHNOLOGY ART ICT GEOGRAPHY MUSIC
1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4
D1 3.7 5.7 2 7.7-C 3.7 5.7 2 7.7-C 3 5 2 7-C 3 4 1 5-E 2.3 5 2.7 7.7-C 2.3 5 2.7 7.7-C
D2 5.7 5.3 -0.3 5-E 5.7 5.3 -0.3 5-E 3.3 5.7 2.3 8-B 3.3 4 0.7 4.7-F 3.3 4.7 1.3 6-D 3.3 5 1.7 6.7-D
D3 4.7 5.7 1 6-D 4.7 5.7 1 6.7 3.3 5 1.7 6.7-D 3.3 4.7 1.3 6-D 3 4.3 1.3 5.7-E 3.3 5.3 2 7.3-C
D4 4.7 5.3 0.7 6-D 4.7 5.3 0.7 6-D 3 4.3 1.3 5.7-E 3 4.7 1.7 6.3-D 2.7 3.3 0.7 4-F 3 4.7 1.7 6.3-D
D5 3.7 5.3 1.7 7-C 3.7 5.3 1.7 7-C 3 4.7 1.7 6.3-D 3 4.3 1.3 5.7-E 2.7 4.3 1.7 6-D 2.7 5.3 2.7 8-B
D6 4.3 5.3 1 6.3 4.3 5.3 1 6.3 3.3 5 1.7 6.7-D 3 5 2 7-C 3 4.7 1.7 6.3-D 3 5.3 2.3 7.7-B
D7 5.3 6.7 1.3 8-B 5.3 6.7 1.3 8-B 3.3 5 1.7 6.7-D 3.3 4.7 1.3 6-D 3.3 5.3 2 7.3-C 3.3 5.7 2.3 8-B
D8 6.3 7.3 1 8.3-B 6.3 7.3 1 8.3-B 3.3 5.3 2 7.3-C 3.3 5.7 2.3 8-B 3.7 6.7 3 9.7-A 3.6 6.3 2.7 9.1-A
D9 5.3 5.7 0.3 6-D 5.3 5.7 0.3 6-D 3.3 5.3 2 7.3-C 3.3 4.7 1.3 6-D 3.3 5 1.7 6.7-A 3.3 5.3 2 7.3-C
D10 3.3 4.3 1 5.3-E 3.3 4.3 1 5.3 3 4.3 1.3 5.7-E 3 4.3 1.3 5.7-E 2.7 3.3 0.7 4-F 2.7 3.7 1 4.7-F
D11 4 5.7 1.7 7.3-C 4 5.7 1.7 7.3 3.3 4.7 1.3 6-D 3.3 4.7 1.3 6-D 3.3 3.3 0 3.3-G 3.3 4.3 1 5.3-E
D12 5.3 5.7 0.3 6-D 5.3 5.7 0.3 6-D 3.3 5 1.7 6.7-D 3.3 4.7 1.3 6-D 3.3 4.7 1.3 6-D 3.3 5 1.7 6.7-D
D13 5 5 0 5-E 5 5 0 5-E 3.3 5.3 2 7.3-C 3.3 4 0.7 4.7-F 3 3.7 0.7 4.3-F 3.3 5.7 2.3 8-B
D14 4.3 5 0.7 5.7-E 4.3 5 0.7 5.7-E 3.3 5.7 2.3 8-B 3.3 5 1.7 6.7-D 3 5.3 2.3 7.7-C 3.3 5.3 2 7.3-C
D15 4.3 4.7 0.3 5-E 4.3 4.7 0.3 5-E 3.3 5 1.7 6.7-D 3 3.7 0.7 4.3-F 3 4.3 1.3 5.7-E 3 5.3 2.3 7.7-C
[Per subject] Column 1 – Year 7 Monitoring
Column 2 – Year 9 Monitoring
Column 3 – Year 7 to Year 9 Difference (KeyStage 3 Progress)
Column 4 –GCSE Prediction(Based on1-10 levels)
Numeric Conversion:
[5]C = 5.3 = Borderline to L4
[5]B = 5.6/5.7 = Middle
[5]A = 5.9/6.0 = Borderline/on L6

45
1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4
N1 3.7 4.7 1 5.7-E 3.3 3.7 0.3 4-F 2.7 DOESN’T TAKE 2.7 4 1.3 5.3-E 2.7 DOESN’T TAKE
N2 4.7 5 0.3 5.3-E 4.3 4 -0.3 3.7-G 2.7 DOESN’T TAKE 2.7 4.7 2 6.7-D 2.7 4 1.3 5.3-E
N3 3.3 4.3 1 5.3-E 3 3.7 0.7 4.3-F 2.7 4 1.3 5.3-E 2.7 3.3 0.7 4-F 2.7 DOESN’T TAKE
N4 5 5 0 5-E 4.3 4.3 0 4.3-F 3 5.3 2.3 7.7-C 3 5.3 2.3 7.7-C 3 4.7 1.7 6.3-D
N5 5 6 1 7-C 4.7 4 -0.7 3.3-G 3.3 DOESN’T TAKE 3.3 4.3 1 5.3-E 3.3 4.3 1 5.3-E
N6 4.7 5 0.3 5.3-E 5.3 6.3 1 7.3-C 3 4.3 1.3 5.7-E 3 4.3 1.3 5.7-E 3 5 2 7-C
N7 5 5.7 0.7 6.3-D 6 6 0 6-D 3 DOESN’T TAKE 3 4.3 1.3 5.7-E 3 4.3 1.3 5.7-E
N8 3.3 4.7 1.3 6-D 3 2.3 -0.7 1.7-U 2.7 4.3 1.7 6-D 2.7 4.3 1.7 6-D 2.7 DOESN’T TAKE
N9 3.3 4.7 1.3 6-D 3 5 2 7-C 2.7 4.7 2 6.7-D 3 5.3 2.3 7.7-C 3 4.3 1.3 5.7-E
N10 4.7 6 1.3 7.3-C 4.7 3.7 -1 2.7-U 2.7 5 2.3 7.3-C 3 4.7 1.7 6.3-D 3 4.3 1.3 5.7-E
N11 4.7 6 1.3 7.3-C 5.3 6 0.7 6.7-D 3 5 2 7-C 3.3 4.7 1.3 6-D 3.3 5.3 2 7.3-C
N12 5.3 6.3 1 7.3-C 5.3 5 -0.3 4.7-F 3.3 5.7 2.3 8-B 3.3 4.3 1 5.3-E 3.3 5 1.7 6.7-D
N13 4.3 5.3 1 6.3-D 5.7 4 -1.7 2.3-U 2.7 4 1.3 5.3-E 2.7 4.7 2 6.7-D 3 5 2 7-C
N14 4.7 5.3 0.7 6-D 3.7 4 0.3 4.3-F 3 DOESN’T TAKE 3 4.7 1.7 6.3-D 3 5 2 7-C
N15 5.7 6 0.3 6.3-D 5 5 0 5-E 3.3 4.7 1.3 6-D 3.3 5 1.7 6.7-D 3.3 5 1.7 6.7
1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4
N1 3.3 5.3 2 7.3-C 2.7 5 2.3 7.3-C 3 4.3 1.3 5.7-E 3 4.3 1.3 5.7-E 2.7 4 1.3 5.3-E 2.7 4.3 1.7 6-D
N2 4.3 5.7 1.3 7-C 3 5.3 2.3 7.7-C 3 5 2 7-C 3 4.7 1.7 6.3-D 2.7 5 2.3 7.3-C 3 5 2 7-C
N3 3.3 5 1.7 6.7-D 2.7 5 2.3 7.3-C 3 5.3 2.3 7.7-C 3 4.7 1.7 6.3-D 2.7 4.7 2 6.7-D 2.7 4.7 2 6.7-D
N4 4.7 5.3 0.7 6-D 3 5 2 7-C 3.3 5 1.7 6.7-D 3.3 4.9 1.6 6.5-D 3 4.7 1.7 6.3-D 3 5.3 2.3 7.7-C
N5 5 5.7 0.7 6.3-D 3.3 5 1.7 6.7-D 3.3 5 1.7 6.7-D 3.3 5 1.7 6.7-D 3.3 4.7 1.3 6-D 3.3 5.3 2 7.3-C
N6 5 5.7 0.7 6.3-D 3 5.3 2.3 7.7-C 3.3 5 1.7 6.7-D 3.3 4.3 1 5.3-E 3 4.3 1.3 5.7-E 3.3 5.3 2 7.3-C
N7 5.3 6 0.7 6.7-D 3 4.7 1.7 6.3-D 3.3 4.3 1 5.3-E 3.3 4.3 1 5.3-E 3 4.3 1.3 5.7-E 3.3 5.3 2 7.3-C
N8 3.3 4.7 1.3 6-D 2.7 5 2.3 7.3-C 3 4.6 1.6 6.2-D 3 4.3 1.3 5.7-E 2.7 4.3 1.7 6-D 2.7 4.3 1.7 6-D
N9 4.3 5.3 1 6.3-D 4 5.3 1.3 6.7-D 3.3 5.3 2 7.3-C 3 5.3 2.3 7.7-C 2.7 4.3 1.7 6-D 3 4.7 1.7 6.3-D
N10 4.7 5.3 0.7 6-D 3 5.3 2.3 7.7-C 3.3 6 2.7 8.7-B 3 4.7 1.7 6.3-D 2.7 4.3 1.7 6-D 3 4.3 1.3 5.7-E
N11 5 6 1 7-C 3.3 5 1.7 6.7-D 3.3 5 1.7 6.7-D 3.3 5 1.7 6.7-D 3.3 5 1.7 6.7-D 3.3 5 1.7 6.7-D
N12 5.3 6.3 1 7.3-C 3.3 4.7 1.3 6-D 3.3 4.7 1.3 6-D 3.3 4.3 1 5.3-E 3.3 4.7 1.3 6-D 3.3 5.3 2 7.3-C
N13 4 5.3 1.3 6.7-D 2.7 4.3 1.7 6-D 3.3 4.7 1.3 6-D 3 4.7 1.7 6.3-D 2.7 4.7 2 6.7-D 3 5.3 2.3 7.7-C
N14 4.3 5.3 1 6.3-D 3 5.3 2.3 7.7-C 3.3 4.7 1.3 6-D 3.3 5.6 2.3 7.9-C 3 5 2 7-C 3 4.7 1.7 6.3-D
N15 5.7 7 1.3 8.3-B 3.7 5 1.3 6.3-D 3.3 5 1.7 6.7-D 3.7 4.3 0.7 5-E 3.3 5.3 2 7.3-C 3.7 5 1.3 6.3-D
Column 4 –GCSE Prediction (Based on1-10 levels)
Numeric Conversion:
[5]B = 5.6/5.7 = Middle
[5]A = 5.9/6.0 = Borderline/onL6

46
1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4
C1 6.3 6.7 0.3 7-C 7 7.7 0.7 8.3-B 3.7 6.3 2.7 9-A 3.3 5.3 2 7.3-C 3.3 6 2.7 8.7-B
C2 6 6.7 0.7 7.3-C 6.3 7.7 1.3 9-A 3.7 5.7 2 7.7-C 3.3 4.7 1.3 6-D 3.3 5 1.7 6.7-D
C3 6 6.3 0.3 6.7-D 5.3 5.7 0.3 6-D 3.3 5.6 2.3 8.3-B 3.3 4.7 1.3 6-D 3.3 6.7 3.3 10-A*
C4 loo6.3 7 0.7 7.7-C 5.7 7 1.3 8.3-B 3.7 6 2.3 8.3-B 3.7 5.3 1.7 7-C 3.3 6 2.7 8.7-B
C5 6.3 7 0.7 7.7-C 7 7.7 0.7 8.3-B 3.7 5.7 2 7.7-C 3.7 5.3 1.7 7-C 3.3 6 2.7 8.7-B
C6 6.3 7.3 1 8.3-B 6 7.3 1.3 8.7-B 3.7 6 2.3 8.3-B 3.7 5.7 2 7.7-C 3.3 6.3 3 9.3-A
C7 5.7 6 0.3 6.3-D 7 7.7 0.7 8.3-B 3.7 5.3 1.7 7-C 3.7 4.7 1 5.7-E 3.3 5 1.7 6.7-D
C8 6.7 8 1.3 9.3-A 7 7.3 0.3 7.7-C 3.7 6.3 2.7 9-A 3.7 5.3 1.7 7-C 3.7 5.7 2 7.7-C
C9 5.3 6.7 1.3 8-B 6.3 7 0.7 7.7-C 3.3 5.7 2.3 8-B 3.7 4.7 1 5.7-D 3.3 5.3 2 7.3-C
C10 6 6.7 0.7 7.3-C 5.3 6.7 1.3 8-B 3.3 6 2.7 8.7-B 3.3 5.7 2.3 8-B 3.3 5.7 2.3 8-B
C11 6.3 7.3 1 8.3-B 5.7 7 1.3 8.3-B 3.7 5.7 2 7.7-C 3.7 5.3 1.7 7-C 3.7 6 2.3 8.3-B
C12 6.3 7 0.7 7.7 6.7 8.3 1.7 10A* 3.7 6 2.3 8.3-B 3.7 5.3 1.7 7-C 3.7 6.7 3 9.7-A
C13 6.3 6.7 0.3 7 5.3 5.7 0.3 6-D 3.3 5.7 2.3 8-B 3.3 4.7 1.3 6-D 3.3 5.3 2 7.3-C
C14 6.7 7.7 1 8.7 6 7.3 1.3 8.7-B 3.7 5.7 2 7.7-C 3.7 5.3 1.7 7-C 3.3 5.7 2.3 8-B
C15 6.3 7 0.7 7.7 7 7.7 0.7 8.3-B 3.7 5.3 1.7 7-B 3.7 5 1.3 6.3-B 3.7 5 1.3 6.3-D
1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4
C1 6.3 7.7 1.3 9-A 3.3 6 2.7 8.7-B 3.3 6.3 3 9.3-A 3.3 5.3 2 7.3-C 3.3 5.3 2 7.3-C 3.3 6 2.7 8.7-B
C2 6.3 6.3 0 6.3-D 3.3 5.7 2.3 8-B 3.3 5.3 2 7.3-C 3.3 5.3 2 7.3-C 3.3 5.3 2 7.3-C 3.3 5.7 2.3 8-B
C3 5.7 6.7 1 7.7-C 3.3 5.7 2.3 8-B 3.3 5.3 2 7.3-C 3.3 5.7 2.3 8-B 3.3 5.3 2 7.3-C 3.3 5.7 2.3 8-B
C4 6 6.3 0.3 6.7-D 3.3 5.7 2.3 8-B 3.3 6 2.7 8.7-B 3.3 5.3 2 7.3-C 3.7 5.7 2 7.7-C 3.3 5.7 2.3 8-B
C5 6.3 6.7 0.3 7-C 3.7 5.7 2 7.7-C 3.3 6 2.7 8.7-B 3.7 6.3 2.7 9-A 3.7 6.3 2.7 9-A 3.3 5.3 2 7.3-C
C6 6.3 7.7 1.3 9-A 3.7 6 2.3 8.3-B 3.7 6.3 2.7 9-A 3.7 4.3 0.7 5-E 3.7 5.7 2 7.7-C 3.7 6 2.3 8.3-B
C7
6.3 7 0.7 7.7-C 3.3 5.3 2 7.3-C 3.7 5.3 1.7 7-C 3.7 7 3.3
10.3-
A*
3.7 5.3 1.7 7-C 3.7 5.3 1.7 7-C
C8
7 7.3 0.3 7.7-C 3.7 6.3 2.7 9-A 3.7 7 3.3
10.3-
A*
3.7 4.3 0.7 5-E 3.7 5.7 2 7.7-C 3.7 6.3 2.7 9-A
C9 6 6.7 0.7 7.3-C 3.3 5.3 2 7.3-C 3.7 5 1.3 6.3-D 3.3 5 1.7 6.7-D 3.3 5 1.7 6.7-D 3.3 6 2.7 8.7-B
C10 5.3 6.7 1.3 8-B 3.3 5.7 2.3 8-B 3.7 6 2.3 8.3-B 3.3 5.3 2 7.3-C 3.3 5.7 2.3 8-B 3.3 6 2.7 8.7-B
C11
6.3 7 0.7 7.7-C 3.7 5.7 2 7.7-C 3.7 7.3 3.7
11-
A*
3.7 5.7 2 7.7-C 3.7 5.7 2 7.7-C 3.7 5.7 2 7.7-C
C12
6.3 7.7 1.3 9-A 3.7 6.3 2.7 9-A 3.7 7 3.3
10.3-
A*
3.7 7 3.3
10.3-
A*
3.7 6.7 3 9.7-A 3.7 5.7 2 7.7-C
C13 5.7 7 1.3 8.3-B 3.3 5 1.7 6.7-D 3.3 4 0.7 4.7-F 3.3 5 1.7 6.7-D 3.3 5.3 2 7.3-C 3.3 5.3 2 7.3-C
C14
6 6.7 0.7 7.3-C 3.7 6.7 3 9.7-A 3.3 7 3.7
10.7-
A*
3.7 5.3 1.7 7-C 3.7 6 2.3 8.3-B 3.3 5.3 2 7.3-C
C15 6.7 7 0.3 7.3-C 3.7 5.7 2 7.7-C 3.3 6 2.7 8.7-B 3.7 6.3 2.7 9-A 3.7 6 2.3 8.3-B 3.7 6.7 3 9.7-A
Column 4 –GCSE Prediction(Based on1-10 levels)
Numeric Conversion:
[5]B = 5.6/5.7 = Middle
[5]A = 5.9/6.0 = Borderline/onL6

47
APPENDIX F - PREDICTED AND ACTUAL GCSE GRADES PER SUBJECT PER CATEGORY
Predicted and Actual Mean Number of A*-C GCSE Grades per Student
per Category (out of 15)
Subject Disengaged Students Nurture Students Control Students
English 5 2 4 4 11 14
Maths 2 4 1 15* 13 51*
History 3 0 3 0 15 3
Philosophy 3 5 2 2 9 10
Languages 3 0 1 0 12 5
Science 5 3 3 8 12 24**
Technology 9 3 5 3 14 13
Art 5 0 3 2 13 4
Computing/ICT 2 26*** 1 25*** 11 18***
Geography 5 0 1 0 14 1
Music 10 1 6 0 15 0
* Extra Mathematic qualifications available for those who want to undertake them such
as Statistics and Further Maths (compulsory for Sets 1 and 2)
** Triple Science options
***Computing or ICT double awards (counting for two GCSE’s)

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