Case for Support:
Holistic Evidence and Design: sensory impacts, practical outcomes (HEAD)
Track record
The PI for this project is Professor Peter Barrett MSc, PhD, DSc, FRICS. He is an experienced researcher who,
since 1991, has won contracts as PI or co-investigator valued at £5.9M (estimating an appropriate share),
mainly from EPSRC. He has run many projects and research teams, several of which are directly relevant to
this project proposal (see below). He has extensive involvement in the international research community
and policy bodies, which provides a sound basis for ensuring maximum impact for the project findings.
From 2001 Professor Barrett has been Chair of the EPSRC Salford Centre for Research and Innovation
(SCRI), renewed in January 2007 until the end of 2011. From 2001-08 he was Pro-Vice Chancellor for
Research & Graduate Studies at Salford University; and is also a Member of the UK High Level Group of the
Construction Technology Platform (2004-date); an Academic member of the Department of Business,
Enterprise and Regulatory Reform’s Advisory Group for “Innovation in Construction Services” initiative
(2007-10); a Member of the Executive Committee (from 2008) of the High Level Group of the European
Construction Platform (2005-date); and President of the International Council for Research and Innovation
in Building and Construction (CIB), which has 2000 researcher members in 60 countries (2007-10).
This project proposal is a natural development of a stream of developmental work by the research
team. The first significant work on Facilities Management in the UK was funded by the EPSRC LINK CMR
programme (GR/H83904/01) and resulted in a widely cited research-based book (Barrett PS 1995), now in
its second edition. This emphasis on the performance of buildings carried through into a European project
(PeBBu) on the innovation required to achieve performance-based building (Sexton M and Barrett PS
2005). About this time Barrett took up the role of championing the CIB theme of Revaluing Construction,
which drove a reassessment of the role of the built environment in the economy (Barrett P S 2007; Barrett
P 2008), but the analysis had already influenced the UK construction strategy (National Platform for the
Built Environment 2006) in its emphasis and scaling of the built environment, rather than just focusing on
construction. It also made clear the importance, but difficulty, of assessing the impact of the built
environment on users throughout a building’s life. This focus led to the organisation of an activity within
SCRI entitled “Senses, Brain and Spaces” working with an international network of built environment
specialists and neuroscientists, psychologists and sociologists. The aim was to better understand the
impacts of spaces on individuals’ health, well-being and productivity. The outcomes of a workshop of 28
international specialists held on 8/9 March 2007 are reported at www.rgc.salford.ac.uk/peterbarrett and
the argument for shaping our assessment of sensory impacts on the brain’s integration of inputs is made in
Barrett and Barrett (2010). This work in turn led directly to an exploration of the issues focused on schools
via SCRI’s work on Optimal Learning Spaces (OLS), working with / part funded by Manchester City Council
and studying their primary schools’ building programme. Phase 1, between 2007-09 centred on an
extensive synthesis of the literature linked to post occupancy evaluations (Zhang Y and Barrett PS 2010),
resulting in “Optimal Learning Spaces: Design Implications for Primary Schools” (Barrett PS and Zhang Y
2009). This output led to an invited presentation to the final session of the “Great Schools Enquiry” chaired
by Baroness Estelle Morris and hosted by the British Council for School Environments (BCSE), in London, on
25 January 2010. A paper based on surveys of pupils’ views is pending publication (Barrett PS, Zhang Y and
Barrett LC 2011) and a twin paper of teachers’ views is ready for submission (Zhang Y and Barrett PS 2011).
In parallel exploratory visits, with invited talks, have been made to specialist sensory laboratories, such as
the Lighting Research Centre at the US Rensselaer Polytechnic Institute, Neuroscience and sight activity at
the Salk Institute and acoustic and air quality facilities at CSTB’s Grenoble campus. Phase 2 of the OLS
initiative has, since 2010, moved to action research on live schools projects, leading to learning about
practical interventions and their constraints. This has shown that there are serious pressures (time, custom,
regulations, costs concerns, etc) that make it hard to maintain a clean focus on creating high quality
learning environments. It has also indicated that, to survive amongst these competing forces, a strong
evidence base is essential in relation to the value of the sensory environment – hence this project proposal.
To study the holistic impact of built spaces on people in the wild is a complex problem. The above
activities both indicate the importance of the issue and extensive preparatory work the team has done.
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For this particular project the rigorous mathematical treatment of complex data is essential, and so the
research team has been augmented by Professor Kobbacy, as Co-I. Khairy Kobbacy, PhD, MSc, BSc is the
Professor of Management Science at the University of Salford. He has long-standing interests in “applied”
Operational Research, working in close collaboration with statisticians in the Centre for Operational
Research and Applied Statistics for almost 20 years. His research interests in operations management are
directed towards the development of intelligent management systems for operations. He chaired four
European Conferences on Intelligent Management Systems in Operations, Salford ( 1997- 2009). Professor
Kobbacy was awarded the Operational Research President’s medal in 1990 and the Literati Club Award in
2001. He was a vice president of the Operational Research Society, UK. His research in maintenance has
been funded by industry and the research councils. Kobbaccy’s publications are mainly in the area of
maintenance modelling which is demanding in terms of the use of mathematical modelling and statistical
analysis as it addresses real world situations, in an analogous way to the proposed project. Example
outputs are an edited book on Complex Systems (Kobbacy K and Murthy P 2008) and a well cited paper on
the application of COX’s Proportional Hazards Model (PHM) (Kobbacy K, Fawzi BB, Percy DF et al. 1997).
The research team has been further strengthened by establishing a core partnership with
Nightingale Associates and Blackpool Council, who respectively provide a strong supply and demand
perspectives. See their letters of support for more details, plus one from the BCSE making clear its
invaluable support. This is important in facilitating practical aspects of the research, but also so that the
rigorous research effort at the core of this proposal delivers results into a context that is attuned to the
practical take up of the findings into practice. All of these partners are fully committed to the powerful
promulgation of the results and this will leverage the research team’s good track record for making an
impact in practice.
Taking just two recent examples of impact achieved, the AHRC funded Dedepa (Designing Dynamic
Environments for the Performing Arts) project made an in-depth investigation of the reality of project
briefing for theatres and critically reviewed the ACE / CABE guidance for clients (Short C A, Barrett PS, Dye
A et al. 2007) with the result that the Cambridge / Salford research team were engaged to update the
guidance to take it beyond a simplistic stress on fixing all the major parameters at the very start (Short A,
Barrett P, Fair A et al. 2009). The second example is in a different domain, that of managing academic
workloads, and here LFHE and HEFCE funded research projects have led to an analysis of current practice in
the UK HE sector, with recommendations for improvement (Barrett PS and Barrett LC 2007 b) and, through
a managed network of twelve universities, examples of a wide range of good practice (Barrett P and
Barrett L 2009) The strategy of highlighting problems, showing what is possible and publicising it widely
has led to an upsurge of interest across the sector (90 universities were represented at the over-subscribed
launch event) and has also led HEFCE to change its Transparency Review regulations to encourage the use
of workload systems rather than the ineffective sample staff workload surveys used to date.
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Description of proposed research and its context
Background
The contribution of the built environment to society has been set out in various reports in recent years. For
example the Pearce Report highlights the crucial role construction plays sustainable development (Pearce
2003). The Revaluing Construction initiative of the International Council for Research and Innovation in
Building and Construction (CIB) (mentioned above) goes broader and in particular stresses the importance
of better understanding the value delivered to society through the use phase of buildings.
In parallel a literature and area of practice has developed around “building performance” with a wide
variety of typologies on offer (Preiser W and Vischer J C 2005). A well-known example of this sort of work is
the PROBE series of case studies / user interviews that focused on building comfort issues (Leaman and
Bordass 1999). The value of post-occupancy performance (POE) studies of buildings has been popularly
called for to assess how well they perform compared with the client / design aspiration and there are some
well developed techniques for a multi-method assessments to be carried out (Zeisel J 2006). The idea is
that the intelligence will then feed forward into new designs, however, POEs are not commonplace and the
lessons learnt are not generally available for use in practice (Bordass B and Leaman A 2005). Another strand
of development in recent years has been the rise in polemical works arguing for “inside-out design” (Frank
KA and Lepori RB 2007) that builds from a focus on user needs and challenges the visual dominance of
much design effort (Pallasmaa J 2009). This is twinned by those arguing specifically for aspects of sensorysensitive design (Derval D 2010; Lehman ML 2011).
These efforts stress that the evidence of building users’ needs should be taken more fully into
account and provide copious case study examples of potential elements of “good” design solutions.
However, there remains a big gap between these putative elements and effectively achieving the desired
holistic effects for users. Norman (1998) has highlighted the pervasive difficulty of designing “everyday
things” in a way that helps and supports users. But, some aspects have gained traction, for example Ulrich’s
(1984) classic evidence of the positive healing effects of views of nature. Less known, Manhke (1996)
provides comprehensive advice specifically on colour for various building types and it is interesting even
now how designers find it hard to accept that “white is not neutral” (Pernao J 2010). But in any event these
fascinating inputs still fall a long way short of comprehensively addressing the design challenge. Nasar
(1999) perhaps goes furthest in his extensive synthesis of the factors to consider in architectural design
competitions, but in the process he highlights the disjuncture between architects’ design preferences and
those of “normal” building users.
Linking multiple aspects into a coherent design is even harder to do. This raises the question of the
choice of the over-arching perspective to synthesise the available alternatives into an optimal design. One
emergent way forward is to use the notion that as the user’s brain is the place that resolves the multiple
sensory inputs for that individual, these mental mechanisms can provide a basis for understanding the
combined effects of sensory inputs on users of buildings. This is the approach being led by the Academy of
Neuroscience for Architecture (ANFA), based in San Diego, and underpinned by works such as Eberhard’s
book (Eberhard J P 2007). So far the only exemplar study using this sort of thinking has focused on
Alzheimer’s care facilities (Zeisel J, Silverstein N, Hyde J et al. 2003). Building out from an understanding of
the impaired functionality of the patients’ brains this study has successfully shown how characteristics of
the built environment can have medically convincing (but non-pharmacological) impacts on symptoms such
as aggression and depression.
So there exists an important research challenge around the issue of better understanding, and
evidencing, the holistic impact of spaces on users. Using the paradigm of the brain’s response to multiple
sensory inputs there is initial evidence that causality between the complex characteristics of built
environments and users’ responses can be revealed. If this can be take forward, then powerful insights to
inform the improved design and adaptation of built spaces can be expected.
Research Hypothesis and Objectives
The research question at the centre of this proposal is: can evidence be found for a link between a
building’s design and the performance of the occupants of that building? To explore this complex issue it
makes sense to focus on building uses for which clear and objective user performance measures are
available. It is also helpful if occupants are closely associated with identified spaces for a reasonable
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percentage of the day so increasing the likelihood that the influence of those spaces can be captures. An
obvious possibility would be hospitals, or maybe prisons, but it has been decided to take primary schools as
the special case to address the above general challenge. The principal reasons are that performance
measures are available, the pupils tend to stay mainly in one classroom and the research team has quite
extensive background experience of this use type. In addition the study is timely given the recent James
Review (2011) of schools in which the transformative impact of school buildings beyond being simply “fit
for purpose” is called into doubt at the same time as national standardisation in designs is proposed. A
Scottish report indicates big (negative) gaps between design intentions and user satisfaction (Scottish
Executive 2004). Thus, results that evidence the aspects of design that have a positive effect on pupils could
be crucial in ensuring the new designs respond to educational as well as cost drivers, especially as the
capital allocation for schools in 2011-12 is still £2137m. Lastly, it would be accepted by most, that anything
that could improve the educational opportunities of the UK’s children should be welcomed.
Taking the above general research question and rooting it in the representative case of primary
schools, the Proposition that this study seeks to explore is that: Demonstrable evidence can be found for
the holistic impact of school building design on the learning rates of children in primary schools.
The novelty of this focus is analogous to the general situation set out in the background section
above. Despite a lot of design knowledge about schools, there is nothing that links the integrated features
of school design directly with the impact on pupils’ performance. DfES design guides cover many specific
elements, but the general criteria in DfES (2002) Building Bulletin 95 conspicuously, do not include creating
good learning environments in favour of stressing flexibility, open to the community, etc. The OECD’s CELE
exemplary school design competition (OECD 2011) continues to extend a database of designs with
interesting features, but again the criteria do not stress the creation of good learning environments.
Children in Scotland (2011) and Sheffield University’s “Imagine: Inspirational School Design” website
similarly provide case study examples of interesting practice. The OECD’s (2009) extensive international
surveys of teachers provide their perspective, but do not evidence, or make the link to, pupil performance
explicit. In addition to the above, there are decades of specialist reports and reviews of specific aspects of
school design, many based on laboratory experiments, such that a lot is known about individual factors,
such as colour, air quality and space configuration, in isolation, but not in combination. Some texts exist
that bring together this material as illustrated evidence to support school design (Dudek M 2008; Lippman
PC 2010), but this does not inform the choices to be made between competing (good) alternative elements
of design. Nor does it appear to provide sufficient evidence to reliably resist the crowding out of the advice
by other practical and financial pressures (based on action research experience).
This study will draw from the all of the above material, but energise them by addressing the missing
causal link between holistic school designs and the impact on student performance. Filling this gap should
have a transformative impact as it will enable researchers and designers to contextualise and calibrate the
specific elements being considered within an holistic impacts model. Various approaches are possible, but
for this type of research question: laboratory studies will not include the interactive richness of research in
the wild; interviews alone will only surface probably conflicting opinions; case studies or participant
observation alone would be hard to generalise from and, as mentioned above, all of these have been done
and do not provide an integrated evidential link to pupil performance. So the time is ripe to carry out a
hypothesis-driven, empirical study (Gray DE 2009), with the following objectives:
 To gather objective measures of the improvement in primary school pupils’ performance;
 To gather objective measures of Other Factors that could contribute to improvements in pupils’
performance;
 To build an Environment–Human Performance (E-H-P) model;
 To combine the above data in an analysis that identifies the discrete impact of primary school
classrooms, as learning environments, on pupils’ improvements in performance;
 To set out the implications for school design and, more broadly, for other building uses.
In general it has been suggested that a good learning space should ideally provide “an environment
characterised by a combination of ‘high challenge’ and ‘low threat’ …” (OECD 2002). This subtle
combination is to be operationalised in this project’s thinking about the E-H-P model via the hypothesis
that the characteristics of the brain’s functioning in synthesising sensory inputs highlights the importance
of three aspects of our environment, namely: naturalness, individualisation and the appropriate level of
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stimulation (Barrett P and Barrett L 2010). These relate respectively to: our basic animal demands, the
needs of children in particular and the implications of the school learning situation. This broad framework
will be used to guide the selection of physical dimensions to measured, working within the rich context
provided by the multitudinous focused studies as summarised by the research team (Barrett PS and Zhang
Y 2009).
Programme and Methodology
This study will draw particularly from the methodological experience of three key studies (which when built
upon below will be indicated with A, B or C):
 Zeisel et al’s (2003) study of the holistic impact of care facilities on Alzheimer’s patients (A)
 Ulrich’s (1984) focused study on the impact of views of nature on hospital patients (B)
 Heschong Mahone’s (2003) studies of daylighting and its effects on pupil learning (C)
The core element of this study will be an expert assessment of 150 diverse classrooms (c4500 pupils)
to test, improve and validate an Environment-Human-Performance (E-H-P) model (A) that allows the
measurement, and so assessment, of built spaces and their human impacts (this scale of study is judged to
be practicable and compares well with A, B, C). A pilot study of five classrooms in each of ten schools
within the Blackpool area will be carried out in the first six months. The survey instruments and
“indicators” (A) will be carefully trialled and refined on the selected classrooms of one of these schools first.
The sample of schools has already been identified to provide a diverse sample of school types and sizes.
Once started the project will further identify diverse classrooms within each school, in terms of their
physical characteristics (orientation, level, size, etc). This will provide the basis for an initial analysis and
development of the E-H-P model. Building from the pilot study over the following nine months, the
assessment of spaces will then extend to twenty more schools (100 classrooms) of diverse types and
locations across UK. The data collected will support further analysis to refine and robustly evidence the EH-P model. The theme of diversity in the spaces sampled is important to provide maximum opportunity for
the impact of the physical factors to become evident (A,B,C). The support of BCSE and Nightingale
Associates (plus the research team’s own contacts) mean that accessing the additional twenty schools will
not be a problem.
After this main phase of measuring spaces and developing the E-H-P Model, a second six month
phase of validation and refinement will be carried out through targeted, follow-up researcher observation
of 50 classrooms, c1500 pupils (C). This phase is essential to calibrate the range of major factors identified
with rich descriptions. In addition, observation of dynamic user influences, especially in relation to outliers,
will strengthen the evidence base for the E-H-P model. The final phase of three months will focus on
finalising the analysis and writing up the results and their initial promotion to the sector.
Alongside achieving diversity in the main independent variable being studied (the physical spaces),
there are the issues of accessing consistent dependent variables across the whole sample and measuring
(C) or controlling for (A,B) other independent variables. Focusing on the choice of dependent variables
first, discussions with educational experts within Blackpool Education Authority have been very valuable
(C). The measures that are available for primary school children, and are consistently used across the UK,
are rooted in regular teacher assessments of individual pupils against a National Curriculum Assessment
Framework that defines “levels” of attainment. This data is, in the case of Blackpool at least, independently
moderated via a sample of 25% of pupils. Levels of attainment for pupils are assessed for English (reading
and writing in KS1), Mathematics and Science. The effort and expertise that goes into these assessments
far exceeds anything the project team could replicate and the measures are well known and understood by
practitioners in the sector. Thus, the decision was clear that these measures should be used if they could
be accessed. In principle the data belongs to the pupils and so a non-contentious process has been
carefully designed with Blackpool to gain their (parents) informed consent via the chosen schools. In
addition to these pupil performance measures, the Authority will also make available data on attendance
and behaviour, more specifically: overall absence (authorised or unauthorised), persistent absence (<85%
attendance), exclusions and permanent exclusions. It would be possible to obtain perceptual views from
teachers and pupils, but this has been done before and it has been decided that the novel and necessary
contribution of this study will be provided by a focus on the measurable performance ad behaviour metrics
listed.
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The assessment of the impact of the built environment on pupils’ performance is complicated by
other significant independent variables. The risks to achieving the former will be mitigated by the explicit
inclusion (or controlling out) of the major additional factors (A,C) in the analysis. The main issue is
variability amongst the pupils themselves across classrooms / schools, but will be addressed (C) by focusing
on progress within a given year, so self-calibrating for variability amongst the children themselves. This
then opens the opportunity to use entry level of achievement / age which is known to determine quite a
large part of progress achieved and so would sweep in issues of individual ability and social economic
background. Anonymous individual data will be collected and known gender differences addressed by
randomly selecting equal numbers of boys and girls for each class sample. Other school factors are known
to have an impact. Physical factors such as the size of the school and of individual classes will be factored
in as measurable variables, but this leaves elements such as the number and quality of the teachers, and
the general school ethos (C). Working with Blackpool it has become apparent that it will be possible to
access a measure of teacher quality via the school Heads, who regularly use the national Ofsted
“judgement framework” for the continuous, internal assessment of their teaching staff. This expert
assessment is felt to be superior to more abstract measures such as qualifications and years’ experience
(C). In terms of questions of school ethos, the selection of groups of classes from discrete schools will
provide an analytical way into assessing this, aide by formal Ofsted reports and Heads’ advice on any
special teaching programmes. This combination of independent and dependent variables is given in Fig 1.
Fig 1: Overview of HEAD Research Design (with egs of BE factors)
The data will be collected and analysed around the chosen classrooms and their pupils. The pupil / teacher
performance data will be from the last complete school year. The built measures will be assessed by
researchers visiting each classroom and carrying out an expert evaluation. This will follow a strategy driven
by the hypothesised shape of the E-H-P Model starting with basic measures, such as orientation and
window size, but then moving to more complex assessment, as many of the factors are both curvilinear and
interactive. For example too much daylight could result in glare, and, without adequate shading devices
and ventilation could lead to overheating in the classroom. The researchers will use a standardised
assessment schedule, including initial ratings and will also make a photographic record. The immediate
characteristics of the classroom will be supplemented by similar data on the physical features of the
surrounding school estate, viewed (distinctively) from the given classroom. The Work Plan provides the
timings of the activities over two years and indicates the main inputs of the RFs.
The analytical strategy will reflect the pilot and main phases of the fieldwork. Given the relatively
small scale of the pilot phase (10 schools), a standard multiple regression analysis will be used on this data
to explore and identify the covariates that are likely to have a significant impact on pupil performance. In
the main phase (total 30 schools) a multilevel modelling approach (Goldstein 2010) will be employed with
random effects. This is deemed to be the appropriate approach as it can reflect the “nested” structure of
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the data (pupil in class in school) so avoiding misleading results due to overestimation of significance.
Further, multilevel models will be able to provide more insight into the complex situation being studied,
whilst also offering a rigorous way of dealing with unmeasured “school effects” by allowing the residuals to
be partitioned at this level. Multilevel modelling is well tested in educational research, a specialist support
Centre exists at Bristol University (2011) and this approach was used with success in Zeisel’s study of built
environment effects on Alzheimer’s patients (A). A specialist off-the-shelf package will be used to carry out
the modelling (eg SSI’s HLM model).
The project will be carried out within a carefully designed management context. The research team
is small and experienced and will work to the programme through constant interaction and weekly
progress meetings. Practical externality will be provided by close working with Nightingale Associates and
Blackpool Council representing two key stakeholder perspectives. Focus will be given to this core
collaboration through formal progress meetings every two months with Nightingales, and Blackpool as
appropriate. Formal reports will be produced at months 6, 15, 21 and 24 (see Work Plan). In addition an
international Sounding Panel has been created to further contextualise the project, first, by providing an
independent perspective on the findings about schools and, second, by assessing the generalisability of the
results to other sectors, such as health, housing and offices. This panel is, thus, made up of a high level
group of experts with, variously, experience of schools, other building types, knowledge of sensory impacts
or neuroscience perspectives. The panel will meet in the form of a one-and-a-half-day workshop at the end
of the pilot phase and towards the end, at 21 months. Eighteen experts, who have already explicitly
confirmed their agreement to be on the panel, are listed in the “Pathways to Impact” section. Further,
complementary, members will be identified to provide a robust group of around 25.
Academic Impact
There is a lot of research about design and the built environment, quite a bit of it concerning schools, but
as argued in the case above, what is lacking is clear evidence of holistic impacts on pupil learning. The key
academic output of the project will be a rigorously evidenced E-H-P model identifying the built
environment factors that impact on pupils’ learning, together with examples calibrating the scales and
exemplary case studies of major dimensions illustrating their effects in use. This novel, holistic, testable
engineering model of school buildings will evidence the causal links and their strengths to pupils’ progress
in learning. The results will be published in refereed journals and presented at relevant conferences. It will
be of great interest to researchers in the field of design and facilities management where the impact of the
building on users is often a key issue. The findings will provide a basis for further studies in these fields and
will serve to calibrate the relative importance of a wealth of existing contentions and case study examples.
For researchers in specialist areas, such as light, acoustics, colour and air quality, the model will
provide a broader context within which their findings can be located, as well as potentially stimulating new
studies to address unexpected emphases in the findings. For educational researchers focused on pedagogy
and policy, depending on the strengths of the correlations found, the results will stimulate a reassessment
of the importance of the built environment context as an active lever for educational achievement.
Successful results focused on schools will also provide a template, in the E-H-P Model, for further
studies to better evidence the impacts on their users of hospitals, offices, homes, etc. Through this process,
the relatively hidden value of the built environment to society will be taken to a new level of
understanding. This will have economic and societal benefits as set out in the Pathways to Impact section.
References
Barrett P (2008). Revaluing Construction. Oxford, Blackwell Publishing.
Barrett P and Barrett L (2009). The Management of Academic Workloads: Improving Practice in the Sector.
Research and Development Series, Leadership Foundation for Higher Education.
Barrett P and Barrett L (2010). "The Potential of Positive Places: Senses, Brain and Spaces." Intelligent
Buildings International 2: 218-228.
7
Barrett P S (2007). "Revaluing Construction: An Holistic Model." Building Research and Information 35(3):
268-286.
Barrett PS (1995). Facilities Management: Towards Best Practice. Oxford, Blackwells Scientific Publications
Ltd.
Barrett PS and Barrett LC (2007 b). "Current Practice in the Allocation of Academic Workloads." Higher
Education Quarterly 61(4): 461-478.
Barrett PS and Zhang Y (2009). Optimal Learning Spaces: Design Implications for Primary Schools. Salford,
UK, SCRI.
Barrett PS, Zhang Y and Barrett LC (2011). "A Child’s Eye View of Primary School Built Environments."
Intelligent Buildings International 3: 1-17.
Bordass B and Leaman A (2005). "Making feedback and post-occupancy evaluation routine." Building
Research and Information 33(4): 361-375.
Bristol University (2011). "Centre for Multilevel Modelling." Retrieved 21/09/2011, from
www.bristol.ac.uk/cmm/learning/multilevel-models/.
Children in Scotland (2011). Making Space 2010: architecture and design for children and young people.
Edinburgh, Children in Scotland.
Derval D (2010). The Right Sensory Mix. Heidelberg, Springer.
DfES (2002). Building Bulletin 95: Schools for the Future: Designs for Learning Communities London, HMSO.
Dudek M (2008). Schools and Kindergartens: A Design Manual. Basel, Birkhauser.
Eberhard J P (2007). Architecture and the Brain: A New Knowledge Base from Neuroscience. Atlanta,
Ostberg.
Frank KA and Lepori RB (2007). Architecture from the Inside Out. Hoboken, NJ, John Wiley.
Goldstein, H. (2010). Multilevel Statistical Models. London, Wiley Series in Probability and Statistics.
Gray DE (2009). Doing Research in the Real World. London, Sage.
Heschong Mahone Group (2003). Windows and Classrooms: A Study of Student Performance and the
Indoor Environment. Fair Oaks CA, Californian Energy Commission.
James S (2011). Review of Education Capital. London, HMSO.
Kobbacy K, Fawzi BB, Percy DF, et al. (1997). "A Full History Proportional Hazards Model For Preventive
Maintenance Modelling." Journal of Quality and Reliability Engineering International 13: 187-198.
Kobbacy K and Murthy P, Eds. (2008). Complex System Maintenance Handbook. London, Springer-Verlag.
Leaman, A. and B. Bordass (1999). "Productivity In Buildings: The 'Killer' Variables." Building Research &
Information (1999), 27(1), 4-19 27(1).
Lehman ML (2011). "How sensory design brings value to buildings and their occupants " Intelligent
Buildings International 3(1): 46-54.
8
Lippman PC (2010). Evidence-based Design of Elementary and Secondary Schools: A Responsive Approach
to Creating Learning Environments. Hoboken, NJ, John Wiley.
Mahnke F (1996). Color, Environment & Human Response. New York, John Wiley & Sons.
Nasar J (1999). Design by Competition: Making Design Competition Work. Cambridge, Cambridge University
Press.
National Platform for the Built Environment (2006). Research Priorities for the UK Built Environment.
London, Constructing Excellence.
Norman DA (1998). The Design of Everyday Things. London, MIT Press.
OECD (2002). Understanding the Brain: Towards a New Learning Science. Paris, OECD.
OECD (2009). Creating Effective Teaching and Learning Environments: First Results from Talis. Paris, OECD.
OECD (2011). Designing for Education: Compendium of Exemplary Educational Facilities. Paris, OECD CELE.
Pallasmaa J (2009). The Thinking Hand. Chichester, John Wiley.
Pearce, D. (2003). The Social and Economic Value of Construction. The Construction Industry's Contribution
to Sustainable Development, CRISP.
Pernao J (2010). The "Otherness" of White. Colour and Light in Architecture, IUAV, Venice, Knemesi.
Preiser W and Vischer J C (2005). Assessing Building Performance. Oxford, Elsevier-ButterworthHeinemann.
Scottish Executive (2004). Evaluation - Building Our Future: Scotland's School Estate Edinburgh, Scottish
Executive.
Sexton M and Barrett PS (2005). "Performance Based Building and Innovation: Balancing client and industry
needs." Building Research and Information 33(2): 142-148.
Short A, Barrett P, Fair A, et al. (2009). Building Excellence in the Arts: A Guide for Clients. London, CABE.
Short C A, Barrett PS, Dye A, et al. (2007). "Impacts of value engineering on five capital arts projects."
Building Research and Information 35(3): 287-315.
Ulrich R (1984). "View Through a Window May Infkuence Recovery from Surgery." Science 224: 420-421.
Zeisel J (2006). Enquiry by Design. New York, W.W. Norton and Co.
Zeisel J, Silverstein N, Hyde J, et al. (2003). "Environmental Correlates to Behavioral Health Outcomes in
Alzheimer's Special Care Units." The Gerontologist 43(5): 697-711.
Zeisel J, Silverstein N M, Hyde J, et al. (2003). "Environmental Correlates to Behavioral Health Outcomes in
Alzheimer's Special Care Units." The Gerontologist 43(5): 697-711.
Zhang Y and Barrett PS (2010). "Findings from a Post-occupancy Evaluation in the UK Primary Schools
Sector." Facilities 28(13/14): 641-656.
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Zhang Y and Barrett PS (2011). "A Teacher’s View of Primary School Design." Intelligent Buildings
International Pending submission.
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