COBRA Paper 1998c
Transcript of COBRA Paper 1998c
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!!This!is!the!author’s!version!of!a!work!that!was!submitted/accepted!for!publication!in!the!following!source:!!!Lowe,!D!J!(1998)!The$development$of$expertise$in$early$stage$cost$estimating$through$experiential$learning.!In!Proceedings!of!the!RICS!Construction!and!Building!Research!Conference,!Oxford!Brookes!University,!2P3!September,!Edited!by!M!Keeping!and!D!Shiers,!ISBN!1P873P640P23P4,!The!Royal!Institution!of!Chartered!Surveyors,!Vol.!1!pp.!83P101,!eScholarID:243817!!This!file!was!downloaded!from:!https://www.escholar.manchester.ac.uk!!©!Copyright!1998!RICS!Foundation!!!Reproduced!in!accordance!with!the!copyright!policy!of!the!publisher.!!Notice:!Changes$introduced$as$a$result$of$publishing$processes$such$as$copy9editing$and$formatting$may$not$be$reflected$in$this$document.$For$a$definitive$version$of$this$work,$please$refer$to$the$published$source.$!
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The development of expertise in early stage design cost estimating through experiential learning David J Lowe
Department of Building Engineering, UMIST, PO Box 88, Manchester, M60 1QD
Abstract
The importance of experience to the early stage design cost estimator is well established
within current literature. It is believed to be acquired over time and has been associated with
the development of knowledge, familiarity, feedback, professional judgement and estimating
expertise. Despite this, however, relatively little is known of how practitioners use their
experiences in developing expertise in estimating. The aim of this investigation was,
therefore, to establish how practitioners learn from their experiences within the work
environment, the nature of that experience and their assessment of its importance to the
development of expertise in early stage design cost estimating. This paper distinguishes
between learning styles (stable or fixed characteristics), measured using a revised version of
Kolb=s (1985) Learning Style Inventory (LSI 1985), and approaches to learning (task
specific strategies), measured by an approaches to learning at work inventory specifically
developed for this project.
Findings from a fully structured interview survey, using a multi-sectional questionnaire, of
experienced early stage design cost estimators (quantity surveyors, n = 84) are presented.
They confirm the perceived high importance attributed to experience in the development of
expertise in early stage design cost estimating. Moreover, they support the perception that
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early stage design cost estimators learn by doing (Experiential Learning). Descriptive
statistics are presented to illustrate the estimators= estimating experience, performance and
practice, while project specific experience and its effect on the way estimates are prepared is
examined. Further, subscales of Kolb=s LSI 1985 and factor scores for the approaches to
learning questionnaire are correlated with measures of time as an estimator to investigate
their relationship with age and tested for homogeneity within the sample.
Keywords: quantity surveyors, design cost estimating, expertise, experiential learning,
learning styles, approaches to learning
Introduction
Experience is perceived by quantity surveyors to be a significant factor in the accuracy of
cost prediction and in the development of the expertise that underlies professional judgement.
Skitmore and Lowe (1995) raise the question what is meant by experience? In practice,
experience is often equated to length of service or age. However, what is really important is
specific experience, derived from estimating projects of a similar type and size. They submit
that while suggesting the general circumstances in which experience may be obtained, this
adds little to the knowledge of what is valid experience. This knowledge they suggest may
provide insights into the crucial question of how what is learned from experience may be
acquired in an efficient and effective way.
Experiential learning is learning which is rooted in doing and experiencing. It involves the
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individual, past and present experience and the learning environment. The aim of this
investigation was, therefore, to establish how practitioners learn from their experiences
within the work environment, the nature of that experience and their assessment of its
importance to the development of expertise in early stage design cost estimating.
Estimating Experience
The association of experience and the quality of estimating performance has been extensively
reported. Oteifa and Baldwin (1991) conclude that the single most important factor in the
production of any accurate estimate is an estimator's experience and expertise. Similarly,
Skitmore and Lowe (1995) suggest that the most significant factor is the estimator's
knowledge of general price levels and that this is invariably acquired through experience.
Further references to experience include: the importance of insight gained through a
background of experience (Park, 1966); estimating competency is essentially dependent on
personal experience (Grant, 1974); the implication that familiarity with specific projects, that
is, 'direct experience', enables the production of more accurate estimates (Morrison and
Stevens, 1980); and the suggestion that "... the achievement of an increase in accuracy is
dependent upon the means by which knowledge and experience gained on previous projects
is related to future work" (Morrison, 1984).
Brandon (1990) considers that "The expert uses his imagination, knowledge and experience
to fill in the gaps and expand the information available on the project at that time". Also,
Ferry and Brandon (1991) suggest that the estimator's intuition is based upon experience,
which is determined by the amount of data passing through the practitioner's hands. Beeston
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(1983) considers the development of judgement a slow and painful process and to be the
result of experience: that is, making many mistakes and learning from them. Further,
Skitmore et al. (1990) conclude that experience contributes to expertise by way of the ability
to identify important aspects of projects and judge market conditions.
As the acquisition of expertise is thought to be an ongoing process (Skitmore et al. 1990),
involving long and consistent practice (Staszewski, 1988) and that lack of practice could lead
to a deterioration of forecasting skills, it can be deduced that the early stage design cost
estimator learns from experience. The investigation, however, of the influence of experience
as a developmental factor in estimating expertise has, to date, been limited in its approach.
It has been considered in terms of the perceived importance of experience to the design cost
estimator. Skitmore et al. (1990) found that practitioners have a consistently high regard for
their own forecasting ability, and the role of work experience and knowledge of market
conditions in contributing to this ability. Alternatively it has been investigated in terms of
quantitative measures of experience such as the length of service as an estimator and the
number of estimates prepared. These measures, however, were found not to be the
determinants of estimating ability (Skitmore et al., 1990). Skitmore et al. (1990) suggest that
other factors such as the type of experience and personality factors must be considered.
Ogunlana (1989) and Lowe (1992) indicate that, while experience is considered significant in
developing the requisite skills and knowledge of the design cost estimator, in practice
practitioners are failing to learn adequately from experience. They suggested reasons for this
include the lack of understanding of how to maximise the potential of learning from
experience and the lack of adequate feedback systems that highlight inadequate estimating
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performance.
It is not, therefore, the length of service but the quality of the experience, the reactions of the
estimator to the experience, the successful incorporation of the experience into working
practices and an individual's knowledge base that is important: the ability of the individual to
learn from experience. Consequently, it is the insight and development derived from the
experience and the methods or strategies adopted by the early stage design cost estimator,
which enable them to effectively learn from experience, that requires further investigation.
Learning from experience
According to Chickering (1976) experiential learning means "the learning that occurs when
changes in judgements, feelings, knowledge, or skills result for a particular person from
living through an event or events". Also, it is considered synonymous with 'meaningful
discovery' (Boydell, 1976); the process that links education, work and personal development
(Kolb, 1984); and rooted in doing and experience. Further, it illuminates that experience and
provides direction for the making of a judgement as a guide to choice and action (Hutton,
1989). Kolb (1984) defines learning as "the process whereby knowledge is created through
the transformation of experience" and occurs " through the active extension and grounding of
ideas and experience in the external world and through internal reflection about the attributes
of these experiences and ideas". He adapted the earlier Lewinian experiential learning model
when formulating his experiential learning model. This comprises the cycle of concrete
experience, observation and reflection, formation of abstract concepts and generalisations and
testing implications of concepts in new situations.
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The importance of reflection
For Boreham (1987) learning from experience really means learning from reflection on
experience. Boud et al. (1985) define reflection as a form of response by the learner to
experiences, ".. a generic term for those intellectual and affective activities in which
individuals engage to explore their experiences in order to lead to new understandings and
appreciations". They believe that it is the evaluation of experience that is important in
learning. Reflection is triggered by the recognition that in some respects the situation is not
normal and therefore in need of special attention. The trigger may be an unexpected action or
outcome, or just an intuitive feeling of unease that something is not quite right (Eraut, 1994).
Most models of experiential learning assume that reflection will happen, but the application
of reflection will depend on the disposition of the learner (Eraut, 1994). Further, reflection is
the experiential skill in which people tend to be most deficient (Duley 1981), while most
expert performance is on-going and non-reflective (Eraut, 1994). Boud et al. (1985) suggest
that it may be the ability to reflect which characterises those who learn effectively from
experience.
Learning styles and approaches
We all acquired complex cognitive strategies, that is, preferred patterns of perceiving,
remembering, thinking, and problem solving, which are a major component of learning style
(Smith, 1982). Biggs (1988) suggests that the terms learning styles and learning strategies
appear to refer to two different aspects of learning. Cognitive styles are seen as stable, even
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unchangeable, individual characteristics that partly control and organise more-fluid cognitive
strategies. Strategies and approaches are ways of handling particular tasks and are amenable
to change through intervention (Ramsden, 1988). Styles are, therefore, focused on the person,
strategies on the task (Biggs, 1988).
Kolb et al. (1979) postulate four learning orientations that relate to the four stages of Kolb's
(1976) experiential learning model. Concrete Experience - an experience-based, involved
approach to learning; Reflective Observation - an observation-based, impartial approach to
learning; Abstract Conceptualisation - a conceptually-based, analytical approach to learning;
and Active Experimentation - an action-based, active approach to learning. Kolb (1976)
derived from these four learning orientations four basic learning style types: the converger -
whose dominant learning abilities are abstract conceptualisation (AC) and active
experimentation (AE); the diverger - who has the opposite learning strengths to the
converger; the assimilator - whose dominant learning abilities are abstract conceptualisation
and reflective observation; and the accommodator who has the opposite learning strengths of
the assimilator (Kolb et al. 1979). Similarly, Honey and Mumford (1992) define four similar
learning styles: activists, reflectors, theorists and pragmatists.
There are a variety of theories expounded on the influence of learning strategies or
approaches. Pask (1976) has distinguished between two major categories of mental
competence that reflect the individual's preference for either a 'Serialist' or 'Holistic' approach
to learning. The serialist approach is to string a sequence of cognitive structures together,
while the holist in contrast, remembers and recalls material as a whole. Alternatively, Kagan
discovered an impulsivity-reflectivity dimension to individual learning (Lovell, 1980).
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Objectives:
The following specific objectives for the investigation were generated:
! To investigate how practitioners consider they learn from experience, the nature of
that experience and their assessment of its importance.
! To assess the practitioners' learning styles and approaches to learning within the
working environment.
! To investigate the relationship between learning styles, approaches to learning and
length of time in the profession.
! To investigate differences in the learning style subscales and factor scores of the
approaches to learning at work questionnaires based upon practitioner subgroups.
! To investigate differences between the practitioner and novice quantity surveyor
samples for the learning style questionnaire subscale scores.
Methodology
The investigation adopted a fully structured interview survey requiring the interviewees to
complete a multi-sectional questionnaire. The questionnaire comprised: an experience profile,
which provided information concerning the position of the subject within their organisation,
their estimating experience, performance and practice; a revised randomised version of
Kolb's (1985) Learning Style Inventory (LSI - 1985); and an approaches to learning
questionnaire (ALQ), which required the subjects to rate the strength of their agreement to
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twenty-four statements on a five-point agreement scale. The original scoring method of
Kolb's LSI - 1985 was replaced by a four-point agreement scale. The rationale for this was to
remove the ipsative nature of the inventory. The ALQ statements were derived from Kolb et
al's (1979) guide for analysis of personal problem solving processes; Kolb's (1984) adaptive
competencies and work abilities; Mumford's (1980) skills involved in effective learning
behaviour and the rational approach to learning; Honey and Mumford's (1989) knowledge
and skills items and abilities of the ideal learner; Richardson (1990) Approaches to studying
questionnaire; Smith's (1982) post project analysis form and Gibbs' (1988) abilities associated
with each stage of the learning cycle. The population for the investigation was experienced
quantity surveyors (involved in early stage design cost estimating) based within Greater
Manchester, Central Lancashire and South Lakeland. The area of study was selected as
representative of North West England. Ultimately, 84 practitioners from 77 practices took
part. This represents 45% of the target organisations.
In addition to the structured interviews with practitioners, the revised version of Kolb's LSI -
1985 was administered to students enrolled on full-time and part-time built environment
courses at five institutions of higher education located within the North West. The sample
comprised 63 students (19%) on full-time subdegree programmes, 131 students (39.6%) on
full-time BSc degree programmes and 137 students (29.5%) on a part-time BSc degree
programmes in Quantity Surveying. The sample was taken to represent the novice quantity
surveyor.
Analysis
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Descriptive statistics were calculated for each question relating to the practitioners'
experience profile, estimating experience, performance and practice. The mean, standard
deviation and internal consistency coefficients (using Cronbach's alpha and the
Spearman-Brown split-half reliability test) were calculated for the subscale scores of Kolb's
revised LSI - 1985 . The items of the LSI-1985 and ALQ were ranked based on the mean
score. A six ("k") factor analysis was performed for the ALQ and factor scores generated.
The subscale and factor scores were then correlated with measures of the number of years the
quantity surveyor had prepared estimates. The subscale and factor scores were also analysed
for differences between different subgroups by means of one-way analysis of variance
(ANOVA) and its comparable non-parametric test.
Results
Profile of respondents
Position within the company/practice: The responses revealed that 40 of the interviewees
were partners or director of their organisation (47.6%), 20 were associates (23.8%), 20 were
principal or senior quantity surveyors (23.8%) and 4 were quantity surveyors (4.8%). This
indicates that predominantly the subjects held a senior position within their organisation.
Further, 28 of the interviewees were Fellows of the RICS (33.3%), 45 were Professional
Associates (53.6%), two were members of the Society of Surveying Technicians (2.4%), one
was a probationer (1.2%) and eight (9.5%) had no association with the RICS. This indicates a
general level of professional attainment within the sample. The practitioners had been
providing general cost advice for a mean of 16.7 years (SD 7.8) and had specialised after
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approximately four years general estimating experience. Also, the length of general
experience is comparable with the mean length of corporate membership of the RICS at 16.7
years (SD 9.0).
Self-professed expertise: The responses indicated that 58 of the interviewees (69%)
considered themselves experts, while 26 (31%) did not. Respondents in the latter group
described themselves or their expertise in this area as experienced, competent/proficient,
reasonable, moderate or average or classified themselves in relation to the type of work they
carried out. Lowe (1992) suggested that some estimators, while being very proficient at the
task, were, however, very reluctant to refer to themselves as experts. A further question,
therefore, sought to assess the individual's self-rated competency level by a less emotive
mechanism. The results in Table 1 indicate a high self regard for their estimating
performance.
<<< Insert table 1 here >>>>
Experience factors
Information about the importance of general estimating experiences to the development of an
early stage estimator was obtained:
Influence of experience: The significance of work experience in developing several
acknowledged abilities considered important by early stage estimators was investigated. The
results (Table 2) indicate that experience had been very significant in developing the ability
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to identify important aspects of projects and significant in developing their ability to judge
market conditions, apply appropriate estimating techniques and select suitable historic cost
data. The importance of learning by doing was further emphasised. Responses revealed that
17 practitioners (20.2%) considered positive experiences to have had the most influence,
while 7 (8.3%) considers negative experiences and 60 (71.4%) considered a balance of both
had the most influence on their development as an early stage estimator. This concurs with
the comments of Bannister and Fransella (1971) that the experience of being 'wrong' is
educationally as important as the experience of being right.
<<< Insert table 2 here >>>>
Development strategies: The results presented in Table 3 reveal a tendency for the quantity
surveyors to develop through a practical active mode associated with individual involvement
in estimating practice as oppose to group activity or a more passive role illustrated by
watching and imitating others. The practitioners considered exposure to or involvement in
estimating practice to be very significant in helping them to develop as early stage estimators.
Their ability to question how things were done, being coached by a mentor and learning by
trial and error were considered significant. However, the more passive approaches, acting
upon advice of others and learning by watching and imitating, were considered neither
significant nor insignificant. Only eleven interviewees proffered further factors. Five
interviewees referred to project specific experience, three mentioned awareness or common
sense, while others referred to feedback, the introduction of IT, advancement and "enjoying
getting stuck in".
<<< Insert table 3 here >>>>
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Systematic reflection on the outcomes of estimates: The investigation revealed that 14
(16.7%) of the practitioners did not systematically reflect on the outcomes of estimates.
Further, while the remaining 70 (83.3%) interviewees considered that they did reflect on the
outcomes of estimates, 45.7% indicated the use of self-assessment as their sole means of
evaluation. Systematic reflection is considered crucial for effective experiential learning, for
example, Sch`n (1987) suggests that it is only through some process of systematic reflection
that a professional may achieve growth and self-renewal. Interestingly, only four practitioners
used diaries or logbooks for systematic reflection despite them being considered helpful in
aiding reflection on experiences (Gibbs, 1988). The results, however, are in keeping with
Beeston (1983) who maintained that few practitioners objectively measure their estimating
accuracy, Ogunlana (1989) who found an absence of a system requiring regular monitoring of
estimating performance and Duley (1981) who considers reflection to be the skill that most
people lack. The results lead to the conclusion that, despite the recommendations of Flanagan
and Norman (1983), Morrison (1984), and Ogunlana (1989), many practitioners have
inadequate feedback systems on their estimating performance.
Prompt to reviewing estimating procedures: A further question sought to determine what
factors would prompt the practitioners to review their estimating practice. The results reveal
that those factors concerned with performance, i.e. a desire to continually improve, client and
self dissatisfaction, also new opportunities and the introduction of new standards to be
positive prompts to reviewing the way they prepared estimates. However, new forms of
contract etc. and major catastrophe were considered to exert a moderate effect; while
reorganisation or the imposition of new people at a higher level were not considered to have
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an affect. The results would suggest that the quantity surveyors consider themselves proactive
besides reactive.
Barriers to changing or questioning estimating procedures: Potential barriers to
practitioners reviewing the way they prepared estimates were investigated. Despite a variety
of blocks to learning suggested in the literature, pressure of work, feeling harassed and short
of time were suggested as the main barriers to changing or questioning estimating
performance, while lack of acceptance from colleagues may have an effect. However, most of
the interviewees considered the remaining factors: reliance on existing methods and
techniques, past negative experiences of change, fear of failure, lack of support from
colleagues and anxiety or discomfort at trying something different not to prevent them from
reviewing their estimating practices. This indicates that the interviewees considered
themselves independent of others and confident in their ability to question and review their
estimating practices. Only one interviewee suggested a further factor and that was movement
away from tried and proven procedures. This finding is in accord with Houle (1980) who
states that the major self-perceived barrier to learning for professionals is insufficient time.
Overall, however, the estimators considered they were unlikely to change or experiment with
the way they prepared estimates within the next twelve months.
The findings above confirm the perceived high importance of experience in the development
of an early stage design cost estimator. Moreover, they support the perception that early stage
design cost estimators learn by doing.
Project specific experience
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Project or task specific experience is thought to be significant in the development of
estimating expertise. Questions designed to elicit information on the importance of project
specific estimating experiences were included in the study.
Description of a significantly learning event: To investigate further the type of event
through which significant learning takes place the practitioners rated twelve bipolar
descriptors of learning from experience (Table 4). This revealed that the type of event
through which the practitioners developed their estimating expertise was predominantly at
work, active, practical, job-centred, competitive, self-initiated and self-directed. The
remaining five factors appear distinct to the individual, having a less general effect.
<<< Insert table 4 here >>>>
Methods of obtaining knowledge: The practitioners were required to indicate how they had
obtained knowledge by rating eight specific factors between two extremes: education (Formal
courses, structured training, cpd etc.) and experience (Learning by doing). The results in
descending order of rating of the experience dimension are presented in Table 5. They
indicate a strong agreement that knowledge of clients' preferences, architects' preferences and
prejudices, contractors in the locality and project specific construction knowledge was gained
by experience. A combination, however, of experience and education had resulted in task
specific knowledge of the effects of the location of a project, estimating techniques, tendering
processes and background construction knowledge.
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<<< Insert table 5 here >>>>
Approaches to Learning
All twenty-four statements used in the ALQ were ranked, based on their mean scores (Table
6). The results indicated a preference for an open and collaborative approach to learning,
represented by a high rating of: "I can accept help from others"; "I am open to new angles and
possibilities"; "I make a conscious effort to learn from experience"; "I am able to take risks";
"I can recognise and admit to making errors" and "I tend to openly share my experiences with
colleagues". They also suggested a reluctance for self-assessment or self-appraisal,
represented by the low rating of: "I make specific action plans"; "I regularly assess my own
development needs"; "I can describe the steps I need to go through to learn from experience";
"I can express my thoughts fluently"; "I often take time to review my
experiences/performance"; and "I ask for feedback on my performance". The low rating
given to goal setting is of concern as Rogers (1986) and Boydell (1976), among others, have
referred to the importance of goal setting to learning, while Handy (1985) believes that
individuals who learn fastest are those who set clearly defined goals for themselves.
Similarly, the low rating of self-assessment may be linked to individuals acquiring a vested
interest in not noticing their inadequacies. Heron (1985) refers to this as falsification, while
Eraut (1994) comments that "... self-knowledge of performance is difficult to acquire, and
self-comment tends to be justificatory rather than critical in intent". Finally, the low rating of
the ability to describe how individuals learn from experience was reasonably predictable as
Wankowski (1991) states that most people are not consciously aware of how or why they
learn.
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<<< Insert table 6 here >>>>
Principal factors extraction with an oblique (Oblimin) rotation was used to determine the
underlying dimensions of the 24 items of the ALQ (Lowe, 1996). The six factor solution
accounts for 43.7% of the total variance in the ALQ. The internal consistencies of the six
factors were measured by the squared multiple correlations. At 0.84 for factor one, 0.78 for
factor two, 0.83 for factor three, 0.68 for factor four, 0.77 for factor five and 0.77 for factor
six they were internally consistent. Variables were ordered, grouped by size and interpretive
labels suggested. Factor one 'Creativity' is associated with the ability to take risks, see
connections, adjust quickly, convert ideas into action and openness. Factor two 'Self-
management' is associated with the ability to assess ones own development needs, analyse,
formulate action plans and review performance. Factor three 'Indifference' is associated with
not making a conscious effort to learn from experience, question things or investigate new
concepts. Factor four 'Review' is associated with the ability to analyse the success of others,
share experiences, and adjusting quickly. Factor five 'Amendment' is associated with making
a conscious effort to learn from experience, listening and adjusting quickly. Finally, factor six
'Self-protection' is associated with not recognising and adjusting to errors, accepting help or
asking questioning. Six factor scores were generated using the regression method.
Individual Learning Styles
The mean and standard deviations for the LSI - 1985 subscales are presented in Table 7. They
reveal the following order of preference: Active Experimentation (AE), Abstract
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Conceptualisation (AC), Reflective Observation (RO) and Concrete Experience (CE), based
on the descending order of mean subscale scores. This is the same order of preference as
Smith and Kolb's (1986) normative data. Cronbach's alpha and Spearman-Brown split half
reliability scores between 0.74 and 0.92, suggested sufficiently strong reliability results for
the four learning styles. This suggests the inventory is internally consistent. The correlation
matrix for the LSI - 1985 subscales, however, revealed no support for the AC-CE and AE-RO
bipolar coordinates. This again confirms that these relationships may have been a function of
the 'ipsative' scales used in the original instruments. The interpretation, therefore, of Kolb's
Learning Style Type Grid that utilises these scores, should be carried out with great care. The
two bipolar dimensions of Kolb's LSI - 1985 indicated a tendency for the sample to favour
the Accommodator quadrant, although the mean coordinates represented the Converger style.
<<< Insert table 7 here >>>>
All forty-eight statements used in the inventory were ranked, based on their mean scores.
Those statements given a high rating included: "When I learn I like to see results from my
work"; "I learn best when I am practical"; "I learn best from a chance to try out and practice";
" I learn by doing"; and "When I learn I become involved and interested". While those given
a low rating included: "I learn best when I rely on my feelings"; "When I learn I like to deal
with my feelings"; "When I am learning I am quiet and reserved"; and "I learn by feeling".
Despite Hutton's (1989) belief that experiential learning requires doing and experiencing, the
results indicated a preference for the active rather than the emotional items.
Relationships between Learning Styles, Approaches to Learning and length of time in
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the profession
The subscale scores for the LSI - 1985 and the Approaches to Learning factor scores were
correlated with three measures of the length of experience of the practitioners: the number of
years as an estimator, the number of years of specialism within estimating and the number of
years as a corporate member of the RICS. Pearson's 'r' and Spearman's 'rs' correlation matrices
are presented in Tables 8 and 9.
<<< Insert table 8 & 9 here >>>>
The results for the Approaches to Learning Questionnaire factor scores indicate that the
practitioners' rating of the Creativity approach increases significantly with all the measures of
time in the profession. Approach A (Creativity) correlates significantly and positively with
the number of years of specialism as an estimator at the 0.1% level, with the number of years
as an estimator at the 1% level and with the number of years as a corporate member of the
RICS at the 5% level. However, Approach B (Self-management), Approach C (Indifference),
Approach D (Review), Approach E (Amendment) and Approach F (Self-protection) do not
correlate significantly with any measure of length of experience.
The results for the LSI - 1985 subscales indicate that the practitioners' scores for Abstract
Conceptualisation and Concrete Experience increase significantly with measures of time in
the profession. Concrete Experience (CE) correlates significantly and positively with the
number of years as an estimator at the 5% level; while Abstract Conceptualisation (AC)
correlates significantly and positively with the number of years of specialism as an estimator
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and the number of years as an estimator at the 5% level. However, Reflective Observation
(RO), Active Experimentation (AE), AC-CE and AE-RO do not correlate significantly with
any measure of length of experience.
Tests for differences in the LSI-1985 subscales and the ALQ factor scores based on
subgroups
The subscales and factor scores of the two inventories were tested for differences between
subgroups. Analysis one contained two subgroups based on the position of the practitioner in
their organisation: partners or directors (n = 40) and quantity surveying practitioners (n = 44).
Analysis two contained two subgroups based on their self-declared expertise at early stage
estimating: experts (n = 58) and non-experts (n = 26). Analysis three contained three
subgroups based on the practitioners class of membership of the RICS: Fellows (n = 28),
Professional Associates (n = 45) and non-members (n = 11). Analysis four contained three
subgroups based on method of reflection on estimating performance: peer appraisal (n = 36),
self assessment (n = 34) and no reflection (n = 14). Analysis five contained three subgroups
based on disposition of the practitioner to change: likely (n = 16), neutral (n = 16) and
unlikely (n = 56). The results are presented in Tables 8 and 9.
The Approaches to Learning Questionnaire
! Analysis one: The t-test for independent samples revealed highly significant
difference at the 1% level in the Approach A (Creativity) factor scores. Closer
examination revealed that the partner/directors' mean score was significantly higher
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than that of the quantity surveying practitioners
! Analysis two: Revealed no significant differences in the subscales or factor scores.
! Analysis three: ANOVA revealed a significant difference at the 5% level in the
Approach A (Creativity) factor score. Closer examination revealed no two groups
significantly different at the 5% level.
! Analysis four: ANOVA revealed a highly significant difference at the 1% level in
Approach B (Self-management) factor score. The Kurskal-Wallis test revealed a
significant difference at the 5% level in the Approach D (Review) factor score. Closer
examination revealed: for Approach B the scores of practitioners who used peer
appraisal (group 1) or self appraisal (group 2) were significantly higher than those of
practitioners who had no formal methods of reflecting on the outcome of estimates
(group 3); and for Approach D the factor score of practitioners who used peer
appraisal (group 1) was higher than that of practitioners who used self appraisal
(group 2).
! Analysis five: ANOVA revealed a significant difference at the 5% level in Approach
D (Review) factor score. Closer examination revealed: for Approach D the mean
score of practitioners likely to change their estimating methods (group 1) was
significantly higher than that of practitioners who were neutral towards change (group
2).
Analysis one provides support for the finding that Approach A Creativity increases
significantly with time in the profession, while analysis four and five provide support for the
approaches to learning factor scores in terms of construct validity.
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Individual Learning Styles
There were no significant differences in the subscales scores for any practitioner subgroup
(Analyses 1-5). This would indicate a homogeneous group in terms of learning styles. An
explanation for this finding could be that individuals adapt their learning styles to meet
organisational norms (Socialisation). Alternatively, it could be due to individuals selecting
career paths that match their preferred learning styles, organisations selecting employees with
learning styles to meet their organisational norms or practitioners developing learning styles
to conform to professional requirements.
The LSI-1985 subscales were also tested for differences between practitioner and student
subgroups. Analysis one contained two subgroups: practitioners (n = 84) and students - main
investigation one total sample (n = 326). Analysis two contained two subgroups: practitioners
(n = 84) and part-time students main investigation one - private practice and Local Authority
employees only (n = 51). The third analysis contained three subgroups: partners or directors
(n = 40), quantity surveying practitioners (n = 44) and part-time students main investigation
one - private practice and Local Authority employees only (n = 51). The results are presented
in Table 9.
! Analysis one: The t-test for independent samples revealed significant differences at
the 5% level in the RO and AC subscales. The Mann-Whitney U - Wilcoxon W Rank
Sum W test revealed significant differences at the 5% level in CE and AE-RO
subscales. Closer examination revealed: for the CE, AC and AE-RO subscales the
practitioners' mean scores were significantly higher than those of the students, while
23
for the RO subscale the practitioners' scores were significantly lower than those of the
students.
! Analysis two: The Mann-Whitney U - Wilcoxon W Rank Sum W test revealed a
significant difference at the 5% level in the CE and highly significant differences at
the 1% level in the AE and AE-RO subscales. Closer examination revealed: for the
CE, AE and AE-RO subscales the practitioners' scores were significantly higher than
those of the students.
! Analysis three: The Kurskal-Wallis test revealed a highly significant difference at the
1% level in the AE-RO subscale score and significant differences at the 5% level in
the CE and AE subscale scores. Closer examination revealed: for the CE subscale the
partners/directors' score was significantly higher than that of the students, for the AE
subscale both the partners/directors' and quantity surveying practitioners' scores were
significantly higher than that of the students, for the AE-RO subscale the
partners/directors' score was significantly higher than that of the students.
For Concrete Experience (Analysis 1 & 2), Abstract Conceptualisation (Analysis 1) and
Active Experimentation (Analysis 2) the scores for the practitioners were significantly higher
than those of the students; for Concrete Experience (Analysis 3) the scores for the
partners/directors were significantly higher than those of the student; and for Active
Experimentation (Analysis 3) the scores for both the partners/directors and quantity
surveying employees were significantly higher than those of the students (Analysis 3). For
Reflective Observation (Analysis 1) the scores for the practitioners were significantly lower
than those of the students. The findings provide support for the practitioners declared
preference for an active learning style, represented by learning by doing (Active
24
Experimentation and Concrete Experience), rather than a passive style, represented by
learning by observation (Reflective Observation), when compared with the student sample.
As previously stated, systematic reflection is considered crucial for effective experiential
learning, for example, Eraut (1994) considers reflection, both in terms of a form of
deliberation and metacognition, to be an important contributor to professional expertise. The
results are, however, in keeping Casey (1983) who suggests that the regular opportunity to
pause and reflect before having another go is not necessarily present in a manager's working
life and Eraut (1994) who states that most expert performance is on-going and non-reflective.
Summary of findings
The following findings have been drawn from the investigation:
! Practitioners rate the importance of experience in the development of estimating
ability very highly.
! Experience is considered to be acquired through preparing estimates, therefore,
learning by doing, which is very significant in developing the ability to identify
important aspects of projects and significant in developing the ability to judge market
conditions, apply appropriate estimating techniques and select suitable historic cost
data.
! Exposure to or involvement in estimating practice is deemed to be very significant in
the development of an early stage design cost estimator. Also the individual's ability
to question how things were done, being coached by a mentor and learning by trial
25
and error were considered significant. However, the more passive approaches, acting
upon advice of others and learning by watching and imitating, were considered
neither significant nor insignificant.
! The type of event through which practitioners believe they develop their estimating
expertise is predominantly at work, active, practical, job-centred, competitive, self-
initiated and self-directed.
! The level of systematic reflection on the outcomes of estimates was low.
! The main barrier to changing or questioning estimating performance is deemed to be
pressure of work, feeling harassed and short of time. However, generally the
estimators were unlikely to change or experiment with the way they prepared
estimates within the next twelve months.
! Practitioners prefer an active learning style, represented by learning by doing (Active
Experimentation, Concrete Experience), rather than a passive style, represented by
learning by observation (Reflective Observation), when compared with the student
sample. Further, their preference for Abstract Conceptualisation and Concrete
Experience increases significantly with measures of time in the profession.
! Practitioners are self-confident, preferring an open and collaborative approach to
learning but exhibiting a reluctance for self-assessment or self-appraisal. Further their
preference for the approach labelled creativity increases significantly with length of
time in the profession.
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30
$Table 1: Frequency, mean and standard deviation for self-rated level of competence
(n = 84)
1
2
3
4
5
Mean
SD
Moderate
0
1
23
48
12
Very high
3.85
0.67
Notes: Bold highlights mode
Table 2: Frequencies, means and standard deviations for the contribution of work experience to the development of abilities (n = 84)
Very Insignificant
Very Significant
1
2
3
4
5
Mean
SD
Identify important aspects of projects
0
2
2
18
62
4.67
0.65
Judge market conditions
0
6
19
24
35
4.05
0.97
Apply appropriate estimating techniques
2
4
20
29
29
3.94
1.00
Select suitable historical cost data
0
9
22
29
24
3.81
0.98
Notes: Bold highlights mode
Table 3: Frequencies, means and standard deviations for approaches to learning (n = 84)
Very Insignificant
Very Significant
1
2
3
4
5
Mean
SD
Exposure to/ involvement in estimating practice
2
3
12
28
39
4.18
0.97
Your ability to question how things are done
0
6
16
38
24
3.95
0.88
Being coached by a mentor or supervisor
3
14
21
29
17
3.51
1.10
Learning by trial and error
8
16
14
28
18
3.38
1.28
Acting upon advice of others(not a mentor)
4
13
41
20
6
3.13
0.93
Learning by watching and imitating others
10
18
26
19
11
3.04
1.21
Notes: Bold highlights mode
31
Table 4: Frequencies, means and standard deviations for rating of 12 bipolar
descriptors of learning from experience (n = 81)
1
2
3
4
5
Mean
SD
At work
44
22
10
3
2
Not at work
1.73
0.99
Practical
36
35
4
6
0
Theoretical
1.75
0.86
Competitive
16
29
26
6
4
Uncompetitive
2.42
1.05
Self initiated
16
31
12
14
8
Initiated by others
2.59
1.26
Self directed
16
30
11
16
8
Directed by others
2.63
1.28
Sudden
15
20
22
18
6
Incremental
2.75
1.21
Alone
16
18
19
16
12
With others
2.88
1.35
Pleasant
9
20
23
18
11
Unpleasant
3.03
1.21
Distant
7
15
29
17
13
Recent
3.17
1.17
Qualification orientated
2
12
32
24
11
Curiosity/Personal interest orientated
3.37
0.98
Passive
1
2
18
39
21
Active
3.95
0.84
Life centred
1
1
13
35
31
Job centred
4.16
0.83
Table 5: Frequencies, means and standard deviations for methods of obtaining task specific knowledge (n = 84)
Education
Experience
1
2
3
4
5
Mea
n
SD
Clients' preferences and prejudices
0
2
1
19
62
4.68
0.62
Architects' preferences and prejudices
0
3
7
18
56
4.51
0.80
Contractors in the locality
0
3
9
19
53
4.45
0.83
Project specific construction knowledge
0
2
15
30
37
4.21
0.82
The effects of the location of a project
2
11
26
25
20
3.60
1.07
Estimating techniques
2
15
26
25
16
3.45
1.07
Tendering processes
2
16
26
23
17
3.44
1.09
Background construction knowledge
3
21
24
16
20
3.35
1.20
33
Table 6: Ranking of Individual Questions of Approaches to Learning Questionnaire (n = 84)
Item
Mean
SD
8
3.64
0.57
I make a conscious effort to learn from experience
7
3.40
0.82
I can accept help from others
12
3.23
0.63
I am open to new angles and possibilities
21
3.14
0.81
I can recognise and admit to making errors
3
3.08
0.95
I tend to openly share my experiences with colleagues
9
3.08
0.79
I'm good at asking questions even when there is a risk to my self esteem
16
3.07
0.69
I am good at seeing connections between things
22
2.98
0.73
I often question things that I hear or read
14
2.95
0.74
I can convert ideas into feasible action
5
2.89
0.98
I reach conclusions via careful thought and analysis
15
2.81
0.87
I am able to take risks
24
2.81
0.83
I like to investigate new concepts before committing myself
18
2.77
0.81
I am able to adjust quickly to new, unfamiliar situations
11
2.71
0.74
I can express my thoughts fluently
23
2.70
0.86
I try to relate new ideas to real life situations
20
2.61
0.86
I tend to convert criticism into constructive suggestions for improvement
10
2.55
0.86
I tend to listen patiently to colleagues
1
2.54
0.95
I often take time to review my experiences/performance
6
2.48
1.06
I have detailed recall of past experiences
19
2.37
0.97
I make specific action plans
17
2.36
1.14
I ask for feedback on my performance
2
2.35
0.95
I can describe the steps I need to go through to learn from experience
13
2.27
0.95
I regularly assess my own development needs
4
1.85
0.96
I tend to analyse what other successful people do
34
Table 7: Means, Standard Deviations, Reliabilities and Scale Intercorrelations for Kolb's
Learning Style Inventory - 1985 revised subscales (n = 84)
Reliability
Correlation matrix
Scal
e
Mea
n
SD
R1
R2
RO
AC
AE
AC-CE
AE-RO
CE1
32.43
4.61
0.74
0.80
0.304** 0.281**
0.395*** 0.403***
0.420*** 0.420***
-0.518*** -0.519***
-0.022 -0.008
RO
32.86
6.57
0.88
0.92
0.450*** 0.471***
0.270* 0.270*
0.150 0.149
-0.786*** -0.765***
AC
36.82
4.85
0.83
0.89
0.442*** 0.414***
0.582*** 0.489***
-0.148 -0.179
AE
40.49
4.40
0.81
0.87
0.040 -0.069
0.383*** 0.371***
AC-CE
4.39
5.21
0.84
0.85
-0.118 -0.173
AE-RO
7.63
6.85
0.86
0.91
P 'r' S 'rs'
*** = p# 0.001 ** = p# 0.01 *= p# 0.05 R1 = Cronbach's Alpha, R2 = Spearman-Brown split-half NB: 1 = Lilliefors (Kolmogrow-Smirnov) test of normality indicates that a non-parametric test is appropriate (P 'r' = Pearson's Correlation Coefficients , S 'rs' = Spearman's Correlation Coefficients)
35
Table 8: Correlations between Approaches to Learning Questionnaire factor scores and Number of years experience, and ANOVA and tests for differences for Approaches to
Learning Questionnaire factor scores
n
Approach
A
Approach
B
Approach
C
Approach
D
Approach
E
Approach
F No. Years Estimator1
84
P 'r' S 'rs'
0.329** 0.300**
0.029 -0.006
-0.097 -0.125
-0.198 -0.189
-0.007 -0.060
-0.088 -0.074
No. Years Specialism1
84
P 'r' S 'rs'
0.393*** 0.357***
0.150 0.120
-0.111 -0.126
-0.029 -0.044
-0.048 -0.058
-0.189 -0.161
No. Years RICS1
73
P 'r' S 'rs'
0.227
0.245*
-0.163 -0.175
-0.014 -0.035
-0.062 -0.058
0.017 0.026
-0.193 -0.220
Partner/ Employee
40 44
't'1 't'2
2.69** -2.51*
0.29 -0.10
0.41 -0.25
-1.86 -1.94
-0.20 -0.42
-0.73 -0.57
Expert/ Non-expert
58 26
't'1 't'2
0.86 -0.67
1.22 -1.00
-0.18 -0.05
-1.95 -1.85
0.59 -0.17
0.16 -0.24
RICS Members.
Fr x2
3.46* 5.44
0.97 2.65
0.75 1.01
1.79 3.74
1.10 3.52
1.31 2.44
Methods of Reflection
Fr x2
0.84 2.64
6.97**
12.11**
0.11 0.19
2.98
6.29*
1.84 2.65
0.58 1.02
Disposition to change
Fr x2
1.01 0.92
0.39 2 0.57
0.84 2.31
3.15* 5.52
1.39 2.66
2.45 4.17
*** = p≤ 0.001 ** = p≤ 0.01 *= p≤ 0.05 't'1 = t-test for Independent Samples, 't'2 = Mann-Whitney U - Wilcoxon Rank Sum W Test, Fr = F Ratio Oneway Analysis of Variance, x2 = Chi-Square Kurskal-Wallis 1-Way Anova NB: 1 = Lilliefors (Kolmogrow-Smirnov) test of normality indicates that a non-parametric test is appropriate NB: 2 = Levene test for homogeneity of variances indicates that a non-parametric test is appropriate
36
Table 9: Correlations between Kolb's Learning Style Inventory - 1985 subscales and
number of years experience, and ANOVA and tests for differences for LSI-1985 subscales
n
CE1
RO
AC
AE
AC-CE
AE-RO
No. Years Estimator1
84
P 'r' S rs'
0.221* 0.219*
0.003 -0.010
0.182
0.220*
-0.010 -0.023
-0.026 -0.045
-0.009 -0.033
No. Years Specialism1
84
P 'r' S 'rs'
0.213 0.195
-0.049 -0.069
0.248* 0.224*
-0.003 -0.030
0.043 0.027
0.045 0.045
No. Years RICS1
73
P 'r' S 'rs'
0.207 0.212
-0.120 -0.109
0.026 0.069
-0.171 -0.150
-0.163 -0.208
0.003 -0.013
Partner/ Employee
40 44
't'1 't'2
1.23 -1.44
-1.24 -1.32
1.25 -1.26
0.32 -0.29
0.10 -0.26
1.40 -1.20
Expert/ Non-expert
58 26
't'1 't'2
0.67 -1.01
0.12 -0.09
0.70 -0.74
-0.28 -0.11
0.05 -0.32
-0.29 -0.21
RICS Membership
Fr x2
0.47 0.68
1.14 2.72
0.61 0.30
1.18 1.92
0.24 1.71
1.71 2.60
Methods of Reflection
Fr x2
1.64 3.07
2.92 5.22
1.85 2.54
2.49 5.93
0.28 0.99
0.37 2 1.12
Disposition to change
Fr x2
1.15 3.83
1.55 2.88
0.82 1.79
1.37 2.29
1.23 3.99
0.38 0.67
Practitioners/ Students
84
326
't'1 't'2
2.42* -2.13*
-2.02* -1.91
1.99* -1.80
0.84 -0.53
-0.27 -0.46
2.29* -2.35*
Practitioners/ PT Students
84 51
't'1 't'2
2.68** -2.50*
-0.94 -0.70
1.64 -1.57
3.07** -2.72**
-0.94 -0.74
3.07** -2.81**
Position in organisation
Fr x2
4.22* 7.91*
1.34 2.27
2.12 3.80
4.71** 7.43*
0.452 0.58
5.72** 9.45**
*** = p≤ 0.001 ** = p≤ 0.01 *= p≤ 0.05 't'1 = t-test for Independent Samples, 't'2 = Mann-Whitney U - Wilcoxon Rank Sum W Test, Fr = F Ratio Oneway Analysis of Variance, x2 = Chi-Square Kurskal-Wallis 1-Way Anova NB: 1 = Lilliefors (Kolmogrow-Smirnov) test of normality indicates that a non-parametric test is appropriate NB: 2 = Levene test for homogeneity of variances indicates that a non-parametric test is appropriate