Paper presented to the National Conference on Agricultural and Food Mechanization 2012, 10-12 January at Pullman, Kuching, Sarawak

1. A Look at Engineering Based Approaches to Developing Harvest,
Processing and Controlled Environments for Essential Oil Production
Murray Hunter
Centre for Communication & Entrepreneurship
University Malaysia Perlis
Abstract
Agriculture is a complex activity requiring complex processes upon uncertain variables. Thus
developing propagation, production, harvesting, and post harvest equipment and processes
cannot be built upon precise theorem. In most cases these processes need to be developed
through observation, conceptualization, trial, error, insight, and emergent and heuristical
thinking. This requires the utilization of various types of thinking processes and converging,
discovery with trans-disciplinary knowledge. This paper examines agricultural engineering
development pathways with three examples the author has been involved within the essential
oil industry, 1. The development of automated tea tree harvesting through reengineering and
adaptation, 2. The development of distillation processes through incremental emergent
engineering and applying thermodynamic theories into practical situations, and 3. The
development of controlled environment vetivert production through conceptual development
and emergent innovation engineering.
Introduction
The ideal engineer is a composite ... He is not a scientist, he is not a mathematician,
he is not a sociologist or a writer; but he may use the knowledge and techniques of
any or all of these disciplines in solving engineering problems.
(N. W. Dougherty, 1955)
Over the time that humankind has existed upon the earth and society progressed from
hunter-gatherers to cultivators, we have encroached upon the Earth’s natural terrestrial
ecosystems with our agricultural systems. These human made eco-systems are not
compatible with the algorithms of nature and thus require our heavy intervention to maintain
their efficiency, productivity, and sustainability. Our interventions to achieve short-term
results have created many long term consequences that were not foreseen – where we
degraded the soil, increased salinity, contaminated our waterways, lowered our water tables,
as well as changing our micro-climates. In fact we do not really understand the true
interrelationships between the variables influencing the results of our agricultural activities,
as most often they are not direct cause and effect relationships (Lovelock 2005). Our
contrived agro-eco-systems are really too complex for us to understand completely (see
Paper presented to the National Conference on Agricultural and Food Mechanization 2012,
10-12 January at Pullman, Kuching, Sarawak

2. figure 1), and the way we really approach issues is through educated guesses based upon
short-term research results taking up limited correlating variables together with our personal
and collective experiences.
Infrastructure Government
Regulation
Positive Inputs Taxes &
Conducive weather Water Negative Outputs
subsidies
Climate Or Sunshine Trade
Floods, droughts, etc Nitrogen Runoffs, wastes,
environment
Agricultural inputs carbon
Research
Weather Fertilizers etc
Rainfall Knowledge
Wind Labour
Sunshine
UV radiation
Temperature Some
Humidity Resource inputs, Production Processes recycling
fertilizers, herbicides,
insecticides, machinery, back to
Human research capabilities Farm size & layout system
Habitisation
Organisation & methods
Knowledge Suitability of conditions
Suppliers & contractors Pollution (air, land & water) Propagation
Pollution Labour sources
Attitudes and concerns Water resources Cultivation Positive Outputs
(create hinterland where Products
farm part of)
Processing
Physical
Environment Customers
Financing & Marketing
Revenue flow
various kinds of back to
Soil capital
Topography system
Atmosphere
Natural flora & Negative Inputs
fauna habitat Business
Urbanisation Adverse physical
Environment Competition conditions
Low prices Pests & diseases
Markets Changing demand Pollution
Finance patterns Heavy metals
Trade environment
An Agricultural Enterprise as a
System
Figure 1. The agricultural enterprise as an eco-system (Hunter 2009, P. 326).
Due to eco-system and agricultural complexity, working within this environment requires an
overall environmental scale view as well as a discipline specific focused view. Our advances
in knowledge come from the ability to conceptualize and effectuate to develop new ideas and
theories that can be acted upon, in a similar way to how Einstein thought spatially and then
only reverted to the discipline of mathematics to retrospectively support his imagination
(Gardner 1993). Therefore in this way science becomes an art based on effectuation in not an
un-similar way that Picasso would have created his masterpieces1. Art infers
conceptualization, which infers creativity as the basis of our innovations. It is from the
concepts that an engineer then works backwards or emergently to solve a problem. Thus
1
Effectuation can be best explained by imagining how a person cooks a meal after coming home from
work. A person may look at what food ingredients are in the food pantry and refrigerator and then use
these ingredients to cook something that comes to mind. The process of effectuation is about thinking
of possibilities that may have potential and then evaluating and confirming the potential. Effectuation
does not rely on preconception, which is something akin to a painter sitting in front of a blank
painting canvass thinking about what to paint. Effectuation is about creating something that will
extend our ideas to fitting the solution.

3. engineering within this innovation paradigm loses its status as a discipline and gains its status
as the process of applying creative effectuation into solutions within the agricultural eco-
environment.
If the above argument string is accepted then it is not disciplinary knowledge that is so
important but rather the ability through our cognitive processes to apply our knowledge to
problems and applications in order to solve them. The fraternity of engineers has largely
ignored this but it is the application of and not the knowledge itself that brings solutions and
innovations. In solving agricultural problems particularly in the areas of mechanization and
controlled environments, we don’t apply algorithms to problems as this doesn’t work when
effectuation is needed. Heuristics are the key to guiding our emerging thinking and problem
solving. Any agricultural issue must be diagnosed through our thinking and applying
knowledge we have to the circumstances we observe, and every solution must be constructed
from what knowledge we have and implemented through our emergent thinking.
Heuristics is something belonging to logic, philosophy and psychology (Hutchinson 1971), a
thinking process something between the algorithmic and stochastic approaches (Polva 1945).
Stafford Beer likened heuristics to a living organism, its DNA and existence developed along
an algorithmic blueprint, but sustaining survival in the environment through heuristics (Beer
1981). Heuristics prescribe general rules for reaching goals, which we cannot reach
algorithmically, because we are not sure of the exact route to get there, as there are a number
of potential paths and these paths are at the point of beginning, unknown to us. Heuristics is
the way we actually live our lives, although we believe we are living life algorithmically with
rules. We need heuristics to make decisions, although we are not aware of this. When
heuristics are mentioned, we think of it’s contribution to artificial intelligence, but heuristics
is the reality of how an engineer develops new processes for products that the actual details of
the production process, although in principal is known, is mysterious in finite detail to the
engineer when starting out (Hunter 2006).
Agricultural Innovation
Innovation is a ”hot topic” in both the fields of agriculture and engineering, but too much
emphasis has been placed on amassing technology, rather than using amassed knowledge to
create new knowledge through emergent thinking. This has important national consequences
as Dr. Asma Abdullah states that there “is also the tendency for Asian countries, including
Malaysia, to deal with the issue of values in development by importing many technologies
and systems wholesale from abroad without going through the process of mental
transformation necessary to master them fully. Although Malaysia is going through rapid
transformation, our growth is one without development in the context of knowledge
contribution to science, engineering and technology. As long as we are consumers and
operators of sophisticated techniques, plants and technologies imported wholesale from
abroad, we are to a certain extent undergoing a technology-less form of industrialization.
This transformation of values and attitudes is a key issue in the nation’s development
agenda” (Asma 1995).

4. A lesson can be learned from some of the Japanese companies which have been able to
successfully compete on cost with their Chinese competitors. Japanese companies through
heuristics have been able to build their on plant and processing equipment at a third of the
cost of the Chinese (Chen 2004), who purchased their equipment from third party vendors.
The Japanese have realized that this is a source of competitive advantage and are able to
continue to export from a much higher cost base because of substantial capital savings. This
is a lesson for us in Malaysia aspiring to become a global player in both agriculture and
manufacturing industries in utilizing heuristical approaches in production process design.
Through heuristic design we are able to increase our production process knowledge base, rely
less on imported machineries and add both innovation and competitive advantage to the
sector. This is an example to follow in other chemical plant development, which potentially
can save firms large capital investments on new projects and acquire technology through
internal deduction and experimentation.
A heuristic approach to production process development in agriculture is an acquisition of
proprietary knowledge, which is exclusive to the firm. The effort to develop the process is
based on trial and error and thus is not easily duplicated quickly by other firms and can be
considered a barrier to entry into that particular product/market, thus enabling the firm to
practice monopoly differentiation for a period of time at a price premium to other firms. Thus
through heuristic production process development the firm has developed a source of
competitive advantage. If the new production process can be developed without heuristics,
then barriers to entry into the particular product/market would be low and the product
category would be crowded with competitors, where the future of Malaysian agriculture is
about developing high value added crop diversity that can compete in uncontested market
space, if possible.
Advances in agricultural mechanization and devising of controlled environments is about
improving productivity, and developing new value added products. Historically our advances
made in agricultural engineering and post harvest processing techniques has probably made a
larger contribution to agriculture production than the “green revolution” in the 1940s and 50s
which enabled the controlled supply of nitrogen and other nutrients to crops – allowing our
mono-cropping model. For example, it was the invention and subsequent development of the
cotton gin by Eli Whitney, saving hundreds of man-hours that allowed the rapid expansion of
the cotton industry of the Southern American States and mass settlement (Schweikart &
Pierson Doti 2010, P. 63).
Diagnosing Problems
Complex issues need two complementary ways of seeing. First we need to see the whole
environment the ‘what is” to get a contextual understanding of what a problem is. This
requires spatial thinking without being locked into specific disciplinary knowledge that will
restrict perspective. This is called field dependence where the environment is seen
holistically, connections between categories of information can be seen, and information is
processed in chunks (Witkin et. al. 1954).

5. Once connections can be made, problems or possibilities (opportunities) can be seen as a
potential to solve or develop. A change in thinking is required where much more focus and
attention should be given to the details. Thus holistic transforms into analytical thinking
which breaks down the whole into simpler parts where information can be reorganized. This
is called field interdependence where the individual items within the field, rather than the
field as a whole is considered (Vaidya and Chasky 1980). Field independency aids analysis,
to look at things in isolation to rest of field, categorize stimuli where one can impose their
own structures upon the problem, in a detached and impersonal manner (Hunter 2011, P.
219). One however must be mindful in the field independence mode that they don’t fall into
the rigidity of their discipline which may narrowly regulate their perceptions of the problem
(Jonassen & Grabowski 1993).
Focus enables researching specific issues that may lead to the solution of the specific problem
or enable the conceptualization of a new system, process, or piece of equipment. Decisions
will have to be made between a number of research priorities due to the multiplicity of
factors, varying degrees each factor influences. For example in the production of essential
oils, yield and quality, resource limits, time, available competencies and cost are all issues
that have influencing variables. The variables that most influence oil quality and yield would
be in this case selected for investigation. Potential factors influencing yield and quality can be
mapped out on the Ishikawa (fishbone) diagram approach as shown in Figure 2.
Location Climate Genetic Material
Humidity
Collection
Temperature Purchase
Sunshine hours
Topography UV radiation Plant physiology
Seasons
Slope & drainage Propagation Yield and
Rainfall characteristics Chemical
Constituents
of the
Humus Nutrients Method of extraction Essential Oil
Extraction time
Compactness Drainage & water
holding qualities
Pest & weed
pH control Pre-harvest handling
Mineral residuals Irrigation & preparation
Plant
densities
Soil type Time & method of
harvest
Agronomic Harvest &
Soil Practices Extraction
Practices
Figure 2: Factors Influencing Essential Oil Yield and Constituents on a Ishikawa (fishbone)
Diagram (Hunter 2009, P. 319).
It is from this position that the information extracted from the environment and re-organized
in an Ishikawa array that the following basic questions that can assist in prioritising research
and development can be asked. These include;

6. 1. What are the specific technical goals and objectives?
2. What are the major technology, infrastructure and climatic constraints (boundaries)?
3. What are the areas where innovations will develop quick improvements?
4. What is the probability of successful outcomes?, and
5. How do we choose between successful outcomes?
Modifying ‘off the shelf solutions’ and knowledge can solve many problems and should be
considered first. An ‘off the shelf solution’ is a research result that has proved positive, but
not tested in the site specific project that is intended. This will save project time and reduce
cost. Importing ideas, practices and equipment may not always suit local conditions and will
be expensive. Similar crops within the region may have methods and equipment that may be
easily modified to lead to a more effective solution. Unexpected costs should also be
identified.
Other factors may require capital intensive solutions, where cost competitive production is a
factor in success and sustainability. For many agricultural activities the use of mechanisation
has been proved to be more efficient than manual labour, even in very low labour cost
countries (Timmer 1973). However small scale decentralised mechanised production units
may not always necessarily lead to lower production costs and there are often some
advantages in flexibility, at early project stages (Austin 1981). The selection of appropriate
farming, harvesting and processing equipment will depend on the technology available, the
potential to adapt the equipment to the site and crop, and the finance available. Not much
equipment will be available ‘off the shelf’ and in most cases existing equipment will need to
be modified. Practical experience during trials is needed to understand exactly what changes
are necessary. Good metal and machine fabricators need to be identified.
The final part of this paper will briefly apply the above discussion to three different types of
projects and outline the engineering and cognitive approaches taken. The engineering aspects
will not be explained in detail as the author’s interest is in the thinking processes.
Project One: Automating the tea tree harvest process
Tea tree (Melaleuca alternifolia) was introduced to Malaysia by the author back in 1991
where a trial plot was planted at MARDI Serdang. With initial promising signs a much larger
trial was undertaken at Berseri, Perlis to take advantage of the unique dry season in that state.
Trial results showed that oil yields were far in excess of what commercial yields were in
Australia at that time and the economics showed that the net return per Ha. Was
approximately three times of what oil palm would provide (Hunter 1997). However at that
time harvesting and filling the distillation bins was a completely manual task. To be an
internationally competitive producer of tea tree oil, these tasks needed to be automated,
especially with rapidly rising wages and shortages of labour.
The Australian tea tree industry had developed many innovative ways of harvesting through
converting multi-crop foliage harvesters into meeting the requirements of specialized tea tree
harvesters. The German company CLASS developed a specialized tea tree harvester within
the Jaguar series which was very efficient, bringing the harvesting operation down to a one-

7. man operation and ability to harvest up to 10 Ha on a daily basis. However in today’s prices
the cost of this harvester is in excess of RM4.7 Million.
The Sabah Economic Development and Investment Authority (SEDIA) made the decision to
develop tea tree as a strategic crop for Sabah in 20082. There was not nearly the amount of
funds available to purchase specialized harvesting equipment from Germany. A local solution
was required. The decision was made to strip down and completely rebuild a corn harvester,
modifying the front-end cutters, mulchers, and foliage carry shafts so it could handle the
harvesting of tea tree and fill a bin attached to the end and carried by the harvester.
As a previous solution to this problem has been achieved, it became a matter of reengineering
and adaptation utilizing locally available items and parts. This required studying the present
solution and determining how this can be transformed into a local version. The critical issues
here were the cutters and flow of the trees into the mulchers after cutting. This was eventually
solved through postulating how to this could be achieved (the conceptual world), trialling this
in the field (experimentation), observing the results (Evaluation), and re-postulating and
modifying the cutters, re-trialling, observing and re-postulating again. Thus the development
process is part conceptualization and part real world experience in determining a final
outcome.
However the solution was not achieved through this single learning loop and the assumptions
had to be changed about the mode of cutting from a linear method along some rails to a
circular method (complete re-evaluation). This was done and the postulate, trial, observe, re-
postulate, and re-trial sequence continued until a positive solution occurred. Figure 3 below
represents this learning process.
Thus the thinking processes in this first example relied on spatial skills. Conceptualization is
a form of imagination and it is very important in being able to work backwards to determine
what will be the kinetic processes and how these can be best governed. The key to developing
this harvester was prior knowledge about how the other harvester worked as a process when
harvesting tea trees, knowledge about the capabilities of what is available locally, and spatial
imagination to be able to run this process within the mind. One is running the mind back from
the solution and adapting local parts to this end in a mental picture. The only way to
determine whether the solution works is to try it and observe and try to imagine what could
control the process better within the imagination.
The locally fabricated harvester cost RM220,000 to build, trial modify and put it into service.
2
This was undertaken by Institute of Development Studies (Sabah) before the formation of SEDIA.

8. Figure 3. The learning process (Hunter 2009, P. 219).
Project Two: Scaling up Essential Oil Distillation Processes
Essential oil distillation is a very well established process and although governed by
numerous laws of thermodynamics related to latent heat, gas laws, vapour laws, steam, and
phyto-chemistry, it is a relatively practical process commonly used around the world by both
large and small agricultural based enterprises. The distillation process is primarily influenced
by the nature of the plant material, characteristics of the volatile materials, and size and shape
of the distillation apparatus. These three factors vary the application of the various laws that
apply.
Consequently scaling up is not a linear process. Steam, vapour pressure, and general volatile
constituent vapourization characteristics will change as size scales up. Thus as designs are
scaled up, theoretical considerations are overridden by practical trial and error as the
converging influences of all relevant theories are too complex to calculate out and thus
unexpected results occur. Thus scaling up distillation is an emergent development process.
The process of postulation based on smaller distillation unit behaviour, observation,
evaluation, and re-postulation is necessary. Postulation becomes a process of imagining the
interaction of the steam, chemical constituents, and biomass, as distillery dimensions are
enlarged. Like the harvester, spatial intelligence is the paramount quality required. A
knowledge of the constituents and various laws relevant to the process are also required so
these can be mentally manipulated extrapolated from observation of the performance of the

9. smaller distillery. One will heuristically determine what laws are important and apply their
calculations through incremental effectuation to scaling up design3.
Project Three: The Production of Vetiver by Hydroponics
Vetiver grass (Chrysopogon zizanoides) is primarily used for soil stabilization, erosion
control, and water treatment. The rhizomes also contain a volatile oil that has woody and
earthy notes valuable for fine and natural perfumery. Traditionally vetiver is cultivated
directly into the soil where the roots grow down some three to four metres in depth and the
roots have to be dug up for distillation. The effort required to produce this oil is well reflected
in the market prices. Production in Malaysia must compete against low cost producing
countries like China, Haiti, Indonesia, and India.
The cultivation of vetiver can also be undertaken hydroponically which would dramatically
lessen labour costs. This could be achieved through plating the grass through a netting
arrangement and then allowing the roots to dangle into a water bath which can be keep
circulating with specifically selected nutrients. It would take approximately twelve months
for the roots to grow to a length of around four feet when they could be trimmed back to six
inches and reinserted into the water bath for another round of growth.
The conceptualization of this alternative vetiver process most probably came into mind
through an insight based on connecting hydroponics with the problem of digging up roots for
distillation. Once again this engineering concept is not the result of using algorithms, but
rather imaginative and effectuated thinking processes. The process would be made effective
through trial and error.
Conclusion
Technical and social disciplines are undergoing convergence which can be seen in the way
many industries are merging together into one. Convergence is creeping into the research and
development process where trans-disciplinary approaches are required to solve problems.
Being an engineer is not good enough in isolation. In order to create, an engineer must have
knowledge across a number of disciplines so that knowledge can be synergized into some
meaningful expressions in the form of new applications and inventions. This would normally
be triggered by some deep insight that relates trans-disciplinary knowledge with some issues
facing society that need to be solved, as is shown in figure 4 in the field of biotechnology.
This creates new knowledge and new knowledge itself is a source of exponential growth of
opportunity.
3
One can only really guess as which laws are taking over dominance in the process based on experience and
knowledge about the characteristics of what is being distilled.

10. “Issues facing society to be solved” New Forms of
Expression
Other disciplines of Insight Expressed
knowledge
Application &
Microbiology
Our current Knowledge Invention
Biology Trans-disciplinary synergy of Deep Insight
knowledge Engineering
Agriculture Physics
Chemistry
Biochemistry
Figure 4. . Trans-disciplinary knowledge and the expression of new knowledge as application
or invention (Hunter 2011, P. 176).
This phenomenon can be seen at a national level if one looks at the number of resident
patents filed per million population in each country. Focusing on the Asia-Pacific region,
Figure 5. shows the number of resident international patents applied for in the region during
2010. International patent filings are more relevant than domestic patent filings as the
international filings figures are a better indicator of the country’s international influence in
the global business arena. Countries like Japan, Republic of Korea, China and Australia are
far in front of the rest of the Asia-Pacific Region. In the Asian Grouping, India had 627
international patent filings during 2010 and Singapore 402. Both countries have invested in
R&D very heavily, with India expected to become an industrial giant in the near future and
Singapore publically emulating the Korean research model in cluster development, in large
investments like the biotechnology Biopolis. Although aggregate filings are low in the rest of
the Asian Region, Malaysia stands out with some relative success with its national policies on
projects like the Multimedia Super Corridor (MSC) in generating new patent filings. The
Asian region still has a long way to go, however issues like innovation, research and
development, and commercialization are on top of the policy agendas at this time.

11. Australia 2139
Brunei 3
China 3910
Indonesia 6
India 627
Japan 26906
Dem. Rep. Korea 4
Republic Korea 5935
Malaysia 54
New Zealand 316
Philippines 15
Singapore 402
Thailand 12
Vietnam 9
0 5000 10000 15000 20000 25000 30000
Source: WIPO Statistics Number of International Patents Filed by Residents
Figure 5. International Patents Filed by Residents in Asia-Pacific Region 2010
Schumpeter (1954) argued that economic growth requires innovation – the generation of
higher quality products at lower unit costs. The future of regions and nations depend on new
ideas and new products that energize those places and facilitate economic growth (Feldman
& Florida 1994).
Knowledge without application is useless in creating tangible benefits to society, but
hopefully this paper has shed light that it is not knowledge in itself that is important rather the
ability to apply it. And the ability to apply it doesn’t rely upon formulae, theory or algorithm,
but rather emergent thinking and the heuristics have developed. This is a neglected part of
engineering education and this is also the quality that makes a good engineer stand out from
the rest of the pack.
Only innovation will make an essential oil industry viable in Malaysia and truly competitive
internationally. This depends upon our ability to conceptualize, imagine and sketch out
concepts in our mind rather than having capital and the most up to date equipment at our
disposal.
References:
Asma, A., Going Glocal: Cultural Dimensions in Malaysian Management, Kuala Lumpur,
Malaysian Institute of Management, 1995, P. 179.
Austin, J. E., (1981), Agroindustrial Project Design Analysis, Baltimore, The John Hopkins
University Press, pp. 121-125.
Beer, S., Brain of the Firm 2nd Ed., Chichester, John Wiley & Sons, 1981, pp. 52-53.

12. Chen, M., Asian Management Systems, 2nd Ed., London, Thomson, 2004, P.220.
Dougherty, N.W. (1972), Student, Teacher, and Engineer: selected speeches and articles of
Nathan W. Dougherty, University of Tennessee Press.
Feldman, M.P. & Florida, R. (1994). The Geographic Sources of Innovation: Technological
Infrastructure and Product Innovation in the United States, Annals of the Association of
American Geographers, Vol. 84, No. 2, pp. 210-229.
Gardner, H. (1993). Creating Minds: An Anatomy of Creativity Seen Through the Lives of
Freud, Einstein, Picasso, Stravinski, Eliot, Graham, and Gandhi, New York, Free Press.
Hunter, M. (1997), Malaysia: A New Source of Tea tree Oil. Invited Paper presented to the
Personal Care Ingredients Asia Exhibition and Conference, April, PWTC, Kuala Lumpur.
Hunter, M. (2006), Heuristics in the development of production processes for household
chemical product manufacturing, Proceedings of the 20th Symposium of Malaysian Chemical
Engineers, Organised by Universiti Techologi Mara, December, 2006
Hunter, M. (2009), Essential Oils: Art, Agriculture, Science, Industry and Entrepreneurship,
A focus on the Asia-Pacific Region, New York, Nova Scientific Publishers.
Hunter, M. (2009). Opportunity, Strategy, & Entrepreneurship: A Meta-Theory, Volume 1,
New York, Nova Scientific Publishers.
Hutchinson, J., G., Management, Theory and Tactics, New York, Rinehart and Winston,
1971, P. 126.
Jonassen, D. H. and Grabowski, B. L. (1993). Cognitive controls, In: Jonassen, D. H. and
Grabowski, B. L. (Eds.), Handbook of Individual Differences, Learning and Instruction,
London, Lawrence Erlbaum Associates.
Lovelock, J. (2005), Gaia: Medicine for an ailing planet, London, John Wiley & Sons.
Polva, G., How to Solve it, Princeton, Princeton University Press, 1945, P. 102.
Schumpeter, J. (1954). Capitalism, Socialism, and Democracy, 3rd Edition, New York,
Harper & Row.
Schweikart, L., & Pierson Doti, L., (2010). American Entrepreneur: Fascinating stories of
the people who defined business in the United States, New York, Amacon.
Timmer, P. C., (1973), Choice of Techniques in Rice Milling on Java, Bulletin of Indonesian
Economic Studies, Vol. 9., No. 2, July, pp. 57-76.
Vaidya, S.and Chansky, N. M. (1980). Cognitive development and cognitive style as factors
in mathematics achievement, Journal of Education Psychology, Vol. 72, pp. 326-330.

13. Witkin, H. A., Lewis, H. B., Hertzman, M., Machover, K., Meissner, P. B. and Wapner, S.
(1954). Personality Through Perception: An experimental and clinical study, New York,
Harper.