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210 South African Journal of Science 96, May 2000
How
much
is
a
clean
beach
worth?
The
impact
of
litter
on
beach
users
in
the
Cape
Peninsula,
South
Africa
A.
Ballancea,
P.G. Ryanb
and
J.K.
Turpieb
Stranded and discarded litter detracts
from the aesthetic quality of beaches,
and the quantities of litter on South
African beaches continue to increase.
We
estimate the deterrent effect this has
on
beach users, and the consequent effect on
the regional economy.
An
interview survey
was used to determine the importance of
beach cleanliness to local and non-local
beach users. Cleanliness was stated as the
most important factor in influencing choice
of beach, especially by foreign tourists.
Almost half the respondents from the Cape
Metropolitan Region are prepared to spend
more than seven times the average trip cost
to
visit clean beaches. Furthermore, up to
97% of the value of these beaches could be
lost by a drop
in
standards of cleanliness.
Litter densities of more than 10 large items
per metre of beach would deter 40% of
foreign tourists, and 60% of domestic tour-
ists interviewed, from returning to Cape
Town. The impact of this on the regional
economy could be a loss of billions of rands
each year. A Travel Cost approach esti-
mated the total annual recreational value of
selected beaches
in
the Cape Peninsula,
South Africa, at between
R3
million and R23
million. The large variation
is
due to a num-
ber of assumptions inherent to the Travel
Cost Method, and extrapolations from the
limited data available. Beach cleaning
within the Cape Metropolitan Region is
clearly necessary, however, expenditure
during the study period (R3 million in
1994-95)
is high
in
relation to the recre-
ational value, and alternative methods of
reducing debris at source are required to
improve beach cleanliness.
Marine
and
beach
pollution is
an
environ-
mental
problem
worldwide,
threatening
wildlife
and
resulting
in
a loss of aesthetic
quality of
the
coastline.1-3 The recent in-
crease
in
density
of large debris items
found
on
South
African beaches is a cause
for concern.4 Plastic makes
up
90%
of all
large debris
stranded
on
South
African
beaches.5
and
is particularly troublesome
because it disperses easily
and
degrades
slowly. The costs of
marine
and
beach
de-
bris are
now
receiving more attention, to
"CSIR Division of Water, Environment and Forestry Tech-
nology, P 0 Box 395, Pretoria, 0001 South Africa. E-mail:
abalance@csir.co.za
bFitzPatrick Institute, Department of Zoology,
UniNrsity
of
Cape Town, Private Bag, Rondebosch, 7701 f>outh Af,,,,a.
provide incentives to reduce pollution.6
Degradation
of
beaches
affects their
aesthetic value to users,
and
loss of this
attraction
may
affect the regional econ-
omy
by
deterring
visitors, particularly
tourists. This was
demonstrated
by
an
oil
spill
in
June 1994,
which
polluted some of
Cape Town's most
popular
beaches.
Tourism is extremely
important
to the
South
African economy.
In
1994, it gener-
ated
revenue
of
R12
billion
(R7
billion
from international tourism), and, directly
and
indirectly,
supported
14 million jobs7•
It
is
also a sector of the economy
that
has
great potential for
growth
and
employ-
ment,
and
hence is a target for public
and
private
investment. Knowledge of
the
impact
of
beach
litter
on
the
regional
economy
is
therefore
important.
This
paper
assesses
the
value of clean beaches
to users
and
the
socioeconomic impacts of
beach
litter
on
the
region.
We
hope
this
will encourage
improved
legislation or
the
development
of alternative strategies
for
preventing
pollution
at
source, thus
reducing
the
environmental
and
aes-
thetic effect of litter.
Methods and study area
The
study
was
conducted
around
the
Cape Peninsula
(33°S,
26°E)
because of
the opportunities for estimating
beach
value
to
tourists
and
residents.
Cape
Town attracts
49%
of international tour-
ists visiting
South
Africa as well as
20%
of
domestic
tourists/
and
many
of the
3.1
million local residents8 use
the
beaches for
recreational
purposes
(walking, swim-
ming, tanning, surfing, etc.).
The beaches of
the
Peninsula differ
in
a
number
of attributes
important
to visi-
tors, such as
water
temperature, exposure
to wind, facilities
and
ease of access. Ten
study
beaches
were
selected across the
range
of these features (Fig.
1)
to assess
attitudes towards cleanliness of a wide
range
of visitors.
All
estimates are 1996
values, to compare
with
the estimates of
income
generated
by
tourism/
and
ex-
penditure
on
beach
cleaning,
11
during
the
period 1994-96.
A questionnaire
survey
using one-to-
one interviews
gauged
attitudes
among
Research
in
Action
one
thousand
visitors
to
the
sample
beaches. The interviews
were
conducted
randomly
with
respect to age, gender,
nationality,
and
activity of
the
respon-
dent,
time of
day
and
day
of the week,
to
minimize biases towards particular user
groups,
and
to
represent
the proportion
of
both
residents
and
tourists
using
the
beaches. Tourists
were
defined as people
from outside of
the
Cape Metropolitan
Region (CMR) or those from
within
the
region
who
were
staying overnight away
from home. Attempts
were
made
to stan-
dardize
the
number
of
interviews
at
beaches
surveyed,
although
differing
weather
conditions (and hence number
of visitors)
at
the
beaches
did
not
always
permit
this. To compensate for small sam-
ple sizes,
the
responses from visitors to
Strandfontein
were
combined
with
those
from Monwabisi,
and
the responses from
visitors to Milnerton
were
combined with
those from Blouberg.
In
both
cases the
beaches
have
similar physical characteris-
tics
and
visitor profiles.
Questionnaires
were
designed to estab-
lish
the
number
of visits, to a particular
site, the cost of the trip,
and
the respon-
dents'
opinions
towards
the
standard
of
cleanliness of
the
beaches. Beach activity
and
anticipated
length
of stay
on
the
beach
were
also sought,
in
search for rela-
tionships
wlth
the
perceived
level of
cleanliness. A profile was constructed of
different
user
groups
according to their
personal
details
and
opinions
(for in-
stance, residential area,
household
in-
come,
length
of stay, activity, perceptions
of cleanliness), across all beaches.
~~(-
..
->1
'
Allantic
Ocean\
Blouber:\
Milne
rio~'\
Sea
Polnt_
1
c~
:-..I
Cam~ig~~J=----~
~-
Uandudn~...>J:
'-?
y-i.1li:.'nd~F.bll!!;
1
~-'
!(
Muizenberg
-;
/
,
~'.fish
Hoek
·
-\
\
....
~
False
Bay
:)/'-·
\~--L
i
(
...
--.(-·
1.
W
_,J;.
~
... E
T
s
a
..
.0
a ...
)6
km
~
Fig.
1.
Selected study beaches.
Research
in
Action
South African Journal of Science 96, May 2000
211
Table 1. Mean scores for relative importance of various beach attributes as perceived by beach users around the Cape Peninsula. Lower scores
indicate greater importance of attribute.
Attribute* Mean score from residents Mean score from domestic tourists Mean score from foreign tourists
Cleanliness
Facilities
Number and type of people
Proximity to home/hotel
Water temperature/surf quality
Wind direction and force
2.5
3.9
4.0
4.2
3.6
2.8
2.3
4.4
4.4
3.7
3.9
2.9
2.2
4.1
4.2
4.5
4.1
3.5
•sixty-two respondents named an additional attraction, of which safety and scenic beauty were cited most frequently (30 and 23 times, respectively).
The Travel Cost
Method
was
used
to
estimate the recreational value of sample
beaches. This
method
is
widely
used
in
the evaluation of
natural
resources
with
recreational appeal,
and
records the actual
travel cost associated
with
visiting a re-
source as a proxy for its
value
to the visi-
tor.
It
was selected for this
study
over
other
techniques as it uses actual values,
which
can
be
summed
across a
wide
range of users to
compute
a
nominal
total
recreational
demand
value, it is restricted
to direct, non-consumptive
use
valuation,
and
it is easy to administer. (For a detailed
appraisal of alternative
techniques
see
ref.
9.)
The
return
trip cost
was
estimated
for each
respondent
using
either
public
transport fares
or
the
Automobile Associa-
tion's cost of35.5 cents
per
kilometre
(1995
rates). The
annual
recreational value of all
beaches to each
respondent
was
calcu-
lated using the
number
of visits
per
year
and
the cost
per
visit. The total
annual
recreational value of each
beach
was de-
termined
using
the
mean
trip cost
per
visitor,
and
the
number
of visitors
per
year
(obtained from extrapolations from
aerial
photographs,
courtesy
of
Cape
Metropolitan Council). A full description
of
the
application
of
the
travel
cost
method
is given
in
ref.
10.
The Travel Cost
Method
estimates the
total value of beaches to users,
but
says
nothing
about
the
value of
individual
beach
attributes, such as cleanliness.
To
establish
the
relative
importance
of
selected attributes, visitors
were
asked to
rank
them
from 1 to
5,
with
1
being
the
most
important. The absolute importance
of beach cleanliness was
determined
by
questioning residents
how
far
they
would
be
prepared
to travel for different levels of
cleanliness,
and
by
asking tourists
how
covered
in
debris
the
beaches
would
have
to
be
for
them
to stop visiting. Three levels
of
beach
cleanliness
were
used,
based
on
the results of a survey of 84 beaches across
the country.4 The levels
were
more
than
10
large items of litter
per
square
metre
of
beach,
between
two
and
10 items
per
metre,
and
less
than
two items
per
square
metre. Photographs of each of these levels
were
shown
to elicit the reaction sought.
The
proportion
of tourists
who
stated
they
would
not
visit Cape Town accord-
ing
to the extent of
beach
litter was
used
to
estimate the tourism
revenue
potentially
lost
by
not
maintaining levels of cleanli-
ness of beaches
in
the Cape Peninsula.
Expenditure
on
cleaning
beaches
was
obtained from local authorities.U·
12
What the survey revealed
Most
respondents
were
residents of
the
Cape Metropolitan Region
(65%
).
Twenty-
one
per
cent of the
people
surveyed
were
domestic tourists,
and
14%
were
foreign
tourists. Perceived standards of cleanli-
ness of Cape beaches
were
high, particu-
larly
among
tourists. Tourists also
spent
significantly longer
on
beaches they con-
sidered to be 'clean' or 'acceptable'
than
on
those
they
saw
as
'too
dirty'
(ANOVA
F
2350
= 5.876, P <
0.005;
'clean' >
'too
dirty'
and
'acceptable'; Newman-Keuls
test).
Cleanliness was
most
frequently
ranked
as the most
important
of the beach attrib-
utes
investigated,
and
foreign tourists
ranked
cleanliness as relatively more im-
portant
than
either domestic tourists or
residents (Table
1).
Furthermore,
44%
of
residents
claimed
they
would
travel
50
km
or more to visit a clean beach. The
average trip distance for residents was
14
km
(cost approximately R4.90)
and
for
tourists
12
km
(nominal cost R4.20), prob-
ably because
many
of the
popular
tourist
hotels are located close to
the
beaches.
Residents
made
approximately
70
trips to
the
beach
each
year
on
average (annual
travel cost R348), whereas tourists
made
10 trips (annual cost
R42).
A trip of
50
km
to visit a clean beach
has
a
minimum
trip
cost of R35.50, more
than
seven
times
greater
than
the cost of a trip for residents
interviewed. However, beach users de-
rive value from a variety of
beach
attrib-
utes,
and
often these features mutually
influence the decision of
which
beach
to
visit.
The extrapolations from the
summer
1
and
winter
beach
attendance
data
gave a
total of 1
871
000
visitors
per
year. Because
these are extrapolations,
and
given the
large variation
in
the
data
available for
determining
beach
attendance,
figures
have
been
rounded
to
the
nearest thou-
sand
visitors. Extrapolation of
the
mean
trip cost across
the
total
number
of
beach
visitors yielded
an
estimated combined
annual
recreational value for the sample
beaches of
R8
million,
although
there was
considerable variation
between
values for
individual beaches (Table
2).
Assuming
similar
mean
trip costs,
and
similar com-
bined
number
of visitors
per
year for all
other
beaches in
the
Cape Peninsula,
the
annual
recreational
use
value
of
all
beaches
in
the region was estimated
at
R18
million.
The figures
should
be
treated as
under-
estimates of
the
actual value. Several esti-
mations
were
made,
as
not
all required
data
were
available
or
accurate,
and
there
are several assumptions
inherent
to the
Travel Cost Method.
13
A sensitivity analysis,
which
estimated
the
cumulative impact
of these variations,
showed
that
the
total
annual
recreational
value
for
sample
beaches was R3-23 million.10 Using
the
same estimation criteria,
the
value for all
the
beaches
in
the
Cape
Peninsula is likely
to lie
between
R9-50 million
per
year.
The
survey
indicated
that
85%
of
both
tourists
and
residents
would
not
visit
beaches if
they
had
more
than
two items
of debris
per
metre. This
would
reduce
the average
annual
recreational value of
the sample beaches from
R1
million to
R150
000.
The total
annual
expenditure
on
travel to sample beaches
would
be
re-
duced
from
R8
million to
R1
million. The
annual
expenditure
on
travel
for all
beaches
in
the
Cape Peninsula
would
be
reduced
from
R18
million to
R15
million.
The
survey
also
showed
that
if
the
beaches
had
more
than
ten large items of
debris
per
metre,
97%
of all visitors
would
not
visit them,
which
would
reduce
the
total recreational value to R300
000
per
year. Such
reduced
annual
expenditure
on
travel represents a
reduction
in
the
regional economy of
R8
million.
Given
the
importance
of
tourism
to
the national
and
regional economy,
the
212 South African Journal of Science
96,
May 2000
Table
2.
Estimated total annual recreational use value of sample beaches on the Cape Peninsula.
Beach Number of residents Mean trip cost for Number of tourists
visiting per year residents (rands) visiting per year
Blouberg and Milnerton 93 000 4.2 54 000
Sea Point 113 000 3.6
51
000
Clifton 73 000 6.7 80 000
Camps Bay 129 000 5.5 86 000
Llandudno 24 000 6.3 32 000
Fish Hoek 115 000
3.1
28 000
Muizenberg 175 000 5.5 109 000
Monwabisi and Strandfontein 667 000 4.5 42 000
Total 1389 000 4.9 482 000
*The total annual value of RB.6 million is not the same as the sum of the values
in
that column due to rounding errors.
potential loss
in
number
of tourists
due
to
a
drop
in
standards
of beach cleanliness
that
this
study
reports
(up
to
40% of
foreign
and
60%
of domestic tourists) is
significant (up to
52%
of the
revenue
from
tourism).
Coastal areas are
important
in
terms of
economic, scientific, recreational, ecologi-
cal
and
educational services.
14
.t5 Reliable
estimates of
beach
value are therefore
important
for
planning
facilities, deter-
mining
access
and
transport
capacity,
estimating potential for
new
business de-
velopment,
and
for coastline protection
and
pollution
controP
6
The
estimated
value of beaches
and
beach
cleanliness
should
be
reflected
in
an
appropriate
budget
for cleansing. Furthermore, esti-
mation of
the
impact of environmental
quality
on
tourism potential is far from
trivial. The relative
and
absolute impor-
tance of cleanliness to
beach
users
shown
in
this
study
provides a
strong
incentive
for pollution control.
Expenditure
on
beach cleansing
in
the
Cape
Metropolitan
area
was
approxi-
mately R3.5 million
in
1994-95;
and
beach
cleaning efforts
have
increased
during
the last five years.12 Given that Cape Town
attracts a significant
proportion
of the
tourist market, it is reasonable to assume
that
the increased expenditure (relative to
the rest of
the
country) is,
at
least partially,
a result of greater importance placed
on
the
aesthetic
quality
of
beaches.
This
study
estimates that
the
regional econ-
omy
could suffer a potential loss of over
. half the tourism
revenue
from a
reduction
in
beach
cleanliness. Keeping
beaches
clean is therefore necessary.
As
only
44%
of
people
surveyed
perceived the beach
they
were
on
as 'clean',
current
methods
of clearing debris
appear
to be insufficient
to tackle the problem.
A
survey
of pollution
on
South
African
beaches
in
1994
showed
four of the
ten
dirtiest
beaches
are
within
the
Cape
Metropolitan Region.4 However, thP Cape
Town
Municipality
Cleansing
Dep<vt-
ment
reported
a
37%
decrease
in
the
volume of litter
generated
on
beaches
under
its control
between
1994-95
and
1995-96.
17
This
may
be
attributable to
more efficient cleaning operations, or re-
duced
amounts
of
litter
entering
the
marine environment.
As
clean-up opera-
tions are expensive
in
relation to
the
value
of
the
beaches,
it
is necessary to consider
alternative
methods
of
reducing
beach
debris. Legislation,
improved
efficiency
of cleansing services, recycling,
reduction
at
source,
and
education
are possible
options.
Most beach debris is generated
by
beach
users or is
washed
or
blown
onto beaches
from the land.5'
18
Plastics, especially pack-
aging materials, constitute over
90%
of
all
beach
debris.5 These items are
very
durable,
which
increases
the
risk
of
entanglement
or
ingestion
by
marine
wildlife. Lack of
waste
collection
and
disposal services
in
many
urban
coastal
settlements contributes to
the
accumula-
tion of waste
on
beaches, as it
is
blown
or
washed
away
from unprotected, informal
waste dumps. Furthermore, the increas-
ing
population
and
influx of people to
coastal
urban
centres intensifies
the
pres-
sure of waste generation
on
the
beach
resources.14
Much
attention
has
been
focused re-
cently
on
methods
of
reducing
plastic
packaging.
One
suggestion is to
produce
less durable plastics,
which
break
down
faster
by
means
of biological, chemical,
photochemical or physical actions.
19
An-
other
option
is to
promote
recycling,
which
requires the creation of markets for
recycled material. Further efforts to re-
duce
plastic packaging have centred
on
charging for packaging.
20
Perhaps the biggest
hurdle
to overcome
is
the
mindset
of
today's
'throw-away'
society. Education of the public to
the
problem
of
litter
in
the
environment
would
go a long
way
to increase levels of
responsibility,
and
thus
to
reduce
the
volume of litter
in
the environment.
Research
in
Action
Mean trip cost for iourists Total annual value
(rands)
(R
million)
4.8 0.6
1.2 0.4
5.3 0.9
4.2 1.0
4.3 0.2
4.0 0.4
6.8 1.7
2.6
3.1
4.2 8.6*
We
thank
P.
Mpande,
B.
Magazi,
and
K-E.
Kiistlin for
help
with
questionnaires;
A.
Pliis for
technical
assistance;
L.
Kruger
and
the
Cape
Metropolitan
Council for
beach
attendance
data;
Cape
Town City
Council Cleansing
Department
for
beach
litter data,
and
M.
de
Wit
and
C.
Shackleton for valuable discus-
sion
and
comments
on
earlier drafts
of
the
manu-
script.
Financial
support
was
received
from
the
Foundation
for Research Development,
through
the
South
African
Network
for Coastal
and
Oceanic
Research
and
the
Desmond
Tutu
Fund.
1. Caulton
E.
and
Mocogini M. (1987). Preliminary
studies of
man-made
litter
in
the
Firth of Forth,
Scotland.
Mar.
Poll.
Bull.
18, 446-450.
2. Corbin
C.J.
and
Singh
J.G. (1993). Marine debris
contamination of beaches
in
St. Lucia
and
Domi-
nica.
Mar.
Poll.
Bull.
26, 325--328.
3.
Laist
D.W.
(1987).
Overview
of
the
biological
effects
of
lost
and
discarded
plastic debris
in
the
marine
environment.
Mar.
Poll.
Bull.
18, 319-326.
4. Ryan
P.G.
and
Moloney
C.
(1995). Survey
of
de-
bris
stranded
on
South
African beaches. Winter
1994.
Unpublished
report, FitzPatrick Institute,
University of
Cape
Town.
5.
Ryan
P.G.
and
Moloney
C.
(1990). Plastic
and
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92,163-165. 0
Widening
access
to
tertiary
science
study:
the 'augmented'
model
J.
Parkinson*
T
he
four-year B.Sc. degree course
at
the
University
of
Natal,
Durban,
is
unusual
in
providing
access to tertiary science
through
'augmentation'
rather
than
the more
usual
foundation
course.
The
augmentation
involves
students
registering for a
reduced
load
of
ordinary
first-year courses,
which
are
supplemented
by
extra tutorials
and
practi-
cals.
This
article describes the
augmented
approach
to science study.
It
examines the de-
velopment
of
the
B.Sc.-4
curriculum
during
the
10
years
it
has
been
operating
and
de-
scribes
some
of
its
successes
and
failures
during
this
period.
The
present
under~representation
of
black
students
in
tertiary
education,
particularly science
and
applied
science,
is well
documented
1 as are the roots of this
under-representation
in
apartheid
policy.
Only
19%
of mathematics teachPrs
and
16%
of science teachers
in
the
country
have
completed
one
or
more
years of
the
subject
at
university level.2 This
has
led
to
the
current
situation
where
few
black
students
match
the
criteria
for
direct
entry
into
tertiary science studies.
During
the 1990s, less
than
10%
of admissions
into
the
Science Faculty
at
the University
of
Natal
in
Durban
(UND)
have
been
black
students
who
meet
the
entrance
requirements. The four-year
B.Sc.
curric-
ulum
described
below
has
allowed
the
faculty
to
more
than
double its intake of
black
students
during
this
period,
by
enabling
admission of
students
who
do
not
meet
the
usual
entrance
require-
ments.
To
increase
enrolment
and
graduation
rates of black students, historically
white
universities have,
in
the
last 15 years,
introduced
four-year science curricula of
*Faculty of Science, University of Natal, Durban,
4041
South Africa.
E-mail: parkinson@scifs1.und.ac.za
a variety
of
types. Some
add
an
initial
foundation
3 year, after
which
students
embark
on
first year.4'5
Others
have
an
initial two-year
programme
combining
foundation
and
first-level courses.6•7 Since
1991,
UND
has
had
a four-year
B.Sc.
cur-
riculum
in
which
students
are
admitted
directly
into
first-year courses.
These
differ from
the
usual
first-year courses
in
having
an
almost double
load
of tutorials,
lectures
and
practicals. This
model
of
academic
development
has
been
rejected
by
many
institutions8 because
the
pool
of black
students
who
can
cope
with
a
curriculum
where
students
start
first-
level courses
immediately
is relatively
small.
Foundation
programmes
are able
to
draw
on
a larger, less-prepared
group
of
students
because
more
time
can
be
spent
on
pre-first
year
material.
Structure
of
the
B.Sc.-4
Students
who
enter
the
four-year
B.Sc.
curriculum
at
UND
take two double-load
'augmented'
level 1 courses
in
their first
year. For example,
in
physics
they
have
nine
contact periods
per
week
for lectures
and
tutorials
and
two
practical sessions,
instead of
the
five periods for lectures
and
tutorials
and
single practical session of
the
regular
first-year
physics
course.
Typically, courses taken are mathematics
and
either
computer
science, physics
or
chemistry, or, for a biology
student,
chem-
istry
and
biology.
Students
also take
an
accredited science
writing
course.
Six of
the
level 1 courses
in
the
faculty
are offered as double-load
'augmented'
courses: cell biology, chemistry,
computer
science,
environmental
biology,
mathe-
matics,
and
physics. some of these double-
load
courses (cell biology,
environmental
biology,
computer
science
and
mathemat-
ics) are
'augmented'
in
that
the
students
213
attend
the
usual
lectures
and
practical
plus
an
additional load of tutorials
and
practicals
in
groups
of
about
30
students.
In
these additional tutorials, tutors
can
address
problems
with
the
lecture mate-
rial as well as
dealing
with
some pre-first
year
material.
Other
level
1
courses
(physics
and
chemistry),
although
covering
the
same
content
as
the
usual
first-year courses, are
entirely separate from it. This enables
the
lecturer to go
more
slowly
and
integrate
pre-first
year
material
into
the
course.
Some of
the
contact time is lecture
mode
but, given
the
small
group
size
(30
stu-
dents
or
fewer),
there
is
opportunity
for
questions
and
other
interactions
with
stu-
dents.
Other
contact time is
devoted
to
small
group
work,
and
problem
solving,
depending
on
the
demands
of the material.
Individual
departments
design courses
and
decide
whether
their
double-load
courses
are
separate
from
the
usual
lecture course
or
'augmented'
with
addi-
tional tutorials
and
practicals, Different
subjects
lend
themselves
to
different
models. Initial
poor
student
performance,
both
in
first-level
and
later level chemis-
try
courses,
led
to
a
change
from
the
lec-
tures
plus
extra tutorials
model
to
the
separate course model.
It
is
not
clear
why
the
lectures
plus
tutorials
model
works (in
terms of
student
performance)
in
some
disciplines
but
not
others. A factor to
be
considered
is
the
extent
to
which
the
first-year course
in
each
discipline as-
sumes
and
builds
on
prior
knowledge.
In
disciplines
where
a
good
deal of
prior
knowledge
is
assumed
such
as
in
chemis-
try, mathematics
and
physics, (but far less
in
biology
and
computer
science),
it
makes educationally
better
sense to
build
teaching of
the
prior
knowledge
into a
separately
taught
level1
course.
In
math-
ematics, however,
student
results
have
been
good
using
the
lectures
plus
tutori-
als model,
and
the
course
has
proved
more
successful
in
dealing
with
the
prior
knowledge
in
tutorials before the lectures
than
was
the case
in
chemistry.
An
element
of
difference
between
mathematics
on
the
one
hand
and
physics
and
chemistry
on
the
other, is
the
diffi-
culty
that
B.Sc.-4
students
had
with
the
lecture
mode
in
chemistry
and
physics,
especially
in
the
first semester.
In
most
disciplines it seems to
be
the
case that sitting
through
lectures
in
which
material
is
presented
rapidly
and
in
a possibly unfa-
miliar
accent
is
not
an
ideal
learning
environment
for
students
entering
the
four-year degree. This
appears
to
be
par-
ticularly
true
in
chemistry
and
physics,
where
students
report
great
difficulty
in
