PLoS One. 2016; 11(1): e0145265.
Published online 2016 Jan 6. doi: 10.1371/journal.pone.0145265
PMCID: PMC4703213
Howard Nusbaum, Editor
Abstract
Researchers
have analysed whether school and local knowledge complement or
substitute each other, but have paid less attention to whether those two
learning models use different cognitive strategies. In this study, we
use data collected among three contemporary hunter-gatherer societies
with relatively low levels of exposure to schooling yet with high levels
of local ecological knowledge to test the association between i) schooling and ii)
local ecological knowledge and verbal working memory. Participants
include 94 people (24 Baka, 25 Punan, and 45 Tsimane’) from whom we
collected information on 1) schooling and school related skills (i.e.,
literacy and numeracy), 2) local knowledge and skills related to hunting
and medicinal plants, and 3) working memory. To assess working memory,
we applied a multi-trial free recall using words relevant to each
cultural setting. People with and without schooling have similar levels
of accurate and inaccurate recall, although they differ in their
strategies to organize recall: people with schooling have higher results
for serial clustering, suggesting better learning with repetition,
whereas people without schooling have higher results for semantic
clustering, suggesting they organize recall around semantically
meaningful categories. Individual levels of local ecological knowledge
are not related to accurate recall or organization recall, arguably due
to overall high levels of local ecological knowledge. While schooling
seems to favour some organization strategies this might come at the
expense of some other organization strategies.
Introduction
Research
suggests that schooling can affect strategies used to recall
information, by changing the brain organization of cognition in a myriad
of ways, but researchers debate whether such cognitive effects
systematically relate to everyday problem-solving [1].
Thus, although several studies show that schooling and the acquisition
of school-related skills can have lasting positive effects on some
cognitive and non-cognitive skills [2–4],
it is also possible that school-based learning has no effect, or even
negative effects, on more procedural, pragmatic and sensory oriented
types of learning also needed for everyday life. This could be
particularly the case in situations where everyday activities do not
necessarily depend on the type of cognitive skills learned at schools,
as is often the case among small-scale, rural populations. Ardila and
colleagues [4]
point that contemporary illiteracy is not the same as preliteracy, as
literacy might have replaced preliterate cognitive skills. Preliterate
societies often have rich cultural traditions, largely passed by oral
means which might require specific cognitive skills, likely different
than those used in school.
Indeed, for most of human
history, the acquisition of knowledge and skills needed for subsistence
did not occur in school, nor did it depend on the skills and behaviours
learned in the classroom. Rather, the learning of subsistence skills
occurred through participation in everyday activities in which local
knowledge of plants, animals, and the environment was socially
transmitted [5].
Research suggests that, even today, in indigenous societies local
ecological knowledge produces positive returns to the individual [6, 7] in the same way that schooling and the skills and behaviours learned in school do [8, 9]. For example, researchers have found that local ecological knowledge helps indigenous societies deal with pest infestations [10], cope with weather variability and adapt to climatic change [11], select cultivars [12], manage natural resources [13], and enhance health and nutritional status [6].
Cognitive
psychologists and anthropologists have analysed the associations
between school and local ecological knowledge, suggesting that among
indigenous groups, schooling and academic skills learned in school
undermine local ecological knowledge, arguably because time and
resources spent in school detract from time and resources spent learning
other forms of knowledge [14–16].
But, to date, we lack research focussing on whether those two models of
knowledge acquisition have a differentiated impact on cognition.
We
argue that this could be the case as both systems use different
learning strategies and display critical differences in the social
organization of learning [17].
Schools represent a special type of setting centered on student´s
learning, reasoning, comprehension, memorizing, problem solving, and
achieving. Therefore, attending school contributes to the development of
specific attitudes towards knowing, understanding, and thinking.
Indeed, long ago, Bartlett [18]
proposed that literate people might use more active information
integration procedures (or “meta-memory”) than illiterate people, who in
turn might more frequently use rote learning (or memorizing by
repetition). Since then, several studies have shown that
school-attendance, as well as the acquisition of skills typically
learned at school (e.g., literacy and numeracy) affect cognition and
cognitive abilities [19].
Even one or two years of school can affect performance in certain
neuropsychological tests, differences being more significant during the
first three years of education, followed by a negatively accelerated
curve tending to plateau [20].
Additionally, some skills learned in school, such as literacy, are
effective tools for acquiring information from any sources (books,
magazines or journals), which might be contrasted with information
obtained from oral sources or own experience, potentially altering the
way the individual conceptualizes and interprets the world [4].
In contrast, children usually acquire local knowledge from early childhood [21], from many social settings and “teachers” [22], and largely through observation, imitation and emulation during the performance of daily life activities [5, 23, 24].
Furthermore, rather than relying in specialized child-focused
activities to teach children, the acquisition of local knowledge is
largely self-motivated [17, 25].
While
the two ways of learning are not necessarily opposite, the prevalence
of one may have impacts on people’s cognition.People without schooling
might favour different types of learning or different learning
strategies helping them learn and remember in ways that are relevant for
their everyday lives. Moreover, some research suggests that such
alternative strategies are not well captured in standard tests. For
example, in a classic study on the effects of schooling on memory, Cole
and Scribner [26]
found differences in memory performance between Liberian children who
attended school and those who did not when using a standard memory test.
However, when non-schooled children were tested using a story, their
recall accuracy improved, as they were able to recall the objects by
associating them with the roles they played in the story. Similar
results have been found on memory tests in research among Mayan children
of rural Guatemala [27].
Here, we test the differentiated association of i) schooling and ii)
local ecological knowledge on verbal working memory using data
collected among three contemporary hunter-gatherer populations with
relatively low levels of exposure to formal schooling, yet with high
levels of local ecological knowledge. We focus on verbal working memory
(or the ability to remember information in the form of words) for two
main reasons. First, the verbal working memory system allows people to
hold a small set of representations active for a short period of time [28, 29].
This ability is critical for many higher-level cognitive abilities,
including learning and understanding language, manipulating numerical
representations, inferring the causal structure of events, and
understanding social interactions [29].
So, working memory is a critical cognitive skill for the acquisition of
any type of knowledge. Second, many of the participants in our study
were not only illiterate but–according to our field experience- some of
them were also unfamiliar with printed materials in general, and we were
afraid they will have problems identifying objects in a photograph. So
we considered that verbal tasks were better accepted and potentially
less biased than tasks involving printed material.
Researchers
differentiate between school attendance and the acquisition of skills
typically learned in school as the two phenomena do not necessarily
correlate [4, 30].
Similarly, researchers studying local knowledge systems have
differentiated between theoretical (or declarative) knowledge and
practical skills [31, 32].
We test whether standard measures of performance on a verbal working
memory task relate to a) schooling, b) skills typically learned in
school (literacy, numeracy), c) local ecological knowledge related to
hunting and medicinal plants, and d) skills related to hunting and
medicinal plants.
The Setting
We
collected data in three indigenous, small-scale, subsistence-based
societies with little involvement in market economies, school-based
education, or modern healthcare systems: the Baka (Congo Basin), the
Punan (Borneo), and the Tsimane’ (Amazonia). The three societies
resemble one another in that they depend on the consumption of local and
self-harvested natural resources for their subsistence, generally based
on a combination of foraging and farming and in that they have only
recently started to integrate more regularly with the broader society,
with only relatively recent adoption of western-style classroom
schooling. Furthermore, as for many other indigenous populations [33, 34],
the quality and rigour of schooling in the studied societies is
relatively limited. Below we provide some glimpses of each of the three
societies, with special emphasis on access to schooling.
The
Baka are one of the several hunter-gatherer groups living in the
tropical rain forests of the Congo Basin. Their population was estimated
twenty years ago to be about 26000 individuals in Cameroon, spread in
more than 400 villages [35].
As other hunter-gatherers in the region, the Baka traditionally
depended on wild animals and plants for their livelihoods, although they
also maintained economic and social relations with sedentary farming
villagers, with whom they exchanged forest products for agricultural
ones and to whom they occasionally provided agricultural manual labour [36].
Baka subsistence activities changed at the turn of the 1960s, when they
began to settle along new logging roads and to cultivate their own
plots [35].
Nowadays, the Baka combine hunting-gathering with cultivation of
cassava and plantain, their major staple crops, alongside their menial
work on the farms of their Bantu neighbours. While no longer nomadic,
the Baka still spend long periods of time in forest camps, where their
subsistence depends on hunting and gathering.
Schooling is relatively recent for the Baka. Some 25 years-ago, Bahuchet [37]
reported that less than 5% of Baka children were registered at school.
Since then, and concomitant with sedentarization efforts, there have
been several efforts to promote schooling among the Baka, yet numbers
remain low, and schooling generally only covers primary education.
Missionaries and local NGOs have trained teachers and established
private schools reserved for Baka people in which teaching is carried
out at least partly in the Baka language. In communities without access
to Baka-speaking schools, Baka children can attend public schools
typically established in their Bantu-speaking neighbouring villages. In
such cases, however, Baka children face important barriers to schooling,
including registration fees, discrimination on the base of their ethnic
origin, and the use of French as language of instruction.
Our second study society, the Punan, is a group of ~10000 people living in Indonesian Borneo [38].
Their traditional economy was based on hunting bearded pigs and
preparing starch from hill sago, a wild clump-forming palm. They have a
long history of barter with the locally settled farmers [38]. Efforts to sedentarize the Punan started in the mid-1950s [39].
Nowadays, the Punan are no longer a nomadic group, but they still
engage in long travels and seasonal stays in the forest for hunting wild
boars and mostly for gathering forest products which can be
commercialized, such as eaglewood [38, 39].
The Punan are undergoing many social and economic changes, including
increasing engagement in wage-labour, adoption of swidden rice
cultivation, and dependence on government subsidies. Collecting and
trading forest products such as eaglewood, rattan, and live animals are
important income-generating activities.
The first
effort to provide schooling to the Punan dates four decades back. In
1973, the then dictatorial national government initiated a massive
national schooling project aiming at raising national loyalty for which
they concentrated in spreading the use of Bahasa [40].
Elementary schools, where teaching was done in Bahasa (Indonesian
national language), were opened in all sub-districts, although secondary
education was generally still out of reach for rural populations [41].
After the downfall of the dictatorship, the 1998 Decentralization Law
put regional development (especially in remote areas) as a national
priority. Limberg and colleagues [42]
reported the building of the first elementary school in the most remote
Punan villages in 2002. Today, Punan children have relatively easy
access to formal schooling at the elementary level, although the overall
attendance rate is low and teachers’ absenteeism is high. Secondary
education is still largely unavailable; the first remote high school was
opened in 2013, before which secondary education was available only in
regional towns [39].
Despite these limitations, parents will send their children to the
towns. Schooling is increasingly becoming a priority for Punan parents,
even to those living in remote villages, as they perceive that education
can provide children with job opportunities [38].
Our
third study society are the Tsimane’, a small-scale indigenous society
of foragers and farmers in the Bolivian Amazon. The Tsimane’ number ~
12,000 people living in ~100 villages of ~20 households, concentrated
along rivers and logging roads. Up until the late 1930s, the Tsimane’
maintained a traditional and self-sufficient lifestyle, but their
interactions with the Bolivian society have steadily increased since the
1940s [43].
Previously semi-nomadic, they are now mostly settled in permanent
villages with school facilities. The Tsimane’ rely on slash-and-burn
farming supplemented by hunting, fishing, gathering, and wage labour in
logging camps, cattle ranches, and in the homesteads of colonist
farmers. Their main cash crops are rice and maize [44], although the barter of thatch palm also provides an important source of income for many households.
The
Tsimane’ have been exposed to schooling since the 1950s, when the
Bolivian government gave Protestant missionaries the responsibility for
schooling remote lowland native Amazonian populations [45].
The missionaries trained young Tsimane’ men who later became teachers.
These teachers provided schooling in 80% of Tsimane’ villages (the rest
having no schooling) until 2006, providing a partially contextualized
primary education curriculum (i.e. teaching in Tsimane’ language and
using examples from the local environment) [15].
However, since 2006, the new Bolivian Education Law has homogenized the
content of school curricula, imposing Spanish as the vehicular language
[46].
The effort to improve overall education to lowland populations is also
leading to the replacement of the missionaries-trained Tsimane’ teachers
by national university-trained teachers, who typically come from
different cultural contexts (i.e., Bolivian highlands) and do not speak
the Tsimane’ language, and consequently have difficulties to adapt to
the lowland ecological and social context [47].
In
sum, in the three studied societies, access to the school system is
relatively recent and, because school attendance was -in practice-
voluntary, many adults of the current generation have never attended
school. Furthermore, in none of the studied societies are the skills
learned in school necessary for subsistence, which in turn depends on
the acquisition of local environmental knowledge transmitted orally and
through the context and acquired by observation and practice (see [48] for a description of Baka local ecological knowledge, [38] for the Punan, and [49]
for the Tsimane’). Such settings thus offer the possibility to test
whether the two differentiated ways of learning, schooling and local
knowledge, differently relate to cognition.
Methods
We set up data collection within the framework of a larger research project [50]
for which six researchers conducted 18 months of fieldwork each. To
work in the Tsimane’ territory, we obtained written permission of the
Great Tsimane’ Council. To work among the Punan, we obtained permission
from RISTEK (Ministry of State for Research and Technology, Indonesia,
SIP NO: 038/SIP/FRP/SM/II/2012). No specific permissions were required
to work in the area where the Baka live. During the first months of
fieldwork, they learned the local languages, adapted to the local mores,
build up trust with participants, collected background information, and
developed the methodologies to be used later. Data on schooling and
school-related abilities were collected at the beginning of fieldwork
and updated later. Data collection on local knowledge and related skills
took place over the course of 12 consecutive months, during which
researchers visited each informant several times. Memory data were
collected in the last three months of field research, once informants
were well familiar with the researchers. All interviews were done in the
local language, with the support of trained field assistants.
Participants
Participants were recruited among adults in the framework study [50]
and participation was strictly voluntary. As the Tsimane’ have a
political organization that represents them, we obtained written
agreement from this organization (The Great Tsimane’ Council). In the
three settings we obtained written consent from the head of the village
and oral Free Prior and Informed Consent from each individual
participating in the study. We opted for oral consent because part of
the target populations had little schooling and very little exposure to
Western customs that involve mastery of concepts such as agreements,
legal contracts, or ‘informed consent’. Consequently many did not
understand well the implications of signing a form. In contrast, they
are comfortable providing informed consent verbally. Participants
include 94 adults, considered here as people over 16 years of age (44
women and 50 men) living in the three mentioned forager societies (24
Baka, 25 Punan, and 45 Tsimane’). For participants under 18 years of
age, we obtained oral informed consent of one of the parents. The ethics
committee of the Autonomous University of Barcelona (CEEAH-04102010)
approved the protocol for this research, including the collection of
oral consent. Oral consent was documented during the first interview (a
census). Due to high mobility, we could not collect data for all
informants and all the tasks, so there are slight sample size variations
(± 8 subjects) in some tests.
School and school-related skills
We
collected school-related information of each participant. We asked
informants about the maximum school grade they had attained. Since,
overall, levels of school achievement are low, and as in some of the
communities some individuals acquire or improve their school-related
skills outside the school (e.g. basic numeracy can be improved when
negotiating prices with vendors or traders), we also conducted direct
measures on literacy and numeracy. We assessed each informant’s literacy
by requesting them to read a simple sentence. We had sentences in
native languages and in the national languages and used the one in which
the informant performed best to assign a score. We coded answers for
literacy tests as 0 = unable, 1 = with difficulty, 2 = well, but because
low variation in data, we later grouped people who read (either with
difficulty or well) in a single group as opposed to people who could not
read at all. To assess numeracy we asked informants to perform four
elementary calculations (adding, subtraction, multiplication, and
division). We assigned a 1 to each correct answer and stopped the test
if the person made an error. Thus, numeracy could range from zero to
four. We had three equally difficult versions of the literacy and
numeracy tests and chose one at random for each person.
Local ecological knowledge and skills
Due
to the variations in local environments and knowledge between our three
case study sites, we had to develop site-specific knowledge tests for
each. To allow for the comparability of data across sites, we followed
the same protocol, including the way in which questions were generated
and the general structure of the tests (see [51]
for detailed description). We assessed the local knowledge of a person
through four tests. The first test measured the person’s knowledge of
medicinal plants and consisted of an identification task, in which we
read to the informants the name of 10 plants and asked them to tell us
whether they knew the plant, and–if so- whether the plant had a
medicinal use. We created a knowledge score corresponding to the number
of plants with medicinal use reported by the informant. The second test
measured individual hunting knowledge and consisted in the
identification of game animals: we presented informants with stimuli
from known origin (i.e., the call of a bird, a skull of a monkey) and
asked them to identify the species presented. We evaluated informants by
contrasting their responses with information from known origin.
The
following tests measured individual skills or practices that, according
to our ethnographic information, embody local knowledge. Thus, to
measure individual skills in the use of medicinal plants, we asked
informants to report the last time they had prepared the plant remedies
they listed in the medicinal plants identification test. We created a
score on skills using medicinal plants that accounts for the total
number of medicinal uses reported by the informant (from the 10 selected
plants) and the last time they were used. To assess hunting skills, we
asked informants to self-report on hunting frequency, weapons used, and
success with difficult-to-catch prey (i.e., sun bear for Punan, tapir
for Tsimane’, and wild boar for Baka). The hunting skills score was
created by assigning points for each self-reported skill. The protocol
for the tests used for each country can be found in http://icta.uab.cat/Etnoecologia/lek.
Verbal working memory
We drew on classic tests based in word recall [52]
to develop three culturally-specific but cross-culturally comparable
tasks to assess verbal working memory. The task consisted of a
multi-trial free recall of words appropriated to each cultural setting.
Such tasks are considered culturally fair methods for assessing
cognitive functioning in minority populations [53].
To
select culturally and linguistically meaningful words for individuals,
we first elicited lists of familiar items in each cultural context. We
did so by conducting free-listings [54].
Specifically, in each society we asked about 20 respondents to list all
the items they could think of in each of four semantic categories: a)
medicinal plants, b) game, c) wild edibles, and d) locally valued
market-items. We calculated the saliency of items listed, i.e., an index
that takes into consideration the frequency and order in which items
were listed [55, 56].
To construct culturally appropriated but cross-culturally comparable
tasks, for each society we chose the exact word used to designate the
four most salient items from each semantic category (4 categories * 4
items = 16 words).
Data were collected in individual
sessions, consisting of three trials with the same informant. Local
assistants read a list of words to participants in their local language.
The list of 16 common words was randomized and all informants were
presented with the same ordered-list in all the trials. Participants
were then asked to recall and repeat back the words in the list without
any particular mention to order.
In Trial 1, the assistant explained: "I am going to read you a list of common words. I would like you to remember as many as possible." Then he read the list of words at a rate of one word every two seconds. After reading was finished, the assistant asked "Tell me as many of the words on the list as you can remember."
As informants listed words, we noted them down keeping the enumeration
order (i.e., 1 for the first item the person remembered, 2 for the
second, and so on). If the informant said a word that was not on the
list, we marked a cell named "Other word"; this cell was marked as many
times as other words were said. If the informant repeated a word, we
marked the enumeration order as many times as the word was repeated.
When
the informant could not recall any more words, we started Trial 2, in
which the entire list was read again in the same order and speed as
previously. Again, we asked informants to recall the items on the list
and noted the answers. After Trial 2, a 20 minutes interval was held, a
time period during which researchers stayed with the interviewee doing
other tasks before proceeding to Trial 3. For Trial 3, the assistant
said to the informant: "Now we are going to go back to the list I read to you earlier. I need you to try and remember the words on this list and tell me what they were." Again researchers noted all the words recalled by the informant in the recall order.
Performance
on the memory test was measured with a number of outcomes regarding
accurate recall, inaccurate recall, and organization recall [52].
Accurate recall refers to the person’s ability to correctly recall
words in the list, and in our case included the total number of correct
words recalled across the three trials and in trials 2 and 3, as well as
the number of words learned across trials (See Table 1
for specific variables and their definitions). Higher scores in
accurate recall variables reflect better performance. Inaccurate recall
refers to deviations from the original list, including repetitions of
correct words, ‘recall’ of non-listed words, or inconsistency in
recalling words between trials. Higher scores in inaccurate recall
variables reflect worse performance (i.e., more recall errors). Last,
organizational recall refers to variables that have been consistently
found to help organize the cognitive process. Such variables include
primacy and recency (or the ability to recall words listed first and
last), semantic clustering (or the number of consecutively recalled
words from the same semantic category), serial clustering (or the number
of words recalled in the same order as presented), and primary memory
(or the ability to recall the last word and 1-back positions during
Trial 1) [29].
Description of the explanatory variables used, by schooling.
Data analysis
We
start the analysis by providing some descriptive statistics and
assessing potential differences on measures of performance on a verbal
working memory task associated to socio-demographic characteristics of
the informant (i.e., studied society, sex, and age group). Such tests
were conducted to assess the reliability of data. We then conducted a
series of analytical tests to determine whether verbal working memory
relates to a) schooling and skills typically learned in school
(literacy, numeracy) and b) local ecological knowledge and skills
related to medicinal plants and hunting. For variables with two levels
(sex, literacy, and numeracy) we used a Wilcoxon rank-sum test. For
variables with more than two levels (society, and age group), we used a
one-way ANOVA. Finally, a set of correlations were run to determine the
relation between an individual's local knowledge and skills and
performance on the memory task. We first tested whether data were
normally distributed with a Shapiro-Wilk test of normality. We used
Pearson product-moment correlations for variables normally distributed
and Spearman's rank-order correlations for variables non-normally
distributed.
Our descriptive
statistics show that younger individuals had higher levels of school
attendance. To test whether there is an effect of age independent of
schooling, we also ran a set of multivariate regressions. Specifically,
we ran a Poisson multivariate regression for each of the variables
derived from the verbal-memory task as dependent variable. An OLS model
was used for the variable Learn slope. As explanatory variables
we included 1) society’s dummies, 2) a binary variable that captures
whether the person is a man or a woman, 3) a set of dummies for the age
categories, and 4) a binary variable that captures whether the person
had attended school or not. For statistical analysis we used Stata. Data
are available in S1 Dataset.
Results
Description of the data
Despite
external efforts to provide formal education to people in the studied
societies, school levels continue to be low. Thus, only half (n = 47) of
all the participants in our entire sample had attended school at some
point in their life, of which 29 (62% were men) and 18 (38%) were women.
Among the three societies, the lowest education levels were found among
the Baka, and the highest among the Punan. Overall, younger
participants have higher levels of education than older participants (Table 1).
The studied sample has weak literacy and numeracy skills: only 28
informants were able to read a simple text and 44 were able to add (Table 1).
However, schooling is apparently not the only way of acquiring literacy
and numeracy: from the 28 who could read, seven had not attended school
and from the 44 informants who could add, 12 had never attended school.
Despite those inconsistencies, a series of one-way ANOVA tests showed
that schooling was associated in a statistically significant way to
literacy and numeracy.
Informants were able to
recognize 5.78 (SD = 5.00) medicinal plants and 5.13 animals (SD =
5.15). The average score in our medicinal plant’s skill test was 6.41
and the score in hunting skills was 3.77. Informants who had attended
school recognized less medicinal plants and had lower levels of
medicinal plants skills (5.00 and 5.20) than informants who had not
attended school (6.56 and 7.61), both differences being statistically
significant (p <.001) in a t-test. Hunting knowledge and skill scores
do not seem to vary depending on schooling.
On
average, each informant was able to accurately recall 30.4 words across
the 3 Trials (10.7 in Trial 2 and 11.5 in Trial 3), with a learning
slope of 1.6 (Table 2).
Typically, correct words were listed only once (i.e., not much
repetitions), but on average across the three trials each informant
listed 3.4 words that were not in the list. Regarding the way people
organize their recall, we found that, across the 3 trials, the
percentage of words recalled, from the first 4 words (23%) was higher
than the percentage of the last 4 words listed (19%) and that semantic
clustering occurred more often than serial clustering (0.16). 27% of the
people in the sample could not recall any of the two last words listed
in Trial 1, whereas 23% could recall the last two words; the remaining
50% could recall only 1 of the two lasts words.
Variables derived from the verbal memory task (n = 94).
To
assess the accuracy of the data, we examined potential differences in
memory related variables according to socio-demographic characteristics
of the sample (Table 3).
Potential differences across the three societies were examined with a
series of one-way ANOVA tests. We found statistically significant
differences in delayed recall (F(2,91) = 3.19, p = .046) and learning slope (F(2,91) = 5.35, p = .006). A Tukey post-hoc test revealed that delayed recall and learning slope were statistically significantly higher among the Punan compared to the Tsimane’ (1.59 ± 0.70, p .07 for delayed recall and 0.92 ± 0.32, p .01 for learning slope)
and the Baka (1.76 ± .80, p .08 and 1.09 ± 0.37, p .01, respectively).
Among the variables that measure inaccurate recall, we found lower repetitions among the Tsimane’ (F(2,91) = 2,71, p = .07) and higher inconsistency among the Baka (F(2,91) = 2,58, p = .08). Last, the Punan also seem to exhibit larger primacy effects (F(2,91) = 4.48, p = .01), but lower serial clustering
(F(2,91) = 5.96, p = .004) than the Baka and the Tsimane’. Results of a
Wilcoxon rank-sum test between women’s and men’s scores suggests no
statistically significant differences in our proxies for accurate and
inaccurate recall. Primacy effects (Z = -1.895, p = 0.06) and serial clustering
(Z = -2.141, p = 0.03), however, are higher among men. When dividing
the sample according to age categories, results from a one-way ANOVA
test suggest that people over 45 years of age listed more intruder words than people in the other two categories (F(2,91) = 11.84, p <.0001), and had lower levels of serial clustering
(F(2,91) = 2.75, p = .07). None of the other variables analysed showed
statistically significant differences between people of different age
categories.
Differences in variables derived from the verbal-memory task, by informant’s socio-demographic characteristics.
Memory, school and school-related skills
We
next examined whether our memory related variables varied according to
school and school-related skills with a series of Wilcoxon rank-sum
tests (Table 4).
Our analysis provides no evidence of differences in accurate recall in
relation to participant attendance to school or the acquisition of
school-related skills. We found more intruders in the lists of
informants without any schooling (Z = 2.858, p = 0.004), and without
literacy (Z = 1.670, p = 0.09) or numeracy (Z = 1.673, p = 0.09); but we
found no differences across the other two variables that proxy
inaccurate recall. We found important differences in proxies of
organization recall. People who had attended school displayed higher primacy (Z = -2.101, p = 0.04) and recency (Z = -2.453, p = 0.01) effects and higher levels of serial clustering (Z = -2.600, p = 0.009) but lower scores in primary memory
(Z = 1.791, p = 0.07). Results testing the association between numeracy
and the different variables calculated resemble results found when
testing the variable schooling. Among the different variables tested, primary memory seems consistently higher among those without schooling, literacy or numeracy.
Differences in variables derived from the verbal-memory task, by school and school-related skills.
Since,
overall, schooled individuals tended to be younger than unschooled
ones, we ran multivariate regressions to test for the potential
confounding effects of age and schooling. The results (not shown) are
substantially no different than the results of bivariate analysis. For
example, results of multivariate analysis confirm that people without
schooling listed more intruders than people with schooling
(p<0.01), even after controlling for their age category. The same
results also show that people in higher age categories listed more intruders (p<0.01), even after controlling for school attendance.
Memory, local ecological knowledge and skills
In our final test, we examined whether our memory-related variables are associated to local ecological knowledge and skills (Table 5).
Our analysis provides no evidence of correlation between measures of
accurate recall and measures of local ecological knowledge and skills.
There was a statistically significant and positive correlation between
the number of intruder words a person listed and three of our
variables for local knowledge: medicinal plants knowledge (rho = 0.253, n
= 86, p = .02), medicinal plants skills (rho = 0.354, n = 86,
p<.001), and hunting skills (rho = 0.226, n = 87, p = .04). However,
we found no association with repetitions and inconsistency.
Regarding the organization of recall, we found that people with higher
medicinal plants knowledge (r = -0.300, n = 86, p = .005) and medicinal
plants skills (rho = -0.334, n = 86, p = .001) had lower recency, and people with higher medicinal plants knowledge also had lower serial clustering (rho = 0.245, n = 86, p = .02).
Differences in variables derived from the verbal-memory task against local ecological knowledge and skills.
Discussion
The
goal of this work was to assess whether the acquisition of two forms of
knowledge (schooling and local ecological knowledge) relate differently
to cognition, for which we compared measures derived from a set of
verbal memory tasks across people with different levels of schooling and
school-related skills and with different levels of local ecological
knowledge and skills. Despite working with three different forager
societies, we found overall comparable results in our evaluation of
verbal working memory across men and women and people from different age
categories. The only significant difference here was that the Punan of
East Kalimantan, who seemed to display lower levels of primacy and serial clustering
than the Baka and the Tsimane’, although they seem to have similar
levels of accurate recall. Data from this study reveal three main
findings. First, people with and without schooling have similar levels
of accurate and inaccurate recall, although they differ in their
strategies used to organize recall. Second, from the two school-related
skills tested, numeracy relates to memory in the same way as schooling
does, whereas literacy showed weaker associations. Third, contrarily to
schooling and school related activities, the level of local ecological
knowledge or skills of an individual does not seem to be related to
accurate recall, inaccurate recall, or recall organization. We centre
the discussion on these three findings.
Memory and schooling
Irrespectively
of whether they had attended school or not, people in our sample have
similar levels of accurate and inaccurate recall. Interestingly,
however, they seem to achieve those results using different strategies:
people with schooling seem to have higher primacy, recency, and serial clustering, but lower primary memory and semantic clustering
than people without schooling. Better performance on primacy, recency,
and serial clustering suggests a larger reliance on rote learning
amongst those with schooling, whereas better performance on semantic
clustering suggests a larger reliance on semantically meaningful
categories to organize recall amongst those who had never attended
school.
The relation between schooling and cognitive
status is well-known, with several studies showing that schooling has
lasting effects both on cognitive [57] and non-cognitive skills [3], even moderating the trajectory of cognitive change as people age [58].
Our findings, however, challenge such previous results. The most
plausible explanation for such contrasting finding lies in the type of
populations being studied.
Most
previous studies analysing the effects of schooling or education on
cognition have to date taken place in Western societies [19, 20, 30],
where schooling and the skills learned at school are considered
fundamentally important for the future work, economic, and social
possibilities (and hence well-being) of the individual. In such
settings, illiteracy or lack of schooling is often cofounded with many
other social factors (i.e., poverty and discrimination) [59].
In contrast, we set our study among hunter-gatherer societies in which
subsistence and well-being do not depend on schooling but rather on
local ecological knowledge. Such dissimilarities in the type of
population being studied might explain the contrasting findings in two
non-antagonist ways. On the one side, as psychologists suggest, it might
just be that people of different cultural backgrounds process
information differently [53, 60],
implying that basic cognitive abilities like attention, executive
control, or short-term memory can be affected by individuals’ experience
in the world (i.e., by culture) [61].
As the three studied societies resemble each other more than they
resemble Western societies, they might experience similar effects of
schooling on cognition. On the other side, the explanation might also
lie in the use of specific cognitive skills common during preliteracy.
Anthropological studies have shown that preliterate societies, like
those studied here, possess complex classification systems that guide
cognition [62–64].
Furthermore, some recent studies also suggest differences on the type
of learning strategy used in such societies in the absence of schooling [23].
As our memory task included words that could be organized in local emic
classifications, it is possible that -in such circumstances- people
could use retrieval strategies more familiar to them. Such an
explanation is in line with Cole and Scribner’s [26]
finding that when non-schooled children were tested using a list of
objects presented in a meaningful way, they recalled them easily by
drawing the connections through the story.
Memory and school related skills
Our
second main finding relates to the different effects of literacy,
numeracy, and schooling on memory. Researchers have argued that
schooling and the skills learned in school might affect cognition
differently, as the process of learning to read might train specific
abilities, such as explicit phonological awareness, spatial perception,
fine motor skills, and the attainment of grapheme to phoneme
correspondence, which might potentially affect brain functioning [19].
Our findings support the hypothesis that the effects of schooling and
school-related skills might be different, but in an unexpected
direction. We found that numeracy relates to memory in the same way that
schooling does, whereas literacy showed weaker associations.
Previous
research has found that illiterate people generally perform less well
than literate people on conventional neuropsychological memory tests
including wordlist learning and recall (the task used here), but also on
story learning and recall, verbal paired associates, digits backwards,
letter-number sequencing tasks, and complex figure drawing (see [4]
and references within). The performance of illiterates seems to
approach that of literates only in object memory and wordlist
recognition memory [4]. According to Ardila and colleagues [19],
such differences in recall between literate and illiterate people can
be explained because illiterate individuals have inefficient encoding
and retrieval strategies or poor organization of the material to be
memorized, which makes it difficult to support a relatively active and
effortful cognitive process such as free recall. Our data do not support
such findings, as there were no differences between literate and
illiterate participants except for in primary memory.
The
difference can also be due to low levels of literacy (even many
literate informants have difficulty reading a short sentence). However,
an important implication of our finding is that, in the studied
populations, differences in verbal working memory performance should be
attributed to school attendance per se, and not to literacy.
Memory and local ecological knowledge and skills
The
third important finding of this work relates to the lack of association
between our measures of local ecological knowledge and skills and our
measures of accurate recall, inaccurate recall, and recall organization
on the other. Why, in contrast to schooling, is local ecological
knowledge not associated to verbal working memory? Researchers studying
the process through which local ecological knowledge is acquired argue
that the acquisition of such types of knowledge is largely based on
emulation, context and meaning [65, 66],
rather than on verbal communication and memorization. The acquisition
of local ecological knowledge generally involves learning mechanisms
that are more procedural, pragmatic and sensory oriented [67, 68]. For example, Schank and Abelson [69]
argue that stories about one's own experiences, and the experiences of
others, are the fundamental constituents of human memory, knowledge, and
social communication, implying that decontextualized information is
hard to remember. Worldwide, the introduction of western-style schooling
in non-western societies has impacted on the value given to local
ecological knowledge, due to the duality between scientific and
traditional knowledge, with the former highly predominating in formal
schooling. In recent work, Berl and Hewlett [23]
notice that contrarily to Ngandu schooled children, Aka adults and
western children, non-schooled Aka children rely more on emulation than
on over-imitation as a learning strategy. In other words, the
acquisition of local ecological knowledge and skills is often embedded
in everyday activities, and does not necessarily depend on oral
communication [23].
Because the acquisition of local ecological knowledge might be more
independent from verbal communication than school-related learning, it
is not surprising that we do not find a relation between levels of local
ecological knowledge and measures of verbal memory.
Conclusion
Our
finding that people from forager societies with and without schooling
have similar levels of accurate and inaccurate recall supports the idea
that although school attendance might relate to the performance of some
cognitive tests, this might not necessarily manifest in daily
performance (see also [70]),
mostly because people might use different strategies for subsistence
and livelihood. From this finding, we conclude that while schooling
seems to favour some organization strategies this might come at the
expense of some other organization strategies. In other words, the
trade-off of schooling might go beyond the fact that time and resources
spent in school detract from time and resources spent learning other
forms of knowledge [14–16]; such trade-off might also affect cognition.
Supporting Information
S1 Dataset
Raw data used in the analysis (n = 94).
(XLSX)
Click here for additional data file.(16K, xlsx)
Acknowledgments
We
extend our deepest gratitude to the Baka, the Punan, and the Tsimane’
individuals and villages for their friendship, hospitality, and
collaboration. We thank CIFOR, IRD, CBIDSI, and the Department of
Economics, University of Indonesia, for institutional and logistical
support during fieldwork. Reyes-García thanks the Dryland Cereals
Research Group at ICRISAT-Patancheru for providing office facilities.
Funding Statement
The research leading to these results has received funding from the European Research Council (ERC) under the European Union's Seventh Framework Programme (FP7/2007-2013) / ERC grant agreement no. FP7-261971-LEK to Reyes-García.Data Availability
All relevant data are within the paper and its Supporting Information files.
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