Pluralistic extension systems involving various stakeholders have been implemented
in many countries to improve the efficiency of, and access to, extension and advisory
services. From the perspective of some sections of society, universities offering
agricultural programmes have the potential to render extension and advisory services
in collaboration with the government because they are involved in knowledge
generation through research and teaching. However, it is unknown whether farmers
are in favour of a pluralistic extension system involving universities. The aim of the
study was to explore farmers’ willingness to accept university-based agricultural
extension in a pluralistic extension system in the province of Gauteng in order to
establish whether the extension services are demand-driven. The objectives of the
study were to profile the socio-demographic characteristics of farmers who receive
public agricultural extension and advisory services in Gauteng; to determine farmers’
perception of public agricultural extension and advisory services, with specific
reference to the perceived quality of extension services and influencing factors, as well
as the frequency of access to public extension services and its determinants; to
ascertain farmers’ access to sources of extension services; to determine farmers’
perception of the effectiveness of public agricultural extension and advisory services,
with specific reference to perceived effectiveness and influencing factors, as well as
exploratory factors associated with the perceived effectiveness; to ascertain farmers’
acceptance of university agricultural extension in a pluralistic extension system, with
specific reference to willingness to accept, the perceived benefits of university
agricultural extension and factors influencing the acceptability of university agricultural
extension; to determine which university agricultural extension delivery system(s)
farmers preferred, as well as factors influencing their choice; to identify the reasons
why farmers prefer different university extension delivery systems; to ascertain
farmers’ perception of a suitable funding model for university agricultural extension
services; and to determine farmers’ willingness to pay for university agricultural
extension services, as well as factors influencing their choice.
A sample of 442 farmers from Gauteng who were receiving agricultural extension and
advisory services from the government were randomly selected to participate in the study. Using a semi-structured survey instrument, primary data were collected through
face-to-face interviews. Quantitative data were subjected to descriptive statistical
analysis, principal axis factoring (PAF), Kendall’s tau correlation, binary logistic
regression (BLR), multiple linear regression (MLR), multinomial logistic regression
(MNLR), ordered logistic regression (OLR), Cochran’s Q test, McNemar’s test and the
binomial test found in the IBM Statistical Package for Social Sciences (SPSS) version
27. Qualitative data were analysed using codes, themes and indicators and converted
to frequencies and percentages. The results obtained in respect of the socio-economic
and demographic characteristics of the respondents showed that the majority of the
respondents were black African females who were above 35 years of age, had an
average of six years' farming experience, spoke Southern Sotho and had spousal
support through marriage and cohabitation. Most of the farmers farmed in small-scale
settings for non-commercial purposes – the average farm/plot size being 4.55 ha –
and occupied communal and rented farmlands. On average, the respondents earned
a net income of about R21 387.56 from farming per annum and had various sources
of income. Large-scale and highly educated farmers a substantial” income from
farming, whereas farmers who were frequently visited by extension officers did not. It
was found that nearly half of the respondents had access to extension services from
various sources apart from the government, such as commodity organisations, mines,
local municipalities, non-governmental organisations and universities. On average, the
respondents were located about 42.4 km away from public extension offices, and the
majority of the farmlands were ≤50 km from the offices. As a result, the respondents
were visited on average twice a month by public extension officers, and farmers who
relied on farm income to sustain their livelihoods and who were satisfied with the
quality of public extension and advisory services received more monthly visits.
However, farmers who made a larger profit received fewer visits per month. About
51.1% of the respondents were satisfied with the quality of public extension and
advisory services, and they included farmers who were frequently visited by extension
officers, commercial farmers and farmers who regarded public extension services as
effective in complying with the principle of Batho Pele in dealing with people and planning activities. The results obtained in respect of the perceived effectiveness of public extension and
advisory services showed that the majority of the respondents were of the view that
the services were ineffective. Highly educated farmers, older farmers, farmers who
were frequently visited by extension officers and farmers who were satisfied with the
quality of services perceived public extension and advisory services to be effective. In
addition, the exploratory factor analysis indicated that public extension and advisory
services that provided relevant and good-quality services, information that improved
agricultural production and access to technologies were perceived as effective by
farmers. The study found that pluralistic extension involving the government and
universities was demand-driven because a significant majority (91.2%) of the farmers
accepted the inclusion of university extension in a pluralistic extension system, even
though most of them did not know universities that offered agricultural programmes in
the study area. The majority of the respondents were in favour of university extension
because of the various benefits it presents, such as better access to extension and
advisory services; access to formal education and training; and the opportunity to get
advice from subject matter specialists and others. The results of the BLR showed that
farmers who made a larger profit from their agricultural enterprises and perceived their
association with universities as an opportunity to access research funding accepted
the inclusion of universities in a pluralistic extension system. Moreover, three important
factors associated with the acceptability of university extension that were extracted
from the exploratory factor analysis were access to research resources, improved
extension services and training, and the diffusion of university research.
The study
findings showed that most farmers (56.8%) in the study area preferred an extension
delivery system that involved public extension as a means of coordination between
farmers and universities (farmer–public extension–university extension delivery
system). The mentioned system was preferred most importantly because it would
enable farmers to acquire more information from various sources and to maintain a
relationship with the government. The results of the MNLR indicated that farmers who
made a greater profit form their agricultural enterprises preferred a farmer–public
extension–university extension delivery system over a farmer–university extension
delivery system. About half of the respondents preferred to receive extension services
from universities at their farming places, whereas the other proportion of farmers was
divided into those who preferred to visit universities only and those who chose both
locations (universities and farming places). Again, most of the farmers (41.9%)
preferred to receive extension and advisory services from universities in their
vernacular languages. From a funding perspective, it was found that the majority
(55.4%) of farmers, especially those who relied on farming as their main source of
income, were willing to pay for university extension services. However, commercial
farmers and those who were located far from public extension offices were not willing
or less likely to pay for university extension services, as shown by the results of the
BLR. However, the majority (91%) of the respondents agreed that the government
should provide funding for transport, university staff allowances, medical aid (where
necessary), Unemployment Insurance Fund (UIF) and pension fund contributions (if
applicable), office space (if required), office equipment and furniture, information and
communication technology (ICT), stationery, training programmes for farmers and
research for university extension services. Therefore, farmers expect the government
to provide most of the funding for university extension services.
To improve the effectiveness of public extension and advisory services, it is
recommended that public extension agents render relevant, good-quality services and
provide information that improves agricultural production and facilitates access to the
technologies required by farmers. Further, it is recommended that a formal framework
for a pluralistic extension system be developed through a participatory process
involving the Ministry of Higher Education and Training, the Ministry of Agriculture,
farmers, universities and other stakeholders. The framework for a pluralistic extension
system should enable universities to provide research resources to farmers; to
improve access to extension services and training of farmers; and to create a platform
for the diffusion of university research outcomes to farmers. An extension delivery
system involving public extension as the means of coordination should be the main
system of university extension. University extension services should be provided
mostly in the farming areas (farmlands) using South African vernacular languages.
The government should provide most of the funding for transport, gross income,
medical aid, UIF and pension fund contributions, office space, office equipment and
furniture, ICT, stationery, training programmes for farmers and research for university
extension services. Moreover, farmers, universities and farmers’ organisations should
pay a negotiated fee for university extension services.
In talle lande bevorder pluralistiese voorligtingstelsels waarby verskeie
belanghebbendes betrokke is, die doeltreffendheid van en toegang tot voorligting en
adviesdienste. Universiteite wat landboukursusse aanbied, kan volgens sommige
sektore in die samelewing saam met die regering voorligting en adviesdienste lewer
omdat hulle deur navorsing en onderrig kennis genereer. Dit is egter onbekend of
boere te vinde sal wees vir ʼn pluralistiese voorligtingstelsel waarby universiteite
betrokke is. Die doel van hierdie studie was om vas te stel of boere in die
Gautengprovinsie universiteite se landbouvoorligting as deel van ʼn pluralistiese
voorligtingstelsel sal aanvaar, en of daar ʼn vraag na sodanige voorligtingsdienste is.
Die oogmerke van hierdie studie was ten eerste om ʼn sosiaal-demografiese profiel
saam te stel van boere in Gauteng wat openbare landbouvoorligting en adviesdienste
ontvang. Ten tweede om boere se siening van openbare landbouvoorligting en
adviesdienste te bepaal, in die besonder hulle siening van die gehalte van
voorligtingsdienste asook die faktore wat dit beïnvloed, en hoe gereeld boere toegang
tot openbare voorligtingsdienste het en faktore wat dit bepaal. Ten derde om boere se
toegang tot die hulpbronne van voorligtingsdienste vas te stel. Vierdens om boere se
siening van die doeltreffendheid van openbare landbouvoorligting en adviesdienste en
die redes daarvoor te bepaal. Vyfdens om vas te stel of boere universiteite se
landbouvoorligting as deel van ʼn pluralistiese voorligtingstelsel sal aanneem, met
verwysing na hulle aanvaarding van die voordele van universiteite se
landbouvoorligting en die faktore wat dit bepaal. In die sesde plek om vas te stel watter
universiteitsvoorligtingstelsel(s) boere verkies, en watter faktore hulle voorkeur
bepaal. In die sewende plek om die vas te stel waarom boere verskillende
universiteitsvoorligtingstelsels verkies. Die agtste doelwit was om boere se siening
van ʼn geskikte befondsingsmodel vir universiteitsvoorligtingsdienste te bepaal. Die
laaste oogmerk is om vas te stel of boere bereid is om vir
universiteitsvoorligtingsdienste te betaal asook die faktore wat hulle bereidwilligheid
beïnvloed.
ʼn Steekproef is lukraak geneem van 442 boere in Gauteng wat voorligting en
adviesdienste van die regering ontvang. Die primêre data is met behulp van ʼn
halfgestruktureerde meningspeiling tydens onderhoude onder vier oë ingesamel. Die
kwantitatiewe data is onderwerp aan ʼn beskrywende statistiese ontleding;
hoofasfaktorering (HAF); Kendall se taukorrelasie; binêre logistiese regressie (BLR);
meervoudige lineêre regressie (MLR); polinome logistiese regressie (PNLR);
geordende logistiese regressie (OLR); Cochran se Q-toets; McNemar se toets; en die
binome toets in die IBM Statistical Package for Social Sciences (SPSS) weergawe 27.
Die kwantitatiewe data is aan die hand van kodes, temas en aanwysers ontleed en na
frekwensies en persentasies herlei. Volgens die resultate wat behaal is ten opsigte
van hulle sosiaal-ekonomiese en demografiese kenmerke, was die meeste
respondente swart vroue van ouer as 35. Hulle het gemiddeld ses jaar ondervinding
van boerdery gehad, was Suid-Sothosprekers en was getroud of het saam met ʼn man
gebly. Die meeste van hulle het om niekommersiële redes op ʼn klein skaal – die
gemiddelde grootte van hulle plasies of kleinhoewes is 4,55 ha – op gemeenskaplike
of gehuurde grond geboer. Hulle het ʼn gemiddelde netto inkomste van nagenoeg
R21 387,56 per jaar uit boerdery verdien, en op verskillende inkomstebronne staat
gemaak. In teenstelling met grootskaalse en hoogs opgeleide boere, het hierdie boere,
wat gereeld besoek van voorligtingsbeamptes ontvang, nie ʼn groot inkomste uit
boerdery verdien nie. Sowat die helfte van die respondente kry toegang tot
voorligtingsdienste uit verskillende bronne benewens die regering, soos
landbouprodukorganisasies, myne, plaaslike munisipaliteite,
nieregeringsorganisasies en universiteite. Die naaste openbare voorligtingskantoor
was gemiddeld 42,4 km ver, en die meeste respondente se landbougrond was minder
as 50 km vanaf ʼn voorligtingskantoor geleë. Gevolglik besoek openbare
voorligtingsbeamptes respondente gemiddeld twee keer per maand. Boere wat ʼn
bestaan uit boerdery maak en tevrede was met die openbare voorligting en
adviesdienste, het egter meer besoeke per maand ontvang. Respondente wat ʼn
aansienlike wins gemaak het, is egter minder kere per maand besoek. Sowat 51,1%
van die respondente was tevrede met die gehalte van openbare voorligting en
adviesdienste. Boere wat gereeld deur voorligtingsbeamptes besoek word,
kommersiële boere en boere wat van mening was dat openbare voorligtingdienste wat
deur hulle hulp en aktiwiteite die Batho Pele-beginsel nastrewe, word hierby
ingereken.
Wat die boere se siening van die doeltreffendheid van openbare voorligting en
adviesdienste betref, toon die uitslag dat die meeste respondente van mening was dat
die dienste ondoeltreffend is. Hoogs opgeleide boere, ouerige boere, boere wat
gereeld besoek van voorligtingbeamptes ontvang, en boere wat tevrede is met die
gehalte van dienste, het te kenne gegee dat die openbare voorligting en adviesdienste
doeltreffend was. Afgesien hiervan was openbare voorligting en adviesdienste
volgens die verkennende faktorontleding relevant en van ʼn goeie gehalte. Boere het
laat blyk dat die inligting wat landbouproduksie laat toeneem en hulle toegang tot
tegnologie verbeter, doeltreffend was. Hierdie studie het bevind dat daar inderdaad ʼn
vraag na pluralistiese voorligting deur die regering en universiteite bestaan, aangesien
91,2% van die boere, wat ʼn oorweldigende meerderheid is, ten gunste was van die
insluiting van universiteitsvoorligting by ʼn pluralistiese voorligtingstelsel, ofskoon die
meeste nie bewus was van universiteite in Gauteng wat landboukursusse aanbied nie.
Die meeste respondente was ten gunste van universiteitsvoorligting vanweë die
voordele wat dit inhou, soos beter toegang tot voorligting en adviesdienste, tot formele
onderwys en tot opleiding asook vak- en ander spesialiste. Die uitslag van die BLR
het getoon dat boere wat ʼn groot wins uit hulle landboubedrywe maak en hulle
verbintenis met universiteite beskou as ʼn geleentheid om fondse vir navorsing te
bekom, die insluiting van universiteite by ʼn pluralistiese voorligtingstelsel aanvaar het.
Hierbenewens is drie faktore rakende die aanvaarding van universiteite se insluiting
uit die verkennende faktorontleding verkry, naamlik toegang tot
navorsingshulpbronne, beter voorligtingsdienste en opleiding, en die verspreiding van
universiteite se navorsing. Volgens die bevindings verkies 56,8% van Gautengse
boere ʼn leweringstelsel waarvolgens openbare voorligting ʼn manier is om boere en
universiteite te koördineer (ʼn leweringstelsel bestaande uit boere, openbare
voorligting en universiteite). Boere het hierdie stelsel verkies omdat hulle sodoende
meer inligting uit verskeie bronne kon inwin en betrekkinge met die regering kon
handhaaf. Die resultate van die PNLR dui daarop dat boere wat ʼn aansienlike wins uit
hulle landboubedrywe maak, ʼn leweringstelsel bestaande uit boere, openbare
voorligting en voorligting deur universiteite verkies het bo ʼn leweringstelsel bestaande
uit boere en universiteitsvoorligting. Nagenoeg die helfte van die respondente het
verkies om universiteitsvoorligtingsdienste op hulle boerderye te ontvang. Die ander
helfte was dit oneens. Sommige boere het slegs besoeke aan universiteite verkies,
terwyl ander weer besoeke aan sowel universiteite as hulle boerderye verkies het. Die
meeste boere (41,9%) het verkies om universiteite se voorligting en adviesdienste in
hulle eie taal te ontvang. Wat befondsing betref, was die meerderheid (55,4%), in die
besonder boere vir wie boerdery hulle belangrikste inkomstebron was, bereid om vir
universiteitsvoorligting te betaal. Kommersiële boere en boere vir wie openbare
voorligtingskantore ver weg was, was egter volgens die uitslag van die BLR onwillig
om vir universiteite se voorligtingsdienste te betaal. Die meeste respondente (91%)
was dit eens dat die regering moet instaan vir vervoerkostes, die toelaes van
universiteitspersoneel, mediese fondse (as dit nodig is), die
Werkloosheidsversekeringsfonds (WVF), pensioenfondsbydraes (as dit toepaslik is),
kantoorruimte (as dit nodig is), kantoortoerusting en -meubels, inligting- en
kommunikasietegnologie (IKT), skryfbehoeftes, opleidingsprogramme vir boere en
navorsing vir universiteitsvoorligtingsdienste. Kortom, boere het verwag dat die
regering universiteite se voorligtingsdienste grotendeels befonds.
Ten einde die doeltreffendheid van openbare voorligting en adviesdienste te verbeter,
word aanbeveel dat voorligtingsagente ʼn toepaslike, uitnemende diens lewer en dat
hulle inligting nie alleen landbouproduksie nie, maar ook boere se toegang tot
tegnologie verbeter. Voorts word aanbeveel dat ʼn raamwerk vir ʼn pluralistiese
voorligtingstelsel ontwikkel word deur die Ministerie van Hoër Onderwys en Opleiding;
die Ministerie van Landbou; boere; universiteite en ander belanghebbendes.
Universiteite moet volgens hierdie raamwerk hulle navorsingshulpbronne aan boere
beskikbaar kan stel, boere se toegang tot voorligtingsdienste kan verbeter, boere kan
oplei en ʼn platform kan skep om hulle navorsingsuitkomste aan boere beskikbaar stel.
ʼn Voorligtingleweringselsel waarby openbare voorligting betrek word om koördinering
te vergemaklik, moet die hoofstelsel van universiteitsvoorligting word. Universiteite
moet oorwegend in landbougebiede (boerderye) en in die inheemse tale voorligting
gee. Die regering moet fondse bewillig vir vervoer, ʼn bruto inkomste, mediese hulp,
bydraes tot die WVF en pensioenfondse, kantoorruimte en -toerusting, IKT,
skryfbehoeftes, opleiding vir boere en navorsing met die oog op landbouvoorligting.
Laastens moet boere, universiteite en boereorganisasies ooreenkom op ʼn tarief vir die
voorligtingsdienste wat universiteite lewer.
Mananeo a go hlahla balemi go ya ka dinyakwa tša bona ao a akaretšago
batšeakarolo ba mehutahuta a phethagaditšwe ka dinageng tše ntši go kaonafatša go
šoma gabotse ga, le go fihlelela, ditirelo tša tlhahlo le keletšo ya balemi. Go ya ka
kwešišo ya dikarolo tše dingwe tša setšhaba, diyunibesithi tšeo di rutago dithuto tša
temo di na le bokgoni bja go aba ditirelo tša tlhahlo le keletšo ya balemi ka go dirišana
le mmušo ka gobane ba kgatha tema ka tšweletšong ya tsebo ka go dira dinyakišišo
le go ruta. Le ge go le bjale, ga go tsebje ge eba balemi ba rata lenaneo la go hlahla
balemi go ya ka dinyakwa tša bona go tšwa ka diyunibesithing. Maikemišetšo a
dinyakišišo tše e bile go utolla go nyaka ga balemi go amogela tlhahlo ya balemi go
tšwa ka diyunibesithing ka go lenaneo la go hlahla balemi go ya ka dinyakwa tša bona
tše di fapanego ka phrobentsheng ya Gauteng ka nepo ya go tseba ge eba ditirelo tša
tlhahlo ya balemi di theilwe go go nyaka ga bona. Maikemišetšo a dinyakišišo e bile
go hlaloša seemo sa balemi bao ba hwetšago ditirelo tša tlhahlo le keletšo go
lebeletšwe dipalopalo tša setšhaba ka Gauteng; go tseba maikutlo a balemi mabapi
le ditirelo tša tlhahlo le keletšo ya setšhaba ka tša temo, go lebeletšwe boleng bjo bo
bonwago bja ditirelo tša tlhahlo ya balemi le mabaka ao a di huetšago, gammogo le
phihlelelo ye e diregago kgafetšakgafetša go ditirelo tša tlhahlo ya setšhaba le tšeo di
laolago se; go tseba phihlelelo ya balemi go methopo ya ditirelo tša tlhahlo ya bona;
go tseba maikutlo a balemi mabapi le go šoma gabotse ga ditirelo tša tlhahlo le keletšo
ya setšhaba ka tša temo, go lebeletšwe kudu go šoma gabotse le mabaka ao a
huetšago se, gammogo le mabaka a kutollo ao a amanago le go šoma gabotse fao go
bonwago; go tseba go amogela ga balemi ga tlhahlo ya balemi go tšwa ka yunibesithi
ka go lenaneo la go hlahla balemi go ya ka dinyakwa tša bona tša go fapana, go
lebeletšwe kudu go nyaka go amogela, dikholego tše di lebeletšwego tša tlhahlo ya
balemi go tšwa ka yunibesithi le mabaka ao a huetšago go amogelega ga tlhahlo ya
balemi go tšwa ka yunibesithi; go tseba gore ke lenaneo(mananeo) lefe la tlhhalo ya
balemi la go tšwa ka yunibesithi leo balemi ba le ratago, gammogo le mabaka ao a
huetšago kgetho ya ona; go tseba mabaka a gore ke ka lebaka la eng balemi ba rata
mananeo ao a fapanego a kabo ya tlhahli ya balemi; go tseba maikutlo a balemi ka ga
mokgwa wa maleba wa thušo ya ditšhelete wa ditirelo tša tlhahlo ya balemi go tšwa
ka yunibesithi; le go tseba go nyaka ga balemi go lefa ditirelo tša tlhahlo ya balemi go
tšwa ka yunibesithi, gammogo le mabaka ao a huetšago kgetho ya bona.
Sampole ya balemi ba 442 go tšwa ka Gauteng bao ba bego ba hwetša ditirelo tša
tlhahlo le keletšo ya balemi go tšwa mmušong ba kgethilwe ka sewelo gore ba kgathe
tema ka dinyakišišong. Ka go šomiša setlabelo sa dinyakišišo sa dipotšišo tša go
nyaka gore baarabi ba hlatholle, tshedimošo ya motheo e kgobokeditšwe ka go dira
dipoledišano tša sebele. Tshedimošo ya bontši e ile sekasekwa ka dipalopalo tša
tlhathollo, mokgwa wa dikamanyo tša tshedimošo (PAF), kamanyo ya Kendall tau,
mokgwapoelomorago ya kgokaganyo (BLR), mokgwapoelomorago ya karolo ka
bontši (MLR), mokgwapoelomorago ya dipalontši (MNLR), mokgwapoelomorago wa
tatelanyakgokaganyo (OLR), teko ya Cochran’s Q, teko ya McNemar le teko ya
payonomiale yeo e hwetšwago ka go Sehlopha sa Dipalopalo sa IBM sa Sengwalwa
sa Dipalopalo sa Dithutamahlale tša Leago (SPSS) bešene ya 27. Tshedimošo ya
bontši e ile ya sekasekwa ka go šomiša dikhoute, merero le dilaetši gomme ya
fetošetšwa go difrekhwentshi le go dipersente. Dipoelo tšeo di hweditšwego mabapi
le seemo sa ekonomi ya setšhaba le sa dipalopalo ka ga baarabi di laeditše gore
bontši bja baarabi ba be ba le basadi ba bathobaso bao ba bego ba na le mengwaga
ya ka godimo ga ye 35, ban a le palogare ya mengwaga ye tshela ya maitemogelo a
bolemi, ba be ba bolela Sesotho sa Borwa ebile ba na le thekgo ya balekane ka
lenyalong le go dula mmogo. Bontši bja balemi ba be ba lema ka mafelong a
mannyane mabakeng a go se rekiše ditšweletšwa tša bona – palogare ya bogolo bja
polasa/pholoto e le dihekthara tše 4.55 – le go ba dinageng tša dipoloasa tša setšhaba
le tšeo di rentišitšwego. Ka kakaretšo, baarabi ba be ba hwetša palomoka ya letseno
la tšhelete ye e ka bago R21 387.56 go tšwa go bolemi ka ngwaga ebile ba na le
methopo ya mehutahuta ya letseno. Balemi ba bagolo le bao ba rutegilego kudu ba
hwetša letseno le lentši go tšwa go bolemi, mola e le gore balemi bao ba bego ba
etelwa kgafetšakgafetša ke bahlankedi ba tlhahlo ya balemi bas a hwetše letseno le
lentši. Go hweditšwe gore tekano ya go nyaka go ba seripagare sa baarabi ba bile le
phihlelelo go ditirelo tša tlhahlo ya balemi go tšwa go methopo ya mehutahuta ka ntle
le mmušo, go swana le mekgatlo ya ditšweletšwa, meepo, mebasepala ya selegae,
mekgatlo ye e sego ya mmušo le diyunibesithi. Ka kakaretšo, baarabi ba be ba le
dikhilometara tše di ka bago tše 42.4 kgole le dikantoro tša tlhahlo ya balemi, gomme
bontši bja dipolasa di be di le dikhilometara tše ≤50 kgole le dikantoro tšeo. Ka lebaka
la se, baarabi ba be ba etelwa ka kakaretšo gabedi ka kgwedi ke bahlankedi ba tlhahli
ya balemi, gomme balemi bao ba bego ba tshephile kudu letseno go tšwa ka polaseng
go tšwetša pele go iphediša ga bona le bao ba bego ba kgotsofetše ka boleng bja
ditirelo tša tlhahlo le tša keletšo ya balemi ba be ba hwetša diketelo tše ntši mo
kgweding. Le ge go le bjale, balemi bao ba bego ba dira dipoelo tše ntši ba hweditše
diketelo tše mmalwa ka kgwedi. Tekano ye e ka bago 51.1% ya baarabi ba be ba
kgotsofetše ka boleng bja ditirelo tša tlhalo le tša keletšo ya balemi, gomme bona ba
be ba akaretša balemi bao ba bego ba etelwa kgafetšakgafetša ke bahlankedi ba
tlhahlo ya balemi, balemi ba tša kgwebo le balemi bao ba bego ba bona ditirelo tša
tlhahlo ya balemi bjalo ka tšeo di šomago gabotse go obamela molawana wa Batho
Pele go šoma le batho le go beakanya mešomo.
Dipoelo tšeo di hweditšwego mabapi le go šoma gabotse ga ditirelo tša tlhahlo le
keletšo ya balemi di laeditše gore bontši bja baarabi ba be ba na le maikutlo a gore
ditirelo tšeo ga di šome gabotse. Balemi bao ba rutegilego kudu, balemi bao ba
tšofetšego, balemi bao ba bego ba etelwa kgafetšakgafetša ke bahlankedi ba tlhahlo
ya balemi le balemi bao bao bego ba kgotsofetše ka boleng bja ditirelo ba bone gore
ditirelo tša tlhahlo le keletšo ya balemi di šoma gabotse. Godimo ga fao, tshekatsheko
ya kutollo ya mabaka e laeditše gore ditirelo tša tlhahlo le keletšo ya balemi yeo e
abago ditirelo tša maleba le tše kaone, tshedimošo yeo e kaonafaditšego tšweletšo ya
tša temo le phihlelelo ya ditheknolotši e bonwe bjalo ka yeo e šomago gabotse ke
balemi. Dinyakišišo di utollotše gore lenaneo la go hlahla balemi go ya ka dinyakwa
tša bona leo le akaretšago mmušo le diyunibesithi ke leo le bego le phethagatšwa go
ya ka ge le nyakwa ka lebaka la gore bontši (91.2%) bja balemi bo amogetše kakaretšo
ya tlhahlo ka diyunibesithi ka gare ga lenaneo la go hlahla balemi go ya ka dinyakwa
tša bona, le ge e le gore bontši bja bona ga ba tsebe diyunibesithi tšeo di abago
mananeo a tša temo ka mo lefapheng le la dinyakišišo. Bontši bja baarabi ba ratile
lenaneo la tlhahlo ka diyunibesithi ka lebaka la dikholego tša mehutahuta leo le fanago
ka tšona, go swana le phihlelelo ye kaone go ditirelo tša tlhahlo le keletšo ya balemi;
phihlelelo go thuto le tlhahlo tša semmušo; le sebaka sa go hwetša keletšo go tšwa
go ditsebi le go tšwa go ba bangwe. Dipoelo tša BLR di laeditše gore balemi bao ba
dirago poelo ye kgolo go tšwa go dikgwebo tša bona tša temo ebile ba bona kamano
ya bona le diyunibesithi bjalo ka sebaka sa go fihlelela thušo ya dinyakišišo ba ile ba
amogela go akaretšwa ga diyunibesithi ka go lenaneo la tlhahlo ya balemi go ya ka
dinyakwa tša bona. Godimo ga fao, mabaka a mararo a bohlokwa ao a amanago le
go amogelega ga tlhahlo ka diyunibesithi ao a hweditšwego go tshekatsheko ya kutollo
ya mabaka e bile phihlelelo go methopo ya dinyakišišo, ditirelo le tlhahlo ya balemi
tšeo di kaonafetšego, le go phatlalatšwa ga dinyakišišo tša ka yunibesithi. Dikutollo
tša dinyakišišo di laeditše gore bontši bja balemi (56.8%) ka lekaleng le la dinyakišišo
le ratile lenaneo la phethagatšo ya tlhahlo ya balemi leo le akaretšago tlhahlo ya
setšhaba ka tša temo bjalo ka mokgwa wa kgokaganyo magareng ga balemi le
diyunibesithi (lenaneo la kabo ya tlhahlo ya balemi–tlhahlo ya setšhaba–ka
diyunibesithi). Lenaneo leo go bolelwago ka lona le be le ratwa kudukudu ka gobane
le tla kgontšha balemi go hwetša tshedimošo ka botlalo go tšwa go methopo ya
mehutahuta le go tšwetša pele kamano le mmušo. Dipoelo tša MNLR di aleditše gore
balemi bao ba bego ba dira poelo ye kgolo go dikgwebo tša bona tša temo ba ratile
lenaneo la kabo ya tlhahlo ya balemi–tlhahlo ya setšhaba–ka diyunibesithi go feta
lenaneo la tlhahlo ya balemi ka yunibesithi. Tekano ye e ka bago seripagare sa
baarabi e nyakile go hwetša ditirelo tša tlhahlo ya balemi go tšwa ka diyunibesithi
mafelong a bona a temo, mola e le gore karolo ye nngwe ya balemi e be e arogane
magareng ga bao ba nyakago go etela diyunibesithi fela le bao ba kgethilego mafelo
ka bobedi (diyunibesithi le mafelo a temo). Gape, bontši bja balemi (41.9%) ba nyaka
go hwetša ditirelo tša tlhalo le keletšo ya balemi go tšwa ka diyunibesithing ka dipolelo
tša bona tša ka gae. Mabapi le thušo ya ditšhelete, go hweditšwe gore bontši (55.4%)
bja balemi, kudukudu bao ba tshephilego bolemi bjalo ka letseno la bona le legolo, ba
be ba nyaka go lefa ditirelo tša tlhahlo ka diyunibesithi. Le ge go le bjale, balemi ba
kgwebo le bao ba lego kgole le dikantoro tša tlhahlo ya balemi ba be ba sa nyake goba
go na le kgonagalo ye nnyane ya gore ba ka lefela ditirelo tša tlhahlo ka diyunibesithi,
ka ge go laeditšwe ke dipoelo tša BLR. Le ge go le bjale, bontši (91%) bja baarabi ba
dumetše gore mmušo o swanetše go aba thušo ya ditšhelete tša dinamelwa,
diputseletšo tša bašomi ba yunibesithi, thušo ya tša kalafo (fao go hlokagalago),
Sekhwama sa ba go Lebogišwa Mešomong (UIF) le ditefelo tša tšhelete ya phenšene
(ge go kgonagala), dikantoro (ge di nyakega), ditlabelo tša dikantoro le fenišara,
theknolotši ya tshedimošo le dikgokagano (ICT), setešenari, mananeo a tlhahlo a
balemi le dinyakišišo tša ditirelo tša tlhahlo tša yunibesithi. Ka fao, balemi ba emetše gore mmušo o abe thušo ya ditšhekete go bontši bja ditirelo tša tlhahlo ka
diytunibesithi.
Go kaonafatša go šoma gabotse ga ditirelo tša tlhahlo le keletšo ya setšhaba, go
šišinywa gore badiredi ba ditirelo tša tlhahlo ya setšhaba ba fane ka ditirelo tša
maleba, tša boleng bjo bokaone le go fana ka tshedimošo yeo e kaonafatšago
tšweletšo ya temo le go nolofatša phihlelelo go ditheknolotši tšeo di nyakwago ke
balemi. Godimo ga fao, go šišinywa gore motheo wa semmušo wa lenaneo la tlhahlo
ya balemi go ya ka fao ba nyakago ka gona le hlongwe ka go diriša tshepedišo ya go
kgatha tema ga ga makala a mangwe go akaretšwa Kgoro ya Thuto le Tlhahlo ya
Godingwana, Kgoro ya Temo, balemi, diyunibesithi le batšeakarolo ba bangwe.
Motheo wa lenaneo la tlhahlo ya balemi go ya ka fao ba nyakago ka gona o swanetše
go kgontšha diyunibesithi go fana ka methopo ya dinyakišišo go balemi; go kaonafatša
phihlelelo go ditirelo tša thušo ya balemi le go hlahla balemi; le go hlama sefala sa go
phatlalatša dipoelo tša dinyakišišo tša yunibesithi go ya go balemi. Lenaneo la kabo
ya tlhahlo ya balemi leo le akaretšago tlhahlo ya setšhaba bjalo ka mokgwa wa
kgokaganyo le swanetše go ba lenaneo le legolo la tlhahlo ka yunibesithi. Ditirelo tša
tlhahlo ka yunibesithi di swanetše go abja kudukudu ka mafelong a temo (ka
dipolaseng) ka go šomiša dipolelo tša ka gae tša Afrika Borwa. Mmušo o swanetše go
aba bontši bja thušo ya ditšhelete tša mabapi le dinamelwa, palomoka ya letseno,
thušo ya kalafo, ditefelo tša UIF le tša phenšene, dikantoro, ditlabelo tša dikantoro le
fenišara, theknolotši ya tshedimošo le dikgokagano (ICT), setešenari, mananeo a
tlhahlo a balemi le dinyakišišo tša ditirelo tša tlhahlo tša yunibesithi. Godimo ga fao,
balemi, diyunibesithi le mekgatlo ya balemi ba swanetše go lefa tšhelete ye go
kwanwego ka yona ya ditirelo tša tlhahlo ka diyunibesithi.