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<title>Electronic Theses and Dissertations</title>
<link>https://ir.unisa.ac.za/handle/10500/506</link>
<description>Collection of UNISA electronic theses and dissertations.</description>
<pubDate>Tue, 05 May 2026 10:48:22 GMT</pubDate>
<dc:date>2026-05-05T10:48:22Z</dc:date>
<item>
<title>Deep learning for spatial multi-omics: predicting cardiomyocyte differentiation efficiency at single-cell resolution</title>
<link>https://ir.unisa.ac.za/handle/10500/32428</link>
<description>Deep learning for spatial multi-omics: predicting cardiomyocyte differentiation efficiency at single-cell resolution
Kgabeng, Tumo
Cardiovascular diseases remain the leading cause of global mortality, with limited &#13;
regenerative capacity of adult cardiac tissue presenting significant therapeutic challenges. &#13;
The primary cause of death worldwide is still cardiovascular diseases, and treating these &#13;
conditions is extremely difficult due to the adult heart tissue's limited capacity for &#13;
regeneration. Cardiomyocytes derived from human induced pluripotent stem cells (hiPSC&#13;
CMs) present promising potential for cardiac regenerative medicine; however, existing &#13;
differentiation protocols are highly inconsistent and do not have accurate predictive &#13;
evaluation techniques. By integrating the analysis of temporal gene expression data and &#13;
spatial transcriptomics, this study developed a novel hybrid deep learning architecture that &#13;
combines Graph Neural Networks (GNNs) and Recurrent Neural Networks (RNNs) to &#13;
predict the outcomes of cardiomyocyte differentiation. RNN components analysed temporal &#13;
gene expression trajectories across 800 samples and 10 time points, while GNN &#13;
components processed spatial transcriptomics data from 752 tissue spots to capture spatial &#13;
relationships. Three fusion strategies - concatenation, attention-based, and ensemble &#13;
approaches - were meticulously evaluated. With an accuracy of 96.67%, the ensemble &#13;
fusion approach outperformed the state-of-the-art computational approaches by a &#13;
significant margin (+13.47% compared to the top GNN approaches and +6.97% compared &#13;
to specialised biological models). &#13;
Keywords: Cardiomyocyte differentiation; Spatial transcriptomics, Spatial multi-omics; &#13;
Single-cell biology; Deep learning; Graph Neural Networks; Recurrent Neural Networks; &#13;
Stem cells; Artificial Intelligence; Cardiac biology
</description>
<pubDate>Fri, 06 Mar 2026 00:00:00 GMT</pubDate>
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<dc:date>2026-03-06T00:00:00Z</dc:date>
</item>
<item>
<title>Factors influencing third-year accounting student dropout during Covid-19 at the Tshwane University of Technology</title>
<link>https://ir.unisa.ac.za/handle/10500/32427</link>
<description>Factors influencing third-year accounting student dropout during Covid-19 at the Tshwane University of Technology
Dladla, Veli Godfrey
For years, student dropout in higher education has been a significant challenge for global tertiary institutions, persisting even when resources were allocated to address the issue. COVID-19 affected all higher education students; however, accounting students continued to be a particularly vulnerable group in higher education. This group of accounting students consistently shows a higher student dropout rate. Most studies have focused on first- and second-year accounting student dropouts before COVID-19. Hence, this study sought to identify and understand factors that affected third-year accounting students' dropout at Tshwane University of Technology during COVID-19.&#13;
The study adopted a deductive approach and analysed seven student retention models, student dropout, and COVID-19 in higher education to identify and comprehend the variables associated with student dropout. Data were collected through an online survey using a questionnaire disseminated through Google Forms. This cross-sectional study had a sample of 400 former students, of whom 174 responded, representing a response rate of 43.50%. A simple random sampling method was adopted to select the respondents. Data analysis was performed utilising Version 28 of SPSS (Statistical Package for the Social Sciences).&#13;
Pilot testing of the study questionnaire was conducted to ensure content validity. Cronbach’s alpha coefficient showed a satisfactory reliability level of 0.872 for the study&#13;
measurement instrument. Based on the research findings, 12 student dropout variables with a perception proportion score of 50% during the COVID-19 period were identified. The study found a statistically significant positive correlation between academic, technological, psychological, economic and financial factors. The hypothesis testing results showed two demographic predictors of psychological elements: the study age group and the accommodation type. Respondents residing in TUT accommodations were 69.30% less likely to experience economic and financial problems, since 74.70% were NSFAS-funded.&#13;
The study broadens the understanding of the effect of COVID-19 on higher education and factors of student dropout. This could inform the development of effective strategies to minimise the impact of future unexpected disruptions of a similar kind and the reduction of higher education student dropout.&#13;
Based on the literature review and study findings, the recommendations to reduce student dropout rates and minimise future pandemic impact are to increase infrastructure investment, institutional funding, student funding and counselling reach. Additional recommendations are to adopt dual-mode delivery of academic content, foster partnerships with network providers, curb resource mismanagement, improve lecturers’ attitude to academic tasks, enhance lecturers’ technological skills and introduce a hybrid form of student academic support.&#13;
The study contributes to the literature on student dropout in higher education, —specifically third-year accounting students during COVID-19—and on the effect of COVID-19 on higher education in general. It also highlights gaps that warrant further research.
</description>
<pubDate>Mon, 25 Aug 2025 00:00:00 GMT</pubDate>
<guid isPermaLink="false">https://ir.unisa.ac.za/handle/10500/32427</guid>
<dc:date>2025-08-25T00:00:00Z</dc:date>
</item>
<item>
<title>Strategies for enhancing changes in the implementation of records and archives management programmes in Tanzania</title>
<link>https://ir.unisa.ac.za/handle/10500/32426</link>
<description>Strategies for enhancing changes in the implementation of records and archives management programmes in Tanzania
Kiyabo, Hamisi
This study aimed to develop strategies for enhancing changes in the implementation of records and archives management programmes in Tanzania. The objectives included determining the effects of inputs such as resources and records management frameworks on sustainable implementation, exploring the effects of monitoring activities, evaluating public organisations' evaluation tactics, and developing a framework for change strategies. Changes in records management programmes are inevitable, and organisations must master change management processes, understand drivers, and provide top management support. However, many organisations struggle with enhancing changes due to unfamiliarity with important issues and processes. In Tanzania, despite a well-designed National Records and Archives Management Policy since 2011, non-compliant behaviour, lack of key performance indicators, limited funds, and shortage of skilled personnel hinder effective implementation. The study employed a result chain framework to analyse the sustainable implementation of records management programmes through an exploratory qualitative approach. Data was collected via focus groups, in-depth interviews, and document analysis, with participants selected based on their roles in records management. The findings of the study highlighted the importance of clear objectives, responsibilities, legal framework, staffing, training, monitoring and evaluation, and resource allocation for effective records management in institutions. However, challenges such as lack of understanding, inadequate budgets, and a poorly structured organisational structure hinder the implementation of these activities. The study recommends the strategies to enhance records and archives management, including respecting the profession, raising awareness, hiring professional personnel, allocating budgets, creating an independent department, renaming the term "registry," and involving top management in records management issues. This study's distinctive contribution lies in the creation of a framework that enhances the implementation of records management programmes.; Utafiti huu ulilenga kuandaa mikakati ya kuimarisha mabadiliko katika utekelezaji wa programu za menejimenti ya kumbukumbu na nyaraka nchini Tanzania. Malengo hayo yalijumuisha kubainisha athari za viwezeshi (inputs) kama vile rasilimali na mifumo ya menejimenti ya kumbukumbu katika utekelezaji endelevu, kuchunguza athari za shughuli za ufuatiliaji, kutathmini mbinu za ufuatiliaji zinazotumiwa na taasisi za umma, na kuandaa mfumo wa mikakati ya mabadiliko. Mabadiliko katika programu za usimamizi wa kumbukumbu hayawezi kuepukika, na mashirika lazima yawe na udhibiti wa michakato ya usimamizi, kuelewa visababishi vya mabadiliko, na kutoa usaidizi wa juu wa usimamizi. Hata hivyo, mashirika mengi yanatatizika kuboresha mabadiliko kutokana na kutofahamika kwa masuala muhimu na taratibu. Nchini Tanzania, licha ya sera iliyoundwa vizuri tangu mwaka 2011, tabia zisizofuata kanuni, ukosefu wa viashirio muhimu vya utendaji kazi, uhaba wa fedha, na uhaba wa wafanyakazi wenye ujuzi unazuia utekelezaji mzuri. Utafiti ulitumia mfumo wa mnyororo wa matokeo. Data ilikusanywa kupitia vikundi lengwa, mahojiano ya kina, na uchambuzi wa hati, huku washiriki wakichaguliwa kulingana na majukumu yao katika programu za menejimenti ya kumbukumbu. Matokeo ya utafiti yalibainisha umuhimu wa uongozi wa juu, malengo yaliyo wazi, majukumu, mfumo wa kisheria, utumishi, mafunzo, ufuatiliaji na tathmini, na ugawaji wa rasilimali kwa ajili ya usimamizi bora wa kumbukumbu katika taasisi. Hata hivyo, changamoto kama vile ukosefu wa uelewa, ufinyu wa bajeti, na muundo duni wa shirika huzuia utekelezaji wa shughuli hizi. Utafiti unapendekeza mikakati ya kuimarisha utekelezaji endelevu wa menejiment ya kumbukumbu na nyaraka ikiwa ni pamoja na kuheshimu taaluma, kuongeza ufahamu, kuajiri wafanyakazi wa kitaalamu, kutenga bajeti, kuunda idara inayojitegemea, kubadili jina la "masijala," na kuhusisha uongozi wa juu katika masuala ya utunzaji wa kumbukumbu. Mchango wa kipekee wa utafiti huu upo katika kuunda mfumo unaoboresha utekelezaji wa programu za menejimenti ya kumbukumbu na nyaraka.
Text in English with abstract in English and Swahili
</description>
<pubDate>Wed, 01 Apr 2026 00:00:00 GMT</pubDate>
<guid isPermaLink="false">https://ir.unisa.ac.za/handle/10500/32426</guid>
<dc:date>2026-04-01T00:00:00Z</dc:date>
</item>
<item>
<title>Enablers and strategies of knowledge sharing in small, medium and micro-enterprises (SMMES): a case of the construction industry in South Africa</title>
<link>https://ir.unisa.ac.za/handle/10500/32425</link>
<description>Enablers and strategies of knowledge sharing in small, medium and micro-enterprises (SMMES): a case of the construction industry in South Africa
Boya, Boitumelo Christina
The Small, Medium and Micro-Enterprises (SMMEs) form the backbone of employment and economic growth in South Africa. However, despite this, their sustainability remains a significant challenge, mainly due to poor knowledge transfer and limited access to resources. Consequently, this study investigated the enablers and strategies of knowledge sharing among SMMEs in the South African construction industry, particularly black-owned SMMEs. The existing literature reveals a scarcity of studies examining a particular demographic at this intersection of factors, and thus a significant gap in awareness of their distinct influence on knowledge sharing. This mixed-methods research study was based on a pragmatic paradigm. Quantitative data were collected through structured questionnaires administered to a purposive sample of black-owned SMMEs. In tandem, the qualitative data were obtained through semi-structured interviews with selected industry experts and firm owners. For the quantitative data, analysis was conducted using the Statistical Package for the Social Sciences (SPSS) version 29.0. Furthermore, the qualitative data were analysed using thematic analysis in ATLAS.ti software. The results established that multiple barriers, including the absence of formal systems, a lack of trust, poor leadership and inadequate technology infrastructure, inhibit knowledge sharing in South African construction SMMEs. Moreover, historical exclusion and inequality continue to manifest as systemic barriers to training and industry collaboration. Nevertheless, key enablers cited include leadership support, organisational culture of openness, access to Information Communication and Technology (ICT) tools and the creation of Communities of Practice (CoPs). The study found that mentorship, structured learning programmes and effective communication systems significantly boost knowledge-sharing outcomes. The study concludes that while historical and structural challenges persist, they can be mitigated through intentional strategic interventions that prioritise human capital development and digital integration. Based on these findings, it is recommended that construction business owners and policymakers implement leadership development initiatives, formalise mentorship programmes, adopt scalable knowledge management systems, and institute recognition and reward structures to enhance competitiveness. This study theoretically addresses a significant research gap in the understanding of how factors such as history, organisations, and technology influence knowledge-sharing practices in SMMEs within a South African context. It pragmatically offers practical recommendations for construction business owners seeking to enhance learning within their organisations to improve competitiveness, while also providing a justified focus for future research on knowledge management.; Tlhotlhomisi (thesis) eno ene e batlisisa ka ga dinatlafatsi le matlhale a kabelano ya dikitso mo lekaleng la Dikgwebopotlana, Dikgwebo tsa Magareng le Dikgwebo-kgolwane (di-KPMK/SMME) mo madirelong a botlhama-dikago a Aforika Borwa, bogolobogolo di-KPMK/SMME tse beng ba tsona e leng Bantsho. Erentswa di-KPMK/SMME e le tsona maikaego-magolo a bothapiwa le tswelelopele ya seikonomi mo nageng ya rona, botshwarelelo jwa tsona bo bokoa thata, fa gongwe e le ka lebaka la go tlhoka neeletsano ya dikitso e e tiileng, go tlhaela ga ditlogo, le go tlhoka kemonokeng go tswa mo ditheong tse di jaaka tsa puso. Patlisiso eno e tlhamile gape le mokoa wa kitso e e mabapi le makaelo a a rileng a dikemo le ditaolo tsa kabelano ya dikitso mo makaleng a botlhama-dikago. Ke patlisiso e e dirisitseng mmeo-tswako, e e ikaegileng ka pharadaeme ya Molebo wa Bokgonegi. Go kokoantswe dinewane tsa Sekwantitatifi/Dipalopalo ka go dirisa mebotsolotso e e rulagantsweng go ya ka ngotelo/sampole ya boitlhomo mabapi le di-KPMP/SMME tsa Bantsho, mme dinewane tsa sekhwalitatifi tsona di kokoantswe ka tiriso ya dipotso-therisano tsa seka-thulaganyo tse di tshwerweng le palo e e kgethilweng ya baitseanape ba madirelo le beng ba difệmệ. Dinewane tsa Sekwantitatifi/Dipalopalo di tsharolotswe ka setsharolodi sa SPSS, go dirisiwa dipalopalo tsa botlhalosi, tsharololo ya ditlhotlheletsi, le Mmotlolo/Mmetlelo wa Tlhotlheletsano ya Dithalethale, mme dinewane tsa sekwalitatifi tsona tsa tlhatlhobiwa ka tsharololo ya semerero ka tiriso ya ATLAS.ti. Tsharololo e nnile ya botlhalosi le boranodi, e e lekang go senola dikgolagano le maitemogelo a dipalopalo ka mokgwa o o tebileng. Dipholo tsa ditsharololo di senotse gore: maparego a a maphata-mantsi, a a akaretsang tlhokego ya ditlhamakanyo tse di tlhomameng, le tlhokego ya botshepegi, le boeteledipele jo bo bokoa, le ditlhaelo tsa sethekenoloji, ke tsona dilo tse di kgoreletsang kabelano ya dikitso mo lephateng la di-KPMP/SMME tsa botlhama-dikago mo Aforika Borwa. Mo godimo ga moo, lefatshe la rona le sa ntse le na le matsapa a hisetori ya tlhaolele le tlhoka-tekatekano, a a sa ntseng a tsweletse go nna maparego a a kgoreletsang katiso le tirisano mo madirelong. Le fa go le jalo, go na le dinatlafatsi tsa botlhokwa tse di nopotsweng, tse di akaretsang kemonokeng ya boeteledipele, setlwaedi sa pontsheng sa semokgatlho, phitlhelego ya Didiriswa tsa Thekenoloji ya Tlhaeletsano (DTT/ICT), ga mmogo le go tlhamiwa ga Dimphato sa Patlisiso (SSP/CoPs). Patlisiso eno e lemogile gore botataisi, mananeo a dithutano le ditlhamakanyo tsa tlhaeletsano tse di kwenneng di oketsa diphitlhelelo tsa kabelano ya dikitso mo go utlwalang. Go feta moo, patlisiso e tlhagisa maremelo a a popota a a tlaa tokafatsang kabelano ya dikitso mo di-KPMP/di-SMME tse dinnye tsa botlhama-dikago. Mo ntlheng ya tiori, patlisiso eno e kaba diphatlha mo dipatlisisong tse di mabapi le tsamaisano ya ditlhotlheletsi tsa sehisetori, tsa semekgatlho le tsa sethekenoloji tse di amang kabelano ya dikitso ntlheng ya di-KPMP/SMME mo Aforika Borwa.&#13;
Se e tlaa nnang mosola-mogolo mo go beng ba dikgwebo tsa botlhama-dikago, baeteledipele ba madirelo le batlhama-dipholisi, ke gore patlisiso eno e ba naya dikatlanegiso tse di ka diragatsegang, mme maikaelelo e le go tokafatsa boithuti jwa tsa semekgatlho le bophamphadisani mo kgwebong. Mo godimo ga moo, patlisiso eno e tlaa nna motheo o mo go ona go ka agelelwang dipatlisiso tsa isago mabapi le tsamaiso ya dikitso mo makaleng le mo makaelong a mangwe a diikonomi tsa matla-bošweng.; Ngakolunye uhlangothi ukungasatshalaliswa kolwazi, ukugqoza kwezinsizakusebenza nokungafinyeleli kwabantu ezikhungweni ezelekelela ngolwazi kuyalukhubaza uzinzo. Lolu cwaningo lusungule ulwazinqolobane olumayelana nezimo eziyingqikithi nokulawulwa kolwazi oluyisizinda sokusatshalaliswa kolwazi embonini yezokwakha ngokulandela isihloko esithile kuyo. Kuthathelwa kupharadayimu yokuqonda ulwazi, lolu cwaningo lusebenzisa indlelakwenza exubile. Ulwazi ngendlelakwenza yekhwantithethivu luqoqwe kusetshenziswa amaphepha anohlu lwemibuzo ngokuqoka ngenhloso labo abangosomabhizini abancane (SMMEs). Ngakolunye uhlangothi indlelakwenza yekhwalithethivu isetshenziswe ngenhlolokhono engahlelekile eqhutshwe kongcweti bezimboni ezikhethiwe nabanikazi bamafemi. Ulwazi lwekhwantithethivu luhlaziywe ngeSPSS, kusetshenziswa izibalo ezichazayo nokuhlaziywa kwamaqiniso ayo. Ngakolunye uhlangothi ikhwalithethivu isebenzise ukuhlaziya ngokwendikimba kuthathelwa ohlelweni oluhlehla nyova oluku-ATLAS. Ukuhlaziya bekuchaza futhi kwenaba, ukuze kujule ekuxhumaneni kwezibalo mayelana nolwazi olutholakele ngokusebenza eminyakeni ethile. Okuzuzwe ucwaningo kuveze imigoqo eminingi, efakwa phakathi ukungabibikho kwenqubo ehlelewe ukulandelwa, ukungethembani, ukusweleka kolwazi lokuhola kanye nokungabibikho kwezinsizakusebenza zobuchwepheshe okuyizona zinto ezikhubaza ukwabelana ngolwazi embonini yezokwakha eNingizimu Afrika kosomabhizinisi abancane. Ngaphezu kwakho konke nokungafakwa komlando, ukungalingani kwezizwe nokunye okuyizithiyo kuyaqhubeka nokuveza imigoqo ekuvivinyeni umsebenzi nasekubambisaneni kulezi zimboni. Noma kunjalo, okuyizinsika ezihlinzeka ngamandla ezicashuniwe zimbandakanya ukwesekwa kwezokuhola, ukuvuleleka ngezinqubo zezinhlangano, ukufinyelelisa amathuluzi e-ICTkuzona zonke izisebenzi nokusungulwa Kwemiphakathi Ezibambele Mathupha (CoPs). Lolu cwaningo luzuze ukuthi ukutholakala kwabantu asebemnkantshubomvu, izinhlelo zokufundisa ezilungiselelwe, nokuxhumana okunemivuzo emihle kungelekelela ekufukuleni ukwabelana ngolwazi nemiphumela emihle. Lolu cwaningo lubuye lwethule injula yohlaka oluzokwelekelea ngolwazi ezimbonini zokwakha ezincane ezibizwa ngamaSMMEs. Ngokwenjulabuchopho, lapha kwengezwe ulwazi oluhlanganisa umlando, izinkampani nezobuchwepheshe, konke okubonakale njengesithikamezo sokwabelana ngolwazi eNingizimu Afrika kumaSMMEs Ekwenzeni umsebenzi, lolu cwaningo luhlinzeke ngokufanele kwenziwe okubhalwe ezinconyweni eziqondene nabanikazi bezimboni ezincane, abaholi bazo nabasungula imithetho nezinqubo. Lokhu kuhloswe ngakho ukuthuthukisa ukufunda ezinkampanini nokuthi abasebenzi bakwazi ukuqhudelana nabakwezinye izimboni nabakwezinye izizwe. Okungaphezu kwakho konke lolu cwaningo luhlinzeke ngolwazi lokuhola neminye iminxa engeseka izwe ukuze kusimame umnotho osafufusa.
Text in English with abstract in English, Setwana, and IsiZulu
</description>
<pubDate>Wed, 01 Jan 2025 00:00:00 GMT</pubDate>
<guid isPermaLink="false">https://ir.unisa.ac.za/handle/10500/32425</guid>
<dc:date>2025-01-01T00:00:00Z</dc:date>
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