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Investigating the influence of first-year expectations and experiences on student academic performance

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dc.contributor.advisor Malan, Katherine M.
dc.contributor.advisor MaseTshaba, M. T.
dc.contributor.author Booi, Elizabeth Mmapholo
dc.date.accessioned 2024-09-03T12:26:32Z
dc.date.available 2024-09-03T12:26:32Z
dc.date.issued 2024-01
dc.identifier.uri https://hdl.handle.net/10500/31620
dc.description Text in English, abstracts in English, Afrikaans and Tswana en
dc.description.abstract This study examines the impact of first-year university students’ expectations and experiences on their academic performance to enable early strategic interventions. The research is grounded in various theoretical frameworks, including Astin’s theory of student involvement, Gardner’s transition theory, Tinto’s theory of student departure and Lizzio’s framework of five senses of success, providing a comprehensive understanding of the transition of students to university life. The study follows a six-step Cross-Industry Standard Process for Data Mining (CRISP-DM). It involves data profiling of student demographics, academic attributes, expectations and experiences from a sample dataset of 2 054 records at the University of the Western Cape, South Africa. Key findings reveal differences in academic performance across different demographics, with financial support significantly affecting outcomes. Factor analysis identified latent factors such as effective learning, social well-being, academic support, and access to information. The study found that the student performance models were not sufficiently robust for accurate predictions, with F1-scores below 60%. In contrast, academic outcome models, especially the random forest model, showed more promise, with F1-scores above 70%. Recommendations focus on targeted interventions, comprehensive orientation, enhanced academic support, and fostering an environment for social well-being. The study highlights the need for a multifaceted approach to student support, emphasising regular monitoring, evaluation and adaptability in interventions to create a supportive academic environment. en
dc.description.abstract Hierdie studie doen ondersoek na die impak van eerstejaaruniversiteit-studente se verwagtinge en ervarings op hul akademiese prestasie ten einde tydige strategiese ingrypings te aktiveer. Die navorsing is op verskeie teoretiese raamwerke gegrond, wat insluit Astin se teorie van studentebetrokkenheid, Gardner se oorgangsteorie, Tinto se teorie oor studente wat opskop en Lizzio se suksesraamwerk van vyf gewaarwordinge. Die navorsing bied dus ’n omvattende begrip van studente se oorgang tot universiteitslewe. Die studie volg ’n ses-stap, kruisindustrie standaard proses vir dataontginning (Cross-Industry Standard Process for Data Mining [CRISP-DM]). Dit behels die datasamestelling van studentedemografie, akademiese eienskappe, verwagtinge en ervarings uit ’n steekproefdatastel van 2 054 rekords van studente aan die Universiteit van Wes-Kaapland, Suid-Afrika. Deurslaggewende bevindinge dui op verskille in akademiese prestasie oor verskillende demografie¨e heen, met finansi¨ele steun wat die uitkomste beduidend affekteer. Faktoranalise het latente faktore soos effektiewe leer, maatskaplike welstand, akademiese ondersteuning en toegang tot inligting ge¨ıdentifiseer. Die studie het bevind dat studenteprestasiemodelle nie sterk genoeg was vir akkurate voorspellings nie. F1-tellings was laer as 60%. Daarteenoor was die akademiese-uitkomstemodelle, veral die ewekansige bosmodel met F1-tellings van ho¨er as 70% meer belowend. Aanbevelings fokus op gerigte ingrypings, omvattende ori¨entasie, verhoogde akademiese ondersteuning en die kweek van ’n omgewing wat maatskaplike welstand bevorder. Die studie vestig die aandag op die behoefte aan ’n veelvlakkige benadering tot studenteondersteuning en lˆe klem op gereelde monitering, evaluering en plooibaarheid van ingrypings ten einde n ondersteunende akademiese omgewing daar te stel. af
dc.description.abstract Patlisiso e e tlhatlhoba tshusumetso ya ditsholofelo tsa ngwaga wa ntlha wa dithuto wa baithuti ba yunibesithi gammogo le maitemogelo a bone a tiragatso ya seakademiki go ka ba kgontsha go dira ditogamaano go sa le gale. Patlisiso e e ikaegile mo matlhomesong a thuto a a mmalwa ao a akaretsang kgopolo ya Astin ya go nna le seabe ga baithuti, kgopolo ya phetogo ya Gardner, kgopolo ya Tinto ya go tsamaya ga baithuti, le letlhomeso la maikutlo a katlego a le matlhano la Lizzio, mme tsotlhe tse di tla tlamela ka kitso ya go tlhaloganya ka botlalo phetogo ya baithuti fa ba tsena mo botshelong jwa yunibesithi. Patlisiso e e latela magato a le marataro a Thulaganyo ya Tekanyetso ya Kgabaganyomadirelo ya Kepadatha (CRISP-DM). E akaretsa go dira porofaele ya datha ya palo ya baithuti, dinonofo tsa seakademiki, ditsholofelo le maitemogelo go tswa seteng ya datha ya tseosekao ya direkoto di le 2 054 tsa kwa Yunibesithing ya Kapa Bophirima, Aforika Borwa. Diphitlhelelo tse di botlhokwa di senola dipharologanyo magareng ga tiragatso ya seakademiki go kgabaganya dipalo tsa baithuti tse di farologanyeng, le tshegetso ya matlole eo e amang dipoelo segolo. Tlhatlhobo ya dintlha e supile dintlha tse di fitlhegileng jaaka go ithuta sentle, boitekanelo jwa loago, tshegetso ya seakademiki, le phitlhelelo ya tshedimosetso. Patlisiso e e fitlhetse gore dikao tsa tiragatso ya baithuti di ne di sa nonofela ponelopele e e tlhomameng, ka maduo a F1 a a ka tlase ga 60%. Mo pharologanyong, dikao tsa dipoelo tsa seakademiki, segolojang sekao sa random forest, se supile tshepiso e nngwe gape, ka maduo a F1 a a kwa godimo ga 70%. Dikatlanegiso di tsepamisa mogopolo mo ditsereganyong tse di lebilweng, molebo ka botlalo, tshegetso e e tokafaditsweng ya seakademiki, gammogo le kgodiso ya maemo a boitekanelo jwa loago. Patlisiso e tlhagisa tlhokego ya mokgwa wa dikarolo di le dintsi tsa tshegetso ya baithuti, go gatelela tekolo ya nako le nako, go tlhatlhoba le go fetofetoga ga ditsereganyo go tlhola maemo a tshegetso a seakademiki. tn
dc.format.extent 1 online resource (vi, 182 leaves) : illustrations (chiefly color) en
dc.language.iso en en
dc.subject Educational data mining en
dc.subject Random forest en
dc.subject Exploratory factor analysis en
dc.subject Student academic performance en
dc.subject First-year experience en
dc.subject First-year expectation en
dc.subject Transition theory en
dc.subject Student involvement theory en
dc.subject Theory of student departure en
dc.subject Five senses of success framework en
dc.subject Student Support and Co-Curricular activities en
dc.subject SDG 4 Quality Education en
dc.subject.other UCTD en
dc.title Investigating the influence of first-year expectations and experiences on student academic performance en
dc.type Dissertation en
dc.description.department Decision Sciences en
dc.description.degree M. Sc. (Operations Research) en


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