FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4387221610> ?p ?o ?g. }

• W4387221610 endingPage "45" @default.
• W4387221610 startingPage "29" @default.
• W4387221610 abstract "Poor ICT performance in teacher training colleges makes it more difficult for the majority of teachers to successfully use ICT resources in their teaching and learning. When teachers can efficiently utilize ICT resources, it empowers them to update their knowledge through online learning, consequently enhancing the overall quality of teaching and learning. This positive outcome can be observed through improved ICT performance. The aim of this article is to identify the appropriate Data Mining algorithms for predicting student teachers’ performance in ICT. The systematic literature review that was guided by the PRISMA statement 2020 served as the study methodology. It makes for clear reporting and offers a detailed checklist and flow diagram that direct the review procedure. On November 6, 2022, about 196 scholarly articles were downloaded from three digital libraries: Science Direct (38), ACM Digital Library (72), IEEE Xplore (51), and 35 from the Google Scholar search engine. After screening and eligibility checking, 28 scholarly articles were selected and analysed through content analysis in terms of the most commonly used algorithms, the year of publication, the study purposes, and the accuracy performance metrics. Considering the specific study findings represented quantitatively, Decision Trees and Naive Bayes were found to be the most commonly used Data Mining algorithms, with a count of 20.6% each. The most recently identified articles were published between 2014 and 2022. In terms of study purposes, a large number of studies focused on predicting student performance. Furthermore, about 6 out of 8 algorithms used in previous studies were found to score 80% or above in the average percentage of the highest and lowest accuracy metrics. Therefore, considering the general findings, the study identified five Data Mining algorithms as appropriate and most commonly used for prediction of student teachers’ performance in ICT. They are Naive Bayes, K-Nearest Neighbour, Support Vector Machine, Random Forest, and Decision Tree. The findings of this study would assist the government, college tutors, and student teachers in making better decisions to improve ICT performance for pre-service and in-service teachers." @default.
• W4387221610 created "2023-10-01" @default.
• W4387221610 creator A5040883660 @default.
• W4387221610 creator A5092976109 @default.
• W4387221610 creator A5092976110 @default.
• W4387221610 date "2023-09-30" @default.
• W4387221610 modified "2023-10-01" @default.
• W4387221610 title "DATA MINING ALGORITHMS FOR PREDICTION OF STUDENT TEACHERS’ PERFORMANCE IN ICT: A SYSTEMATIC LITERATURE REVIEW" @default.
• W4387221610 doi "https://doi.org/10.33407/itlt.v96i4.5246" @default.
• W4387221610 hasPublicationYear "2023" @default.
• W4387221610 type Work @default.
• W4387221610 citedByCount "0" @default.
• W4387221610 crossrefType "journal-article" @default.
• W4387221610 hasAuthorship W4387221610A5040883660 @default.
• W4387221610 hasAuthorship W4387221610A5092976109 @default.
• W4387221610 hasAuthorship W4387221610A5092976110 @default.
• W4387221610 hasBestOaLocation W43872216101 @default.
• W4387221610 hasConcept C111472728 @default.
• W4387221610 hasConcept C11413529 @default.
• W4387221610 hasConcept C119857082 @default.
• W4387221610 hasConcept C12267149 @default.
• W4387221610 hasConcept C124101348 @default.
• W4387221610 hasConcept C124952713 @default.
• W4387221610 hasConcept C127413603 @default.
• W4387221610 hasConcept C136764020 @default.
• W4387221610 hasConcept C138885662 @default.
• W4387221610 hasConcept C142362112 @default.
• W4387221610 hasConcept C154945302 @default.
• W4387221610 hasConcept C15744967 @default.
• W4387221610 hasConcept C164913051 @default.
• W4387221610 hasConcept C17744445 @default.
• W4387221610 hasConcept C180747234 @default.
• W4387221610 hasConcept C189708586 @default.
• W4387221610 hasConcept C199539241 @default.
• W4387221610 hasConcept C202532154 @default.
• W4387221610 hasConcept C23123220 @default.
• W4387221610 hasConcept C2522767166 @default.
• W4387221610 hasConcept C2779356329 @default.
• W4387221610 hasConcept C2779473830 @default.
• W4387221610 hasConcept C2779530757 @default.
• W4387221610 hasConcept C41008148 @default.
• W4387221610 hasConcept C513874922 @default.
• W4387221610 hasConcept C52001869 @default.
• W4387221610 hasConcept C539667460 @default.
• W4387221610 hasConcept C67363961 @default.
• W4387221610 hasConcept C84525736 @default.
• W4387221610 hasConceptScore W4387221610C111472728 @default.
• W4387221610 hasConceptScore W4387221610C11413529 @default.
• W4387221610 hasConceptScore W4387221610C119857082 @default.
• W4387221610 hasConceptScore W4387221610C12267149 @default.
• W4387221610 hasConceptScore W4387221610C124101348 @default.
• W4387221610 hasConceptScore W4387221610C124952713 @default.
• W4387221610 hasConceptScore W4387221610C127413603 @default.
• W4387221610 hasConceptScore W4387221610C136764020 @default.
• W4387221610 hasConceptScore W4387221610C138885662 @default.
• W4387221610 hasConceptScore W4387221610C142362112 @default.
• W4387221610 hasConceptScore W4387221610C154945302 @default.
• W4387221610 hasConceptScore W4387221610C15744967 @default.
• W4387221610 hasConceptScore W4387221610C164913051 @default.
• W4387221610 hasConceptScore W4387221610C17744445 @default.
• W4387221610 hasConceptScore W4387221610C180747234 @default.
• W4387221610 hasConceptScore W4387221610C189708586 @default.
• W4387221610 hasConceptScore W4387221610C199539241 @default.
• W4387221610 hasConceptScore W4387221610C202532154 @default.
• W4387221610 hasConceptScore W4387221610C23123220 @default.
• W4387221610 hasConceptScore W4387221610C2522767166 @default.
• W4387221610 hasConceptScore W4387221610C2779356329 @default.
• W4387221610 hasConceptScore W4387221610C2779473830 @default.
• W4387221610 hasConceptScore W4387221610C2779530757 @default.
• W4387221610 hasConceptScore W4387221610C41008148 @default.
• W4387221610 hasConceptScore W4387221610C513874922 @default.
• W4387221610 hasConceptScore W4387221610C52001869 @default.
• W4387221610 hasConceptScore W4387221610C539667460 @default.
• W4387221610 hasConceptScore W4387221610C67363961 @default.
• W4387221610 hasConceptScore W4387221610C84525736 @default.
• W4387221610 hasIssue "4" @default.
• W4387221610 hasLocation W43872216101 @default.
• W4387221610 hasOpenAccess W4387221610 @default.
• W4387221610 hasPrimaryLocation W43872216101 @default.
• W4387221610 hasRelatedWork W1470425429 @default.
• W4387221610 hasRelatedWork W3032901101 @default.
• W4387221610 hasRelatedWork W3168126470 @default.
• W4387221610 hasRelatedWork W3204641204 @default.
• W4387221610 hasRelatedWork W4205958290 @default.
• W4387221610 hasRelatedWork W4226139868 @default.
• W4387221610 hasRelatedWork W4285225238 @default.
• W4387221610 hasRelatedWork W4285407528 @default.
• W4387221610 hasRelatedWork W4383746529 @default.
• W4387221610 hasRelatedWork W4386984454 @default.
• W4387221610 hasVolume "96" @default.
• W4387221610 isParatext "false" @default.
• W4387221610 isRetracted "false" @default.
• W4387221610 workType "article" @default.