FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4365448001> ?p ?o ?g. }

• W4365448001 endingPage "120111" @default.
• W4365448001 startingPage "120111" @default.
• W4365448001 abstract "Preserving integrity in online assessments is a matter of concern, worldwide. There exist several ways for cheating in online assessments. Exploiting the available Internet for finding solutions is one of the popular ways of cheating. Several researchers have proposed solutions to handle Internet cheating. Some of them suggest the use of secure browsers, however, these are vulnerable to hacking and prone to technical errors. Many works propose e-proctoring, but it is a resource-intensive method and has significant privacy concerns. Other works propose preventive measures like paraphrasing of questions, but smart google search algorithms defeat the purpose. In this work, we use machine learning to create a model by analysing the assessment log files, for the detection of cheaters who indulge in Internet cheating. Additionally, to address the persistent problem of the identification of ground truth in academic dishonesty, we modify an online quiz tool to collect labelled data. We transform the raw dataset using feature engineering methods, to derive thirteen features from the student and question-related attributes of the assessment log files. Our objective is to obtain the best predictive model for the classification of honest and dishonest students. We create models using two feature selection algorithms (ANOVA and Mutual Information) and five machine learning classifiers (Logistic regression, Support vector machines, Naïve Bayes, K nearest neighbour and Random forest) and evaluate them. From among all the models, Random forest classifier with top features selected by the MI method obtains the best performance with an accuracy of about 85%. We discuss the features that are most influential for the automated detection of cheaters. We also give insights into the critical aspects of a cheat-proof assessment design." @default.
• W4365448001 created "2023-04-15" @default.
• W4365448001 creator A5011728956 @default.
• W4365448001 creator A5066338886 @default.
• W4365448001 date "2023-09-01" @default.
• W4365448001 modified "2023-10-01" @default.
• W4365448001 title "Preserving integrity in online assessment using feature engineering and machine learning" @default.
• W4365448001 cites W1493357981 @default.
• W4365448001 cites W1990073097 @default.
• W4365448001 cites W1995742667 @default.
• W4365448001 cites W2070097038 @default.
• W4365448001 cites W2187670843 @default.
• W4365448001 cites W2201006441 @default.
• W4365448001 cites W2579144703 @default.
• W4365448001 cites W2583830827 @default.
• W4365448001 cites W2587286194 @default.
• W4365448001 cites W2597720601 @default.
• W4365448001 cites W2611461819 @default.
• W4365448001 cites W2624492605 @default.
• W4365448001 cites W2747279489 @default.
• W4365448001 cites W2765571868 @default.
• W4365448001 cites W2790516095 @default.
• W4365448001 cites W2793343875 @default.
• W4365448001 cites W2796668783 @default.
• W4365448001 cites W2803256609 @default.
• W4365448001 cites W2806963187 @default.
• W4365448001 cites W2901286824 @default.
• W4365448001 cites W2902813639 @default.
• W4365448001 cites W2909471010 @default.
• W4365448001 cites W2919115771 @default.
• W4365448001 cites W2936922813 @default.
• W4365448001 cites W2996081225 @default.
• W4365448001 cites W3006568366 @default.
• W4365448001 cites W3008632672 @default.
• W4365448001 cites W3011905866 @default.
• W4365448001 cites W3026091703 @default.
• W4365448001 cites W3037810171 @default.
• W4365448001 cites W3047349791 @default.
• W4365448001 cites W3094685058 @default.
• W4365448001 cites W3130678980 @default.
• W4365448001 cites W3132358865 @default.
• W4365448001 cites W3160876788 @default.
• W4365448001 cites W3181388821 @default.
• W4365448001 cites W3213940694 @default.
• W4365448001 cites W4220695000 @default.
• W4365448001 cites W4223632447 @default.
• W4365448001 cites W4253584691 @default.
• W4365448001 cites W4313479734 @default.
• W4365448001 doi "https://doi.org/10.1016/j.eswa.2023.120111" @default.
• W4365448001 hasPublicationYear "2023" @default.
• W4365448001 type Work @default.
• W4365448001 citedByCount "1" @default.
• W4365448001 countsByYear W43654480012023 @default.
• W4365448001 crossrefType "journal-article" @default.
• W4365448001 hasAuthorship W4365448001A5011728956 @default.
• W4365448001 hasAuthorship W4365448001A5066338886 @default.
• W4365448001 hasConcept C108583219 @default.
• W4365448001 hasConcept C110875604 @default.
• W4365448001 hasConcept C116834253 @default.
• W4365448001 hasConcept C119857082 @default.
• W4365448001 hasConcept C12267149 @default.
• W4365448001 hasConcept C124101348 @default.
• W4365448001 hasConcept C136764020 @default.
• W4365448001 hasConcept C138885662 @default.
• W4365448001 hasConcept C148483581 @default.
• W4365448001 hasConcept C154945302 @default.
• W4365448001 hasConcept C15744967 @default.
• W4365448001 hasConcept C169258074 @default.
• W4365448001 hasConcept C2776401178 @default.
• W4365448001 hasConcept C2778024590 @default.
• W4365448001 hasConcept C2778827112 @default.
• W4365448001 hasConcept C41008148 @default.
• W4365448001 hasConcept C41895202 @default.
• W4365448001 hasConcept C52001869 @default.
• W4365448001 hasConcept C59822182 @default.
• W4365448001 hasConcept C77805123 @default.
• W4365448001 hasConcept C86803240 @default.
• W4365448001 hasConcept C95623464 @default.
• W4365448001 hasConceptScore W4365448001C108583219 @default.
• W4365448001 hasConceptScore W4365448001C110875604 @default.
• W4365448001 hasConceptScore W4365448001C116834253 @default.
• W4365448001 hasConceptScore W4365448001C119857082 @default.
• W4365448001 hasConceptScore W4365448001C12267149 @default.
• W4365448001 hasConceptScore W4365448001C124101348 @default.
• W4365448001 hasConceptScore W4365448001C136764020 @default.
• W4365448001 hasConceptScore W4365448001C138885662 @default.
• W4365448001 hasConceptScore W4365448001C148483581 @default.
• W4365448001 hasConceptScore W4365448001C154945302 @default.
• W4365448001 hasConceptScore W4365448001C15744967 @default.
• W4365448001 hasConceptScore W4365448001C169258074 @default.
• W4365448001 hasConceptScore W4365448001C2776401178 @default.
• W4365448001 hasConceptScore W4365448001C2778024590 @default.
• W4365448001 hasConceptScore W4365448001C2778827112 @default.
• W4365448001 hasConceptScore W4365448001C41008148 @default.
• W4365448001 hasConceptScore W4365448001C41895202 @default.
• W4365448001 hasConceptScore W4365448001C52001869 @default.
• W4365448001 hasConceptScore W4365448001C59822182 @default.
• W4365448001 hasConceptScore W4365448001C77805123 @default.

• next