Intelligent modelling for predicting students' final grades

Simjanoska, Monika; Gušev, Marjan; Bogdanova, Ana Madevska

doi:10.1109/mipro.2014.6859753

Cited by 7 publications

(5 citation statements)

References 16 publications

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“…Figure 2 shows the dispersion of studies conducted in the European region, which are located in Greece [39], Macedonia [40], Norway [41], Poland [42], Serbia [43] and the United Kingdom [44].…”

Section: Q4: Where Do the Studies Take Place?mentioning

confidence: 99%

“…Out of all 20 papers, 14 were focused on Higher Education students and 1 focused on Secondary Education Students [39]. The other 5 were not aimed at a particular group of students, since they were theoretical in nature [32,40,41,44,47].…”

Section: P O S T Q5: Which Is the Population Of The Study?mentioning

confidence: 99%

“…Other researchers used AIs to analyze secondary achievement data from the students (previous grades obtained in tests and/or assignments) in order to either predict the students' final score in the course [38][39][40] or to categorize the students' work throughout the course according to a pre-established set of grade categories (A, B, C, etc.) [44].…”

Section: P O S Tmentioning

confidence: 99%

See 2 more Smart Citations

AI-Driven Assessment of Students: Current Uses and Research Trends

Prieto

Gamazo

Cruz-Benito

et al. 2020

Lecture Notes in Computer Science

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During the last decade, the use of AIs is being incorporated into the educational field whether to support the analysis of human behavior in teachinglearning contexts, as didactic resource combined with other technologies or as a tool for the assessment of the students.This proposal presents a Systematic Literature Review and mapping study on the use of AIs for the assessment of students that aims to provide a general overview of the state of the art and identify the current areas of research by answering 6 research questions related with the evolution of the field, and the geographic and thematic distribution of the studies.As a result of the selection process this study identified 20 papers focused on the research topic in the repositories SCOPUS and Web of Science from an initial amount of 129.The analysis of the papers allowed the identification of three main thematic categories: assessment of student behaviors, assessment of student sentiments and assessment of student achievement as well as several gaps in the literature and future research lines addressed in the discussion.

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Section: Q4: Where Do the Studies Take Place?mentioning

confidence: 99%

Section: P O S T Q5: Which Is the Population Of The Study?mentioning

confidence: 99%

Section: P O S Tmentioning

confidence: 99%

See 1 more Smart Citation

AI-Driven Assessment of Students: Current Uses and Research Trends

Prieto

Gamazo

Cruz-Benito

et al. 2020

Lecture Notes in Computer Science

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“…Examples of studies that utilised information from students' activities in online learning and assessment platforms in predicting performance include ( [12], [13], [14] Figures 1 and 2 show the studies reviewed here categorised according to the types and variety of the data sources they used. Many studies used multiple data sources.…”

Section: Evolution Of Data Sources In Student Performance Predictionmentioning

confidence: 99%

A Comparative Analysis of Selected Studies in Student Performance Prediction

Ashenafi¹

2017

IJDKP

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“…Целенаправленный поиск журнальных и книжных источников, в названиях и текстах которых применяется термин интеллектуальное моделирование и его вариации, показал, что таких публикаций не много. В результате удалось найти только несколько статей украинских авторов [1][2][3][4][5][6] и примерно столько же из ближнего зарубежья [7][8][9][10][11][12][13] по данной тематике, в то время как в англоязычной литературе словосочетание intelligent modeling распространено несколько больше, например [14][15][16][17][18][19][20][21]. Это говорит, с одной стороны, о том, что такая тематика уже заявила о своем существовании и актуальности, а с другой -что понятие интеллектуального моделирования все еще не является устоявшимся, широко применяемым и общепризнанным.…”

Section: обзор публикаций по интеллектуальному моделированиюunclassified

Conceptual fundamentals of intelligent modeling

Stepashko¹

2016

Upr. sist. maš.

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Рассмотрены вопросы интеллектуализации средств моделирования сложных процессов и систем. В результате аналитического обзора подходов предложена усовершенствованная концепция интеллектуального моделирования на основе анализа и структуризации знаний в предметной области построения моделей. Розглянуто питання інтелектуалізації засобів моделювання складних процесів та систем. В результаті аналітичного огляду підходів запропоновано удосконалену концепцію інтелектуального моделювання на основі аналізу і структуризації знань у предметній галузі побудови моделей.

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Intelligent modelling for predicting students' final grades

Cited by 7 publications

References 16 publications

AI-Driven Assessment of Students: Current Uses and Research Trends

AI-Driven Assessment of Students: Current Uses and Research Trends

A Comparative Analysis of Selected Studies in Student Performance Prediction

Conceptual fundamentals of intelligent modeling

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