Using artificial intelligence methods to assess academic achievement in public high schools of a European Union country

Cruz-Jesus, Frederico; Castelli, Mauro; Oliveira, Tiago; Mendes, Ricardo Manuel Nogueira; Nunes, Catarina; Sa-Velho, Mafalda; Rosa-Louro, Ana

doi:10.1016/j.heliyon.2020.e04081

Cited by 77 publications

(42 citation statements)

References 73 publications

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“…The main use of AI for assessment is focused mainly on higher education contexts, although there are some examples of its use at secondary education level [43,47].…”

Section: Resultsmentioning

confidence: 99%

“…Some of them explicitly mention this type of evaluation, while others can be extrapolated from what is described in the work. Three of the papers that do not use formative assessment focus on the use of AI in English language teaching [27,44,50], another two used AI in secondary education [43,47] and the other two in mathematics, but at university level [48,49].…”

Section: Formative Evaluation As the Reason For The Use Of Aimentioning

confidence: 99%

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Artificial Intelligence for Student Assessment: A Systematic Review

2021

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Artificial Intelligence (AI) is being implemented in more and more fields, including education. The main uses of AI in education are related to tutoring and assessment. This paper analyzes the use of AI for student assessment based on a systematic review. For this purpose, a search was carried out in two databases: Scopus and Web of Science. A total of 454 papers were found and, after analyzing them according to the PRISMA Statement, a total of 22 papers were selected. It is clear from the studies analyzed that, in most of them, the pedagogy underlying the educational action is not reflected. Similarly, formative evaluation seems to be the main use of AI. Another of the main functionalities of AI in assessment is for the automatic grading of students. Several studies analyze the differences between the use of AI and its non-use. We discuss the results and conclude the need for teacher training and further research to understand the possibilities of AI in educational assessment, mainly in other educational levels than higher education. Moreover, it is necessary to increase the wealth of research which focuses on educational aspects more than technical development around AI.

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“…The main use of AI for assessment is focused mainly on higher education contexts, although there are some examples of its use at secondary education level [43,47].…”

Section: Resultsmentioning

confidence: 99%

Section: Formative Evaluation As the Reason For The Use Of Aimentioning

confidence: 99%

Artificial Intelligence for Student Assessment: A Systematic Review

2021

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“…Moreover, these authors reinforced that most scientists, engineers, and clinicians are not prepared to contribute to the AI revolution in healthcare. Moreover, Cruz-Jesus et al [60] (research from the FCT grant (vide Appendix A-DSAIPA/DS/0032/2018)) also conducted a study in the area of education, namely with regard to academic performance, which is one of the most global challenges. They presented an innovative approach, using cutting-edge AI techniques, to predict the academic performance of practically all high school students in Portugal.…”

Section: Theoretical Backgroundmentioning

confidence: 99%

Impact of Artificial Intelligence Research on Politics of the European Union Member States: The Case Study of Portugal

2020

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Currently, artificial intelligence (AI) is at the center of academic and public debate. However, its implications on politics remain little understood. To understand the impact of the AI phenomenon on politics of the European Union (EU), we have carried out qualitative multimethod research by performing a systematic literature review and a case study. The first method was performed according to the preferred reporting items for systematic reviews and meta-analyses (PRISMA), in order to report the state-of-the-art in the existing literature and explore the most relevant research areas. The second method contained contributions from experts in data science and AI of the Portuguese scientific community. The results showed that solutions such as intelligent decision support systems are improving the political decision-making process and impacting the Portuguese society at local, regional, and national levels. We also found that practitioners and scientists are currently shifting their interests from environmental and biological sciences to healthcare services, which is bringing new challenges in terms of protecting patient/citizen data and growing concerns about handling of critical information. Future research may focus on comparative studies with other EU States to obtain a comprehensive and holistic understanding of the AI phenomenon.

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“…At the same time, the possible errors in methods are obvious for users and can be identified and corrected immediately based on the feedback of the education administrators. Frederico et al [20] attempted to find the factors that affected academic performance through feature importance. They transformed the academic performance prediction into a binary classification problem of whether students successfully completed their studies.…”

Section: Related Workmentioning

confidence: 99%

An interpretable prediction method for university student academic crisis warning

Zhai

Wang

et al. 2021

Complex Intell. Syst.

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Data-driven techniques improve the quality of talent training comprehensively for university by discovering potential academic problems and proposing solutions. We propose an interpretable prediction method for university student academic crisis warning, which consists of K-prototype-based student portrait construction and Catboost–SHAP-based academic achievement prediction. The academic crisis warning experiment is carried out on desensitization multi-source student data of a university. The experimental results show that the proposed method has significant advantages over common machine learning algorithms. In terms of achievement prediction, mean square error (MSE) reaches 24.976, mean absolute error (MAE) reaches 3.551, coefficient of determination ($$R^{2}$$ R 2 ) reaches 80.3%. The student portrait and Catboost–SHAP method are used for visual analysis of the academic achievement factors, which provide intuitive decision support and guidance assistance for education administrators.

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Using artificial intelligence methods to assess academic achievement in public high schools of a European Union country

Cited by 77 publications

References 73 publications

Artificial Intelligence for Student Assessment: A Systematic Review

Artificial Intelligence for Student Assessment: A Systematic Review

Impact of Artificial Intelligence Research on Politics of the European Union Member States: The Case Study of Portugal

An interpretable prediction method for university student academic crisis warning

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