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

ABSTRACT: Understanding academic achievement (AA) is one of the most global challenges, as there is evidence that it is deeply intertwined with economic development, employment, and countries' wellbeing. However, the research conducted on this topic grounds in traditional (statistical) methods employed in survey (sample) data. This paper presents a novel approach, using state-of-the-art artificial intelligence (AI) techniques to predict the academic achievement of virtually every public high school student in Portugal, i.e., 110,627 students in the academic year of 2014/2015. Different AI and non-AI methods are developed and compared in terms of performance. Moreover, important insights to policymakers are addressed.

SUBMITTER: Cruz-Jesus F

PROVIDER: S-EPMC7287246 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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

Cruz-Jesus Frederico F Castelli Mauro M Oliveira Tiago T Mendes Ricardo R Nunes Catarina C Sa-Velho Mafalda M Rosa-Louro Ana A

Heliyon 20200609 6

Understanding academic achievement (AA) is one of the most global challenges, as there is evidence that it is deeply intertwined with economic development, employment, and countries' wellbeing. However, the research conducted on this topic grounds in traditional (statistical) methods employed in survey (sample) data. This paper presents a novel approach, using state-of-the-art artificial intelligence (AI) techniques to predict the academic achievement of virtually every public high school studen ...[more]

PMID: 32551378

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Project description:BackgroundEuropean Member States, the European Commission and its agencies work together to enhance preparedness and response for serious cross-border threats to health such as Ebola. Yet, common understanding of public health emergency preparedness across EU/EEA countries is challenging, because preparedness is a relatively new field of activity and is inherently fraught with uncertainty. A set of practical, widely accepted and easy to use recommendations for generic preparedness that bundles the activities described in separate guidance documents supports countries in preparing for any possible health threat. The aim of this consensus procedure was to identify and seek consensus from national-level preparedness experts from EU/EEA countries on key recommendations of public health emergency preparedness.MethodsTo identify key recommendations and to prioritize the recommendations we started with a literature consensus procedure, followed by a modified Delphi method for consultation of public health emergency preparedness leaders of EU/EEA countries. This consisted of six consecutive steps: a questionnaire to achieve consensus on a core set of recommendations, a face-to-face consultation, preselection of prioritized recommendations, a questionnaire to achieve consensus on the prioritized set and a face-to-face consensus meeting to further prioritize recommendations.ResultsAs a result, EU/EEA experts selected 149 recommendations as core preparedness principles and prioritized 42. The recommendations were grouped in the seven domains: governance (57), capacity building and maintenance (11), surveillance (19), risk-assessment (16), risk- and crisis management (35), post-event evaluation (6) and implementation of lessons learned (5).ConclusionsThis prioritised set of consensus principles can provide a foundation for countries aiming to evaluate and improve their preparedness for public health emergencies. The recommendations are practical, support generic preparedness planning, and can be used by all countries irrespective of their current level of preparedness.

Dataset Information

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

Publications

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

Similar Datasets

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