Test (évaluation)

Résumé

droite|vignette|280x280px|Etudiants qui passent leurs examens au Mahatma Gandhi Seva Ashram, Jaura, en Inde. droite|vignette|280x280px|Etudiants cambodgiens qui passe un examen en vue d'une demande pour l'école technique de Don Bosco de Sihanoukville en 2008. vignette|280x280px|Etudiants américains en classe d'ordinateurs fondamentale en train de faire une évaluation sur ordinateur. Une évaluation ou test (anglicisme) ou examen (informellement examination ou exam.) est une évaluation dans le but de mesurer les connaissances, compétences, aptitudes, d'un candidat évalué, ou dans le but de le classer dans différentes catégories (p.ex. en fonction de leurs croyances). Une évaluation peut être administré verbalement, sur le papier, sur un ordinateur, ou dans une zone(un domaine) prédéterminée qui exige qu'un candidat à l'évaluation démontre ou exécute un ensemble de compétences. Les évaluations varient dans le style, la rigueur et les exigences. Par exemple, dans une évaluation de livre fe

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Concepts associés (15)

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Séances de cours associées (4)

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Evaluating the Explainers: Black-Box Explainable Machine Learning for Student Success Prediction in MOOCs

Natasa Krco, Mirko Marras, Vinitra Swamy

Neural networks are ubiquitous in applied machine learning for education. Their pervasive success in predictive performance comes alongside a severe weakness, the lack of explainability of their decisions, especially relevant in human-centric fields. We implement five state-of-the-art methodologies for explaining black-box machine learning models (LIME, PermutationSHAP, KernelSHAP, DiCE, CEM) and examine the strengths of each approach on the downstream task of student performance prediction for five massive open online courses. Our experiments demonstrate that the families of explainers do not agree with each other on feature importance for the same Bidirectional LSTM models with the same representative set of students. We use Principal Component Analysis, Jensen-Shannon distance, and Spearman's rank-order correlation to quantitatively cross-examine explanations across methods and courses. Furthermore, we validate explainer performance across curriculum-based prerequisite relationships. Our results come to the concerning conclusion that the choice of explainer is an important decision and is in fact paramount to the interpretation of the predictive results, even more so than the course the model is trained on. Source code and models are released at http://github.com/epfl-ml4ed/evaluating-explainers.

2022

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Task-based evaluation of meeting browsers: from BET task elicitation to user behavior analysis

Andrei Popescu-Belis

This paper presents recent results of the application of the task-based Browser Evaluation Test (BET) to meeting browsers, that is, interfaces to multimodal databases of meeting recordings. The tasks were defined by browser-neutral BET observers. Two groups of human subjects used the Transcript-based Query and Browsing interface (TQB), and attempted to solve as many BET tasks – pairs of true/false statements to disambiguate – as possible in a fixed amount of time. Their performance was measured in terms of precision and speed. Results indicate that the browser’s annotation-based search functionality is frequently used, in particular the keyword search. A more detailed analysis of each test question for each participant confirms that despite considerable variation across strategies, the use of queries is correlated to successful performance.

2008

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This paper presents a methodology to compute an innovative density indicator of spatial events. The methodology is based on a modified Kernel Density Estimator (KDE) that operates along road networks, and named Network based Kernel Density Estimator (NetKDE). In this research, retail and service economic activities are projected on the road network whose edges are weighted by a set of centrality values calculated with a Multiple Centrality Assessment (MCA). First, this paper calculate a density indicator for the point pattern analysis on human activities in a network constrained environment. Then, this indicator is modified to evaluate network performance in term of centrality. The methodology is applied to the city of Barcelona to explore the potential of the approach on more than 11,000 network edges and 166,000 economic activities.

Springer-Verlag New York, Ms Ingrid Cunningham, 175 Fifth Ave, New York, Ny 10010 Usa2010

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