Search results for "Learning Analytics"

showing 3 items of 33 documents

Framework for pedagogical learning analytics

2018

Learning analytics is an emergent technological practice and a multidisciplinary scientific discipline, which goal is to facilitate effective learning and knowledge of learning. In this design science research, I combine knowledge discovery process, a concept of pedagogical knowledge, ethics of learning analytics and microservice architecture. The result is a framework for pedagogical learning analytics. The framework is applied and evaluated in the context of agency analytics. The framework contributes to the practical use of learning analytics.

microserviceknowledge discoverypedagogical learning analyticsstudent agencypedagogical knowledgeGDPRethics
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Enriching Didactic Similarity Measures of Concept Maps by a Deep Learning Based Approach

2021

Concept maps are significant tools able to support several tasks in the educational area such as curriculum design, knowledge organization and modeling, students' assessment and many others. They are also successfully used in learning activities in which students have to represent domain knowledge according to teacher's assignment. In this context, the development of Learning Analytics approaches would benefit of methods that automatically compare concept maps. Detecting concept maps similarities is relevant to identify how the same concepts are used in different knowledge representations. Algorithms for comparing graphs have been extensively studied in the literature, but they do not appea…

Information retrievalLearning AnalyticKnowledge representation and reasoningComputer scienceConcept mapKnowledge organizationLearning analyticsContext (language use)SemanticsLearning AnalyticsConcept MapConcept MapsDeep LearningInfersentSimilarity (psychology)Semantic Similarity MeasuresDomain knowledgeNatural Language Processing
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Intelligent Knowledge Understanding from Students Questionnaires: A Case Study

2022

Learning Analytics techniques are widely used to improve students’ performance. Data collected from students’ assessments are helpful to predict their success and questionnaires are extensively adopted to assess students’ knowledge. Several mathematical models studying the correlation between students’ hidden skills and their performance to questionnaires’ items have been introduced. Among them, Non-negative matrix factorizations (NMFs) have been proven to be effective in automatically extracting hidden skills, a time-consuming activity that is usually tackled manually prone to subjective interpretations. In this paper, we present an intelligent data analysis approach based upon NMF. Data a…

QuestionnairesSettore INF/01 - InformaticaLatent skillsNon-negative matrix factorizationLearning analytics
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