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Text mining in education
(Wiley, 2019)
The explosive growth of online education environments is generating a massive volume of data, specially in text format from forums, chats, social networks, assessments, essays, among others. It produces exciting challenges ...
Subgroup Discovery in MOOCs: A Big Data Application for Describing Different Types of Learners
(Taylor & Francis, 2019)
The aim of this paper is to categorize and describe di erent types of learners in mas-
sive open online courses (MOOCs) by means of a subgroup discovery approach based
on MapReduce. The nal objective is to discover ...
The use of artificial intelligence for sign language recognition in education: from a literature overview to the ISENSE project
(IEEE, 2023)
Common strategies to guarantee the inclusion of
d/Deaf students in university are still absent. Recent studies
have demonstrated how innovative technologies, such as
artificial intelligence and virtual/augmented reality, ...
Multi-source and multimodal data fusion for predicting academic performance in blended learning university courses
(Elsevier, 2021)
In this paper we apply data fusion approaches for predicting the final academic performance of university students using multiple-source, multimodal data from blended learning environments. We collect and preprocess data ...
Educational data mining and learning analytics: An updated survey
(Wiley, 2020)
This survey is an updated and improved version of the previous one published
in 2013 in this journal with the title “data mining in education”. It reviews in a
comprehensible and very general way how Educational Data ...
Artificial intelligence to automate the systematic review of scientific literature
(Springer, 2023)
Artificial intelligence (AI) has acquired notorious relevance in modern computing as it effectively solves complex tasks traditionally done by humans. AI provides methods to represent and infer knowledge, efficiently ...
A case-study comparison of machine learning approaches for predicting student’s dropout from multiple online educational entities
(MDPI, 2023)
Predicting student dropout is a crucial task in online education. Traditionally, each educational entity (institution, university, faculty, department, etc.) creates and uses its own prediction model starting from its own ...
A Taxonomy of Information Attributes for Test Case Prioritisation: Applicability, Machine Learning
(Association for Computing Machinery, 2023)
Most software companies have extensive test suites and re-run parts of them continuously to ensure recent changes have no adverse effects. Since test suites are costly to execute, industry needs methods for test case ...
A holographic mobile-based application for practicing pronunciation of basic English vocabulary for Spanish speaking children
(Elsevier, 2019)
This paper describes a holographic mobile-based application designed to help Spanish-speaking children to practice the pronunciation of basic English vocabulary words. The mastery of vocabulary is a fundamental step when ...
Process mining for self-regulated learning assessment in e-learning
(Springer, 2020)
Content assessment has broadly improved in e-learning scenarios in recent decades. However, the eLearning process can give rise to a spatial and temporal gap that poses interesting challenges for assessment of not only ...