Results 1 - 4 of 4

Human algorithmic stability and human rademacher complexity

by Mehrnoosh Vahdat, Luca Oneto, Ro Ghio, Davide Anguita, Mathias Funk, Matthias Rauterberg - In Proc. of the European Symposium on Artificial Neural Networks (ESANN , 2015
"... Abstract. In Machine Learning (ML), the learning process of an algo-rithm given a set of evidences is studied via complexity measures. The way towards using ML complexity measures in the Human Learning (HL) domain has been paved by a previous study, which introduced Human Rademacher Complexity (HRC) ..."
Abstract - Cited by 2 (2 self) - Add to MetaCart
Abstract. In Machine Learning (ML), the learning process of an algo-rithm given a set of evidences is studied via complexity measures. The way towards using ML complexity measures in the Human Learning (HL) domain has been paved by a previous study, which introduced Human Rademacher Complexity (HRC): in this work, we introduce Human Algo-rithmic Stability (HAS). Exploratory experiments, performed on a group of students, show the superiority of HAS against HRC, since HAS allows grasping the nature and complexity of the task to learn. 1
(Show Context)

M.: Advances in learning analytics and educational data mining

by Mehrnoosh Vahdat, Ro Ghio, Luca Oneto, Davide Anguita, Mathias Funk, Matthias Rauterberg - In: European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning , 2015
"... Abstract. The growing interest in recent years towards Learning An-alytics (LA) and Educational Data Mining (EDM) has enabled novel ap-proaches and advancements in educational settings. The wide variety of research and practice in this context has enforced important possibilities and applications fr ..."
Abstract - Cited by 1 (1 self) - Add to MetaCart
Abstract. The growing interest in recent years towards Learning An-alytics (LA) and Educational Data Mining (EDM) has enabled novel ap-proaches and advancements in educational settings. The wide variety of research and practice in this context has enforced important possibilities and applications from adaptation and personalization of Technology En-hanced Learning (TEL) systems to improvement of instructional design and pedagogy choices based on students needs. LA and EDM play an im-portant role in enhancing learning processes by offering innovative methods of development and integration of more personalized, adaptive, and inter-active educational environments. This has motivated the organization of the ESANN 2015 Special Session in Advances in Learning Analytics and Educational Data Mining. Here, a review of research and practice in LA and EDM is presented accompanied by the most central methods, bene-fits, and challenges of the field. Additionally, this paper covers a review of novel contributions into the Special Session. 1
(Show Context)

Questions as data: illuminating the potential of learning analytics through questioning an emergent field

by Jon Mason , Weiqin Chen , Tore Hoel
"... Abstract In providing a meta-analysis of a series of workshop papers and questions arising on the emergent field of learning analytics, this paper contributes to the ongoing formation of a shared research agenda. The first ICCE Learning Analytics workshop in 2014 demonstrated the effectiveness of a ..."
Abstract - Add to MetaCart
Abstract In providing a meta-analysis of a series of workshop papers and questions arising on the emergent field of learning analytics, this paper contributes to the ongoing formation of a shared research agenda. The first ICCE Learning Analytics workshop in 2014 demonstrated the effectiveness of a focused questioning session for collecting relevant data beyond the content of the papers themselves. In December 2014, approximately 40 participants attended the workshop held in Nara, Japan, and contributed to the collection of open research questions. Six papers were presented covering topics including scope; interoperability standards; privacy and control of individual data, extracting data from learning content and processes; and the development of conceptual frameworks. These papers established a base from which the group generated a set of questions that invite further investigation. Utilising the first stage of the Question Formulation Technique, a pedagogical approach designed to stimulate student inquiry, a prominent finding from the workshop that questions emerging from focused inquiry provide a useful set of data in their own right. With an explicit workshop focus on learning analytics interoperability, this paper reports on the emergent issues identified in the workshop and the kinds of questions associated with each issue in the context of current research in the field of learning analytics. The study considers the complexity arising from the fact that data associated with learning is itself becoming a digital learning resource while also enabling analysis of learner behaviours and systems usage.
(Show Context)

The Influence of Virtual Learning Environments in Students' Performance

by Paulo Alves , Luísa Miranda , Carlos Morais , 2017
"... Abstract This paper focuses mainly on the relation between the use of a virtual learning environment (VLE) and students' performance. Therefore, virtual learning environments are characterised and a study is presented emphasising the frequency of access to a VLE and its relation with the stude ..."
Abstract - Add to MetaCart
Abstract This paper focuses mainly on the relation between the use of a virtual learning environment (VLE) and students' performance. Therefore, virtual learning environments are characterised and a study is presented emphasising the frequency of access to a VLE and its relation with the students' performance from a public higher education institution during the academic year of 2014-15. The main aim of this research work is to obtain indicators which may help understand relations between the use of VLEs and students' performance. Finding the frequency of access to the VLE and assessing the consequences of such use represent challenges to which teachers and researchers try to respond in order to know students better and consequently, develop strategies which meet their interests and needs. This study is mainly quantitative with descriptive features, involving data obtained from literature research and from experimental research using a sample of approximately 6300 undergraduates. The data was extracted from the VLE and student registration system databases using learning analytics procedures. The results show that there are relatively positive indicators regarding students' access to a virtual learning environment and the relation between such access and their performance.
(Show Context)