Evaluación de los Sistemas e-Learning: Estudio de las publicaciones realizadas en la Web Of Knowledge

El propósito de este estudio es analizar el crecimiento y desarrollo de la literatura sobre la evaluación de los sistemas e-Learning. La bibliografía publicada en 18 de las principales revistas de la base de datos ISI Web of Knowledge fue obtenida, de manera directa, a través de las palabras clave: “model”, “evaluation”, “e-Learning system”, con sus respectivos sinónimos. La información como autor, título, subtítulo, fuente, citas, etc., se registró en MS-Excel (2010) para su análisis e interpretación. El estudio encontró 127 artículos de esta temática, publicados en el período 2008-2012. Además, revela que el 2012 fue el año más prolífico, con 33 artículos. La revista más productiva es Computers & Education, con 15 artículos; se la puede considerar como una revista básica de consulta. Se encontró que Peter Shea y Temi Bidjerano, ambos de Estados Unidos, son los autores que más han publicado y realizado trabajos conjuntos. Podría ser una limitante del estudio que la información que se tomó fue restringida a un período de cinco años, tiempo que de manera general se acepta, en relación a la antigüedad de la producción bibliográfica. El documento proporciona información confiable y auténtica sobre el tema y es el primer estudio de este tipo

Evaluation of a Learning Analytics Application for Open edX Platform

Massive open online courses (MOOCs) have recently emerged as a revolution in education. Due to the huge amount of users, it is difficult for teachers to provide personalized instruction. Learning analytics computer applications have emerged as a solution. At present, MOOC platforms provide low support for learning analytics visualizations, and a challenge is to provide useful and effective visualization applications about the learning process. At this paper we review the learning analytics functionality of Open edX and make an overview of our learning analytics application ANALYSE. We present a usability and effectiveness evaluation of ANALYSE tool with 40 students taking a Design of Telematics Applications course. The survey obtained very positive results in a system usability scale (SUS) questionnaire (78.44/100) in terms of the usefulness of visualizations (3.68/5) and the effectiveness ratio (92/100) of the actions required for the respondents. Therefore, we can conclude that the implemented learning analytics application is usable and effective.Acknowledgements: This work has been supported by the "eMadrid" project (Regional Government of Madrid) under grant S2013/ICE-2715, the "RESET" project (Ministry of Economy and Competiveness) under grant RESET TIN2014-53199-C3-1-R and the European Erasmus+ SHEILA project under grant 562080-EPP-1-2015-BE-EPPKA3-PI-FORWARD

Interfaces adaptativas personalizadas para brindar recomendaciones en repositorios de objetos de aprendizaje

Context: There are many repositories that allow searching and retrieving learning objects, so a lot of learning resources can be accessed. However, it is required to improve the presentation and visualization of those learning resources considering the student’s preferences, needs, and cognitive features.Method: The aim of this paper is to incorporate a customized interface with an adaptive multi-agent system for learning objects recommendation from local and remote repositories based on the student’s cognitive profile.Results: The prototype validation was made through a case study in which the interface has adapted not only the presentation but the visualization of learning objects taking into account the student’s preferences, needs and cognitive features.Conclusions: We can conclude that personalized adaptive interfaces demonstrate their efficacy and represent a great contribution to e-learning environments since they modify in real time the visualization and presentation of educational resources using the student’s cognitive profile.Contexto: existen muchos repositorios de recursos educativos que permiten buscar y recuperar objetos de aprendizaje, de esta forma se puede tener acceso a millones de recursos educativos; sin embargo, se requiere mejorar la presentación, visualización y satisfacción de uso de dichos objetos de aprendizaje, teniendo en cuenta las preferencias y necesidades de los estudiantes.Método: el objetivo de este artículo es incorporar una interfaz adaptativa personalizada a un sistema multiagente con el fin de recomendar objetos de aprendizaje, desde repositorios locales y remotos utilizando el perfil cognitivo de los estudiantes.Resultados: la validación del prototipo se realizó a través de un caso de estudio en el cual la interfaz adaptó tanto la presentación como la visualización de los objetos de aprendizaje a través de las preferencias, necesidades y características de los estudiantes.Conclusiones: se puede concluir que las interfaces adaptativas personalizadas demuestran su eficacia y representan entonces un gran aporte en los entornos de e-learning, debido a que modifican en tiempo real la visualización y la presentación, teniendo en cuenta el perfil cognitivo del aprendiz

Enabling Context Aware Applications in Learning Environments

Master'sMASTER OF SCIENC

Knowledge driven approaches to e-learning recommendation.

Learners often have difficulty finding and retrieving relevant learning materials to support their learning goals because of two main challenges. The vocabulary learners use to describe their goals is different from that used by domain experts in teaching materials. This challenge causes a semantic gap. Learners lack sufficient knowledge about the domain they are trying to learn about, so are unable to assemble effective keywords that identify what they wish to learn. This problem presents an intent gap. The work presented in this thesis focuses on addressing the semantic and intent gaps that learners face during an e-Learning recommendation task. The semantic gap is addressed by introducing a method that automatically creates background knowledge in the form of a set of rich learning-focused concepts related to the selected learning domain. The knowledge of teaching experts contained in e-Books is used as a guide to identify important domain concepts. The concepts represent important topics that learners should be interested in. An approach is developed which leverages the concept vocabulary for representing learning materials and this influences retrieval during the recommendation of new learning materials. The effectiveness of our approach is evaluated on a dataset of Machine Learning and Data Mining papers, and our approach outperforms benchmark methods. The results confirm that incorporating background knowledge into the representation of learning materials provides a shared vocabulary for experts and learners, and this enables the recommendation of relevant materials. We address the intent gap by developing an approach which leverages the background knowledge to identify important learning concepts that are employed for refining learners' queries. This approach enables us to automatically identify concepts that are similar to queries, and take advantage of distinctive concept terms for refining learners' queries. Using the refined query allows the search to focus on documents that contain topics which are relevant to the learner. An e-Learning recommender system is developed to evaluate the success of our approach using a collection of learner queries and a dataset of Machine Learning and Data Mining learning materials. Users with different levels of expertise are employed for the evaluation. Results from experts, competent users and beginners all showed that using our method produced documents that were consistently more relevant to learners than when the standard method was used. The results show the benefits in using our knowledge driven approaches to help learners find relevant learning materials

Participation and Experiences of Reclassified English Language Learners in a Learning Management System

abstract: In this study, I investigate how secondary reclassified ELLs use the Learning Management System Schoology in three secondary English classrooms. Particularly, I focus on the digital literacy practices reclassified ELLs use as they navigate Schoology to complete a multi-page research paper. In examining the digital literacy practices of secondary reclassified ELLs who have recently exited the language development program, I add to research in the fields of New Literacies and Multiliteracies, sociocultural approaches to learning, and identity studies. In this qualitative study, I employed ethnographic techniques (i.e., data collection, participant observation, interviewing, and collection of archived material and digital artifacts stored in Schoology). I drew from communities of practice and identity frameworks to examine focal participants' literacy practices when participating in the online space of Schoology and provided screenshots to showcase this participation. I examined email exchanges that were co-created by teacher and student that demonstrated their reliance on a digital tool to continue the teaching and learning processes. I exhibit screenshots of focal participants' engagement with the revision process as they used Schoology’s and Microsoft Word's digital editing tools. Finally, I examined focal participants' participation in Schoology's online discussion forum to highlight how they revealed aspects of their identities and performed these identities in a mainstream-learning environment as well. My analysis establishes that focal participants' access to an LMS like Schoology and other digital spaces (e.g., email) supports the language learning and literacy practices of reclassified ELLs. In addition, my analysis of focal participants' digital and communication practices shows that they contributed to their agency, positioned themselves as empowered and knowledgeable learners, and performed the role of "peer as mentor" when providing feedback to their peers. Finally, in my analysis of focal participants' inventories of digital literacy practices, I discovered that their engagement in Schoology for the purposes of learning and communication reinforced their language learning, both traditional and digital literacies, and overall academic achievement. Findings of this study emphasizes the importance of technology integration at the secondary level so that all students have equal access to digital and multimodal ways of learning in today's digital age.Dissertation/ThesisDoctoral Dissertation Curriculum and Instruction 201

Ontology-based personalisation of e-learning resources for disabled students

Students with disabilities are often expected to use e-learning systems to access learning materials but most systems do not provide appropriate adaptation or personalisation to meet their needs.The difficulties related to inadaptability of current learning environments can now be resolved using semantic web technologies such as web ontologies which have been successfully used to drive e-learning personalisation. Nevertheless, e-learning personalisation for students with disabilities has mainly targeted those with single disabilities such as dyslexia or visual impairment, often neglecting those with multiple disabilities due to the difficulty of designing for a combination of disabilities.This thesis argues that it is possible to personalise learning materials for learners with disabilities, including those with multiple disabilities. This is achieved by developing a model that allows the learning environment to present the student with learning materials in suitable formats while considering their disability and learning needs through an ontology-driven and disability-aware personalised e-learning system model (ONTODAPS). A disability ontology known as the Abilities and Disabilities Ontology for Online LEarning and Services (ADOOLES) is developed and used to drive this model. To test the above hypothesis, some case studies are employed to show how the model functions for various individuals with and without disabilities and then the implemented visual interface is experimentally evaluated by eighteen students with disabilities and heuristically by ten lecturers. The results are collected and statistically analysed.The results obtained confirm the above hypothesis and suggest that ONTODAPS can be effectively employed to personalise learning and to manage learning resources. The student participants found that ONTODAPS could aid their learning experience and all agreed that they would like to use this functionality in an existing learning environment. The results also suggest that ONTODAPS provides a platform where students with disabilities can have equivalent learning experience with their peers without disabilities. For the results to be generalised, this study could be extended through further experiments with more diverse groups of students with disabilities and across multiple educational institutions