Machine Learning applications to e-learning courses

The Ph.D. thesis project is aimed at improving the quality and the effectiveness of on-line teaching in scientific degree courses at the University Level that required the use of E-learning platform, based on the Moodle Content Management System. The aim of this research project is to assist the teacher, through the development of new tools based on Artificial Intelligence, to design innovative successful e-learning courses to give to the students the opportunity to improve their learning outcomes. These originals tools overcome the limitations of the standard Moodle activities applying machine learning techniques by analysing large amount of students’ data extracted by Moodle log data. Recently many e-learning resources have been developed for university students, are available on the Web. The increase of LMS (Learning Management System) as Moodle and their ease of use led many teachers to realize e-learning paths for their students, often supporting them with some frontal activities, giving to them the advantages of on-line learning. The aim was to deepen the topics discussed in class through the consultation of additional materials, video recordings of lessons, and other activities to exploiting the potentials of on-line courses

Adaptive and cooperative model of knowledge management in MOOCs

One of the characteristics of Massive Open Online Courses (MOOC) is the heterogeneity of their participants’ profiles and, for the most traditional MOOC model, this is an important cause of the low completion rate. The MOOC model presents two apparent antagonistic concepts, globalization and diversity. MOOCs represent globalization (participants have to be adapted to the course) and their participants represent diversity. The authors of this paper argue that both concepts complement each other; that is, a MOOC can adapt the contents and navigation to the diversity of participants; and in turn the participants themselves can increase and improve the contents of the MOOC, through heterogeneous cooperation, to encourage massive learning. To proof it, this paper presents a new model, called ahMOOC, combining the hybrid-MOOC (hMOOC) and the adaptive MOOC (aMOOC). The hMOOC allows integrating characteristics of xMOOCs (based on formal e-training) with cMOOCs (based on informal and cooperative e-training). The aMOOC offers different learning strategies adapted to different learning objectives, profiles, learning styles, etc. of participants. The ahMOOCs continues having a lower dropout rate (such as hMOOC) than the traditional MOOCs. The qualitative analysis show the capacity of participants, with heterogeneous profiles, to create, in a cooperative and massive way, useful knowledge to improve the course and, later, to apply it in their specific work context. The study also shows that participants have a good perception on the capabilities of the ahMOOC to adapt the learning process to their profiles and preferences

Extending MOOC ecosystems using web services and software architectures

[EN]This paper present a research project that tries to extend the MOOC ecosystems by integrating external tools like social networks. This integration is developed by using a software architecture that mediate between the different systems and platforms establishing communication workflows and analyzing the information retrieved. This kind of system is applied in a real case, and it allows teachers and managers of the MOOC platform to get enhanced information and insights about users interaction with contents and MOOC tools, as well as some metrics impossible to retrieve or calculate manually in this kind of eLearning platforms with high amounts of users

Adapting e-learning and learning services for people with disabilities

Providing learning materials and support services that are adapted to the needs of individuals has the potential to enable learners to obtain maximal benefit from university level studies. This paper describes EU4ALL project which has been exploring how to present customized learning materials and services for people with disabilities. A number of the technical components of the EU4ALL framework are described. This is followed with a brief description of prototype implementations. This is then followed by a discussion of a number of research directions that may enhance the adaptability, usability and accessibility of information and support systems can be used and consumed by a diverse user population

Protected Users: A Moodle Plugin To Improve Confidentiality and Privacy Support through User Aliases

[EN]The privacy policies, terms, and conditions of use in any Learning Management System (LMS) are one-way contracts. The institution imposes clauses that the student can accept or decline. Students, once they accept conditions, should be able to exercise the rights granted by the General Data Protection Regulation (GDPR). However, students cannot object to data processing and public profiling because it would be conceived as an impediment to teachers to execute their work with normality. Nonetheless, regarding GDPR and consulted legal advisors, a student could claim identity anonymization in the LMS, if adequate personal justifications are provided. Per contra, the current LMSs do not have any functionality that enables identity anonymization. This is a big problem that generates undesired situations which urgently requires a definitive solution. In this work, we surveyed students and teachers to validate the feasibility and acceptance of using aliases to anonymize their identity in LMSs as a sustainable solution to the problem. Considering the positive results, we developed a user-friendly plugin for Moodle that enables students' identity anonymization by the use of aliases. This plugin, presented in this work and named Protected users, is publicly available online at GitHub and published under GNU General Public License

Facilitating collaborative learning in TaaS: a mobile cloud system for enhancing teamwork performance

Mobile cloud-based learning is a novel trend that brings many advantages to distributed learners to achieve collaborative learning, but it still lacks of mechanisms to enhance their teamwork performances. To make up that shortcoming, combining the features of cloud environment, we have identified a learning flow, a specification of workflow, based on Kolb team learning experience. This novel learning flow can be executed by our newly designed system, Teamwork as a Service (TaaS), in conjunction with cloud-hosting learning management systems, following which learners benefit from functions given by cloudbased services, separately for organizing cloud jigsaw classroom, planning and publishing tasks, rational task allocation and mutual supervision. We introduce a genetic algorithm method for grouping learners into appropriate teams, for two different scenarios of expectations for forming teams. Experimental results prove that our approach is workable to facilitate teamwork, while learners\u27 capabilities and preferences are being taken into consideration

Learning flexibility: the environment and a case study

This paper outlines the flexible student learning environment in the Faculty of Engineering and Surveying, before concentrating on evaluating one online learning option. This Faculty provides a variety of high quality on-campus, distance education and on-line academic programmes and various learning strategies for the heterogeneous student cohort (national and international). By accessing appropriate flexible learning and different learning experiences, students are empowered to determine learning opportunities and methodologies to suit their personal needs. The off-campus mode study may disadvantage students since they don’t have the benefit of face-to-face instructions or to participate in formative assessments delivered informally in lectures. This may lead to feelings of remoteness and isolation leading to poorer learning, lower results in assessments, and may also contribute to drop-out rates, particularly in first year courses. To overcome this inequity, the usual training materials presented for a first year course in 2005 were supplemented with PowerPoint lectures, enhanced with synchronous audio, and a series of quizzes to be used as formative assessments. The lectures and quizzes were presented online via a course web site and were designed to become an integral part of the learning experience. An evaluation of the effectiveness of these strategy demonstrated improved students' learning, a positive contribution to the learning experience, increased enjoyment of the course, and a strong learning motivator. Students reported feeling less disenfranchised with the university and having a greater affinity with the lecturer

Self Learning and self evaluation exercises database in basic mechanics: a theoretical-practical approach

In the School of Mines of the Technical University of Madrid (UPM) the first course of different degrees has been implemented and adapted to the European Higher Educational Area (EHEA). In all of the degrees there is a first semester course which gathers all the contents of basic mechanics: from the first kinematics concepts to the rigid solid plane motion Before the Bologna process took place, the authors had established the final assessment of the theoretical contents through open questions of theoretical-practical character In the present work, the elaboration of a wide database containing theoretical-practical questions that students can access on line is presented. The questions are divided in thirteen different questionnaires composed of a number of questions randomly chosen from a certain group in the database. Each group corresponds to a certain learning objective that the student knows. After answering the questionnaire and checking the grade assigned according to the performance of the student, the pupils can see the correct response displayed on the screen and widely explained by the professors. This represents a 10% of the final grade. As the student can access the questionnaires as many times as they want, the main goal is the self-assessment of each learning objective and therefore, getting the students involved in their own learning process so they can decide how much time they need to acquire the required level

SEMAG: A Novel Semantic-Agent Learning Recommendation Mechanism for Enhancing Learner-System Interaction

In this paper, we present SEMAG - a novel semantic-agent learning recommendation mechanism which utilizes the advantages of instructional Semantic Web rules and multi-agent technology, in order to build a competitive and interactive learning environment. Specifically, the recommendation-making process is contingent upon chapter-quiz results, as usual; but it also checks the students' understanding at topic-levels, through personalized questions generated instantly and dynamically by a knowledge-based algorithm. The learning space is spread to the social network, with the aim of increasing the interaction between students and the intelligent tutoring system. A field experiment was conducted in which the results indicated that the experimental group gained significant achievements, and thus it supports the use of SEMAG

How to design for persistence and retention in MOOCs?

Design of educational interventions is typically carried out following a design cycle involving phases of investigation, conceptualization, prototyping, implementation, execution and evaluation. This cycle can be applied at different levels of granularity e.g. learning activity, module, course or programme. In this paper we consider an aspect of learner behavior that can be critical to the success of many MOOCs i.e. their persistence to study, and the related theme of learner retention. We reflect on the impact that consideration of these can have on design decisions at different stages in the design cycle with the aim of en-hancing MOOC design in relation to learner persistence and retention, with particular attention to the European context