M. Elena Rodríguez

Extending Learning Objects by Means of Social Networking

Learning objects have been the promise of providing people with high quality learning resources. Initiatives such as MIT OpenCourseWare, MERLOT and others have shown the real possibilities of creating and sharing knowledge through Internet. Thousands of educational resources are available through learning object repositories. We indeed live in an age of content abundance, and content can be considered as infrastructure for building adaptive and personalized learning paths, promoting both formal and informal learning. Nevertheless, although most educational institutions are adopting a more open approach, publishing huge amounts of educational resources, the reality is that these resources are barely used in other educational contexts. This paradox can be partly explained by the difficulties in adapting such resources with respect to language, e-learning standards and specifications and, finally, granularity. Furthermore, if we want our learners to use and take advantage of learning object repositories, we need to provide them with additional services than just browsing and searching for resources. Social networks can be a first step towards creating an open social community of learning around a topic or a subject. In this paper we discuss and analyze the process of using a learning object repository and building a social network on the top of it, with respect to the information architecture needed to capture and store the interaction between learners and resources in form of learning object metadata

Clarifying the Semantics of Relationships between Learning Objects

In this paper we discuss about the ambiguities and deficiencies of the Learning Object Metadata (LOM) standard to specify relationships between learning objects (LOs), specially those relationships that relate LOs instances. We also study the impact of relationships in the internal organizational structure of LOs. As main contribution, we develop a taxonomy of possible relationships between LOs that has been created by refining the LOM standard relationships with other meaningful relationships from a common sense ontology.

Towards an Adaptive e-Assessment System Based on Trustworthiness

Adaptive systems aim to deliver personalized resources and activities based on the competences and knowledge the learner has to acquire. Feedback provided by the assessment activities helps to evaluate the next step in the formative process of the learner. However, classical approaches do not take into account other evidences to select the further formative process. In this chapter, we focus on the adaptive e-assessment systems needed to select the next assessment activity to be deployed. In addition to help the learner to acquire knowledge, a trust-based e-assessment system is proposed to ensure a secure environment and authorship validation in online and blended learning environments while avoiding the time and physical space limitations imposed by face-to-face examination.

A learner profile analysis based on competences to improve online teaching strategies

European Universities are developing Bachelor degrees according the European Higher Education Area which focuses on the acquisition of a set of cross curricula and specific competences. The educational models are now centered on activities as a means for learners to achieve new competences improving their performance and skills. The purpose of this article is to analyze the online learner profile, through an initial assessment, in order to know if there is a gap between the expected competences and the real ones. This study focuses on some online courses with a set of specific Computer Engineering competences related to Math, Logic and Programming. Using a mixed methodology that combines a qualitative and quantitative data, the online learner profile is analyzed. The paper provides a detailed description about findings, seeking causes and providing guidelines, for improving the learning process based on competences. To conclude, it is introduced some recommendations and learning strategies to teachers in order to reduce the gap.

Engagement Analytics: A Microlevel Approach to Measure and Visualize Student Engagement

Learner disengagement is a persisting issue in the Science Technology Engineering and Mathematics (STEM) subjects. Student engagement is dynamically constituted by the behavioural, cognitive and emotional dimensions of engagement in a learning environment. Although strongly linked with academic achievement, much of the details of engagement becomes lost in a retrospective measurement. Timely and microlevel data on the other hand has the ability to enrich the traditional learning analytics dataset. From a pilot study carried out at Universitat Oberta de Catalunya, where we have designed a self-reported data capture module that collects microlevel engagement data, initial results suggest the validity of the proposed approach and data. In this paper we emphasize how our approach enables better understanding of the student learning process and their characteristics such as cognitive patterns, emotional states and behaviours that leads to academic success and also enable richer feedback from teachers and informed decision making by the institution.

Assuring Authorship and Authentication Across the e-Assessment Process

As the virtualisation of Higher Education increases, a challenge is growing regarding the use of reliable technologies in blended and on-line learning. Continuous evaluation is being combined with final face-to-face examinations aiming to ensure students’ identity. This collides with some universities’ principles, such as: flexibility, mobility or accessibility. Thus, it is necessary to develop an e-assessment system to fully virtually assess students and to help teachers to prevent and detect from illegitimate behaviours (i.e. cheating and plagiarism).

Towards a General Adaptive e-Assessment System

Assessment is an important part of the learning process. The instructor should be able to evaluate whether a learner has acquired the knowledge and competences provided in the course. Moreover, assessment activities also help a learner to check his level of expertise. Typically, the assessment model and assessment activities of subjects in official programmes are the same for all the learners, since they should be evaluated having the same opportunities and conditions. However, when the learner is evaluated by means of a continuous assessment model, he is proving on each activity his knowledge and proficiency level and, at the same time, his reputation could be also built based on the actions he is performing within the course. Therefore, the assessment model can be adapted based on this information. In this paper, we present a general system to adapt the assessment based on different evidences gathered from the learning process of the learner.

A Technology Enhanced Assessment System for Skill and Knowledge Learning

This paper presents a technology-enhanced assessment system that can be used for both skill and knowledge learning. For this purpose, a general technology-enhanced assessment system is designed and developed for an online logic course at a fully online university, taking into account e-learning standards and specifications, which can be easily adapted to any institute and subject requiring a high level of skill learning. Through this system, both learning and formative assessment facilities are provided to students. To evaluate its effects on student learning process, the system is applied in a real logic course at the Universitat Oberta de Catalunya (UOC). Based on the evaluation, it shows that students� are more engaged with the system and, as a result, their performance in the subject had improved. Also, based on the feedback obtained through the evaluation, it shows that students are satisfied with the facilities and assessments provided by the system. Overall, the introduction of the technology-enhanced assessment system for skill and knowledge learning has yielded some interesting results.

Understanding User Engagement in Digital Education.

Engagement is a crucial goal in both interactive system design and education. Whereas engagement in digital systems are based on concepts such as immersion and user experience, engagement in education is described in three dimensions of behavioral, cognitive and emotional engagements. In this paper a research approach to understand user engagement in digital education is presented. The approach is based on a microlevel student engagement measurement that takes into account engagement in HCI and also in e-learning, facing the challenge of integrating the two points of view. The research followed an action research methodology which emphasizes investigation and improvement of a real-world situation with iterative plan-act-reflect cycles. The approach was tested in a fully online university where we designed and developed a module for capturing engagement data. The results show that user engagement can be captured in online educational settings providing a useful and actionable understanding of user engagement in digital education.

Using an Intelligent Tutoring System with Plagiarism Detection to Enhance e-Assessment

Nowadays, online learning has become a promising solution to personalize and increase flexibility in the learning-teaching process. However, e-assessment is still questioned in terms of authorship and identity checking. Some virtual learning environments are introducing technological solutions, such as plagiarism detection tools, to increase the security when submitting assessment activities. However, this is a partial solution. When the activities are performed on third-party tools, as it is the case of intelligent tutoring systems, the identity and authorship checking can fail. This paper introduces a modular plagiarism detection tool that combines different input data sources in order to verify the authorship. A case study is presented to show the potential of the tool.