Ana-Elena Guerrero-Roldán

Virtual Laboratory ontology for engineering education

Virtual laboratories are an indispensable space for developing practical activities in a virtual environment. In the field of computer and software engineering different types of practical activities have to be performed in order to obtain basic competences which are impossible to achieve by other means. This paper specifies an ontology for a general virtual laboratory. The proposed ontology provides a mechanism to select the best resources needed in a virtual laboratory once a specific practical activity has been defined and the main competences that students have to achieve in the learning process have been fixed. Furthermore, the proposed ontology can be used to develop an automatic and wizard tool that creates a Moodle classroom using the practical activity specification and the related competences.

A Virtual Laboratory Structure for Developing Programming Labs

Virtual Laboratories in a Virtual Learning Environment are indispensable spaces for developing practical activities. This paper proposes an integrated structure for Virtual Laboratories for undergraduate degree programmes in Computer Engineering and Software Engineering. The general structure proposed is based on the experience gained in designing and developing Virtual Laboratories during the past eleven years in a virtual university. Technological, pedagogical, strategic and academic staff resources are included in the Virtual Laboratories structure. The proposed structure has been applied to different computer areas and this paper presents the special case of a Virtual Programming Laboratory. Its effectiveness has been evaluated by the students using a web questionnaire.

User Centered Design of a Learning Object Repository

This work outlines the design process of a user centered learning object repository. A repository should foster the development and acquisition of both generic and specific informational competencies. The results of the first stage of the user centered design process are presented which provide a clear understanding of user and task requirements and the context of use. A user study was conducted using quantitative and qualitative methodologies. A qualitative approach was performed through the content analysis of 24 in-depth interviews achieved through a random stratified sampling method. Regarding the quantitative approach, more than 5 million student navigation sessions were processed in order to know the real information behavior accomplished in the virtual campus and more specifically all the services and resources used and the search actions carried out by users. Our aim is to achieve a thorough informational behavior analysis that involves access, treatment, integration, evaluation, creation and communication of information for learning purposes which will be useful for integrating learning object repositories in virtual learning environments.

A Behavioral Biometrics Based and Machine Learning Aided Framework for Academic Integrity in E-Assessment

The common approaches to academic integrity in the e-learning environment are resource-intensive and require technology and/or dedicated invigilation staff to monitor assessment activities. These approaches are observational and often external to the learning spaces where the majority of the instructional content resides. Authentic assessments such as discussions, projects and portfolios may not always undergo the same scrutiny as high-stakes examinations and therefore differ in the level of identity and authorship assurance they provide. In this paper, we propose an integrated approach to enhancing academic integrity of e-assessments. The approach is based on behavioral biometrics and aided by machine-learning techniques. It provides continuous identity and authorship assurance throughout the learning activities within the existing learning space. It can be applied to measure the degree of learner collaboration with peers and interaction with the course content, concurrently verifying learner identity and validating authorship of the academic artifacts. We present the preliminary results and discuss future directions.

Designing Learning Tools: The Case of a Competence Assessment Tool

Advancements in technology offer new challenges and opportunities for online education. The interaction design of digital learning and assessment tools directly influence the learning experience. The aim of this work is to show the process of user-centered design and development of an online assessment tool that allows setting, monitoring and displaying the achievements of educational skills and competences. The main challenges addressed were: dealing with a rich and complex educational context; researching the actual needs of the actors involved and managing the different requirements for the tool; the process to generate design solutions and the evaluation of the tool. It was evaluated in a real case scenario in a virtual learning environment of a fully online higher education institution.

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.

Open Proctor: An Academic Integrity Tool for the Open Learning Environment

Managing integrity of continuous and authentic assessments in an open and distance environments is a complex process. The core challenge is to map student identities with their academic work in effective and efficient manners, while preserving privacy, ensuring minimal disruption, minimizing impacts on accessibility and convenience. To address this issue, we have developed a prototype cloud-based application entitled OpenProctor that employs machine-learning techniques to analyze patterns in the learner-produced textual content in order to provide identity and authorship assurance. In contrast to the traditional academic integrity approaches that seek to control the remote learning environment, our method takes advantage of the readily available learner-generated data to analyze how the students go about doing their academic work. We present the framework, the architecture and main functions of the OpenProctor system and discuss the future research directions and plans for the system’s future development.

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.