David Baneres

Experiences in Digital Circuit Design Courses: A Self-Study Platform for Learning Support

The synthesis of digital circuits is a basic skill in all the bachelor programmes around the ICT area of knowledge, such as Computer Science, Telecommunication Engineering or Electrical Engineering. An important hindrance in the learning process of this skill is that the existing educational tools for the design of circuits do not allow the student to validate if his design satisfies the specification. Furthermore, an automatic feedback is essential in order to help students to fix incorrect designs. In this paper, we propose an online platform where the students can design and verify their circuits with an individual and automatic feedback. The technical aspects of the platform and the designed verification tool are presented. The impact of the platform on the learning process of the students is illustrated by analyzing the student performance on the course where the platform has been used. Results on the utilization of the platform versus the success rate and marks in the final exam are presented and compared with previous semesters.

A Semi-automatic System to Detect Relevant Learning Content for Each Subject

Today, the crisis has worsened the panorama for Universities, placing new constraints that require being more sustainable economically. In addition, universities will also have to improve their research and teaching in order to obtain more research funds and attract more students. In this panorama, analytics can be a very useful tool since it allows academics (and university managers) to get a more thorough view of their context, to better understand the environment, and to identify potential improvements. Some analytics have been done under the names of Learning analytics, Academic analytics, Educational Data Mining and etcetera. However, these systems, under our humble opinion, only take into account the small part of data related to the problem, but not contextual data. In order to perform analytics efficiently and reproduce their results easily in other contexts, it is necessary to have as much information as possible about the context. For example, when communication forums are analyzed to see the concepts in which students have more doubts, it is important to analyze also what concepts are taught in the subject. Having access to both sources, more information can be obtained and may help to discover not only the problem (a concept is difficult for students) but also its cause (maybe it is not explained in the materials of the course). The work presented in the paper proposes a novel approach to work in that direction: gathering information from different aspects within subjects. In particular, the paper presents an approach that uses natural language processing techniques to analyze the subjects materials in order to discover which concepts are taught and their importance in the subject. The contribution of the paper is a system that allows obtaining a better understanding of subjects. The results can be used for analyzing the suitability of materials to subjects and to enrich and contextualize other analytical processes.

Layout-aware gate duplication and buffer insertion

An approach for layout-aware interconnect optimization is presented. It is based on the combination of three sub-problems into the same framework: gate duplication, buffer insertion and placement. Different techniques to control the combinatorial explosion are proposed. The experimental results show tangible benefits in delay that endorse the suitability of integrating the three sub-problems in the same framework. The results also corroborate the increasing relevance of interconnect optimization in future semiconductor technologies.

Dominator-based partitioning for delay optimization

Most of the logic synthesis algorithms are not scalable for large networks and, for this reason, partitioning is often applied. However traditional mincut-based partitioning techniques are not always suitable for delay and area logic optimizations. The paper presents an approach that uses a dominator-based partitioning and conventional logic synthesis techniques for delay optimization of large networks. The calculation of dominators is crucial to find topologically ordered clusters suitable for logic restructuring. As a result, a scalable and efficient strategy for delay optimization is proposed and evaluated, showing tangible improvements with respect to existing techniques. A comparison with a standard mincut-based partitioning technique is also presented.

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.

Towards an Analytical Framework to Enhance Teaching Support in Digital Systems Design Course

Learning digital systems design is a difficult skill that students of Bachelors on Computer Science, Electronic Engineering or Telecommunications have to acquire in the initial courses. The problem aggravates when the student is learning in a virtual environment with no face-to-face interaction with the instructor. In this case, simulators or intelligent tutoring systems, such as Veril UOC [1], are used in order to acquire this skill. This paper describes several improvements introduced in the instructor view of this framework Veril UOC. The new information that can be extracted of the system can improve the personalized feedback that the instructor can perform to the students, and, at the same time, the real-time information gives insights related to the courses operation.

ICT-FLAG: a web-based e-assessment platform featuring learning analytics and gamification

The purpose of this paper is to present an innovative web-based eLearning platform called ICT-FLAG that provides e-assessment tools with general-purpose formative assessment services featuring learning analytics and gamification.,The paper reports on the technical development of the platform driven by the Reference Model for Open Distributed Processing software methodology, which guides the platform construction, including the analysis and design steps.,The ICT-FLAG platform is technically tested by integrating it into a real e-assessment tool. Results are positive in terms of functional and non-functional aspects as well as user’s satisfaction on usability, emotional state, thus validating the platform as a valuable educational tool.,Because of the chosen technical paper as article type, validation of the impact of the ICT-FLAG platform in the learning process is not provided. Ongoing research with this platform is to measure the learning outcomes of its use in a real context of eLearning.,The paper shows implications of the main technical issues and challenges encountered during the integration of the ICT-FLAG platform with external eLearning tools, involving relevant aspects of interoperability, security, modularity, scalability, portability and so on.,This platform can fill the gap of many e-assessment systems, which currently do not have built-in analytical and gamification tools for learning, thus providing them with the experience to improve the quality of education and learning.

Towards a Learning Analytics Support for Intelligent Tutoring Systems on MOOC Platforms

Nowadays, many MOOC platforms have arisen to provide free knowledge. These platforms have a large catalog of courses for different specializations that progressively demand more specific learning resources and assessment methods to evaluate the progression of students. Current MOOC platforms are gradually giving support to these new requirements but with a limited assistance. This paper presents the state of art of the analytical system for three relevant MOOC platforms, one of the main pillars for analyzing the progression of courses. Other initiatives are also reviewed to show that current MOOC analytical systems are not ready to support custom MOOC-aware intelligent tutoring systems (ITSs). Thus, the design of a learning analytics system to assist these tools for MOOC platforms is presented.

Principles for an Effort-Aware System

Learners require a certain effort to acquire a specific skill or competence. The invested effort can be affected by many factors as previous knowledge, abilities or time available for learning. The evaluation of the effort has been mainly related to cognitive science or instructional psychology due to the relation between effort and mental work. This paper focuses on how the effort can be estimated on e-learning systems. This information can enhance instructional process since teachers can analyze the total time learners invest on acquiring knowledge and they can adjust better the complexity of the course. The paper contributes on principles to design an effort-based system. Finally, a particular application to an intelligent tutoring system is performed.

Intelligent Tutoring System for Learning Digital Systems on MOOC Environments

The number of Massive Open Online Courses (MOOCs) has increased exponentially in the last years in all areas of knowledge. Some of these courses require that the learner has to acquire practical skills. This is a challenge for a MOOC since scalable new methodologies and tools have to be developed to teach and assess these skills. This paper presents an intelligent tutoring system (ITS) adapted for a MOOC to learn digital systems design. Learning this skill has several difficulties mostly for novice learners in the area of Computer Science or Electronic Engineering specialties. The problem aggravates on virtual environments without face-to-face interaction with the instructor. ITSs are suitable for MOOC environments since they promote the self-learning process and they improve the support to personalized feedback.