Profiling students’ self-regulation with learning analytics: a proof of concept

The ability to regulate one's own learning processes is a key factor in educational scenarios. Self-regulation skills notably affect students' ef cacy when studying and academic performance, for better orworse. However, neither students or instructors generally have proper understanding of what self-regulated learning is, the impact that it has or how to assess it. This paper has the purpose of showing how learning analytics can be used in order to generate simple metrics related to several areas of students' selfregulation, in the context of a rst-year university course. These metrics are based on data obtained from a learning management system, complemented by more speci c assessment-related data and direct answers to self-regulated learning questionnaires. As the end result, simple self-regulation pro les are obtained for each student, which can be used to identify strengths and weaknesses and, potentially, help struggling students to improve their learning habits.Xunta de Galicia | Ref. ED431B 2020/3

Monitoring students’ self-regulation as a basis for an early warning system

Among the elements that determine a student’s academic success, their ability to regulate their own learning processes is an important, yet typically underrated factor. It is possible for students to improve their self-regulated learning skills, even at university levels. However, they are often unaware of their own behavior. Moreover, instructors are usually not prepared to assess students’ self-regulation. This paper presents a learning analytics solution which focuses on rating selfregulation skills, separated in several different categories, using activity and performance data from a LMS, as well as self-reported student data via questionnaires. It is implemented as an early warning system, offering the possibility of detecting students whose poor SRL profile puts them at risk of academic underperformance. As of the date of this writing, this is still a work in progress, and is being tested in the context of a first year college engineering course

Predictors and early warning systems in higher education: a systematic literature review

The topic of predictive algorithms is often regarded among the most relevant fields of study within the data analytics discipline. Nowadays, these algorithms are widely used by entrepreneurs and researchers alike, having practical applications in a broad variety of contexts, such as in finance, marketing or healthcare. One of such contexts is the educational field, where the development and implementation of learning technologies led to the birth and popularization of computerbased and blended learning. Consequently, student-related data has become easier to collect. This Research Full Paper presents a literature review on predictive algorithms applied to higher education contexts, with special attention to early warning systems (EWS): tools that are typically used to analyze future risks such as a student failing or dropping a course, and that are able to send alerts to instructors or students themselves before these events can happen. Results of using predictors and EWS in real academic scenarios are also highlighted

Supporting intensive continuous assessment with BeA in a flipped classroom experience

This paper presents the changes performed in a university course to adopt European Higher Education Area principles taking advantage of new technologies and educational approaches. Particularly, a Flipped Classroom model that also involves an Intensive Continuous Assessment approach is adopted, moving the presentation of theoretical contents to videos that can be watched outside of the classroom and using the classroom face-to-face time to provide explanations, problem solving and to perform assessment activities every week. A main part of innovation in the experience comes from the use of an online tool (BeA - Blended e-Assessment) that facilitates the assessment and reviewing of paper-based exams. This tool supports teachers in assessment tasks, that can be performed in a faster, simpler, more transparent and less error-prone way. The paper shows the results of an experience involving a control group and an experimentation group, in which this new approach and tool have been applied. The results obtained demonstrate the effectiveness of both proposals. In conjunction, the paper describes how a traditional university course based on lectures can be successfully adapted to a more innovative approach based on the principles of active learning and accountability thanks to the use of our blended e-Assessment tool.Xunta de Galicia | Ref. ED431B 2017/67Xunta de Galicia | Ref. ED431D 2017/12Ministerio de Economía, Industria y Competitividad | Ref. TIN2016-80515-

Exploring the synergies between gamification and data collection in higher education

In recent years, gamification techniques have been gaining popularity in all kind of educational scenarios, helping students improve their learning process by fostering engagement and attention. Implementing gamification aspects in a course can also provide an opportunity to gather student data that would not have been available otherwise. This paper describes a data gathering process in the context of a university course, as a work-in-progress. Among these data there is information regarding the participation of students in quizzes presented as games in the classroom. These quizzes combined questions covering course con-tents, as well as some regarding self-regulated learning habits. The main advantage observed was a high student participation in the quizzes. As a result, this gamification approach proved to be a more effective way to gather student data compared to other methods applied in previous academic years, which often failed due to many students ignoring optional activities.Xunta de Galicia | Ref. ED431B 2020/3

Adding TQ-BOT into a Third-party Learning Management System

Intelligent Tutoring Systems are computer programs that aim at providing personalized instruction to students. In recent years, artificial intelligence conversational robots, usually known as chatterbots, have become very popular in the Internet. In this paper we show how chatterbots can be integrated in e-Learning Systems. To perform such an integration the Service Oriented Architecture paradigm is adopted and e-learning standardization initiatives are considered. A middleware is provided to enable the integration and reuse of chatterbots by e-Learning systems enabling a tight control of their operation. Such middleware takes to account several issues such as authorising users, creating instances, transferring data to and from the chatterbot, assigning permissions to users, and subscribing to events. Our approach is applied to the specific case of TQ-Bot, which is use to track and supervise the student progress and to provide answers orienting the student to the more appropriate course contents

Arquitectura de ordenadores: ejercicios prácticos de ARM-Thumb

La arquitectura ARM, desarrollada hace más de 35 años, está presente en la actualidad en miles de millones de dispositivos, desde Fugaku, el superordenador japonés líder del ranking de los ordenadores más potentes del mundo en 2020, hasta el Catweazle Mini, un femtocomputador de poco más de 0,25 centímetros cúbicos de volumen. Thumb es una versión reducida de ARM en la que la mayoría de las instrucciones ocupan 16 bits, y está orientada fundamentalmente al desarrollo de dispositivos embebidos, como por ejemplo los dispositivos para controlar un ascensor, un electrodoméstico, determinadas funciones de un automóvil, y en general cualquier dispositivo del ámbito del Internet de las Cosas. El presente libro está basado en las clases prácticas y exámenes prácticos que los autores han ido preparando a lo largo de más de veinte años de experiencia impartiendo las asignaturas de arquitectura de ordenadores en los diversos planes de estudio de la Escuela de Ingeniería de Telecomunicación de la Universidade de Vigo

Generating OER by recording lectures : a case study

The University of Vigo, Vigo, Spain, has the objective of making all the teaching material generated by its teachers freely available. To attain this objective, it encourages the development of Open Educational Resources, especially videos. This paper presents an experience of recording lectures and generating the corresponding videos as a step toward this objective. The core system used to record lectures is Opencast Matterhorn (free and open-source customizable software to support the management of educational audio and video content). This paper also focuses on the study and analysis of the students' experience of using recorded videos as support for their learning process. This case study was carried out in the Fall 2012 offering of the first-year Computer Architecture course in the University of Vigo's Telecommunication Technologies Engineering program. Finally, the paper addresses students' level of satisfaction with the recorded lectures and gives students' opinions on the use of these videos.Ministerio de Ciencia e Innovación | Ref. TIN2010-21735-C02-01AECID | Ref. A2/042374/11Ministerio de Ciencia e Innovación | Ref. TIN2010-21735-C02-0

Systematic literature review of predictive analysis tools in higher education

The topic of predictive algorithms is often regarded among the most relevant fields of study within the data analytics discipline. They have applications in multiple contexts, education being an important one of them. Focusing on higher education scenarios, most notably universities, predictive analysis techniques are present in studies that estimate academic outcomes using different kinds of student-related data. Furthermore, predictive algorithms are the basis of tools such as early warning systems (EWS): applications able to foresee future risks, such as the likelihood of students failing or dropping out of a course, and alert of such risks so that corrective measures can be taken. The purpose of this literature review is to provide an overview of the current state of research activity regarding predictive analytics in higher education, highlighting the most relevant instances of predictors and EWS that have been used in practice. The PRISMA guidelines for systematic literature reviews were followed in this study. The document search process yielded 1382 results, out of which 26 applications were selected as relevant examples of predictors and EWS, each of them defined by the contexts where they were applied and the data that they used. However, one common shortcoming is that they are usually applied in limited scenarios, such as a single course, evidencing that building a predictive application able to work well under different teaching and learning methodologies is an arduous task.Departamento de Educación da Xunta de Galicia | Ref. (TIN2016-80515-R AEI / EFRD, UE)Agencia Estatal de Investigaciones | Ref. (TIN2016-80515-R AEI / EFRD, UE)European Regional Development Fund (ERDF) | Ref. (TIN2016-80515-R AEI / EFRD, UE

A systematic review of commercial smart gloves: current status and applications

Smart gloves have been under development during the last 40 years to support human-computer interaction based on hand and finger movement. Despite the many devoted efforts and the multiple advances in related areas, these devices have not become mainstream yet. Nevertheless, during recent years, new devices with improved features have appeared, being used for research purposes too. This paper provides a review of current commercial smart gloves focusing on three main capabilities: (i) hand and finger pose estimation and motion tracking, (ii) kinesthetic feedback, and (iii) tactile feedback. For the first capability, a detailed reference model of the hand and finger basic movements (known as degrees of freedom) is proposed. Based on the PRISMA guidelines for systematic reviews for the period 2015–2021, 24 commercial smart gloves have been identified, while many others have been discarded because they did not meet the inclusion criteria: currently active commercial and fully portable smart gloves providing some of the three main capabilities for the whole hand. The paper reviews the technologies involved, main applications and it discusses about the current state of development. Reference models to support end users and researchers comparing and selecting the most appropriate devices are identified as a key need