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Discussion forums are a valuable source of information in educational platforms such as Massive Open Online Courses (MOOCs), as users can exchange opinions or even help other students in an asynchronous way, contributing to the sustainability of MOOCs even with low interaction from the instructor. Therefore, the use of the forum messages to get insights about students’ performance in a course is interesting. This article presents an automatic grading approach that can be used to assess learners through their interactions in the forum. The approach is based on the combination of three dimensions: (1) the quality of the content of the interactions, (2) the impact of the interactions, and (3) the user’s activity in the forum. The evaluation of the approach compares the assessment by experts with the automatic assessment obtaining a high accuracy of 0.8068 and Normalized Root Mean Square Error (NRMSE) of 0.1799, which outperforms previous existing approaches. Future research work can try to improve the automatic grading by the training of the indicators of the approach depending on the MOOCs or the combination with text mining techniques.
Raquel L. Pérez-Nicolás; Carlos Alario-Hoyos; Iria Estévez-Ayres; Pedro Manuel Moreno-Marcos; Pedro J. Muñoz-Merino; Carlos Delgado Kloos. Evaluation of an Algorithm for Automatic Grading of Forum Messages in MOOC Discussion Forums. Sustainability 2021, 13, 9364 .
AMA StyleRaquel L. Pérez-Nicolás, Carlos Alario-Hoyos, Iria Estévez-Ayres, Pedro Manuel Moreno-Marcos, Pedro J. Muñoz-Merino, Carlos Delgado Kloos. Evaluation of an Algorithm for Automatic Grading of Forum Messages in MOOC Discussion Forums. Sustainability. 2021; 13 (16):9364.
Chicago/Turabian StyleRaquel L. Pérez-Nicolás; Carlos Alario-Hoyos; Iria Estévez-Ayres; Pedro Manuel Moreno-Marcos; Pedro J. Muñoz-Merino; Carlos Delgado Kloos. 2021. "Evaluation of an Algorithm for Automatic Grading of Forum Messages in MOOC Discussion Forums." Sustainability 13, no. 16: 9364.
Selenium WebDriver is a framework used to control web browsers automatically. It provides a cross-browser Application Programming Interface (API) for different languages (e.g., Java, Python, or JavaScript) that allows automatic navigation, user impersonation, and verification of web applications. Internally, Selenium WebDriver makes use of the native automation support of each browser. Hence, a platform-dependent binary file (the so-called driver) must be placed between the Selenium WebDriver script and the browser to support this native communication. The management (i.e., download, setup, and maintenance) of these drivers is cumbersome for practitioners. This paper provides a complete methodology to automate this management process. Particularly, we present WebDriverManager, the reference tool implementing this methodology. WebDriverManager provides different execution methods: as a Java dependency, as a Command-Line Interface (CLI) tool, as a server, as a Docker container, and as a Java agent. To provide empirical validation of the proposed approach, we surveyed the WebDriverManager users. The aim of this study is twofold. First, we assessed the extent to which WebDriverManager is adopted and used. Second, we evaluated the WebDriverManager API following Clarke’s usability dimensions. A total of 148 participants worldwide completed this survey in 2020. The results show a remarkable assessment of the automation capabilities and API usability of WebDriverManager by Java users, but a scarce adoption for other languages.
Boni García; Mario Munoz-Organero; Carlos Alario-Hoyos; Carlos Delgado Kloos. Automated driver management for Selenium WebDriver. Empirical Software Engineering 2021, 26, 1 -51.
AMA StyleBoni García, Mario Munoz-Organero, Carlos Alario-Hoyos, Carlos Delgado Kloos. Automated driver management for Selenium WebDriver. Empirical Software Engineering. 2021; 26 (5):1-51.
Chicago/Turabian StyleBoni García; Mario Munoz-Organero; Carlos Alario-Hoyos; Carlos Delgado Kloos. 2021. "Automated driver management for Selenium WebDriver." Empirical Software Engineering 26, no. 5: 1-51.
This dataset contains the information from the forum of three MOOCs on programming (multiple editions) offered through the edX platform. These MOOCs are offered in the Spanish and English versions.
Carlos Alario-Hoyos. Dataset MOOC Forum edX. 2021, 1 .
AMA StyleCarlos Alario-Hoyos. Dataset MOOC Forum edX. . 2021; ():1.
Chicago/Turabian StyleCarlos Alario-Hoyos. 2021. "Dataset MOOC Forum edX." , no. : 1.
This dataset contains the information from the forum of three MOOCs on programming (multiple editions) offered through the edX platform. These MOOCs are offered in the Spanish and English versions.
Carlos Alario-Hoyos. Dataset MOOC Forum edX. 2021, 1 .
AMA StyleCarlos Alario-Hoyos. Dataset MOOC Forum edX. . 2021; ():1.
Chicago/Turabian StyleCarlos Alario-Hoyos. 2021. "Dataset MOOC Forum edX." , no. : 1.
Massive open online courses (MOOCs) pose a challenge for instructors when trying to provide personalised support to learners, due to large numbers of registered participants. Conversational agents can be of help to support learners when working with MOOCs. This article presents an adaptive learning module for JavaPAL, a conversational agent that complements a MOOC on Java programming, helping learners review the key concepts of the MOOC. This adaptive learning module adapts the difficulty of the questions provided to learners considering their level of knowledge using item response theory (IRT) and also provides recommendations of video fragments extracted from the MOOC for when learners fail questions. The adaptive learning module for JavaPAL has been evaluated showing good usability and learnability through the system usability scale (SUS), reasonably suitable video fragments recommendations for learners, and useful visualisations generated as part of the IRT-based adaptation of questions for instructors to better understand what is happening in the course, to design exams, and to redesign the course content.
Nuria González-Castro; Pedro J. Muñoz-Merino; Carlos Alario-Hoyos; Carlos Delgado Kloos. Adaptive learning module for a conversational agent to support MOOC learners. Australasian Journal of Educational Technology 2021, 37, 24 -44.
AMA StyleNuria González-Castro, Pedro J. Muñoz-Merino, Carlos Alario-Hoyos, Carlos Delgado Kloos. Adaptive learning module for a conversational agent to support MOOC learners. Australasian Journal of Educational Technology. 2021; 37 (2):24-44.
Chicago/Turabian StyleNuria González-Castro; Pedro J. Muñoz-Merino; Carlos Alario-Hoyos; Carlos Delgado Kloos. 2021. "Adaptive learning module for a conversational agent to support MOOC learners." Australasian Journal of Educational Technology 37, no. 2: 24-44.
Smart learning environments (SLEs) have gained considerable momentum in the last 20 years. The term SLE has emerged to encompass a set of recent trends in the field of educational technology, heavily influenced by the growing impact of technologies such as cloud services, mobile devices, and interconnected objects. However, the term SLE has been used inconsistently by the technology-enhanced learning (TEL) community, since different research works employ the adjective smart to refer to different aspects of novel learning environ- ments. Previous surveys on SLEs are narrowly focused on specific technologies, or remain at a theoretical level that does not discuss practical implications found in empirical studies. To address this inconsistency, and also to contribute to a common understanding of the SLE concept, this paper presents a systematic literature review (SLR) of papers published between 2000 and 2019 discussing SLEs in empirical studies. Sixty eight papers out of an initial list of 1,341 papers were analyzed to identify: 1) what affordances make a learning environment smart; 2) which technologies are used in SLEs; and 3) in what pedagogical contexts are SLEs used. Considering the limitations of previous surveys, and the inconsistent use of the SLE concept in the TEL community, this paper presents a comprehensive characterization
Bernardo Tabuenca; Sergio Serrano-Iglesias; Adrian Carruana-Martin; Cristina Villa-Torrano; Yannis A. Dimitriadis; Juan I. Asensio-Perez; Carlos Alario-Hoyos; Eduardo Gomez-Sanchez; Miguel L. Bote-Lorenzo; Alejandra Martinez-Mones; Carlos Delgado Kloos. Affordances and Core Functions of Smart Learning Environments: A Systematic Literature Review. IEEE Transactions on Learning Technologies 2021, PP, 1 -1.
AMA StyleBernardo Tabuenca, Sergio Serrano-Iglesias, Adrian Carruana-Martin, Cristina Villa-Torrano, Yannis A. Dimitriadis, Juan I. Asensio-Perez, Carlos Alario-Hoyos, Eduardo Gomez-Sanchez, Miguel L. Bote-Lorenzo, Alejandra Martinez-Mones, Carlos Delgado Kloos. Affordances and Core Functions of Smart Learning Environments: A Systematic Literature Review. IEEE Transactions on Learning Technologies. 2021; PP (99):1-1.
Chicago/Turabian StyleBernardo Tabuenca; Sergio Serrano-Iglesias; Adrian Carruana-Martin; Cristina Villa-Torrano; Yannis A. Dimitriadis; Juan I. Asensio-Perez; Carlos Alario-Hoyos; Eduardo Gomez-Sanchez; Miguel L. Bote-Lorenzo; Alejandra Martinez-Mones; Carlos Delgado Kloos. 2021. "Affordances and Core Functions of Smart Learning Environments: A Systematic Literature Review." IEEE Transactions on Learning Technologies PP, no. 99: 1-1.
Over the past years, higher education institutions have been exploring different mechanisms to adapt their learning and teaching practices to increase students’ engagement. One of the proposals has been to reuse Massive Online Open Courses (MOOCs) as Small Online Private Courses (SPOCs), or as complementary resources in traditional courses through blended learning practices, such as flipped classroom. However, the integration of online courses as a complement to face-to-face courses poses some challenges. First, students are not used to such blended learning approaches and it is generally difficult for teachers to motivate them to access online resources for the preparation of face-to-face sessions. Second, students are not used to the dynamics of blended learning scenarios, which are less teacher-centered and require their active participation. We propose the use of the mobile application MyMOOCSpace (MMS) to meet these challenges and increase students’ motivation and use of learning resources in blended learning courses that use SPOCs as a complement. MMS is a mobile learning application based on gamification mechanisms to promote collaboration and motivation of students in the use of digital resources as a complement to blended learning courses. In this paper, we present the results of a quasi-experiment in a blended course with 294 students that uses a SPOC as a complement, with the aim to assess the effect of MMS on students’ motivation and learning resources consumption. In particular, the behavior of two groups of students with the main digital resources of the SPOC (videos and formative assessments) was analyzed: one using the MMS (GTest group), and the other not using MMS (GTrad group). The results suggest that the use of MMS had a positive correlation with the videos consumption, besides increasing student’ interaction with assessment exercises in the SPOC.
Luis Ramírez-Donoso; Mar Pérez-Sanagustín; Andrés Neyem; Carlos Alario-Hoyos; Isabel Hilliger; Felipe Rojos. Fostering the use of online learning resources: results of using a mobile collaboration tool based on gamification in a blended course. Interactive Learning Environments 2021, 1 -15.
AMA StyleLuis Ramírez-Donoso, Mar Pérez-Sanagustín, Andrés Neyem, Carlos Alario-Hoyos, Isabel Hilliger, Felipe Rojos. Fostering the use of online learning resources: results of using a mobile collaboration tool based on gamification in a blended course. Interactive Learning Environments. 2021; ():1-15.
Chicago/Turabian StyleLuis Ramírez-Donoso; Mar Pérez-Sanagustín; Andrés Neyem; Carlos Alario-Hoyos; Isabel Hilliger; Felipe Rojos. 2021. "Fostering the use of online learning resources: results of using a mobile collaboration tool based on gamification in a blended course." Interactive Learning Environments , no. : 1-15.
The assessment of surgical technical skills to be acquired by novice surgeons has been traditionally done by an expert surgeon and is therefore of a subjective nature. Nevertheless, the recent advances on IoT (Internet of Things), the possibility of incorporating sensors into objects and environments in order to collect large amounts of data, and the progress on machine learning are facilitating a more objective and automated assessment of surgical technical skills. This paper presents a systematic literature review of papers published after 2013 discussing the objective and automated assessment of surgical technical skills. 101 out of an initial list of 537 papers were analyzed to identify: 1) the sensors used; 2) the data collected by these sensors and the relationship between these data, surgical technical skills and surgeons’ levels of expertise; 3) the statistical methods and algorithms used to process these data; and 4) the feedback provided based on the outputs of these statistical methods and algorithms. Particularly, 1) mechanical and electromagnetic sensors are widely used for tool tracking, while inertial measurement units are widely used for body tracking; 2) path length, number of sub-movements, smoothness, fixation, saccade and total time are the main indicators obtained from raw data and serve to assess surgical technical skills such as economy, efficiency, hand tremor, or mind control, and distinguish between two or three levels of expertise (novice/intermediate/advanced surgeons); 3) SVM (Support Vector Machines) and Neural Networks are the preferred statistical methods and algorithms for processing the data collected, while new opportunities are opened up to combine various algorithms and use deep learning; and 4) feedback is provided by matching performance indicators and a lexicon of words and visualizations, although there is considerable room for research in the context of feedback and visualizations, taking, for example, ideas from learning analytics.
Pablo Castillo-Segura; Carmen Fernández-Panadero; Carlos Alario-Hoyos; Pedro J. Muñoz-Merino; Carlos Delgado Kloos. Objective and automated assessment of surgical technical skills with IoT systems: A systematic literature review. Artificial Intelligence in Medicine 2021, 112, 102007 .
AMA StylePablo Castillo-Segura, Carmen Fernández-Panadero, Carlos Alario-Hoyos, Pedro J. Muñoz-Merino, Carlos Delgado Kloos. Objective and automated assessment of surgical technical skills with IoT systems: A systematic literature review. Artificial Intelligence in Medicine. 2021; 112 ():102007.
Chicago/Turabian StylePablo Castillo-Segura; Carmen Fernández-Panadero; Carlos Alario-Hoyos; Pedro J. Muñoz-Merino; Carlos Delgado Kloos. 2021. "Objective and automated assessment of surgical technical skills with IoT systems: A systematic literature review." Artificial Intelligence in Medicine 112, no. : 102007.
One important problem in MOOCs is the lack of personalized support from teachers. Conversational agents arise as one possible solution to assist MOOC learners and help them to study. For example, conversational agents can help review key concepts of the MOOC by asking questions to the learners and providing examples. JavaPAL, a voice-based conversational agent for supporting learners on a MOOC on programming with Java offered on edX. This paper evaluates JavaPAL from different perspectives. First, the usability of JavaPAL is analyzed, obtaining a score of 74.41 according to a System Usability Scale (SUS). Second, learners? performance is compared when answering questions directly through JavaPAL and through the equivalent web interface on edX, getting similar results in terms of performance. Finally, interviews with JavaPAL users reveal that this conversational agent can be helpful as a complementary tool for the MOOC due to its portability and flexibility compared to accessing the MOOC contents through the web interface.
Cristina Catalán Aguirre; Nuria González-Castro; Carlos Delgado Kloos; Carlos Alario-Hoyos; Pedro J. Muñoz-Merino. Conversational agent for supporting learners on a MOOC on programming with Java. Computer Science and Information Systems 2021, 20 -20.
AMA StyleCristina Catalán Aguirre, Nuria González-Castro, Carlos Delgado Kloos, Carlos Alario-Hoyos, Pedro J. Muñoz-Merino. Conversational agent for supporting learners on a MOOC on programming with Java. Computer Science and Information Systems. 2021; (00):20-20.
Chicago/Turabian StyleCristina Catalán Aguirre; Nuria González-Castro; Carlos Delgado Kloos; Carlos Alario-Hoyos; Pedro J. Muñoz-Merino. 2021. "Conversational agent for supporting learners on a MOOC on programming with Java." Computer Science and Information Systems , no. 00: 20-20.
MOOCs (massive open online courses) have a built-in forum where learners can share experiences as well as ask questions and get answers. Nevertheless, the work of the learners in the MOOC forum is usually not taken into account when calculating their grade in the course, due to the difficulty of automating the calculation of that grade in a context with a very large number of learners. In some situations, discussion forums might even be the only available evidence to grade learners. In other situations, forum interactions could serve as a complement for calculating the grade in addition to traditional summative assessment activities. This paper proposes an algorithm to automatically calculate learners’ grades in the MOOC forum, considering both the quantitative dimension and the relevance in their contributions. In addition, the algorithm has been implemented within a web application, providing instructors with a visual and a numerical representation of the grade for each learner. An exploratory analysis is carried out to assess the algorithm and the tool with a MOOC on programming, obtaining a moderate positive correlation between the forum grades provided by the algorithm and the grades obtained through the summative assessment activities. Nevertheless, the complementary analysis conducted indicates that this correlation may not be enough to use the forum grades as predictors of the grades obtained through summative assessment activities.
Sergio García-Molina; Carlos Alario-Hoyos; Pedro Manuel Moreno-Marcos; Pedro J. Muñoz-Merino; Iria Estévez-Ayres; Carlos Delgado Kloos. An Algorithm and a Tool for the Automatic Grading of MOOC Learners from Their Contributions in the Discussion Forum. Applied Sciences 2020, 11, 95 .
AMA StyleSergio García-Molina, Carlos Alario-Hoyos, Pedro Manuel Moreno-Marcos, Pedro J. Muñoz-Merino, Iria Estévez-Ayres, Carlos Delgado Kloos. An Algorithm and a Tool for the Automatic Grading of MOOC Learners from Their Contributions in the Discussion Forum. Applied Sciences. 2020; 11 (1):95.
Chicago/Turabian StyleSergio García-Molina; Carlos Alario-Hoyos; Pedro Manuel Moreno-Marcos; Pedro J. Muñoz-Merino; Iria Estévez-Ayres; Carlos Delgado Kloos. 2020. "An Algorithm and a Tool for the Automatic Grading of MOOC Learners from Their Contributions in the Discussion Forum." Applied Sciences 11, no. 1: 95.
Carlos Alario-Hoyos; María Jesús Rodríguez-Triana; Maren Scheffel; Inmaculada Arnedillo-Sánchez; Sebastian Maximilian Dennerlein. Correction to: Addressing Global Challenges and Quality Education. Computational Science and Its Applications - ICCSA 2011 2020, C1 -C1.
AMA StyleCarlos Alario-Hoyos, María Jesús Rodríguez-Triana, Maren Scheffel, Inmaculada Arnedillo-Sánchez, Sebastian Maximilian Dennerlein. Correction to: Addressing Global Challenges and Quality Education. Computational Science and Its Applications - ICCSA 2011. 2020; ():C1-C1.
Chicago/Turabian StyleCarlos Alario-Hoyos; María Jesús Rodríguez-Triana; Maren Scheffel; Inmaculada Arnedillo-Sánchez; Sebastian Maximilian Dennerlein. 2020. "Correction to: Addressing Global Challenges and Quality Education." Computational Science and Its Applications - ICCSA 2011 , no. : C1-C1.
Massive Open Online Courses (MOOCs) can be enhanced with the so-called learning-by-doing, designing the courses in a way that the learners are involved in a more active way in the learning process. Within the options for increasing learners’ interaction in MOOCs, it is possible to integrate (third-party) external tools as part of the instructional design of the courses. In MOOCs on computer sciences, there are, for example, web-based Integrated Development Environments (IDEs) which can be integrated and that allow learners to do programming tasks directly in their browsers without installing desktop software. This work focuses on analyzing the effect on learners’ engagement and behavior of integrating a third-party web-based IDE, Codeboard, in three MOOCs on Java programming with the purpose of promoting learning-by-doing (learning by coding in this case). In order to measure learners’ level of engagement and behavior, data was collected from Codeboard on the number of compilations, executions and code generated, and compared between learners who registered in Codeboard to save and keep a record of their projects (registered learners) and learners who did not register in Codeboard and did not have access to these extra features (anonymous learners). The results show that learners who registered in Codeboard were more engaged than learners who did not register (in terms of number of compilations and executions), spent more time coding and did more changes in the base code provided by the teachers. The main implication of this study suggests the need for a trade-off between designing MOOCs that allow a very easy and anonymous access to external tools aimed for a more active learning, and forcing learners to give a step forward in terms of commitment in exchange for benefitting from additional features of the external tool used.
Jesús Manuel Gallego-Romero; Carlos Alario-Hoyos; Iria Estévez-Ayres; Carlos Delgado Kloos. Analyzing learners’ engagement and behavior in MOOCs on programming with the Codeboard IDE. Educational Technology Research and Development 2020, 68, 2505 -2528.
AMA StyleJesús Manuel Gallego-Romero, Carlos Alario-Hoyos, Iria Estévez-Ayres, Carlos Delgado Kloos. Analyzing learners’ engagement and behavior in MOOCs on programming with the Codeboard IDE. Educational Technology Research and Development. 2020; 68 (5):2505-2528.
Chicago/Turabian StyleJesús Manuel Gallego-Romero; Carlos Alario-Hoyos; Iria Estévez-Ayres; Carlos Delgado Kloos. 2020. "Analyzing learners’ engagement and behavior in MOOCs on programming with the Codeboard IDE." Educational Technology Research and Development 68, no. 5: 2505-2528.
Tools are an essential support in any human activity. As the technology advances, we are able to design more advanced tools that help us in doing the activities more efficiently. Recently, we have seen breakthroughs in the two main components of tools, namely the interface and the computing engine behind. Natural interfaces allow us to communicate with tools in a way better adapted for humans. In relation to the engine, we are shifting from a computing paradigm to another one based on artificial intelligence, which learns as it is used. In this paper, we examine how these technological advances have an impact on education, leading to smart learning environments.
Carlos Delgado Kloos; Carlos Alario-Hoyos; Pedro J. Munoz-Merino; Maria Blanca Ibanez; Iria Estevez-Ayres; Carmen Fernandez-Panadero. Educational Technology in the Age of Natural Interfaces and Deep Learning. IEEE Revista Iberoamericana de Tecnologias del Aprendizaje 2020, 15, 26 -33.
AMA StyleCarlos Delgado Kloos, Carlos Alario-Hoyos, Pedro J. Munoz-Merino, Maria Blanca Ibanez, Iria Estevez-Ayres, Carmen Fernandez-Panadero. Educational Technology in the Age of Natural Interfaces and Deep Learning. IEEE Revista Iberoamericana de Tecnologias del Aprendizaje. 2020; 15 (1):26-33.
Chicago/Turabian StyleCarlos Delgado Kloos; Carlos Alario-Hoyos; Pedro J. Munoz-Merino; Maria Blanca Ibanez; Iria Estevez-Ayres; Carmen Fernandez-Panadero. 2020. "Educational Technology in the Age of Natural Interfaces and Deep Learning." IEEE Revista Iberoamericana de Tecnologias del Aprendizaje 15, no. 1: 26-33.
In education, several studies have tried to track student persistence (i.e., students’ ability to keep on working on the assigned tasks) using different definitions and self-reported data. However, self-reported metrics may be limited, and currently, online courses allow collecting many low-level events to analyze student behaviors based on logs and using learning analytics. These analyses can be used to provide personalized and adaptative feedback in Smart Learning Environments. In this line, this work proposes the analysis and measurement of two types of persistence based on students’ interactions in online courses: (1) local persistence (based on the attempts used to solve an exercise when the student answers it incorrectly), and (2) global persistence (based on overall course activity/completion). Results show that there are different students’ profiles based on local persistence, although medium local persistence stands out. Moreover, local persistence is highly affected by course context and it can vary throughout the course. Furthermore, local persistence does not necessarily relate to global persistence or engagement with videos, although it is related to students’ average grade. Finally, predictive analysis shows that local persistence is not a strong predictor of global persistence and performance, although it can add some value to the predictive models.
Pedro Manuel Moreno-Marcos; Pedro J. Muñoz-Merino; Carlos Alario-Hoyos; Carlos Delgado Kloos. Re-Defining, Analyzing and Predicting Persistence Using Student Events in Online Learning. Applied Sciences 2020, 10, 1722 .
AMA StylePedro Manuel Moreno-Marcos, Pedro J. Muñoz-Merino, Carlos Alario-Hoyos, Carlos Delgado Kloos. Re-Defining, Analyzing and Predicting Persistence Using Student Events in Online Learning. Applied Sciences. 2020; 10 (5):1722.
Chicago/Turabian StylePedro Manuel Moreno-Marcos; Pedro J. Muñoz-Merino; Carlos Alario-Hoyos; Carlos Delgado Kloos. 2020. "Re-Defining, Analyzing and Predicting Persistence Using Student Events in Online Learning." Applied Sciences 10, no. 5: 1722.
Pedro Manuel Moreno-Marcos; Pedro J. Muñoz-Merino; Jorge Maldonado-Mahauad; Mar Pérez-Sanagustín; Carlos Alario-Hoyos; Carlos Delgado Kloos. Temporal analysis for dropout prediction using self-regulated learning strategies in self-paced MOOCs. Computers & Education 2020, 145, 1 .
AMA StylePedro Manuel Moreno-Marcos, Pedro J. Muñoz-Merino, Jorge Maldonado-Mahauad, Mar Pérez-Sanagustín, Carlos Alario-Hoyos, Carlos Delgado Kloos. Temporal analysis for dropout prediction using self-regulated learning strategies in self-paced MOOCs. Computers & Education. 2020; 145 ():1.
Chicago/Turabian StylePedro Manuel Moreno-Marcos; Pedro J. Muñoz-Merino; Jorge Maldonado-Mahauad; Mar Pérez-Sanagustín; Carlos Alario-Hoyos; Carlos Delgado Kloos. 2020. "Temporal analysis for dropout prediction using self-regulated learning strategies in self-paced MOOCs." Computers & Education 145, no. : 1.
Carlos Delgado Kloos; Carlos Alario-Hoyos; Pedro J. Muñoz-Merino; Cristina Catalán Aguirre; Nuria González Castro. Principles for the Design of an Educational Voice Assistant for Learning Java. Security Education and Critical Infrastructures 2019, 99 -106.
AMA StyleCarlos Delgado Kloos, Carlos Alario-Hoyos, Pedro J. Muñoz-Merino, Cristina Catalán Aguirre, Nuria González Castro. Principles for the Design of an Educational Voice Assistant for Learning Java. Security Education and Critical Infrastructures. 2019; ():99-106.
Chicago/Turabian StyleCarlos Delgado Kloos; Carlos Alario-Hoyos; Pedro J. Muñoz-Merino; Cristina Catalán Aguirre; Nuria González Castro. 2019. "Principles for the Design of an Educational Voice Assistant for Learning Java." Security Education and Critical Infrastructures , no. : 99-106.
Carlos Alario-Hoyos. GLUE!: an architecture for the integration of external tools in virtual learning environments. 2019, 1 .
AMA StyleCarlos Alario-Hoyos. GLUE!: an architecture for the integration of external tools in virtual learning environments. . 2019; ():1.
Chicago/Turabian StyleCarlos Alario-Hoyos. 2019. "GLUE!: an architecture for the integration of external tools in virtual learning environments." , no. : 1.
Massive Open Online Courses (MOOCs) have gained popularity over the last years, offering a learning environment with new opportunities and challenges. These courses attract a heterogeneous set of participants who, due to the impossibility of personal tutorship in MOOCs, are required to create their own learning path and manage one’s own learning to achieve their goals. In other words, they should be able to self-regulate their learning. Self-regulated learning (SRL) has been widely explored in settings such as face-to-face or blended learning environments. Nevertheless, research on SRL in MOOCs is still scarce, especially on supporting interventions. In this sense, this document presents MOOCnager, a Chrome plug-in to help learners improve their SRL skills. Specifically, this work focuses on 3 areas: goal setting, time management and selfevaluation. Each area is included in one of the 3 phases composing Zimmerman’s SRL Cyclical Model. In this way, the plug-in aims to support enrolees’ self-regulation throughout their complete learning process. Finally, MOOCnager was uploaded to the Chrome Web Store, in order to get a preliminary evaluation with real participants from 6 edX Java MOOCs designed by the Universidad Carlos III de Madrid (UC3M). Results were not conclusive as the use of the plug-in by the participants was very low. However, learners seem to prefer a seamless tool, integrated in the MOOC platform, which is able to assist them without any learner-tool interaction.
María Elena Alonso-Mencía; Carlos Alario-Hoyos; Carlos Delgado Kloos. Chrome Plug-in to Support SRL in MOOCs. Computer Vision 2019, 3 -12.
AMA StyleMaría Elena Alonso-Mencía, Carlos Alario-Hoyos, Carlos Delgado Kloos. Chrome Plug-in to Support SRL in MOOCs. Computer Vision. 2019; ():3-12.
Chicago/Turabian StyleMaría Elena Alonso-Mencía; Carlos Alario-Hoyos; Carlos Delgado Kloos. 2019. "Chrome Plug-in to Support SRL in MOOCs." Computer Vision , no. : 3-12.
Technology is advancing at an ever-increasing speed. The backend capabilities and the frontend means of interaction are revolutionizing all kinds of applications. In this paper, we analyze how the technological breakthroughs seem to make educational interactions look smarter and more human. After defining Education 4.0 following the Industry 4.0 idea, we identify the key breakthroughs of the last decade in educational technology, basically revolving around the concept cloud computing, and imagine a new wave of educational technologies supported by machine learning that allows defining educational scenarios where computers interact and react more and more like humans.
Carlos Delgado Kloos; Carlos Alario-Hoyos; Pedro J. Munoz-Merino; Maria Blanca Ibañez; Iria Estevez-Ayres; Raquel M. Crespo-Garcia. What Can You Do with Educational Technology that is Getting More Human? 2019 IEEE Global Engineering Education Conference (EDUCON) 2019, 1480 -1487.
AMA StyleCarlos Delgado Kloos, Carlos Alario-Hoyos, Pedro J. Munoz-Merino, Maria Blanca Ibañez, Iria Estevez-Ayres, Raquel M. Crespo-Garcia. What Can You Do with Educational Technology that is Getting More Human? 2019 IEEE Global Engineering Education Conference (EDUCON). 2019; ():1480-1487.
Chicago/Turabian StyleCarlos Delgado Kloos; Carlos Alario-Hoyos; Pedro J. Munoz-Merino; Maria Blanca Ibañez; Iria Estevez-Ayres; Raquel M. Crespo-Garcia. 2019. "What Can You Do with Educational Technology that is Getting More Human?" 2019 IEEE Global Engineering Education Conference (EDUCON) , no. : 1480-1487.
Learners in massive open online courses (MOOCs) are required to be autonomous during their learning process, and thus they need to self-regulate their learning to achieve their goals. According to existing literature, self-regulated learning (SRL) research in MOOCs is still scarce. More studies which build on past works regarding SRL in MOOCs are required, as well as literature reviews that help to identify the main challenges and future research directions in relation to this area. In this paper, the authors present the results of a systematic literature review on SRL in MOOCs, covering all the related papers published until the end of 2017. The papers considered in this review include real experiences with at least a MOOC (other learning scenarios sometimes claimed as MOOCs, such as blended courses, or online courses with access restrictions, are out of the scope of this analysis). Most studies on SRL in MOOCs share some common features: they are generally exploratory, based on one single MOOC and tend not to specify in which SRL model they are grounded. The results reveal that high self-regulators engage in non-linear navigation and approach MOOCs as an informal learning opportunity. In general, they prefer setting specific goals based on knowledge development and control their learning through assignments.
M. Elena Alonso-Mencía; Carlos Alario-Hoyos; Jorge Maldonado-Mahauad; Iria Estévez-Ayres; Mar Pérez-Sanagustín; Carlos Delgado Kloos. Self-regulated learning in MOOCs: lessons learned from a literature review. Educational Review 2019, 72, 319 -345.
AMA StyleM. Elena Alonso-Mencía, Carlos Alario-Hoyos, Jorge Maldonado-Mahauad, Iria Estévez-Ayres, Mar Pérez-Sanagustín, Carlos Delgado Kloos. Self-regulated learning in MOOCs: lessons learned from a literature review. Educational Review. 2019; 72 (3):319-345.
Chicago/Turabian StyleM. Elena Alonso-Mencía; Carlos Alario-Hoyos; Jorge Maldonado-Mahauad; Iria Estévez-Ayres; Mar Pérez-Sanagustín; Carlos Delgado Kloos. 2019. "Self-regulated learning in MOOCs: lessons learned from a literature review." Educational Review 72, no. 3: 319-345.