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Collaboration is considered as one of the main drivers of learning and it has been broadly studied across numerous contexts, including Massive Open Online Courses (MOOCs). The research on MOOCs has risen exponentially during the last years and there have been a number of works focused on studying collaboration. However, these previous studies have been restricted to the analysis of collaboration based on the forum and social interactions, without taking into account other possibilities such as the synchronicity in the interactions with the platform. Therefore, in this work we performed a case study with the goal of implementing a data-driven approach to detect and characterize collaboration in MOOCs. We applied an algorithm to detect synchronicity links based on their submission times to quizzes as an indicator of collaboration, and applied it to data from two large Coursera MOOCs. We found three different profiles of user accounts, that were grouped in couples and larger communities exhibiting different types of associations between user accounts. The characterization of these user accounts suggested that some of them might represent genuine online learning collaborative associations, but that in other cases dishonest behaviors such as free-riding or multiple account cheating might be present. These findings call for additional research on the study of the kind of collaborations that can emerge in online settings.
José A. Ruipérez-Valiente; Daniel Jaramillo-Morillo; Srećko Joksimović; Vitomir Kovanović; Pedro J. Muñoz-Merino; Dragan Gašević. Data-driven detection and characterization of communities of accounts collaborating in MOOCs. Future Generation Computer Systems 2021, 125, 590 -603.
AMA StyleJosé A. Ruipérez-Valiente, Daniel Jaramillo-Morillo, Srećko Joksimović, Vitomir Kovanović, Pedro J. Muñoz-Merino, Dragan Gašević. Data-driven detection and characterization of communities of accounts collaborating in MOOCs. Future Generation Computer Systems. 2021; 125 ():590-603.
Chicago/Turabian StyleJosé A. Ruipérez-Valiente; Daniel Jaramillo-Morillo; Srećko Joksimović; Vitomir Kovanović; Pedro J. Muñoz-Merino; Dragan Gašević. 2021. "Data-driven detection and characterization of communities of accounts collaborating in MOOCs." Future Generation Computer Systems 125, no. : 590-603.
Technology has become an integral part of our everyday life, and its use in educational environments keeps growing. Additionally, video games are one of the most popular mediums across cultures and ages. There is ample evidence that supports the benefits of using games for learning and assessment, and educators are mainly supportive of using games in classrooms. However, we do not usually find educational games within the classroom activities. One of the main problems is that teachers report difficulties to actually know how their students are using the game so that they can analyze properly the effect of the activity and the interaction of students. To support teachers, educational games should incorporate learning analytics to transform data generated by students when playing useful information in a friendly and understandable way. For this work, we build upon Shadowspect, a 3D geometry puzzle game that has been used by teachers in a group of schools in the US.We use learning analytics techniques to generate a set of metrics implemented in a live dashboard that aims to facilitate that teachers can understand students’ interaction with Shadowspect. We depict the multidisciplinary design process that we have followed to generate the metrics and the dashboard with great detail. Finally, we also provide uses cases that exemplify how teachers can use the dashboard to understand the global progress of their class and each of their students at an individual level, in order to intervene, adapt their classes and provide personalize feedback when appropriate.
Jose A. Ruiperez-Valiente; Manuel J. Gomez; Pedro A. Martinez; Yoon Jeon Kim. Ideating and Developing a Visualization Dashboard to Support Teachers Using Educational Games in the Classroom. IEEE Access 2021, 9, 83467 -83481.
AMA StyleJose A. Ruiperez-Valiente, Manuel J. Gomez, Pedro A. Martinez, Yoon Jeon Kim. Ideating and Developing a Visualization Dashboard to Support Teachers Using Educational Games in the Classroom. IEEE Access. 2021; 9 (99):83467-83481.
Chicago/Turabian StyleJose A. Ruiperez-Valiente; Manuel J. Gomez; Pedro A. Martinez; Yoon Jeon Kim. 2021. "Ideating and Developing a Visualization Dashboard to Support Teachers Using Educational Games in the Classroom." IEEE Access 9, no. 99: 83467-83481.
The emergence of Massive Open Online Courses (MOOCs) broadened the educational landscape by providing free access to quality learning materials for anyone with a device connected to the Internet. However, open access does not guarantee equals opportunities to learn, and research has repetitively reported that learners from affluent countries benefit the most from MOOCs. In this work, we delve into this gap by defining and measuring completion and assessment biases with respect to learners' language and development status. We do so by performing a large-scale analysis across 158 MITx MOOC runs from 120 different courses offered on edX between 2013 and 2018, with 2.8 million enrollments. We see that learners from developing countries are less likely to complete MOOCs successfully, but we do not find evidence regarding a negative effect of not being English-native. Our findings point out that not only the specific population of learners is responsible for this bias, but also that the course itself has a similar impact. Independent of and less frequent than completion bias, we found assessment bias, that is when the mean ability gained by learners from developing countries is lower than that of learners from developed countries. The ability is inferred from the responses of the learners to the course-assessment using Item Response Theory (IRT).Finally, we applied Differential Item Functioning (DIF) methods with the objective of detecting items that might be causing the assessment bias, obtaining weak, yet positive results with respect to the magnitude of the bias reduction. Our results provide statistical evidence on the role that course design might have on these biases, with a call for action so that the future generation of MOOCs focus on strengthening their inclusive design approaches.
Sa'Ar Karp Gershon; José A. Ruipérez-Valiente; Giora Alexandron. Defining and Measuring Completion and Assessment Biases with Respect to English Language and Development Status: Not All MOOCs are Equal. 2021, 1 .
AMA StyleSa'Ar Karp Gershon, José A. Ruipérez-Valiente, Giora Alexandron. Defining and Measuring Completion and Assessment Biases with Respect to English Language and Development Status: Not All MOOCs are Equal. . 2021; ():1.
Chicago/Turabian StyleSa'Ar Karp Gershon; José A. Ruipérez-Valiente; Giora Alexandron. 2021. "Defining and Measuring Completion and Assessment Biases with Respect to English Language and Development Status: Not All MOOCs are Equal." , no. : 1.
Massive Open Online Courses (MOOCs) offer online courses at low cost for anyone with an internet access. At its early days, the MOOC movement raised the flag of democratizing education, but soon enough, this utopian idea collided with the need to find sustainable business models. Moving from open access to a new financially sustainable certification and monetization policy in December 2015 we aim at this change-point and observe the completion rates before and after this monetary change. In this study we investigate the impact of the change on learners from countries of different development status. Our findings suggest that this change has lowered the completion rates among learners from developing countries, increasing gaps that already existed between global learners from countries of low and high development status. This suggests that more inclusive monetization policies may help MOOCs benefits to spread more equally among global learners.
Sa'Ar Karp Gershon; José A. Ruipérez-Valiente; Giora Alexandron. MOOC MONETIZATION CHANGES AND COMPLETION RATES: ARE LEARNERS FROM COUNTRIES OF DIFFERENT DEVELOPMENT STATUS EQUALLY AFFECTED? 2021, 1 .
AMA StyleSa'Ar Karp Gershon, José A. Ruipérez-Valiente, Giora Alexandron. MOOC MONETIZATION CHANGES AND COMPLETION RATES: ARE LEARNERS FROM COUNTRIES OF DIFFERENT DEVELOPMENT STATUS EQUALLY AFFECTED? . 2021; ():1.
Chicago/Turabian StyleSa'Ar Karp Gershon; José A. Ruipérez-Valiente; Giora Alexandron. 2021. "MOOC MONETIZATION CHANGES AND COMPLETION RATES: ARE LEARNERS FROM COUNTRIES OF DIFFERENT DEVELOPMENT STATUS EQUALLY AFFECTED?" , no. : 1.
Games have become one of the most popular activities across cultures and ages. There is ample evidence that supports the benefits of using games for learning and assessment. However, incorporating game activities as part of the curriculum in schools remains limited. Some of the barriers for broader adoption in classrooms is the lack of actionable assessment data, the fact that teachers often do not have a clear sense of how students are interacting with the game, and it is unclear if the gameplay is leading to productive learning. To address this gap, we seek to provide sequence and process mining metrics to teachers that are easily interpretable and actionable. More specifically, we build our work on top of Shadowspect, a three-dimensional geometry game that has been developed to measure geometry skills as well other cognitive and noncognitive skills. We use data from its implementation across schools in the U.S. to implement two sequence and process mining metrics in an interactive dashboard for teachers. The final objective is to facilitate that teachers can understand the sequence of actions and common errors of students using Shadowspect so they can better understand the process, make proper assessment, and conduct personalized interventions when appropriate.
Manuel Gomez; José Ruipérez-Valiente; Pedro Martínez; Yoon Kim. Applying Learning Analytics to Detect Sequences of Actions and Common Errors in a Geometry Game. Sensors 2021, 21, 1025 .
AMA StyleManuel Gomez, José Ruipérez-Valiente, Pedro Martínez, Yoon Kim. Applying Learning Analytics to Detect Sequences of Actions and Common Errors in a Geometry Game. Sensors. 2021; 21 (4):1025.
Chicago/Turabian StyleManuel Gomez; José Ruipérez-Valiente; Pedro Martínez; Yoon Kim. 2021. "Applying Learning Analytics to Detect Sequences of Actions and Common Errors in a Geometry Game." Sensors 21, no. 4: 1025.
Mariano Albaladejo-González; Sofia Strukova; José A. Ruipérez-Valiente; Félix L Gómez Mármol. Exploring the Affordances of Multimodal Data to Improve Cybersecurity Training with Cyber Range Environments. Investigación en Ciberseguridad 2021, 1 .
AMA StyleMariano Albaladejo-González, Sofia Strukova, José A. Ruipérez-Valiente, Félix L Gómez Mármol. Exploring the Affordances of Multimodal Data to Improve Cybersecurity Training with Cyber Range Environments. Investigación en Ciberseguridad. 2021; ():1.
Chicago/Turabian StyleMariano Albaladejo-González; Sofia Strukova; José A. Ruipérez-Valiente; Félix L Gómez Mármol. 2021. "Exploring the Affordances of Multimodal Data to Improve Cybersecurity Training with Cyber Range Environments." Investigación en Ciberseguridad , no. : 1.
Félix Gómez Mármol; José A. Ruipérez-Valiente; Pantaleone Nespoli; Gregorio Martínez Pérez; Diego Rivera Pinto; Xavier Larriva Novo; Manuel Álvarez-Campana; Víctor Villagrá González; Jorge Maestre Vidal; Francisco A. Rodríguez López; Miguel Páramo Castrillo; Javier I. Rojo Lacal; Ram´on García-Abril Alonso. COBRA: Cibermaniobras adaptativas y personalizables de simulación hiperrealista de APTs y entrenamiento en ciberdefensa usando gamificación. Investigación en Ciberseguridad 2021, 1 .
AMA StyleFélix Gómez Mármol, José A. Ruipérez-Valiente, Pantaleone Nespoli, Gregorio Martínez Pérez, Diego Rivera Pinto, Xavier Larriva Novo, Manuel Álvarez-Campana, Víctor Villagrá González, Jorge Maestre Vidal, Francisco A. Rodríguez López, Miguel Páramo Castrillo, Javier I. Rojo Lacal, Ram´on García-Abril Alonso. COBRA: Cibermaniobras adaptativas y personalizables de simulación hiperrealista de APTs y entrenamiento en ciberdefensa usando gamificación. Investigación en Ciberseguridad. 2021; ():1.
Chicago/Turabian StyleFélix Gómez Mármol; José A. Ruipérez-Valiente; Pantaleone Nespoli; Gregorio Martínez Pérez; Diego Rivera Pinto; Xavier Larriva Novo; Manuel Álvarez-Campana; Víctor Villagrá González; Jorge Maestre Vidal; Francisco A. Rodríguez López; Miguel Páramo Castrillo; Javier I. Rojo Lacal; Ram´on García-Abril Alonso. 2021. "COBRA: Cibermaniobras adaptativas y personalizables de simulación hiperrealista de APTs y entrenamiento en ciberdefensa usando gamificación." Investigación en Ciberseguridad , no. : 1.
Javier Pastor-Galindo; Mattia Zago; Pantaleone Nespoli; Sergio López Bernal; Alberto Huertas Celdrán; Manuel Gil Pérez; José A. Ruipérez-Valiente; Gregorio Martínez Pérez; Félix Gómez Mármol. A Review of Spotting political social bots in Twitter: A use case of the 2019 Spanish general election. Investigación en Ciberseguridad 2021, 1 .
AMA StyleJavier Pastor-Galindo, Mattia Zago, Pantaleone Nespoli, Sergio López Bernal, Alberto Huertas Celdrán, Manuel Gil Pérez, José A. Ruipérez-Valiente, Gregorio Martínez Pérez, Félix Gómez Mármol. A Review of Spotting political social bots in Twitter: A use case of the 2019 Spanish general election. Investigación en Ciberseguridad. 2021; ():1.
Chicago/Turabian StyleJavier Pastor-Galindo; Mattia Zago; Pantaleone Nespoli; Sergio López Bernal; Alberto Huertas Celdrán; Manuel Gil Pérez; José A. Ruipérez-Valiente; Gregorio Martínez Pérez; Félix Gómez Mármol. 2021. "A Review of Spotting political social bots in Twitter: A use case of the 2019 Spanish general election." Investigación en Ciberseguridad , no. : 1.
Massive Open Online Massive Open Online Courses (MOOCs) have been transitioning slowly from being completely open and without clear recognition in universities or industry, to private settings through the emergence of Small and Massive Private Online Courses (SPOCs and MPOCs). Courses in these new formats are often for credit and have clear market value through the acquisition of competencies and skills. However, the endemic issue of academic dishonesty remains lingering and generating untrustworthiness regarding what students did to complete these courses. In this case study, we focus on SPOCs with academic recognition developed at the University of Cauca in Colombia and hosted in their Open edX instance called Selene Unicauca. We have developed a learning analytics algorithm to detect dishonest students based on submission time and exam responses providing as output a number of indicators that can be easily used to identify students. Our results in two SPOCs suggest that 17% of the students that interacted enough with the courses have performed academic dishonest actions, and that 100% of the students that were dishonest passed the courses, compared to 62% for the rest of students. Contrary to what other studies have found, in this study, dishonest students were similarly or even more active with the courseware than the rest, and we hypothesize that these might be working groups taking the course seriously and solving exams together to achieve a higher grade. With MOOC-based degrees and SPOCs for credit becoming the norm in distance learning, we believe that if this issue is not tackled properly, it might endanger the future of the reliability and value of online learning credentials.
Daniel Jaramillo-Morillo; José A. Ruipérez-Valiente; Mario F. Sarasty; Gustavo Ramírez-Gonzalez. Identifying and characterizing students suspected of academic dishonesty in SPOCs for credit through learning analytics. International Journal of Educational Technology in Higher Education 2020, 17, 1 -18.
AMA StyleDaniel Jaramillo-Morillo, José A. Ruipérez-Valiente, Mario F. Sarasty, Gustavo Ramírez-Gonzalez. Identifying and characterizing students suspected of academic dishonesty in SPOCs for credit through learning analytics. International Journal of Educational Technology in Higher Education. 2020; 17 (1):1-18.
Chicago/Turabian StyleDaniel Jaramillo-Morillo; José A. Ruipérez-Valiente; Mario F. Sarasty; Gustavo Ramírez-Gonzalez. 2020. "Identifying and characterizing students suspected of academic dishonesty in SPOCs for credit through learning analytics." International Journal of Educational Technology in Higher Education 17, no. 1: 1-18.
While social media has been proved as an exceptionally useful tool to interact with other people and massively and quickly spread helpful information, its great potential has been ill-intentionally leveraged as well to distort political elections and manipulate constituents. In the paper at hand, we analyzed the presence and behavior of social bots on Twitter in the context of the November 2019 Spanish general election. Throughout our study, we classified involved users as social bots or humans, and examined their interactions from a quantitative (i.e. amount of traffic generated and existing relations) and qualitative (i.e. user’s political affinity and sentiment towards the most important parties) perspectives. Results demonstrated that a non-negligible amount of those bots actively participated in the election, supporting each of the five principal political parties.
Javier Pastor-Galindo; Mattia Zago; Mattia Zago Pantaleone Nespoli; Sergio Lopez Bernal; Alberto Huertas Celdran; Manuel Gil Perez; Jose A. Ruiperez-Valiente; Gregorio Martinez Perez; Felix Gomez Marmol. Spotting Political Social Bots in Twitter: A Use Case of the 2019 Spanish General Election. IEEE Transactions on Network and Service Management 2020, 17, 2156 -2170.
AMA StyleJavier Pastor-Galindo, Mattia Zago, Mattia Zago Pantaleone Nespoli, Sergio Lopez Bernal, Alberto Huertas Celdran, Manuel Gil Perez, Jose A. Ruiperez-Valiente, Gregorio Martinez Perez, Felix Gomez Marmol. Spotting Political Social Bots in Twitter: A Use Case of the 2019 Spanish General Election. IEEE Transactions on Network and Service Management. 2020; 17 (4):2156-2170.
Chicago/Turabian StyleJavier Pastor-Galindo; Mattia Zago; Mattia Zago Pantaleone Nespoli; Sergio Lopez Bernal; Alberto Huertas Celdran; Manuel Gil Perez; Jose A. Ruiperez-Valiente; Gregorio Martinez Perez; Felix Gomez Marmol. 2020. "Spotting Political Social Bots in Twitter: A Use Case of the 2019 Spanish General Election." IEEE Transactions on Network and Service Management 17, no. 4: 2156-2170.
Massive Open Online Courses (MOOCs) came into the educational ecosystem attracting the attention of the public media, businesses, teachers, and learners from all over the world. The original courses were completely open and free, targeting the worldwide population. However, current MOOC providers have pivoted towards more private directions, and we often find that MOOC materials are completely closed within their hosting platforms and cannot be retrieved from them by their learners. This diminishes the potential of MOOCs by making content available to a small proportion of learners and severely limits the reusability of the educational resources. In this paper, we present a process that we call ‘unMOOCing’, in which we transform the resources of a MOOC into OERs. We taught a MOOC on Open Education in the UNED Abierta platform, and we ‘unMOOCed’ all of its educational resources, making them available to download by the learners that are taking the course. The results of the unMOOCing were very encouraging: the possibility of downloading the course resources was the most highly rated component of the course. Additionally, the two unMOOCed materials that were considered as most useful (presentations and contents in a PDF) were downloaded by 90% of the learners. Now that the majority of MOOC providers are moving towards a more closed educational approach, we believe that this paper sends a powerful message for bringing back the original MOOC concept of ‘Openness’ with the unMOOCing process, thus contributing to the wider dissemination and democratization of education across the globe.
José Ruipérez-Valiente; Sergio Martin; Justin Reich; Manuel Castro. The UnMOOCing Process: Extending the Impact of MOOC Educational Resources as OERs. Sustainability 2020, 12, 7346 .
AMA StyleJosé Ruipérez-Valiente, Sergio Martin, Justin Reich, Manuel Castro. The UnMOOCing Process: Extending the Impact of MOOC Educational Resources as OERs. Sustainability. 2020; 12 (18):7346.
Chicago/Turabian StyleJosé Ruipérez-Valiente; Sergio Martin; Justin Reich; Manuel Castro. 2020. "The UnMOOCing Process: Extending the Impact of MOOC Educational Resources as OERs." Sustainability 12, no. 18: 7346.
There is increasing interest in using data to design digital games that serve the purposes of learning and assessment. One game element, difficulty, could benefit vastly from applying data-driven methods as it affects both players’ overall enjoyment and efficiency of learning and qualities of assessment. However, how difficulty is being defined varies across the learning, assessment, and game perspectives, yet little is known about how educational difficulty can be balanced in educational games for each of the potentially conflicting goals. In this paper, we first review varying definitions of difficulty and then we discuss how we came up with a difficulty metric and used it to refine our game-based assessment Shadowspect. The design guidelines, metrics and lessons learned will be useful for designers of learning games and educators interested in balancing difficulty before they implement these tools in the classroom.
Yoon Jeon Kim; Jose A. Ruipérez-Valiente. Data-Driven Game Design: The Case of Difficulty in Educational Games. Transactions on Petri Nets and Other Models of Concurrency XV 2020, 449 -454.
AMA StyleYoon Jeon Kim, Jose A. Ruipérez-Valiente. Data-Driven Game Design: The Case of Difficulty in Educational Games. Transactions on Petri Nets and Other Models of Concurrency XV. 2020; ():449-454.
Chicago/Turabian StyleYoon Jeon Kim; Jose A. Ruipérez-Valiente. 2020. "Data-Driven Game Design: The Case of Difficulty in Educational Games." Transactions on Petri Nets and Other Models of Concurrency XV , no. : 449-454.
Digital games for learning are one of the most prominent examples of the use of technologies in the classroom, where numerous studies have presented promising results among children and adolescents. However, scarce evidence exists regarding different ways of implementing games within the classroom and how those affect students' learning and behaviors. In this study we explore the effect that collaboration can have in digital gameplay in a K12 context. More specifically, we have designed a 2 × 2 experimental study in which high school first year students participated in solo or collaborative gameplay in pairs, solving puzzles of diverse difficulty, using Shadowspect, a digital game on geometry. Our main results, computed by applying learning analytics on the trace data results, suggest that students playing solo had higher in-game engagement and solved more puzzles, while students collaborating were less linear in their pathways, skipping more tutorial levels and were more exploratory with Shadowspect features. These significant differences that we observe in solo and collaborative gameplay call for more experimentation around the effect of having K12 students collaborate on digital tasks, so that teachers can take better decisions about how to implement these practices in the classrooms of the future.
José A. Ruipérez-Valiente; Yoon Jeon Kim. Effects of solo vs. collaborative play in a digital learning game on geometry: Results from a K12 experiment. Computers & Education 2020, 159, 104008 .
AMA StyleJosé A. Ruipérez-Valiente, Yoon Jeon Kim. Effects of solo vs. collaborative play in a digital learning game on geometry: Results from a K12 experiment. Computers & Education. 2020; 159 ():104008.
Chicago/Turabian StyleJosé A. Ruipérez-Valiente; Yoon Jeon Kim. 2020. "Effects of solo vs. collaborative play in a digital learning game on geometry: Results from a K12 experiment." Computers & Education 159, no. : 104008.
Over the last years, existing technologies have been applied to agricultural environments, resulting in new precision agriculture systems. Some of the multiple profits of developing new agricultural technologies and applications include the cost reduction around the building and deployment of them, together with more energy-efficient consumption. Therefore, agricultural precision systems focus on developing better, easier, cheaper, and overall more efficient ways of handling agricultural monitoring and actuation. To achieve this vision, we use a set of technologies such as Wireless Sensor Networks, Sensors devices, Internet of Things, or data analysis. More specifically, in this study, we proposed a combination of all these technologies to design and develop a prototype of a precision agriculture system for medium and small agriculture plantations that highlights two major advantages: efficient energy management with self-charging capabilities and a low-cost policy. For the development of the project, several prototype nodes were built and deployed within a sensor network connected to the cloud as a self-powered system. The final target of this system is, therefore, to gather environment data, analyze it, and actuate by activating the watering installation. An analysis of the exposed agriculture monitoring system, in addition to results, is exposed in the paper.
Javier Rodríguez Robles; Álvaro Martin; Sergio Martin; José Ruipérez-Valiente; Manuel Castro. Autonomous Sensor Network for Rural Agriculture Environments, Low Cost, and Energy Self-Charge. Sustainability 2020, 12, 5913 .
AMA StyleJavier Rodríguez Robles, Álvaro Martin, Sergio Martin, José Ruipérez-Valiente, Manuel Castro. Autonomous Sensor Network for Rural Agriculture Environments, Low Cost, and Energy Self-Charge. Sustainability. 2020; 12 (15):5913.
Chicago/Turabian StyleJavier Rodríguez Robles; Álvaro Martin; Sergio Martin; José Ruipérez-Valiente; Manuel Castro. 2020. "Autonomous Sensor Network for Rural Agriculture Environments, Low Cost, and Energy Self-Charge." Sustainability 12, no. 15: 5913.
La creciente utilización de sistemas de mediación digital en la mayoría de espacios educativos —ya sean presenciales o no, formales o abiertos, y tanto en el nivel de educación básica como en situaciones de aprendizaje a lo largo de la vida— está acelerando el avance de la analítica del aprendizaje y haciendo que el uso de la información digital sea una práctica común en el campo de la educación. Las herramientas educativas digitales facilitan la interacción entre estudiantes, profesores y recursos de aprendizaje, y generan de manera continua un notable volumen de datos que pueden analizarse aplicando una variedad de metodologías. Esto ha hecho que aumenten exponencialmente las investigaciones que toman como referencia la información que procede de la actividad de los estudiantes en esos espacios digitales. Partiendo de esas evidencias, este número especial muestra un conjunto de estudios en el campo del aprendizaje digital y la investigación educativa basada en datos, que enriquecen el conocimiento sobre los procesos de aprendizaje y la gestión de la enseñanza en espacios mediados digitalmente.
Daniel Domínguez Figaredo; Justin Reich; José A. Ruipérez-Valiente. Analítica del aprendizaje y educación basada en datos: Un campo en expansión. RIED. Revista Iberoamericana de Educación a Distancia 2020, 23, 33 -43.
AMA StyleDaniel Domínguez Figaredo, Justin Reich, José A. Ruipérez-Valiente. Analítica del aprendizaje y educación basada en datos: Un campo en expansión. RIED. Revista Iberoamericana de Educación a Distancia. 2020; 23 (2):33-43.
Chicago/Turabian StyleDaniel Domínguez Figaredo; Justin Reich; José A. Ruipérez-Valiente. 2020. "Analítica del aprendizaje y educación basada en datos: Un campo en expansión." RIED. Revista Iberoamericana de Educación a Distancia 23, no. 2: 33-43.
Con el despegue de la popularidad del área de analítica de aprendizaje durante la última década, numerosas investigaciones han surgido y la opinión pública se ha hecho eco de esta tendencia. Sin embargo, la realidad es que el impacto que ha tenido en la práctica ha sido bastante bajo, y se está produciendo poca transferencia a las instituciones educativas. Una de las posibles causas es la elevada complejidad del campo, y que no existan procesos claros; por ello, en este trabajo, se propone un pragmático proceso de implementación de analíticas de aprendizaje en cinco etapas: 1) entornos de aprendizaje, 2) recolección de datos en crudo, 3) manipulación de datos e ingeniería de características, 4) análisis y modelos y 5) aplicación educacional. Además, se revisan una serie de factores transversales que afectan esta implementación, como la tecnología, ciencias del aprendizaje, privacidad, instituciones y políticas educacionales. El proceso que se detalla puede resultar de utilidad para investigadores, analistas de datos educacionales, educadores e instituciones educativas que busquen introducirse en el área. Alcanzar el verdadero potencial de las analíticas de aprendizaje requerirá de estrecha colaboración y conversación entre todos los actores involucrados en su desarrollo, que permita su implementación de forma sistemática y productiva.
José A. Ruipérez-Valiente. El Proceso de Implementación de Analíticas de Aprendizaje. RIED. Revista Iberoamericana de Educación a Distancia 2020, 23, 85 -101.
AMA StyleJosé A. Ruipérez-Valiente. El Proceso de Implementación de Analíticas de Aprendizaje. RIED. Revista Iberoamericana de Educación a Distancia. 2020; 23 (2):85-101.
Chicago/Turabian StyleJosé A. Ruipérez-Valiente. 2020. "El Proceso de Implementación de Analíticas de Aprendizaje." RIED. Revista Iberoamericana de Educación a Distancia 23, no. 2: 85-101.
Tal y como ocurre en otros campos de investigación, el desarrollo de la analítica del aprendizaje está influido por las redes de investigadores que contribuyen al mismo. Este artículo describe una de estas redes: la Red Española de Analítica de Aprendizaje (SNOLA). El artículo presenta las líneas de investigación de los miembros de SNOLA, así como los principales retos que la analítica del aprendizaje tiene que afrontar en los próximos años desde la visión de estos investigadores. Este análisis está basado en datos de archivo de SNOLA y en una encuesta realizada a los actuales miembros de la red. Aunque esta aproximación no cubre toda la actividad relacionada con analítica del aprendizaje en España, los resultados proporcionan una visión general representativa del estado de la investigación relacionada con analítica del aprendizaje en dicho contexto. El artículo muestra cuáles son estas tendencias y los principales retos, entre los que se encuentran la necesidad de adoptar un compromiso ético con los datos, desarrollar sistemas que respondan a las necesidades de los usuarios y alcanzar mayor impacto institucional.
Alejandra Martínez Monés; Yannis Dimitriadis Damoulis; Emiliano Acquila-Natale; Ainhoa Álvarez; Manuel Caeiro Rodríguez; Ruth Cobos Pérez; Miguel Ángel Conde González; Francisco José García Peñalvo; Davinia Hernández Leo; Iratxe Menchaca Sierra; Pedro José Muñoz-Merino; Salvador Ros; Teresa Sancho Vinuesa. Achievements and challenges in learning analytics in Spain: The view of SNOLA. RIED. Revista Iberoamericana de Educación a Distancia 2020, 23, 187 -212.
AMA StyleAlejandra Martínez Monés, Yannis Dimitriadis Damoulis, Emiliano Acquila-Natale, Ainhoa Álvarez, Manuel Caeiro Rodríguez, Ruth Cobos Pérez, Miguel Ángel Conde González, Francisco José García Peñalvo, Davinia Hernández Leo, Iratxe Menchaca Sierra, Pedro José Muñoz-Merino, Salvador Ros, Teresa Sancho Vinuesa. Achievements and challenges in learning analytics in Spain: The view of SNOLA. RIED. Revista Iberoamericana de Educación a Distancia. 2020; 23 (2):187-212.
Chicago/Turabian StyleAlejandra Martínez Monés; Yannis Dimitriadis Damoulis; Emiliano Acquila-Natale; Ainhoa Álvarez; Manuel Caeiro Rodríguez; Ruth Cobos Pérez; Miguel Ángel Conde González; Francisco José García Peñalvo; Davinia Hernández Leo; Iratxe Menchaca Sierra; Pedro José Muñoz-Merino; Salvador Ros; Teresa Sancho Vinuesa. 2020. "Achievements and challenges in learning analytics in Spain: The view of SNOLA." RIED. Revista Iberoamericana de Educación a Distancia 23, no. 2: 187-212.
Massive Open Online Courses (MOOCs) have been transitioning slowly from being completely open and without clear recognition in universities or industry, to private settings through the emergence of Small and Massive Private Online Courses (SPOCs and MPOCs). Courses in these new formats are often for credit and have clear market value through the acquisition of competencies and skills. However, the endemic issue of academic dishonesty remains lingering and generating untrustworthiness regarding what students did to complete these courses. In this case study, we focus on SPOCs with academic recognition developed at the University of Cauca in Colombia and hosted in their Open edX instance called Selene Unicauca. We have developed a learning analytics algorithm to detect dishonest students based on submission time and exam responses providing as output a number of indicators that can be easily used to identify students. Our results in two SPOCs suggest that 17% of the students that interacted enough with the courses have performed academic dishonest actions, and that 100% of the students that were dishonest passed the courses, compared to 62% for the rest of students. Contrary to what other studies have found, in this study, dishonest students were similarly or even more active with the courseware than the rest, and we hypothesize that these might be working groups taking the course seriously and solving exams together to achieve a higher grade. With MOOC-based degrees and SPOCs for credit becoming the norm in distance learning, we believe that if this issue is not tackled properly, it might endanger the future of the reliability and value of online learning credentials.
Daniel A. Jaramillo-Morillo; José A. Ruipérez-Valiente; Mario F. Solarte Sarasty; Gustavo A. Ramírez-González. Identifying and Characterizing Students Suspected of Academic Dishonesty in SPOCs for Credit through Learning Analytics. 2020, 1 .
AMA StyleDaniel A. Jaramillo-Morillo, José A. Ruipérez-Valiente, Mario F. Solarte Sarasty, Gustavo A. Ramírez-González. Identifying and Characterizing Students Suspected of Academic Dishonesty in SPOCs for Credit through Learning Analytics. . 2020; ():1.
Chicago/Turabian StyleDaniel A. Jaramillo-Morillo; José A. Ruipérez-Valiente; Mario F. Solarte Sarasty; Gustavo A. Ramírez-González. 2020. "Identifying and Characterizing Students Suspected of Academic Dishonesty in SPOCs for Credit through Learning Analytics." , no. : 1.
Video games have become one of the most popular mediums across cultures and ages. There is ample evidence that supports the benefits of using games for learning and assessment, and educators are largely supportive of using games in classrooms. However, the implementation of educational games as part of the curriculum and classroom practices has been rather scarce. One of the main barriers is that teachers face to actually know how their students are using the game so that they can analyze properly the effect of the activity and the interaction of students. Therefore, to support teachers to fully leverage the potential benefits of games in classrooms and make data-based decisions, educational games should incorporate learning analytics by transforming click-stream data generated from the gameplay into meaningful metrics and present visualizations of those metrics so that teachers can receive the information in an interactive and friendly way. For this work, we use data collected in a case study where teachers used Shadowspect geometry puzzle games in their classrooms. We apply learning analytics techniques to generate a series of metrics and visualizations that seek to facilitate that teachers can understand the interaction of students with the game. In this way, teachers can be more aware of the global progress of the class and each one of their students at an individual level, and intervene and adapt their classes when necessary.
Pedro A. Martínez; Manuel J. Gómez; José A. Ruipérez-Valiente; Gregorio Martínez Pérez; Yj Kim. Visualizing Educational Game Data: A Case Study of Visualizations to Support Teachers. 2020, 1 .
AMA StylePedro A. Martínez, Manuel J. Gómez, José A. Ruipérez-Valiente, Gregorio Martínez Pérez, Yj Kim. Visualizing Educational Game Data: A Case Study of Visualizations to Support Teachers. . 2020; ():1.
Chicago/Turabian StylePedro A. Martínez; Manuel J. Gómez; José A. Ruipérez-Valiente; Gregorio Martínez Pérez; Yj Kim. 2020. "Visualizing Educational Game Data: A Case Study of Visualizations to Support Teachers." , no. : 1.
We propose a general-purpose method for detecting cheating in Massive Open Online Courses (MOOCs) using an Anomaly Detection technique. Using features that are based on measures of aberrant behavior, we show that a classifier that is trained on data of one type of cheating (Copying Using Multiple Accounts) can detect users who perform another type of cheating (unauthorized collaboration). The study exploits the fact that we have dedicated algorithms for detecting these two methods of cheating, which are used as reference models. The contribution of this paper is twofold. First, we demonstrate that a detection method that is based on anomaly detection, which is trained on a known set of cheaters, can generalize to detect cheaters who use other methods. Second, we propose a new time-based person-t aberrant behavior statistic.
Giora Alexandron; José A. Ruipérez-Valiente; David E Pritchard. Towards a General Purpose Anomaly Detection Method to Identify Cheaters in Massive Open Online Courses. 2020, 1 .
AMA StyleGiora Alexandron, José A. Ruipérez-Valiente, David E Pritchard. Towards a General Purpose Anomaly Detection Method to Identify Cheaters in Massive Open Online Courses. . 2020; ():1.
Chicago/Turabian StyleGiora Alexandron; José A. Ruipérez-Valiente; David E Pritchard. 2020. "Towards a General Purpose Anomaly Detection Method to Identify Cheaters in Massive Open Online Courses." , no. : 1.