Proyectos

Publicaciones

2024

How Can Generative AI Support Education?

Carlos Delgado Kloos, Carlos Alario-Hoyos, Iria Estevez-Ayres, Patricia Callejo, Miguel A. Hombrados Herrera, Pedro J. Muñoz-Merino, Pedro Manuel Moreno-Marcos, Mario Muñoz and María-Blanca Ibáñez. 2024 IEEE Global Engineering Education Conference (EDUCON).

Enhancing Research on Engineering Education: Empowering Research Skills Through Generative Artificial Intelligence for Systematic Literature Reviews

Pablo Castillo, Carmen Fernandez-Panadero, Carlos Alario-Hoyos and Carlos Delgado Kloos. 2024 IEEE Global Engineering Education Conference (EDUCON).

Student and teacher impact on the use of telepresence classrooms

Adrián Carruana Martín, Carlos Alario-Hoyos, Pedro Manuel Moreno-Marcos and Carlos Delgado Kloos. Education and Information Technologies 2024.

Personalized Strategies for Academic Success in Learning Anatomy: Exploring Metacognitive and Technological Adaptation in Medical Students

Mónica Stambuk-Castellano, Anna Carrera, R. Shane Tubbs, Carlos Alario-Hoyos, Enric Verdú, Joe Iwanaga, Francisco Reina. Clinical Anatomy, Volume 37, Issue 4, May 2024.

Evaluation of LLM Tools for Feedback Generation in a Course on Concurrent Programming

Iria Estévez-Ayres, Patricia Callejo, Miguel Ángel Hombrados-Herrera, Carlos Alario-Hoyos and Carlos Delgado Kloos. International Journal of Artificial Intelligence in Education, May 2024.

A Web Application for a Cost-Effective Fine-Tuning of Open-Source LLMs in Education

Victor Diez-Rozas, Iria Estevez-Ayres, Carlos Alario-Hoyos, Patricia Callejo and Carlos Delgado Kloos. 25th International Conference, Artificial Intelligence in Education 2024.

Content Modeling in Smart Learning Environments: A systematic literature review.

Alberto Jiménez-Macías, Pedro J. Muñoz-Merino, Margarita Ortiz-Rojas, Mario Muñoz-Organero and Carlos Delgado Kloos. Journal of Universal Computer Science (JUCS), Volume 30, Issue 3, 2024.

Transforming Open Edx into the next On-Campus LMS.

Ignacio Despujol Zabala, Carlos Alario-Hoyos, Carlos Turró Ribalta, Carlos Delgado Kloos, Germán Montoro Manrique, Jaime Busquets Mataix. EMOOC 2023, published in February 2024.

Analysis and Prediction of Students’ Performance in a Computer-Based Course Through Real-Time Events

Lucia Uguina-Gadella; Iria Estévez-Ayres; Jesús Arias Fisteus; Carlos Alario-Hoyos and Carlos Delgado Kloos. IEEE Transactions on Learning Technologies, volume 17, 2024.

2023

Innovat MOOC Teacher Training on Educational Innovation in Higher Education

Carlos Alario-Hoyos, Carlos Delgado Kloos, Doris Kiendl, and Liliya Terzieva. EMOOCs 2023.

Construcción de Centros de Enseñanza y Aprendizaje para las Universidades de Latinoamérica en el Siglo XXI

Carlos Alario-Hoyos, Carlos Delgado Kloos, Miguel Morales, Héctor Amado, Rocael Hernández, Mar Pérez-Sanagustín, António Teixeira, Mario Solarte, Astrid Helena González, and Karla Valdez. Inteligencia Artificial: Amenazas, desafíos y oportunidades en la Educación Superior,  Vol. 5 (2023). El Congreso CODES 2023.

Leveraging the Potential of Generative AI to Accelerate Systematic Literature Reviews: An Example in the Area of Educational Technology

Pablo Castillo-Segura, Carlos Alario-Hoyos, Carlos Delgado Kloos, and Carmen Fernández Panadero. 2023 World Engineering Education Forum – Global Engineering Deans Council (WEEF-GEDC).

Transforming Education in the 21st Century: The Role of PROF-XXI Project in Developing Teaching Competencies

Miguel Morales Chan, Carlos Alario-Hoyos, Hector R. Amado-Salvatierra, Mar Pérez-Sanagustín, António Moreira Teixeira, Carlos Delgado Kloos, and Rocael Hernandez-Rizzardini. 2023 IEEE Learning with MOOCS (LWMOOCS).

Statoodle: A Learning Analytics Tool to Analyze Moodle Students’ Actions and Prevent Cheating

Pedro Manuel Moreno-Marcos, Jorge Barredo, Pedro J. Muñoz-Merino, and Carlos Delgado Kloos. Responsive and Sustainable Educational Futures 18th European Conference on Technology Enhanced Learning, EC-TEL 2023.

A Study of Student and Teacher Challenges in Smart Synchronous Hybrid Learning Environments

A Carruana Martín, Carlos Alario-Hoyos, Carlos Delgado Kloos
Sustainability 15 (15), 11694

Analysis of Orchestration Load and Teacher Agency in Smart Synchronous Hybrid Learning Environments

AC Martín, C Alario-Hoyos, A Martínez-Monés, CD Kloos
Preprints

Recreation of different educational exercise scenarios for exercise modeling

A Jiménez-Macías, PJ Muñoz-Merino, CD Kloos
2023 IEEE Global Engineering Education Conference (EDUCON), 1-9

Recognizing the Value of Recognition in Education

CD Kloos, C Alario-Hoyos, MB Ibáñez, PM Moreno-Marcos, …
2023 IEEE Global Engineering Education Conference (EDUCON), 1-5

ABENEARIO: A system for learning early maths with ABN

A Martín Díaz, C Alario-Hoyos, I Estévez-Ayres, C Delgado Kloos, …
Education and Information Technologies, 1-23

Experiences with Micro-Credentials at UC3M: Academic and Technological Aspects

CA Hoyos, CD Kloos
2023 IEEE World Engineering Education Conference (EDUNINE), 1-6

Analyzing feature importance for a predictive undergraduate student dropout model

A Jiménez-Macias, PM Moreno-Marcos, PJ Muñoz-Merino, M Ortiz-Rojas, …
Computer Science and Information Systems 20 (1), 175-194

Smart Groups: A system to orchestrate collaboration in hybrid learning environments. A simulation study

A Carrruana Martín, C Alario-Hoyos, C Delgado Kloos
Australasian Journal of Educational Technology 38 (6), 150-168

2022

Adaptation of a process Mining Methodology to Analyse Learning Strategies in a Synchronous Massive Open Online Course

Jorge Maldonado-Mahauad, Carlos Alario-Hoyos, Carlos Delgado Kloos, Mar Perez-Sanagustin

The study of learners’ behaviour in Massive Open Online Courses (MOOCs) is a topic of great interest for the Learning Analytics (LA) research community. In the past years, there has been a special focus on the analysis of students’ learning strategies, as these have been associated with successful academic achievement. Different methods and techniques, such as temporal analysis and process mining (PM), have been applied for analysing learners’ trace data and categorising them according to their actual behaviour in a particular learning context. However, prior research in Learning Sciences and Psychology has observed that results from studies conducted in one context do not necessarily transfer or generalise to others. In this sense, there is an increasing interest in the LA community in replicating and adapting studies across contexts. This paper serves to continue this trend of reproducibility and builds upon a previous study which proposed and evaluated a PM methodology for classifying learners according to seven different behavioural patterns in three asynchronous MOOCs of Coursera. In the present study, the same methodology was applied to a synchronous MOOC on edX with N = 50,776 learners. As a result, twelve different behavioural patterns were detected. Then, we discuss what decision other researchers should made to adapt this methodology and how these decisions can have an effect on the analysis of trace data. Finally, the results obtained from applying the methodology contribute to gain insights on the study of learning strategies, providing evidence about the importance of the learning context in MOOCs.

 

The impacts of scaffolding socially shared regulation on teamwork in an online project-based course

Catalina Cortázar, Miguel Nussbaum, Carlos Alario-Hoyos, Julián Goñi, Danilo Alvares

Employers now consider teamwork one of the essential skills for students to acquire during their academic life. However, COVID-19 has accelerated the transition towards online learning, affecting how we work in teams. This study looked at how scaffolding socially shared regulation of learning can influence teamwork in an online, project-based course. Intra-group peer assessment was used to analyze three variables during a first-year engineering course. By following the proposed scaffolding, students found an optimum balance in their contribution to team meetings. They also managed to establish a positive working environment earlier in the semester. This study contributes to the field by showing that scaffolding socially shared regulation in an online, project-based course allows for an interplay between collaboration during class and cooperation outside of it. This interplay ultimately leads teams to achieve better results on their final project.

H2O Learn – Hybrid and Human-Oriented Learning: Trustworthy and Human-Centered Learning Analytics (TaHCLA) for Hybrid Education

Carlos Delgado-Kloos, Yannis Dimitriadis, Davinia Hernández-Leo, Carlos Alario-Hoyos, Alejandra Martínez-Monés, Patricia Santos, Pedro J. Muñoz-Merino, Juan I. Asensio-Pérez, Lluis Vicent-Safont

This paper presents the H2O Learn (Hybrid and Human-Oriented Learning) project, a coordinated research project funded by the Spanish Research Agency, which just started in 2021 and will last for three years. The main goal of the H2O Learn project is to build Trustworthy and Human-Centered Learning Analytics (TaHCLA) solutions to support human stakeholders when designing, orchestrating and (self-,socially- or co-) regulating learning in Hybrid Learning (HL). The contributions of H2O Learn consider key requirements for trustworthy Artificial Intelligence (AI), as defined by the European Commission: 1) fostering human (i.e., teachers, learners…) agency; 2) enabling transparency of the Learning Analytics (LA) systems; 3) seeking socio-emotional and inclusive wellbeing; and 4) promoting accountability by enabling the assessment of algorithms and design processes.

Programming Teaching Interaction

Carlos Delgado Kloos, Carmen Fernández-Panadero, Carlos Alario-Hoyos, Pedro M Moreno-Marcos, María Blanca Ibáñez, Pedro J. Muñoz-Merino, Boni García, Iria Estévez-Ayres

There are many applications that help orchestrate face-to-face, online, or hybrid classes through the cloud. Examples are polling apps like Wooclap or Mentimeter, digital boards like Jamboard or Miro, or diagramming tools like diagrams.net, Coggle, or Kialo. However, one can go one step further and integrate some of these tools in order to use the most appropriate tool for each teaching moment and have information flow across tools preserving consistency without having to do this manually. In this paper, we present a specific experience and extrapolate it to highlight the power of programming the teaching interaction.

Transforming the learning experience in pre-service teacher training using the flipped classroom

Camila Barahona, Miguel Nussbaum, Pablo Espinosa, Alejandra Meneses, Carlos Alario-Hoyos, Mar Pérez-Sanagustín

The lack of information and communication technology skills among teachers is highlighted as being one of the main barriers to increasing the use of technology in teaching and learning. This study shows how technology used in a flipped classroom can improve learning among pre-service teachers, as well as boosting perceptions of their own technology skills. The students covered the instructional content before class through videos complemented by formative assessment. The data resulted in a report that the teacher then used to adapt their lecture, as well as defining the questions to be asked using an in-class response system. The responses to these questions were then discussed with the students. The results show that it is possible to change pre-service teachers’ perceptions of using technology in the classroom, both as a student and as a future teacher.

 

A Competency Framework for Teaching and Learning Innovation Centers for the 21st Century: Anticipating the Post-COVID-19 Age

Mar Pérez-Sanagustín, Iouri Kotorov, António Teixeira, Fernanda Mansilla, Julien Broisin, Carlos Alario-Hoyos, Óscar Jerez, Maria do Carmo Teixeira Pinto, Boni García, Carlos Delgado Kloos, Miguel Morales, Mario Solarte, Luis Magdiel Oliva-Córdova, Astrid Helena Gonzalez Lopez

During the COVID-19 pandemic, most Higher Education Institutions (HEIs) across the globe moved towards “emergency online education”, experiencing a metamorphosis that advanced their capacities and competencies as never before. Teaching and Learning Centers (TLCs), the internal units that promote sustainable transformations, can play a key role in making this metamorphosis last. Existing models for TLCs have defined the competencies that they could help develop, focusing on teachers’, students’, and managers’ development, but have mislead aspects such as leadership, organizational processes, and infrastructures. This paper evaluates the PROF-XXI framework, which offers a holistic perspective on the competencies that TLCs should develop for supporting deep and sustainable transformations of HEIs. The framework was evaluated with 83 participants from four Latin American institutions and used for analyzing the transformation of their teaching and learning practices during the pandemic lockdown. The result of the analysis shows that the PROF-XXI framework was useful for identifying the teaching and learning competencies addressed by the institutions, their deficiencies, and their strategic changes. Specifically, this study shows that most institutions counted with training plans for teachers before this period, mainly in the competencies of digital technologies and pedagogical quality, but that other initiatives were created to reinforce them, including students’ support actions.

2021

Educational Pyramids Aligned: Bloom’s Taxonomy, the DigCompEdu Framework and Instructional Designs

Carlos Delgado Kloos, Carlos Alario-Hoyos

There are currently numerous learning theories and methodologies that teachers can use in their classes, depending on their educational goal and the specific subject matter taught. In addition, there are numerous technologies and tools that can help in the implementation of these learning theories and methodologies. This article builds on the Bloom’s taxonomy for the cognitive domain for learners and the DigCompEdu framework of digital competences for educators and defines a classification that organizes instructional design methods with the aim to help educators find the right method for orchestrating their classes. This classification uses the analogy of the pyramid, climbing levels as the student has a more active role in his own learning. The pyramid proposed to organize instructional design methods contains six levels, from the base of the pyramid (lowest level) to the top of the pyramid (highest level): knowledge transfer, interactive knowledge transfer, challenged knowledge, analytic learning, experiential learning, and active learning. This pyramid is intended to put some order into the many learning theories and methodologies that exist.

 

PROF-XXI: Teaching and Learning Centers to Support the 21st Century Professor

Carlos Delgado Kloos, Carlos Alario-Hoyos, Miguel Morales, Rocael Hernández Rizzardini, Óscar Jerez, Mar Pérez-Sanagustín, Iouri Kotorov, S. Alejandra Recinos Fernández, Mario Solarte, Daniel Jaramillo, António Moreira Teixeira, Astrid Helena González López

PROF-XXI is a European-funded project whose aim is the creation of Teaching and Learning Centers (TLCs) for Latin American Higher Institutions in an effort to promote the development of competences for university professors and foster teaching innovation in onsite, but also in online and hybrid education. PROF-XXI includes a partnership of seven higher education institutions, three from European countries (Spain, France, and Portugal), and four from Latin American countries (two from Guatemala, and two from Colombia). This article presents the main results of the first part of the project, including the diagnosis of institutional practices, the state of the art of TLCs around the world, the framework on 21st century professors in Latin America, and the PROF-XXI framework.

 

Conversational agent for supporting learners on a MOOC on programming with Java

Cristina Catalan Aguirre, Nuria Gonzalez Castro, Carlos Delgado Kloos, Carlos Alario-Hoyos, Pedro José Muñoz Merino

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.

 

Can Feedback based on Predictive Data Improve Learners’ Passing Rates in MOOCs? A Preliminary Analysis

Mar Perez-Sanagustin, Ronald Pérez-Álvarez, Jorge Maldonado-Mahauad, Esteban Villalobos, Isabel Hilliger, Josefina Hernández, Diego Sapunar, Pedro Manuel Moreno-Marcos, Pedro J Muñoz-Merino, Carlos Delgado Kloos, Jon Imaz

This work in progress paper investigates if timely feedback increases learners’ passing rate in a MOOC. An experiment conducted with 2,421 learners in the Coursera platform tests if weekly messages sent to groups of learners with the same probability of dropping out the course can improve retention. These messages can contain information about:(1) the average time spent in the course, or (2) the average time per learning session, or (3) the exercises performed, or (4) the video-lectures completed. Preliminary results show that the completion rate increased 12% with the intervention compared with data from 1,445 learners that participated in the same course in a previous session without the intervention. We discuss the limitations of these preliminary results and the future research derived from them.

 

COVID-19 and teacher continuing education: how InnovaT project has supported innovative higher education teaching in Chile and Peru.

L Pasqualin, Liliya Terzieva, C Alario-Hoyos, C Delgado Kloos, R Ticona, MA Maldonado

COVID-19 and teacher continuing education: how InnovaT project has supported innovative higher education teaching in Chile and Peru. — BUas Research Portal Skip to main navigation Skip to search Skip to main content BUas Research Portal Home BUas Research Portal Logo Home Research Units Profiles Research output Activities Press / Media Projects Prizes Datasets Search by expertise, name or affiliation COVID-19 and teacher continuing education: how InnovaT project has supported innovative higher education teaching in Chile and Peru. L Pasqualin, Liliya Terzieva, C Alario, C Kloos, R Ticona, MA Maldonado Academy for Leisure & Events Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review Overview Fingerprint Projects (1) Original language English Title of host publication IRC Proceedings 2021 Editors Dortmund University Place of …

 

Adaptive learning module for a conversational agent to support MOOC learners

Nuria González-Castro, Pedro J Muñoz-Merino, Carlos Alario-Hoyos, Carlos Delgado Kloos

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.

 

Analysing self-regulated learning strategies of MOOC learners through self-reported data

M Elena Alonso-Mencía, Carlos Alario-Hoyos, Iria Estévez-Ayres, Carlos Delgado Kloos

Massive open online courses (MOOCs) require registered learners to be autonomous in their learning. Nevertheless, prior research studies showed that many learners lack the necessary self-regulated learning (SRL) skills to succeed in MOOCs. This research study aimed to gain insights into the relationships that exist between SRL and background information from MOOC learners. To this end, a series of three MOOCs on computer programming offered through edX were used to collect self-reported data from learners using an adaptation of the Motivated Strategies for Learning Questionnaire. Results show significant differences in general learning strategies and motivation by continent, prior computing experience and percentage of completed MOOCs. Men reported higher motivation than women, whereas pre-university learners needed further guidance to improve their learning strategies.

 

Evaluation of an Algorithm for Automatic Grading of Forum Messages in MOOC Discussion Forums

Raquel L Pérez-Nicolás, Carlos Alario-Hoyos, Iria Estévez-Ayres, Pedro Manuel Moreno-Marcos, Pedro J Muñoz-Merino, Carlos Delgado Kloos

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.

 

An Algorithm and a Tool for the Automatic Grading of MOOC Learners from Their Contributions in the Discussion Forum

Sergio García-Molina, Carlos Alario-Hoyos, Pedro Manuel Moreno-Marcos, Pedro J Muñoz-Merino, Iria Estévez-Ayres, Carlos Delgado Kloos

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. View Full-Text

2020

Analyzing learners’ engagement and behavior in MOOCs on programming with the Codeboard IDE

Jesús Manuel Gallego-Romero, Carlos Alario-Hoyos, Iria Estévez-Ayres, Carlos Delgado Kloos

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 …

May 2020

Self-regulated learning in MOOCs: lessons learned from a literature review

M Elena Alonso-Mencía, Carlos Alario-Hoyos, Jorge Maldonado-Mahauad, Iria Estévez-Ayres, Mar Pérez-Sanagustín, Carlos Delgado Kloos

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 …

 

February 2020

Temporal analysis for dropout prediction using self-regulated learning strategies in self-paced MOOCs

Pedro Manuel Moreno-Marcos, Pedro J Munoz-Merino, Jorge Maldonado-Mahauad, Mar Perez-Sanagustin, Carlos Alario-Hoyos, Carlos Delgado Kloos

MOOCs (Massive Open Online Courses) have usually high dropout rates. Many articles have proposed predictive models in order to early detect learners at risk to alleviate this issue. Nevertheless, existing models do not consider complex high-level variables, such as self-regulated learning (SRL) strategies, which can have an important effect on learners’ success. In addition, predictions are often carried out in instructor-paced MOOCs, where contents are released gradually, but not in self-paced MOOCs, where all materials are available from the beginning and users can enroll at any time. For self-paced MOOCs, existing predictive models are limited in the way they deal with the flexibility offered by the course start date, which is learner dependent. Therefore, they need to be adapted so as to predict with little information short after each learner starts engaging with the MOOC. To solve these issues, this paper …

2019

Carlos Alario Hoyos, Iria Manuela Estévez Ayres, Carlos Delgado Kloos Árbol académico, Julio Villena Román, Pedro J. Muñoz Merino, Enrique Llorente Pérez

MOOCs have made it possiblenot only to provide quality open education for any learnerworldwide, but also to rethink theway on-campusteachingis delivered. Thematerials produced for a MOOC canbeconsumed byon-campusstudents beforearriving to the classroom, using class time to do activities that promote active learning, following this way a flippedclassroom strategy. This paper presents the experience of redesigning a first-year engineering course with a large number of students (over 400 each year), in which MOOCs are reused, and a flipped classroom strategy is implemented, dedicatingmost of traditional lecture time to do hands-on, interactive activities. The results show an increase in students’ motivation,both in the use of MOOC content outside the classroom, and in the realization of hands-on, interactive activities inside theclassroom. In relation to the teacher, having information on students’ previous work outside the classroom, and onstudents’ work in the hands-on, interactive activities carried out inside the classroom, allows understanding better thedifferences between groups, tailoring the explanations during class time, and providing proper reinforcement activities tobe done after class.

M. Elena Alonso-Mencía, Carlos Alario-Hoyos, Jorge Maldonado-Mahauad, Iria Estévez-Ayres, Mar Pérez-Sanagustín & Carlos Delgado Kloos

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.
2018

Pedro Manuel Moreno-Marcos, Carlos Alario-Hoyos, Pedro J Munoz-Merino, Iria Estevez-Ayres, Carlos Delgado Kloos

One of the characteristics of MOOCs (Massive Open Online Courses) is that the overall number of social interactions tend to be higher than in traditional courses, hindering the analysis of social learning. Learners typically ask or answer questions using the forum. This makes messages a rich source of information, which can be used to infer learners behaviour and outcomes. It is not feasible for teachers to process all forum messages and automated tools and analysis are required. Although there are some tools for analysing learners interactions, there is a need for methodologies and integrated tools that help to interpret the learning process based on social interactions in the forum. This work presents the 3S (Social, Sentiments, Skills) learning analytics methodology for analysing forum interactions in MOOCs. This methodology considers a temporal analysis combining the social, sentiments and skill dimensions …

Armin Weinberger, Carlos Alario-Hoyos, Poline Bala, Dennis Batangan, Carlos Delgado Kloos, Narayanan Kulathuramaiyer, John Carlo Navera, Josenh Palis, Alwin Melkie Sambul, Peter Sy, Tat-Chee Wan

This Paper explores the current use of Massive Open Online Courses (MOOCs) as a means of educational outreach among identified remote populations in Southeast Asia. Often excluded from traditional educational outreach, these groups are targeted through the COMPETEN-SEA Project, a Capacity Building in Higher Education project funded by the Erasmus+ programme of the European Commission and implemented in partnership with European and Southeast Asian universities. It is hoped that the Project will aid participating Southeast Asian countries address societal needs and attain national development goals.

Cristina Catalán Aguirre, Carlos Delgado Kloos, Carlos Alario-Hoyos, Pedro J Muñoz-Merino

This paper presents an initial design of a conversational agent for educational purposes built for Google Assistant and its first prototype. Recent studies suggest that people will get more and more attached to voice assistant because they can easily use technology without being forced to learn it. Speech recognition might facilitate a more efficient work environment without being overly rigid and overly domineering. Modern frameworks allow harnessing natural language understanding as well a machine learning tools, thereby making it easy to build conversational agents. In this paper, we present first design decisions and a prototype for building an agent for learning Java that complements a MOOC for programming with Java.

Jorge Maldonado-Mahauad, Mar Pérez-Sanagustín, Pedro Manuel Moreno-Marcos, Carlos Alario-Hoyos, Pedro J Muñoz-Merino, Carlos Delgado-Kloos

In the past years, predictive models in Massive Open Online Courses (MOOCs) have focused on forecasting learners’ success through their grades. The prediction of these grades is useful to identify problems that might lead to dropouts. However, most models in prior work predict categorical and continuous variables using low-level data. This paper contributes to extend current predictive models in the literature by considering coarse-grained variables related to Self-Regulated Learning (SRL). That is, using learners’ self-reported SRL strategies and MOOC activity sequence patterns as predictors. Lineal and logistic regression modelling were used as a first approach of prediction with data collected from N = 2,035 learners who took a self-paced MOOC in Coursera. We identified two groups of learners: (1) Comprehensive, who follow the course path designed by the teacher; and (2) Targeting, who seek …

Pedro Manuel Moreno-Marcos, Carlos Alario-Hoyos, Pedro J Muñoz-Merino, Carlos Delgado Kloos

This paper surveys the state of the art on prediction in MOOCs through a Systematic Literature Review (SLR). The main objectives are: (1) to identify the characteristics of the MOOCs used for prediction, (2) to describe the prediction outcomes, (3) to classify the prediction features, (4) to determine the techniques used to predict the variables, and (5) to identify the metrics used to evaluate the predictive models. Results show there is strong interest in predicting dropouts in MOOCs. A variety of predictive models are used, though regression and Support Vector Machines stand out. There is also wide variety in the choice of prediction features, but clickstream data about platform use stands out. Future research should focus on developing and applying predictive models that can be used in more heterogeneous contexts (in terms of platforms, thematic areas, and course durations), on predicting new outcomes and making …

Christian M Stracke, Rocael Hernández, Carlos Delgado Kloos, Mar Pérez Sanagustín, António Moreira Teixeira

Presentation at OE Global 2018, Delft, The Netherlands, by Stracke, C. M., et al. (2018, 24 April) on: «How to make MOOCs better for specific target groups and developing countries?»

Pedro Manuel Moreno-Marcos, Carlos Alario-Hoyos, Pedro J Muñoz-Merino, Iria Estévez-Ayres, Carlos Delgado Kloos

Forum messages in MOOCs (Massive Open Online Courses) are the most important source of information about the social interactions happening in these courses. Forum messages can be analyzed to detect patterns and learners’ behaviors. Particularly, sentiment analysis (e.g., classification in positive and negative messages) can be used as a first step for identifying complex emotions, such as excitement, frustration or boredom. The aim of this work is to compare different machine learning algorithms for sentiment analysis, using a real case study to check how the results can provide information about learners’ emotions or patterns in the MOOC. Both supervised and unsupervised (lexicon-based) algorithms were used for the sentiment analysis. The best approaches found were Random Forest and one lexicon based method, which used dictionaries of words. The analysis of the case study also showed an …

Carlos Alario-Hoyos, Iria Estévez-Ayres, Jesús M Gallego-Romero, Carlos Delgado Kloos, Carmen Fernández-Panadero, Raquel M Crespo-García, Florina Almenares, María Blanca Ibáñez, Julio Villena-Román, Jorge Ruiz-Magaña, Jorge Blasco

Many MOOCs are being designed replicating traditional passive teaching approaches but using video lectures as the means of transmitting information. However, it is well known that learning-by-doing increases retention rates and, thus, allows achieving a more effective learning. To this end, it is worth exploring which tools fit best in the context of each MOOC to enrich learners’ experience, including built-in tools already available in the MOOC platform, and third-party external tools which can be integrated in the MOOC platform. This paper presents an example of the integration of a software development tool, called Codeboard, in three MOOCs which serve as an introduction to programming with Java. We analyze the effect this tool has on learners’ interaction and engagement when running the MOOCs in synchronous (instructor-paced) or asynchronous (self-paced) modes. Results show that the overall use of the …

2017

José A Ruipérez-Valiente, Pedro J Muñoz-Merino, José A Gascón-Pinedo, C Delgado Kloos

The emergence of massive open online courses (MOOCs) has caused a major impact on online education. However, learning analytics support for MOOCs still needs to improve to fulfill requirements of instructors and students. In addition, MOOCs pose challenges for learning analytics tools due to the number of learners, such as scalability in terms of computing time and visualizations. In this work, we present different visualizations of our “Add-on of the learNing AnaLYtics Support for open Edx” (ANALYSE), which is a learning analytics tool that we have designed and implemented for Open edX, based on MOOC features, teacher feedback, and pedagogical foundations. In addition, we provide a technical solution that addresses scalability at two levels: first, in terms of performance scalability, where we propose an architecture for handling massive amounts of data within educational settings; and, second, regarding.

Alario-Hoyos, C., Estévez-Ayres, I., Delgado Kloos, C., Villena-Román, J.

The concept of SPOCs (Small Private Online Courses) emerged as a way of describing the reuse of MOOCs (Massive Open Online Courses) for complementing traditional on-campus teaching. But SPOCs can also drive an entire methodological change to make a better use of face-to-face time between students and teachers in the classroom. This paper presents the redesign and evaluation of a first-year programming course in several engineering degrees, with over 400 students overall, through the reuse of MOOCs as SPOCs on campus, combined with a flipped classroom strategy aimed at promoting active learning. Results from a students’ self-reported questionnaire show a very positive acceptance of the SPOC, which includes both videos and complementary formative activities, and an increase of motivation through the combination of the SPOC and activities implemented in lectures to flip the classroom.

2016

Ruipérez-Valiente, J. A., Muñoz-Merino, P. J., Gascón-Pinedo, J. A., & Kloos, C. D.

The emergence of massive open online courses (MOOCs) has caused a major impact on online education. However, learning analytics support for MOOCs still needs to improve to fulfill requirements of instructors and students. In addition, MOOCs pose challenges for learning analytics tools due to the number of learners, such as scalability in terms of computing time and visualizations. In this work, we present different visualizations of our “Add-on of the learNing AnaLYtics Support for open Edx” (ANALYSE), which is a learning analytics tool that we have designed and implemented for Open edX, based on MOOC features, teacher feedback, and pedagogical foundations. In addition, we provide a technical solution that addresses scalability at two levels: first, in terms of performance scalability, where we propose an architecture for handling massive amounts of data within educational settings; and, second, regarding the representation of visualizations under massiveness conditions, as well as advice on color usage and plot types. Finally, we provide some examples on how to use these visualizations to evaluate student performance and detect problems in resources.

Ruipérez-Valiente, J. A., Muñoz-Merino, P. J., Kloos, C. D., Niemann, K., Scheffel, M., & Wolpers, M

Presentación del Profesor Carlos Delgado Kloos en la Jornada de Educación Abierta celebrada el 11 de marzo de 2013 en la Universidad Carlos III de Madrid en el marco de la Open Education Week promovida por el Consorcio OpenCourseWare.

2015

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