Search

Your search keyword '"López Pernas, Sonsoles"' showing total 243 results
Start Over Author "López Pernas, Sonsoles"
243 results on '"López Pernas, Sonsoles"'

1. Empowering Database Learning Through Remote Educational Escape Rooms

Author

Barra, Enrique, López-Pernas, Sonsoles, Gordillo, Aldo, Pozo, Alejandro, Muñoz-Arcentales, Andres, and Conde, Javier

Subjects
Computer Science - Computers and Society, Computer Science - Databases
Abstract

Learning about databases is indispensable for individuals studying software engineering or computer science or those involved in the IT industry. We analyzed a remote educational escape room for teaching about databases in four different higher education courses in two consecutive academic years. We employed three instruments for evaluation: a pre- and post-test to assess the escape room's effectiveness for student learning, a questionnaire to gather students' perceptions, and a Web platform that unobtrusively records students' interactions and performance. We show novel evidence that educational escape rooms conducted remotely can be engaging as well as effective for teaching about databases.

Published
2024
Full Text
View/download PDF

2. Have Learning Analytics Dashboards Lived Up to the Hype? A Systematic Review of Impact on Students' Achievement, Motivation, Participation and Attitude

Author

Kaliisa, Rogers, Misiejuk, Kamila, López-Pernas, Sonsoles, Khalil, Mohammad, and Saqr, Mohammed

Subjects
Computer Science - Human-Computer Interaction, Computer Science - Computers and Society, 97U50, 97D60
Abstract

While learning analytics dashboards (LADs) are the most common form of LA intervention, there is limited evidence regarding their impact on students learning outcomes. This systematic review synthesizes the findings of 38 research studies to investigate the impact of LADs on students' learning outcomes, encompassing achievement, participation, motivation, and attitudes. As we currently stand, there is no evidence to support the conclusion that LADs have lived up to the promise of improving academic achievement. Most studies reported negligible or small effects, with limited evidence from well-powered controlled experiments. Many studies merely compared users and non-users of LADs, confounding the dashboard effect with student engagement levels. Similarly, the impact of LADs on motivation and attitudes appeared modest, with only a few exceptions demonstrating significant effects. Small sample sizes in these studies highlight the need for larger-scale investigations to validate these findings. Notably, LADs showed a relatively substantial impact on student participation. Several studies reported medium to large effect sizes, suggesting that LADs can promote engagement and interaction in online learning environments. However, methodological shortcomings, such as reliance on traditional evaluation methods, self-selection bias, the assumption that access equates to usage, and a lack of standardized assessment tools, emerged as recurring issues. To advance the research line for LADs, researchers should use rigorous assessment methods and establish clear standards for evaluating learning constructs. Such efforts will advance our understanding of the potential of LADs to enhance learning outcomes and provide valuable insights for educators and researchers alike.

Published
2023

4. Modeling Digital Twin Data and Architecture: A Building Guide with FIWARE as Enabling Technology

Author

Conde, Javier, Munoz-Arcentales, Andrés, Alonso, Álvaro, López-Pernas, Sonsoles, and Salvachúa, Joaquín

Subjects
Computer Science - Computers and Society
Abstract

The use of Digital Twins in the industry has become a growing trend in recent years, allowing to improve the lifecycle of any process by taking advantage of the relationship between the physical and the virtual world. Existing literature formulates several challenges for building Digital Twins, as well as some proposals for overcoming them. However, in the vast majority of the cases, the architectures and technologies presented are strongly bounded to the domain where the Digital Twins are applied. This article proposes the FIWARE Ecosystem, combining its catalog of components and its Smart Data Models, as a solution for the development of any Digital Twin. We also provide a use case to showcase how to use FIWARE for building Digital Twins through a complete example of a Parking Digital Twin. We conclude that the FIWARE Ecosystem constitutes a real reference option for developing DTs in any domain., Comment: 7 pages, 3 figures

Published
2023
Full Text
View/download PDF

5. A modern approach to transition analysis and process mining with Markov models: A tutorial with R

Author

Helske, Jouni, Helske, Satu, Saqr, Mohammed, López-Pernas, Sonsoles, and Murphy, Keefe

Subjects
Statistics - Methodology, Computer Science - Computers and Society, 60J10
Abstract

This chapter presents an introduction to Markovian modeling for the analysis of sequence data. Contrary to the deterministic approach seen in the previous sequence analysis chapters, Markovian models are probabilistic models, focusing on the transitions between states instead of studying sequences as a whole. The chapter provides an introduction to this method and differentiates between its most common variations: first-order Markov models, hidden Markov models, mixture Markov models, and mixture hidden Markov models. In addition to a thorough explanation and contextualization within the existing literature, the chapter provides a step-by-step tutorial on how to implement each type of Markovian model using the R package seqHMM. The chaper also provides a complete guide to performing stochastic process mining with Markovian models as well as plotting, comparing and clustering different process models.

Published
2023

6. An introduction and tutorial to model-based clustering in education via Gaussian mixture modelling

Author

Scrucca, Luca, Saqr, Mohammed, López-Pernas, Sonsoles, and Murphy, Keefe

Subjects
Statistics - Methodology, 62H30
Abstract

Heterogeneity has been a hot topic in recent educational literature. Several calls have been voiced to adopt methods that capture different patterns or subgroups within students behavior or functioning. Assuming that there is an average pattern that represents the entirety of student populations requires the measured construct to have the same causal mechanism, same development pattern, and affect students in exactly the same way. Using a person-centered method (Finite Gaussian mixture model or latent profile analysis), the present tutorial shows how to uncover the heterogeneity within engagement data by identifying three latent or unobserved clusters. This chapter offers an introduction to the model-based clustering that includes the principles of the methods, a guide to choice of number of clusters, evaluation of clustering results and a detailed guide with code and a real-life dataset. The discussion elaborates on the interpretation of the results, the advantages of model-based clustering as well as how it compares with other methods.

Published
2023

28. The Curious Case of Centrality Measures: A Large-Scale Empirical Investigation

Author

Saqr, Mohamm and López-Pernas, Sonsoles

Abstract

There has been extensive research using centrality measures in educational settings. One of the most common lines of such research has tested network centrality measures as indicators of success. The increasing interest in centrality measures has been kindled by the proliferation of learning analytics. Previous works have been dominated by single-course case studies that have yielded inconclusive results regarding the consistency and suitability of centrality measures as indicators of academic achievement. Therefore, large-scale studies are needed to overcome the multiple limitations of existing research (limited datasets, selective and reporting bias, as well as limited statistical power). This study aims to empirically test and verify the role of centrality measures as indicators of success in collaborative learning. For this purpose, we attempted to reproduce the most commonly used centrality measures in the literature in all the courses of an institution over five years of education. The study included a large dataset (n=3,277) consisting of 69 course offerings, with similar pedagogical underpinnings, using meta-analysis as a method to pool the results of different courses. Our results show that degree and eigenvector centrality measures can be a consistent indicator of performance in collaborative settings. Betweenness and closeness centralities yielded uncertain predictive intervals and were less likely to replicate. Our results have shown moderate levels of heterogeneity, indicating some diversity of the results comparable to single laboratory replication studies. [Note: The appendix pages are not included in the page range since they are unnumbered.]

Published
2022

29. The Dynamics of Students’ Playing Profiles in a Programming Educational Escape Room

Author

López-Pernas, Sonsoles, Gordillo, Aldo, Barra, Enrique, Saqr, Mohammed, Huang, Ronghuai, Series Editor, Kinshuk, Series Editor, Jemni, Mohamed, Series Editor, Chen, Nian-Shing, Series Editor, Spector, J. Michael, Series Editor, Gonçalves, José Alexandre de Carvalho, editor, Lima, José Luís Sousa de Magalhães, editor, Coelho, João Paulo, editor, García-Peñalvo, Francisco José, editor, and García-Holgado, Alicia, editor

Published
2024
Full Text
View/download PDF

30. Mapping the Topics, Trends, and Themes of Education Technology in Legal Education with Topic Modeling and Network Analysis

Author

Huhta, Kaisa, López-Pernas, Sonsoles, Saqr, Mohammed, Huang, Ronghuai, Series Editor, Kinshuk, Series Editor, Jemni, Mohamed, Series Editor, Chen, Nian-Shing, Series Editor, Spector, J. Michael, Series Editor, Gonçalves, José Alexandre de Carvalho, editor, Lima, José Luís Sousa de Magalhães, editor, Coelho, João Paulo, editor, García-Peñalvo, Francisco José, editor, and García-Holgado, Alicia, editor

Published
2024
Full Text
View/download PDF

31. More Data is not Always Better Data: An Exploratory Learning Analytics Study in Early Prediction

Author

Rai, Pranuj, López-Pernas, Sonsoles, Elmoazen, Ramy, Saqr, Mohammed, Huang, Ronghuai, Series Editor, Kinshuk, Series Editor, Jemni, Mohamed, Series Editor, Chen, Nian-Shing, Series Editor, Spector, J. Michael, Series Editor, Gonçalves, José Alexandre de Carvalho, editor, Lima, José Luís Sousa de Magalhães, editor, Coelho, João Paulo, editor, García-Peñalvo, Francisco José, editor, and García-Holgado, Alicia, editor

Published
2024
Full Text
View/download PDF

32. How a Learning Analytics Dashboard Intervention Influences the Dynamics of Students’ Learning Behavior

Author

Akçapınar, Gökhan, López-Pernas, Sonsoles, Er, Erkan, Saqr, Mohammed, Huang, Ronghuai, Series Editor, Kinshuk, Series Editor, Jemni, Mohamed, Series Editor, Chen, Nian-Shing, Series Editor, Spector, J. Michael, Series Editor, Gonçalves, José Alexandre de Carvalho, editor, Lima, José Luís Sousa de Magalhães, editor, Coelho, João Paulo, editor, García-Peñalvo, Francisco José, editor, and García-Holgado, Alicia, editor

Published
2024
Full Text
View/download PDF

33. Why Learning and Teaching Learning Analytics is Hard: An Experience from a Real-Life LA Course Using LA Methods

Author

Saqr, Mohammed, López-Pernas, Sonsoles, Huang, Ronghuai, Series Editor, Kinshuk, Series Editor, Jemni, Mohamed, Series Editor, Chen, Nian-Shing, Series Editor, Spector, J. Michael, Series Editor, Gonçalves, José Alexandre de Carvalho, editor, Lima, José Luís Sousa de Magalhães, editor, Coelho, João Paulo, editor, García-Peñalvo, Francisco José, editor, and García-Holgado, Alicia, editor

Published
2024
Full Text
View/download PDF

35. Data fusion and homogenization

Author

Munoz-Arcentales, Andres, primary, Conde, Javier, additional, Alonso, Álvaro, additional, Salvachúa, Joaquín, additional, Velasquez, Washington, additional, and López-Pernas, Sonsoles, additional

Published
2024
Full Text
View/download PDF

36. Contributors

Author

Alexeev, Dmitriy, primary, Alonso, Álvaro, additional, Andreou, Andreas, additional, Arcas, Francisco, additional, Arukwe, Christopher, additional, Charitonidou, Marianna, additional, Chen, Zheyi, additional, Conde, Javier, additional, Danielescu, Andreea, additional, Dhivyaprabha, T.T., additional, Evans, Leighton, additional, Gajdošík, Tomáš, additional, Gajdošíková, Zuzana, additional, Hussaini, Adamu, additional, Krishnaveni, M., additional, Kumar, P.V. Hareesh, additional, Lakshminarayana, S., additional, Lekshmi, S., additional, Liang, Hengshuo, additional, Liao, Weixian, additional, López-Pernas, Sonsoles, additional, Lu, Chao, additional, Lyu, Zhihan, additional, Maheshwari, Aditi, additional, Marciš, Matúš, additional, Markakis, Evangelos K., additional, Mavromoustakis, Constandinos X., additional, McKenna, H. Patricia, additional, Muñoz, Andres, additional, Munoz-Arcentales, Andres, additional, Ndaguba, Emeka, additional, Pańkowska, Małgorzata, additional, Qian, Cheng, additional, Qian, Mian, additional, Rzeszewski, Michal, additional, Salvachúa, Joaquín, additional, Shchekochikhin, Oleg, additional, Shvedenko, Valeria, additional, Shvedenko, Vladimir N., additional, Sidhu, Navjot, additional, Sree Lakshmi, G., additional, Subashini, P., additional, Terroso-Saenz, Fernando, additional, Tian, Pu, additional, Velasquez, Washington, additional, Vilenskii, Mikhail, additional, Xu, Guobin, additional, Yu, Wei, additional, and Żytniewski, Mariusz, additional

Published
2024
Full Text
View/download PDF

38. The Temporal Dynamics of Online Problem-Based Learning: Why and When Sequence Matters

Author

Saqr, Mohamm and López-Pernas, Sonsoles

Abstract

Early research on online PBL explored student satisfaction, effectiveness, and design. The temporal aspect of online PBL has rarely been addressed. Thus, a gap exists in our knowledge regarding how online PBL unfolds: when and for how long a group engages in collaborative discussions. Similarly, little is known about whether and what sequence of interactions could predict higher achievement. This study aims to bridge such a gap by implementing the latest advances in temporal learning analytics to analyze the sequential and temporal aspects of online PBL across a large sample (n = 204 students) of qualitatively coded interactions (8,009 interactions). We analyzed interactions at the group level to understand the group dynamics across whole problem discussions, and at the student level to understand the students' contribution dynamics across different episodes. We followed such analyses by examining the association of interaction types and the sequences thereof with students' performance using multilevel linear regression models. The analysis of the interactions reflected that the scripted PBL process is followed a logical sequence, yet often lacked enough depth. When cognitive interactions (e.g., arguments, questions, and evaluations) occurred, they kindled high cognitive interactions, when low cognitive and social interactions dominated, they kindled low cognitive interactions. The order and sequence of interactions were more predictive of performance, and with a higher explanatory power as compared to frequencies. Starting or initiating interactions (even with low cognitive content) showed the highest association with performance, pointing to the importance of initiative and sequencing.

Published
2023
Full Text
View/download PDF

39. Learning Analytics to Explore the Motivational Profiles of Non-Traditional Practical Nurse Students: A Mixed-Methods Approach

Author

Kleimola, Riina, López-Pernas, Sonsoles, Väisänen, Sanna, Saqr, Mohamm, Sointu, Erkko, and Hirsto, Laura

Abstract

Learning analytics provides a novel means to examine various aspects of students' learning and to support them in their individual endeavors. The purpose of this study was to explore the potential of learning analytics to provide insights into non-traditional, vocational practical nurse students' (N = 132) motivational profiles for choosing their studies, using a mixed-methods approach. Non-traditional students were somewhat older learners than those following a more straightforward educational pathway and had diverse educational or professional backgrounds. Institutional admission data and analytics were used to identify their specific study motives and distinct motivational profiles, and to illustrate the connections between the motives emerging in the motivational profiles. Furthermore, the association between the motivational profiles and study performance was examined. The results of qualitative content analysis indicated that non-traditional practical nurse students pursued such specialized training for various reasons, and that pragmatic, professional rationales were emphasized over prosocial, altruistic factors. Through the adoption of person-centered latent class analysis, three motivational profiles were identified: self-aware goal-achievers, qualification attainers, and widely oriented humanitarians. Additionally, the analyses of epistemic networks for the profiles showed the complex interplay between the motives, confirming that some motive connections appear to be more prominent than others. Moreover, the findings indicated that study motives reported at admission did not seem to dictate students' later study performance, as no statistically significant associations were found between the motivational profile and the students' final grade point average or study dropout. This investigation paves the way for more-targeted motivational support and the use of learning analytics in the context of vocational education and training.

Published
2023
Full Text
View/download PDF

45. Computing Education Research in Finland

Author

Malmi, Lauri, Hellas, Arto, Ihantola, Petri, Isomöttönen, Ville, Jormanainen, Ilkka, Kilamo, Terhi, Knutas, Antti, Korhonen, Ari, Laakso, Mikko-Jussi, López-Pernas, Sonsoles, Poranen, Timo, Salakoski, Tapio, Suhonen, Jarkko, Apiola, Mikko, editor, López-Pernas, Sonsoles, editor, and Saqr, Mohammed, editor

Published
2023
Full Text
View/download PDF

46. Computing Education Research in Schools

Author

Dagienė, Valentina, Gülbahar, Yasemin, Grgurina, Natasa, López-Pernas, Sonsoles, Saqr, Mohammed, Apiola, Mikko, Stupurienė, Gabrielė, Apiola, Mikko, editor, López-Pernas, Sonsoles, editor, and Saqr, Mohammed, editor

Published
2023
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results