Luisa M. Regueras

651 total citations
26 papers, 417 citations indexed

About

Luisa M. Regueras is a scholar working on Computer Science Applications, Education and Artificial Intelligence. According to data from OpenAlex, Luisa M. Regueras has authored 26 papers receiving a total of 417 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Computer Science Applications, 11 papers in Education and 9 papers in Artificial Intelligence. Recurrent topics in Luisa M. Regueras's work include Online Learning and Analytics (13 papers), Intelligent Tutoring Systems and Adaptive Learning (8 papers) and Educational Technology and Assessment (7 papers). Luisa M. Regueras is often cited by papers focused on Online Learning and Analytics (13 papers), Intelligent Tutoring Systems and Adaptive Learning (8 papers) and Educational Technology and Assessment (7 papers). Luisa M. Regueras collaborates with scholars based in Spain, Israel and Portugal. Luisa M. Regueras's co-authors include María Pérez, Elena Verdú, Juan Pablo de Castro Fernández, María Fé Muñoz-Moreno, José Paulo Leal, Ricardo Queirós, Alfredo Corell, Ricardo Garcı́a, Eran Gal and Javier de Castro and has published in prestigious journals such as PLoS ONE, Expert Systems with Applications and IEEE Access.

In The Last Decade

Luisa M. Regueras

24 papers receiving 386 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Luisa M. Regueras Spain 11 217 134 126 123 107 26 417
Juan Pablo de Castro Fernández Spain 11 204 0.9× 124 0.9× 118 0.9× 121 1.0× 102 1.0× 30 418
Bin‐Shyan Jong Taiwan 10 116 0.5× 133 1.0× 138 1.1× 98 0.8× 28 0.3× 34 382
Janice L. Pearce United States 9 204 0.9× 35 0.3× 70 0.6× 90 0.7× 59 0.6× 38 386
I‐Han Hsiao United States 14 438 2.0× 110 0.8× 232 1.8× 182 1.5× 227 2.1× 65 679
Derick Leony Spain 8 220 1.0× 138 1.0× 70 0.6× 87 0.7× 54 0.5× 21 348
Yen‐Teh Hsia Taiwan 10 84 0.4× 128 1.0× 122 1.0× 96 0.8× 62 0.6× 28 335
Christine Prasad New Zealand 6 416 1.9× 97 0.7× 171 1.4× 168 1.4× 79 0.7× 6 497
Wilkerson L. Andrade Brazil 12 223 1.0× 72 0.5× 51 0.4× 142 1.2× 64 0.6× 64 427
Tsong‐Wuu Lin Taiwan 10 69 0.3× 118 0.9× 106 0.8× 80 0.7× 31 0.3× 34 359
Jun‐Ming Su Taiwan 11 169 0.8× 44 0.3× 74 0.6× 197 1.6× 110 1.0× 49 397

Countries citing papers authored by Luisa M. Regueras

Since Specialization
Citations

This map shows the geographic impact of Luisa M. Regueras's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Luisa M. Regueras with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Luisa M. Regueras more than expected).

Fields of papers citing papers by Luisa M. Regueras

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Luisa M. Regueras. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Luisa M. Regueras. The network helps show where Luisa M. Regueras may publish in the future.

Co-authorship network of co-authors of Luisa M. Regueras

This figure shows the co-authorship network connecting the top 25 collaborators of Luisa M. Regueras. A scholar is included among the top collaborators of Luisa M. Regueras based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Luisa M. Regueras. Luisa M. Regueras is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Regueras, Luisa M., et al.. (2025). Techno-Pedagogical Approaches and Academic Performance: A Quantitative Study Based on LMS Log Data. Education Sciences. 15(11). 1533–1533.
2.
Pérez, María, Luisa M. Regueras, Juan Pablo de Castro Fernández, & Elena Verdú. (2023). Clustering of LMS Use Strategies with Autoencoders. Applied Sciences. 13(12). 7334–7334. 1 indexed citations
3.
Regueras, Luisa M., María Pérez, & Juan Pablo de Castro Fernández. (2022). A Rule-Based Expert System for Teachers’ Certification in the Use of Learning Management Systems.. International Journal of Interactive Multimedia and Artificial Intelligence. 7(7). 75–81. 1 indexed citations
4.
Pérez, María, Juan Pablo de Castro Fernández, Luisa M. Regueras, & Alfredo Corell. (2021). MSocial: Practical Integration of Social Learning Analytics Into Moodle. IEEE Access. 9. 23705–23716. 10 indexed citations
5.
Regueras, Luisa M., María Pérez, Juan Pablo de Castro Fernández, & Elena Verdú. (2019). Clustering Analysis for Automatic Certification of LMS Strategies in a University Virtual Campus. IEEE Access. 7. 137680–137690. 9 indexed citations
6.
Henning, Peter A., Elena Verdú, Luisa M. Regueras, et al.. (2018). Learning pathway recommendation based on a pedagogical ontology and its implementation in Moodle. peDOCS. 39–50. 4 indexed citations
7.
Corell, Alfredo, Luisa M. Regueras, Elena Verdú, María Pérez, & Juan Pablo de Castro Fernández. (2018). Effects of competitive learning tools on medical students: A case study. PLoS ONE. 13(3). e0194096–e0194096. 40 indexed citations
8.
Garcı́a, Ricardo, Elena Verdú, Luisa M. Regueras, Juan Pablo de Castro Fernández, & María Pérez. (2013). A neural network based intelligent system for tile prefetching in web map services. Expert Systems with Applications. 40(10). 4096–4105. 10 indexed citations
9.
Fernández, Juan Pablo de Castro, et al.. (2012). An OLS regression model for context-aware tile prefetching in a web map cache. International Journal of Geographical Information Systems. 27(3). 614–632. 15 indexed citations
10.
Verdú, Elena, María Pérez, Luisa M. Regueras, Juan Pablo de Castro Fernández, & Ricardo Garcı́a. (2012). A genetic fuzzy expert system for automatic question classification in a competitive learning environment. Expert Systems with Applications. 39(8). 7471–7478. 33 indexed citations
11.
Verdú, Elena, Luisa M. Regueras, María Pérez, et al.. (2011). A distributed system for learning programming on-line. Computers & Education. 58(1). 1–10. 78 indexed citations
12.
Verdú, Elena, Luisa M. Regueras, María Pérez, & Juan Pablo de Castro Fernández. (2010). Estimating the difficulty level of the challenges proposed in a competitive e-learning environment. 225–234. 4 indexed citations
13.
Verdú, Elena, María Pérez, Luisa M. Regueras, & Juan Pablo de Castro Fernández. (2010). A Diversity-Enhanced Genetic Algorithm to Characterize the Questions of a Competitive e-Learning System. 5. 25–29. 1 indexed citations
14.
Regueras, Luisa M., Elena Verdú, María Pérez, & Juan Pablo de Castro Fernández. (2010). Design of a Competitive and Collaborative Learning Strategy in a Communication Networks Course. IEEE Transactions on Education. 54(2). 302–307. 30 indexed citations
15.
Verdú, Elena, et al.. (2008). An analysis of the research on adaptive learning: the next generation of e-learning. WSEAS Transactions on Information Science and Applications archive. 5(6). 859–868. 30 indexed citations
16.
Verdú, Elena, et al.. (2008). APPLICATION OF INTELLIGENT ADAPTIVE SYSTEMS IN A COMPETITIVE LEARNING ENVIRONMENT. 273–275.
17.
Verdú, Elena, et al.. (2008). Is Adaptive Learning Effective? A Review of the Research. 13 indexed citations
18.
Regueras, Luisa M., et al.. (2007). An applied project of ICT-based active learning for the new model of university education. International Journal of Continuing Engineering Education and Life-Long Learning. 17(6). 447–447. 2 indexed citations
19.
Verdú, Elena, et al.. (2006). Quest: a contest-based approach to technology-enhanced active learning in higher education. 10–15. 3 indexed citations
20.
Regueras, Luisa M., et al.. (2002). An internetworking proposal for industrial estates: HFC networks as access solution for SMEs. 2. 868–871. 1 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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