https://hdl.handle.net/10259/4220 2026-10-13T07:34:14Z https://hdl.handle.net/10259/12208 Exploring age-related differences in immersive Virtual Reality experiences for Cultural Heritage Rodríguez García, Bruno; Miguel Alonso, Inés; Checa Cruz, David; Bustillo Iglesias, Andrés Immersive Virtual Reality (iVR) has reached a level of technological maturity that enables its use for the general public. However, further investigation is needed into the optimization of iVR applications and particularly, their design features in relation to various user characteristics such as age and previous iVR experience. To solve this issue, this study evaluates a Cultural Heritage dissemination experience in iVR, tested in a real-world setting, the Museum of Burgos (Spain), with participants from three age groups: children, young adults, and older adults. The iVR experience was structured in four levels of progressively complex interaction. A control group was formed to view a video containing the same dissemination content. A total of 206 participants completed a three-steps assessment measuring prior knowledge, User Experience (UX), and learning outcomes. The findings emphasized that iVR's strengths, immersion and interactivity, must be strategically optimized to outperform more well-stablished dissemination formats like video. The results showed that children responded positively to high interactivity; their motivation and rapid adaptation supported the use of interactive formats, provided cognitive demands are gradually introduced. Young adults exhibited the highest adaptability and fastest completion times, performing well across all interaction types, though with moderate UX ratings. Older adults preferred soft interaction and immersive aesthetics, achieving better learning outcomes in this context but extending the time to complete the iVR experience. 2026-09-01T00:00:00Z https://hdl.handle.net/10259/11961 Activity and Dropout Tracking in Moodle Using UBUMonitor Application Ji, Yi Peng; Marticorena Sánchez, Raúl; Pardo Aguilar, Carlos; López Nozal, Carlos; Juez Gil, Mario Teaching with online learning platforms should simplify the monitoring of students’ activity, particularly when evaluating student dropout. Popular learning environments such as Moodle should implement visual analytic tools that facilitate such tasks, nevertheless, institutions are usually reluctant to incorporate them. This paper presents UBUMonitor, a desktop application that allows the visualization of student’s activity data, extended as a proof of concept with a module for dropout tracking. Therefore, by using UBUMonitor, teachers will be able to easily visualize their students’ engagement with their subject, which can facilitate early action to prevent students from dropping out more effectively. 2022-08-01T00:00:00Z https://hdl.handle.net/10259/11886 The role of awareness and gamification on technical debt management Crespo, Yania; López Nozal, Carlos; Marticorena Sánchez, Raúl; Gonzalo Tasis, Margarita; Piattini, Mario Managing technical debt and developing easy-tomaintain software are very important aspects for technological companies. Integrated development environments (IDEs) and static measurement and analysis tools are used for this purpose. Meanwhile, gamification also is gaining popularity in professional settings, particularly in software development. Objective. This paper aims to analyse the improvement in technical debt indicators due to the use of techniques to raise developers’ awareness of technical debt and the introduction of gamification into technical debt management. Method. A quasi-experiment that manipulates a training environment with three different treatments was conducted. The first treatment was based on training in the concept of technical debt, bad smells and refactoring, while using multiple plugins in IDEs to obtain reports on quality indicators of both the code and the tests. The second treatment was based on enriching previous training with the use of SonarQube to continuously raise awareness of technical debt. The third was based on adding a gamification component to technical debt management based on a contest with a top ten ranking. The results of the first treatment are compared with the use of SonarQube for continuously raising developers’ awareness of technical debt; while the possible effect of gamification is compared with the results of the previous treatment. Results. It was observed that continuously raising awareness using a technical debt management tool, such as SonarQube, significantly improves the technical debt indicators of the code developed by the participants versus using multiple code and test quality checking tools. On the other hand, incorporating some kind of competition between developers by defining a contest and creating a ranking does not bring about any significant differences in the technical debt indicators. Conclusions. Investment in staff training through tools to raise developers’ awareness of technical debt and incorporating it into continuous integration pipelines does bring improvements in technical debt management. 2022-10-01T00:00:00Z https://hdl.handle.net/10259/11884 Processing and analysis of portable EEG data for cognitive load assessment in neurotypical university students Sáiz Manzanares, María Consuelo; Ortega Renuncio, Raúl; Marticorena Sánchez, Raúl The use of electroencephalogram (EEG) to gain insight into cognitive and metacognitive processing during task execution is being pioneered in natural learning contexts; an opportunity not without its challenges. Accordingly, a pilot study was conducted to explore the feasibility of this approach. The aims of this study were: (1) to demonstrate how raw data extracted from an EEG device may be processed; (2) to determine whether there were differences in pre-task cognitive load between senior university students (Group 1), novice university teachers (Group 2) and experienced university teachers (Group 3); (3) To determine whether the peak power (μV2) per brain band (Delta, Theta, Alpha, Beta and Gamma) recorded during task performance was different depending on the type of participant; (4) To determine whether there were un-labelled groupings (clusters), and whether they corresponded to the type of participant. The raw data were processed using the MNE-Python toolkit. No significant differences were found in the perception of cognitive load or in peak power with respect to participant type. However, different frequencies of maximum activation of brain channels in the Delta wave were found by participant type. The largest overlaps were found between Group 1 and Group 2. Future studies will address the influence of other variables such as age, gender, type of studies and cranial tomography. In addition, 3D analyses with integration of brain surfaces and sensors will be applied. 2026-03-01T00:00:00Z