In recent years, research interest in human and non-human behavioral analysis has
increased significantly. One key element in the resulting studies is the use of software
that facilitates comparative analysis of behavioral patterns, such as using T-Pattern and
T-String analysis -TPA- with THEME. Furthermore, all these studies use mixed methods
research. Results from these studies have indicated a certain amount of similarity
between the biological, temporal, and spatial patterns of human social interactions and
the interactions between the contents of their constituent cells. TPA has become an
important, widely-used technique in applied behavioral science research. The objectives
of the current review were: (1) To identify the results of research over the last 4 years
related to the concepts of T-Pattern, TPA, and THEME, since it is in this period in which
more publications on these topics have been detected (2) To examine the key concepts
and areas in the selected articles with respect to those concepts, applying data and text
mining techniques. The results indicate that, over the last 4 years, 20% of the studies
were laboratory focused with non-humans, 18% were in sports environments, 9% were
in psychological therapy environments and 9% were in natural human contexts. There
were also indications that TPA is beginning to be used in workplace environments, which
is a very promising setting for future research in this area., This work was funded through the Asistentes de voz e inteligencia artificial en Moodle: un camino hacia una universidad inteligente-SmartLearnUni- Project selected in the 2020 round of the Spanish Ministerio de Ciencia e Innovación (Proyectos de I+D+i - RTI Tipo B. Reference: PID2020-117111RB-I00).

The use of advanced learning technologies (ALT) techniques in learning management
systems (LMS) allows teachers to enhance self-regulated learning and to carry out the personalized
monitoring of their students throughout the teaching–learning process. However, the application of
educational data mining (EDM) techniques, such as supervised and unsupervised machine learning,
is required to interpret the results of the tracking logs in LMS. The objectives of this work were (1) to
determine which of the ALT resources would be the best predictor and the best classifier of learning
outcomes, behaviours in LMS, and student satisfaction with teaching; (2) to determine whether
the groupings found in the clusters coincide with the students’ group of origin. We worked with
a sample of third-year students completing Health Sciences degrees. The results indicate that the
combination of ALT resources used predict 31% of learning outcomes, behaviours in the LMS, and
student satisfaction. In addition, student access to automatic feedback was the best classifier. Finally,
the degree of relationship between the source group and the found cluster was medium (C = 0.61). It
is necessary to include ALT resources and the greater automation of EDM techniques in the LMS to
facilitate their use by teachers., This research was funded by the MINISTERIO DE CIENCIA E INNOVACIÓN, grant number PID2020-117111RB-I00.

Nowadays, technological teaching tools, such as virtual labs, have become essential,
especially in nursing degrees. These resources help implement practical learning based on selfregulation and it is important to know how satisfied students are with them. This means it is important
to study students’ perceived satisfaction with virtual labs in flipped learning experiences, which was
the general objective of the present study. The aims of the study were: (1) to determine whether there
were significant differences in nursing students’ perceived levels of satisfaction according to the type
of subject or gender; (2) to ascertain what strengths and weaknesses nursing students perceived about
using virtual labs; and (3) to determine the kinds of feelings (positive, negative or neutral) nursing
students had using virtual labs. A mixed research methodology was applied, with a sample of
222 undergraduate nursing students at Burgos University (Spain). There were significant differences
in the satisfaction perceived by students depending on the subject. Students reported medium-high
satisfaction with virtual labs, although they did note that digital skills are needed to use them and
suggested incorporating intelligent assistants. Virtual labs seem to be effective, although further
studies are needed., This work was supported by the Vice-Rectorate for Teaching Staff from University of Burgos (Spain) (grant numbers TVLab_01, 3/02/21) and the Ministry of Science and Innovation of Spain Projects I+D+i Research Challenges (grant number PID2020-117111RB-I00, 01/01/21).

Chatbots are a promising resource for giving students feedback and helping them deploy metacognitive strategies in their learning processes. In this study we worked with a sample of 57 university students, 42 undergraduate and 15 Master's degree students in Health Sciences. A mixed research methodology was applied. The quantitative study analysed the influence of the variables educational level (undergraduate vs. master's degree) and level of prior knowledge on the frequency of chatbot use (low vs. average), learning outcomes, and satisfaction with the chatbot's usefulness. In addition, we examined whether the frequency of chatbot use depended on students' metacognitive strategies. The qualitative study analysed the students' suggestions for improvement to the chatbot and the type of questions it used. The results indicated that the level of degree being studied influenced the frequency of chatbot use and learning outcomes, with Master's students exhibiting higher levels of both, but levels of prior knowledge only influenced learning outcomes. Significant differences were also found in students' perceived satisfaction with the use of the chatbot, with Master's students scoring higher, but not with respect to the level of prior knowledge. No conclusive results were found regarding frequency of chatbot use and the levels of students' metacognitive strategies. Further studies are needed to guide this research based on the students' suggestions for improvement., This work was supported by Ministerio de Ciencia e Innovación [PID2020-117111RB-I00].

Monitoring through the use of eye-tracking technology helps in understanding the cognitive load learners experience when doing tasks. This data gives the teacher and the student important information for improving learning outcomes. This study examined whether students’ participation in a learning virtual laboratory, with a self-regulated video monitored with eye-tracking, would influence their learning outcomes. It also examined whether students’ prior knowledge affected their learning outcomes. Lastly, the study identified clusters related to cognitive load in relevant Areas of Interest vs. non-relevant Areas of Interest. The sample comprised 42 university students of health sciences. The results indicate that participation in the virtual laboratory was related to better learning outcomes. In addition, prior knowledge did not affect cognitive load. A number of different clusters were found related to indicators of cognitive load in relevant and non-relevant AOIs. More applied studies are needed about the effects of monitoring on learning outcomes and on what it means for individualization of learning., his work was supported by the Ministerio de Ciencia e Innovación de España. Proyectos de I + D+i-RTI Tipo B under Grant number [PID2020-117111RB-I00].

Los avances neurotecnológicos están posibilitando en los contextos educativos nuevos conocimientos sobre la forma de
aprender de cada estudiante. No obstante, su aplicación plantea retos para la docencia en contextos naturales. En este
trabajo se presenta un ejemplo de uso y aplicabilidad de la tecnología de seguimiento ocular en el ámbito de la Educación
Superior. Se trabajó con una muestra de 20 estudiantes de tres universidades (Burgos y Valladolid en España y Miño en
Portugal). Los objetivos fueron: 1) comprobar si existían diferencias significativas en indicadores de esfuerzo cognitivo (FC,
FD, SC, PD, VC) hallados con la tecnología de seguimiento ocular entre estudiantes con y sin conocimientos previos; 2)
comprobar si existían clústeres de patrones de conductas de aprendizaje entre los estudiantes; 3) analizar diferencias en la
visualización de los patrones de conducta. Se utilizó un diseño cuasiexperimental sin grupo control y un diseño descriptivo.
Los resultados indicaron diferencias significativas entre los estudiantes con y sin conocimientos previos respecto de los
resultados de aprendizaje. También, se hallaron dos tipos de clústeres en los indicadores de esfuerzo cognitivo. Finalmente,
se efectuó un análisis comparativo sobre los patrones de conducta de aprendizaje en estudiantes del clúster 1 vs. clúster
2. El uso de la tecnología de seguimiento ocular posibilita el registro de un gran volumen de datos respecto del proceso de
aprendizaje. No obstante, en la actualidad su uso en contextos educativos naturales exige al profesorado conocimientos
tecnológicos y de minería de datos., Advances in neuro-technology provide new insights into how individual students learn in educational contexts. However,
applying it poses challenges for teachers in natural settings. This paper presents an example of the use and applicability of
eye-tracking technology in Higher Education. We worked with a sample of 20 students from three universities (Burgos and
Valladolid in Spain and Miño in Portugal). The objectives were: (1) to determine whether there were significant differences
in indicators of cognitive effort (FC, FD, SC, PD, VC) found with eye-tracking technology between students with and
without prior knowledge; (2) to determine whether there were clusters of learning behavior patterns among students; and
(3) to analyze differences in the visualization of behavior patterns. A quasi-experimental design without a control group and
a descriptive design were used. The results indicated significant differences in learning outcomes between students with
and without prior knowledge. In addition, two clusters were found in indicators of cognitive effort. Finally, a comparative
analysis of learning behavior patterns between students in cluster 1 vs. cluster 2 was performed. Eye-tracking technology
makes it possible to record large data about the learning process. However, using it in natural educational settings currently
requires teachers to have technological and data mining skills., Este trabajo se ha desarrollado con la ayuda a dos proyectos de investigación: Proyecto europeo SmartArt 2019-1-ES01-KA204- 095615-Coordinador 6 y «Asistentes de voz e inteligencia artificial en Moodle: un camino hacia una universidad inteligente». Convocatoria 2020 Proyectos de I+D+i - RTI Tipo B. Referencia: PID2020-117111RB-I00.

The study of the use of metacognitive strategies during learning interaction in collaborative groups is considered referential for understanding the development of such strategies. The use of metacognitive strategies is related to better learning outcomes. We monitored the interaction in five collaborative groups at three points in time (initial, intermediate and final). These groups consisted of undergraduate health science (n = 9) and biomedical engineering students (n = 10). The aims were: 1) To check whether there were significant differences in the use of metacognitive strategies between the groups of students monitored depending on the type of degree or the point in time measurement. 2) To test whether there were significant differences in students' learning outcomes depending on whether or not they had participated in the interaction moni-toring during collaborative interaction. Test clustering without a pre-assignment variable against learning outcomes in collaborative groups. Significant differences were detected in the use of some of the metacognitive strategies of orientation, planning and elaboration in favour of the col-laborative groups of Biomedical Engineering students. Also, students who participated in moni-toring collaborative group in both clusters obtained better learning outcomes. Lastly, the assign-ment groups are exactly related to the collaboration groups with respect to the use of metacogni-tive strategies in the final measurement., This research was part of the project “Voice assistants and artificial intelligence in Moodle: a path to a smart university” -SmartLearnUni-. Project number: PID2020-117111RB-I00, funded by Agencia Estatal de Investigación. Ministerio de Ciencia e Innovación y Universidades. Gobierno de España.

Academic leaders all over the world are encouraging the use of active methodologies in teaching, especially in higher education. The reason for this is that social changes are happening at an ever-increasing rate, and they require students and teachers to develop digital skills. This is especially significant for health sciences degrees, in which future graduates must have effective problem-solving skills. To respond to this challenge, the use of a project-based learning (PBL) methodology, together with various monitoring techniques based on the use of Educational Data Mining (EDM) and mixed methods, will provide teachers with information about the effectiveness of the methodology and guide the implementation of personalized educational responses. This study provides a protocol for the application of the PBL methodology in e-Learning and blended-Learning (b-Learning) teaching modalities for health sciences students studying occupational therapy in higher education. In addition, statistical techniques for the analysis of covariance and unsupervised learning allow differences to be detected between the two teaching modalities, thus specifying their effectiveness in terms of a range of variables related to behavioral patterns, performance, and satisfaction. Data visualization also helps in understanding the qualitative aspects of the learning process. These data will help teachers to produce more effective proposals for the implementation of the PBL methodology based on the based on the context of the teaching-learning process. Therefore, this protocol offers many resources and materials to help teachers implement the PBL methodology in e-Learning and bLearning teaching methods., The study was carried out as part of the research project "SmartLearnUni", funded by the Spanish Ministry of Science and Innovation 2020 I+D+i Projects - RTI Type B. Reference: PID2020-117111RB-I00. The authors also gratefully acknowledge the collaboration of the health sciences students at the University of Burgos, especially the students studying for their Occupational Therapy and Nursing degrees.

This dataset contains the data generated during the execution of the project ““Asistentes de voz e inteligencia artificial en Moodle: un camino hacia una universidad inteligente” -SmartLearnUni-”, code PID2020-117111RB-I00, corresponding to the 2021 Call of “Convocatoria 2020 Proyectos de I+D+i - RTI Tipo B. Ministerio de Ciencia e Innovación y Universidades. Agencia Estatal de Investigación. Gobierno de España para el período 2021-2024"., The research work conducted within the framework of the REWIND project (PID2020-117111RB-I00), which was funded by the Ministry of Science and Innovation of the Government of Spain (Ministerio de Ciencia e Innovación del Gobierno de España), the State Research Agency (Agencia Estatal de Investigación, AEI), through the 2020 Call of " Proyectos de I+D+i - RTI Tipo B para el período 01/01/2021 28/02/2025".