New technologies

In Praise of Empathic AI (2024). Trends in Cognitive Sciences (UK, Q1)
In this article, we investigate the social implications of empathetic artificial intelligence (AI) and ask how people feel about its seemingly empathetic expressions. We highlight AI's unique ability to simulate empathy without the same biases that plague humans. While we acknowledge serious obstacles, we propose that AI's expressions of empathy could improve human well-being.

Analyzing interactions in virtual areas: a methodological proposal (2023) Pedagogical Studies (Chile, Q3)
The contingency caused by SARS COV-2 in 2020 and 2021 has led to the widespread use of technology-mediated education and the implementation of specific strategies to address the teaching-learning process in virtual classrooms. The study of interactions in a virtual classroom is a new field of research focused on how the constituent elements of teaching practice develop in this context. This article offers a methodological proposal for analyzing interactions in virtual classrooms based on the contributions of virtual ethnography and the interactionist approaches of Isabelle Vinatier. The proposal is structured in three stages: the ethnographic recording of virtual exchanges, the interactionist analysis of virtual teaching practice, and the presentation of a case study. The essay concludes with reflections on the contributions of Vinatier's interactionist model to the analysis of virtual classrooms.

The potential of immersive virtual reality to improve learning: A meta-analysis (2022). Educational Research Review (United Kingdom, Q1)
Research into the impact of immersive virtual reality (IVR) technology on learning has become necessary with the decline in the cost of virtual reality technologies and the development of high-quality head-mounted displays. This meta-analysis investigates the overall effect size by combining the results of primary experimental studies that reveal the effect of IVR on learning outcomes. In addition, effect sizes were calculated based on measurement timing, measurement types, educational level, field of education, control group educational resources, and immersion type subgroups. One hundred and five independent outcomes were calculated from 48 primary studies published between 2016 and September 2020, including 39 randomized controlled trials and nine quasi-experimental studies. The sample size of the primary studies includes 3,179 students, 847 from K12 and 2,332 from higher education. A random effects model was used to calculate the effect size. As a result of the meta-analysis, the overall effect size on VR-I learning outcomes was found to be small (g = 0.38). Furthermore, according to the results of the subgroup analysis, it was revealed that I-VR significantly differentiated the effect size depending on the educational level, field of education, and computer/traditional sources. There were no significant differences depending on the other subgroups.

The role of generative artificial intelligence in scientific publishing (2024). Educación XX1 (Spain, Q2)
Although artificial intelligence is not a new technology, over the last year it has become extraordinarily popular, and its use is expanding into various areas of our lives. Tools such as ChatGPT, Microsoft Copilot, Google Bard, Llama, DALL·E, and HeyGen, among many others, have sparked considerable interest due to their ability to automatically generate various types of content (text, images, videos, etc.) in response to certain instructions. This interest is justified by the potential of these technologies to reduce the workload devoted to superfluous tasks, which would lead to increased productivity. This enthusiasm has also spread to the field of scientific production, where it is hoped that generative artificial intelligence (GAI) systems will improve the processes of writing, reviewing, and publishing scientific papers. However, their use also raises a number of ethical dilemmas that, as editors of scientific journals, we must consider in our task of ensuring the integrity, accuracy, and transparency of published research. It is therefore essential that editorial teams establish clear editorial policies aimed at promoting the ethical and responsible use of generative artificial intelligence during the preparation and review of publications. To this end, we will reflect below on the potential, implications, and limitations of incorporating AI-based tools into the various activities involved in the scientific publication process.

Indicators of effectiveness in preventing ICT addiction: Clickeando, case study (2024). Spanish Journal of Pedagogy (Q2).
There are not many ICT addiction prevention programs, and even fewer that have been scientifically validated. Preventing ICT addiction is key to government mental health policies for adolescents. Clickeando is a universal school program for the prevention of ICT addiction in adolescents. It has been running for fourteen years and has been designed based on the quality indicators highlighted for this type of program. Since 2020, Clickeando has been evaluating its participants in order to link the efforts of preventive agencies and agents, which has made it possible to assess the effects of the program on its target population in the present study. The main results indicate that the program succeeds in producing changes in ICT use, mainly through a decrease in addictive mobile phone use among both girls and boys in secondary school. At the same time, there are behaviors that have a significant impact on the development of addictive patterns that should be targeted in future modifications of the workshop (such as time spent on social media or instant messaging systems), as they are decisive for the effectiveness of the intervention. The impact of COVID-19 on young people's mental health has highlighted the need for assessment protocols and preventive measures that promote the healthy use of technology. These measures should also take into account  age and gender in their implementation to maximize their effectiveness.

Generating meaning: active inference and the scope and limits of passive AI (2024). Trends in cognitive sciences (United Kingdom, Q1)
Prominent accounts of sentient behavior describe brains as generative models of the organism's interaction with the world, showing intriguing similarities to current advances in generative artificial intelligence (AI). However, because they struggle to control intentional, life-sustaining sensorimotor interactions, generative models of living organisms are inextricably anchored to the body and the world. Unlike passive models learned by generative AI systems, these must capture and control the sensory consequences of action. This allows embodied agents to intervene in their worlds in ways that constantly test their best models, thereby providing a solid foundation that we argue is essential for the development of genuine understanding. We review the resulting implications and consider future directions for generative AI.

Communication and emerging teaching models: a study of YouTube teachers (2024). Multidisciplinary Journal of Educational Research (Spain, Q1)
Technological advances in recent decades have led to increased use of audiovisual content in education, giving rise to emerging models of teachers who create videos and upload them to YouTube. The aim of this research is to highlight some of the factors related to teachers' decisions to subscribe to educational YouTube channels and to become content creators or edutubers. A study was conducted through a survey of 1,139 teachers in Spain. The results reveal significant differences that show possible advantages or gaps in relation to the subject matter. The results are discussed with the most recent international literature on the subject. It concludes that the sample is mostly satisfied with the use of videos in education. The following variables are identified as key factors in subscribing to YouTube educational channels: age, stage, type of school, and satisfaction with the use of videos. Likewise, in the tendency to become edutubers: gender, age, stage, satisfaction with the use of videos, and subscription to YouTube educational channels.

Social robots for language learning: a review (2018). Review of Educational Research (United States, Q1)
In recent years, robots have been increasingly implemented as tutors in first and second language education. The field of robot-assisted language learning (RALL) is developing rapidly. Studies targeting different languages, age groups, and aspects of language and using different robots and methodologies have been published. This review presents an overview of the results obtained so far in RALL research and analyzes the current possibilities and limitations of using social robots for first and second language learning. Thirty-three studies in which vocabulary, reading skills, speaking skills, grammar, and sign language were taught are analyzed. In addition to providing information on the learning gains achieved in RALL situations, these studies raise more general questions regarding student motivation and the social behavior of robots in learning situations. This review concludes with directions for future research on the use of social robots in language education.

Eye tracking research on teacher professional vision: a meta-analytic review (2024). Educational Research Review (UK, Q1)
Eye tracking is increasingly being used by research groups around the world to study the professional vision and visual knowledge of teachers in service and in training. These studies provide evidence on how teachers process complex visual information in classrooms. Focusing on this growing body of evidence, the present meta-analytic review (k = 98 studies) aims to systematically aggregate and integrate previous research on eye tracking on teachers' professional vision and teachers' perceptions. Four objectives are addressed. First, we review the methodological characteristics of previous eye tracking studies in terms of sample, stimulus, and eye movement characteristics. The results show that most studies use mobile eye-tracking devices in action or remote eye trackers with classroom videos of the action; photographs and virtual classroom simulations are used less frequently. The average sample size of the reviewed studies is 13 teachers in service and 13 in training per study, indicating the benefit of meta-analytic synthesis. Second, we meta-analyzed experience-related differences between experienced and inexperienced teachers on two frequently used eye movement measures: teachers' gaze proportions and the Gini coefficient as a measure of the equitable distribution of teachers' gaze in the classroom. The results suggest that experienced teachers had higher gaze proportions on students in the classroom than inexperienced teachers (g = 0.926), who, in turn, looked more often at teaching materials and other objects in the classroom. Experienced teachers distributed their gaze more evenly than inexperienced teachers among students in the classroom (g = 0.501). Third, we synthesize the results reported in eye-tracking research on professional teaching vision processes using cognitive theory of visual experience as an organizing framework; the review also discusses the boundary conditions of eye-tracking research with respect to student, teacher, and instruction characteristics. Fourth, we review studies that explore the use of gaze repetitions and eye movement modeling examples as an instructional tool to support reflection in teacher training and professional development.

Exploring the impact of personalized and adaptive learning technologies on reading literacy: a global meta-analysis. Educational Research Review (United Kingdom, Q1)
Promoting reading literacy among students has long been a central educational activity, considering that it is one of the most cognitively demanding skills to acquire. Technology that adapts learning experiences to students' strengths and needs (i.e., personalized and adaptive learning; PAL) may be more effective than traditional curricular approaches. However, the literature on the effectiveness of PAL presents an inconclusive assessment of its impact on student reading performance, and no global synthesis has been conducted. This meta-analysis sought to assess the degree of differences in effect estimates and explore the reasons for differences across a wider range of populations and interventions. Twenty-seven studies were reviewed, and an effect size of g = 0.29 was found. Implications for future policy and practice are presented.

Effects of virtual reality on learning outcomes in K-6 education: A meta-analysis (2022). Educational Research Review (UK, Q1)
Virtual reality (VR) has gained popularity in educational settings in recent years. Its presence and immersive characteristics allow for new learning possibilities. Due to this growth, many studies have been conducted to evaluate the impact of VR on learning outcomes. The proliferation of experimental studies has created a need for meta-analyses that summarize the effect of VR in terms of learning gains. However, in the current literature, there are few reviews focused on K-6 students and on analyzing the influence of certain variables: level of immersion, duration of the intervention, and knowledge mastery. The present meta-analysis aims to address these needs. After a pre-selection of 4,658 references published between 2010 and 2021, 21 experimental studies were finally included in the meta-analysis. The results indicate that, on average, VR promotes greater student learning compared to control conditions (ES = 0.64). Furthermore, this effect is even greater when immersive VR is used (ES = 1.11) compared to semi-immersive (ES = 0.19) and non-immersive (ES = 0.32) systems. This effect does not depend on the educational level (kindergarten (ES = 0.59), 1-3 (ES = 0.69), 4-6 (ES = 0.70)), nor on most of the knowledge domains in which VR is used. Furthermore, brief interventions—less than 2 hours (ES = 0.72)—are more effective than longer ones (ES = 0.49).

Towards an AI policy framework in academic publishing (2024). Trends in cognitive sciences (United Kingdom, Q1)
The rapid adoption of artificial intelligence (AI) tools in academic research raises pressing ethical concerns. I examine leading editorial policies in science and medicine, uncovering inconsistencies and limitations in guidance on AI use. To foster the responsible integration of AI while upholding transparency, I propose an enabling framework with policy templates for authors and reviewers.