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This study aims to describe and evaluate various visual and creative tools for supporting the in-depth biographical interview aimed at analyzing educational communities and their stakeholders.

Researching educational spaces today requires new ways of understanding, analyzing and studying. The complex characteristics, functions and realities demand research that responds to educational singularities. It is a matter of deeply understanding the educational phenomenon's peculiarities. For these purposes, instruments and research paradigms are needed to extract data and reach information saturation regarding the data obtained from the proposed objects of study. With this in mind, the following paper suggests reflecting on data collection tools that can complement the interview and biographical-narrative research approach. The authors highlight the use of photo-elucidation, the biogram-based timeline, the organigram and the flight of the geese, all of which are instruments endowed with a visual character that allows a deeper understanding of the object studied.

The main contribution of this paper is to unpack the uses and applications of four visual tools that support the interview technique. First, photo-elucidation is presented as a sensory strategy to stimulate the narrative during the dialogical exchange of the interview. Next, the timeline is described as a visual concretization of the traditional biogram widely used in educational research. Next, the authors unravel the uses of the organizational chart in educational research, which, due to its nature and utility, provides a glimpse of the organizational functioning of an institution and is particularly suitable for research in institutional frameworks. Finally, the tool known as the flight of the geese is presented. This tool is recommended for use in educational leadership and teamwork studies due to its simplicity and high representativeness of the hierarchy of roles and functions.

Researching educational spaces today requires new ways of understanding, analyzing and studying. The complex characteristics, functions, and realities demand research that responds to educational singularities. It is a matter of deeply understanding the educational phenomenon's peculiarities. For these purposes, instruments and research paradigms are needed to extract data and reach information saturation regarding the data obtained from the proposed objects of study. With this in mind, the following paper invites us to reflect on data collection tools that can complement the interview and biographical-narrative research approach. The authors highlight the use of photo-elucidation, the biogram-based timeline, the organigram, and the flight of the geese, all of which are instruments endowed with a visual character that allows a deeper understanding of the object studied.

The challenges facing 21st-century society are becoming increasingly complex, requiring the development of new citizen competencies. This study aims to validate an educational model focused on developing complex thinking in higher education students. Current educational models lack future-ready competencies, necessitating the emergence of new models to guide future generations toward the common good.

This was an adaptation of the causal-layered analysis (CLA) applied to 415 participants from higher education institutions in Mexico, Panama and Spain. Sessions were designed to present the proposed educational model and explore participants’ perceptions of its significance and contributions to future education.

Key findings include the following: participants perceived complexity as difficult and challenging; causes of problems were linked to outdated educational models requiring replacement by those that develop students’ competencies; participants envisioned changes that would develop individuals capable of understanding and transforming society; and participants recognized the model’s transformative potential, offering a novel proposal for 21st-century education.

This research sought to gather opinions from different stakeholders using the CLA methodology, providing a deep understanding of participants’ perspectives on the proposed solution.

This study investigates a novel educational strategy in science, technology, engineering and mathematics (STEM) teaching that integrates the engineering design process (EDP) as a framework. The strategy aims to help teachers explain STEM concepts in a simplified way. We employed the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) methodology to enable a systematic review that evaluated the effectiveness of this approach in improving both teaching and learning in STEM subjects.

In order to fulfill the objectives of the review, key data were extracted from each of the 400 articles that were reviewed from three databases: Scopus, ProQuest Central and EBSCO. Two types of analysis were conducted, namely descriptive analysis and literature classification.

This systematic review analyzed 44 articles on the EDP, focusing on 18 detailed studies mainly from ProQuest, SCOPUS and EBSCO. It revealed a limited focus on gender’s impact on EDP and a trend toward interdisciplinary use and integrated research approaches. The study underscores the need for further exploration of demographic influences and preparation programs in EDP across various disciplines, aiming to inform future research and educational policies.

The study’s value lies in its comprehensive assessment of engineering design (ED) research over the past decade, serving as a key reference point. It highlights progress in the field, consolidates findings and provides insights into the field’s evolution, guiding future research directions in ED.

The study aims to identify the status quo of artificial intelligence in entrepreneurship education with a view to identifying potential research gaps, especially in the adoption of certain intelligent technologies and pedagogical designs applied in this domain.

A scoping review was conducted using six inclusive and exclusive criteria agreed upon by the author team. The collected studies, which focused on the adoption of AI in entrepreneurship education, were analysed by the team with regards to various aspects including the definition of intelligent technology, research question, educational purpose, research method, sample size, research quality and publication. The results of this analysis were presented in tables and figures.

Educators introduced big data and algorithms of machine learning in entrepreneurship education. Big data analytics use multimodal data to improve the effectiveness of entrepreneurship education and spot entrepreneurial opportunities. Entrepreneurial analytics analysis entrepreneurial projects with low costs and high effectiveness. Machine learning releases educators’ burdens and improves the accuracy of the assessment. However, AI in entrepreneurship education needs more sophisticated pedagogical designs in diagnosis, prediction, intervention, prevention and recommendation, combined with specific entrepreneurial learning content and entrepreneurial procedure, obeying entrepreneurial pedagogy.

This study holds significant implications as it can shift the focus of entrepreneurs and educators towards the educational potential of artificial intelligence, prompting them to consider the ways in which it can be used effectively. By providing valuable insights, the study can stimulate further research and exploration, potentially opening up new avenues for the application of artificial intelligence in entrepreneurship education.

The study aims to analyze pedagogical e-leadership in online higher education in Spain through the application of VAL-ED at the International University of La Rioja.

The methodology used to achieve the objectives has been a descriptive and quantitative methodology through a cross-sectional study based on the implementation of the questionnaire: Adaptation of the VAL-ED to the university context, developed by Palomino et al. (2022a).

Indeed, the data obtained allow the authors to affirm how both directors and supervisors, as well as teachers, have been able to evaluate the leadership behavior of directors, compared to the competence standards of VAL-ED, having obtained very positive results that show how their leadership is, without a doubt, oriented to students. Given the fact that in the second specific objective the study sets out to determine to what extent the three groups of respondents (faculty, supervisors and directors) coincide in the effective performance of the pedagogical leadership of the directors, it can be highlighted that no great differences have been found in the responses of effectiveness obtained from directors, supervisors and teachers, since the results of the resulting scores among these three groups of respondents were reasonably similar.

The research is original as the sample was collected personally by the authors of this article.

To increase the understanding of how entrepreneurship education impacts entrepreneurial careers, the purpose of the paper is to investigate the role that a venture creation program (VCP) might have in mitigating or surpassing a lack of other antecedents of entrepreneurial careers. In particular, the authors focus on entrepreneurial pedigree and prior entrepreneurial experience.

Data from graduates of VCPs at three universities in Northern Europe were collected through an online survey. Questions addressed graduate background prior to education, yearly occupational employment subsequent to graduation and graduates' own perceptions of entrepreneurial activity in employment positions. The survey was sent to 1,326 graduates and received 692 responses (52.2% response rate).

The type of VCP, either independent (Ind-VCP) or corporate venture creation (Corp-VCP), influenced the mitigation of prior entrepreneurial experience. Prior entrepreneurial experience, together with Ind-VCP, made a career as self-employed more likely. However, this was not the case for Corp-VCP in subsequently choosing intrapreneurial careers. Entrepreneurial pedigree had no significant effect on career choice other than for hybrid careers.

Entrepreneurial experience gained from VCPs seems to influence graduates toward future entrepreneurial careers. Evidence supports the conclusion that many VCP graduates who lack prior entrepreneurial experience or entrepreneurial pedigree can develop sufficient entrepreneurial competencies through the program.

This study offers novel evidence that entrepreneurship education can compensate for a lack of prior entrepreneurial experience and exposure for students preparing for entrepreneurial careers.

This paper explores the convergence of Education 4.0 and Industry 4.0 and presents a Twin Peaks model for their seamless integration.

A high-level literature review is conducted to identify and discuss the important challenges and opportunities offered by both Education 4.0 and Industry 4.0. A novel Twin Peaks model is devised for the convergence of these domains and to cope with the challenges effectively.

The proposed Twin Peak model for the convergence of Education 4.0 and Industry 4.0 suggests that the development of these two domains is interdependent. It emphasizes ethical considerations, inclusivity and understanding the concerns of stakeholders from both education and industry. We have also explained how continuous incremental adaptation within the proposed Twin Peaks model might assist in addressing concerns of one sector with the opportunities of the other.

First, Education 4.0 and Industry 4.0 are reviewed in terms of opportunities and challenges they present. Second, a novel Twin Peaks model for the convergence of Education 4.0 and Industry 4.0 is presented. The proposed discovers that the convergence is adaptive, iterative and must be ethically sound while considering the broader societal implications of the digital transformation. Third, this study also acts as a torch-bearer for the necessity for more research of this kind to guarantee that our educational ecosystem is adaptable and capable of producing the skills required for success in the era of IR4.0.

Design-based research (DBR) involves multiple iterations, and innovations are needed in analytical methods for understanding how learners experience a learning experience in ways that both embrace the complexity of learning and allow for data-driven changes to the design of the learning experience between iterations. The purpose of this paper is to propose a method of crafting design moves in DBR using network analysis.

This paper introduces learning experience network analysis (LENA) to allow researchers to investigate the multiple interdependencies between aspects of learner experiences, and to craft design moves that leverage the relationships between struggles, what worked and experiences aligned with principles from theory.

The use of network analysis is a promising method of crafting data-driven design changes between iterations in DBR. The LENA process developed by the authors may serve as inspiration for other researchers to develop even more powerful methodological innovations.

LENA may provide design-based researchers with a new approach to analyzing learner experiences and crafting data-driven design moves in a way that honors the complexity of learning.

LENA may provide novice design-based researchers with a structured and easy-to-use method of crafting design moves informed by patterns emergent in the data.

To the best of the authors’ knowledge, this paper is the first to propose a method for using network analysis of qualitative learning experience data for DBR.