The review was conducted in three major stages and eight steps using thematic synthesis. The researchers searched relevant Health and Medicine databases for primary studies published in any language with an English abstract and followed Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) 2020 guidelines. Studies focusing on nurse educator challenges and nursing student attrition were critically appraised with the Mixed Methods Appraisal Tool. Thematic content analysis combined deductive and inductive reasoning; where included studies presented both nurse educators and students, the analysis used only data from educators. Of 1,330 initially identified studies, 37 met the inclusion criteria.

The abstract identifies persistent challenges in nursing education environments and highlights the importance of effective clinical and educational learning environments. Proposed responses include enhancing the nursing profession’s image, revising curricula and implementing student-focused teaching methods. It also calls for support for students during clinical placements, learning environments with adequate infrastructure, fair workload distribution and competitive remuneration to support educator motivation and retention. The authors additionally suggest that revised policies could improve continuous professional development and mentorship for new nurse educators. These are presented in the abstract as possible solutions rather than outcomes evaluated by the review.

South Africa provided the motivating context for the research. The abstract reports that problems in nursing training have contributed to a shortage of newly qualified nurses, while nursing education institutions accredited by the South African Nursing Council can register only limited numbers of students. Despite assistance from nurse educators, some students still fail to complete their training, and the authors suggest that educators may face challenges in addressing factors related to attrition. The findings are described as globally relevant, but the available evidence is limited to the abstract. It does not provide the geographic distribution, detailed characteristics or study-level quality findings for the 37 included studies, so the scope and limitations of the underlying evidence cannot be assessed further from the supplied material. The article is an early-access version in BMC Nursing and remains subject to further editorial changes.

Subject of Research: Nurse educator challenges associated with nursing student attrition in South African and global nursing education

Article Title: Challenges experienced by nurse educators to minimise the attrition of nursing students: a systematic review

Article References: Kent, A., Scholtz, S., Lubbe, W., & Rabie, T. (2026). Challenges experienced by nurse educators to minimise the attrition of nursing students: a systematic review. BMC Nursing. https://doi.org/10.1186/s12912-026-05455-5

Image Credits: AI Generated

DOI: 10.1186/s12912-026-05455-5

Keywords: nursing student attrition, nurse educators, systematic review, mixed-studies review, thematic synthesis, nursing education, clinical placements, South Africa, Challenges, experienced, nurse, educators

The research team, led by Ebtsam Aly Abou Hashish, together with Razaz Abdulaziz Felemban and Wid H. Allehaiby, designed an explanatory sequential mixed-methods study conducted at a Saudi health sciences university. The quantitative phase drew on a stratified random sample of 351 undergraduate students spread across four health sciences colleges, including medicine, nursing, applied medical sciences, and science and health professions. Students completed three validated instruments: the Leadership Style Questionnaire, which captures how educators lead; the Critical Thinking Disposition Scale, which measures a student’s habitual tendency toward reflective, analytical thinking; and the University Student Engagement Inventory, which assesses behavioral, emotional, and cognitive engagement with learning.

The statistical architecture of the study was deliberately rigorous. The team applied descriptive statistics to establish baseline scores, Pearson’s correlations to probe bivariate relationships, and multiple linear regression to isolate the independent contribution of each leadership style after adjusting for the others. Crucially, they also deployed a bootstrapped cross-sectional indirect-effect analysis, a technique that tests whether one variable statistically channels the influence of another. In this case, the question was whether student engagement might serve as a statistical bridge between democratic leadership and critical thinking disposition, a hypothesis that the data ultimately supported.

The headline quantitative result is striking in its clarity. Democratic leadership, characterized by participatory decision-making, shared dialogue, and collaborative classroom management, demonstrated the strongest positive bivariate associations with both outcomes. The correlation with student engagement reached r = .363, and the correlation with critical thinking disposition was even stronger at r = .402, both significant at p < .001. In adjusted regression analyses, democratic leadership remained independently associated with student engagement (β = 0.39, p < .001) and critical thinking disposition (β = 0.15, p = .007). By contrast, laissez-faire leadership, the hands-off style in which educators provide minimal direction, showed no statistically significant independent association with either outcome once the remaining leadership styles were accounted for.

Students reported mean scores above the scale midpoint for both engagement and critical thinking disposition, indicating generally positive learning climates. But the bootstrapped indirect-effect analysis revealed something more subtle: student engagement statistically accounted for part of the association between democratic leadership and critical thinking disposition. In plain terms, educators who lead democratically appear to kindle engagement first, and that engagement, in turn, helps cultivate the dispositional habits of mind that underpin clinical reasoning and evidence-based decision-making. This pathway matters because critical thinking disposition is not merely an academic abstraction; in health sciences, it is the psychological foundation for sound diagnostic judgment and the disciplined evaluation of evidence in fast-moving clinical environments.

The qualitative phase of the study then put flesh on these statistical bones. The researchers collected data from 58 unique participants through 40 semi-structured interviews and four focus group discussions, the latter involving 28 participants, including 10 who had also taken part in interviews. Analyzing the transcripts using inductive reflexive thematic analysis, the team found that students’ narratives converged with and expanded the quantitative results. Students described participatory teaching behaviors, open dialogue, constructive questioning, collaborative learning, and clear instructional guidance as the concrete mechanisms through which democratic educators supported their engagement and reflective thinking.

These qualitative themes are technically important because they identify the behavioral granularity of democratic leadership. Participatory teaching behaviors might include inviting students to co-construct learning activities or vote on case-selection priorities. Open dialogue refers to classroom climates in which students feel safe voicing uncertainty, a precondition for the intellectual humility that critical thinking requires. Constructive questioning, the Socratic practice of probing assumptions rather than merely testing recall, directly trains the analytical habits measured by the Critical Thinking Disposition Scale. Collaborative learning harnesses peer interaction to sustain emotional and cognitive engagement, while clear instructional guidance ensures that autonomy does not collapse into confusion, distinguishing genuine democratic leadership from the disengagement of laissez-faire approaches.

The study’s theoretical framing draws on widely recognized models of educational leadership psychology, in which educator behaviors are understood as a core component of the classroom environment. Within health sciences education, the stakes are unusually high. Critical thinking disposition is fundamental to clinical reasoning, the cognitive engine that allows practitioners to synthesize patient data, weigh competing hypotheses, and update decisions as evidence evolves. Student engagement, meanwhile, is a robust predictor of academic persistence, knowledge retention, and professional identity formation. If educator leadership styles shape both, then leadership development becomes not a soft peripheral concern but a strategic lever for producing competent, reflective clinicians.

The authors are careful about the limits of their evidence. Because the data are cross-sectional, the study cannot establish temporal order; it is possible that more engaged students with stronger critical thinking dispositions perceive their educators as more democratic, rather than the reverse. The bootstrapped indirect-effect analysis, while suggestive of a pathway from leadership through engagement to critical thinking, cannot prove causation. The authors explicitly call for longitudinal and multi-institutional studies to further examine the temporal relationships among educator leadership, student engagement, and critical thinking disposition. They also note that the findings emerged from a single Saudi health sciences university, raising questions about generalizability across cultures and educational systems.

Nevertheless, the practical implications are hard to ignore. The researchers suggest that participatory teaching approaches may represent valuable components of faculty development and educational practice. For universities training health professionals, that recommendation translates into concrete action: embedding leadership-style training into educator onboarding, coaching faculty toward dialogue-rich, question-driven classroom climates, and auditing teaching practices for the hallmarks of democratic leadership. The study received no specific grant funding and was approved by the King Abdullah International Medical Research Center under IRB Approval No. NRJ25/038/1, with informed consent obtained from all participants in written or electronic form. As health sciences faculties worldwide grapple with how to cultivate critical thinkers rather than memorizers, this Saudi study offers a technically grounded, culturally specific, and broadly resonant answer: the way educators lead may matter as much as what they teach.

Subject of Research: Academic educators’ leadership styles and their associations with student engagement and critical thinking disposition among Saudi health sciences students: a mixed-methods study

Article Title: Academic educators’ leadership styles and their associations with student engagement and critical thinking disposition among Saudi health sciences students: a mixed-methods study

Article References: Abou Hashish, E. A., Felemban, R. A., & Allehaiby, W. H. (2026). Academic educators’ leadership styles and their associations with student engagement and critical thinking disposition among Saudi health sciences students: a mixed-methods study. BMC Medical Education, 26(1), Article 1509. https://doi.org/10.1186/s12909-026-10239-1

Image Credits: AI Generated

DOI: 10.1186/s12909-026-10239-1

Keywords: Academic, educators, leadership, styles, associations, student, engagement, critical, thinking, disposition, Saudi, health

The research team, led by Michaela Gelewski, Simone Lehrl, and Stefanie Schnebel at the University of Education Weingarten, focused on a persistent gap in early science education. Decades of evidence show that experiences with science in early childhood play a central role in fostering children’s scientific knowledge and inquiry skills, and that young children frequently encounter physical phenomena such as movement, balance, light, sound, and material properties in their everyday lives. Yet many early childhood educators report limited confidence and knowledge in science, with the challenges particularly pronounced in physics, a domain often perceived as abstract and difficult to translate into developmentally appropriate learning experiences. Professional development is widely regarded as a key strategy to address this deficit, but empirical evidence on play-based physics programs specifically has remained scarce.

PhysikSPIEL was designed to close that gap. The program, which ran in approximately three-month cycles in 2024 and 2025, is grounded in the concept of play-based science learning within Guided Play, a framework in which children’s agency is combined with an intentionally structured learning context. In this approach, the play remains largely child-directed, but educators deliberately create the conditions for learning through the selection of materials, the arrangement of the environment, and pedagogical prompts. The program’s designers emphasize that play-based science learning extends beyond hands-on manipulation of materials to include minds-on engagement, meaning observing, questioning, comparing, reasoning, and developing emerging explanations. Children’s independent exploration alone does not ensure meaningful science learning; educators must recognize emerging opportunities and connect with children’s ideas and questions.

Structurally, the program combined three half-day sessions with a six-week implementation phase. The first two sessions centered on hands-on exploration of physics phenomena related to magnetism and forces and motion, with participants generating questions, exploring possible explanations, and reflecting on how children could be supported in play-based contexts. The selected concepts were not treated as content to be transmitted through predefined experiments but as scientific perspectives that could be connected to children’s experiences and emerging ideas. During the implementation phase, participants designed and implemented a play-based learning environment in their own settings, supported by a resource called the MiniBook, which presented six core physics concepts in accessible language along with prompts and reflective questions. Participants also had the opportunity to be observed by a PhysikSPIEL trainer, followed by a coaching session focused on joint analysis of the implemented learning situation. The final session centered on collective reflection through structured group discussions and video-based examples.

The study assessed five competence facets organized into two dimensions: motivational orientations, comprising domain-specific self-efficacy expectations, self-efficacy expectations regarding sustained shared thinking, domain-specific academic self-concept, and domain-specific enthusiasm; and pedagogical beliefs, represented by co-constructive teaching and learning beliefs. Sustained shared thinking, or SST, is an interactional format in which two or more individuals work together in an intellectual way to solve a problem, clarify a concept, or extend a narrative, with both parties contributing to the thinking. Previous research, including the EPPE study involving approximately 3,000 children and the subsequent REPEY study, identified SST as a key feature of high-quality educational interactions that promote children’s cognitive development. The researchers hypothesized that participation in PhysikSPIEL would be associated with increases in all five self-reported facets.

Participants were 42 early childhood educators from Germany and kindergarten teachers from Switzerland, drawn from an initial pool of 69 registrants, with only complete and matched pre-post datasets included in the analyses. The final sample had a mean age of 45.16 years, ranging from 23 to 62. Data were collected using a standardized self-report questionnaire administered immediately before and after the program, with all competence dimensions assessed on four-point Likert scales. The scales showed acceptable to high internal consistency, with Cronbach’s alpha ranging from 0.74 for the co-constructive beliefs scale to 0.90 for the domain-specific self-efficacy scale. The SST self-efficacy measure consisted of only two items, which showed a strong interitem correlation of r = .76, and the researchers noted that it captures perceived capability to initiate SST rather than the broader range of interactional processes involved.

The results revealed a differentiated pattern of change. Domain-specific self-efficacy expectations showed the largest increase, rising from a mean of 2.83 to 3.25 on the four-point scale, a difference of 0.42 points, with similar patterns in both countries. Mixed ANOVA analyses confirmed a statistically significant time effect for this scale, F(1,39) = 73.07, p < .001, with a partial eta squared of .65, indicating a substantial change. Self-efficacy expectations regarding SST also increased significantly, from 3.19 to 3.46, F(1,39) = 13.02, p < .001, with a partial eta squared of .25. Domain-specific academic self-concept rose from 2.67 to 2.99, F(1,21) = 17.17, p < .001, with a partial eta squared of .30, and domain-specific enthusiasm increased from 3.29 to 3.44, F(1,40) = 6.19, p = .017, with a smaller but significant partial eta squared of .13. In contrast, co-constructive teaching and learning beliefs remained largely stable, shifting only from 3.27 to 3.19, F(1,38) = 1.26, p = .270, with a negligible partial eta squared of .03.

Correlational analyses added a structural dimension to these findings. The motivational orientations were strongly interrelated, forming what the researchers describe as a motivational subsystem within professional competence. The strongest association emerged between domain-specific self-efficacy expectations and self-efficacy expectations regarding SST, r = .60, p < .001, which appears conceptually coherent given that the latter represents a domain-specific application of the broader self-efficacy construct. Domain-specific academic self-concept and enthusiasm were also strongly related, r = .56, p < .001. Notably, co-constructive teaching and learning beliefs showed no significant associations with most other variables, including only a weak, non-significant correlation with SST self-efficacy, r = .23, p = .15. This pattern provides empirical support for treating generalized pedagogical beliefs and domain-specific self-efficacy judgments as distinct facets, even though both concern dialogic, extending interactions with children.

The differential pattern across dimensions is theoretically meaningful. The researchers argue that motivational orientations may be more sensitive to short-term, practice-oriented professional development than pedagogical beliefs, which are deeply embedded, experience-based dispositions that change slowly over time. The program’s hands-on exploration sessions provided mastery experiences and direct engagement with physics content, mechanisms that social-cognitive theory identifies as primary sources of self-efficacy. The implementation phase, with its observation and coaching components, provided situated feedback on educators’ own enactment of dialogic interactions, which was particularly relevant to SST self-efficacy. By contrast, co-constructive beliefs were addressed more indirectly through collaborative reflection, and the researchers suggest that such broader pedagogical orientations may require more sustained professional learning experiences to change, particularly when baseline levels are already high.

The authors are careful to frame these findings as preliminary rather than definitive. The pre-post design without a control group precludes causal conclusions about program effects, the relatively small and self-selected sample limits statistical power and generalizability, and the reliance on self-report measures leaves open the possibility of social desirability bias and discrepancies between perceived and enacted practice. Deviations from normality were also detected for some variables, particularly the SST scale. Participants who chose to enroll in a physics-related program may have been comparatively motivated from the outset, and the observed changes reflect self-assessed perceptions rather than directly observed behavior. Future research, the team suggests, should employ larger and more diverse samples, include control groups, and combine self-report data with observational and performance-based measures to clarify how self-assessed competencies relate to professional practice.

Even with those caveats, the study offers a technically grounded contribution to a field where evidence has been thin. It demonstrates that different facets of professional competence vary in their responsiveness to practice-oriented professional development, and that motivational orientations, the conditions considered particularly relevant for fostering scientific interactions in early childhood education, can shift within a roughly three-month window. As countries increasingly recognize early science education as a foundation for later STEM learning, programs like PhysikSPIEL suggest a practical pathway: equip the adults who guide children’s play with the confidence and enthusiasm to see physics in a marble run, a magnet, or a balancing act, and the science may follow the child into the classroom and beyond.

Subject of Research: Changes in general and physics-related professional competence facets of early childhood educators

Article Title: Changes in general and physics-related professional competence facets of early childhood educators

Article References: Gelewski, M., Lehrl, S., & Schnebel, S. (2026). Changes in general and physics-related professional competence facets of early childhood educators. Frontiers in Education, 11, Article 1923768. https://doi.org/10.3389/feduc.2026.1923768

Image Credits: AI Generated

DOI: 10.3389/feduc.2026.1923768

Keywords: Changes, general, physics-related, professional, competence, facets, early, childhood, educators, scientific research

The research, led by Chin-Siang Ang of the Lee Kong Chian School of Medicine at Nanyang Technological University and TMC Academy, adopted an exploratory qualitative design built around a deceptively simple instrument: a sentence-completion survey. Participants were asked to finish three prompts, one addressing changes AI had already brought to education, one describing how AI is currently changing it, and one anticipating future transformation. Sentence completion, a semi-structured qualitative technique, encourages people to express their views in their own words while keeping responses focused on a shared topic. Responses were collected anonymously online during the first half of 2025, following institutional review board approval, and analysed in NVivo 15 using a two-stage process combining inductive thematic analysis with content analysis.

The analytical pipeline was designed to let patterns emerge from the data rather than imposing predefined categories. Every response was read repeatedly, coded inductively for its principal idea, and grouped into broader thematic categories through constant comparison. Where participants expressed more than one distinct idea, each idea was coded separately to preserve the breadth of interpretation. To check consistency, roughly 20 percent of responses were independently re-coded two weeks after the initial coding, yielding an agreement rate of 89 percent. The resulting thematic framework was then applied as a consistent structure for comparing patterns across the two participant groups and across the three temporal prompts, with frequency counts used descriptively rather than as measures of statistical significance.

When asked what AI had already changed, educators and students named many of the same broad developments but located them in different corners of university life. Educators most frequently cited the need to redesign assessment, with 58 responses on that theme, followed by the reduced effectiveness of plagiarism detection and authorship verification, the normalisation of technology dependence, the elimination of assessment tasks that AI can readily complete, and the continuing shift away from memorisation-based learning. Students, by contrast, centred their accounts on learning support and the practical organisation of study: 82 responses highlighted increased access to information and academic support, followed by a higher baseline quality of submitted work, reduced time to complete assignments, changing expectations about which academic skills matter, and more personalised learning support.

The pattern repeated for ongoing change, though with a subtle shift in tone. Educators described the present in terms of uncertainty and adaptation, most prominently uncertainty about the authenticity of student work, cited in 64 responses, alongside the need for continual adaptation of teaching practice, changing classroom dynamics, increasing workload despite promised efficiency gains, and a growing emphasis on learning processes rather than content acquisition. Students again emphasised the texture of daily study: immediate access to learning support, changing approaches to completing assignments, reduced anxiety when facing academic difficulties, opportunities to explore topics beyond course requirements, and, notably, pressure to keep pace with peers who were also using AI. Both groups agreed that academic practice was still evolving; they simply disagreed, in effect, about where the change was happening.

It was the future where the two narratives pulled furthest apart. Educators anticipated declining validity of traditional assessment, reduced value placed on human expertise and teaching, diminished deep learning and critical thinking, widening educational inequalities, and a changing meaning attached to academic credentials. Some responses reached further still, questioning the purpose of higher education itself and the commodification of learning. Students projected almost the opposite trajectory: expanded access to high-quality learning, a shift from knowledge acquisition towards skill application, more personalised learning pathways, faster degree completion, and the normalisation of lifelong learning. Compared with the past and present prompts, relatively few themes were shared across the two groups, suggesting that expectations about AI become increasingly shaped by the priorities attached to institutional roles.

The study frames these divergences through the concept of sensemaking, the idea that people construct meaning when situations challenge established routines and expectations. From this perspective, the findings do not reveal two camps holding opposing opinions about AI. Instead, they reveal two vantage points onto the same process. Educators are responsible for designing learning experiences, evaluating achievement, and maintaining academic standards, so it is unsurprising that they interpret AI primarily through assessment, authenticity, and the credibility of academic work. Students encounter AI most directly while studying, completing assignments, and managing the demands of university life, so their accounts naturally centre on support, efficiency, and access. The perspectives are complementary rather than contradictory, two readings of a single transformation experienced from different positions within the institution.

The temporal design also offers an explanation for why the wider literature on AI in higher education can appear conflicted. Studies emphasising learning support tend to report practical benefits for students, while those focused on assessment frequently highlight concerns about integrity and validity. The new findings suggest these accounts may simply capture different moments and different roles within a continuing process of educational change. Participants described coherent narratives rather than isolated observations: educators moved from completed changes in assessment, through continuing adaptation in teaching, to long-term concerns about standards and institutional purpose, while students moved from increased access to support, through the integration of AI into everyday study, to expectations of flexible and personalised education. Expectations about the future, the study notes, were closely connected to present experience, meaning that future-oriented responses should be read as reflections of current educational realities rather than predictions.

The implications reach into policy and assessment design. Because educators and students do not start from a shared understanding of AI, institutional strategies that assume consensus may fail to address the concerns of either group, and the study argues that developing AI policy through consultation with multiple stakeholder groups could produce clearer expectations and stronger confidence in institutional responses. On assessment specifically, the findings point away from a primary focus on detecting AI use and towards creating opportunities for students to demonstrate reasoning, judgement, and disciplinary understanding, with approaches that make learning processes more visible likely to reflect contemporary realities better than restriction or surveillance alone.

The study acknowledges its limits. Sentence completion captures concise interpretations across a large sample but lacks the depth of interviews or classroom observation; participants were not given a formal definition of impact, so responses reflect their own reference points; the sample was drawn through snowball sampling from universities in a single national context; and the data represent a snapshot during a period of rapid change rather than a longitudinal record. Future work, the author suggests, could include academic leaders, learning designers, librarians, employers, and policy makers, and could follow educators and students over time. What the study establishes in the meantime is a point that universities cannot afford to ignore: as AI continues to evolve, institutional responses will depend as much on how educators and students interpret what the technology means as on what the technology can actually do.

Subject of Research: Educators' and students' interpretations of artificial intelligence-driven educational change in higher education across past, present, and future perspectives

Article Title: Educators’ and students’ views on the impact of artificial intelligence in higher education

Article References: Ang, C.-S. (2026). Educators’ and students’ views on the impact of artificial intelligence in higher education. Discover Education, 5(1), Article 967. https://doi.org/10.1007/s44217-026-02174-6

Image Credits: AI Generated

DOI: 10.1007/s44217-026-02174-6

Keywords: artificial intelligence, higher education, generative AI, assessment, academic integrity, sensemaking, qualitative research, students, educators, educational change, Singapore, sentence completion

The research team, led by Jeffrey P. Carpenter of Elon University together with Ingrid Mosquera-Gende of Universidad Internacional de La Rioja and Paula Marcelo-Martínez of the University of Huelva, framed their investigation using learning ecosystem theory. Drawing on Bronfenbrenner’s social ecological model and Barron’s concept of learning ecologies, the authors distinguish a learning ecosystem from the more familiar notion of a learning ecology by its focus on a particular system rather than an individual. A learning ecosystem, as Sancho-Gil and Domingo-Coscollola define it, comprises living and non-living components interacting as a system: people, objects, symbols, and physical and virtual spaces, all interwoven and governed by formal and informal rules. Crucially, such ecosystems are dynamic, non-linear, and unpredictable, with mutable and permeable boundaries between their parts. This theoretical lens allowed the researchers to move beyond the single-platform studies that have dominated the literature on educator social media use, in which a 2018 systematic review identified no studies with an explicitly multiplatform focus.

The anatomy of the #CharlasEducativas ecosystem is strikingly complex. At its core remain the live YouTube interview broadcasts, most lasting between one-and-a-half and two hours, in which the founder interviews invited guests, the majority of them primary and secondary school teachers, but also early childhood educators, university faculty, psychologists, families, and learners speaking about their own diversity. Around this core, the ecosystem has sprouted synchronous spaces such as X/Twitter Spaces audio livestreams and occasional Telegram streams, where participants greet one another, answer questions, and debate in parallel dialogues while the host moderates. Asynchronous spaces include the YouTube archive, podcasting platforms, and the Telegram channel, which is used to announce chats, share guest information, and sustain debates between live events. X/Twitter, described by the authors as both the cradle and the nerve center of the initiative, hosted 8,401 original tweets from 1,233 users between January 2021 and June 2023, generating 175,844 likes, with an average of 7.32 posts per contributor.

Among the ecosystem’s distinctive features is the #DebateDominguero, a weekly Sunday poll on X/Twitter addressing educational topics, often those that have attracted substantial social media attention during the preceding week, and, during holidays, personal questions designed to help participants know one another better. Informative spaces, including the dedicated website charlaseducativas.com created to lessen dependence on external platforms, provide archives and calendars without interactive components. Participants have also contributed creatively: one user began producing sketchnotes, graphic summaries of each chat containing key concepts and quotes, complete with an avatar of the founder as a symbol of the community. Beyond the digital realm, the ecosystem crossed into physical space in 2023 with a first in-person event organized with colleagues from the #claustrovirtual community, drawing more than 150 teachers from across Spain for a Saturday of learning and face-to-face reunion; a second event in April 2024 attracted more than 270 attendees.

The ecosystem has even formalized some of its informal learning. Beginning in the third season, the initiative introduced monographs, sequences of consecutive chats devoted to a single topic. A 2022 monograph on Attention to Diversity extended this format and offered participants formal professional certification: by complementing the chat viewings with an open online course run in collaboration with a private education company and volunteer participants acting as informal tutors, teachers could convert informally acquired learning into credentialed value. Social responsibility initiatives further broadened the ecosystem’s scope, including a charity audio-a-thon on X/Twitter Spaces and a merchandise project selling t-shirts, bags, mugs, and sweatshirts designed by teachers, with all profits going to organizations that help children.

To understand what content flows through this ecosystem, the researchers categorized the chat topics into seven groups. Attention to diversity and inclusion emerged as the most frequently featured theme, though a large residual category testified to the sheer variety of subjects addressed, spanning early childhood, primary, secondary, tertiary, vocational, and adult education. Teaching methodologies such as gamification and project-based learning also featured prominently. This breadth contrasts with many online educator spaces that concentrate on a single content area, grade level, or pedagogical approach. The authors suggest that such topical breadth may attract educators with multiple professional interests, and may allow participants to alternate between giving and receiving knowledge as their own expertise becomes relevant at different moments, although they note that some educators may prefer the greater depth offered by more narrowly focused communities.

The third research question probed participant perceptions, drawing on 86 publicly available tweets, open-ended questionnaire responses from 83 teachers collected after the first in-person event, and fragments from a two-hour anniversary video featuring 19 special guests. Two coders independently applied an adapted category system covering educational topics, community building, and format, achieving an interrater reliability index of 0.783, which Landis and Koch’s classification rates as substantial agreement. The analysis generated 252 data units, and the findings clustered around three dimensions: the ecosystem as a source of learning, as a space of community building, and in terms of its formats. Participants valued the initiative as a different way of learning, an opportunity to encounter new points of view, and a context for reflecting on and modifying their own teaching practice. They praised the variety of topics and the quality of guests, and highlighted the ability to watch recordings and listen to podcasts, with some describing the archive as a library of knowledge and experiences.

The community dimension proved especially resonant. Participants repeatedly described the #CharlasEducativas as a family, a network of support that some said they did not find in their physical workplaces. The tone of the exchanges, informal and full of humor, emerged as a defining characteristic. One participant recalled the experience of watching a chat as though sitting down to dinner with the host and the guest, tablet propped in the middle of the table. Another observed that the initiative had achieved something important in both the chats and on X/Twitter, given that social networks are known to harbor hatred, bad manners, and badly managed controversy. The environment was characterized as a safe space for exchange, support, and learning, with acknowledgements directed toward the founder, the guests, and fellow participants, and metaphors describing the founder as a source of community unity.

The study also confronts the fragility inherent in such ecosystems. The maintenance of the live chats has depended largely on a single individual, consistent with prior research showing that informally developed online communities rely heavily on key volunteers who coordinate, moderate, and lead. Participants described the founder as a matriarch or chief, but the authors note that this leadership role demands a significant and consistent investment of time and energy that could become challenging to sustain. Similar precarity affects other contributors: the participant who created sketchnotes for nearly every chat during the first two seasons eventually found the workload unsustainable. The authors observe that learning ecosystems relying on social media and voluntary participation achieve a stability that is always in tension with the precarity of social media platforms and the absence of institutional sponsorship. Notably, when X/Twitter underwent significant changes, the ecosystem did not collapse, as additional platforms came more to the fore, illustrating a resilience born of multiplatform diversification.

The implications reach beyond this single case. For educators, the authors suggest that diversifying platform use and seeking out resilient learning ecosystems may be wise given threatened and real bans, ownership changes, and shifting platform practices. For administrators and policymakers, the message is more cautionary: because participation in such ecosystems is self-directed and informal, attempts to formalize, require, or scale up participation risk destroying the autonomy, voice, and choice that draw teachers to these spaces in the first place. The authors call for future research using interviews to probe how teachers experience different ecosystem components, studies of additional multiplatform instances, and work teasing out the impacts of such experiences on teaching beliefs, practices, and student outcomes. As online professional activities become routine elements of teachers’ working lives, the #CharlasEducativas offer a glimpse of what educator professional learning may look like in a future characterized by multiplatform social media activity: organic, community-driven, and spanning every space where teachers gather.

Subject of Research: Multiplatform social media ecosystems for self-directed teacher professional learning

Article Title: Multiplatform ecosystems of professional learning: The case of the #CharlasEducativas

Article References: Carpenter, J. P., Mosquera-Gende, I., & Marcelo-Martínez, P. (2025). Multiplatform ecosystems of professional learning: The case of the #CharlasEducativas. Journal of New Approaches in Educational Research, 14(1), Article 6. https://doi.org/10.1007/s44322-024-00024-7

Image Credits: AI Generated

DOI: 10.1007/s44322-024-00024-7

Keywords: professional learning, social media, learning ecosystem, teacher professional development, multiplatform, YouTube, X/Twitter, online communities, informal learning, Spain, educators, hashtags

The study’s starting point is a gap the authors identified in the existing literature. Since the public release of ChatGPT in late 2022, a flood of commentary has examined the general opportunities and risks of large language models in education, from their ability to pass professional examinations to their tendency to produce confident but incorrect statements, a phenomenon known as hallucination. Yet, the researchers argue, much of this work lacks specificity about its target audience. Students, educators, and institutions face different pressures and need different strategies, and broad-brush analyses often fail to deliver concrete, tailored recommendations. The German team designed their investigation to separate these perspectives, treating students and educators as distinct stakeholder groups with distinct needs.

Methodologically, the research employs a mixed-method design that integrates quantitative and qualitative strands. The quantitative core is an online questionnaire completed by 188 students, which probed how often they use generative AI tools, for which academic tasks, and with what attitudes toward benefit and risk. The qualitative complement is a scenario analysis, a foresight technique with a long pedigree in technology assessment, used here to map plausible future states of higher education under different assumptions about AI adoption and regulation. By pairing measured present-day behavior with structured speculation about tomorrow, the authors aimed to produce findings that are both empirically grounded and strategically useful for universities planning their next moves.

The survey results confirm what many instructors suspect anecdotally: generative AI is already woven into the fabric of student workloads. Students reported using tools such as ChatGPT for assignment writing and for exam preparation, and they largely view the technology as an effective instrument for achieving their academic goals. This instrumental framing matters. For most respondents, the appeal is not novelty but efficiency, a way to compress the time between a blank page and a finished draft, or to generate practice questions and explanations on demand. The technology functions, in the students’ own usage patterns, as a personal tutor and drafting assistant rolled into one always-available interface.

Underneath that convenience, however, lie technical realities that the study situates carefully. Large language models of the kind behind ChatGPT are trained on vast text corpora and generate responses by predicting plausible continuations, which makes them remarkably fluent but not reliably truthful. The cited literature the authors draw upon documents both the breadth of these systems’ competence, including strong performance on professional licensing examinations, and their persistent weaknesses, including hallucinated facts and uneven reasoning. This duality explains why the same tool that helps a student understand a difficult concept can also, if trusted uncritically, embed subtle errors into an essay or a problem set. Fluency, the research implicitly warns, is not the same as understanding.

The scenario analysis extends the picture from the present into possible futures. Rather than predicting a single outcome, the method constructs multiple coherent scenarios in which generative AI is integrated into higher education to varying degrees and with varying degrees of responsibility. Across these futures, the study highlights both opportunities and challenges for students and educators alike. On the opportunity side, AI can personalize learning, lower barriers for students working in a second language, and free educators from repetitive tasks. On the challenge side, unmanaged adoption threatens academic integrity, erodes the practice-based skills that degrees are supposed to certify, and widens gaps between students and institutions with different levels of AI literacy and access.

The study’s central warning is that irresponsible and excessive use of generative AI could pose significant challenges to higher education. If students outsource the cognitive work that assignments are designed to develop, the assessment no longer measures learning, and the learning itself may never occur. The authors’ response is not prohibition but redesign. Their recommendations for educators are concrete: establish clear policies governing AI use, reevaluate learning objectives in light of what machines can now do, enhance AI skills among teaching staff, update curricula to reflect an AI-saturated professional world, and reconsider examination methods so that assessment remains meaningful when text generation is effectively free.

Each of those recommendations carries technical and institutional weight. Clear policies reduce the ambiguity that currently leaves students guessing about what is permitted, a confusion documented across the wider literature on academic integrity in the ChatGPT era. Reevaluated learning objectives shift the emphasis from producing text, which AI does cheaply, toward critical evaluation, original argumentation, and verification, which remain human responsibilities. Curriculum updates echo a parallel movement in engineering education toward transdisciplinary programs that integrate AI with non-IT fields, preparing graduates for workplaces where language models are standard equipment. And rethought examinations, whether through oral defenses, supervised performance, or process-based assessment, address the simple fact that take-home essays can no longer reliably certify individual authorship.

The research also carries a message for students, who emerge from the survey as pragmatic adopters rather than passive victims of technological change. The findings suggest that the burden of responsible use is shared: students need the AI literacy to recognize when a model’s output is plausible but wrong, and the academic honesty to use these tools in ways consistent with their institutions’ rules and their own learning goals. The authors’ framing of separate solution strategies for each stakeholder group reflects a broader shift in the field, away from treating generative AI as a problem to be banned and toward treating it as an infrastructure to be governed, in the same way universities already govern libraries, laboratories, and the internet itself.

Published open access and already widely read and cited, the study by Krause, Panchal, and Ubhe lands at a moment when institutions worldwide are moving from improvised responses to durable policy. Its mixed-method evidence base, 188 surveyed students and a disciplined look at alternative futures, is modest in scale but pointed in implication. The transformation of learning is not a distant prospect; it is measurable in current student behavior and visible in the scenarios the authors map. Whether that transformation strengthens or hollows out higher education depends, the research concludes, on the choices educators and institutions make now: the policies they write, the skills they teach, and the assessments they redesign for a world in which fluent text is no longer proof of thought.

Subject of Research: The impact of generative AI tools such as ChatGPT on students, educators, and assessment in higher education

Article Title: Evolution of Learning: Assessing the Transformative Impact of Generative AI on Higher Education

Article References: Krause, S., Panchal, B. H., & Ubhe, N. (2025). Evolution of Learning: Assessing the Transformative Impact of Generative AI on Higher Education. Frontiers of Digital Education, 2(2), Article 21. https://doi.org/10.1007/s44366-025-0058-7

Image Credits: AI Generated

DOI: 10.1007/s44366-025-0058-7

Keywords: generative AI, ChatGPT, higher education, large language models, scenario analysis, academic integrity, AI literacy, curriculum design, assessment, educational technology, students, educators

The research, led by Bryndís Jóna Jónsdóttir of the University of Iceland together with colleagues from the University of Iceland and the Mindfulness Centre in Reykjavík, followed 150 educators from five public compulsory schools serving pupils aged six to fifteen. The study was designed to answer a question that has dogged the field for years: do the benefits of mindfulness-based interventions actually last, or do they fade once the initial enthusiasm of an eight-week course wears off? Most previous studies have measured outcomes only three to twelve months after training, leaving the long-term picture largely unknown.

To address that gap, the researchers structured the study around a clear conceptual distinction between what they call mental health skills and mental health outcomes. The skills category included mindfulness itself, self-compassion, and teachers’ sense of professional self-efficacy, all understood as modifiable psychological capacities that can be developed through training. The outcomes category covered perceived stress, anxiety, and depression, reflecting an individual’s current state of psychological functioning and distress. This framework allowed the team to track both the resources educators build and the symptoms they carry, across four measurement waves at baseline and at three, twelve, and twenty-four months.

The intervention at the heart of the study was Mindfulness-Based Cognitive Therapy for Life, or MBCT-L, an adaptation of the well-known mindfulness-based cognitive therapy program designed for broader populations with a greater emphasis on appreciation and gratitude. Educators in the three intervention schools completed an eight-week course of weekly group sessions combining guided mindfulness practices, reflective inquiry, group dialogue, and home practice. Crucially, the course was embedded in a broader whole-school implementation: each school formed a mindfulness implementation team that promoted practice spaces, informative materials, and brief mindfulness activities woven into daily school life. Optional teacher training was later offered to build internal capacity for bringing age-appropriate mindfulness to students, though this component was not part of the well-being intervention being evaluated.

Methodologically, the study was a non-randomized trial, with three schools allocated to the intervention and two serving as a waitlist comparison group that would receive the training after the follow-up period. The researchers acknowledge this as a key limitation, since school preferences rather than chance determined group assignment, potentially allowing unmeasured factors such as leadership support or school culture to influence results. Data were analyzed using linear mixed-effects models that accounted for the nesting of repeated measurements within teachers and teachers within schools, fitted with restricted maximum likelihood to handle the modest sample size. Effect sizes were interpreted using conventional benchmarks, with small effects around 0.2 and medium effects around 0.5 on Cohen’s d.

The results on mental health skills were the study’s strongest and most durable findings. Self-compassion showed statistically significant time-by-group interaction effects favoring the intervention group at every measurement point, from three months through the full two-year follow-up. Teacher sense of efficacy, measured with a validated nine-item scale covering instructional strategies, student engagement, and classroom management, became significantly different between groups at twelve and twenty-four months, even though the difference was not yet significant at three months. Mindfulness scores themselves improved significantly within the intervention group at all time points, though the between-group comparison at twenty-four months was only marginally significant, with a small-to-moderate effect size of 0.34, partly because the comparison group showed an unexpected rise in mindfulness scores at twelve months that the researchers could not explain with available data.

The sustained gains in self-compassion may be the study’s most consequential result. Teaching is a profession characterized by high expectations, constant evaluation, and frequent self-critical tendencies, and prior research has linked self-compassion to lower perceived stress and better occupational health among educators. In one Australian study cited by the authors, self-compassion was the single strongest predictor of lower stress, ahead of mindfulness itself. The Icelandic findings suggest that mindfulness training can cultivate this capacity for self-kindness in a way that endures, potentially helping teachers respond to professional setbacks with balance rather than harsh self-judgment. The persistence of improved self-efficacy is equally notable, given the well-established associations between teachers’ beliefs in their own effectiveness and job satisfaction, engagement, and retention.

The picture for mental health outcomes was more nuanced. Perceived stress, measured with the widely used Perceived Stress Scale, decreased significantly in the intervention group relative to the comparison group at three and twelve months, with small-to-moderate effects. At twenty-four months the difference remained in favor of the intervention group but was no longer statistically significant, suggesting the stress-reduction benefit may attenuate over time or that the study lacked the statistical power to detect it in a smaller sample. Anxiety showed significant within-group decreases at three and twelve months but no significant between-group differences, and depression showed no significant effects at all. The authors suggest a likely floor effect: both groups began with minimal to mild levels of anxiety and depression, leaving little room for measurable improvement in a generally non-clinical population.

These mixed results echo the broader and sometimes inconsistent literature on mindfulness in schools. The large-scale UK MYRIAD trial, which tested school-based mindfulness training, found short-term reductions in teacher burnout but no significant differences on broader mental health indicators compared with usual provision. A meta-analysis by Klingbeil and Renshaw reported a moderate overall effect size of 0.60 for mindfulness interventions on teachers’ outcomes, while systematic reviews have consistently called for more rigorous longitudinal research extending beyond the typical three-to-six-month follow-up window. The Icelandic study directly answers that call, providing four-wave data across twenty-four months, though the authors caution that their small, self-selected, predominantly female sample of 97 percent women limits generalizability.

Participation was voluntary, with 56 percent of eligible educators in intervention schools enrolling and attending an average of 7.3 of the eight sessions, a level of engagement the researchers note aligns with recommendations that mindfulness should never be compulsory. Attrition reduced the sample over time, with 51 percent of the intervention group and 64 percent of the comparison group completing the final follow-up, though sensitivity analyses excluding participants with only baseline data left the findings substantively unchanged. The study relied entirely on self-report measures, and the authors recommend that future work incorporate observational, physiological, and qualitative data. They also call for research into whether improvements in educator well-being ripple outward into school climate, staff retention, absenteeism, teaching quality, and student outcomes. For now, the message is cautiously encouraging: mindfulness training may not eliminate the structural stressors of teaching, but it appears capable of building psychological resources, particularly self-compassion and professional confidence, that educators can draw on for years, positioning it as a promising long-term health-promotion strategy for the profession rather than a quick fix for existing distress.

Subject of Research: Long-term effects of a school-based mindfulness intervention on educators' mental health skills and outcomes over two years

Article Title: Mindfulness and Educators’ Mental Health and Well-Being: Outcomes of a Two-Year Study

Article References: Jónsdóttir, B. J., Stefánsson, K. K., Kaldalóns, I. V., Frostadóttir, A. D., & Jónsson, Ó. P. (2026). Mindfulness and Educators’ Mental Health and Well-Being: Outcomes of a Two-Year Study. School Mental Health. https://doi.org/10.1007/s12310-026-09914-x

Image Credits: AI Generated

DOI: 10.1007/s12310-026-09914-x

Keywords: mindfulness, educators, teacher well-being, self-compassion, self-efficacy, stress, mental health, MBCT-L, whole-school approach, longitudinal study, burnout, school mental health

The research team, led by Goutam Roy of Charles Sturt University together with colleagues Shukla Sikder and Will Letts, set out to address a gap that has long been acknowledged but rarely examined directly. While numerous studies have documented the importance of building scientific literacy in the early years and its long-term benefits, few have asked what happens after the initial spark: how children move from developing an understanding of scientific ideas to genuinely retaining and extending that understanding across contexts. The authors define scientific literacy as a combination of acquiring scientific knowledge, establishing connections with the real world, and applying that knowledge in similar or new situations, a framing that aligns with what scholars call Vision 2 of scientific literacy, which emphasises applicability in daily life rather than purely academic science content.

To investigate the process, the researchers adopted a qualitative design grounded in cultural-historical theory, using digital video observation to capture the full texture of children’s play. The study took place at an early childhood centre in the central west region of New South Wales, Australia, where four educators and 22 children aged four to five participated. Before any filming began, the team held a one-hour professional development session with educators and the centre director to discuss the study’s aims, relevant scientific concepts, and how educators might support children’s learning through play. Over a two-week period, three cameras documented a series of colour-focused play activities, generating more than nine and a half hours of video footage across three sessions lasting just over three hours and twenty minutes in total.

The three play experiences were deliberately sequenced to build on one another. In the first activity, children mixed liquid and ice-block colours at a table while educators asked open-ended questions about what would happen when one colour was added to another. Children discovered, for example, that adding red to an existing green produced what one child memorably called a ‘yucky colour’, and educators extended the conversation by inviting children to draw rainbows and think about where rainbow colours come from. The researchers interpret this stage as the establishment of an initial scientific literacy: children acquired knowledge of colour mixing and immediately applied it in a hands-on situation, linking what Vygotsky termed everyday concepts with the beginnings of scientific understanding.

The second day pushed the children’s knowledge into new territory through two experiments. First, children cut stalks of celery and placed them in coloured water, observing how the vegetable absorbed the dye and changed colour, an everyday application of the previous day’s learning. Then an educator attempted something more ambitious: creating a real rainbow using only a spray bottle of plain water and sunlight. The children were asked how many colours a rainbow contains and whether it could be made without dyes. Despite several attempts, including moving to a higher position, no rainbow appeared. The researchers argue that this failure was itself pedagogically valuable. The educator connected the disappointment back to the concept by naming the rainbow’s colours and singing a rainbow song with the children, demonstrating that unsuccessful experiments can still deepen curiosity, imagination, and reasoning when educators explain the underlying process.

The third activity transformed the children’s knowledge once more by changing the state of an object. Working with corn flour, liquid colours, and water, children created mixtures ranging from thin to thick, deciding for themselves whether to add more flour or more water. Crucially, the educator did not prescribe instructions but instead asked children what they wanted to do, prompting them to reason about cause and effect: adding corn flour made the mixture thicker, while adding water thinned it. The researchers observed children drawing on their earlier learning about colour mixing, applying it to a new material, and making informed decisions about proportions. This, they argue, is the hallmark of sustaining scientific literacy: the ability to apply scientific reasoning across related contexts, revisiting prior knowledge and generating new explanations.

From the analysis, conducted using the dialectical-interactive approach developed by Hedegaard and Fleer across three interpretive levels, the team distilled a four-stage continuous process for sustaining scientific literacy: planned play-based scientific experiences, initial scientific literacy, continuation, and sustaining scientific literacy. In the first stage, educators design a series of connected activities aligned with specific science concepts and children’s interests. In the second, children acquire knowledge and apply it practically, as with the colour mixing. The continuation stage involves interrelated problem-solving tasks that link previous knowledge to new applications, such as the celery and rainbow experiments. Finally, sustaining scientific literacy emerges as children consciously apply their understanding in progressively more advanced situations, using critical thinking and decision-making. The process depends on educators acting as play partners who scaffold learning through questions, prompts, and shared dialogue, consistent with the Australian Early Years Learning Framework’s emphasis on planned, intentional teaching through play.

The theoretical engine driving this process is Vygotsky’s account of the relationship between everyday and scientific concepts. Vygotsky argued that children’s everyday concepts form the foundation of their scientific concepts, and that scientific concepts in turn restructure and elevate everyday concepts, writing that scientific concepts ‘are not learned in final form—they too develop.’ The study’s authors apply this insight to scientific literacy, suggesting that isolated, one-off science play experiences are insufficient to sustain it. Instead, scientific ways of thinking, knowing, and applying knowledge must be revisited and transformed across a series of related experiences, allowing children to build conscious awareness of concepts they initially engage with only implicitly. When educators make these connections explicit through carefully planned play, children progress toward higher-order skills such as problem-solving, analytical competence, and the socio-scientific decision-making that scholars like Holbrook and Rannikmae and Johnson identify as the ultimate aims of scientific literacy.

The authors are candid about the practical challenges of implementing their framework. The four-stage process depends on educators’ willingness and intentionality, and some may feel uncertain about their own scientific knowledge, lacking the confidence to guide children from developing to sustaining scientific literacy. The researchers stress that educators do not need to be science content experts; the emphasis falls on planning, organising, engaging, describing, and questioning to prompt children’s higher-level understanding. They also caution that pedagogical responsiveness cannot be assumed across all early childhood contexts without adequate policy support and professional development, and that cultural differences in orientations toward co-constructed learning may require the process to be adapted locally rather than applied as a uniform pathway.

The study’s implications reach beyond the preschool classroom. Because scientific literacy underpins informed citizenship, the ability to evaluate evidence, and engagement with complex socio-scientific issues later in life, ensuring that early gains endure is arguably as important as producing them. The researchers suggest that future work should examine how the process can be negotiated across diverse settings, how structural and policy supports can help educators sustain children’s scientific literacy, and whether interdisciplinary approaches could strengthen the framework. For now, the humble act of mixing colours, feeding celery dyed water, and chasing an elusive rainbow offers a compelling demonstration that sustained scientific literacy can begin not with formal lessons, but with play, guided by educators who know when to step in and when to let children lead.

Subject of Research: How educators can support children in sustaining scientific literacy through play-based experiences in the early years.

Article Title: Sustaining Scientific Literacy Among Children Through Play In The Early Years: A Cultural-Historical View

Article References: Roy, G., Sikder, S., & Letts, W. (2026). Sustaining Scientific Literacy Among Children Through Play In The Early Years: A Cultural-Historical View. Early Childhood Education Journal. https://doi.org/10.1007/s10643-026-02322-5

Image Credits: AI Generated

DOI: 10.1007/s10643-026-02322-5

Keywords: scientific literacy, early childhood education, play-based learning, cultural-historical theory, Vygotsky, preschool science, educators, STEM education, everyday concepts, scientific concepts, video observation, Australia