ABSTRACT Educators in higher education face persistent challenges in scaling AI literacy across disciplines and helping novice learners understand abstract AI concepts. Although research on game‐based learning (GBL) reports mixed outcomes, few studies have examined its large‐scale use in mandatory, asynchronous AI literacy courses for diverse undergraduate populations. Addressing this gap, this study investigates a scalable GBL‐based AI literacy course delivered to 4898 first‐year undergraduates across disciplines. Using a mixed‐methods design with 311 valid pre‐ and post‐survey responses and 20 interviews, the study evaluates students' cognitive, behavioural, affective, and ethical learning of AI. Quantitative results show significant improvements in overall AI literacy across cognitive, behavioural, and affective dimensions, while ethical learning gains were not statistically significant. Qualitative findings suggest that GBL stimulated students' epistemic curiosity and engagement with AI ethics while revealing pedagogical, technical, and learner‐centered challenges. The study provides large‐scale empirical evidence and proposes an instructional design framework for scalable AI literacy integration in higher education.

ABSTRACT Since the introduction of the maximally maintained inequality (MMI) hypothesis, the effect of educational expansion on inequality of educational opportunity (IEO) has been widely debated, with empirical studies producing conflicting results. Using data from the European Social Survey (ESS), this study examines whether the effect of educational expansion is context‐dependent by focusing on four macro‐level indicators derived from the choice dimension (educational returns and costs) and the capital dimension (economic capital inequality and cultural capital inequality). The results show that, at the upper secondary level, the effect of educational expansion varies significantly across social contexts, with educational returns, economic capital inequality and cultural capital inequality exerting significant moderating effects. For higher education, educational expansion is overall associated with lower IEO, but this association does not vary significantly across the four macro‐level indicators. This study provides empirical evidence explaining why the effects of educational expansion are context‐dependent rather than unidirectional.

ABSTRACT Self‐regulation of learning is a crucial factor in how students learn and manage their own emotional, cognitive and metacognitive resources. This study has three main goals: first, to identify self‐regulation of learning profiles among 697 Spanish university students using cluster analysis, second, to differentiate these profiles based on sex, academic year, and field of study (Education, Humanities and Social Sciences, Economics and Engineering); and finally, to uncover their preferred ways of learning, teaching methodologies, and assessment methods. Our study has revealed four types of learners: strategic (28.12%), non‐strategic (26.11%), external (22.81%) and anxious (22.96%). Findings revealed that strategic learners, characterised by the highest levels of self‐regulation and self‐efficacy, preferred active and applied methodologies, whereas anxious learners exhibited the highest levels of study‐related exhaustion ( p < 0.001). Our study highlights the importance of recognising the diversity of self‐regulated learning profiles among university students to tailor teaching, learning, and assessment strategies, that improve academic performance across a broader range of learners. To support less effective learner profiles, it is essential to provide additional scaffolding through personalised tutorials, enhance planning skills, and deliver structured feedback. Additionally, diversifying teaching and assessment methods—such as incorporating video‐based resources for anxious learners and offering practical, step‐by‐step guidance—can help these students gradually develop autonomy and improve self‐regulation.

ABSTRACT This paper examines the decolonisation of curricula in Indigenous schooling as an act of resistance to epistemicide, focusing on curricular practices and pedagogical actions that affirm Indigenous knowledge. The study adopted a multiple‐case design grounded in an emic–etic approach and involved two Indigenous community schools in the state of Alagoas, Brazil. Its aim was to map and analyse the curricular practices and pedagogical initiatives developed in these schools. The findings show that both schools and their actors are engaged in an ongoing struggle to rebuild and re‐signify their curricula, reaffirming the premise that every Indigenous person has science . In doing so, they not only challenge dominant epistemic narratives but also advance social justice and emancipation by recognising and valuing traditional Indigenous knowledge.

ABSTRACT While family foreign language planning (FFLP) is increasingly common in contexts like China, its socioemotional consequences for children remain underexplored. Drawing on interviews and written protocols from six Chinese families, this study investigates how children's learning emotions mediate the relationship between FFLP and socioemotional development. Thematic analysis reveals three distinct pathways: (1) directive FFLP mediated by anticipatory anxiety, fostering regulated self‐management; (2) directive FFLP mediated by oppositional joy, enabling assertive autonomy; and (3) responsive FFLP mediated by sustained positive engagement, supporting holistic growth in social–emotional competencies and psychological well‐being. Critically, outcomes depend not on planning style alone, but on children's emotional interpretation of parental practices. The study reconceptualises FFLP as an affective ecology and highlights emotion as the central mechanism through which language planning shapes well‐being, calling for child‐centred approaches in both parenting and educational policy.

ABSTRACT Treating teachers as mere tools or instruments, denying them of their humanity for the school's goals, causes them to teach in dehumanizing times. Recent research indicates that organizational dehumanization may have a significant impact on an individual's self‐efficacy and work behaviour. However, the causal relationship between organizational dehumanization and self‐esteem, self‐efficacy, and demotivating teaching style remains unclear in this literature. Utilizing job demand‐resources theory, we examine the mediating role of self‐esteem and the moderating role of perceived coworker support in organizational dehumanization and teacher self‐efficacy and demotivating teaching style relationships. Data were collected from early childhood ( N = 307) and primary ( N = 664) teachers for study 1 (an experimental study) and study 2 (a three‐wave study), respectively. Overall, the combined results of experimental and three‐wave studies provide strong evidence that experiencing dehumanizing treatment from the school leads teachers to internalize negative self‐evaluation, leading to low self‐esteem, which subsequently reduces teacher self‐efficacy but increases demotivating teaching style adoption. And this detrimental effect is less critical among teachers with high perceived coworker support. This study sheds light on dehumanization in the school setting by suggesting practical implications to reduce dehumanizing practices and highlighting the importance of perceived coworker support among teachers in classroom practices.

ABSTRACT For four decades, discourses on digital divides have shaped engagement with societal transformation processes in the context of digitality. With the rapid development of AI technologies, these disparities are manifesting in an emerging “AI Divide” that not only reproduces existing social inequalities but potentially amplifies them. This article analyses the interactions between AI development, digital inequality and social participation, and argues, by way of example, against technological solutionism and techno‐ableism, which reduce complex social challenges to technically solvable problems. Instead, the necessity of a critical integration of AI safety and AI alignment with inclusive educational processes is elaborated. Central to this is the question of how transformative education can enable people not merely to adapt technically, but to actively participate in shaping an inclusive, AI‐influenced society. The article proposes anchoring inclusion as a continuous moment of reflection in the development and implementation of AI, and outlines pedagogical enabling spaces that can promote both “Inclusive AI” and “AI for Inclusion”.

ABSTRACT This study explores how English as a foreign language (EFL) tutors in China's competitive and challenging shadow education sector (re)construct their professional identities in the age of artificial intelligence (AI). Drawing on semi‐structured interviews and reflective teaching journals, the study investigates Chinese EFL tutors' identity work in AI‐mediated tutoring contexts. The findings reveal three interrelated identity shifts. First, tutors reconstruct themselves from knowledge and skill providers to learning facilitators who guide students in analysing and refining AI‐generated materials for exam‐oriented tasks. Second, emotional and motivational support becomes a central dimension of tutor identity, as tutors respond to students' discouragement and uncertainty triggered by AI‐generated feedback. Third, tutors construct themselves as interpreters and evaluators of AI‐generated content, exercising pedagogical judgement to assess relevance, accuracy and alignment with assessment requirements. Across these dimensions, identity construction emerges as a key site of professional learning through which EFL tutors renegotiate expertise and sustain professional legitimacy amid technological disruption and market competition. The study contributes to research on language teacher identity and AI in education by highlighting how EFL tutors maintain epistemic authority in AI‐mediated shadow education.

ABSTRACT Hidden curriculum research has traditionally focused on schools, universities and professional training settings. Yet many contemporary workplaces also function as pedagogic environments in which tacit norms, evaluative standards and forms of accountability are learned through participation rather than explicit instruction. This paper proposes a method for studying such processes by conceptualising valuation practices as a hidden curriculum of professional judgement. Rather than treating financial valuation in medical innovation investment primarily as a technical tool for estimating future returns, the paper reframes it as an evaluative infrastructure through which actors learn what counts as relevant evidence, defensible assumptions and legitimate decision‐making. Methodologically, it develops an artefact‐sensitive and practice‐proximate framework for tracing implicit learning across four dimensions: modelling, commensuration, dispute and justification and stabilisation. The framework is illustrated through de‐identified valuation episodes from medical innovation investment, a setting in which clinical, regulatory, policy and market knowledge must be translated into organisationally recognisable judgements. The paper contributes to education research by extending hidden curriculum analysis beyond formal educational institutions, by offering a transferable method for studying workplace learning in evaluative environments and by reframing valuation infrastructures as sites of educational governance and professional formation.

ABSTRACT The emergence of the smart classroom, highlighting the incorporation of developed digital tools, redefined the conventional learning and teaching dynamics. In the meantime, the interpersonal features of teaching, especially teacher credibility and care, are vital in promoting constructive learner results. The present research investigates the degree to which learners' perceptions of teacher credibility and care affect their psychological well‐being (PWB) and motivation in smart classes. Based on a purposive sampling strategy, 440 EFL students who were engaged in digital learning settings participated. They completed four valid questionnaires, evaluating PWB, motivation, credibility and teacher care. The structural equation modelling (SEM) results indicated that credibility and teacher care considerably predicted students' PWB and motivation; however, the links with teacher care were stronger, suggesting that teacher care had a more pronounced bivariate relation with the outcomes. The research emphasises the significance of incorporating relational competencies, including credibility and teacher care, in the professional development of teachers. Developing intimacy, actual interplay and reliability in smart class settings enhances learners' motivation and fosters an environment that leads to PWB, ultimately promoting educational development.