Search Results (51)

This study advances Spanish Heritage Language (SHL) pedagogy by investigating the integration of Critically Oriented Sociolinguistic Topics (COST) into the heritage language curriculum. Thirteen self-identified SHL students from three courses (Intermediate, Advanced I, and Advanced II) at two universities in the Washington, D.C. metro area participated in semi-structured Zoom interviews exploring their motivations for enrolling in an SHL class, their perceptions of Spanish, and the impact of COST. Analysis identified recurring themes about underlying language ideologies and enrollment motivations, such as improving academic Spanish and grammar, career preparation, and connecting with course topics. Dominant ideologies, including essentialist, standard language, deficit, and commodification, were evident in students’ perceptions of Spanish and Latinx communities in the U.S. and abroad. Findings showed that students developed critical awareness of language variation that supported validation of their HL practices and the emergence of student agency. Some students moved from reproducing to contesting deficit and standard ideologies, asserting legitimacy for their own bilingual repertoires. These findings underscore the need for integrating COST in SHL courses to promote student agency, foster positive attitudes, and strengthen students’ linguistic confidence. Full article

Recent advances in generative artificial intelligence (AI) have enabled the creation of AI-generated characters modeled after historical figures, offering new opportunities for reflective and interactive engagement in both cultural heritage and education. This study explores the development and evaluation of a large language model representation of Joseph Lister (1827–1912), a pioneer of antiseptic surgery, within a retrieval-augmented generation framework. The purpose was to examine the model’s accuracy, authenticity, and reliability, highlighting challenges, best practices, and ethical considerations. Drawing on primary and secondary sources, including Lister’s writings, the model was constructed using OpenAI’s GPT-4o and refined through iterative validation. Prompts were categorized by cognitive complexity, and responses were evaluated against historical materials. The findings revealed a strong fidelity to Lister’s voice, with appropriate tone, diction, and temporal limits. Moreover, the model demonstrated behavioral control, reflective depth, and consistency across the different prompts. However, minor lapses in temporal framing and occasional embellishments were noted. The findings suggest that, when developed with care, AI-generated characters can support ethically grounded, historically sensitive learning experiences. At the same time, this approach warrants continued scrutiny and underscores the need for further interdisciplinary research and responsible implementation. Full article

In the Swedish compulsory school system, multilingual students’ reading and writing development is supported, among other measures and practices, by heritage language (HL) teachers. To effectively support multilingual students, whether they require special educational assistance or not, collaboration between heritage language teachers and special education needs (SEN) teachers is essential. Thus, a key consideration is how HL and SEN teachers work together to promote reading and writing skills in multilingual children. We present two sub-studies: Study 1, a questionnaire answered by 33 HL teachers, and Study 2, consisting of in-depth interviews with a different group of 13 HL teachers. Both sub-studies aim to increase our understanding of HL teachers’ experiences of collaborative practices with SEN teachers for promoting reading and writing development among multilingual students with or without the need of special educational support. The findings reveal that HL teachers, though well qualified and committed, are often excluded from collaborative planning with SEN teachers. This study highlights the systemic barriers and opportunities for improving literacy support through interprofessional collaboration. Full article

Artificial intelligence technologies, particularly machine learning and computer vision, are being increasingly utilized to preserve, restore, and create immersive virtual experiences with cultural artifacts and sites, thus aiding in conserving cultural heritage and making it accessible to a global audience. This paper examines the performance of Generative Adversarial Networks (GAN), especially Style-Based Generator Architecture (StyleGAN), as a deep learning approach for producing realistic images of Egyptian monuments. We used Sigmoid loss for Language–Image Pre-training (SigLIP) as a unique image–text alignment system to guide monument generation through semantic elements. We also studied truncation methods to regulate the generated image noise and identify the most effective parameter settings based on architectural representation versus diverse output creation. An improved discriminator design that combined noise addition with squeeze-and-excitation blocks and a modified MinibatchStdLayer produced 27.5% better Fréchet Inception Distance performance than the original discriminator models. Moreover, differential evolution for latent-space optimization reduced alignment mistakes during specific monument construction tasks by about 15%. We checked a wide range of truncation values from 0.1 to 1.0 and found that somewhere between 0.4 and 0.7 was the best range because it allowed for good accuracy while retaining many different architectural elements. Our findings indicate that specific model optimization strategies produce superior outcomes by creating better-quality and historically correct representations of diverse Egyptian monuments. Thus, the developed technology may be instrumental in generating educational and archaeological visualization assets while adding virtual tourism capabilities. Full article

The study of historical monuments within both architectural and literary frameworks reveals a dynamic interplay between scientific observation and artistic interpretation—a vital characteristic of travel writing/the travelogue. This approach, exemplified by British traveler and writer Henry Finnis Blosse Lynch (1862–1913), reflects how factual detail and creative representation are seamlessly integrated in depictions of sites, landscapes, and cultural scenes. This case study highlights Lynch as a pioneering explorer who authored the first comprehensive volume on Armenian architecture and as a writer who vividly portrayed Armenian monuments through both verbal description and photographic imagery, becoming the first traveler to document such sites using photography. Additionally, this paper emphasizes the significance of Lynch’s detailed accounts of architectural monuments, churches, monasteries, cities, villages, populations, religious communities, and educational institutions in vivid language. The careful study of his work can contribute meaningfully to the investigation of the travelogue as a literary genre and to the preservation and protection of the architectural heritage of historical and contemporary Armenia, particularly in regions facing cultural or political threats. Full article

Early printed books, particularly incunabula, are invaluable archives of the beginnings of modern educational systems. However, their complex layouts, antique typefaces, and page degradation caused by bleed-through and ink fading pose significant challenges for automatic transcription. In this work, we present a modular pipeline that addresses these problems by combining modern layout analysis and language modeling techniques. The pipeline begins with historical layout-aware text segmentation using Kraken, a neural network-based tool tailored for early typographic structures. Initial optical character recognition (OCR) is then performed with Kraken’s recognition engine, followed by post-correction using a fine-tuned ByT5 transformer model trained on manually aligned line-level data. By learning to map noisy OCR outputs to verified transcriptions, the model substantially improves recognition quality. The pipeline also integrates a preprocessing stage based on our previous work on bleed-through removal using robust statistical filters, including non-local means, Gaussian mixtures, biweight estimation, and Gaussian blur. This step enhances the legibility of degraded pages prior to OCR. The entire solution is open, modular, and scalable, supporting long-term preservation and improved accessibility of cultural heritage materials. Experimental results on 15th-century incunabula show a reduction in the Character Error Rate (CER) from around 38% to around 15% and an increase in the Bilingual Evaluation Understudy (BLEU) score from 22 to 44, confirming the effectiveness of our approach. This work demonstrates the potential of integrating transformer-based correction with layout-aware segmentation to enhance OCR accuracy in digital humanities applications. Full article

Drawing on data from a three-year longitudinal study of 56 Chinese–Canadian families with early elementary school-aged children, this study explores Chinese immigrant parents’ lived-through emotional experiences of heritage language maintenance (HLM). Informed by Vygotsky’s concept of perezhivanie, thematic analysis of annual interview data reveals the mixed and refracted nature of parental emotions involved in Chinese language preservation and bilingual child-rearing. These emotional experiences were profoundly shaped by the intersection of environmental, personal, and situational factors and were deeply entangled with parents’ perceptions of and attitudes toward their children’s heritage language learning and use at home. The emotional work involved significantly influenced the parents’ language and literacy planning and HLM practices. By foregrounding the emotional dimensions of heritage language education, this study offers important implications for educational stakeholders seeking to support immigrant parents both emotionally and practically in raising bilingual children in the host country. Full article

Recognising linguistic diversity as a person’s characteristic is arguably central to their multilingual identity and is important as an equity issue. Different indicators suggest that students with migrant backgrounds, whose linguistic diversity is often not reflected in European education systems, tend to underperform compared to their peers without migrant backgrounds. There is a dire need, therefore, to alleviate the educational inequalities that negatively affect some of the most plurilingual students in European school systems. This can be carried out by revisiting assessment tools. Developing assessments to make children’s full linguistic and cultural repertoire visible, and what they can do with it, is one way that potential inequalities in school systems and assessment practices can be addressed so that cultural and linguistic responsiveness of assessments and practices can be improved. This paper explores the concept of discontinuities or mismatches between the assessment of plurilingual children’s linguistic practices in one primary school in Catalonia and their actual linguistic realities, including heritage languages. It asks: (1) What are the children’s linguistic profiles? (2) What mismatches and/or educational inequalities do they experience? and (3) How does the co-creation and use of a rubric assessing plurilingual and intercultural competence attempt to mitigate these mismatches and inequalities? Mismatches are identified using a context- and participant-relevant reflection tool, based on 18 reflective questions related to aspects of social justice. Results highlight that mismatches exist between children’s plurilingual and intercultural knowledge and skills compared to the school, education system, curriculum, and wider regional and European policy. These mismatches highlight two plurilingual visions for language education. The paper highlights how language assessment tools and practices can be made more culturally and linguistically fair for plurilingual children with migration backgrounds. Full article

This article carries out an interdisciplinary analysis of five MOOC courses developed by the University of Valladolid and offered on higher education platforms between 2020 and 2024. This research is based on the study of the lexical categories used by the informants participating in these courses, establishing a correlation with the theoretical and practical debates surrounding the definition of heritage and the frameworks of contemporary heritage education. Through a metalinguistic approach, the semantic limits of the emerging lexical categories are examined, paying attention to their ambiguity, polysemy and contexts of use, both from a formal linguistic perspective and from a hermeneutic approach. The analysis is based on natural language processing tools, complemented by qualitative techniques from applied linguistics and cultural studies. This dual approach, both scientific–statistical and humanistically nuanced, allows us to identify recurrent discursive patterns, as well as significant variations in the conceptualization of heritage according to the socio-cultural and geographical profiles of the participants. The results of the linguistic analysis are contrasted with the thematic lines investigated by our research group, focusing on cultural policy, legacy policies, narratives linked to the culture of depopulation, disputed scientific paradigms, and specific lexical categories in the Latin American context. In this sense, the article takes a critical look at discursive production in massive online learning environments, positioning language as a key indicator of the processes of cultural resignification and the construction of legacy knowledge in the Ibero-American context. The findings of my scientific article underscore the pressing need for a multiform liberation of the traditionally constrained concept of heritage, which has long been framed within rigid institutional, legal, and disciplinary boundaries. This normative framework, often centered on materiality, monumentalism, and expert-driven narratives, limits the full potential of heritage as a relational and socially embedded construct. My research reveals that diverse social agents—ranging from educators and local communities to cultural mediators and digital users—demand a more flexible, inclusive, and participatory understanding of heritage. This shift calls for redefining legacy not as a static legacy to be preserved but as a dynamic bond, deeply rooted in affective, symbolic, and intersubjective dimensions. The concept of “heritage as bond”, as developed in contemporary critical theory, provides a robust framework for this reconceptualization. Furthermore, the article highlights the need for a new vehiculation of access—one that expands heritage experience and appropriation beyond elite circles and institutionalized contexts into broader social ecosystems such as education, digital platforms, civil society, and everyday life. This approach promotes legacy democratization, fostering horizontal engagement and collective meaning-making. Ultimately, the findings advocate for a paradigm shift toward an open, polyphonic, and affective heritage model, capable of responding to contemporary socio-cultural complexities. Full article

The East–West Mountain Region (EWMR) of Wuhan is a vital natural and cultdural asset, characterized by its scenic nature landscapes and rich historical and cultural heritage. This study aims to address the problems of landscape character degradation and weakened public preferences caused by rapid urbanization and proposes a research framework integrating landscape character assessment and public preferences. Initially, we utilize K-means cluster analysis to identify landscape character types based on six landscape elements, resulting in a landscape character map with 20 types. Subsequently, we employ emotion analysis based on Natural Language Processing (NLP) techniques to analyze user-generated content (UGC) from Weibo check-in data to establish perception characteristic indicators reflecting public preferences. Finally, we quantitatively identify the environmental factors influencing public preferences through the SoIVES model and compare and integrate the landscape character map with the public emotion value map. The results show that (1) public preferences hotspots are concentrated in three types: (a) urban construction-driven types, including areas dominated by commercial service functions and those characterized by mixed-function residential areas; (b) natural terrain-dominated types with well-developed supporting facilities; and (c) hybrid transition types predominated by educational and scientific research land uses. These areas generally feature a high degree of functional diversity and good transportation accessibility. (2) Landscapes eliciting stronger emotional responses integrate moderate slopes, multifunctional spaces, and robust public services, whereas areas with weaker responses are characterized by single-function use or excessive urbanization. (3) The emotional variations within categories could be influenced by (a) functional hybridity through enhanced environmental exploration; (b) spatial usage frequency through place attachment formation; and (c) visual harmony through cognitive overload prevention. These findings provide critical insights for formulating zoning optimization plans aimed at the refined conservation and utilization of urban landscape resources, as well as offering guidance for improving landscape planning and management in the EWMR. Full article

This paper presents an augmented reality (AR) mobile application developed for Android devices, which brings five bust sculptures of historical personalities of the city of Komotini, Greece, to ‘life’ using the Unity engine. These busts narrate their achievements in two languages, Greek and English, to educate visitors on historical and cultural heritage and provide a comprehensive glimpse into the area’s past using 3D models, textures, and animations tailored to the educational content. Based on the users’ location, the application provides an interactive educational experience, allowing the users to explore the history and characteristics of the busts in an innovative way. The users may interact with the busts using markerless AR, discover information and historical facts about them, and stimulate their understanding of the busts’ significance in the context of local history and culture. Interactive elements, such as videos and 3D animations, are incorporated to enrich the learning experience. A location-based knowledge quiz game was also developed for this purpose. The application was evaluated by statistical analysis to measure the effect of using the application on the involvement of users in the educational process and to study the users’ satisfaction and experience. This approach revealed that the proposed AR app is effective in providing educational content, promotes active user participation, and provides a high level of user satisfaction. Full article

Couplets, consisting of a pair of clauses, are an important form of Chinese intangible cultural heritage, playing a significant role in the education and transmission of traditional Chinese culture. By engaging in couplet creation, students can enhance their Chinese comprehension and expression skills, literary creativity, and cultural identity. Personalized Chinese couplet (PCc) generation entails creating paired clauses that meet specific requirements while adhering to certain linguistic rules (e.g., morphological and syntactical symmetry). However, generating PCcs and evaluating the results is a challenging task that requires both cultural context and language understanding. Large Language Models (LLMs) have powerful learning and language comprehension abilities, providing new possibilities for addressing the challenges. In this study, we propose a framework for generating and evaluating PCcs using LLMs. First, we construct a couplet database, then use a retrieval method and design a specific prompt to provide a pair of clauses as references to guide the LLM following the rules of couplet style. Second, we construct a custom PCc generation dataset to train the base model, improving its ability for this task. Finally, we introduce a debate method based on LLMs to evaluate the quality of the generated couplets. By simulating adversarial human debate processes, it obtains more comprehensive and nuanced reference data for evaluation purposes. The experimental results show that our approach effectively generates and evaluates couplets. Reduced creation difficulty promotes couplet education and the preservation of Chinese intangible cultural heritage. Positive feedback from participants indicates that our framework can enhance user engagement, offer a positive PCc creation experience, and contribute to the education and transmission of couplet culture. Full article

In today’s globalized world, foreign language (FL) communication is characterized by the presence of regional variations that can impact L2 learners’ speech perception in their target language. While it is essential for FL programs to prepare their students for real-world language variation, research on learner perception of spoken regional varieties remains scarce, especially for less commonly taught languages, such as Italian. To address this, this study used a quantitative approach to explore to what extent listeners’ background factors (i.e., accent familiarity, contact with Italian speakers, heritage learner status, L1) and speaker accent impact FL learners’ perceptions of (1) intelligibility, (2) comprehensibility, and (3) acceptability of regionally accented Italian speech. A total of forty-seven FL learners of Italian listened to the speech of six Italian native speakers with different regional accents (two each from Northern, Central, and Southern Italy), rated them for comprehensibility and acceptability, and transcribed utterances for intelligibility. Mixed-effects models revealed statistically significant effects of speaker accent and listener L1 background on all three perceptual constructs. Additionally, greater contact corresponded with higher comprehensibility, while heritage learners rated speech as less acceptable for educational contexts. Listeners’ overall positive perception of regionally accented speech encourages the introduction of authentic spoken varieties in the FL classroom. Full article

Cultural ecosystem services (CES) provided by 12 major urban parks on the Macau Peninsula were quantitatively evaluated using social media data. Furthermore, the potential implications of these findings for cultural heritage preservation and landscape design optimization were investigated. A CES evaluation framework consisting of six dimensions was established. User-generated content (UGC) was then collected using web-crawling techniques. A sentiment analysis based on natural language processing (NLP) and a spatial clustering analysis were subsequently performed on the collected data. Significant differences between CES dimensions were identified across Macau’s urban parks (F = 19.45, p < 0.01). Among the CES dimensions, esthetic appreciation (M = 76.04) and landscape experience (M = 72.47) received the highest scores. Moreover, landscape experience was found to have the strongest influence on visitors’ emotional evaluations (β = 0.95, p < 0.01). The spatial autocorrelation analysis indicated that the CES distribution did not exhibit significant clustering patterns (Z = 0.59). Based on these findings, it is recommended that educational functions be enhanced, public facilities upgraded, and local cultural heritage integrated into landscape and spatial planning. This research provides a novel CES quantification method based on social media data. It also offers theoretical and practical frameworks for urban planning and cultural heritage conservation in Macau. Full article

To unlock more aspects of human cognitive structuring, human–AI and human–robot interactions require increasingly advanced communication skills on both the human and robot sides. This paper compares three methods of retrieving cultural heritage information in primary school education: search engines, large language models (LLMs), and the NAO humanoid robot, which serves as a facilitator with programmed answering capabilities for convergent questions. Human–robot interaction has become a critical aspect of modern education, with robots like the NAO providing new opportunities for engaging and personalized learning experiences. The NAO, with its anthropomorphic design and ability to interact with students, presents a unique approach to fostering deeper connections with educational content, particularly in the context of cultural heritage. The paper includes an introduction, extensive literature review, methodology, research results from student questionnaires, and conclusions. The findings highlight the potential of intelligent and embodied technologies for enhancing knowledge retrieval and engagement, demonstrating the NAO’s ability to adapt to student needs and facilitate more dynamic learning interactions. Full article