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Early career teachers (ECTs) of Color are key in making change, resisting racism and pushing back against white supremacy in K-12 education, specifically in English Language Arts (ELA) classrooms. Through a narrative telling inquiry (Clandinin and Connelly, 2000) of Nora, an Asian American ELA ECT in the Midwest, and by drawing on Fisher’s (2011) Critical Integral Pedagogy of Fearlessness, this study aims to recognize the narrative power within teaching praxis as Nora stories herself toward becoming a critical pedagogue.

Using narrative inquiry methodology and methods (Clandinin and Connelly, 2000), the authors simultaneously considered the commonplace tenets of narrative inquiry – temporality, sociality and place – of the intertwined relationships of the participants and observers. The field texts included in the corpus of data include myriad tellings of Nora’s experiences in her initial years of teaching ELA. Data were analyzed in stages of parsing out narrative blocks and structures.

The findings indicate that Nora, as an ECT, went through recursive cycles of fear as conceptualized by Fisher (2011) – bravery, courageousness and being fear-less – of working toward radical love (Hooks, 2000) within her ELA instruction. The authors argue that Nora confronted her personal and professional fears as she strove to become a critical pedagogue in her ELA classroom.

Current scholarship portrays ECTs as lacking agency in their development and/or effectiveness in the classroom and little is said about Asian American ELA ECTs and critical instruction. The authors present Nora’s counter-narrative to make visible what is right with ELA ECTs, specifically teachers of Color, as they transform their fear into courage to fight for educational equity.

A semiparametric stochastic frontier model is proposed for panel data, incorporating several flexible features. First, a constant elasticity of substitution (CES) production frontier is considered without log-transformation to prevent induced non-negligible estimation bias. Second, the model flexibility is improved via semiparameterization, where the technology is an unknown function of a set of environment variables. The technology function accounts for latent heterogeneity across individual units, which can be freely correlated with inputs, environment variables, and/or inefficiency determinants. Furthermore, the technology function incorporates a single-index structure to circumvent the curse of dimensionality. Third, distributional assumptions are eschewed on both stochastic noise and inefficiency for model identification. Instead, only the conditional mean of the inefficiency is assumed, which depends on related determinants with a wide range of choice, via a positive parametric function. As a result, technical efficiency is constructed without relying on an assumed distribution on composite error. The model provides flexible structures on both the production frontier and inefficiency, thereby alleviating the risk of model misspecification in production and efficiency analysis. The estimator involves a series based nonlinear least squares estimation for the unknown parameters and a kernel based local estimation for the technology function. Promising finite-sample performance is demonstrated through simulations, and the model is applied to investigate productive efficiency among OECD countries from 1970–2019.

Web users rely heavily on online content make decisions without assessing the veracity of the content. The online content comprising text, image, video or audio may be tampered with to influence public opinion. Since the consumers of online information (misinformation) tend to trust the content when the image(s) supplement the text, image manipulation software is increasingly being used to forge the images. To address the crucial problem of image manipulation, this study focusses on developing a deep-learning-based image forgery detection framework.

The proposed deep-learning-based framework aims to detect images forged using copy-move and splicing techniques. The image transformation technique aids the identification of relevant features for the network to train effectively. After that, the pre-trained customized convolutional neural network is used to train on the public benchmark datasets, and the performance is evaluated on the test dataset using various parameters.

The comparative analysis of image transformation techniques and experiments conducted on benchmark datasets from a variety of socio-cultural domains establishes the effectiveness and viability of the proposed framework. These findings affirm the potential applicability of proposed framework in real-time image forgery detection.

This study bears implications for several important aspects of research on image forgery detection. First this research adds to recent discussion on feature extraction and learning for image forgery detection. While prior research on image forgery detection, hand-crafted the features, the proposed solution contributes to stream of literature that automatically learns the features and classify the images. Second, this research contributes to ongoing effort in curtailing the spread of misinformation using images. The extant literature on spread of misinformation has prominently focussed on textual data shared over social media platforms. The study addresses the call for greater emphasis on the development of robust image transformation techniques.

This study carries important practical implications for various domains such as forensic sciences, media and journalism where image data is increasingly being used to make inferences. The integration of image forgery detection tools can be helpful in determining the credibility of the article or post before it is shared over the Internet. The content shared over the Internet by the users has become an important component of news reporting. The framework proposed in this paper can be further extended and trained on more annotated real-world data so as to function as a tool for fact-checkers.

In the current scenario wherein most of the image forgery detection studies attempt to assess whether the image is real or forged in an offline mode, it is crucial to identify any trending or potential forged image as early as possible. By learning from historical data, the proposed framework can aid in early prediction of forged images to detect the newly emerging forged images even before they occur. In summary, the proposed framework has a potential to mitigate physical spreading and psychological impact of forged images on social media.

This study focusses on copy-move and splicing techniques while integrating transfer learning concepts to classify forged images with high accuracy. The synergistic use of hitherto little explored image transformation techniques and customized convolutional neural network helps design a robust image forgery detection framework. Experiments and findings establish that the proposed framework accurately classifies forged images, thus mitigating the negative socio-cultural spread of misinformation.

The purpose of this paper is to explore teacher candidates’ response to young adult literature (prose and comics) featuring fat identified protagonists. The paper considers the textual and embodied resources readers use and reject when imagining and interpreting a character’s body. This paper explores how readers’ meaning making was influenced when reading prose versus comics. This paper adds to a corpus of scholarship about the relationships between young adult literature, comics, bodies and reader response theory.

At the time of the study, participants were enrolled in a teacher education program at a Midwestern University, meeting monthly for a voluntary book club dedicated to reading and discussing young adult literature. To examine readers’ responses to comics and prose featuring fat-identified protagonists, the author used descriptive qualitative methodologies to conduct a thematic analysis of meeting transcripts, written participant reflections and researcher memos. Analysis was grounded in theories of reader response, critical fat studies and multimodality.

Analyses indicated many readers reject textual clues indicating a character’s body size and weight were different from their own. Readers read their bodies into the stories, regarding them as self-help narratives instead of radical counternarratives. Some readers were not able to read against their assumptions of thinness (and whiteness) until prompted by the researcher and other participants.

Although many reader response scholars have demonstrated readers’ tendencies toward personal identification in the face of racial and class differences, there is less research regarding classroom practices around the entanglement of physical bodies, body image and texts. Analyzing reader’s responses to the constructions of fat bodies in prose versus comics may help English Language Arts (ELA) educators and students identify and deconstruct ideologies of thin-thinking and fatphobia. This study, which demonstrates thin readers’ tendencies to overidentify with protagonists, suggests ELA classrooms might encourage readers to engage in critical literacies that support them in reading both with and against their identities.

This study aims to explore the perceived barriers that a secondary English teacher faced when attempting to discuss racial injustice through young adult literature in Mississippi.

The authors rely on Critical Whiteness Studies and qualitative methods to explore the following research question: What are the barriers that a White ELA teacher perceives when teaching about racial injustice through The Hate U Give?

The authors found that there were several perceived barriers to discussing modern racial injustice in the Mississippi ELA classroom. The participating teacher indicated the following barriers: a lack of racial literacy, fears of discomfort and an urge to avoid politics.

Much has been written about the urgent need for antiracist teaching practices in secondary English classes. This article explores the barriers a white ELA teacher perceived when attempting to discuss modern racial injustice through literature instruction in a white context of the “four pandemics” (Ladson-Billings, 2021).

By engaging levels of W/writerliness, this paper aims to identify how English Language Arts teachers’ personal and professional W/writerly identities impact their performance of pedagogical agency.

In this narrative inquiry, the author draws on theories of writing identity and agency to analyze how four mid-career English teachers’ personal beliefs around writing intersect with their professional practice. Data sources include interviews, journal entries and classroom observations.

Nuanced differences in teachers’ W/writerly identities produce more substantial differences in their pedagogy, especially impacting their performance of agency to (re)define successful writing outcomes and to balance process and product in their writing instruction.

This paper presents one method to expand preservice and in-service English Language Arts (ELA) practitioners’ approaches to teaching writing even alongside limitations of their teaching context by (1) emphasizing their ownership over their own writing in university methods courses; (2) leading teachers on an exploration of W/writerly identities; and (3) investigating ways teachers can transfer their personal and professional learning to students via their own pedagogical agency.

The study extends the work of scholars in the National Writing Project, suggesting that nuanced exploration of ELA teachers’ W/writerly identities in preservice and in-service settings could increase their sense of agency to work against and within cultures of standardization.

Challenges of conducting site visit activities, a vital component of architecture learning during the recent pandemic have proved our unreadiness in facing the digital future. The lack of understanding of learning technology has affected the education experience. Thus, there is a need to investigate immersive learning technology such as immersive virtual reality (IVR) to replace students’ concrete experience in the current learning setting. This study aims to answer: (1) What is the influence of IVR in experiential learning (EL) in enhancing the personal spatial experience? (2) Does IVR in EL influence students' approach to learning during the architecture design process?

The research was conducted as an action research design approach. Action research was employed in the first-year architecture design studio by the lecturer as a practitioner-researcher. The personal spatial experience survey was performed in the earlier phase to identify the students’ prior spatial experience. Architectural Spatial Experience Simulation (ASES) a learning tool was implemented and assessed with Architecture Design Learning Assessment (ADLA) rubric, which was developed to evaluate EL and student’s approach to learning during the architecture design learning process.

The outcomes revealed that ASES as a learning tool in EL could improve the participants’ spatial experience, particularly those with minimal prior personal spatial experience. ASES was recognized to enhance the participants’ EL experience and encourage changes in student’s approach to learning from surface to deep learning.

This research benefits the architecture design learning process by offering a learning tool and a framework to resolve challenges in performing site visit activities and digital learning. It also contributes by expanding the EL theory and students’ approach to learning knowledge in the architecture education field.

This paper explores a five-year case example of two educators engaged in practice-based professional development (PBPD) for the Self-Regulated Strategy Development (SRSD) model in a middle school. It examines the transformative effects and challenges of improving writing instruction, the activities involved and alternative PBPD delivery methods. Highlighting a collaborative effort between an institute of higher education (IHE), a middle school and ThinkSRSD, a PBPD for SRSD developer, the example underscores the long-term benefits and innovative insights into engaging with PBPD for SRSD over multiple years.

The case involves analyzing survey data collected over five years. These surveys, which included specific SRSD-related queries and open-ended questions, were instrumental in assessing the evolution of the educators’ perceptions regarding SRSD and their engagement with PBPD. Additionally, the paper details PBPD activities as documented in a research journal, providing a comprehensive account of the developmental process.

Through a cross-institutional partnership, two middle school general educators participated in PBPD for SRSD for 30 h across five years. Their engagement with PBPD progressed from initial introduction and implementation to facilitating PBPD for SRSD among peers and at the national level. Over time, the most consistently enacted SRSD action was “memorize it,” while actions such as “discuss it,” “support it” and “independent performance” showed greater variability. Both educators consistently praised SRSD and sought continued PBPD engagement over the five years.

Our case example is the first five-year analysis of PBPD for SRSD among general middle school educators, highlighting the benefits and challenges of adopting evidence-based writing instruction. Our example emphasizes the need for continuous and focused professional development in areas crucial for student success, including self-regulation, prewriting strategies and techniques for fostering independent performance. Moreover, the two middle school educators’ critical feedback is invaluable for refining PBPD for SRSD. This work also enriches professional development schools (PDS) literature by offering effective strategies to support middle school teachers in developing a vibrant writing community, a cornerstone for student advancement in writing.

Arts-integration is a promising approach to building students’ abilities to create and critique arguments with data, also known as informal inferential reasoning (IIR). However, differences in disciplinary practices and routines, as well as school organization and culture, can pose barriers to subject integration. The purpose of this study is to describe synergies and tensions between data science and the arts, and how these can create or constrain opportunities for learners to engage in IIR.

The authors co-designed and implemented four arts-integrated data literacy units with 10 teachers of arts and mathematics in middle school classrooms from four different schools in the USA. The data include student-generated artwork and their written rationales, and interviews with teachers and students. Through maximum variation sampling, the authors identified examples from the data to illustrate disciplinary synergies and tensions that appeared to support different IIR processes among students.

Aspects of artistic representation, including embodiment, narrative and visual image; and aspects of the culture of arts, including an emphasis on personal experience, the acknowledgement of subjectivity and considerations for the audience’s perspective, created synergies and tensions that both offered and hindered opportunities for IIR (i.e. going beyond data, using data as evidence and expressing uncertainty).

This study answers calls for humanistic approaches to data literacy education. It contributes an interdisciplinary perspective on data literacy that complements other context-oriented perspectives on data science. This study also offers recommendations for how designers and educators can capitalize on synergies and mitigate tensions between domains to promote successful IIR in arts-integrated data literacy education.

Within the scope of the research, articles about service robots were examined by the systematic review method.

The research aims to evaluate the articles on service robots, an artificial intelligence (AI) application in restaurant businesses, using a systematic review method. In systematic reviews, the data obtained as a result of scanning databases to find an answer to a research question are synthesized and reported. The criterion sampling technique, one of the purposeful sampling methods, was used for the sample of the research. Inclusion and exclusion criteria were applied within the scope of screening.

The articles on service robots were carried out between 2018 and 2023. In terms of research methods, most of the articles are quantitative, while there are studies on mixed and qualitative methods. In studies, data were generally collected by survey technique. The keywords of the studies on service robots are examined; the most commonly used words were service robot and AI, technology, restaurant, satisfaction, revisit intention, consumer behavior, intention, preference, hospitality and foods. The objectives of the articles pertinent to service robots are mostly to determine people's attitudes and acceptance toward these services focuses.

The studies seem to focus more on customer acceptance, trust, expectations, risks, adaptation, reasons for preference, impact on creative services, emotional and cognitive effects and human–robot interaction. Despite this, it is observed that there are fewer studies on topics such as the development of service robots in restaurant businesses, their reflections on the future, future opportunities and the quality of chef service robots. Based on this, it is recommended to consider studies that will serve as a reference for revealing innovative opportunities that can meet future expectations in order to increase the quality of service robots in restaurant businesses.