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This research addresses a need in early childhood education for evidence-based teaching strategies that build emotional self-regulation skills in young children. The intervention assessed in this study focused on increasing the emotion vocabulary of preschool-aged students.

This mixed-methods, quasi-experimental study evaluated the impact a dialogic reading approach combined with direct instruction of emotion words during a shared book-reading activity had on students' emotion vocabulary knowledge. The study was conducted in a licensed daycare center in a suburb of Chicago, Illinois, with ten four- and five-year-old students. Pre- and post-session surveys assessed the intervention's impact on the students' receptive and expressive vocabulary knowledge, and observation notes captured the students' responses to the intervention activities.

The results showed significant increases with small to medium effect sizes between the students’ pre- and post-session survey scores for both receptive and expressive emotion vocabulary knowledge, a strong positive correlation between the level of student engagement during the intervention and their emotion vocabulary assessment scores, and the impact other variables had on the intervention’s effectiveness.

This research provides information on a culturally adaptable and quickly learned teaching strategy that could be used to build emotional self-regulation skills in the early childhood classroom.

This research uniquely applies this intervention as a universal strategy with preschool-aged children.

In this study, STEM resources reviewed in Goodreads were investigated to determine their authorship, linguistic characteristics and impact. The analysis reveals gender disparity favoring titles with male authors.

This paper applies theoretical concepts of knowledge commons to understand how individuals leverage the affordances of the Goodreads platform to share their perceptions of STEM-related books.

The analysis reveals gender disparity favoring titles with male authors. Female-authored STEM publications represent popular science nonfiction and juvenile genres. Analysis of the scholarly impact of the reviewed titles revealed that Google Scholar provides broader and more diverse coverage than Web of Science. Linguistic analysis of the reviews revealed the relatively low aesthetic disposition of reviewers with an emphasis on embodied experiences that emerged from the reading.

This study contributes to the understanding of the impact of popular STEM resources as well as the influence of the language of user-generated reviews on production, consumption and discoverability of STEM titles.

This paper aims to trace how Asian American girls engaged with civic learning in a virtual out-of-school literacy community featuring a curriculum of diverse literary texts.

The researcher used practitioner inquiry to construct a virtual literacy education community dedicated to the civic learning of Asian American girls.

The paper explores how participants mobilized critical practices of textual consumption and production rooted in their intersectional identities and embodied experiences to make meaning of the civic constraints and affordances of marginalized identities and to read and (re)design author choices for civic purposes. These findings – examples of youths’ critical civic meaning-making – indicate how they claimed space for Asian American civic girlhoods in literacy education.

This paper foregrounds how Asian American girls mobilize critical processes of text consumption and production to assert civic identities in literacy education – a significantly under-examined topic in literacy studies. This work has implications for how literacy practitioners and scholars can prioritize Asian American civic girlhoods through pedagogy and research.

Maintaining the safety of the human is a major concern in factories where humans co-exist with robots and other physical tools. Typically, the area around the robots is monitored using lasers. However, lasers cannot distinguish between human and non-human objects in the robot’s path. Stopping or slowing down the robot when non-human objects approach is unproductive. This research contribution addresses that inefficiency by showing how computer-vision techniques can be used instead of lasers which improve up-time of the robot.

A computer-vision safety system is presented. Image segmentation, 3D point clouds, face recognition, hand gesture recognition, speed and trajectory tracking and a digital twin are used. Using speed and separation, the robot’s speed is controlled based on the nearest location of humans accurate to their body shape. The computer-vision safety system is compared to a traditional laser measure. The system is evaluated in a controlled test, and in the field.

Computer-vision and lasers are shown to be equivalent by a measure of relationship and measure of agreement. R² is given as 0.999983. The two methods are systematically producing similar results, as the bias is close to zero, at 0.060 mm. Using Bland–Altman analysis, 95% of the differences lie within the limits of maximum acceptable differences.

In this paper an original model for future computer-vision safety systems is described which is equivalent to existing laser systems, identifies and adapts to particular humans and reduces the need to slow and stop systems thereby improving efficiency. The implication is that computer-vision can be used to substitute lasers and permit adaptive robotic control in human–robot collaboration systems.

This article aims to help educators provide a holistic view of the LGBTQ community by highlighting children’s books that include non-parental LGBTQ characters.

The author selected over 80 children’s books honored by the American Library Association’s Rainbow Book List. Twenty-two books were analyzed that contain examples of LGBTQ adults existing beyond the homonormative nuclear family, e.g. two same-sex parents raising children.

The author discusses various ways of living represented in these books, such as chosen families, extended families, romantic partnerships and singlehood.

With the increased number of high-quality LGBTQ-inclusive children’s books published in the past decade, this study provides the foundation for educators to select various texts that reveal diverse representations of LGBTQ individuals.

When companies face a crisis, they sometimes deliver blame-shifting communications, trying to shift blame onto another actor to protect their reputation. While previous research has considered how different features of the message affect its persuasiveness, little is known about whether specific senders can blame more effectively. This paper aims to contribute to research in this domain through an investigation of the sender’s social perception as a critical moderator to the persuasiveness of blame shifting.

The authors conduct four between-subjects scenario experiments to test the research hypotheses. In each experiment, participants are presented with a realistic crisis scenario and the crisis communications delivered by the company. The authors assess the extent to which perceptions of the sender influence the message’s ability to reduce negative word-of-mouth intentions and to increase purchase intentions.

The authors show that blame shifting is more likely to be effective when deployed by senders that are small (Study 1) or have a positive CSR track record (Study 2). Furthermore, The authors find that even large senders can successfully deploy blame shifting if they can benefit from being known for their CSR programs (Study 3). Finally, the authors show that the effect of blame shifting depends on the receiver’s level of concern about the crisis: stakeholders significantly concerned by the crisis reject blame-shifting communications (Study 4).

Further research should examine the impact of information about brand competence on blame-shifting effectiveness. Further research is also needed to explore sender effects for other defensive crisis communication strategies such as denial or the use of excuses or justifications.

The study offers critical information for marketers considering the use of defensive crisis communications strategies such as blame shifting.

The study extends the understanding of how sender effects influence blame-shifting communications. The analysis allows us to clarify why this strategy is effective for certain senders and certain receivers while, for others, it tends to backfire. Blame shifting backfires for large senders unless they can boast a strong CSR record.

With a historic lack of attention to synthesis methods such as systematic review and meta-analysis and a lack of randomised controlled trials, the evidence base for behavioural interventions for children and adults who are autistic or are diagnosed with developmental disabilities is patchy. The Sharland Foundation Developmental Disabilities Applied Behavioural Research and Impact Network (SF-DDARIN), a network of like-minded researchers and practitioners across the UK, aims to address this. The purpose of this paper is to describe the network’s work and provide the context for the remaining articles in the special issue that exemplify network projects.

In this case study paper, the authors describe how the SF-DDARIN works and is resourced, detailing the process used to maximise research opportunities by facilitating network members working together. The authors outline the progressive research steps that the SF-DDARIN has identified are needed to develop and improve the evidence base for behavioural interventions systematically and, with examples, describe how the network delivers these steps.

Since its establishment in 2016, the SF-DDARIN network members have collectively worked on more than 53 projects involving over 50 researchers, had over 120 special schools contribute to projects and have recruited over 500 participants. This has been achieved through funding from the Sharland Foundation, primarily to cover the staffing costs of a small support team and internship partnerships with external organisations. Some projects have attracted external funding.

SF-DDARIN may provide an innovative, effective and resource-efficient model for other groups seeking to develop and extend their evidence base in developmental disability research.

The purpose of this paper is to develop a blockchain-based data capture and transmission system that will collect real-time power consumption data from a household electrical appliance and transfer it securely to a local server for energy analytics such as forecasting.

The data capture system is composed of two current transformer (CT) sensors connected to two different electrical appliances. The CT sensors send the power readings to two Arduino microcontrollers which in turn connect to a Raspberry-Pi for aggregating the data. Blockchain is then enabled onto the Raspberry-Pi through a Java API so that the data are transmitted securely to a server. The server provides real-time visualization of the data as well as prediction using the multi-layer perceptron (MLP) and long short term memory (LSTM) algorithms.

The results for the blockchain analysis demonstrate that when the data readings are transmitted in smaller blocks, the security is much greater as compared with blocks of larger size. To assess the accuracy of the prediction algorithms data were collected for a 20 min interval to train the model and the algorithms were evaluated using the sliding window approach. The mean average percentage error (MAPE) was used to assess the accuracy of the algorithms and a MAPE of 1.62% and 1.99% was obtained for the LSTM and MLP algorithms, respectively.

A detailed performance analysis of the blockchain-based transmission model using time complexity, throughput and latency as well as energy forecasting has been performed.

A maturity model for Industry 4.0 (I4.0 MM) with influencing factors is designed to address maturity issues in adopting Industry 4.0. Standardisation in I4.0 supports manufacturing industry transformation, forming reference architecture models (RAMs). This paper aligns key factors and maturity levels in I4.0 MMs with reputable I4.0 RAMs to enhance strategy for I4.0 transformation and implementation.

Three steps of alignment consist of the systematic literature review (SLR) method to study the current published high-quality I4.0 MMs, the taxonomy development of I4.0 influencing factors by adapting and implementing the categorisation of system theories and aligning I4.0 MMs with RAMs.

The study discovered that different I4.0 MMs lead to varied organisational interpretations. Challenges and insights arise when aligning I4.0 MMs with RAMs. Aligning MM levels with RAM stages is a crucial milestone in the journey toward I4.0 transformation. Evidence indicates that I4.0 MMs and RAMs often overlook the cultural domain.

Findings contribute to the literature on aligning capabilities with implementation strategies while employing I4.0 MMs and RAMs. We use five RAMs (RAMI4.0, NIST-SME, IMSA, IVRA and IIRA), and as a common limitation in SLR, there could be a subjective bias in reading and selecting literature.

To fully leverage the capabilities of RAMs as part of the I4.0 implementation strategy, companies should initiate the process by undertaking a thorough needs assessment using I4.0 MMs.

The novelty of this paper lies in being the first to examine the alignment of I4.0 MMs with established RAMs. It offers valuable insights for improving I4.0 implementation strategies, especially for companies using both MMs and RAMs in their transformation efforts.

This study aims to inform and guide information professionals in thinking clearly about the challenges and opportunities this technology may create.

This column uses the Web browser Arc as a focal point for exploring elements that seem key to understanding how artificial intelligence (AI) may change our relationship with information. Large language model’s were used to help draft or rewrite sentences. That text was then reviewed or revised by the author.

The following elements are key to understanding the potential of informational interface software like Arc. The ability to abstract information from the original content. The ability to produce multimedia compelling user experiences. The ability to “read” multimodal forms of information and take action based on that “understanding”. This may impact the value exchange between the user and the underlying information, with implications for libraries.

Everything about AI the future of AI or any technology is speculative.

Libraries that wish to continue to be part of adding value to how users interact with information need to pay attention and find ways to adapt.

As new paradigms are created to ensure information exchange is sustainable for everyone, there may be opportunities for libraries. And even if not, libraries may leverage their expertise or relationships to build something that could not be imagined without them. Yet these are only possible if libraries engage.