Search results

This chapter traces the origin of racism and reviews the historical and contemporary debates around race and racialisation in western thought. There are persistent disagreements surrounding the origin and nature of racism. Because of the evolution of racist ideas, behaviours and institutional practices and policies, there are various views about the meaning and analytical application of racism. This chapter explores how ideas of race – understood as innate and immutable human differences that can be classified and ranked hierarchically based on race – has emerged in western history and evolved over time. It examines how this has influenced social and political practices and associated policies across the evolution of modernity. The chapter specifically discusses the Atlantic slave trade and how it shaped the historical development of race and racism within the context of colonialism. It concludes with a discussion and critical review of some of the racist systems and policies which have been enforced across different multiracial countries.

Developing a reliable cost estimate at the early stage of construction projects is challenging due to inadequate project information. Most of the information during this stage is qualitative, posing additional challenges to achieving accurate cost estimates. Additionally, there is a lack of tools that use qualitative project information and forecast the budgets required for project completion. This research, therefore, aims to develop a model for setting project budgets (excluding land) during the pre-conceptual stage of residential buildings, where project information is mainly qualitative.

Due to the qualitative nature of project information at the pre-conception stage, a natural language processing model, DistilBERT (Distilled Bidirectional Encoder Representations from Transformers), was trained to predict the cost range of residential buildings at the pre-conception stage. The training and evaluation data included 63,899 building permit activity records (2021–2022) from the Victorian State Building Authority, Australia. The input data comprised the project description of each record, which included project location and basic material types (floor, frame, roofing, and external wall).

This research designed a novel tool for predicting the project budget based on preliminary project information. The model achieved 79% accuracy in classifying residential buildings into three cost_classes ($100,000-$300,000, $300,000-$500,000, $500,000-$1,200,000) and F1-scores of 0.85, 0.73, and 0.74, respectively. Additionally, the results show that the model learnt the contextual relationship between qualitative data like project location and cost.

The current model was developed using data from Victoria state in Australia; hence, it would not return relevant outcomes for other contexts. However, future studies can adopt the methods to develop similar models for their context.

This research is the first to leverage a deep learning model, DistilBERT, for cost estimation at the pre-conception stage using basic project information like location and material types. Therefore, the model would contribute to overcoming data limitations for cost estimation at the pre-conception stage. Residential building stakeholders, like clients, designers, and estimators, can use the model to forecast the project budget at the pre-conception stage to facilitate decision-making.

The purpose of this paper is to share findings from empirically driven conceptual research into the implications for English teachers of understanding generative AI as a “tool” for writing.

The paper reports early findings from an Australian National Survey of English teachers and interrogates the notion of the AI writer as “tool” through intersectional feminist discursive-material analysis of the metaphorical entailments of the term.

Through this work, the authors have developed the concept of “coloniser tool-thinking” and juxtaposed it with First Nations and feminist understandings of “tools” and “objects” to demonstrate risks to the pursuit of social and planetary justice through understanding generative AI as a tool for English teachers and students.

Bringing together white and First Nations English researchers in dialogue, the paper contributes a unique perspective to challenge widespread and common-sense use of “tool” for generative AI services.

This concluding chapter summarises the main themes and topics discussed in this book, synthesising the key issues facing contemporary anti-racism efforts. It reflects on a possible anti-racist future(s) in a context of greater sociocultural affiliations and more interconnected local and global environments. Ideas about race and ethnicity have adapted, and racial hierarchies, structures and processes continuously shape the way social groups engage, interact and live with difference. This raises questions regarding the enduring influence of race and racism. What will the state of multiracial societies be in the evolving digital economy that has transformed the structural and institutional environment affecting everyday life? What kind of an anti-racist future can be imagined that will contribute to ensuring greater social equity? This chapter ponders on a range of possibilities to chart directions towards an anti-racist future that fosters increased intercultural understanding for relational engagements across difference. It draws conclusions and lessons for an anti-racist future and lays out some directions for future research.

This chapter examines the concepts of race and racism, critically reviewing their historical and contemporary applications in everyday life as well as in academic and policy debates. Racism has been extensively researched, with various theories and conceptualisations developed across social science. However, there is a great deal of disagreement regarding its nature, contemporary significance and empirical validation. This chapter examines these and attempts to synthesise some of the common definitions of racism provided in the literature. It explores related concepts and underlying themes pertaining to expressions of race and racism. Furthermore, it unpacks current knowledge about racial issues and discusses recent advances in the conceptual understanding of various forms of racism. It also elucidates the social, political and analytical applications of racism as a concept and the significance of racism in contemporary societies. The chapter concludes by highlighting how racism is a dynamic phenomenon, continuously evolving with the social, political and technological transformations in contemporary societies.

While technical vocational education training (TVET) has been studied in-depth, the evolution and performance patterns of the subject remain unknown and limited. A bibliometric analysis was performed to examine the global scientific literature to assess the state of the art in TVET research over the past 23 years.

The Web of Science (WoS) database was searched to explore TVET-related research from 1999 to 2021, resulting in the identification of 7,512 articles. The VOSviewer software was used to investigate the network of collaboration between authors, institutions, countries and author keywords.

The results reveal that the subject categories of “education” and “educational research” are the most prolific contributors to TVET-related research, with 3,314 articles. Most of the previous studies in Phase I (1999–2006) focussed on human capital resources development in the TVET sector. Phase II (2007–2014) follows with the centralisation of TVET, focussing on technology transition in education. However, in Phase III (2015–2021), researchers appear to focus on vocational studies in higher education towards increasing the productivity of human resources via the implementation of technology transition.

The valuable findings of this study can facilitate better understanding among scholars on the trends of TVET research developments and on the direction of future research.

This paper bridges the gap between the theory and practice by developing a life cycle sustainability tracker (LCST). The study is seeking to proffer solutions to an observed shortcoming of conventional life cycle sustainability assessment (LCSA) communication platforms. Notably, the static nature of the information provided on such platforms has made it difficult for them to be used for real-time decision-making and predictions. The main aim of this paper is to develop a LCST that facilitates a dynamic visualisation of life cycle sustainability results and allows for an integrated benchmark across the dimensions of sustainability.

The study leverages the model development capabilities of the design science research strategy in accomplishing a dynamic and novel communication platform. A life cycle thinking methodology and appropriate multicriteria decision approach (MCDA) is applied to accomplish a comprehensive, streamlined and replicable approach in mapping and tracking the progress of sustainable development goals (SDGs) in the National Infrastructure Pipeline (NIP) projects in India.

It was found that: (1) The use of the LCST tracker provides a dynamic and holistic insight into the key LCSA indicators with clearly defined benchmarks to assess the impact on the SDG 11, (2) The NIP projects achieve an upward trend across all the regions, and the percentage of opportunities ranges from 11 to 24%, with the South experiencing the highest growth and the North having the minimal increase in percentage and (3) The assessment score (52–58%) provides performance metrics that align well with the LCST – which ranges between “Fair” and “Average” for all the regions in India.

The novelty of this research is that the LCST provides a transparent and harmonised approach to reporting on the LCSA results. The LCST utilises heat maps and radial mapping to achieve an intuitive display of large amounts of highly heterogeneous data, thus allowing the synthesis of large sets of information compactly and with coherence. Progress towards the SDGs change on a yearly basis; hence, a dynamic LCSA tool provides a timely and the valuable context to map and track performance across different regions and contexts.

The purpose of this paper is to provide a transcript of a dialogue among literacy educators and researchers on the impact of generative aritficial intelligence (AI) in the field. In the spring of 2023, a lively conversation emerged on the National Council of Research on Language and Literacy (NCRLL)’s listserv. Stephanie initiated the conversation by sharing an op-ed she wrote for Atlanta Journal-Constitution about the rise of ChatGPT and similar generative AI platforms, moving beyond the general public’s concerns about student cheating and robot takeovers. NCRLL then convened a webinar of eight leading scholars in writing and literacies development, inspired by that listerv conversation and an organizational interest in promoting intergenerational collaboration among literacy scholars.

As former doctoral students of two of the panel participants, webinar facilitators Grace and Victoria positioned themselves primarily as learners about this topic and gathered questions from colleagues, P-16 practitioners and those outside the field of education to assess the concerns and wonderings that ChatGPT and generative AI have raised. The following webinar conversation was recorded on two different days due to scheduling conflicts. It has been merged and edited into one dialogue for coherence and convergence.

Panel participants raise a host of questions and issues that go beyond topics of ethics, morality and basic writing instruction. Furthermore, in dialogue with one another, they describe possibilities for meaningful pedagogy and critical literacy to ensure that generative AI is used for a socially just future for students. While the discussion addressed matters of pedagogy, definitions of literacy and the purpose of (literacy) education, other themes included a critique of capitalism; an interrogation of the systems of power and oppression involved in using generative AI; and the philosophical, ontological, ethical and practical life questions about being human.

This paper provides a glimpse into one of the first panel conversations about ChatGPT and generative AI in the field of literacy. Not only are the panel members respected scholars in the field, they are also former doctoral students and advisors of one another, thus positioning all involved as both learners and teachers of this new technology.

Anti-racism has been practiced in various ways, with varying degrees of effectiveness. This chapter engages with the body of scholarship that focuses on approaches aimed at promoting anti-racist actions, policies and social change. It discusses some of the main anti-racism strategies that have been deployed across different countries and examines anti-racism practices in interpersonal, intergroup and community settings. These approaches encompass civil rights campaigns, legislative and policy interventions, affirmative action, diversity and inclusion training, prejudice reduction, intergroup contact, organisational development and holistic anti-racism approaches. Some anti-racism practices and policies, such as awareness campaigns, social marketing and diversity training, also extend to digital platforms, with social media and multimedia networks deployed to broaden the reach and impact of anti-racist endeavours. This chapter specifically engages with local anti-racism movements and draws principles for broader implementation of anti-racism policy and practice. It concludes with a brief discussion of the effectiveness of contemporary anti-racism approaches.

Racism occurs in many ways and varies across countries, evolving and adapting to sociocultural history, as well as contemporary economic, political and technological changes. This chapter discusses the multilevel dimensions of racism and its diverse manifestations across multiracial societies. It examines how different aspects of racism are mediated interpersonally, and embedded in institutions, social structures and processes, that produce and sustain racial inequities in power, resources and lived experiences. Furthermore, this chapter explores the direct and indirect ways racism is expressed in online and offline platforms and details its impacts on various groups based on their intersecting social and cultural identities. Targets of racism are those who primarily bear the adverse effects. However, racism also affects its perpetrators in many ways, including by limiting their social relations and attachments, and by imposing social and economic costs. This chapter thus analyses the many aspects of racism both from targets and perpetrators' perspectives.