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The purpose of this study is to explore mathematics teachers' collaboration within their professional learning communities (PLCs), and to gain insight into how the teachers developed their collective efficacy through it to focus on improving student learning.

Using a qualitative approach, data were collected from three high-performing secondary schools, mainly through semi-structured in-depth interviews with the Heads of Mathematics Unit. For explication and triangulation purposes, focus group interviews with the mathematics teachers and students and document analysis were also conducted.

The findings indicate that PLCs were the vessel through which a culture of disciplined teacher collaboration was fostered. More importantly, this culture encouraged teachers to participate in reflective dialogues that became a driver for their learning, and eventually led to their changed professional practice for improved student learning. The collaborative setting within the PLCs allowed teachers to pool their resources, knowledge and individual expertise to identify their student learning focus, and administer and measure their student intervention strategies. This collaborative professional learning reduced professional isolation, and as a result, improved teachers' collective pursuit of professional growth to impact student outcomes.

The aim of this qualitative study was to provide a detailed description of the teachers' collaboration within their PLCs based on the researchers' interpretation of how the participants make sense of their PLC practices and experiences. Hence, findings are indicative, and not definitive. In addition, the Heads of the Mathematics Unit, and the mathematics teacher participants in this study illustrated salient aspects of subject subcultures, where their beliefs, norms and practices were non-generic, or specific only to their subject context. Therefore, the implications to practice were built from commonalities shared only among the mathematics units.

This is a study in a Malaysian context that provides empirical evidences that are concerned primarily with the process of teachers developing their collective efficacy through disciplined collaboration within their PLCs.

The purpose of this study was to analyze importance of artificial intelligence (AI) in education and its emphasis on assessment and adversity quotient (AQ).

The study utilizes a systematic literature review of over 141 journal papers and psychometric tests to evaluate AQ. Thematic analysis of quantitative and qualitative studies explores domains of AI in education.

Results suggest that assessing the AQ of students with the help of AI techniques is necessary. Education is a vital tool to develop and improve natural intelligence, and this survey presents the discourse use of AI techniques and behavioral strategies in the education sector of the recent era. The study proposes a conceptual framework of AQ with the help of assessment style for higher education undergraduates.

Research on AQ evaluation in the Indian context is still emerging, presenting a potential avenue for future research. Investigating the relationship between AQ and academic performance among Indian students is a crucial area of research. This can provide insights into the role of AQ in academic motivation, persistence and success in different academic disciplines and levels of education. AQ evaluation offers valuable insights into how individuals deal with and overcome challenges. The findings of this study have implications for higher education institutions to prepare for future challenges and better equip students with necessary skills for success. The papers reviewed related to AI for education opens research opportunities in the field of psychometrics, educational assessment and the evaluation of AQ.

Athletes have leveraged their social platform and reach to advocate for a variety of social causes. Most recently, given the persistent impacts of climate change on sport, the sport sector has been leveraged to engage and educate fans, sport participants, and athletes to promote climate action while consuming sport and in their everyday lives. This chapter conceptualizes the term sport eco-activism and presents a rich history of the early stages of this form of activism and its interaction with sport. Specifically, we provide historical context and examples of how athletes and activist sport organizations (e.g., Surfers Against Sewage, Protect Our Winters) have drawn attention to the impacts of climate change on sport. We also highlight how these entities encourage spectators and participants to change their behaviors and further advocate for collective climate action. In addition, we offer insights on future directions of eco-activism within sport and how such activists can best resonate with their target audiences to create positive change through sport.

An important facet of student’s sense of belonging is students’ relationships with, and time spent in, the university campus. The purpose of this paper is to explore the notion that access to campus “green space”, including parks, fields and gardens, may bolster students’ sense of belonging, improve well-being feelings and promote place attachment.

The authors surveyed students in different locations (including three green and one non-green campus spaces) across a large UK campus-based Northern institution. 146 students participated in the study in one of the four campus locations. The authors investigated how being in green spaces on campus may impact students’ sense of belonging, well-being and place attachment. The authors also qualitatively explored students’ perceptions of campus spaces through Ahn’s (2017) 10 Words Question measure.

Analyses demonstrate that students surveyed in green spaces reported significantly more positive sense of belonging, compared to students surveyed in non-green campus spaces. Campus location did not impact well-being, however. Students associated green spaces on campus with “calm”, “positive emotion” and “nature” words and non-green spaces with “busy”, “social” and “students”.

Taken together, the results of this paper suggest that access to green spaces can be important for campus sense of belonging. Thus, efforts should be made to ensure the sustainability of these important spaces across university campuses.

This study crucially examines how occupying green spaces on university campuses may impact students’ feelings of belongingness. To the best of the authors’ knowledge, this is the first study that uses field-based methods to understand students’ feelings whilst occupying green spaces.

This paper aims to review in-memory computing (IMC) for machine learning (ML) applications from history, architectures and options aspects. In this review, the authors investigate different architectural aspects and collect and provide our comparative evaluations.

Collecting over 40 IMC papers related to hardware design and optimization techniques of recent years, then classify them into three optimization option categories: optimization through graphic processing unit (GPU), optimization through reduced precision and optimization through hardware accelerator. Then, the authors brief those techniques in aspects such as what kind of data set it applied, how it is designed and what is the contribution of this design.

ML algorithms are potent tools accommodated on IMC architecture. Although general-purpose hardware (central processing units and GPUs) can supply explicit solutions, their energy efficiencies have limitations because of their excessive flexibility support. On the other hand, hardware accelerators (field programmable gate arrays and application-specific integrated circuits) win on the energy efficiency aspect, but individual accelerator often adapts exclusively to ax single ML approach (family). From a long hardware evolution perspective, hardware/software collaboration heterogeneity design from hybrid platforms is an option for the researcher.

IMC’s optimization enables high-speed processing, increases performance and analyzes massive volumes of data in real-time. This work reviews IMC and its evolution. Then, the authors categorize three optimization paths for the IMC architecture to improve performance metrics.

As a part of doctoral study, this study aims to analyze research on library management models (LMMs) by conducting a systematic literature review (SLR).

A Preferred Reporting Items for Systematic Review and Mata-Analysis approach was used to search four databases. The search criteria included studies published in English until 2022, resulting 9,125 records. Out of these records, a total of 36 studies were selected for final analysis

The results show a positive attitude among researchers toward the development of LMM for libraries globally. The results depict that more than one-third (39%) of the target population was comprised of academic staff and students. The majority (91.76%) of studies were conducted using survey. Quantitative methods were predominant (89%) for LMMs. There were a significant number of studies conducted in 2016. The country-wise distribution shows the USA and China each contribute (20%) of the studies.

The findings of this research could assist policymakers and authorities in reconciling the LMMs applied in libraries for providing efficient access to information resources and services to end users.

To the best of the authors’ knowledge, this study is unique as no comprehensive study has been conducted on LMMs using the SLR method.

The present study aims to explore the intergenerational differences in the virtue of appreciation. The construct of appreciation takes a broadened perspective with six dimensions of “have” focus, awe, ritual, present moment, loss/adversity and interpersonal appreciation. Four different generations are studied – baby boomers (above 55 years), pre-millennial or Generation X (41–55 years), millennial or Generation Y (23–39 years) and post-millennial or Generation Z (below 23 years).

The collected data is analyzed in two stages. First, the adaptability of the scale is examined using exploratory factor analysis, confirmatory factor analysis, reliability and validity estimates. And in the second stage, the variations in appreciation scores are explored using ANOVA and post hoc analysis.

The results reveal statistically significant intergenerational differences among four subscales of appreciation, i.e. “have” focus, awe, present moment and loss/adversity. Only one subscale of appreciation, i.e. ritual, does not vary significantly across respondents of different generations. Also, younger generations have lesser scores on subscales of appreciation than older generations. Thus, it seems that older generations are generally more appreciative than younger generations.

The present study, to the best of the authors’ knowledge, could be the first research that examines the variation among generations for the experience of broader construct of appreciation within the Indian context.