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The purpose of this article is to theoretically outline and empirically test two contribution-based indicators: (1) the scholars' annual contribution-based measurement and (2) the annual contribution modified h-index, computing six criteria: total number of papers, computed SCImago Journal Rank values, total number of authors, total number of citations of a scholar’s work, number of years since paper publication and number of annual paper citations.

Despite widespread scholarly agreement about the relevance of research production in evaluation and recruitment processes, the proposed mechanisms for gauging publication output are still rather elementary, consequently obscuring each individual scholar’s contributions. This study utilised the Technique for Order of Preference by Similarity to Ideal Solution method, and the authors built two indicators to value author's contribution.

To test both indicators, this study focussed on the most productive scholars in communication during a specific time period (2017–2020), ranking their annual research contribution and testing it against standard productivity measures (i.e. number of papers and h-index).

This article contributes to current scientometric studies by addressing some of the limitations of aggregate-level measurements of research production, providing a much-needed understanding of scholarly productivity based on scholars' actual contribution to research.

The purpose of this paper is to explore students' mathematization through a flow of lessons using the Thailand Lesson Study Incorporated Open Approach (TLSOA) to improve the excellence of instruction.

A total of 16 Grade 4 students were selected because they have been taught using the TLSOA model for four years. Six Lesson Study (LS) team members participated, and two instruments were utilized, namely student worksheets, and field notes. An ethnographic research design was employed.

The results revealed that the students' mathematical ideas were developed from the real world to the mathematical world through a flow of lessons based on the four phases of the Open Approach (OA).

Firstly, the students demonstrated their ability to represent the real world independently when the teacher posed an open-ended problem. Secondly, the students demonstrated their ability to use semi-concrete aids to develop their ideas while self-learning. Thirdly, the students showed how they developed their ideas to solve the open-ended problem using relevant objects or related concepts as part of a whole-class discussion and comparison exercise. Finally, the students demonstrated their abilities to represent the mathematical world using numbers and symbols to communicate their ideas when they were required to make a summary by connecting their mathematical ideas.

This study adds new insight to the literature on students' mathematization using the TLSOA model.

This study was done to compare the modes of teaching mathematics in higher education in the United Arab Emirates (UAE). The three teaching methods were used as follow: before, during and after the COVID-19 pandemic. The three teaching methods are: (1). Normal on-campus face-to-face teaching and learning activity before the COVID-19 pandemic. (2). Full online teaching and learning activity during the COVID-19 pandemic. (3). Blended teaching and learning activity after the COVID-19 pandemic.

Over the last few years, there has been a considerable amount of literature investigating the efficacy of the various delivery modes: on-campus delivery (face-to-face), online delivery and blended learning (hybrid), in helping college students improve their mathematical skills. However, the extent to which one learner learns best has been hotly debated among the researchers. Therefore, this study aims to compare the efficacy of implementing three teaching and learning delivery modes before, while, and after the COVID-19 pandemic: on-campus delivery (face-to-face), online delivery and blended learning (hybrid) on academic achievement in mathematics at a higher education institution in the UAE. The main research question explores whether there is a statistically significant difference (p = 0.05) in students’ academic based on the delivery methods: on-campus face-to-face, online and blended learning. The participants in the study were students from one of the largest higher education institutions in the UAE, and all of them studied the same mathematics course before, during and after the COVID-19 pandemic. Student scores in the three academic semesters were thoroughly compared and analyzed using the ANOVA test to check if there is a significant difference between the three groups followed by a Tukey test to identify the significant difference in favor of which group. The results showed that there were significant differences in the mean scores in the students’ achievement in the mathematics courses favoring the blended learning delivery mode. The findings also show that the students’ achievement in mathematics using the on-campus face-to-face teaching and learning was better than the students’ achievement in mathematics using online teaching and learning delivery modes.

The main study question was: is there a statistical significant difference at the significance level (a = 0.05) in students’ achievements in mathematics courses at higher education in the UAE, which can be attributed to the method of teaching? The descriptive statistics reveal that the average student’s score in the final exam after the COVID-19 pandemic is 65.7 with a standard deviation of 16.65, which are higher than the average student’s score in the final exam before the COVID-19 pandemic of 58.7 with a standard deviation 20.53, and both are higher than the average students’ score in the final exam during the COVID-19 pandemic 51.8 with standard deviation 21.48. Then, the ANOVA test reveals that there is a statistically significant difference between the three groups in the final exam marks. The researchers used the multiple comparison tests (Tukey test) to determine the difference. The Tukey test reveals that there is a statically significant difference between the average students’ score in the final exam after the COVID-19 pandemic and the average students’ score in the final exam during the COVID-19 pandemic, where p = 0.015 < 0.05 as well as there is a statically significant difference between the average students’ score in the final exam after the COVID-19 pandemic and the average students’ score in the final exam before the COVID-19 pandemic, where p = 0.000 < 0.05 in favor of the average students’ score in the final exam after the COVID-19 pandemic. On the other hand, there is a statically significant difference between the average students’ score in the final exam before the COVID-19 pandemic and the average students’ score in the final exam during the COVID-19 pandemic, where p = 0.016 < 0.05 in favor of the average students’ score in the final exam before the COVID-19 pandemic.

There are several limitations that may reduce the possibility of generalizing the expected results of the current study to students outside the study population: (1) The study is limited to students of a federally funded postsecondary education institution in the UAE, in which most students are studying in their non-native language. (2) The study is limited to the mathematics courses. (3) The achievement test used in the study is a standardized test developed by the college as a cross-campus summative assessment.

The hybrid education model, also known as blended learning, combines traditional face-to-face instruction with online learning components. When applied to teaching mathematics in higher education, this approach can have several implications and benefits. Here are some key points supported by references: (1) Enhanced Accessibility and Flexibility: hybrid models offer flexibility in learning, allowing students to access course materials, lectures and resources online. This flexibility can accommodate diverse learning styles and preferences. A study by Means et al. (2013) in “Evaluation of Evidence-Based Practices in Online Learning” highlights how blended learning can improve accessibility and engagement for students in higher education. (2) Personalized Learning Experience: by incorporating online resources, instructors can create a more personalized learning experience. Adaptive learning platforms and online quizzes can provide tailored feedback and adaptive content based on individual student needs (Freeman et al., 2017). This individualization can improve student performance and understanding of mathematical concepts. (3) Increased Student Engagement: the integration of online components, such as interactive simulations, videos and discussion forums, can enhance student engagement and participation (Bonk and Graham, 2012). Engaged students tend to have better learning outcomes in mathematics. (4) Improved Assessment and Feedback Mechanisms: hybrid models allow for the implementation of various assessment tools, including online quizzes, instant feedback mechanisms and data analytics, which can aid instructors in monitoring students’ progress more effectively (Means et al., 2013). This timely feedback loop can help students identify areas needing improvement and reinforce their understanding of mathematical concepts. (5) Cost-Effectiveness and Resource Optimization: integrating online materials can potentially reduce overall instructional costs by optimizing resources and enabling efficient use of classroom time (Graham, 2013). (6) Challenges and Considerations: despite the benefits, challenges such as technological barriers, designing effective online materials and ensuring equitable access for all students need to be addressed (Garrison and Vaughan, 2014). It requires thoughtful course design and continuous support for both students and instructors. When implementing a hybrid education model in teaching mathematics, instructors should consider pedagogical strategies, technological infrastructure and ongoing support mechanisms for students and faculty.

The research is the first research in the UAE to discuss the difference in teaching mathematics in higher education before, during and after the COVID-19 pandemic.

This study considered the use of video conferencing virtual backgrounds with employees located in a large multinational corporate organisation in Ireland and the USA to discern if background images evoking gendered stereotypes of leadership can cue stereotype threat in female technology workers undertaking a leadership activity, thus negatively effecting performance. This study aims to contribute to the body of research on stereotype threat by establishing whether virtual backgrounds used in video conferencing software are inherently identity safe or whether their use could have a negative performance impact on marginalised groups.

Using a mixed methods research design with 22 participants in two countries working in the one large organisation, using two quantitative methods (an experiment and a survey) and one qualitative method (semi-structured interviews), the study examined the relationship between performance on the leadership activity and exposure to gendered backgrounds on a video conference call.

It found that female leaders undertaking a leadership test experienced more anxiety and achieved lower scores on average when exposed to a male-gendered virtual background compared to male colleagues or female leaders exposed to a female gendered background. It was also found that these leaders were aware of the stereotype of leadership being White and male, and showed symptoms of prolonged exposure to stereotype threat in the workplace. While the authors still are working through a post-pandemic environment, it may be judicious for organisations to restrict the use of virtual backgrounds to identity-safe ones, specifically chosen by the company.

The study makes several practical recommendations, indicating actions which can be taken at the individual, team and corporate levels. Re-running this experiment in a more controlled environment with a larger sample set could yield more definitive, statistically significant results and contribute more to the literature.

Some individual impacts were found via the interviews. Male leaders in the organisation need to do more to mentor and endorse their female colleagues. By doing this, they can counter the negative effects of solo status and the subsequent performance degradations of their female counterparts, while also setting an example for other leaders. Participation in the mentoring programme and initiatives such as Dare and value, inclusion, belonging, and equity should be encouraged and supported. Reverse mentoring should also be encouraged among the population of male leaders to aid in allyship and bias-awareness.

Teams should note that a democratic vote is not always the best way to decide on the names of teams, projects or meeting rooms. These may skew towards niche interests that can serve to alienate members of the team who do not associate themselves with that interest. Rather, the teams should strive to be fully inclusive and educated on the need for identity-safety. Team events may also serve to alienate members if teams are not mindful of the need to be inclusive. Activities, such as “go-kart” racing and physical or competitive team events have been highlighted as unsuitable for some team members, and should be avoided in favour of inclusivity.

A significant body of research has documented the effect to which stereotype threat can be triggered by both the physical environment and by the use of various technology media. However, there is a dearth of research exploring the relationship between stereotype threat, defined as “the concrete, real-time threat of being judged and treated poorly in settings where a negative stereotype about one’s group applies” (Steele et al., 2002, p. 385), and video conferencing software features, such as virtual backgrounds.

This chapter sought to answer the following questions: (a) what does special education means for students with intellectual disability?, (b) what is being done, and (c) how do we maintain tradition? The answers, while complicated, suggest special education for students with intellectual disability historically and currently involves attention to what, how, and where, with the how being the key elements of special education for students with intellectual disability. This chapter discussed the what, how, and where for students with intellectual disability in a historical and current framework while also providing evidence-based practices for students with intellectual disability to implement to maintain the tradition of high-quality services.

The authors consider whether the emotional states of happiness and fear causally affect test performance using a new experiment. The paper aims to discuss this issue.

Happiness and fear are induced with 360-degree videos shown in virtual reality before participants take a test consisting of mathematics scholastic aptitude tests (SAT) questions.

The results show that scores improve by 0.48 standard deviations under the happiness condition, and the effect is particularly large for women (0.75 s.d.). Inducing fear has no effect on test scores.

This is one of the first studies to employ virtual reality for emotion induction. It establishes that test scores can be improved by inducing an emotional state of happiness shortly before the test.

Images taken from construction site interiors often suffer from low illumination and poor natural colors, which restrict their application for high-level site management purposes. The state-of-the-art low-light image enhancement method provides promising image enhancement results. However, they generally require a longer execution time to complete the enhancement. This study aims to develop a refined image enhancement approach to improve execution efficiency and performance accuracy.

To develop the refined illumination enhancement algorithm named enhanced illumination quality (EIQ), a quadratic expression was first added to the initial illumination map. Subsequently, an adjusted weight matrix was added to improve the smoothness of the illumination map. A coordinated descent optimization algorithm was then applied to minimize the processing time. Gamma correction was also applied to further enhance the illumination map. Finally, a frame comparing and averaging method was used to identify interior site progress.

The proposed refined approach took around 4.36–4.52 s to achieve the expected results while outperforming the current low-light image enhancement method. EIQ demonstrated a lower lightness-order error and provided higher object resolution in enhanced images. EIQ also has a higher structural similarity index and peak-signal-to-noise ratio, which indicated better image reconstruction performance.

The proposed approach provides an alternative to shorten the execution time, improve equalization of the illumination map and provide a better image reconstruction. The approach could be applied to low-light video enhancement tasks and other dark or poor jobsite images for object detection processes.

This study aimed to explore teachers' learning processes through a hybrid cross-cultural lesson study (LS) because little is known about the learning process through this novel and promising LS approach.

This cross-cultural LS lasted over six months focusing on developing a research lesson (RL) related to linear functions/equations by addressing a commonly concerned student learning difficulty. The data collected were lesson plans, videos of RLs, cross-culture sharing meetings and post-lesson study teacher interviews. A cultural-history activity theory (CHAT) perspective (Engeström, 2001) was used as a theoretical and analytical framework, and contradictions were viewed as driving forces of teachers' learning. The data were analyzed to identify contradictions and consequent teachers' learning by resolving these contradictions.

The results revealed four contradictions occurring during the hybrid cross-cultural LS that are related to the preferred teaching approach, culturally relevant tasks, making sense of the specific topic and enactment of the RL. By addressing these contradictions, the participating teachers perceived their learning in cultural beliefs, pedagogical practice and organization of the lesson.

This study details teachers' collaborative learning processes through hybrid cross-cultural LS and provides implications for effectively conducting cross-cultural LS. However, how the potential learning opportunity revealed from this case could be actualized at a larger scale in different cultures and the actual impact on local practices by adapting effective practices from another culture are important questions to be investigated further.

This study expands teacher learning through cross-cultural LS by focusing on contradictions cross-culturally as driving forces.

The purpose of this paper is to perform a comparative analysis of the delay associated in running two real-time machine learning-based applications, namely, a video quality assessment (VQA) and a phishing detection application by using the edge, fog and cloud computing paradigms.

The VQA algorithm was developed using Android Studio and run on a mobile phone for the edge paradigm. For the fog paradigm, it was hosted on a Java server and for the cloud paradigm on the IBM and Firebase clouds. The phishing detection algorithm was embedded into a browser extension for the edge paradigm. For the fog paradigm, it was hosted on a Node.js server and for the cloud paradigm on Firebase.

For the VQA algorithm, the edge paradigm had the highest response time while the cloud paradigm had the lowest, as the algorithm was computationally intensive. For the phishing detection algorithm, the edge paradigm had the lowest response time, and the cloud paradigm had the highest, as the algorithm had a low computational complexity. Since the determining factor for the response time was the latency, the edge paradigm provided the smallest delay as all processing were local.

The main limitation of this work is that the experiments were performed on a small scale due to time and budget constraints.

A detailed analysis with real applications has been provided to show how the complexity of an application can determine the best computing paradigm on which it can be deployed.