Assessment Practices Research Articles

Exploration of Property Insurance Benefits in Extreme Weather

In recent years, the increasing frequency of extreme weather events has highlighted the insurance industry's dilemma - the profitability of insurance companies and the capacity of policyholders to bear the burden are in crisis. Therefore, seeking the development of property insurance in this environment is crucial. This paper establishes a Risk Assessment Model with a four-level index system, including four main indicators: natural, economic, social, and engineering defense, to assess the disaster risk and losses of a specific area. Subsequently, a Rate-Adjusted Break-Even Analysis Model is established and coupled with the Risk Assessment Model to facilitate practical insurance decision-making. By establishing this highly flexible and practical assessment system, precise indicators can be selected for evaluation based on the varying impacts of natural disasters in different regions. This will enable more accurate decision-making for local catastrophic insurance coverage. Consequently, it allows local residents to obtain better post-disaster relief protection against natural calamities, while businesses can also benefit from substantial reconstruction returns.

Using Generative AI to Promote Psychological, Feedback, and Artificial Intelligence Literacies in Undergraduate Psychology

Background With the arrival of generative artificial intelligence (genAI) tools, psychology educators are rethinking their assessment practices. Objective This paper describes one approach to integrating genAI into an assessment designed to promote psychological literacy. Method Students used ChatGPT to generate a media release about a published article and then wrote a critique. We evaluated whether students were able to use the marking rubric to assess the ChatGPT output, and whether working with the rubric early in the assessment process had benefits for their grades on subsequent tasks. Results The results show that students accurately assessed the ChatGPT output against the marking rubric, judging the output to be stylistically good but lacking in accurate coverage of the aims, methods, and results of the research. Working with genAI and the marking rubric early in the assessment process had benefits for performance, relative to cohorts that had engaged in peer review. Conclusion By allowing students to use genAI and scaffolding the process of critiquing and revising, students gained competencies in psychological, feedback, and AI literacies. Teaching implications Integrating genAI presents opportunities for learning, if educators can think beyond the artifact and design assessment that allows our students to showcase their learning process.

Enhancing Flexible Assessment Through ePortfolios: A Scholarly Examination

In contemporary educational settings, the demand for flexible assessment practices has gained prominence due to students' diverse learning needs and preferences. Portfolios have emerged as a versatile tool for facilitating personalised and adaptable assessment processes. This paper investigates how ePortfolios can cater to students' flexible assessment needs. By examining the benefits, challenges, and implementation strategies associated with ePortfolios, this paper highlights their potential to enhance assessment practices, foster student engagement, and promote lifelong learning. As part of implementation strategies, we provide examples to support teaching staff and institutions in translating the underpinning principles and theory into actionable practice.

EPortfolio-based Professional Development: Insights from a Southeast Asian Online Educators’ Community of Practice

This study examines the implementation and impacts of an ePortfolio-based professional learning initiative within a Southeast Asian online community of practice (CoP), part of the SEAMEO-AUS EduLink Project. Targeting the development of educators' competencies in ePortfolio pedagogy, the project engaged 541 educators from various Southeast Asian countries in two online self-paced courses and a series of four expert-led webinars, culminating in a final project webinar. The research utilised course analytics and post-webinar surveys to analyse participant engagement, satisfaction, and perceived learning outcomes. The findings indicate substantial engagement with the courses and positive reception of the webinar series. About 75% of participants completed the asynchronous courses, while 64% found the webinar content immediately applicable to their practice. The webinars, focusing on diverse aspects of ePortfolio use, successfully complement the online courses, with 91% of participants expressing intent to attend future events. This study underscores the effectiveness of combining asynchronous and synchronous learning modalities in professional development, particularly in the context of ePortfolios. It highlights the role of ePortfolios in promoting reflective practice, collaborative learning, and authentic assessment. Additionally, the project's success in fostering a supportive CoP model illustrates the potential of online communities in professional development, especially in regions with emerging ePortfolio practices. The paper concludes by emphasising the value of ePortfolio-based initiatives in enhancing educators' skills and fostering cross-cultural educational collaborations. It offers recommendations for educators and policymakers on implementing similar initiatives, underlining the need for sustainable and contextually sensitive approaches in professional development.

Evaluating Students' Academic Progress in the Role of Fuzzy Logic

This paper explores the role of fuzzy logic in the assessment of student performance in local high school, Badr, Libya, positing that it offers a more flexible and accurate alternative to traditional categorization methods of academic achievement. Conventional assessment tools, such as standardized test scores and GPAs, often yield a distorted and overly simplistic view of student performance. Utilizing a mixed-methods research design, this study compares the performance, attendance, and self-reported satisfaction of students assessed through fuzzy logic with those evaluated by traditional methods. The results demonstrate that students assessed using fuzzy logic achieved higher average scores and expressed greater satisfaction with the assessment process. Additionally, educators employing fuzzy logic provided more detailed and constructive feedback, enriching the learning experience. Thus, this research indicates that fuzzy logic can effectively mitigate the shortcomings of traditional assessment methods, enhancing the recognition of diverse student abilities. The findings advocate for the integration of fuzzy logic in educational assessment practices to promote inclusivity and improved learning outcomes.

Evaluation Proposal for School Teaching and Learning

Objective: This work aims to present a proposal for an evaluation method, entitled: Cycle of Autonomous Learning Evaluation (Caaa). Theoretical Framework: The use of assessment instruments in schools as a genuine assessment and the low level of student learning in Brazil exposes the emerging need to rethink the assessment practices that are carried out, since in order to raise their learning to a higher and better quality, it is essential to qualify the means that give access to it. Method: In order to construct this study, we immersed ourselves in educational theory relating to learning assessment in the school context and active teaching practices, as well as in the documents that underpin Brazilian education and what they guide in terms of learning assessment. Results and Discussion: The studies carried out resulted in the development of the assessment method: Cycle of Autonomous Assessment of Learning (Caaa). Research Implications: The practical and theoretical implications of this research are discussed, providing insights into how the Cycle of Autonomous Assessment for Learning (Caaa) can be applied or influence practices in the field of education. Originality/Value: This work contributes to the development of the praxis of school learning assessment in Brazil.

Mental Health Risk Assessment and Safety Planning During UK Covid-19 Pandemic Lockdown: Mixed Methods Survey and Interview Study

Risk assessment and safety planning are central to mental health nursing practice but were seriously affected by the Covid-19 pandemic and associated lockdowns. In this study, we aimed to explore how the UK pandemic lockdowns affected risk assessment and safety planning from the perspective of mental health practitioners. A sequential, mixed methods study design was used. A link to an online survey questionnaire was distributed and semi-structured interviews with a subset of respondents were conducted. Survey data were analysed to describe perceived changes in the frequency and nature of risk assessment and safety planning during the pandemic lockdowns. This was supplemented by thematic analysis of qualitative interview data. In total, 106 practitioners were surveyed and 10 participated in semi-structured interviews. More respondents increased than decreased risk assessment frequency but there was no significant overall change. Remote contact was more common in community settings and largely involved telephone appointments. Participants did not wish to continue with remote working following the pandemic. Risk assessment practice changed in UK mental health services as a result of COVID-19 lockdowns.

Diffuse correlation tomography: a technique to characterize tissue blood flow abnormalities in benign and malignant breast lesions

Accurate assessment and quantification of neoangiogenesis associated with breast cancer could be potentially used to improve the sensitivity and specificity of non-invasive diagnosis, as well as predict outcomes and monitor treatment effects. In this study, we adapted an emerging technology, namely diffuse correlation tomography (DCT), to image microvascular blood flow in breast tissues and evaluate the potential for discriminating between benign and malignant lesions. A custom-made DCT system was designed for breast blood flow imaging, with both the source-detector array and reconstruction algorithm optimized to ensure precise imaging of breast blood flow. The global features and local features of three-dimensional blood flow images were extracted from the relative blood flow index (rBFI), which was obtained from most of the breasts targeted to the lesion. A total of 37 women with 19 benign and 18 malignant lesions were included in the study. Significant differences between malignant and benign groups were found in 12 image features. Moreover, when selecting the lesion mean relative blood flow index (MrBFI) as a single indicator, the malignant and benign tumors were discriminated with an accuracy of 89.2%. The blood flow features were found to successfully identify malignant and benign tumors, suggesting that DCT, as an alternate functional imaging modality, has the potential to be translated into clinical practice for diagnosis and assessment of breast cancers. There is potential to reduce the need for biopsy of benign lesions by improving the specificity of diagnostic imaging, as well as monitoring response to breast cancer treatment.

Comparative Assessment of Environmental Disclosure Practices: A Case Study of Two Leading Oil Companies in India

This study conducts a comparative analysis of the environmental disclosure practices of two leading oil companies in India: OIL and Petronet LNG. By evaluating their sustainability reports and publicly available environmental information, the research assesses key performance areas such as energy consumption, greenhouse gas emissions, water management, waste treatment, and biodiversity conservation. The analysis reveals that both companies exhibit similar environmental disclosure practices, with strengths in energy and emissions management but significant gaps in compliance, biodiversity, and grievance mechanisms. A statistical t-test shows no significant difference between the environmental performance of the two companies, indicating comparable transparency levels. The study highlights the need for both organizations to improve their environmental reporting and align more closely with global sustainability standards, such as the Global Reporting Initiative (GRI) and Carbon Disclosure Project (CDP). Recommendations include enhancing biodiversity conservation efforts, strengthening supplier environmental assessments, and improving compliance with environmental regulations. Keywords: Environmental disclosure, Oil industry, Sustainability reporting, Comparative analysis, India, Greenhouse gas emissions, Energy management, Water usage, Biodiversity, Compliance, Corporate social responsibility (CSR).

Comparison of Diffusion-weighted MRI using Singe-Shot Echo-planar Imaging (SS-EPI) and Split Acquisition of Fast Spin Echo Signal (SPLICE) Imaging, a non-EPI technique, in Tumors of the Head and Neck.

Diffusion-weighted imaging (DWI) using single-shot echo planar imaging (DW-EPI) is susceptible to distortions around air-filled cavities and dental fillings, typical for the head and neck area. Non-EPI, Split acquisition of fast spin echo signals for diffusion imaging (DWSPLICE) could reduce these distortions and enhance image quality, thereby potentially improving recurrence assessment in squamous cell carcinoma (SCC) of the head and neck region. This study evaluated whether DW-SPLICE is a viable alternative to DW-EPI through quantitative and qualitative analyses. The DW-SPLICE sequence was incorporated into the standard 3.0T head and neck MRI protocol with DW-EPI. Retrospective analysis was conducted on two subgroups: firstly benign or malignant lesions, and secondly post-treatment SCC recurrence. In both subgroups Image quality and distortion were scored by two independent radiologists, blinded for DW-technique, and evaluated using mixed-effect linear models. Lesion apparent diffusion coefficient (ADC) values were assessed with inter-class correlation (ICC) and Bland-Altman analyses. DWI's delineation geometric similarity to T1-weighted post-contrast (T1Wc) MRI was evaluated using the Dice Similarity Coefficient (DSC) before and after registration. Recurrence in post-treatment SCC scans was evaluated by the same two radiologists blinded for DW-technique. Recurrence detection rates were then compared between DW-SPLICE and DW-EPI using mixed logistic regression at six months and at one-year post-scan follow-up data. From August 2020 to January 2022, 55 benign or malignant lesion scans (55 patients) and 74 post-treatment SCC scans (66 patients) were analyzed. DW-SPLICE scored better on image quality and showed less overall distortion than DW-EPI (0.04<p<0.001). There was high ADC measurement reliability (ICC=0.93, p<0.001), though a proportional bias was also observed (β=0.11, p=0.03), indicating the bias increases as ADC values rise. DWSPLICE exhibited greater geometric similarity to T1Wc before registration (DSC 0.63 vs 0.47, p<0.001) and outperformed DW-EPI by more accurately identifying recurrences after one year (OR=0.96, p=0.05) but not after six months (OR=0.72, p=0.13). DW-SPLICE surpasses DW-EPI on image distortion and quality and improves diagnostic reliability for detecting recurrent or residual SCC on 3T MRI of the HN. Consistent use of one method for follow-up is advised, as ADC values are not completely interchangeable. Integrating DW-SPLICE can significantly improve tumor assessments in clinical practice. ANTs = Advanced Normalization Tools; DSC = Dice Similarity Coefficient; DW-EPI = Diffusion-weighted single-shot echo planar imaging; DW-MS-EPI = Diffusion-weighted multi-shot echo planar imaging; DW-SPLICE = Diffusion-weighted split acquisition of fast spin echo signals for diffusion imaging; DW-TSE = Diffusion-weighted Turbo Spin Echo; ICC = Intraclass Correlation Coefficient; ROC = Receiver Operating Characteristic; SCC = Squamous cell carcinoma; T1WIc = T1 weighted imaging with gadolinium contrast.

Research on risk detection and management based on machine learning

With the rapid advancement in financial risk management, machine learning techniques are playing an increasingly crucial role in credit assessment and risk detection. They provide financial institutions with more scientific and precise platforms and methodologies for risk management. This paper explores various traditional machine learning methods in risk assessment, introduces the XGBoost ensemble learning method, and integrates traditional machine learning with Long Short-Term Memory (LSTM) neural networks to enhance the generalization capability of risk control and credit assessment models. This approach offers new perspectives and improvement directions for risk assessment standards and practices in the financial industry, affirming the potential application of machine learning technologies in future risk management.The results show that the random forest and decision tree have excellent accuracy and recall rates for distinguishing fraudulent transactions. After the introduction of LSTM neural networks, the accuracy and recall rates of fraudulent transaction recognition models reach around 99%, indicating that these models have good adaptability for fraud risk recognition.

Deep in the Virgin Forest: Macunaíma as a metaphor to decolonial mathematics education

Macunaíma, Mário de Andrade's characterless hero, is reinterpreted in this text as the starting point for a discussion on Mathematics Education from a decolonial perspective. We aim to examine hegemonic mathematics and its connection to coloniality through two key concepts: sacred and earthly. These terms, used metaphorically, serve to delve into the fundamental nature of how mathematics is taught in schools and universities. Building upon this initial problematization, we suggest alternative approaches rooted not only in decolonial references but also in literature and music. Subsequently, we explore additional metaphors that can be instrumental in reshaping school mathematics and teacher training within a new paradigm that transcends dichotomies, avoids assimilation with Western hegemonic thinking, and rejects assessment practices that lead to segregation.

AI-assisted marking: Functionality and limitations of ChatGPT in written assessment evaluation

Generative artificial intelligence technologies, such as ChatGPT, bring an unprecedented change in education by leveraging the power of natural language processing and machine learning. Employing ChatGPT to assist with marking written assessment presents multiple advantages including scalability, improved consistency, eliminating biases associated with human subjectivity. This work aimed to evaluate the usefulness, reliability and accuracy of ChatGPT in marking written assessments of varied types and to identify its limitations and challenges. ChatGPT was instructed using a set of prompts to mark the assessment based on a rubric. ChatGPT was able to evaluate and assess both coding and reflective assessments and to distinguish between assignments of different quality, demonstrating high consistency and accuracy for higher quality assessments, comparable to a human marking. ChatGPT was also able to generate textual detailed justifications based on the rubric and assessment task description. There was a significant difference in the outcomes generated by different prompts. These preliminary findings suggest that utilising ChatGPT as a marking assistant can increase written assessment marking efficiency, reduce cost and potentially decrease the unfairness and bias by providing a moderating perspective. Implications for practice or policy: Assessment designers could reconsider the design, purpose and objectives of written assessments and leverage ChatGPT effectively for teaching and learning. Assessors might consider adapting the technology as a grading aid, to support a human-in-the-loop grading process, providing additional resources and time, moderating and refining individual feedback, to increase consistency and quality. Curriculum and programme leaders could develop guidelines around the ethical use of generative AI-assisted assessment practice, monitor and regulate the ongoing evaluation and refinement.

How to make sense of generative AI as a science communication researcher? A conceptual framework in the context of critical engagement with scientific information

A guiding theory for a continuous and cohesive discussion regarding generative artificial intelligence (GenAI) in science communication is still unavailable. Here, we propose a framework for characterizing, evaluating, and comparing AI-based information technologies in the context of critical engagement with scientific information in online environments. Hierarchically constructed, the framework observes technological properties, user experience, content presentation, and the context in which the technology is being used. Understandable and applicable for non-experts in AI systems, the framework affords a holistic yet practical assessment of various AI-based information technologies, providing both a reflection aid and a conceptual baseline for scholarly references.

Assessment of Knowledge, Attitude, and Practices (KAP) of Anganwadi Teachers and Asha Workers with Regard to Nutrition Education Intervention

Nutrition is one of the important aspects that deals with good health and wellbeing of people. Nutrition education helps to resolve the nutrition problems by imparting nutrition education and bring desirable changes in terms of Knowledge, Attitude and Practices (KAP). The existing study was conducted to know the knowledge, attitude, and practices of AWW and ASHA’s with regard to nutrition education for pregnant women and lactating mother. Data was gathered using pre-tested questionnaires with a sample size of 90 respondents chosen from three mandals (area) in the Guntur district. Random sampling procedure was used for selection of the respondents. The results of the study found that Anganwadi teachers and ASHA Workers had low to medium level of knowledge, poor attitude and poor practices during baseline test. After implementing intervention programme to the Anganwadi teachers and ASHA Workers for a period of one month a significant improvement in the Knowledge, Attitude and Practices was observed during Endline test (t=10.5; t=10.3). The above findings can be used to plan a digital material on nutrition education interventions which aiming at bringing change in the behavior of the respondents i.e., KAP and it can be used as ready reckoners during sudden epidemics.

Assessment of nurses' Knowledge and Practice for Patients Undergoing Surgeries for Closed Pelvis Fracture .

Assessment of nurses' Knowledge and Practice for Patients Undergoing Surgeries for Closed Pelvis Fracture .

Post-16 students’ experience of practical science during the COVID-19 pandemic and the impact on students’ self-efficacy in practical work

This paper presents the findings from a detailed study investigating UK undergraduate students’ experience of practical science in their post-16 studies during the COVID-19 pandemic. It also examines their perceived confidence and preparedness in relation to areas of practical science skills at the start of their undergraduate courses. The study employed an exploratory sequential mixed methods design. Findings from student focus groups held at the end of their post-16 studies were used to support the development of a comprehensive skills audit and quantitative survey for incoming undergraduate students. Survey data were collected in September and October 2021 from 275 students commencing Biosciences, Chemistry, Physics and Natural Science degrees at two universities in England. The research is important because although almost all students had the opportunity to undertake practical work as part of their post-16 studies during the COVID-19 pandemic, there was considerable variation in students’ experiences. The data indicate that COVID-19-related closures of post-16 education establishments, ongoing social distancing requirements and the consequent removal of the assessment criteria for students to have ‘routinely and consistently’ undertaken each of the practical assessment requirements had implications for the development of students’ self-efficacy in relation to practical science. The research presents important considerations which are relevant for educators supporting students’ transition from post-16 to Higher Education and have the potential to impact on incoming students over many years to come.

A NOVEL WAY TO CLASSIFY THE SLAKE DURABILITY INDEX OF ROCKS

Slaking, the disintegration of rocks upon exposure to moisture and air, poses significant challenges in engineering applications, such as in slope stability and embankment design. This study improves the slake durability index test by introducing several enhancements to better reflect the field conditions of rocks. A new test methodology is developed which includes a revised slake durability classification table, a novel Discard Method for calculating weight retention in the test drum, and an updated classification chart. The improved methodology considers parameters such as porosity and strength, evaluated through index, Schmidt hammer rebound and point load tests. The new classification table categorizes rocks into durability classes according to the field observations and laboratory test results. The Discard Method improves accuracy by eliminating broken pieces from the durability calculation, addressing the limitations in the suggested method. A Configured Discard Method equation further defines the durability estimation by combining porosity, strength and slake durability data. Field investigations and laboratory tests conducted with various rock types demonstrate that the new classification system provides more accurate and practical assessments of rock durability. This study highlights the importance of effective porosity and strength impact which enhance the reliability of slake durability evaluations, offering a revised classification framework that simplifies field assessments while maintaining the accuracy. Future research should focus on developing these methods and expanding their applicability to diverse geological contexts by including more material to test.

The Impact of Immersive 360-Degree Video Learning on Enhancing Oral Communication Skills

This study investigates the pivotal role of immersive 360-degree video and its perceived advantages on the enhancement of oral communication skills within the framework of the ELC650 course, 'English for Professional Interaction'. The research involved twenty-four students enrolled in the Bachelor of Applied Language (Arabic Communication Professionals) (Hons) program. The distribution of questionnaires immediately after the students watched the video aimed to assess the role of immersive 360-degree video and its perceived advantages of this technology in preparing students for conducting assessments within a meeting discussion. Employing a cross-sectional design, the study collects both closed-ended and open-ended responses through the distributed questionnaires. The latter serves as a crucial means of triangulating the data, offering real-time insights into the students' understanding of professional interaction and assessment practices using 360-degree video. The study's findings on the use of 360-degree video in education can inform government decisions and contribute to achieving SDG 4, which aims to improve the quality of education. It is important for government and learning institutions to recognize and embrace the role of 360-degree video in enhancing learning quality, specifically in fostering communication skills within the area of professional interaction in English. Other than that, this study holds implications for refining curriculum design, shaping instructional strategies, and optimizing the integration of innovative technologies in language education, particularly for students specializing in Arabic communication.

Bridging the procedures skill gap from medical school to residency: a simulation-based mastery learning curriculum.

The transition from medical student to intern is a recognized educational gap. To help address this, the Association of American Medical Colleges developed the Core Entrustable Professional Activities for entering residency. As these metrics outline expectations for all graduating students regardless of specialty, the described procedural expectations are appropriately basic. However, in procedure-heavy specialties such as emergency medicine, the ability to perform advanced procedures continues to contribute to the disconnect between undergraduate and graduate medical education. To prepare our graduating students for their internship in emergency medicine, we developed a simulation-based mastery learning curriculum housed within a specialty-specific program. Our overall goal was to develop the students' procedural competency for central venous catheter placement and endotracheal intubation before graduation from medical school. Twenty-five students participated in a simulation-based mastery learning procedures curriculum for ultrasound-guided internal jugular central venous catheter placement and endotracheal intubation. Students underwent baseline assessment, deliberate practice, and post-test assessments. Both the baseline and post-test assessments used the same internally developed checklists with pre-established minimum passing scores. Despite completing an emergency medicine rotation and a critical care rotation, none of the students met the competency standard during their baseline assessments. All twenty-five students demonstrated competency on both procedures by the end of the curriculum. A second post-test was required to demonstrate achievement of the central venous catheter and endotracheal intubation minimum passing scores by 16% and 28% of students, respectively. Students demonstrated procedural competency for central venous catheter placement and endotracheal intubation by engaging in simulation-based mastery learning procedures curriculum as they completed their medical school training. With three instructional hours, students were able to achieve basic procedural competence for two common, high-risk procedures they will need to perform during emergency medicine residency training.