Evaluation Of Proficiency Research Articles

Cobalt doped MoS2: A photoactivated nanomaterial for removal of methylene blue and phenol

This research work reports the study about synthesis, characterizations and Photocatalytic applications of hydrothermally produced MoS2 and Cobalt doped MoS2 nanomaterials to overcome the environmental pollution caused by wastewater. MB dye and Phenol were used as model pollutants for evaluation of photocatalytic proficiency of MoS2 and Cobalt doped MoS2 nanostructures. The well matched ionic radius of Cobalt with host Mo atom increases their probability regarding alteration of nanomaterial’s optical, structural and catalytic properties. The Cobalt incorporation provided the synergistic effect attributed to efficient degradation up to 96 % and 80 % for MB dye and phenol respectively. Additionally, the prepared samples were characterized to elucidate their optical, electronic and structural properties. Scavenger analysis and reusability test had performed to check the role of active species and stability of optimized sample. This study predicts that the fabrication of Cobalt doped MoS2 can be used as potential and promising photocatalyst for industrial applications for wastewater treatment.

Development and Validation of a Comprehensive English Test for Sophomore Students in Liaoning, China

The English proficiency of Chinese college students varies in different regions and majors. For college students, it’s of great importance to know their strengths and weaknesses in the process of language learning and to have targeted practice . For language teachers, it is quite significant to identify the problems and needs of students in English learning, to adjust the teaching methods and contents and to improve the teaching effect. At the same time, the feedback of the test results can also promote the school’s attention to and investment i n English teaching and promote the in depth reform of English teaching. In this procedure, a comprehensive English test is an effective way. This study describes developing and validating a comprehensive English test for sophomore students at Shenyang Univ ersity of Chemistry and Technology in Liaoning, China. The test is designed to assess students' English proficiency upon completing the "New Century College English Reading" course. The research employed a mixed methods approach, combining qualitative meth ods for test development and expert review with quantitative methods for statistical validation. The test development process included content analysis of course materials, creation of test specifications aligned with course objectives, and item writi ng. T he test covers four key language domains: listening, reading, translation, and writing. Validation is conducted through expert r eview using a content, construct, and face validity checklist. Five experienced English language teaching and assessment experts evaluated the test using a 15 item checklist with a 5 point Likert scale. Results showed high overall validity, with mean scores above 4.0 for content validity, construct validity, and face validity, indicating strong agreement among experts on the test' s validation. While the study provides strong evidence for the test's validity, limitations include the sample size and geographic scope. Future research directions include longitudinal studies to assess predictive validity and cross regional validation to evaluate the test's applicability across China's educational contexts. This study contributes to English language assessment in Chines e higher education in Liaoning province. It provides a validated tool that aligns closely with curriculum objectives and a ddresses the need for comprehensive language proficiency evaluation.

Putting GPT-4o to the Sword: A Comprehensive Evaluation of Language, Vision, Speech, and Multimodal Proficiency

As large language models (LLMs) continue to advance, evaluating their comprehensive capabilities becomes significant for their application in various fields. This research study comprehensively evaluates the language, vision, speech, and multimodal capabilities of GPT-4o. The study employs standardized exam questions, reasoning tasks, and translation assessments to assess the model’s language capability. Additionally, GPT-4o’s vision and speech capabilities are tested through image classification and object-recognition tasks, as well as accent classification. The multimodal evaluation assesses the model’s performance in integrating visual and linguistic data. Our findings reveal that GPT-4o demonstrates high accuracy and efficiency across multiple domains in language and reasoning capabilities, excelling in tasks that require few-shot learning. GPT-4o also provides notable improvements in multimodal tasks compared to its predecessors. However, the model shows variability and faces limitations in handling complex and ambiguous inputs, particularly in audio and vision capabilities. This paper highlights the need for more comprehensive benchmarks and robust evaluation frameworks, encompassing qualitative assessments involving human judgment, as well as error analysis. Future work should focus on expanding datasets, investigating prompt-based assessment, and enhancing few-shot learning techniques to test the model’s practical applicability and performance in real-world scenarios.

Student Progress Tracing of Arabic Learning: A Qualitative Investigation of Speaking Skills Formative Evaluation in Islamic Elementary School

Formative evaluation of Arabic language proficiency plays a crucial role in identifying students' progress in the learning process, particularly in speaking skills or maharatul kalam. The aim of this study is to explore the implementation of formative evaluation on Arabic speaking skills in the third-grade class of SDIT Harapan Bunda Manado. The research adopts a qualitative approach with data collected through interviews with Arabic language teachers and observations in three different classes. The findings indicate that the types of speaking skills tests implemented in this school align with the principles of Arabic language teaching for beginners. The formative evaluation method of maharatul kalam includes reading texts aloud and identifying vocabulary words presented by the teacher. This evaluation is conducted formatively throughout the learning process. Both evaluation methods aim to measure students' reading, pronunciation, and vocabulary mastery as a foundation for developing more complex Arabic language skills in subsequent levels. Interactive evaluation, utilizing varied technologies and approaches, enables teachers to provide constructive feedback and customize learning according to individual student needs.

Authentic assessment in medical education: exploring AI integration and student-as-partners collaboration.

Traditional assessments often lack flexibility, personalized feedback, real-world applicability, and the ability to measure skills beyond rote memorization. These may not adequately accommodate diverse learning styles and preferences, nor do they always foster critical thinking or creativity. The inclusion of Artificial Intelligence (AI), especially Generative Pre-trained Transformers, in medical education marks a significant shift, offering both exciting opportunities and notable challenges for authentic assessment practices. Various fields, including anatomy, physiology, pharmacy, dentistry, and pathology, are anticipated to employ the metaverse for authentic assessments increasingly. This innovative approach will likely enable students to engage in immersive, project-based learning experiences, facilitating interdisciplinary collaboration and providing a platform for real-world application of knowledge and skills. This commentary paper explores how AI, authentic assessment, and Student-as-Partners (SaP) methodologies can work together to reshape assessment practices in medical education. The paper provides practical insights into effectively utilizing AI tools to create authentic assessments, offering educators actionable guidance to enhance their teaching practices. It also addresses the challenges and ethical considerations inherent in implementing AI-driven assessments, emphasizing the need for responsible and inclusive practices within medical education. Advocating for a collaborative approach between AI and SaP methodologies, the commentary proposes a robust plan to ensure ethical use while upholding academic integrity. Through navigating emerging assessment paradigms and promoting genuine evaluation of medical knowledge and proficiency, this collaborative effort aims to elevate the quality of medical education and better prepare learners for the complexities of clinical practice.

Multicultural integration and future pathways: an analysis of Chinese language education policies and practices in Philippine public secondary schools

ABSTRACT This paper examines the integration of Chinese language education within the Philippine public secondary school system, highlighting its role in promoting multicultural understanding and enhancing global competitiveness. Through a mixed-methods approach, involving surveys and interviews with educators, and administrators across a representative sample of schools, the study explores the current state of Chinese language policies as part of the SPFL (Special Program in Foreign Languages) foreign language education, curriculum designs, personnel training, community engagement, and resource allocation. The findings reveal several challenges, including limited instructional time, inadequate teacher training, scarce teaching resources, and a nascent stage of digital resource development. The study also delves into the societal and educational aspirations driving the demand for Chinese language education, against the backdrop of the Philippines' broader goals for national talent development and cultural integration. Recommendations are proposed to address the identified gaps, emphasizing the need for curriculum standards that more closely integrate language with multicultural activities, enhanced teacher support, community-based language activities, a multidimensional approach to language proficiency evaluation and leveraging digital education, etc., The paper advocates for an expanded notion of communicative competence that encompasses the ability for cultural exchange and digital literacy.

A Method for Quantitative Evaluation of Proficiency by Using Multipoint Surface Electromyography

A Method for Quantitative Evaluation of Proficiency by Using Multipoint Surface Electromyography

Capturing relationships between suturing sub-skills to improve automatic suturing assessment

Suturing skill scores have demonstrated strong predictive capabilities for patient functional recovery. The suturing can be broken down into several substep components, including needle repositioning, needle entry angle, etc. Artificial intelligence (AI) systems have been explored to automate suturing skill scoring. Traditional approaches to skill assessment typically focus on evaluating individual sub-skills required for particular substeps in isolation. However, surgical procedures require the integration and coordination of multiple sub-skills to achieve successful outcomes. Significant associations among the technical sub-skill have been established by existing studies. In this paper, we propose a framework for joint skill assessment that takes into account the interconnected nature of sub-skills required in surgery. The prior known relationships among sub-skills are firstly identified. Our proposed AI system is then empowered by the prior known relationships to perform the suturing skill scoring for each sub-skill domain simultaneously. Our approach can effectively improve skill assessment performance through the prior known relationships among sub-skills. Through the proposed approach to joint skill assessment, we aspire to enhance the evaluation of surgical proficiency and ultimately improve patient outcomes in surgery.

Algorithm Design and Implementation of Automatic Assessment and Expansion of English Vocabulary

Automatic assessment and expansion of English vocabulary play a crucial role in language learning and proficiency evaluation. In this paper, we propose the use of an Optimized Bi-directional Long Short-Term Memory Deep Learning (Obi-LSTM-DL) model for these purposes. We conduct experiments using a comprehensive vocabulary dataset and evaluate the model's performance across various scenarios. The results demonstrate the effectiveness of the Obi-LSTM-DL model in accurately assessing vocabulary proficiency levels and expanding vocabulary knowledge. Through optimization experiments, we show that increasing the vocabulary size leads to improved model performance. Additionally, the model's proficiency level assessment capability allows for tailored instruction and support for language learners. Comparative analysis with baseline models further confirms the superiority of the Obi-LSTM-DL model. The results demonstrate the effectiveness of the Obi-LSTM-DL model in accurately assessing vocabulary proficiency levels and expanding vocabulary knowledge. Through optimization experiments, we show that increasing the vocabulary size leads to improved model performance, with an average increase in accuracy of 1.5% for every 1,000 words added to the vocabulary. Additionally, the model's proficiency level assessment capability allows for tailored instruction and support for language learners. Comparative analysis with baseline models further confirms the superiority of the Obi-LSTM-DL model, with an average increase in accuracy of 3.2% over traditional models.

AI-POWERED PEDAGOGY: FOREIGN LANGUAGE STUDY IN HIGHER EDUCATION

The paper explores the transformative role of Artificial Intelligence (AI) in foreign language study within the context of higher education. It discusses how AI has redefined traditional teaching methods by introducing innovative pedagogical tools. Through an in-depth analysis, the research illustrates the enhancement of communicative capabilities, where AI significantly improves the interaction dynamics in the target language among students. Presently, AI-driven language platforms enable personalized learning, catering to individual strengths and cultural backgrounds. However, concerns emerge about the potential erosion of traditional teaching roles in the face of AI’s capabilities. Yet, for AI to enhance the learning process, educators must possess robust digital competencies to effectively leverage AI technologies. Furthermore, the utilization of AI enables the customization of learning experiences, adapting to individuals’ needs, propensities, and skill levels, thus fostering motivation and commitment to language acquisition. AI’s capability to offer immediate and precise feedback is also highlighted as a critical factor in expediting the learning process and easing the anxiety related to performance evaluation. Moreover, the emergence of intelligent conversational assistants is showcased as a pivotal development in the domain. These AI-driven language bots act as virtual language partners, offering realistic conversation practice and proficiency evaluations that contribute to a supportive and boundless learning environment. While acknowledging the substantial benefits of AI in foreign language education, the paper concludes by reaffirming the irreplaceable role of human teachers as the central organizers of the educational process. It is implied that the successful integration of AI in language pedagogy rests upon its alignment with conventional teaching practices guided by experienced educators.

Evaluation of Students' Proficiency in Removing Gutta-Percha Prior to Fiber Post Placement: A Retrospective Study.

This retrospective study focuses on dental students' proficiency in removing gutta-percha during fiber post space preparation, which is important for maintaining apical seal integrity in endodontically treated teeth. Emphasizing the significance of preventing further reinfection. The primary objective of this study was to assess the proficiency of undergraduate dental students in the manipulation of gutta-percha during fiber post preparation, specifically focusing on the psychomotor skills involved. In addition, the study aims to determine the predictive value of these skills on the ultimate clinical outcomes of the procedure, with particular emphasis on variations attributable to tooth type. The analysis encompassed 290 periapical radiographs obtained from endodontically treated teeth, all of which had undergone fiber post placement by undergraduate students at the College of Dentistry, Taibah University, Saudi Arabia. Postoperatively, the length of the remaining gutta-percha was measured by two experts in the field, and subsequent outcomes were classified into three categories: optimal, suboptimal, and inadequate, based on the extent of gutta-percha remaining. Students showed optimal removal rates ranging from 33.3% to 73.1%. Among the studied sample, upper anterior teeth were the highest included teeth (n=117, 40%). Remarkably, lower anterior teeth were more prone to suboptimal and inadequate gutta-percha remaining lengths (n=24, 33%). However, the chi-square test revealed no statistically significant difference in students' psychomotor skills while removing the gutta-percha and preparing the teeth to receive fiber posts across tooth types (p-value > 0.05). With the limitations of this study, more than half of the included cases show that undergraduate students of the College of Dentistry at Taibah University, Saudi Arabia, possess an optimum level of psychomotor skills in removing gutta-percha while preparing the teeth for receiving fiber posts. This study suggests enhancing the preclinical training of students by considering more training on different tooth types in relation to dental arches.

A Dive into Delivery of Oral Hygiene Advice Based on the Personalized Oral Hygiene Advice Model.

Oral health's impact on overall well-being highlights the importance of preventive measures through effective oral hygiene practices. Currently, there is growing recognition of the need for customized oral hygiene advice depending on the patient's unique needs and circumstances. This narrative review addresses the gap in understanding the significance of personalized guidance through the proposal of the Personalized Oral Hygiene Advice Model (POHAM) as a comprehensive guide for oral health professionals. This model was developed to adapt to evolving patient demographics and diverse challenges, promoting a patient-centric and effective oral health approach. The POHAM comprises a flow chart of strategies from establishing a good rapport with patients, conducting comprehensive assessment through history-taking, psychosocial and technology proficiency evaluation, tailored education modules, and customized oral care product recommendations until the reassessment. These strategies aim to enhance patient engagement and adherence, as well as act as a guide for oral health professionals to use in the clinical setting before and during the course of oral treatment. Nevertheless, continued research, education, and technological advancements are needed to realize the full potential of personalized oral hygiene strategies, ensuring a transformative and sustainable oral healthcare landscape.

Proficiency evaluation of shape and WPT radiomics based on machine learning for CT lung cancer prognosis

BackgroundLung cancer is a fatal disease which has high occurrence and mortality rates, worldwide. Computed tomography imaging is being widely used by clinicians for detection of lung cancer. Radiomics extracted from medical images together with machine learning platform has enabled automated lung cancer diagnosis. Therefore, this study is proposed with the aim to efficiently apply radiomics and ML techniques to classify pulmonary nodules in CT images. Lung Image Data Consortium is utilized which contains 1018 CT lung cancer cases.ResultsRadiomics are extracted using Shape, Gray Level Co-occurrence Method, Gray Level Difference Method, and Gray Level Run Length Matrix along with Wavelet Packet Transform. To select a relevant set of features two techniques, Analysis of variance and Chi-square test, are applied. The classification of nodule into benign or malignant is evaluated by using state-of-art models: Support vector machine, Decision Trees, Ensemble Trees (BOCET, BACET, RUSBOCET), Ensemble Subspace KNN and Ensemble Subspace Discriminant. The results show that, BACET gives best AUROC (92.9%), MGSVM gives best accuracy (90.4%), FGSVM yields the best sensitivity (97.8%), MGSVM gives best precision (94.1%) and RUSBOCET gives best specificity (84%).ConclusionsThe results show that the proposed methodology can be successfully used for the classification of pulmonary nodules based on CT images. The outcome thus can help clinicians to reach better decision, treatments and early diagnosis.

AI‐based language tutoring systems with end‐to‐end automatic speech recognition and proficiency evaluation

AbstractThis paper presents the development of language tutoring systems for non‐native speakers by leveraging advanced end‐to‐end automatic speech recognition (ASR) and proficiency evaluation. Given the frequent errors in non‐native speech, high‐performance spontaneous speech recognition must be applied. Our systems accurately evaluate pronunciation and speaking fluency and provide feedback on errors by relying on precise transcriptions. End‐to‐end ASR is implemented and enhanced by using diverse non‐native speaker speech data for model training. For performance enhancement, we combine semisupervised and transfer learning techniques using labeled and unlabeled speech data. Automatic proficiency evaluation is performed by a model trained to maximize the statistical correlation between the fluency score manually determined by a human expert and a calculated fluency score. We developed an English tutoring system for Korean elementary students called EBS AI PengTalk and a Korean tutoring system for foreigners called KSI Korean AI Tutor. Both systems were deployed by South Korean government agencies.

Beyond Traditional Assessment: A Fuzzy Logic-Infused Hybrid Approach to Equitable Proficiency Evaluation via Online Practice Tests

This article presents a hybrid approach to assessing students’ foreign language proficiency in a cyber–physical educational environment. It focuses on the advantages of the integrated assessment of student knowledge by considering the impact of automatic assessment, learners’ independent work, and their achievements to date. An assessment approach is described using the mathematical theory of fuzzy functions, which are employed to ensure the fair evaluation of students. The largest possible number of students whose reevaluation of test results will not affect the overall performance of the student group is automatically determined. The study also models the assessment process in the cyber–physical educational environment through the formal semantics of calculus of context-aware ambients (CCAs).

Evidence of How Physicians and Their Patients Adopt mHealth Apps in Germany: Exploratory Qualitative Study.

The enactment of the "Act to Improve Healthcare Provision through Digitalisation and Innovation " (Digital Healthcare Act; Digitale-Versorgung-Gesetz [DVG]) in Germany has introduced a paradigm shift in medical practice, allowing physicians to prescribe mobile health (mHealth) apps alongside traditional medications. This transformation imposes a dual responsibility on physicians to acquaint themselves with qualifying apps and align them with patient diagnoses, while requiring patients to adhere to the prescribed app use, similar to pharmaceutical adherence. This transition, particularly challenging for older generations who are less skilled with technology, underscores a significant evolution in Germany's medical landscape. This study aims to investigate physicians' responses to this novel treatment option, their strategies for adapting to this form of prescription, and the willingness of patients to adhere to prescribed mHealth apps. Using an exploratory qualitative study design, we conducted semistructured interviews with 28 physicians and 30 potential patients aged 50 years and older from August 2020 to June 2021. The findings reveal several factors influencing the adoption of mHealth apps, prompting a nuanced understanding of adoption research. Notably, both physicians and patients demonstrated a lack of information regarding mHealth apps and their positive health impacts, contributing to a deficiency in trust. Physicians' self-perceived digital competence and their evaluation of patients' digital proficiency emerge as pivotal factors influencing the prescription of mHealth apps. Our study provides comprehensive insights into the prescription process and the fundamental factors shaping the adoption of mHealth apps in Germany. The identified information gaps on both the physicians' and patients' sides contribute to a trust deficit and hindered digital competence. This research advances the understanding of adoption dynamics regarding digital health technologies and highlights crucial considerations for the successful integration of digital health apps into medical practice.

BUILDING MEDIA LITERACY SKILLS FOR FUTURE JOURNALISTS: STRATEGIES TO ANALYZE FAKE NEWS AND RESIST DISINFORMATION

The advent of the digital age has ushered in an era of unparalleled access to information, transforming the way we engage with content. However, this transformative shift has also given rise to a concerning surge in fake news and disinformation. This article delves into the crucial role that educators play in preparing students to navigate this complex and information-saturated landscape. Focusing on the principles of media literacy, our exploration revolves around the implementation of targeted teaching strategies. These strategies are designed to cultivate in students the essential skills of critical analysis, empowering them to sift through information with discernment. The emphasis lies on nurturing critical thinking skills, honing the ability to evaluate sources, employing effective fact-checking techniques, fostering cross-platform awareness, and fostering collaborative learning environments. By leveraging real-world case studies and delving into an examination of cognitive biases, the article underscores the significance of these pedagogical strategies in equipping students to not only decipher the veracity of information but also to actively resist the allure of misinformation. The practical application of these strategies becomes evident in the context of empowering students to navigate the intricate web of online content with resilience. The article concludes by delving into the realm of assessment methods, paving the way for a robust evaluation of students' media literacy proficiency. Furthermore, it extends its gaze towards future research directions, recognizing the evolving nature of media consumption and the constant morphing of the digital landscape. In a resounding call to action, the article advocates for the integration of media literacy into educational curricula, acknowledging it as a fundamental cornerstone for fostering informed, critically-thinking individuals poised to thrive in an ever-evolving informational milieu.

Enhancing EMS readiness: a pilot evaluation of CPR proficiency and training dynamics among paramedics in Poland

Effective Cardiopulmonary Resuscitation (CPR) is crucial for improving outcomes in cardiac arrest situations. This study aims to assess the proficiency of paramedics in the Lubelskie Voivodeship, Poland, in performing CPR, focusing on compression depth and ventilation techniques. A cohort of 69 paramedics was engaged in this analysis, utilizing an Ambu manikin to simulate CPR scenarios. This setup allowed for a comprehensive assessment of each participant’s technique, focusing on compression depth consistency and the efficiency and accuracy of ventilation techniques. The study revealed that paramedics demonstrated commendable proficiency in chest compression, achieving an average depth of 58.48 mm, which falls within the recommended range of 50 mm to 60 mm. However, there was a notable variation in compression depths, ranging from 47 mm to 72 mm. Additionally, ventilation techniques displayed significant inconsistencies, with 87.4% of ventilations performed below the recommended volume range. Many participants also deviated from the advised compression-to-ventilation ratio, further indicating the need for enhanced guidelines adherence. While paramedics exhibit a strong foundation in CPR techniques, the observed variations and inconsistencies underline the importance of continuous and focused training. This study advocates for the development and implementation of targeted training programs to address these gaps. Such initiatives should reinforce adherence to established CPR guidelines and emphasize integrating realistic simulation experiences to improve overall CPR performance, ultimately contributing to better patient outcomes in emergencies.

Self-Assessment versus Objective Proficiency Evaluation in English as a Foreign Language among Italian First-Year University Students

Self-Assessment versus Objective Proficiency Evaluation in English as a Foreign Language among Italian First-Year University Students

A machine learning-based investigation of syntactic complexity measures in second language acquisition of Chinese

Abstract L2 syntactic complexity research has shown that employing multidimensional measures to assess writing proficiency levels may yield more accurate results compared to one-dimensional measures. However, the optimal number and combination of measures have not been thoroughly explored. This study addresses these gaps by employing a novel machine learning-based approach to quantitatively investigate the effectiveness of multidimensional measures and determine the optimal combination of measures. Through the analysis of a dataset comprising 36 L2 Chinese learners, we found that multidimensional syntactic complexity measures outperformed one-dimensional measures in accurately differentiating learners. Specifically, a combination of three measures (Mean Length of Sentence, Mean Length of T-unit, and Mean Length of Clause) achieved the highest accuracy in classifying the learners. The implications of this research include the development of computer-assisted placement tests and proficiency evaluations, as well as providing practical guidance for language teachers in designing complexity-based instruction.