Linguistic Assessment Research Articles

Sentence Comprehension in Spanish-Speaking Children With Hearing Loss: On the Integration of Morphosyntactic and Lexico-Semantic Cues.

Children with hearing loss (CHL) who use hearing devices (cochlear implants or hearing aids) and communicate orally have trouble comprehending sentences with noncanonical order. This study explores sentence comprehension strategies in Spanish-speaking CHL, focusing on their ability to integrate morphosyntactic cues (word order, morphological case marking) with verbs differing in their syntax-to-semantics configuration. Fifty-eight Spanish-speaking CHL and 58 children with typical hearing (CTH) with a hearing age of 3;5-7;8 (years;months; i.e., time of adequate access to sound, in the case of CHL since effective fitting or implantation) were recruited in Argentina. A sentence comprehension task using the truth-value judgment paradigm was designed, including sentences with activity verbs and object-experiencer psych verbs in subject-verb-object (SVO) and object-verb-subject (OVS) orders, thus varying in canonicity. Both groups showed good comprehension of SVO sentences with activity verbs but had difficulties with structures that deviated from canonicity. Comprehension was at chance level in both groups and at all hearing ages for sentences with activity verbs in OVS order and sentences with object-experiencer psych verbs in SVO order (both are noncanonical for the verb type). Sentences with object-experiencer psych verbs in OVS order were also comprehended at chance level by CHL and by the youngest CTH. These results suggest that Spanish-speaking CTH aged 7 years prioritize semantic information over case marking in sentences with a noncanonical syntactic structure. In CHL, difficulties with noncanonical structures seem to extend to semantic deviations, at least until hearing age 7 years. CHL might also struggle with the semantic structures of object-experiencer psych verbs beyond the age when CTH do. These findings are relevant for the linguistic assessment and education of CHL.

Performance of ChatGPT and Bard on the medical licensing examinations varies across different cultures: a comparison study

BackgroundThis study aimed to evaluate the performance of GPT-3.5, GPT-4, GPT-4o and Google Bard on the United States Medical Licensing Examination (USMLE), the Professional and Linguistic Assessments Board (PLAB), the Hong Kong Medical Licensing Examination (HKMLE) and the National Medical Licensing Examination (NMLE).MethodsThis study was conducted in June 2023. Four LLMs (Large Language Models) (GPT-3.5, GPT-4, GPT-4o and Google Bard) were applied to four medical standardized tests (USMLE, PLAB, HKMLE and NMLE). All questions are multiple-choice questions and were sourced from the question banks of these examinations.ResultsIn USMLE step 1, step 2CK and Step 3, there are accuracy rates of 91.5%, 94.2% and 92.7% provided from GPT-4o, 93.2%, 95.0% and 92.0% provided from GPT-4, 65.6%, 71.6% and 68.5% provided from GPT-3.5, and 64.3%, 55.6%, 58.1% from Google Bard, respectively. In PLAB, HKMLE and NMLE, GPT-4o scored 93.3%, 91.7% and 84.9%, GPT-4 scored 86.7%, 89.6% and 69.8%, GPT-3.5 scored 80.0%, 68.1% and 60.4%, and Google Bard scored 54.2%, 71.7% and 61.3%. There was significant difference in the accuracy rates of four LLMs in the four medical licensing examinations.ConclusionGPT-4o performed better in the medical licensing examinations than other three LLMs. The performance of the four models in the NMLE examination needs further improvement.Clinical trial numberNot applicable.

The Stability of Linguistic Skills of Arabic-Speaking Children Between Kindergarten and First Grade.

This study aimed to evaluate the stability of phonological awareness (PA) and language achievements between kindergarten and first grade among Arabic-speaking children. A total of 1,158 children were assessed in PA and language skills in both grades and were classified based on distinct and integrated achievements on PA and language following percentiles' cutoff criteria. The classification of distinct achievements constituted high, intermediate, low, and very low achievement-based groups for each domain. The classification of the integrated achievements on both domains constituted four groups: intermediate-high PA and language, very low PA, very low language, and doubly low (very low PA and language). Descriptive statistics and McNemar's tests were used to examine the stability of these groups. The analyses showed a significant improvement in achievements on most tasks. The distinct classification for PA and language indicated that many more kindergarteners in the extreme distribution with high and very low achievement levels maintained this profile in first grade compared to those with intermediate achievements. For PA, 55.7% of kindergarteners with high, 30% with intermediate, 30.4% with low, and 45.5% with very low achievements maintained their achievements in first grade. For language, 52.5% of kindergarteners with high, 34.5% with intermediate, 38.8% with low, and 59.8% with very low achievements maintained their language achievements. The integrated classification indicated a higher achievement stability rate for kindergarteners with intermediate-high PA and language (91.3%) and for doubly low achievers (84.7%) compared to very low PA (24.1%) or very low language (31.8%) achievers. The study indicated a higher variability in the distribution of the intermediate achievements compared to the high and very low achievements, which were more stable across grade. The results emphasize the need for dynamic linguistic assessments and early intervention for children with very low achievements in PA and language who show a poor prognosis.

EVALUATION OF THE INVESTMENT CLIMATE BASED ON FUZZY LOGIC

The subject of the study is the investment climate of the country, region and investment attractiveness of the enterprise. The article is aimed at substantiating a fuzzy logical model for assessing the investment climate of a country, region and investment attractiveness of an enterprise under the influence of three groups of factors: economic, organizational and psychological. The hypothesis of the study is that it is possible to define the investment climate (IC) and make decisions on foreign direct investment (FDI) based on data on indicators of influence factors, even if these indicators are not clearly quantified. The division of all influence factors into three groups: economic, organizational and psychological, and the definition of linguistic assessments for those factors that do not have a natural quantitative scale, allows taking into account the expert assessment of those aspects of the investment climate that are not assessed by statistical data and cannot be expressed quantitatively, but only with the help of descriptive words based on a sense of the situation. The developed model allows determining the state of the investment climate or attractiveness under the influence of a set of factors that the user determines, depending on the country, territory, enterprise and the availability of statistical and expert information. A review of previous studies shows that the development of models based on the theory of fuzzy logic, as opposed to regression analysis, allows not only to use a larger number of indicators, but also to take into account the so-called qualitative indicators that were previously not taken into account due to the impossibility of their quantitative measurement. The objective of the study is to build a model based on fuzzy modelling, which is the method of this research. The results of the study show that the use of the obtained model can help determine the investment climate based on the analysis of factors. Practical implications – obtaining a built-in model for assessing the investment climate for making investment decisions. Value/originality of the study: the developed model, unlike similar ones, is flexible, i.e. it can include any number of factors and can be used by specialists of different levels, from civil servants to entrepreneurs. The model also allows for the inclusion of any factors that the researcher deems necessary, as they can be assessed on any scale.

Canva-based E-comic on the Dangers of Plastic Waste Environment as Learning Media for IPAS Effectively Improve Learning Outcomes

The decline in IPAS learning outcomes and focus on the material on the dangers of plastic waste is indicated by the unawareness of disposing of waste in its place. The purpose of this study was to develop Canva-based E-comics on the material of the Dangers of Plastic Waste for the Environment as an Effective IPAS Learning Media to Improve Learning Outcomes. The subjects used were fifth grade students of SDN Ngijo 01 Semarang. The method used is development research with the ADDIE model. Data collection used interviews, observations, tests, and questionnaires. Data analysis used descriptive and inferential statistical techniques. Development through five stages namely analysis, design, development, implementation, and evaluation. The results of media feasibility included a feasible category based on the assessment of material experts, media experts, linguists, and teacher and student response questionnaires. The effectiveness of e-comic is in the effective category to be used based on the increase in student learning outcomes after using this media. The conclusion is that the Canva-based e-comic media developed is valid, feasible, and effective in the teaching and learning process of the material on the dangers of plastic waste in IPAS subjects.

Classification-based consensus model considering quantum interference in linguistic distribution environment

Multi-attribute group classification (MAGC) is widely used in dealing with a variety of practical problems. However, cognitive biases, resulting from factors such as irrational behaviors, epistemic uncertainty, and interference phenomena, may critically affect the consensus reaching process (CRP) of MAGC. To eliminate such influences, this study proposes an ordinal classification consensus model in a linguistic environment based on quantum probability theory (QPT), with the aim of classifying the alternatives into several predefined ordinal classifications accepted by a majority of experts. First, the linguistic distribution assessments (LDAs), which can depict the quantitative distribution and qualitative vagueness, are used to express the uncertain preference of experts. Second, the LDAs best-worst method (BWM) and LDAs maximizing deviation model (MDM) are developed to identify the subjective and objective weight of attributes, and then these two types of attributes weight are integrated by quantum-like Bayesian networks (QLBN). Third, a maximum consensus model (MCM), maximizing the consensus level of ordinal classification results of experts, is provided to determine the parameters of QLBN. When the consensus level is lower than the predetermined threshold, a minimum adjustment distance model (MADM) is designed to guide the preference-modification of experts to derive the consensus classification of alternatives. Finally, a risk assessment case study is conducted to verify the feasibility and effectiveness of the proposed method. Sensitivity analysis and comparison analysis are performed to verify the feasibility and effectiveness of the proposed method.

Minimum adjustment cost consensus model with bounded risk preference attitudes: A perspective based on fractional stochastic dominance

Linguistic multi-attribute group decision making with linguistic distribution assessment (LMAGDM-LDA) problems have been widely investigated. However, in the existing studies, the risk attitudes of decision maker are seldom considered. Inspired by this, in this paper, we employ the idea of fractional stochastic dominance to develop a consensus reaching framework for LMAGDM-LDA with bounded risk preference attitudes. Then, we design an interactive learning algorithm for obtaining the bounded risk preference threshold. Next, we analyze the deception behaviors and average behaviors of experts, and develop the minimum adjustment cost consensus model with bounded risk preference attitude (MACC-BRP). And we justify the connection between the MACC-BRP and the minimum adjustment cost consensus model with other risk attitudes. Furthermore, we provide a distance-based method to obtain the rankings of alternatives. Furthermore, a numerical analysis is provided to show the computation process of the proposed method, and a comparison analysis and a simulation analysis are further conducted to show the advantages and features of the proposal. The simulation results show the effects of the risk preference threshold, the intrinsic individual weight and the average threshold. The comparison results show that the proposed minimum adjustment cost consensus models have clear advantages.

Pengembangan Lembar Kerja Peserta Didik (LKPD) Berbasis Berpikir Kritis pada Mata Pelajaran PPKn di Kelas III MIN 3 Simalungun

The purpose of this study was to determine the feasibility of critical thinking-based Learner Worksheets (LKPD) in Civics subjects in Class III MIN 3 Simalungun. The background is that the Learner Worksheet used at MIN 3 Simalungun is an instant version of the publisher provided by the school not the result of the preparation carried out by the teacher himself. And printed with black ink on opaque paper. LKPDs found in schools are not yet based on critical thinking. Indicators of critical thinking have not been included in the LKPD, so it does not train students' critical thinking skills. This research is an R&D (Research and Development) study. This study uses the ADDIE development model (Analysis, Design, Development, Implementation, and Evaluation). Researchers only limit it to the development stage. Researchers modify the development model as needed, because in terms of the formulation of the problem it is only limited to whether or not the LKPD will be developed. So, for this reason, researchers do not carry out the implementation and evaluation stages. Based on the results obtained after being validated by validators from 3 teams of experts, namely from material experts, a percentage of 94% was obtained which was declared very feasible. The assessment of the media expert showed a percentage of 88%, also declared very feasible. In addition, the assessment of linguists obtained a percentage of 86% and was declared very feasible. So it can be concluded

Genres of New Media in Linguistic Expertise Practices

The article addresses the debatable points of research into present-day media genres: memes, surveys, comments, social network posts, etc. that become the materials for forensic linguistic expertise. The issue of identifying the object of linguistic expertise of information materials is discussed. The ways the new discursive reality transforms the existing methodological approaches are conceptualized. The brevity of the texts under examination, the dependence on the sociocultural context and the communicative situation, the presence of hypertext determine the complexity of the expert assessment of new media materials. The cases of ambiguous interpretation of brief comments and the peculiarities of defining the subject of speech in them are dealt with in the article. Special attention is paid to the techniques of play on words (pun) and irony as well as the linguistic semiotic analysis of creolized texts. The problem areas of expert research into new media materials included in the space of social communications are characterized. Special attention is paid to the problem of multi-discipline expertise, since the specificity of the material under study and the tasks to be solved determine the involvement of specialists of the socio-humanistic profile (psychologists, sociologists, political scientists, religious scholars, etc.) and necessitate solving the issue of the boundaries of experts’ competence. The new discursive reality associated with the involvement of mass audience in the production of media content suggests some changes in approaches to the linguistic expert assessment of the materials under scrutiny.

Aptitude for Research Among Medical Students in India: Identifying the Challenges.

Introduction Understanding the reasons behind the undervaluation of research among undergraduate medical students in India is crucial for advancing medical knowledge. This cross-sectional study aims to investigate the knowledge, interest, and barriers faced by 606 Indian medical students through an online questionnaire distributed via social media platforms. Aims To identify the knowledge of research and the challenges faced by medical students to pursue research in their undergraduate education. Methods and material This was a prospective observational study carried out over a period of one month in October 2022. Study approval was taken from the Genebandhu Independent Ethics Committee (Reference Number- ECG004/2022). The responses obtained from the questionnaire were recorded in Google Sheets and transferred to Microsoft Excel (Redmond, WA, USA). Results Among the participants, 46.53% were male and 53.47% were female, primarily from the first (11.39%) and second (9.90%) years of their medical education. Notably, the majority had undertaken United States Medical Licensing Examination (USMLE) (54.95%), followed by National Eligibility cum Entrance Test (Postgraduate) (NEET-PG) (34.65%) and Professional and Linguistic Assessments Board (PLAB) (7.92%). The study revealed that 78.22% considered research pivotal to their academic trajectory, with a mean age of 23.14 years (SD=2.82) and an average research knowledge score of 2.75 (SD=1.31). The type of postgraduate exam significantly influenced enthusiasm for research activities (p<0.001), with higher enthusiasm among those preparing for exams abroad. Nonetheless, the type of medical college did not significantly affect interest in research activities (p=0.4879). Conclusion Addressing the undervaluation of research among undergraduate medical students in India is imperative. The curriculum should integrate robust support mechanisms to nurture research skills, emphasizing its importance for future medical practitioners. This could involve seminars, courses, and interactive sessions aimed at fostering research acumen among students.

Learner Assessment System in e-Learning with OBE Approach: Activity Performance, Ability Level and Recommendation

E-learning can lead learners to achieve learning outcomes if it is designed based on several principles. One is applying assessments that motivate and inform ability levels. In Outcome-based Education (OBE), assessment is integral to the system. However, e-learning has limitations in providing assessment instruments according to needs, such as assessing complex and detailed aspects and accommodating a variety of numerical and linguistic assessment data. Moreover, the presence and involvement of learners affect their performance and learning outcomes. This study proposes a learner assessment system in e-learning with the OBE approach, including learning design, activity performance analysis, ability level determination, and recommendations. This system adds the e-rubric to e-learning to overcome instrument limitations and accommodate comprehensive assessments. Various numerical and linguistic assessment data are unified using 2-tuple fuzzy linguistics, producing ability levels as two tuples. Performance analysis was based on event log data using descriptive statistical technique and alignment-based conformance checking, from frequency, time, and sequence of activity objects, resulting in five activity performance variables. The performance value of each variable is converted into High, Medium, or Low levels. The ability and performance levels are processed using rule-based methods to produce recommendations for learning stages and activity performance directions. The results of this research can be used as input for academic stakeholders and online learning providers and potentially be applied to the advancement of e-learning in higher education. Doi: 10.28991/HIJ-2024-05-03-03 Full Text: PDF

A group stability-based consensus model for multi-criteria group decision-making problems with linguistic distribution assessments

In multi-criteria group decision-making (MCGDM) problems with linguistic distribution assessments (LDAs), this study proposes a group stability-based consensus model to facilitate the generation of solutions that satisfy predefined group stability and group consensus requirements. The group stability and group consensus measures are constructed at the criteria, alternative, expert, and global levels. In terms of different degrees of group stability and group consensus in MCGDM problems, it can be categorized into four situations by comparing with predefined thresholds, which are: 1) group stability measure is satisfied, and group consensus measure is satisfied; 2) group stability measure is not satisfied, and group consensus measure is satisfied; 3) group stability measure is satisfied, and group consensus measure is not satisfied; 4) group stability measure is not satisfied, and group consensus measure is not satisfied. To accelerate the group stability-based group consensus reaching process, optimization problems with group stability and group consensus requirements are constructed to obtain suggested intervals and recommended intervals for LDAs. This contributes to the feedback mechanisms corresponding to the four different situations. The proposed method is applied to an ultrasonic medical imaging workstation selection problem to demonstrate its effectiveness. The superiority of the proposed method is validated through comparative experiments.

Pengembangan Buku Portofolio Literasi Berbasis Ajaran Tri-N untuk Meningkatkan Kemampuan Menulis Siswa Sekolah Dasar

This study aims to improve the writing skills of fable stories in grade V students. The type of research used is R&amp;D (Research and Development) or development research. This development research uses the ADDIE development model (Analysis, Design, Development, Impementation, and Evaluation). The researcher has developed a literacy portfolio book based on Tri-N teaching for students' writing skills. Data collection was conducted by observing the learning process, interviewing educators, tests in the form of pre and post tests, and questionnaires to determine student and teacher responses. Data collection is supported by documentation of the implementation of learning by applying the product. The results of research using this development product can be said to be feasible based on the assessment of media experts and linguists. Based on the results of the pre test, post test, teacher response, and student response, the use of Tri-N teaching-based literacy portfolio books can improve the writing skills of fifth grade elementary school students so that it can be said that this product is effective.,

1030 Role of International Webinar Among International Medical Graduates (IMGs) on Enhancing Understanding of the UK Surgical Training Pathways and Professional and Linguistic Assessments Board (PLAB) Test: A Global Perspective

1030 Role of International Webinar Among International Medical Graduates (IMGs) on Enhancing Understanding of the UK Surgical Training Pathways and Professional and Linguistic Assessments Board (PLAB) Test: A Global Perspective

Synthesis of an algorithm for automated adjustment of lumber drying based on linguistic information

Relevance. Lumber drying is associated with high risks of obtaining a low-quality or even unusable product. The problem under consideration has a number of reasons, both in violation of the technological process and in incorrect settings of drying mode parameters at different stages. The procedure for automated adjustment of parameters is usually associated with a linguistic assessment of the quality of the product, according to which a decision on adjusting the parameters should be made, taking into account signs of a violation of the technological process. Technical and scientific publications contain generalized information about methods for selecting parameters for various situations, which can be formalized and included in algorithms for adjusting the parameters of a programmable logic controller. Aim. To create an algorithm using a Fuzzy controller that allows you to configure process parameters and adapt the drying chamber to the optimal parameters for drying lumber under given operating conditions. Methods. Analysis of the technical process database obtained during one and a half years of operation of the main parameters dispatch system for 28 full lumber drying cycles, with the aim of forming an automated adjustment algorithm that takes into account the lumber drying conditions. Results. The authors have created an algorithm for automated adjustment of parameters for three stages of drying based on linguistic ideas about the quality of the product. The algorithm eliminates the possibility of obtaining a low-quality product, as well as encourages service personnel to correctly generate a technological process passport. Conclusions. The inclusion of an automated parameter adjustment loop in the control circuit allows us to minimize the number of poor-quality processes when starting to operate a new drying chamber and eliminate defects in further technical processes.

A Consensus-Based 360 Degree Feedback Evaluation Method with Linguistic Distribution Assessments

The 360 degree feedback evaluation method is a multidimensional, comprehensive assessment method. Evaluators may hesitate among multiple evaluation values and be simultaneously constrained by the biases and cognitive errors of the evaluators, evaluation results are prone to unfairness and conflicts. To overcome these issues, this paper proposes a consensus-based 360 degree feedback evaluation method with linguistic distribution assessments. Firstly, evaluators provide evaluation information in the form of linguistic distribution. Secondly, utilizing an enhanced ordered weighted averaging (OWA) operator, the model aggregates multi-source evaluation information to handle biased evaluation information effectively. Subsequently, a consensus-reaching process is established to coordinate conflicting viewpoints among the evaluators, and a feedback adjustment mechanism is designed to guide evaluators in refining their evaluation information, facilitating the attainment of a unanimous evaluation outcome. Finally, the improved 360 degree feedback evaluation method was applied to the performance evaluation of the project leaders in company J, thereby validating the effectiveness and rationality of the method.

The consistent fuzzy suitability assessment of forest land resources with multi-source heterogeneous data.

In view of the suitability assessment of forest land resources, a consistent fuzzy assessment method with heterogeneous information is proposed. Firstly, some formulas for transforming large-scale real data and interval data into fuzzy numbers are provided. To derive the unified representation of multi-granularity linguistic assessment information, a fuzzy quantitative transformation for multi-granularity uncertain linguistic information is proposed. The proofs of the desirable properties and some normalized formulas for the trapezoidal fuzzy numbers are presented simultaneously. Next, the objective weight of each assessment indicator is further determined by calculating the Jaccard-Cosine similarity between the trapezoidal fuzzy numbers. Moreover, the trapezoidal fuzzy numbers corresponding to the comprehensive assessment values of each alternative are obtained. The alternatives are effectively ranked according to the distance from the centroid of the trapezoidal fuzzy number to the origin. Finally, based on the proposed consistent fuzzy assessment method, the suitability assessment of forest land resources is achieved under a multi-source heterogeneous data setting.

A game theoretic conflict analysis model with linguistic assessments and two levels of game play

In a conflict scenario, the domestic and international stake holders vye to safeguard their specific vested interests and objectives, like in the Syrian and Afghan conflicts. Knowledge about the position of domestic players can help both domestic and international players determine the root causes of conflict and work in groups to resolve the divergent issues. Due to complex nature of conflicts, it is pertinent to study conflict at domestic and international levels separately. For this purpose, we design a two-level conflict analysis model based on game theory and linguistic assessments of players. The first level deals with local players by playing a game between each of them in view of local issues and taking into account the local grouping. At the second level, game is played between local groups and international players regarding multiple issues. In this way, all the parties calculate the gains or losses of comparable actions of each other. Thus, the proposed model provides a comprehensive study of conflict. This paper studies Syrian conflict to validate the conflict analysis algorithm and explain the computations and results.

Linguistic and Auditory Assessment: An Effort to Improve the Beginning Reading Ability of Dyslexic Children in Grade IV at Elementary School Level

This study describes the implementation of linguistic and auditory awareness assessment in improving dyslexic children's early reading skills. The factors studied include linguistic (phoneme, morphology, orthography) and auditory (phoneme, morpheme, semantic, syntax) awareness, which are important in the early reading process. The research method was descriptive qualitative, with one 10-year-old student subject from grade 4. The assessment phase involved classical identification with learning instruments from grade 4 to grade 1, as well as a pre-early reading assessment focusing on linguistic and auditory awareness. Results showed significant linguistic awareness (33.59%) and auditory awareness (60%) influence reading ability. Phoneme and morphology aspects affect reading ability in terms of linguistics, while morphemes and syntax are significant in auditoris.

Threatening as a sociocultural–conceptual communicative act

AbstractThe present article revisits threatening discourses from the perspectives of anthropological linguistics, Cultural Linguistics, speech act theory and pragmatics. On the basis of linguistic data from 11th‐century Britain (Old English), 14th‐century Norway (Old Norse), 19th‐century Ireland (Early Modern Irish English and Modern Irish), 20th‐century Hong Kong (Hong Kong English) as well as 21st century South Africa (Black South African English), the discussion establishes verbal threats as socio‐pragmatic modes of action, that is, commissives that come as both illocutionary and perlocutionary acts. The main aim of the article is to elaborate on the central role that sociocultural norms and conventions play in the enregisterment of threat in a speech community at a given point in time. The article contributes to the development of forensic–linguistic threat assessment through a stronger focus on the sociocultural embeddedness of threatening discourses.