Production Tasks Research Articles

Distorted time perception in patients with neurocognitive impairment

BackgroundTime perception is known to be distorted in patients with neuropsychiatric disorders. Therefore, this study aims to investigate the correlation between cognitive decline and time distortion by examining time perception in participants with neurocognitive impairment (Alzheimer's disease [AD], vascular dementia [VD], and Parkinson's disease dementia [PDD]) compared to those with subjective cognitive impairment (SCI). MethodsOverall, 569 participants with cognitive decline complaints between 2013 and 2022 were investigated. Participants were subjected to a verbal estimation task, time production task, time comparison task, and neuropsychological assessments. ResultsTime perception abilities were distorted in patients with neurocognitive impairment compared to those with SCI. Despite similar educational backgrounds, the vascular cognitive impairment (VCI)/VD group demonstrated the lowest MMSE scores (22.4 ± 4.2, p-value <0.001) and larger time-estimation errors. Patients with VCI/VD significantly underestimated time in the 35-s (19.6 ± 12.6s) and 60-s (28.7 ± 19.9s) tasks. In the time production task, patients with VCI/VD produced shorter times in their 15-s (12.7 ± 4.3; p-value = 0.001), 30-s (23.6 ± 8.3; p value < 0.001), and 60-s (43.8 ± 18.9; p-value <0.001) trials. In the time comparison task, the VCI/VD group had significantly fewer correct answers than that in the SCI groups (6.0 ± 1.3 vs. 7.1 ± 0.9, p-value <0.001). Correlation analysis revealed that multiple cognitive functions are involved in the time perception tasks. ConclusionsPatients with VCI/VD had the poorest time perception. These findings may provide a modest contribution to understanding the underlying pathophysiology and psychological connections related to temporal abilities in time perception.

L2 Spanish clitics among Brazilian Portuguese-speaking learners: the predictive role of lexical knowledge

We examined the acquisition of third-person accusative clitics (e.g., lo, la, los, las) in L2 Spanish among Brazilian Portuguese (BP) speakers. In BP, the animacy of the referent is the main feature constraining accusative pronoun use while, in Spanish, animacy does not affect clitic realization. We tested Lardiere’s (2008; 2009) Feature Reassembly Hypothesis (FRH), Schwartz &amp;amp; Sprouse’s (1996) Full Transfer/Full Access hypothesis (FT/FA), and the suitability of productive vocabulary knowledge as a proxy for overall proficiency and its predictive power for the acquisition of clitics. 74 BP-speaking L2 Spanish learners and a comparison group of 23 native Spanish speakers completed a language background questionnaire, a vocabulary test (Prueba Léxica de Español y Portugués/Prova Léxica de Espanhol e Português, PLEP), an elicited production task, and an acceptability judgment task. Only the L2 Spanish participants completed the tasks in both languages. Our findings are consistent with the FRH, showing that the participants successfully disassemble animacy features from their L1 when acquiring the non-animacy-driven clitics in Spanish. However, animacy effects were found in the L2 production data but not in their receptive grammatical knowledge. Furthermore, animacy effects were not dependent on proficiency as no interactions between these factors were found, thus rejecting the existence of a full transfer stage.

A behavioral conditional diffusion probabilistic model for human motion modeling in multi-action mixed human-robot collaboration

Collision avoidance is priority for human-robot collaboration (HRC). Human motions have stochastic, making it difficult for robots to recognize humans. To establish accurate human motion models is important to recognize humans. In the collaboration process, the action categories may suddenly and continuously switch to adapt to complex production tasks, namely, the stochastic of human motions, and we call this collaboration process as multi-action mixed HRC. The previous HRC rarely considered the stochastic of human motions. However, the stochastic in multi-action mixed HRC brings great challenges to human motion modeling. On the one hand, the same observed motions may develop into different action categories, the motion distribution need to be predicted. On the other hand, the connected motions between two action categories are missing, and need to be predicted. To address these two problems, this study introduced diffusion probabilistic models to capture the stochastic of human motions. However, the current diffusion probabilistic models cannot realize the high-accuracy human motion prediction. Most of them did not consider the condition distribution in diffusion process, and did not comprehensively capture the spatiotemporal characteristics between human and robot. To solve the above problems, a behavioral conditional probabilistic diffusion model (BCDPM) is proposed. The BCDPM model can capture the stochastic of human motions to model the human motion distribution. A mask mechanism is combined with diffusion prior generated by BCDPM model to predict the missing connected motions. The BCDPM model consists of the designed constrain network, the denoising network, and enhanced memory graph neural network. The constrain network can generate the condition distribution, the denoising network and enhanced memory graph neural network can capture the short term and long term spatiotemporal characteristics, respectively. Moreover, the overlapping motion primitives are explicitly encoded into the implicit BCDPM model to mine commonalities of motions. The results show the proposed method can obtain excellent accuracy in prediction and outstanding F1 score in collision detection experiment.

Influences of early and intense L2 exposure on L1 causal verb production: Comparison of 5-, 7-, and 9-year-old bilingual and monolingual children

This study investigates the influences of early and intense L2 exposure on children’s L1 causative verb production, assessed by an experimental causative verb production task. Turkish expresses causality by morphological and lexical means, whereas English does so by periphrastic and lexical means. Learning L2 English might enhance L1 Turkish causative verb production by highlighting the parallels and contrasts in causal expressions between the languages, which may result in an enriched L1 causative use. Five-, 7 -, and 9-year-old L1-Turkish L2-English bilingual ( n = 80) and L1-Turkish monolingual ( n = 80) children participated in the study in L1-Turkish. Results indicated that language group differences only emerged for the use of morphological causative verbs in favor of 5-year-old bilinguals compared with monolingual peers. Age group differences occurred only for the monolingual group and only for morphological verbs. Specifically, monolingual 7- and 9-year-olds performed better than monolingual 5-year-olds. Causative verb-type differences were only seen for 5-year-old monolinguals, who performed better for lexical than morphological verbs; in contrast, 5-year-old bilinguals performed equally well on the two types of causatives, and better than 5-year-old monolinguals on morphological causatives. Overall, these findings indicate that learning an L2 with structural similarities and differences compared with L1 might enhance children’s awareness and correct use of causal linguistic structures.

A local space transfer learning-based parallel Bayesian optimization with its application

The optimization of process parameters in polyolefin production can bring significant economic benefits to the factory. However, due to small data sets, high costs associated with parameter verification cycles, and difficulty in establishing an optimization model, the optimization process is often restricted. To address this issue, we propose using a transfer learning Bayesian optimization strategy to improve the efficiency of parameter optimization while minimizing resource consumption. Specifically, we leverage Gaussian process (GP) regression models to establish an integrated model that incorporates both source and target grade production task data. We then measure the similarity weights of each model by comparing their predicted trends, and utilize these weights to accelerate the solution of optimal process parameters for producing target polyolefin grades. In order to enhance the accuracy of our approach, we acknowledge that measuring similarity in a global search space may not effectively capture local similarity characteristics. Therefore, we propose a novel method for transfer learning optimization that operates within a local space (LSTL-PBO). This method employs partial data acquired through random sampling from the target task data and utilizes Bayesian optimization techniques for model establishment. By focusing on a local search space, we aim to better discern and leverage the inherent similarities between source tasks and the target task. Additionally, we incorporate a parallel concept into our method to address multiple local search spaces simultaneously. By doing so, we can explore different regions of the parameter space in parallel, thereby increasing the chances of finding optimal process parameters. This localized approach allows us to improve the precision and effectiveness of our optimization process. The performance of our method is validated through experiments on benchmark problems, and we discuss the sensitivity of its hyperparameters. The results show that our proposed method can significantly improve the efficiency of process parameter optimization, reduce the dependence on source tasks, and enhance the method's robustness. This has great potential for optimizing processes in industrial environments.

A hybrid method for the intelligent effectiveness management of production operators

AbstractThe paper presents a hybrid method for the effective management of human resources when executing production processes. The method was proposed for managing production operators in systems of relatively high complexity—with the possibility of multiple alternative ways of designating operators to production stations. The method combines a novel approach of assessing the effectiveness of production operators, the use of an intelligent algorithm and the risk assessment method. The concept of effectiveness was used in the sense of a praxeological approach. Availability, performance and quality were defined as its components, and were evaluated through the prism of losses occurring in production processes. The aim of the study is to develop a hybrid method in order to delegate production operators to tasks, not only on the basis of a competence metric, but also on the basis of an individual effectiveness indicator and the risk assessment of production process stages. For this purpose, a novel method of assessing the effectiveness of the use of available resources when implementing production processes (based on a set of quantitative indicators and taking into account the categorization of production losses) was juxtaposed using the Tabu Search algorithm and the FMEA method. The method enables a near-optimal solution to be generated—one in which operators are assigned to production tasks in the most effective way possible, which in turn minimizes both the risk of production delays and quality defects due to operator fault.

Salient semantics

Semantic features are components of concepts. In philosophy, there is a predominant focus on those features that are necessary (and jointly sufficient) for the application of a concept. Consequently, the method of cases has been the paradigm tool among philosophers, including experimental philosophers. However, whether a feature is salient is often far more important for cognitive processes like memory, categorization, recognition and even decision-making than whether it is necessary. The primary objective of this paper is to emphasize the significance of researching salient features of concepts. I thereby advocate the use of semantic feature production tasks, which not only enable researchers to determine whether a feature is salient, but also provide a complementary method for studying ordinary language use. I will discuss empirical data on three concepts, conspiracy theory, female/male professor, and life, to illustrate that semantic feature production tasks can help philosophers (a) identify those salient features that play a central role in our reasoning about and with concepts, (b) examine socially relevant stereotypes, and (c) investigate the structure of concepts.

Exploring the Relationship Between Working Memory Capacity and L2 Oral Fluency

This study investigated the relationship between working memory capacity (WMC) and L2 oral fluency and explored the maintenance of newly presented information in L2 speaking production. When performing speech production tasks, knowledge from long-term memory is at frequent use and hence involves the operation of the episodic buffer, one component of the working memory system, where information is retrieved from long-term memory and stored in chunks as we speak in chunks. In this study, we measured WMC by assessing chunk capacity and chunk size held in and retrieved from the episodic buffer. Chunk capacity was measured by Pair-word Speaking Task; chunk size was measured by Procedure Description Task; and oral fluency was measured by speech rate and mean length of run using an IELTS speaking task. Twenty-nine English-major students participated in this study. The results showed a strong positive correlation between chunk capacity and the two measures of fluency while chunk size negatively correlated with fluency. Data from the recall interviews revealed that participants employed various strategies for the maintenance of the presented information which involved different types of information binding.

Cartoons Influence on Primary School Pupils Towards Violence and Aggression in Niger State

Screen plays, including cartoons, are a crucial part of children's lives, helping to satisfy their energy and keep them engaged both at home and in school. Research has found that aggression and violence are prevalent among primary school pupils, and scholars have called for further investigation into the possible causes of this issue. Biological and personal factors such as family dynamics, fear of abandonment, punishment, sexual assault, and domestic violence have been studied extensively. However, little research has been conducted on the impact of entertainment media, specifically cartoons, on primary school students' aggression and violence. This study aims to fill this gap by examining the influence of cartoons on the attitudes of children towards violence and aggression of primary school pupils in Niger state. The study adopted a descriptive survey design. Purposive sampling technique was adopted in selecting 120 primary school pupils from 12 schools across the three senatorial zones in Niger state. Four research questions were answered and questionnaire was used as instrument for data collection. The quantitative data were analyzed using descriptive statistics and T-test at 0.05 level of significance. The results showed that cartoon had a positive influence on primary school pupils (x ̅ =1.44 on a threshold of 1.50). Also, it was discovered that cartoons affects pupils’ time to focus on productive tasks (x ̅ =1.62 on a threshold of 1.50), among others. The result of the difference between pupils’ reaction to cartoons based on gender showed that there was a significant difference (t = -3.28; df = 248; p&lt;0.05). Also, the result of the difference between the reactions of pupils to cartoon among public and private schools pupils indicated that there was a significant difference (t = 2.70; df = 248; p&lt;0.05). Following these findings, recommendations are made for parents to pay greater attention to presenting their children with carefully chosen cartoons that could have a positive impact on them. For the teachers, it was recommended that they should create a classroom environment that is less conducive to aggressive or violent behaviour so as to curb whatsoever the pupils might have learnt in their respective homes. Pupils are advised to be aware of their attitudes towards aggression and violence and take steps to stop such behaviour among themselves and their peers. Recommendations are made for curriculum planners to incorporate media literacy and social-emotional learning into the curriculum. Policy makers are advised to develop guidelines for media content, invest in research, and provide funding as these would aid in promoting positive attitudes towards aggression and violence among cartoon viewing pupils.

Framework design of distributed P2P2G energy transaction considering photovoltaic power and dispatch of manufacturing facilities

In this paper, a distributed peer-to-peer-to-grid (P2P2G) energy transaction framework considering photovoltaic generation and dispatch of manufacturing facilities is designed to increase the penetration of renewable energy resource. The factory with typical manufacturing assembly production task, photovoltaic panels and battery is regarded as a micro-grid (MG) to participate in the energy transaction market. The designed framework contains two levels. In the upper level, each MG determines the scheduling of manufacturing facilities and battery and the quantities of P2P2G energy transactions based on the given P2P energy transaction price and distribution locational marginal price (DLMP), in which the complex typical manufacturing assembly process is formulated as a kind of deferable load and the DLMP is updated according to the optimal power flow (OPF) of the network. In the lower level, peer-to-peer (P2P) energy transaction prices are updated by non-cooperative games and the homologous Rosen-Nash equilibrium points are obtained by using Nikaido-Isoda relaxation and alternating direction method of multipliers (ADMM) algorithm. The efficacy of the designed framework is demonstrated by a case study, and the results indicate the designed framework can improve the utilisation rate of renewable energy.

Two aspects of feed-forward control of action stability: effects of action speed and unexpected events.

We explored two types of anticipatory synergy adjustments (ASA) during accurate four-finger total force production task. The first type is a change in the index of force-stabilizing synergy during a steady state when a person is expecting a signal to produce a quick force change, which is seen even when the signal does not come (steady-state ASA). The other type is the drop in in the synergy index prior to a planned force change starting at a known time (transient ASA). The subjects performed a task of steady force production at 10% of maximal voluntary contraction (MVC) followed by a ramp to 20% MVC over 1s, 3s, and as a step function (0s). In another task, in 50% of the trials during the steady-state phase, an unexpected signal could come requiring a quick force pulse to 20% MVC (0-surprise). Inter-trial variance in the finger force space was used to quantify the index of force-stabilizing synergy within the uncontrolled manifold hypothesis. We observed significantly lower synergy index values during the steady state in the 0-ramp trials compared to the 1-ramp and 3-ramp trials. There was also larger transient ASA during the 0-ramp trials. In the 0-surprise condition, the synergy index was significantly higher compared to the 0-ramp condition whereas the transient ASA was significantly larger. The finding of transient ASA scaling is of importance for clinical studies, which commonly involve populations with slower actions, which can by itself be associated with smaller ASAs. The participants varied the sharing pattern of total force across the fingers more in the task with "surprises". This was coupled to more attention to precision of performance, i.e., inter-trial deviations from the target as reflected in smaller variance affecting total force, possibly reflecting higher concentration on the task, which the participants perceived as more challenging compared to a similar task without surprise targets.

Effects of home-based EEG neurofeedback training as a non-pharmacological intervention for Parkinson's disease

ObjectivesAberrant movement-related cortical activity has been linked to impaired motor function in Parkinson's disease (PD). Dopaminergic drug treatment can restore these, but dosages and long-term treatment are limited by adverse side-effects. Effective non-pharmacological treatments could help reduce reliance on drugs. This experiment reports the first study of home-based electroencephalographic (EEG) neurofeedback training as a non-pharmacological candidate treatment for PD. Our primary aim was to test the feasibility of our EEG neurofeedback intervention in a home setting. MethodsSixteen people with PD received six home visits comprising symptomology self-reports, a standardised motor assessment, and a precision handgrip force production task while EEG was recorded (visits 1, 2 and 6); and 3 × 1-hr EEG neurofeedback training sessions to supress the EEG mu rhythm before initiating handgrip movements (visits 3 to 5). ResultsParticipants successfully learned to self-regulate mu activity, and this appeared to expedite the initiation of precision movements (i.e., time to reach target handgrip force off-medication pre-intervention = 628 ms, off-medication post-intervention = 564 ms). There was no evidence of wider symptomology reduction (e.g., Movement Disorder Society Unified Parkinson's Disease Rating Scale Part III Motor Examination, off-medication pre-intervention = 29.00, off-medication post intervention = 30.07). Interviews indicated that the intervention was well-received. ConclusionBased on the significant effect of neurofeedback on movement-related cortical activity, positive qualitative reports from participants, and a suggestive benefit to movement initiation, we conclude that home-based neurofeedback for people with PD is a feasible and promising non-pharmacological treatment that warrants further research.

Positioning accuracy improvement for target point tracking of robots based on Extended Kalman Filter with an optical tracking system

Although industrial robots have been successfully used in a wide spectrum of applications for production automation, they still face challenges for many high precision tasks especially in low-volume high-mix production due to their low absolute positioning accuracy. To respond to such rapidly changing production tasks, an efficient means is required to determine the pose relationship between the robot and the workpiece without human intervention such as teaching the robot. For this purpose, the paper proposes the use of the Extended Kalman Filter (EKF) with an optical tracking system to improve the robot positioning accuracy with a particular focus on the target point tracking of the end-of-arm tool, which is an essential part for many robotic tasks. To this end, a comprehensive kinematic error model is first derived for the end-of-arm tool that accounts for the errors in the Denavit-Hartenberg (D-H) parameters, the positioning errors of the robot base and the end-of-arm tool installation. Then, by using the optical tracking system, the pose of the end-of-arm tool relative to the workpiece can be determined in an efficient way. Based on the EKF algorithm, the kinematic parameter errors of the system can be estimated online to compensate the positioning error of the target point during the robot movement. Simulation and experimental tests have been performed to demonstrate the effectiveness of the proposed method. The proposed approach utilizes the given trajectory to design a compensation scheme where the kinematic parameter errors of the robot are estimated during the motion and then the positioning error of the end-of-arm tool is compensated at the target point. As a result, this approach can improve the target point accuracy of the robot without continuous feedback to reduce the tracking error along the trajectory in real time. It is easy to implement and suitable for low-volume, high-mix scenarios to determine the pose relationship between the robot and the workpiece without human intervention.

A Learners’ Dictionary Versus ChatGPT in Receptive and Productive Lexical Tasks

Abstract This study assesses the effectiveness of ChatGPT versus the Longman Dictionary of Contemporary English (LDOCE) in supporting English language learners in lexically challenging receptive and productive lexical tasks. With a sample of 223 university students at B2 to C1 proficiency levels, this research investigates whether a leading AI-driven chatbot or a high-quality learners’ dictionary better assists learners in accurately understanding and producing English. The results reveal ChatGPT’s superior performance in both task types. Efficiency, in terms of consultation speed, also favoured ChatGPT, though only in the production task. This study advocates for an integrated approach that leverages both AI, with its interactive and immediate feedback, and more traditional lexicographic tools that may foster learner autonomy and linguistic proficiency.

Students’ stance towards translanguaging in an EFL oral productive assessment task

ABSTRACT Albeit the growing plurilingual research due to the new sociolinguistic realities in education and a reaction to the dominant monolingual bias, few studies have focused on plurilingual assessment and students’ ideologies towards using their plurilingual competence and resources such as translanguaging. A total sample of 36 undergraduates who completed a five-month EMI or ESP course in Catalonia, Spain, participated in our study. We examined their stance-taking discourse on a speaking assessment task in which they could draw upon all their communicative resources if they felt that it would increase the efficiency and effectiveness of their message. Findings suggested that, rather than two clear extreme positions, there is a continuum of positions in favour and against the legitimacy of using their whole plurilingual repertoire. Moreover, our results also showed the dominance of a deeply-ingrained monolingual mindset among the learners which leads them to implicitly or explicitly resist the possibility of translanguaging.

An experimental study of classical truth logic on multi-propositions consistent and incompatible: Dual-process theories and modal syllogistic of deduction.

This study looked at a classical truth logic of multi-propositions that is new in some ways: [1] Alethic modalities were mixed with logical consistency and incompatibility in a single plate form, i.e., necessary consistency (NC), possible consistency (PC)/ possible incompatibility (PI) and impossible incompatibility (IPI); [2] multi-propositions were judged by individuals as either NC, PC/PI, or IPI; [3] Four quantifiers; All (∀), No (∼∀), Some (∃), and Some Not (∼∃) of four propositional modes and three shapes ([Formula: see text], ▱ and [Formula: see text]) are used to evaluate predictions; and [4] it inspired by multi-propositional of dual-process theories (DPTs) of deduction and modal syllogistic of multi-propositions, from which logicians have derived general hypotheses. HP 1- Individuals will more likely to endorse inferences as PC/PI rather than NC. HP 2: It's easier to calculate that inference has PC/ PI if it has also NC. Generally, logicians predict more endorsing PC for NC than for PI proposition. HP 3: It's easier to calculate that inference is not NC if it is also not PC. Generally, logicians predict more PI than IPI proposition endorses as NC. A modal syllogistic as a classical truth logic is presented by multi-propositions (two premises and one inference), each one from four modes has quantifiers such as universal quantifiers and existential quantifier; ∀, ∼∀, ∃, and ∼ ∃. They were evaluated by a single-mental model (Experiment I) and a multi-mental model (Experiment II). Logicians applied the immediate inference task (IIT), evaluation task (ET), and production task (PT) to evaluate three experiments. The results of the experiments suggested that students mostly endorsed PC/PI inferences over NC inferences. Even when logicians divided PC/PI separately as PC and PI, individuals endorsed PC most likely as compared to NC, and PI than IPI. Logicians also highlighted fallacies that were continuously resisted and endorsed when students were asked to judge multi-propositions that had NC. The purpose of this experimental study is to present a glimpse of students' endorsement of multi-propositions and explain that each individual has a different working memory and intelligence.

Effect of Music on Working Memory of Female Operators Working in a Medical Infusion Set Assembly Company

Abstract Aim: With the increasing presence of individuals, particularly women, in the workplace, it becomes imperative to prioritize the well-being of employees. Numerous interventions exist to enhance working conditions, and one such intervention is the incorporation of music. This research aims to investigate the correlation between music exposure and the working memory of female operators employed in a medical infusion set assembly company. Methods: The study involved the assessment of 81 employees from the assembly unit of a company specializing in the production of infusion sets. The current research is an interventional study, the data of which were collected by the method of interview and cognitive tests (N-back test). The evaluation was conducted under two conditions: with background music and without background music. The research focused on assessing the working memory and productivity (task performance) of the participants. Results: The mean age of the participants in this study was 37 ± 33.09 years, with a mean work history of 0.2 ± 1.3 years. Furthermore, 56.7% of the participants were married. The results of the study showed that productivity was significantly better in the music-playing mode (P = 0.005). Furthermore, the results of the N-back test significantly showed an increase in correct answers in the condition of playing music (P &lt; 0.05). Conclusions: The integration of background music in the workplace emerges as a beneficial factor, contributing to enhanced working memory and improved performance among female employees.

Are brain activity changes underlying rare word production after learning specific or do they extend to semantically related rare words?

Learning words in the mother tongue is a fundamental lifelong skill that involves complex cognitive and neural changes. In adults, newly learned words affect the organization of the lexical–semantic network and, compared to words that have been in the lexicon for longer, they activate the same cortical areas, but more extensively and/or intensively. It is however still unclear (1) which brain and cognitive processes underlying word production change when infrequent/unknown words are compared before and after learning and (2) whether integrating newly learned words impacts word specific processes or has a broader impact on unlearned words. The present study aims to investigate the electrophysiological changes underlying the production of rare words induced by learning and the effect of learning on an unlearned list of rare words belonging to the same semantic categories.To this end, 24 neurotypical adults learned one of two matched lists of 40 concrete rare words from 4 semantic categories. EEG (electroencephalographic) recordings were acquired during a referential word production task (picture naming) of the learned and unlearned words before and after the learning phase.The results show that the production of rare word is associated with event-related (ERP) differences between before and after learning in the period from 300 to 800 msec following the presentation of the imaged concept (picture). These differences consisted in a larger involvement of left temporal and parietal regions after learning between 300 and 400 msec i.e., the time window likely corresponding to lexical and phonological encoding processes. Crucially, the ERP changes are not restricted to the production of the learned rare words, but are also observed when participants try to retrieve words of a list of semantically and lexically matched rare words that they have not learned.The ERP changes on unlearned rare words are weaker and suggest that learning new words induces boarder effects also on unlearned words.

The Solo Broadcast Journalism Practices from an Industry Perspective

Social networking is a rapidly growing source of news in broadcast journalism. Broadcast journalism is facing a continuing decline in electronic media circulation and social media changes. The concept of online convergence in broadcast journalism has become a news trend on social media. Solo broadcast journalism and social media are becoming practices in news organisations today. Therefore, this article aims to identify the practices of solo broadcast journalism from an industry practitioner’s perspective. A qualitative methodological approach was used in this study. Face-to-face interviews were conducted with eight informants who practised solo broadcast journalism. The data were analysed thematically. The results showed that production tasks, location reviews, good time management, relationships with the community, preparation tasks, and comfortable places are among the concepts of practising solo broadcast journalism in news organisations. The findings of this study show that journalists practice solo broadcast journalism to get news in line with the development of digital media today. The findings of this study are expected to benefit the National ICT Agenda on National Broadband Policy from the perspective of newspaper organisations in expanding the use of technology in the distribution and publication of stories for news. The findings of this study will help make appropriate adjustments to develop human capital by integrating broadcast journalism practices with technology-assisted work in solo broadcast journalism. In addition, this study is also significant to the National Education Policy. The study will impact the educational curriculum of broadcast journalism by introducing changes in line with the development of solo broadcast journalism. Keywords: Practice, solo broadcast journalism, industry practitioner, Industrial Revolution 4.0, social media.

The Relationship between Story Comprehension, Story Grammar Production, and Executive Function in Preschool-Age Korean-English Bilingual Children with and without Vocabulary Delay

Objectives: This study investigated the relationship between story comprehension and story grammar abilities, as well as executive function in preschool Korean-English bilingual children with vocabulary delay (VD) compared to typically developing (TD) children and examined predictors of their narrative abilities. Methods: A total of 30 children (13 children with VD, 17 TD children) aged from 4-6 years participated in the study. Children performed non-word repetition (NWR) and word list recall for verbal working memory, matrix for non-verbal working memory, fruit stroop for inhibition, and Dimensional Change Card Sort (DCCS) for shifting. They also performed story comprehension and story grammar production tasks in both languages to assess their narrative abilities. For data analyses, one-way ANOVA, Pearson correlation, and stepwise multiple regression were conducted. Results: The VD group showed significantly lower performance in working memory, inhibition, shifting tasks. Moreover, VD group had significantly lower performance in story comprehension and story grammar production tasks in both languages. In the TD group, Korean story comprehension performance was correlated with English story comprehension, Korean story grammar production, English story grammar production performances. On the other hand, in the VD group, only Korean story comprehension showed a significant correlation with Korean story grammar production performance. Lastly, matrix significantly predicted English story comprehension abilities and word list recall significantly predicted Korean story grammar production abilities in the TD group. Conclusion: By examining the relationship between children’s ability to understand stories, produce story grammar and sub-factors of executive function, we can improve the narrative education and intervention for bilingual children’s literacy and academic achievement in the future.