Interactive Feedback Research Articles

The effects of interactive electronic picture books on young children’s oral expression skills

The application of interactive electronic picture books can strengthen young children’s reading comprehension skills. Interactive electronic picture books that involve interaction with sensors, with the interaction integrated into the story, should be developed to enhance children’s reading experience and improve their oral expression skills. Interactive electronic picture books that involved children manipulating stuffed animals containing sensors that provided feedback were developed for this study. Visual, auditory, and tactile stimuli can be used to create an interactive feedback system. Data was collected through semi-structured interviews with teachers, who gave their opinions regarding the curriculum of their preschool. The results indicate that the intuitiveness of the system helped improve the children’s reading experience, strengthened their motivation to read, and improved their cognitive abilities. In addition, interactive electronic picture books were found to improve the children’s oral expression skills.

Show-and-Tell: An Interface for Delivering Rich Feedback upon Creative Media Artefacts

In this paper, we explore an approach to feedback which could allow those learning creative digital media practices in remote and asynchronous environments to receive rich, multi-modal, and interactive feedback upon their creative artefacts. We propose the show-and-tell feedback interface which couples graphical user interface changes (the show) to a text-based explanations (the tell). We describe the rationale behind the design and offer a tentative set of design criteria. We report the implementation and deployment into a real-world educational setting using a prototype interface developed to allow either traditional text-only feedback or our proposed show-and tell feedback across four sessions. The prototype was used to provide formative feedback upon music students’ coursework resulting in a total of 103 pieces of feedback. Thematic analysis was used to analyse the data obtained through interviews and focus groups with both educators and students (i.e., feedback givers and receivers). Recipients considered show-and-tell feedback to possess greater clarity and detail in comparison with the single modality text-only feedback they are used to receiving. We also report interesting emergent issues around control and artistic vision, and we discuss how these issues could be mitigated in future iterations of the interface.

TrafficGPT: Viewing, processing and interacting with traffic foundation models

With the promotion of ChatGPT to the public, Large language models indeed showcase remarkable common sense, reasoning, and planning skills, frequently providing insightful guidance. These capabilities hold significant promise for their application in urban traffic management and control. However, large language models (LLMs) struggle with addressing traffic issues, especially processing numerical data and interacting with simulations, limiting their potential in solving traffic-related challenges. In parallel, specialized traffic foundation models exist but are typically designed for specific tasks with limited input-output interactions. Combining these models with LLMs presents an opportunity to enhance their capacity for tackling complex traffic-related problems and providing insightful suggestions. To bridge this gap, we present TrafficGPT—a fusion of multiple LLMs and traffic foundation models. This integration yields the following key enhancements: 1) empowering LLMs with the capacity to view, analyze, process traffic data, and provide insightful decision support for urban transportation system management; 2) facilitating the intelligent deconstruction of broad and complex tasks and sequential utilization of traffic foundation models for their gradual completion; 3) aiding human decision-making in traffic control through natural language dialogues; and 4) enabling interactive feedback and solicitation of revised outcomes. By seamlessly intertwining large language model and traffic expertise, TrafficGPT not only advances traffic management but also offers a novel approach to leveraging AI capabilities in this domain. The TrafficGPT demo can be found in https://github.com/lijlansg/TrafficGPT.git.

Research on the Performance Management of Carbon Reduction by Local Governments from a Game Perspective—The Case of the Zhejiang Power Restriction Incident

The implementation of low-carbon development and carbon reduction has become an issue of general concern. When local governments adopt carbon reduction measures, they inevitably have a negative impact on the economic development of enterprises and the daily lives of residents. However, the resolution of conflicts of interest between local governments, enterprises, and residents will have a direct impact on the motivation and effectiveness of local governments in implementing carbon reduction measures. This study takes China as an example, conducts a case review of the actual situation of the Zhejiang power restriction incident, and studies and constructs a tripartite evolutionary game model based on the local government, enterprises, and residents. By exploring the factors that influence the behavioral strategies of each stakeholder, this study finds the equilibrium conditions that the tripartite governance target model must satisfy. It is suggested that interactive feedback from enterprises and residents should be incorporated into the performance management of local governments and that performance assessment should be used to establish an effective responsibility and pressure transmission mechanism to help the government’s internal control to better implement carbon reduction policies.

Soil microbial community contributes more to plant-soil feedback and plant-plant interactions than root traits under warming and drought

Soil microbial community contributes more to plant-soil feedback and plant-plant interactions than root traits under warming and drought

Modulating metal-carrier interaction of high-loading Co-Al2O3-SiO2 catalysts for boosted N-propylcarbazole hydrogenation

We developed a series of high-loading Co-Al2O3-SiO2 catalysts to enhance the hydrogenation of N-propylcarbazole (NPCZ) by fine-tuning the Al/Si ratio. Our research reveals that adjusting this ratio can significantly modify the electronic structure of Co nanoparticles, as confirmed by XPS, H2-TPD, and CO-DRIFT analyses, thereby affecting the adsorption of hydrogen species and their interaction with unsaturated π-bonds of NPCZ intermediates. Optimal Al concentration promotes Co nanoparticles dispersion, while excessive Al leads to increased acidity and reduced surface area. The Co70/Al4Si1O catalyst, with an Al/Si ratio of 4, demonstrated superior hydrogenation efficiency by enabling fast and stable hydrogenation of NPCZ, achieving an activation energy of 64.53 kJ/mol and maintaining high performance over 10 cycles. Through DFT calculations, we explored the d-band center and Bader charge across 6 different Co10/Al-Si-O models and assessed the adsorption energies of NPCZ intermediates, along with the energetics of three stepwise reactions. The initial hydrogenation step from NPCZ to 4H-NPCZ is predominantly influenced by the catalyst's acidity/basicity, whereas the subsequent deeper hydrogenation steps of 4H-NPCZ and 8H-NPCZ are governed by the d-π feedback interaction between the metal and the adsorbate. This research offers critical guidance on selecting optimal supports for Co-based catalysts in LOHC hydrogenation.

Analysis on metabolic functions of rhizosphere microbial communities of Pinus massoniana provenances with different carbon storage by Biolog Eco microplates.

Rhizosphere microorganisms are influenced by vegetation. Meanwhile, they respond to vegetation through their own changes, developing an interactive feedback system between microorganisms and vegetation. However, it is still unclear whether the functional diversity of rhizosphere soil microorganisms varies with different carbon storage levels and what factors affect the functional diversity of rhizosphere soil microorganisms. In this study, the Biolog-Eco microplate technique was used to analyze the metabolic diversity of carbon source of rhizosphere soil microorganisms from 6 Pinus massoniana provenances with three levels of high, medium and low carbon storage. The results showed that the average well color development(AWCD) value of rhizosphere microorganisms was significantly positive correlated with carbon storage level of Pinus massoniana (p < 0.05). The AWCD value, Simpson and Shannon diversity of high carbon sequestrance provenances were 1.40 (144h incubation) 0.96 and 3.24, respectively, which were significantly higher (p < 0.05) than those of other P. massoniana provenances. The rhizosphere microbial AWCD, Shannon and Simpson diversity of the 6 provenances showed the same variation trend (SM>AY>QJ>SX>HF>SW). Similarly, microbial biomass carbon (MBC) content was positively correlated with carbon storage level, and there were significant differences among high, medium and low carbon storage provenances. The PCA results showed that the differences in the carbon source metabolism of rhizosphere microorganisms were mainly reflected in the utilization of amino acids, carboxylic acids and carbohydrates. Pearson correlation analysis showed that soil organic carbon (SOC), total nitrogen (TN) and pH were significantly correlated with rhizosphere AWCD (p < 0.05). Soil properties are important factors affecting rhizosphere microbial carbon source metabolism. The study confirmed that the microorganisms of high carbon storage provenances had relatively high carbon metabolic activity. Among them, the carbon metabolic activity of rhizosphere microorganisms of SM provenance was the highest, which was the preferred provenances in effective ecological service function.

Enhancing Students' Preparation for Math Exams using the Advanced Features of the Halomda Platform

This paper highlights the new enhancements of the Halomda platform designed to improve students' learning and exam preparation. The new features include a Graph Plotter, Algebraic Calculator and Context ChatGPT Recommended Key Guidelines. The use of these features is demonstrated though a working example of solving a double integral, illustrating how students' self-preparation for mathematics exams is supported by interactive context feedback. In addition, the system's ability to check intermediate steps of a solution, complemented by graphing, comparison of algebraic equivalence of algebraic operations, and guided AI bot assistance, contributes to an enriched learning experience and improved self-assessment for students. In case of insufficient understanding of the solution, the AI chat can be consulted for further clarification. Since the solution in the "Help" mode is developed by the teacher who prepared the test paper, in case of misunderstanding, the student can turn to external sources, and the fastest way is the AI chat.

Frequency-locked measurement of floating potential fluctuations in cold micro-plasma jets: Interactive surface feedback effects on reactive species generation

Frequency-locked measurements of floating potential fluctuations are carried out in a cold atmospheric pressure micro-plasma jet interacting with substrates of varying electrical permittivity (εr). The range of fluctuation frequencies (∼ 0.5–9 kHz) is compared with that determined from the time series of floating potential fluctuations and its fast Fourier transform. Results of these independent methods to determine the fluctuation frequencies are found to agree reasonably well, thereby affirming their existence in the micro-plasma jet. Substrate feedback effects dictated by εr are found to influence the amplitude of fluctuations and threshold breakdown voltage. The spectral emission line intensity corresponding to the reactive oxygen and nitrogen species, which is critical for biomedical applications, decrease drastically in the presence of stronger levels of fluctuations, indicating a bearing on their generation.

Exploring and counteracting stage specific course completion risk factors in open higher education distance learning

Abstract A major challenge for distance learning in higher education is supporting course completion. Counteracting completion risk factors requires investigating their significance across (non)completion stages. We tested the predictability of known risk factors at each completion stage. Not initiating was explained by available time, low motivation and completion methods. Abandonment was predicted by life situation and inappropriate completion methods. Failed submissions were explained by difficulty level and material availability. At early stages, supporting motivation by designing suitable course completion methods seems the most effective risk countermeasure. At later stages, academic skills protect from non-completion. Intrinsic motivation requires experiencing competence, autonomy and relatedness. Flexible distance learning methods with constructive, informational feedback and social interaction in the instructional design might best support course completion.

A novel method for measuring interaction among multiple objectives in reservoir operation using niche theory

Accurate capture and presentation of the interactive feedback relationships among various objectives in multi-objective reservoir operation is essential for maximizing operational benefits. In this study, the niche theory of ecology was innovatively applied to the field of reservoir operation, and a novel state–relationship (S–R) measurement analysis method was developed for multi-objective reservoir operation. This method enables the study of interaction among multiple objectives. This method was used to investigate the relationship among the objectives of power generation, water supply, and ecological protection for cascade reservoir operation in the Wujiang River Basin in China. The results indicated that the ecological protection objective was the most competitive in acquiring and capturing resources like flow and water level, while the water supply objective was the weakest. Power generation competed most strongly with ecological protection and relatively weakly with water supply. These findings facilitate decision-making throughout the reservoir operation process in the region. The S–R method based on the niche theory is convenient, efficient, and intuitive, allowing for the quantification of feedback relationships among objectives without requiring the solution of the Pareto frontier of a multi-objective problem in advance. This method provides a novel and feasible idea for studying multi-objective interactions.

Annual Research Review: 'There, the dance is - at the still point of the turning world' - dynamic systems perspectives on coregulation and dysregulation during early development.

During development we transition from coregulation (where regulatory processes are shared between child and caregiver) to self-regulation. Most early coregulatory interactions aim to manage fluctuations in the infant's arousal and alertness; but over time, coregulatory processes become progressively elaborated to encompass other functions such as sociocommunicative development, attention and executive control. The fundamental aim of coregulation is to help maintain an optimal 'critical state' between hypo- and hyperactivity. Here, we present a dynamic framework for understanding child-caregiver coregulatory interactions in the context of psychopathology. Early coregulatory processes involve both passive entrainment, through which a child's state entrains to the caregiver's, and active contingent responsiveness, through which the caregiver changes their behaviour in response to behaviours from the child. Similar principles, of interactive but asymmetric contingency, drive joint attention and the maintenance of epistemic states as well as arousal/alertness, emotion regulation and sociocommunicative development. We describe three ways in which active child-caregiver regulation can develop atypically, in conditions such as Autism, ADHD, anxiety and depression. The most well-known of these is insufficient contingent responsiveness, leading to reduced synchrony, which has been shown across a range of modalities in different disorders, and which is the target of most current interventions. We also present evidence that excessive contingent responsiveness and excessive synchrony can develop in some circumstances. And we show that positive feedback interactions can develop, which are contingent but mutually amplificatory child-caregiver interactions that drive the child further from their critical state. We discuss implications of these findings for future intervention research, and directions for future work.

From Digital Human Modeling to Human Digital Twin: Framework and Perspectives in Human Factors

The human digital twin (HDT) emerges as a promising human-centric technology in Industry 5.0, but challenges remain in human modeling and simulation. Digital human modeling (DHM) provides solutions for modeling and simulating human physical and cognitive aspects to support ergonomic analysis. However, it has limitations in real-time data usage, personalized services, and timely interaction. The emerging HDT concept offers new possibilities by integrating multi-source data and artificial intelligence for continuous monitoring and assessment. Hence, this paper reviews the evolution from DHM to HDT and proposes a unified HDT framework from a human factors perspective. The framework comprises the physical twin, the virtual twin, and the linkage between these two. The virtual twin integrates human modeling and AI engines to enable model-data-hybrid-enabled simulation. HDT can potentially upgrade traditional ergonomic methods to intelligent services through real-time analysis, timely feedback, and bidirectional interactions. Finally, the future perspectives of HDT for industrial applications as well as technical and social challenges are discussed. In general, this study outlines a human factors perspective on HDT for the first time, which is useful for cross-disciplinary research and human factors innovation to enhance the development of HDT in industry.

HIFINet: Examination-Diagnosis-Treatment Hierarchical Feedback Interaction Network for Medication Recommendation

Medication combination recommendation is critical in clinic, since accurately predicting therapeutic drug can provide essential decision support to physicians. However, current approaches do not consider the multilevel structure of electronic health record (EHR) data or the hierarchical dependencies between multiple visits, leading to suboptimal recommendations. To address these limitations, we propose a novel hierarchical feedback interaction network (HIFINet) to utilize an examination-diagnosis-treatment hierarchical network for modeling the inherent multilevel structure of EHR data. The feedback long short-term memory network called FeLSTM, which is the basic unit of our hierarchical network, performs hierarchical interactions and leverages change information as feedback to propagate forward among different levels. Additionally, HIFINet contains four modules. First, an embedding module is designed to learn the health information representation of patients. Second, a three-layer time-series learning module is employed to capture temporal dependencies within each sequence. Next, a differential feedback interaction module is developed to capture the difference features between visits. Finally, an attention fusion module is used to learn a comprehensive representation of the patient’s health information and to recommend next multiple treatment medications. HIFINet is compared with state-of-the-art approaches on a real-world dataset. The results indicate that HIFINet outperforms other approaches, offering more accurate recommendations.

Multilingual interventions in feedback: communication strategy in teacher professional development training

ABSTRACT In Indonesia, most recent studies about teacher professional development have commonly focused on the programme’s employment, effectiveness, problems, and the skills teachers gained due to the programme. Little focus has been placed on the consistent investigations of how multilingual interventions take place in feedback-giving practices, notably in teacher professional development training. Through a case study, we sought to establish a sociocultural framework for examining what instructors learn from the uncertified teachers’ exchanges in delivering spoken feedback and how this influences instructors’ approach to multilingual interventions. All language use during encounters, reflections, and interview responses were recorded. Uncertified instructors valued bilingual feedback for meaning-making interactions, which improved their comprehension and provided a model for multilingual interventions in feedback-giving practices. The research sheds new light on how instructional practitioners and teachers can effectively offer feedback for highly valuable interactions and knowledge.

Quantifying Landscape-Flux via Single-Cell Transcriptomics Uncovers the Underlying Mechanism of Cell Cycle.

Recent developments in single-cell sequencing technology enable the acquisition of entire transcriptome data. Understanding the underlying mechanism and identifying the driving force of transcriptional regulation governing cell function directly from these data remains challenging. This study reconstructs a continuous vector field of the cell cycle based on discrete single-cell RNA velocity to quantify the single-cell global nonequilibrium dynamic landscape-flux. It reveals that large fluctuations disrupt the global landscape and genetic perturbations alter landscape-flux, thus identifying key genes in maintaining cell cycle dynamics and predicting associated functional effects. Additionally, it quantifies the fundamental energy cost of the cell cycle initiation and unveils that sustaining the cell cycle requires curl flux and dissipation to maintain the oscillatory phase coherence. This study enables the inference of the cell cycle gene regulatory networks directly from the single-cell transcriptomic data, including the feedback mechanisms and interaction intensity. This provides a golden opportunity to experimentally verify the landscape-flux theory and also obtain its associated quantifications. It also offers a unique framework for combining the landscape-flux theory and single-cell high-through sequencing experiments for understanding the underlying mechanisms of the cell cycle and can be extended to other nonequilibrium biological processes, such as differentiation development and disease pathogenesis.

Testing a novel extended educational technology acceptance model using student attitudes towards virtual classrooms

AbstractMany technology acceptance models used in education were originally designed for general technologies and later adopted by education researchers. This study extends Davis' technology acceptance model to specifically evaluate educational technologies in higher education, focusing on virtual classrooms. Prior research informed the construction of the model, which contains perceived usefulness, perceived ease of use, behavioural intent, access and convenience, system attributes and self‐efficacy. Education‐specific constructs include cognitive engagement, feedback, instructor practice and class interaction and communication. Additionally, a new construct called comfort and well‐being is introduced. A total of 427 valid responses on a 5‐point Likert scale were received from university students. Exploratory factor analysis, confirmatory factor analysis and structural equation modelling were used to analyse the data. The model accounted for 78% of variance of behavioural intent, with comfort and well‐being demonstrating the strongest influence. Cognitive engagement, access and convenience influenced perceived usefulness, and system attributes and self‐efficacy influenced perceived ease of use. Feedback, instructor practice and class interaction and communication were not significant as educational constructs for this cohort. Based on this analysis, a final extended educational technology acceptance model (EETAM) is proposed for further use and testing.Practitioner notesWhat is already known about this topic Most technology acceptance models used in education were made for general technologies, or do not include factors specific to learning and pedagogy. Most students prefer face‐to‐face learning experiences and active class engagement. Qualitative research shows that instructional attributes and student comfort and well‐being are known to be important for students. What this paper adds A novel extended educational technology acceptance model, informed by prior empirical research, is presented. Confirmation of the importance of including student comfort and well‐being in technology acceptance models used in education. The model revealed the heterogeneous nature of the student learning experience. Implications for practice and research Technology acceptance models used in educational settings should include factors specific for education and learning, and student comfort and well‐being. We encourage use of the presented model in educational settings to further test the model.

Mediating Effect of Tourists’ Feedback Information on the Relationship between Interaction and Service Innovation in Tanzania

Studies on feedback information and interactions among tourists and tourism services are limited to residents, service providers, and mostly business-to-business. Little remains unknown about the relevance of tourists’ feedback information and interactions to service innovation. This study examined the mediating effect of tourist feedback information in the relationship between tourists’ interactions and service innovation. A survey of 290 Tanzanian tourism firms gathered the scale data that was analysed using Structural Equation Modelling in the Partial Least Square method. Tourist feedback information and tourists’ interactions were found to positively affect service innovation. While tourists’ interactions exhibited a strong positive effect on service innovation, there is a partial mediation of feedback information between the two. These results inform the service industry to capitalize on customer feedback information in enriching new service designs. As a result, practitioners in service firms are at a high point to set strategies to improve interactions as good practices in service innovation. Specifically, the tourism industry actors obtain insights into handling customers and benefiting from their actions and information. Theoretically, the study offers an understanding of interactions as applied in the service dominant logic such that apart from the exchange focus, feedback and interactions can also be considered as information sources for service innovation across firms. These results suggest that tourist interactions and feedback should be treated as key information points for enabling service innovation.

Abstract TP71: Creative Methods Utilized to Improve Stroke Education at an Academic Medical Center

Background: Stroke patients admitted to a hospital can be cared for in several different settings requiring hospital clinical staff to have a strong knowledge base of signs and symptoms of a stroke as well as the care and management of patients after a stroke. Stroke patients may present with other co-morbidities which may take precedence over their stroke diagnosis causing them to be admitted to non-stroke units. In addition, patients may also have an acute stroke during their hospitalization for a non-related admission. Therefore, hospital systems must continue to expose all staff to education regarding stroke recognition, care and management. Purpose: To increase the knowledge of stroke recognition, prevention, care, and treatment options of clinical staff at one academic medical center. Methods: Members of the stroke clinical team and unit nurse specialists provide educational opportunities through a mobile education program which brings interactive games to the unit staff to test and reinforce their stroke knowledge. They provide brain themed prizes and provide direct staff feedback on stroke codes that occurred on the unit. This team also provides in-person educational in-services to units where gaps in our data metrics have occurred. They are a resource that all clinical staff can reach out to for additional education on stroke management. Results: Feedback from the clinical staff after receiving education either from interactive games, in-services or direct feedback has been positive. We have seen increased confidence with our inpatient units nursing staff in activating the stroke code immediately as soon as signs and symptoms of stroke are observed. They also have a stronger understanding of the importance of meeting our time targets to improve patient outcomes. Conclusions: Making learning fun and rewarding staff for their understanding and impact on patient care creates an incentive to continue to learn more about stroke care, management, and improves their recognition of stroke among all patients. We continue to develop creative and alternative methods to provide education to the clinical staff throughout the health care system.

The dynamic influence of interactive feedback on elevating EFL students’ writing skills

This study investigates the effect of interactional feedback on students’ writing skills. One hundred participants enrolled in an intermediate EFL course at the State University of Malang, Indonesia, were recruited for this research. The quantitative method was employed for data analysis. The primary data analysis method used was the ANCOVA test, followed by the Wilcoxon and Mann-Whitney tests. The results reveal that the dependent variables in the experimental group exhibited higher means compared to the control group. The ANCOVA test show that the dependent variables (writing length, accuracy, and effectiveness) were significantly affected by the addition of feedback (p = 0.000). However, no significant differences were found between the experimental and control groups regarding accuracy (p = 0.425) and writing length variables (p = 0.731). As a result, interactional feedback significantly impacted EFL students’ writing ability. This result highlights the need for thorough planning and preparation, including preparing ESL/EFL students through explicit instruction prior to peer review, to ensure that learners’ interactional feedback is useful. The findings suggest that EFL teachers should carefully select feedback styles that align with the intended purpose of providing feedback. For instance, more specific feedback options may prove more effective in assisting students in revising and improving their written assignments. Finally, this study provides valuable recommendations for further research in this field.