Types Of Feedback Research Articles

Fusion of dual modalities of non-invasive sensory feedback for object profiling with prosthetic hands.

Either non-invasive somatotopic or substitute sensory feedback is capable of conveying a single modality of sensory information from prosthetic hands to amputees. However, the neurocognitive ability of amputees to integrate multi-modality sensory information for functional discrimination is unclear. The purpose of this study was to assess the fusion of non-invasive somatotopic tactile and substitute aperture feedbacks for profile perception of multiple physical features during grasping objects. Two left transradial amputees with somatotopic evoked tactile sensation (ETS) of five fingers participated in the study. The tactile information of prosthetic hand was provided to amputees by the ETS feedback elicited on the stump projected finger map. Hand aperture information was conveyed to amputees with substitute electrotactile stimulation on the forearm or upper arm. Two types of sensory feedback were integrated to a commercial prosthetic hand. The efficacy of somatotopic ETS feedback on object length identification task was assessed with or without substitute aperture stimulation. The object size identification task was utilized to assess how ETS stimulation at the stump may affect aperture perception with stimulation on the ipsilateral upper arm or forearm. Finally, the task of identifying combined length and size was conducted to evaluate the ability of amputees to integrate the dual modalities of sensory feedback for perceiving profile features. The study revealed that amputee subjects can effectively integrate the ETS feedback with electrotactile substitutive feedback for object profile discrimination. Specifically, ETS was robust to provide object length information with electrotactile stimulation at either the forearm or upper arm. However, electrotactile stimulation at the upper arm for aperture perception was less susceptible to the interference of ETS stimulation than at the forearm. Amputee subjects are able to combine somatotopic ETS and aperture feedbacks for identifying multi-dimensional features in object profiling. The two sensory streams of information can be fused effectively without mutual interference for functional discrimination.

A systematic review of coach augmented verbal feedback during practice and competition in team sports

Coaches use of augmented verbal feedback (AVF), often measured through systematic observation, is acknowledged as having a vital role in athlete learning. The purpose of this review was to identify coaches’ use of AVF, through systematic observation, in developmental and performance contexts. A literature search was conducted using EBSCO HOST and SCOPUS databases. Studies were reviewed using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Data were extracted from 31 studies which met the inclusion criteria. Analysis revealed three themes: (a) variation in observation tool and feedback types observed; (b) evidence base surrounding feedback types observed; (c) quality of coach feedback. The multiple feedback types measured across the studies suggests there is limited agreement on the types of feedback most important to measure. For the impact of feedback to be better understood, feedback types captured via systematic observation need revising in line with research that has identified the important characteristics of feedback. A greater evidence-informed approach to the observation of feedback may help to develop a greater understanding of the feedback process in learning and performance. Where there were consistencies in feedback type, the quality of AVF delivered by coaches could be questioned.

Digital game-based learning: Pedagogical agent and feedback types on achievement, flow experience, and cognitive load

Digital game-based learning: Pedagogical agent and feedback types on achievement, flow experience, and cognitive load

Electrical impedance tomography: a review on hardware systems and circuits

Abstract Electrical impedance tomography (EIT) is a widely used functional imaging technology in the field of biomedical engineering with the characteristics of non-radiation, high temporal resolution, real-time, miniaturization, and low cost, but with relatively poor spatial resolution, which makes it become an effective complementary imaging alternative in conjunction with structural imaging technologies such as MRI and CT for bedside monitoring. The hardware systems and circuits (HSC) are the physical basis for EIT, and have major impacts on imaging speed, accuracy, cost and other key performance specifications. This review attempts to provide researchers with a relatively comprehensive picture of HSC for different EIT systems, which is organized as follows. Firstly, the general EIT hardware systems are classified as serial, fully parallel and semi-parallel types, respectively, according to their hardware architecture. Secondly, the main analogy front-end circuits of EIT hardware systems are summarized, in which the current drive circuits are divided into open loop, linear closed-loop and nonlinear closed-loop based on different feedback types. Thirdly, the common error sources and evaluation indicators on EIT measurements are summarized. Finally, the future development trends and research challenges of EIT are discussed. This review is expected to promote the development of EIT technology, especially on the design of HSC.

The Efficacy of Recast vs. Explicit Corrective Feedback on Students’ English Pronunciation of Common Words: The Case of English Department Students at Ibn Tofail University

This study investigates the effectiveness of recast and explicit corrective feedback on students’ pronunciation improvement among first-year English university undergraduates at Ibn Tofail University, and compares these feedback types to determine the most effective one. A pilot study was conducted to give insights into the pronunciation difficulties faced by students. Based on this latter, the main study was done to address the aims of the investigation. A quasi-experiment was designed with 45 participants divided into three groups: Explicit, Recast and a Control group. The impact of recast and explicit corrective feedback was assessed through the Kruskal-Wallis Test, and the comparative assessment was done using Welch’s T-test. The results indicate that both recast and explicit corrective feedback positively influenced students’ pronunciation development. Yet, the explicit feedback appears superior and more effective than recast, demonstrating a high influence on students’ pronunciation errors. Hence, the investigation suggests that educators should be explicit enough to help students better develop their pronunciation.

ChatGPT's capabilities in providing feedback on undergraduate students’ argumentation: A case study

In argumentation teaching, providing timely and high-quality feedback is always a challenging task for teachers because of the high complexity and large volume of students’ argumentation contents. ChatGPT, a large language model introduced in November 2022, offers a potential solution for this problem. To examine the potential reliability and credibility of leveraging ChatGPT for argumentation feedback, the study conducted a retrospective analysis by applying ChatGPT to generate feedback on 50 sets of argumentation contents that human teachers had previously assessed. The study first assessed the feedback accuracy of ChatGPT and the factors that influenced the evaluation of arguments. The findings showed that ChatGPT demonstrated impressive precision rate (91.8 %) and recall rate (63.2 %) when providing feedback on arguments, indicating that ChatGPT possesses a fundamental capability to provide feedback on arguments. However, this capability of ChatGPT was significantly affected by the length of arguments and the discourse markers used in the arguments. The study then qualitatively compared the ChatGPT's feedback and teacher's feedback. The results revealed that these two types of feedback each had their own advantages and disadvantages. While ChatGPT could potentially generate comprehensive feedback and textual-based feedback, and limited to the linguistic level when provide affective feedback, teacher's feedback was more focused on student's overall learning progress, based on personal teaching experience to correctly identify immediate critical problem of the student, and consideration on the humanistic empathy interaction. Although the overall findings suggested that ChatGPT exhibited potential reliability and credibility for argumentation feedback, the study did identify several limitations.

Empathic pedagogical conversational agents: A systematic literature review

AbstractArtificial intelligence (AI) and natural language processing technologies have fuelled the growth of Pedagogical Conversational Agents (PCAs) with empathic conversational capabilities. However, no systematic literature review has explored the intersection between conversational agents, education and emotion. Therefore, this study aimed to outline the key aspects of designing, implementing and evaluating these agents. The data sources were empirical studies, including peer‐reviewed conference papers and journal articles, and the most recent publications, from the ACM Digital Library, IEEE Xplore, ProQuest, ScienceDirect, Scopus, SpringerLink, Taylor & Francis Online, Web of Science and Wiley Online Library. The remaining papers underwent a rigorous quality assessment. A filter study meeting the objective was based on keywords. Comparative analysis and synthesis of results were used to handle data and combine study outcomes. Out of 1162 search results, 13 studies were selected. The results indicate that agents promote dialogic learning, proficiency in knowledge domains, personalized feedback and empathic abilities as essential design principles. Most implementations employ a quantitative approach, and two variables are used for evaluation. Feedback types play a vital role in achieving positive results in learning performance and student perceptions. The main limitations and gaps are the time range for literature selection, the level of integration of the empathic field and the lack of a detailed development stage report. Moreover, future directions are the ethical implications of agents operating beyond scheduled learning times and the adoption of Responsible AI principles. In conclusion, this review provides a comprehensive framework of empathic PCAs, mostly in their evaluation. The systematic review registration number is osf.io/3xk6a.Practitioner notesWhat is already known about this topic Emotions play a pivotal role in shaping the interaction process, making it essential to consider them when designing methodological strategies or learning tools. Empathic Pedagogical Conversational Agents (PCAs) have emerged as a crucial approach for enhancing and personalizing the learning experience (24/7) for pupils and supporting human teachers in their teaching process. Despite the creation of numerous empathic PCAs, there is a scarcity of Systematic Literature Reviews (SLRs) on their application in the educational field, particularly concerning the integration of emotional abilities in combination with the competencies of each subject. What this paper adds It offers new insights into the design principles underlying the integration of the empathic field. It reviews different approaches for incorporating students' prior knowledge in real time. It provides a comprehensive and up‐to‐date overview of the research designs used for implementation, including quantitative, qualitative and mixed methods. It examines the factors that influence the effectiveness of empathic PCA in teaching and learning. It evaluates the types of feedback that enhance the impact of the empathic field on learning outcomes. Implications for practice and/or policy It is crucial to grasp the topics that this paper introduces in order to effectively integrate new learning tools into any context. Techno‐pedagogical designers seeking to gain insights into empathic PCAs will find immense value in this SLR, as it comprehensively covers each stage of the process. For future research endeavours, this study offers a wealth of ideas to draw upon, enabling researchers to address the challenges outlined and explore new avenues of investigation.

A Study on Teacher Feedback and AES Feedback in Chinese College students’ English Writings

Feedback holds significant importance in second language writing instruction, as evidenced by numerous studies indicating its direct or indirect impact on the quality of learners’ written work. Despite this recognition, there has been a dearth of comprehensive research concerning the distinct influences of teacher feedback and Automated Essay Scoring (AES) feedback on the writing quality of learners. Addressing this gap, the present study employs a mixed-method approach, integrating both qualitative and quantitative methodologies. By meticulously examining AES feedback, teacher feedback, writing revision logs, and conducting interviews, this investigation identifies noteworthy differentials in the multidimensional aspects of writing quality attributed to these two distinct feedback modalities. Primarily, within the realm of syntactic complexity, lexical richness, fluency, and accuracy, the cohort exposed to teacher feedback demonstrated notably superior performance relative to their AES feedback counterparts. Secondarily, an assessment of revised text quality revealed compelling insights. The ultimate version of the text, stemming from the AES feedback group’s iterative revisions, exhibited marked enhancements in terms of accuracy, total word count, and average word length. In contrast, the initial and final drafts of the teacher feedback group unveiled discernible disparities in vocabulary intricacy, accuracy, total word count, and average word length. Evidently, while the ultimate version did not witness a significant surge in average word length or total word count, it showcased heightened vocabulary sophistication and enhanced accuracy in relation to the initial draft. This study underscores the value of judiciously deploying these two categories of feedback within the landscape of writing instruction. The nuanced benefits of each feedback type can be strategically harnessed to suit distinct writing contexts, thereby augmenting the caliber of learners’ written compositions.

Exploring learner attention and processing in second language writing: The role of eye-tracking and written corrective feedback

This paper highlights the importance of the timing of feedback and distinguishing between instruction and feedback in the context of written corrective feedback (WCF) for second language (L2) learners. It proposes the integration of eye-tracking and qualitative data collection methods to assess learner attention and WCF processing. The reviewed eye-tracking studies demonstrate the potential of this approach, revealing correlations between learners’ noticing and subsequent writing improvements. However, the limited studies utilizing eye-tracking in this area calls for further research to explore the benefits of metalinguistic explanations provided before or after writing production. Additionally, the paper emphasizes the need to address the dominance of quantitative approaches in WCF literature and encourages the combination of eye-tracking with qualitative data sources to broaden our understanding of revision as negotiation. It suggests investigating the impact of different feedback modes and languages, especially in younger L2 writers and diverse writing systems. Moreover, the paper advocates for ecologically valid experiments that involve eye-tracking during revision with feedback present, considering the various types of feedback and their influence on learners’ noticing and subsequent writing improvements. Addressing these concerns will contribute to a comprehensive understanding of WCF, noticing and processing feedback, L2 writing production, and effective pedagogical practices.

Conditions and Synthesis of Adaptive Prescribed-Time Controllers

This paper addresses conditions and synthesis of adaptive prescribed-time controllers. The sufficient condition says that a system can achieve prescribed-time stabilization if its certain variant can be made globally bounded (on infinite time interval). From the condition one can know far more varieties of (uncertain nonlinear) systems can achieve prescribed-time control, rather than just special varieties in the related literature. The necessary condition states that a system can achieve prescribed-time stabilization attached global uniform boundedness (GUB) on finite time interval only if it, by some feedback type, can achieve GUB on infinite time interval. From the condition, or rather, its converse-negative version, one can see that what kind of systems cannot virtually achieve the prescribed-time stabilization attached GUB for some feedback type. The sufficient condition builds on two crucial transformations which change prescribed-time convergence on finite-time interval into global boundedness on infinite-time interval. With the aid of the conditions and transformations, we conduct the synthesis of adaptive prescribed-time controllers for general uncertain nonlinear systems typically with unknown control directions. By integrating time-varying factors into Lyapunov functions, an adaptive smooth controller is devised such that the system states converge to zero before an arbitrarily prescribed time, while the controller and its dynamic gains are bounded.

Interactive Robot Task Learning: Human Teaching Proficiency With Different Feedback Approaches

The deployment of versatile robot systems in diverse environments requires intuitive approaches for humans to flexibly teach them new skills. In our present work, we investigate different user feedback types to teach a real robot a new movement skill. We compare feedback as star ratings on an absolute scale for single roll-outs versus preference-based feedback for pairwise comparisons with respective optimization algorithms (i.e., a variation of co-variance matrix adaptation -evolution strategy (CMA-ES) and random optimization) to teach the robot the game of skill cup-and-ball. In an experimental investigation with users, we investigated the influence of the feedback type on the user experience of interacting with the different interfaces and the performance of the learning systems. While there is no significant difference for the subjective user experience between the conditions, there is a significant difference in learning performance. The preference-based system learned the task quicker, but this did not influence the users’ evaluation of it. In a follow-up study, we confirmed that the difference in learning performance indeed can be attributed to the human users’ performance.

Density calculations of NGC 3783 warm absorbers using a time-dependent photoionisation model

Outflowing wind, as one type of AGN feedback involving non-collimated ionised winds such as those prevalent in Seyfert-1 AGNs, impacts the host galaxy by carrying kinetic energy outwards. However, the distance of the outflowing wind is poorly constrained because of a lack of direct imaging observations, which limits our understanding of its kinetic power, and thus of its impact on the local galactic environment. One potential approach to solving this problem involves determination of the density of the ionised plasma, making it possible to derive the distance using the ionisation parameter ξ, which can be measured based on the ionisation state. Here, by applying a new time-dependent photoionisation model, tpho, in SPEX, we define a new approach, the tpho-delay method, which we use to calculate or predict a detectable density range for warm absorbers of NGC 3783. The tpho model solves self-consistently the time-dependent ionic concentrations, which enables us to study the delayed states of the plasma in detail. We show that it is crucial to model the non-equilibrium effects accurately for the delayed phase, where the non-equilibrium and equilibrium models diverge significantly. Finally, we calculate the crossing time to consider the effect of the transverse motion of the outflow on the intrinsic luminosity variation. Future spectroscopic observations with more sensitive instruments are expected to provide more accurate constraints on the outflow density, and therefore on the feedback energetics.

Effects of Using Immersive Virtual Reality for Science Education on Learning Outcomes: A Randomized Controlled Pilot Study

Immersive virtual reality (IVR) technology influences students cognitive process and affective experience according to previous research findings. Yet empirical studies that investigate the impact of immersive virtual reality (IVR) on science education in secondary schools are limited. This article reports a pilot study that has two objectives: 1) To investigate whether learning science with IVR leads to more positive learning outcomes than that with a traditional video-viewing activity; 2) To investigate whether corrective feedback produces more positive learning outcomes than explanatory feedback in IVR-mediated contexts. A randomized controlled pilot trial was designed during a school year at a secondary school in western China. Forty-seven participatory students were randomly assigned to a control group (learning with instructional videos, n = 17), an intervention group 1 (learning with IVR with corrective feedback, n = 15), and an intervention group 2 (learning with IVR with explanatory feedback, n = 15). We evaluated an array of student learning-related outcomes, including extraneous and germane cognitive load, intrinsic learning motivation, academic self-efficacy, learner satisfaction, and academic achievement. The results revealed significant difference in intrinsic learning motivation, academic self-efficacy, learner satisfaction, and academic achievement and insignificant difference in extraneous and germane cognitive load when students learned with video and IVR. In terms of the type of feedback provided in IVR-mediated environments, students who were prompted with corrective feedback and explanatory feedback showed little difference in their learning outcomes. Reasons related to the findings and limitations are discussed.

Haptic feedback in a virtual crowd scenario improves the emotional response

Research has shown that incorporating haptics into virtual environments can increase sensory fidelity and provide powerful and immersive experiences. However, current studies on haptics in virtual interactions primarily focus on one-on-one scenarios, while kinesthetic haptic interactions in large virtual gatherings are underexplored. This study aims to investigate the impact of kinesthetic haptics on eliciting emotional responses within crowded virtual reality (VR) scenarios. Specifically, we examine the influence of type or quality of the haptic feedback on the perception of positive and negative emotions. We designed and developed different combinations of tactile and torque feedback devices and evaluated their effects on emotional responses. To achieve this, we explored different combinations of haptic feedback devices, including “No Haptic,” “Tactile Stimulus” delivering tactile cues, and “Haptic Stimulus” delivering tactile and torque cues, in combination with two immersive 360-degree video crowd scenarios, namely, “Casual Crowd” and “Aggressive Crowd.” The results suggest that varying the type or quality of haptic feedback can evoke different emotional responses in crowded VR scenarios. Participants reported increased levels of nervousness with Haptic Stimulus in both virtual scenarios, while both Tactile Stimulus and Haptic Stimulus were negatively associated with pleasantness and comfort during the interaction. Additionally, we observed that participants’ sense of touch being real was enhanced in Haptic Stimulus compared to Tactile Stimulus. The “Haptic Stimulus” condition had the most positive influence on participants’ sense of identification with the crowd.

Use of variable online visual feedback to optimize sensorimotor coding and learning of a motor sequence.

The present study characterized the impact of reliable and/or unreliable online visual feedback and their order of presentation on the coding and learning of a motor sequence. Participants practiced a 12-element motor sequence 200 times. During this acquisition phase, two groups received a single type (i.e., either reliable or unreliable) of online visual feedback, two other groups encountered both types of feedback: either reliable first then unreliable, or unreliable first then reliable. Delayed retention tests and intermanual transfer tests (visuospatial and motor) were administered 24 hours later. Results showed that varying the reliability of online visual information during the acquisition phase allowed participants to use different task coding modalities without damaging their long-term sequence learning. Moreover, starting with reliable visual feedback, replaced halfway through with unreliable feedback promoted motor coding, which is seldom observed. This optimization of motor coding opens up interesting perspectives, as it is known to promote better learning of motor sequences.

The Role of In-Group and Out-Group Facial Feedback in Implicit Rule Learning.

Implicit learning refers to the fact that people acquire new knowledge (structures or rules) without conscious awareness. Previous studies have shown that implicit learning is affected by feedback. However, few studies have investigated the role of social feedback in implicit learning concretely. Here, we conducted two experiments to explore how in-group and out-group facial feedback impact different difficulty levels of implicit rule learning. In Experiment 1, the Chinese participants in each group could only see one type of facial feedback, i.e., either in-group (East Asian) or out-group (Western) faces, and learned the implicit rule through happy and sad facial expressions. The only difference between Experiment 2 and Experiment 1 was that the participants saw both the in-group and out-group faces before group assignment to strengthen the contrast between the two group identities. The results showed that only in Experiment 2 but not Experiment 1 was there a significant interaction effect in the accuracy of tasks between the difficulty levels and groups. For the lowest difficulty level, the learning accuracy of the in-group facial feedback group was significantly higher than that of the out-group facial feedback group, whereas this did not happen at the two highest levels of difficulty. In conclusion, when the contrast of group identities was highlighted, out-group feedback reduced the accuracy of the least difficult task; on the contrary, there was no accuracy difference between out-group and in-group feedback conditions. These findings have extensively important implications for our understanding of implicit learning and improving teaching achievement in the context of educational internationalization.

Winds versus jets: a comparison between black hole feedback modes in simulations of idealized galaxy groups and clusters

ABSTRACT Using the SWIFT simulation code, we compare the effects of different forms of active galactic nuclei (AGNs) feedback in idealized galaxy groups and clusters. We first present a physically motivated model of black hole (BH) spin evolution and a numerical implementation of thermal isotropic feedback (representing the effects of energy-driven winds) and collimated kinetic jets that they launch at different accretion rates. We find that kinetic jet feedback is more efficient at quenching star formation in the brightest cluster galaxies (BCGs) than thermal isotropic feedback, while simultaneously yielding cooler cores in the intracluster medium (ICM). A hybrid model with both types of AGN feedback yields moderate star formation rates, while having the coolest cores. We then consider a simplified implementation of AGN feedback by fixing the feedback efficiencies and the jet direction, finding that the same general conclusions hold. We vary the feedback energetics (the kick velocity and the heating temperature), the fixed efficiencies and the type of energy (kinetic versus thermal) in both the isotropic and the jet case. The isotropic case is largely insensitive to these variations. On the other hand, jet feedback must be kinetic in order to be efficient at quenching. We also find that it is much more sensitive to the choice of energy per feedback event (the jet velocity), as well as the efficiency. The former indicates that jet velocities need to be carefully chosen in cosmological simulations, while the latter motivates the use of BH spin evolution models.

Social comparison feedback in decision-making context: Environmental externality levels and psychological traits matter

Social comparison feedback has been widely applied to encourage energy and water conservation, with the ultimate aim to protect ecosystems and the environment. Yet, the effectiveness of social comparison feedback varies. In this study, with 360 UK participants from Prolific, we conducted an online experiment based on a modified dictator game with multi-round purchasing decisions involving trade-offs between individual monetary payoff and real-world carbon offsets donation. A 2 × 3 between-subjects design was implemented, varying in the externality levels associated with the purchase (high versus low), and the type of feedback (self-feedback, social comparison feedback, and tangible emissions feedback – i.e. social comparison enriched with information relating environmental impacts to daily activity and nature). Furthermore, we measured several psychological traits of participants. Our findings show that social comparison interventions are only effective under certain circumstances. Both interventions with social comparison are more effective in the low-externality context. Furthermore, the effect of tangible emissions feedback is moderated by individuals’ tendency to conform to specific social norms and compete with others. Compared to standard social comparison feedback, social comparison feedback enriched with tangible emissions information is overall more effective. We highlight the importance of tailoring social comparison interventions to local environmental and cultural contexts.

Prediction and Analysis of Shoes Popularity Based on Random Forest Regression Model

Since the era of big data, e-commerce has become a popular industry. People are more inclined to online shopping websites and apps, which are more convenient ways to buy commodities. In order to increase the popularity and fame of websites and apps to attract more customers, e-commerce often analyzes and models customer feedback and purchase types in order to get customers' higher preferences for the performance of products. This paper collected a variety of popular shoes scoring situation, current price, sales volume, wanted quantity, releasing date, releasing price and other relevant quantities. The HM aggregation operator is used to define the popularity (the popularity of the shoe). In this paper, the random forest algorithm is used to conduct regression modeling analysis with the pre-processed data, and the importance estimation of each criterion and a regression prediction model are obtained according to the established model. Then this paper analyzes the shortcomings of the model, and adds data normalization processing to the steps of data preprocessing to make the model more powerful in estimating outliers. According to the results, some suggestions are made for the research and development priorities of footwear companies and it is verified that the model can basically complete the prediction of popularity.

Teacher behaviour and student engagement with L2 writing feedback: a case study

Abstract Feedback is essential for student learning and engagement is key for its efficacy. Yet research on student engagement with feedback predominantly attributes it to learner factors, overlooking teacher influence. This case study explored how one writing teacher’s behaviours shaped a motivated undergraduate’s engagement with various types of feedback in a writing course over one semester. Data sources included interviews, class observations, and text analysis. Findings revealed the pivotal role of teacher feedback behaviours in shaping student engagement, often through complex interactions with learner factors and teacher non-feedback behaviours. While some feedback behaviours enhanced student engagement, most had negligible or detrimental effects, highlighting the contextual nature of “best practices”. Certain teacher behaviours also exerted lasting impacts on student engagement. Additionally, some teacher non-feedback behaviours, both teaching and non-teaching, also contributed to shaping student engagement. These findings have implications for both research and teacher education.