Effects Of Feedback Research Articles

The application of artificial intelligence in biomechanical feedback and learning effectiveness enhancement in ideological and political education

The application of artificial intelligence (AI) in ideological and political education (IPE) optimizes the learning effect with the help of biomechanical feedback mechanism, and provides technical support for deepening the reform of IPE in colleges and universities. With the help of AI technology, especially its advantages in data analysis and deep learning (DL), accurate matching and personalized recommendation of learning resources can be realized. In this study, an AI-assisted IPE system with biomechanical feedback was constructed. By analyzing students’ physiological reactions and behavior patterns in the learning process, the system can evaluate the learning state and adjust teaching strategies. The key findings show that this learning method combined with biomechanical feedback can significantly improve students’ learning participation, understanding depth and satisfaction, and make IPE more in line with students’ needs.

Benchmarking in inflammatory bowel disease: lessons from Australia and New Zealand

Abstract Inflammatory bowel disease (IBD) is a complex chronic disease estimated to affect almost 1% of the Western population, where proactive care has largely replaced a reactive approach. Whilst there have also been great strides in new care models and therapies, care quality, and outcomes are poorly known, leaving us designing and delivering services without an effective feedback loop. Quality of care, guidelines, consensus statements, and standards will each be discussed, as a solid understanding of these concepts is essential. Assessing quality involves measuring the 3 core domains of structure, process, and outcomes. Benchmarking is an extension of quality assessment, which is recurrent or continuous and enables transparent, valid comparisons of quality between care sites. Assessment of QUALITY and BENCHMARKING are resource intensive unless processes are automated and use routinely collected data generated in the moments of care. Digital tools now provide realistic opportunities to make this affordable and sustainable, though concerns around privacy and security hamper solutions, whilst siloed data within institutions restrict comparative use. One novel solution to enable IBD benchmarking has been developed in Australia and New Zealand (ANZ). Crohn’s Colitis Care (CCCare) is a cloud-based, IBD-specific EMR, now being used in routine care documentation at 22 sites across ANZ. De-identified data feed from CCCare’s clinical module into a Clinical Quality Registry, in which audit, research, and benchmarking can be performed. The pathway from conception to implementation will be presented. Lessons learnt from the ANZ benchmarking journey will be discussed and suggestions for an effective global approach to IBD data will be proposed.

Competition modulates the effects of social comparison on ERP responses during face processing.

Little is known about the effect of prior social performance feedback on face processing. Our previous study explored how equal and unequal social comparison-related outcomes modulate event-related potential (ERP) responses to subsequently-presented faces, where interests between oneself and others were independent (noncompetitive situations). Here, we aimed to extend this investigation by assessing how different unequal social comparison-related outcomes affect face processing under noncompetitive and competitive situations (i.e., a conflict of interest exists between the self and others). To address this issue, 39 participants were exposed with self-related and social comparison-related outcomes, categorized as positive or negative, after performing an attentional task with peers. Rewards and punishments depended on social comparison-related outcomes in the competition condition and on self-related outcomes in the noncompetition condition. ERP results showed that social comparison-related outcomes influenced P100 responses to faces in the self-positive condition. More notably, the effects on N170 responses observed in the noncompetition condition was absent in the competition condition. There was an effect on LPP responses only in the competition and self-negative condition. These findings suggest that social comparison-related outcomes influence early face processing irrespective of competition, while competition subsequently disrupts this processing but later, enhances depending on self-related outcomes.

Exponential synchronization of bi-directional associative memory neural networks with delay on arbitrary time domains

Abstract We investigate the exponential synchronization of bi-directional associative memory neural networks with delays on a family of different time domains. By utilizing the theory of time scales, we provide stabilization results that are applicable to continuous-time, discrete-time, and general nonuniform hybrid time domains. Our approach employs a unified matrix-measure theory, a recent alternative to traditional Lyapunov functions, to establish exponential synchronization and design effective feedback laws. Notably, our methodology does not require symmetry or diagonality in the control gain matrix, distinguishing it from prior works. Furthermore, we explore various special cases of the considered systems and provide a detailed discussion highlighting the advantages of our findings over existing results. The effectiveness of our proposed criteria is demonstrated through small-scale and medium-scale simulated numerical examples across different time domains. Additionally, we apply our results to an example from the literature, showcasing the broad applicability and improved performance of our method in comparison to previous approaches.

Conditions for Super-Eddington Accretion onto the First Black Holes

Abstract Observations of supermassive black holes at high redshift challenge our understanding of the evolution of the first generation of black holes (BHs) in proto-galactic environments. One possibility is that they grow much more rapidly than current estimates of feedback and accretion efficiency permit. Following our previous analysis of super-Eddington accretion onto stellar-mass black holes in mini-haloes under no-feedback conditions, we now investigate whether this can be sustained when thermal feedback is included. We use four sets of cosmological simulations at sub-pc resolution with initial black hole masses varying from 1 × 103 M⊙ − 6 × 104 M⊙, exploring a range of feedback efficiencies. We also vary the feedback injection radius to probe the threshold of numerical overcooling. We find that super-Eddington growth sustained on the order of ∼$100 \, \rm kyr$ is possible with weak thermal feedback efficiency in all environments and moderate efficiency for two of the BHs. Trans-Eddington growth is possible for a 1 × 103 M⊙ − 6 × 103 M⊙ BH at moderate feedback efficiencies. We discuss the effectiveness of thermal feedback in heating the gas, suppressing accretion, and driving outflows at these parameter configurations. Our results suggest that super-Eddington growth may be possible in the presence of thermal feedback for black holes formed from the first stars.

Online Peer Feedback Versus Online Teacher Feedback? Effect of Online Feedback on Students’ Self-Regulated Learning

Online Peer Feedback Versus Online Teacher Feedback? Effect of Online Feedback on Students’ Self-Regulated Learning

The Effects of Social Feedback Through the "Like" Feature on Brain Activity: A Systematic Review.

Problematic social media (SM) use is a growing concern, particularly among adolescents who are drawn to these platforms for social interactions important to their age group. SM dependence is characterized by excessive, uncontrolled usage that impairs personal, social, and professional aspects. Despite the ongoing debate over recognizing SM addiction as a distinct diagnostic category, the impact of social feedback, particularly through the "like" button, on brain activity remains under scrutiny. This systematic review aims to study the neural correlates of online social feedback, focusing on the effects of the "like" feedback on brain activity using fMRI and EEG. The review followed the recommendations of the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Protocols (PRISMA). The review included 11 studies with 504 participants, identifying key brain structures such as the amygdala, ventromedial prefrontal cortex (vmPFC), and ventral striatum involved in reward processing. Positive feedback ("likes") activates areas like the nucleus accumbens (NACC), vmPFC, and amygdala, with NACC correlating with increased SM use intensity. Negative feedback activates the ventrolateral prefrontal cortex (vlPFC) and left medial prefrontal cortex (mPFC). Behavioral data indicates that positive feedback influences subsequent social interactions. The review highlights disparities in the literature regarding the neural response to social feedback, emphasizing the need for further research to clarify the roles of sex, personality traits, and the person giving feedback. Overall, understanding the neurobiological underpinnings of SM engagement is essential for developing effective interventions to prevent or address the negative effects of excessive SM use.

Effects of tactile feedback in post-stroke hand rehabilitation on functional connectivity and cortical activation: an fNIRS study

Effects of tactile feedback in post-stroke hand rehabilitation on functional connectivity and cortical activation: an fNIRS study

How Self-Regulated Learning Is Affected by Feedback Based on Large Language Models: Data-Driven Sustainable Development in Computer Programming Learning

Self-regulated learning (SRL) is a sustainable development skill that involves learners actively monitoring and adjusting their learning processes, which is essential for lifelong learning. Learning feedback plays a crucial role in SRL by aiding in self-observation and self-judgment. In this context, large language models (LLMs), with their ability to use human language and continuously interact with learners, not only provide personalized feedback but also offer a data-driven approach to sustainable development in education. By leveraging real-time data, LLMs have the potential to deliver more effective and interactive feedback that enhances both individual learning experiences and scalable, long-term educational strategies. Therefore, this study utilized a quasi-experimental design to examine the effects of LLM-based feedback on learners’ SRL, aiming to explore how this data-driven application could support learners’ sustainable development in computer programming learning. The findings indicate that LLM-based feedback significantly improves learners’ SRL by providing tailored, interactive support that enhances motivation and metacognitive strategies. Additionally, learners receiving LLM-based feedback demonstrated better academic performance, suggesting that these models can effectively support learners’ sustainable development in computer programming learning. However, the study acknowledges limitations, including the short experimental period and the initial unfamiliarity with LLM tools, which may have influenced the results. Future research should focus on refining LLM integration, exploring the impact of different feedback types, and extending the application of these tools to other educational contexts.

The Impact of Timely Formative Feedback on University Student Motivation

While key attributes of effective feedback have frequently been included in studies on student learning, little research has focused on the impact of the timeliness of feedback on student motivation. By providing students with written feedback at 1, 3, 7, 10, or 14 days after submission, this mixed design study enriches our understanding of the feedback timeliness and its importance on student motivation. Based on survey data of undergraduate and postgraduate students from a wide range of disciplines including health and social sciences, screenwriting, business administration, and finance over a three-year period, our findings indicate that students express significantly lower levels of motivation if the feedback took greater than 10 days but they did not distinguish between ‘timely’ and ‘extremely timely’ feedback. Our quantitative analysis reveals that feedback comments and turnaround are significant determinants of student motivation, providing areas of focus for both educators and administrators. However, content of feedback showed the highest impact and our qualitative analysis supported this, with 57% of students mentioning content of the feedback. Students especially appreciate thorough, personalised, and specific assessment of strengths and weaknesses. Not surprisingly, 48% mentioned the importance of a high-quality educator, so great teaching is also important in motivating our students.

Effective instructor feedback does not always promote better public speaking outcomes: the importance of self-efficacy and feedback orientation(s) in the introductory course

ABSTRACT Research has yet to fully explain the processes through which feedback affects student outcomes. The majority of research has also focused on feedback from an instructor's perspective. Guided by feedback intervention theory (FIT; Kluger, A. N., & DeNisi, A. [1996]. The effect of feedback interventions on performance: A historical review, a meta-analysis, and a preliminary feedback intervention theory. Psychological Bulletin, 119[2], 254–284. https://doi.org/10.1037/0033-2909.119.2.254), and using longitudinal online survey data from students in an undergraduate introductory communication course at a 4-year university (N = 2,523), we found that self-efficacy mediated the relationship between perceived feedback effectiveness and both PSA and CC, playing a positive role in increasing students’ CC and decreasing their PSA. Various feedback orientations, especially feedback sensitivity and confidentiality, exerted moderating and/or conditional indirect effects on our proposed feedback cycle. These findings advance scholarly knowledge of the feedback cycle according to FIT, repositioning self-efficacy as a critical mediator. They also speak to the importance of understanding how students’ feedback orientations can dampen or strengthen the positive impact of effective feedback on public speaking outcomes. Additional theoretical implications and pedagogical recommendations are discussed.

The effect of feedback on student performance

The effect of feedback on student performance

Effects of Peer Video Feedback Based on Cultural Historical Activity Theory in the Operational Training of New Nurses: A Quasi-Experimental Study.

Previous studies have confirmed the potential effectiveness of peer video feedback in the operational training of health care students. However, an appropriate theoretical framework to support peer video feedback has not been established. The cultural historical activity theory (CHAT) provides a suitable framework. This study evaluated the effectiveness of a peer video feedback activity system, adapted from CHAT, in enhancing operational skills, self-regulated learning abilities, and teaching satisfaction among new nurses. A quasi-experimental design was employed, involving 213 new nurses. The experimental group received training through a CHAT-based peer video feedback activity system, and the control group was trained through traditional instructor feedback. Data were collected after seven operational training sessions provided by the nursing department. Posttraining, the CHAT group scored statistically higher in operational examinations, self-regulated learning abilities, and teaching satisfaction compared with the control group (p = .004, p = .004, and p < .001, respectively). Operational training with a peer video feedback activity system can significantly enhance the operational skills, self-regulated learning abilities, and teaching satisfaction of new nurses. [J Contin Educ Nurs. 2025;56(1):27-33.].

Exploring the effects of informal feedback on organizational outcomes in academic libraries

Exploring the effects of informal feedback on organizational outcomes in academic libraries

Dynamical effects of Mechano-Chemo-Transduction on Cardiac Alternans.

In every heartbeat, cardiac muscle cells perform excitation-Ca2+ signaling-contraction (EC) coupling to pump blood against the vascular resistance. Cardiomyocytes can sense the mechanical load and activate mechano-chemo-transduction (MCT) mechanism, which provides feedback regulation of EC coupling. MCT feedback is important for the heart to upregulate contraction in response to increased load to maintain cardiac output. MCT feedback enhances the L-type Ca2+ current, sensitizes ryanodine receptors (RyRs), and augments SERCA pump activity, thereby maintaining contraction amplitude despite increased load. However, under certain conditions, MCT feedback can also promote cardiac alternans, seen as beat-to-beat variations in action potential duration, Ca2+ transients, and contraction strength, which is a precursor to arrhythmias. While alternans can arise from instabilities in either membrane voltage or intracellular Ca2+ cycling, underlying mechanisms of MCT-induced alternans, particularly electromechanically discordant alternans where stronger beats are paradoxically associated with shorter action potentials, remain unclear. In this study, we used a mathematical model of the ventricular myocyte to investigate the effects of MCT feedback on the dynamical system that generates alternans. We systematically analyzed how MCT feedback, acting through L-type Ca2+ channels (LTCCs), RyRs, or SERCA, affects the stability of membrane voltage and Ca2+ cycling, as well as the coupling between them. Our results show that MCT feedback can generally promote both concordant and discordant alternans in action potential and Ca2+ transients, depending on the underlying instability mechanism. We found that MCT feedback through RyRs predominantly increases Ca2+ instability, while LTCC and SERCA feedback have complex effects due to the interplay between stability and coupling alterations. We also showed how to determine underlying mechanisms from experimental and clinical observations. Our modeling studies provide new insights into the complex dynamics underlying cardiac alternans and highlight the importance of MCT feedback in the development of life-threatening arrhythmias in the heart under mechanical load.

A Comprehensive Approach to Intelligent Garment for Posture Correction: A Preliminary Study for Integrating Aesthetics and Sensor Interaction

PurposeThis study investigates design and evaluation of an intelligent vest integrating Marginal Absolute Relative Gradient (MARG) sensors for posture correction. The research aims to enhance ergonomic interventions through a lightweight, aesthetic garment that provides real-time feedback, addressing both functional and design in wearable technology.MethodsThe vest incorporates Adafruit FLORA microcontroller boards and MARG sensors to monitor neck and shoulder movements. Experimental setups involved recording roll and pitch angles during various postures. A sample of 10 female participants was recruited for usability testing, and quantitative analyses of sensor data were performed to validate the vest's performance. Moreover, user feedback on the vest's visual (LED) and tactile (vibration) feedback, comfort, and posture correction effectiveness was collected.ResultsData revealed distinct posture patterns, including a mean neck pitch of −61.80° during forward tilts and synchronized neck-shoulder movements when leaning right (correlation coefficient of 0.46 for pitch). Conversely, independent movements were observed in leftward tilts (correlation coefficients of 0.07 for roll and −0.18 for pitch). User feedback indicated high ratings for comfort (mean = 4.4) and LED feedback effectiveness (mean = 4.3), while haptic feedback received moderate scores (mean = 3.6).ConclusionThe intelligent vest successfully integrates posture correction functionality with user-friendly design, providing detailed real-time feedback and maintaining wearability. This study highlights its potential in health-related applications and underscores the importance of aesthetics in wearable technology for enhanced adoption and usability.

Plasma displacement calculation for TT-1 device based on multiple magnetic probes fitting methods

The HT-6M device has been upgraded and rebranded as the Thailand Tokamak 1 (TT-1), which has been reinstalled and is now operational in Thailand. In tokamak discharge experiments, precise monitoring of plasma position and the implementation of effective feedback control are essential for ensuring the stability of the high-temperature plasma. Accurate calculation of plasma displacement is critical to the success of the experiment. This paper presents a method for calculating plasma displacement through a multi-probe fitting technique, utilizing data from twelve magnetic field probes. Initially, magnetic field signals generated by the plasma are collected via multiple magnetic field probes installed poloidally outside the vacuum chamber, coupled with corresponding signal conditioning and integration circuits, with each probe undergoing calibration. Subsequently, during tokamak discharges, interference signals from the toroidal field coils, ohmic heating coils, and vertical field coils are generated by the magnetic system and corrected through a detailed calibration process. Lastly, the distances between the probes and the plasma are computed using data from the magnetic field probes, which are arranged in a circular configuration. The least squares method is employed to formulate a residual equation for fitting the actual plasma displacement. The effectiveness of this approach was validated through experimental data from the TT-1 device, demonstrating that the calculated plasma displacement exhibits a consistent trend with the CCD video recordings. This multi-probe displacement calculation method enables precise control of plasma displacement, thereby providing theoretical support for tokamak experiments and establishing a foundation for future experimental operations and data analysis.

High-Density Surface Electromyography Feedback Enhances Fibularis Longus Recruitment in Chronic Ankle Instability.

This study aimed to determine whether individuals with chronic ankle instability (CAI) can activate the fibularis longus compartments with high-density surface electromyography (HD-sEMG) biofeedback to the same extent as those without CAI, and to analyze the effect of ankle position on compartment activation in individuals with CAI using HD-sEMG feedback. There were 16 volunteers per group (CAI and No-CAI). The sEMG amplitude at each compartment (anterior and posterior) and the barycenter of the spatial sEMG amplitude distribution of the fibularis longus were recorded during eversion in neutral and plantar flexion positions at 30% and 70% of maximum voluntary contraction force, both with and without visual feedback on the spatial sEMG amplitude distribution. sEMG amplitude of the posterior compartment of the fibularis longus in the CAI group trained with HD-sEMG feedback during eversion at 70% maximum voluntary contraction (in plantar flexion) was significantly higher than without HD-sEMG feedback (95% CI = 3.75-34.50% root mean square) and was similar to the activation of the No-CAI group (95% CI = -14.34% to 34.20% root mean square). Furthermore, individuals with CAI who underwent training with HD-sEMG feedback in plantar flexion exhibited a posterior displacement of the barycenter (95% CI = 0.56-2.84 mm). Utilizing HD-sEMG feedback during eversion in plantar flexion position increases activation of the fibularis longus posterior compartment in individuals with CAI to the same extent as healthy people. HD-sEMG-based topographic maps can serve as effective feedback training to restore motor control of the ankle. Long-term efficacy for improving motor function requires investigation through longitudinal studies.

SMILE, YOU’LL FEEL BETTER: TESTING THE FACIAL FEEDBACK HYPOTHESIS IN YOUNG AND OLDER ADULTS

Abstract We investigated age differences in the effect of facial feedback on the emotional experience on a sample of young and older adults. The Facial Feedback Hypothesis proposes that feedback from facial expressions impacts the emotional experience by enhancing or dampening the emotional experience (James, 1884; Darwin 1897). Embodied cognition, the bidirectional relationship between the mind and the body is central to maturational dualism, which suggests older adults show reductions in proprioception, interoception, and physiological reactivity (Niedenthal et al., 2005; Mendes, 2010). Based on this, we expected older adults to show reduced facial feedback effects. Participants were instructed to pose a happy, angry, and neutral facial expression and rate their happiness and anger on a 7-point scale before and during the facial manipulation. We found that in the Angry Condition, there was a main effect of Time, such that both age groups showed reductions in happiness scores, F(1,119) = 86.243, p&amp;lt;.001, η2=.420 and increases in anger, F(1,119) = 29.798, p&amp;lt;.001, η2=.200, as well as a Time x Age Group interaction, F(1,119) = 4.546, p&amp;lt;.035, η2=.03, showing that older adults had a larger decrease in happiness scores, but no age differences in feelings of anger. In the Happy Condition, we did not find any significant age differences in ratings of happiness or anger from pre to post while posing the happy or angry facial expression. Contrary to our hypotheses, these results suggest that older adults do experience facial feedback effects specifically for anger, but not happiness.

The interaction effect of regulatory focus and negative feedback on proactive behavior: the mediating role of perceived insider status

There are two conflicting opinions regarding negative feedback from supervisors in the current literature: that it motivates subordinates’ proactive behavior, and that it discourages proactive behavior. This demonstrates the theoretical confusion over the exact nature of the relationship between negative feedback and proactive behavior. To clarify this confusion, this study investigates the mediating and moderating processes underlying the linkage between negative feedback and proactive behavior based on motivated information process theory. Using three-wave and multi-source data among 332 Chinese employees, our results show that regulatory focus moderates the indirect effects of negative feedback on proactive behavior through perceived insider status, such that the effect is stronger among employees with a higher prevention focus, whereas the effect is weaker in employees with a higher promotion focus. We also discuss meaningful theoretical and practical implications of this research.