Feedback Information Research Articles

Feedback, training, goal-setting, planning and performance: understanding the pathway to improved organizational outcomes

PurposeAs competitive pressures persist and global economic influences continue to present new challenges, businesses need to be able to respond to emerging circumstances. Goal-setting and planning are key mechanisms contributing to organizational competitive success, yet organizations underappreciate the role of competency and capacity building factors that contribute to successful planning. This paper integrates three theoretical models enabling an investigation into the positive relationships between managerial activities generating information feedback, training in planning and skills and organizational performance outcomes, while exploring the positive mediating roles of goal-setting and planning.Design/methodology/approachA unique organizational sample of agribusiness producers (n = 499) in Canada is examined. A structural equation path analysis model is used to evaluate the main relationships.FindingsThe results suggest that organizations are finding that managerial and training activities should not be considered in isolation, but rather as supports for goal-setting, planning and performance outcomes. Thus, the implications are that managers can find organizational value enhanced through the building of human resource competency (e.g. management activities and training) with these emerging capacities aiding goal setting and planning activities.Originality/valueThis study makes three main contributions: first, by adopting a rational-design perspective and integrating theoretical frameworks focusing on (a) planning-performance and (b) goal-setting-planning. This extended model goes beyond previous studies by including managerial activities, training, goals, planning and performance outcomes. Second, this study uniquely accounts for a more comprehensive set of key confounding factors such as operational activities, organizational strategy and organizational size in the integrated framework. Finally, as far as the authors are aware, there has not been a survey study at the organizational level that has explored the role of managerial activities and training in planning within a similarly comprehensive model.

Relieving negative Chinese transfer in EFL syntactic writing through negative feedback based on computational thinking

Negative feedback can temporarily relieve negative Chinese transfer (NCT) in English as a foreign language (EFL) syntactic writing by focusing only on the surface writing constructs, neglecting that EFL writing is an embodiment of the process by which higher-order thinking operates. To solve the problem, the researchers conducted a pretest, interventionist group dynamic assessment (IGDA) in the form of negative feedback based on computational thinking (CT), higher-order thinking, and post-test quasi-experimental design, with a control group receiving the direct correction feedback instructing model to mitigate the NCT in EFL syntactic writing. We analyzed the syntactic writing types and frequencies of the NCT obtained through repeated-measure ANOVA and confirmed by qualitative data through video recording. The results indicated that IGDA in the form of negative feedback based on CT principal skills could (1) significantly decrease syntactic writing errors caused by the NCT, (2) improve learners’ EFL writing performance, and finally, (3) elevate the computer as an essential mediation tool. This innovative instructing mode of intervening with writing constructs and higher-order thinking and bringing about deeper thinking and creativity contributes to the EFL writing teaching methodology in a foreign language higher education.

Teacher Educators’ Use of Formative Feedback During Preservice Teachers’ Simulated Teaching Experiences in Mathematics and Science

Teacher Educators’ Use of Formative Feedback During Preservice Teachers’ Simulated Teaching Experiences in Mathematics and Science

Research on Application and Quality Evaluation of Intelligent Teaching Model of AI Three Teachers in the Course of Motion Control Technology

Motion control technology is an important branch of automation, and is one of the important development directions of the emerging industry of high-end equipment manufacturing. As a comprehensive discipline with the intersection of mechanical, electrical and electronic, its teaching mode faces many challenges. There are practical problems that need to be solved, such as teaching content not matching seamlessly with post knowledge and skill literacy requirements, teaching project design is not high in modularity, and teaching evaluation system is not perfect. These problems seriously restrict the cultivation of students' technical practical ability. This project proposes the "intelligent teaching model of AI three teachers for the course of Motion Control Technology", which emphasizes student-centered, builds a core curriculum system that connects with the technology of field engineers in enterprises, and proposes the three-way collaborative teaching and education strategy of "vocational school Teacher + Al Teacher + enterprise tutor" to enable students to participate in learning in an all-round way. And timely access to feedback information, the formation of continuous improvement of the teaching cycle. Optimize the teaching team and teaching mode, improve the teaching quality, meet the diversified learning needs of students, and promote the continuous innovation and development of education and teaching.

Comparison of Microsurgical and Conventional Techniques for Augmentation of Keratinized Mucosa Around Dental İmplants

Objective: This study aims to compare the clinical outcomes of periodontal microsurgery with conventional periodontal surgery in keratinized mucosa augmentation around the implant. Materials and Methods: Ten patients with at least 2 implants with a keratinized mucosal width of < 2 mm were included. Free gingival graft (FGG) was applied in the test group with the microsurgery technique whereas in the control group with the conventional periodontal surgery technique. Keratinized mucosa width (KMW) and palatal mucosal thickness (MT) were measured at baseline and 3rd month. Graft shrinkage(GS) was evaluated at the 3rd month. Donor site wound healing was evaluated at the 10th day and 3rd month. Feedback forms were collected on the 10th day. Results: KMW values increased significantly in both groups at 3rd month compared to baseline. The percentage of GS was lower in the test group at 3rd month, but this difference was not significant. MT values in the test group were closer to the baseline values at 3rd month compared to the control group. Wound healing scores were similar in both groups at the 10th day and 3rd month. Postoperative pain levels decreased more rapidly in the test group. Conclusion: The microsurgical technique provides a faster increase in palatal mucosal thickness and lower graft shrinkage during the healing period and an earlier reduction in postoperative pain levels.

AI-enabled correction: A professor’s journey

ABSTRACT AI-enabled assessment of student papers has the potential to provide both summative and formative feedback and reduce the time spent on grading. Using auto-ethnography, this study compares AI-enabled and human assessment of business student examination papers in a law module based on previously established rubrics. Examination papers were corrected by the professor and then subjected to a series of tests by Gen-AI tools. While we were impressed with the personalised feedback of Gen-AI tools, the accuracy of grading and the learning capacity of AI tools, we found that Gen-AI tools used are not fully satisfactory to enable fully autonomous correction due to erroneous grading, the hallucination phenomenon and verbose feedback that is not always personalised. The 8C model of challenges of AI-enabled correction is outlined. This paper has implications for professors, HEIs and instructional designers and all those who correct student papers in a third-level institution.

The impact of financial feedback on the innovative activity of companies: the moderating role of corporate governance quality

ABSTRACT This research analyzes performance feedback and corporate innovative activity in the context of corporate governance quality. The research goal is as follows: to examine the influence of social and historical performance feedback on R&D intensity of a firm, and to determine whether governance quality strengthens interconnection between performance feedback and R&D intensity. The sample consists of panel data on 283 South-Eastern Asian public companies from the manufacturing industry sector. The sample covers seven countries during the time period from 2015 to 2020, providing 1698 firm-year observations. It was discovered that sample firms are sensitive to positive and negative social performance feedback and do not respond to historical feedback. A comparative analysis between types of feedback has shown that firms value social feedback more than historical feedback. It was also established that higher corporate governance quality decreases performance feedback sensitivity among firms, which weakens the relationship between the feedback and innovative activity. Firms with weak governance systems value social performance feedback more than companies with mature governance. The study of these types of feedback in combination with the quality of corporate governance can be used by company executives in corporate strategic planning and operational decision-making. CEOs should be ready to use performance feedback information in addition to their personal judgment.

Different sensory information is used for state estimation when stationary or moving.

The accurate estimation of limb state is necessary for movement planning and execution. While state estimation requires both feedforward and feedback information, we focus here on the latter. Prior literature has shown that integrating visual and proprioceptive feedback improves estimates of static limb position. However, differences in visual and proprioceptive feedback delays suggest that multisensory integration could be disadvantageous when the limb is moving. We formalized this hypothesis by modeling feedback-based state estimation using the longstanding maximum likelihood estimation model of multisensory integration, which we updated to account for sensory delays. Our model predicted that the benefit of multisensory integration was largely lost when the limb was passively moving. We tested this hypothesis in a series of experiments in human subjects that compared the degree of interference created by discrepant visual or proprioceptive feedback when estimating limb position either statically at the end of the movement or dynamically at movement midpoint. In the static case, we observed significant interference: discrepant feedback in one modality systematically biased sensory estimates based on the other modality. However, no interference was seen in the dynamic case: participants could ignore sensory feedback from one modality and accurately reproduce the motion indicated by the other modality. Together, these findings suggest that the sensory feedback used to compute a state estimate differs depending on whether the limb is stationary or moving. While the former may tend toward multimodal integration, the latter is more likely to be based on feedback from a single sensory modality.Significance statement The estimation of limb state involves feedforward and feedback information. While estimation based on feedback has been well studied when the limb is stationary, it is unknown if similar sensory processing supports limb position estimates when moving. Using a computational model and behavioral experiments, we show that feedback-based state estimation may involve multisensory integration in the static case, but it is likely based on a single modality when the limb is moving. We suggest that this difference may stem from visual and proprioceptive feedback delays.

Towards an idealized model of feedback uptake: longitudinal development of feedback literacy from a social constructivist perspective

ABSTRACT One of the potentials and challenges for the implementation of effective feedback processes lies in promoting and enacting purposeful student uptake of teacher written feedback. The theoretical framework in addressing this puzzle emanates from the inter-related concepts of social constructivist approaches to feedback and student feedback literacy. Feedback from a social constructivist perspective is underpinned by social and relational interaction in co-constructing inferences from feedback information. Feedback literacy represents the capacities to use feedback information productively. The aim of this longitudinal qualitative inquiry is to analyze how an undergraduate student interprets and uses teacher written feedback to enhance her work and her feedback literacy over a four-year period, in collaboration with a co-researcher. The main data sources comprise all written feedback provided by teachers over the four-year period; co-constructed analysis and action planning; enactment of action plans; and the student’s reflective journal of feedback experiences. The findings are presented in three chronological stages to demonstrate the main feedback literacy development of the student in appreciating the value of feedback, enhancing emotional resilience in response to critical feedback and managing feedback uptake. Experiencing successful feedback uptake is identified as a significant factor in enhancing self-efficacy and supporting the development of student feedback literacy. On the basis of the longitudinal evidence, an idealized model of feedback uptake is proposed underpinned by social constructivist principles. The originality of our contribution to social constructivist feedback research lies in illustrating how its principles are implemented over time.

Innovative approach of teaching ray-optics in the classroom

Abstract The present work discusses an innovative approach to teaching ray optics for students of class X. The school students were taught various concepts related to ray optics viz. Reflection, refraction, lateral displacement, mirrors, lenses, their types and terminologies, thin and thick lens, power of a lens, all cases of image formation in lenses, total internal reflection and its applications, human eye, its defects and corrections, making of telescope and microscope through practical demonstrations and hands-on approach using a self-conceived Ray Optics Kit. This activity was done independently in twenty two schools of Delhi, both government and private, with a massive total participation of 1200 students as part of SPIE Optics Outreach Activity. SPIE@ANDC Student Chapter members were trained at the college and they followed ‘Train the Trainer’ approach to create a pool of more than fifteen students who collectively conducted the workshops in teams in each of these schools. The student performance was assessed through a pre and post test as well as using a feedback form. An improvement of 65% in students’ performance was observed as indicated by comparing their pre-test and post-test results. The students as well as teachers gave a highly appreciative feedback of the whole activity. The feedback on their social media pages is a testimony of the success of the activity. Each school was awarded a Ray Optics Kit so as to make teaching and learning of ray optics interesting and engaging for batches in the future academic years.

Development and application of closed-loop-oriented intelligent control system for blast furnace air volume addition or reduction

Adjusting the upper and lower parts is an important means to ensure stable operation of blast furnaces. It is a common operation method to adjust the smelting state of the blast furnace by adjusting the air volume. Most of the domestic blast furnace air volume increase and decrease operations are confirmed by manual experience, and it is difficult to realize intelligent automatic control. This paper presents an intelligent control system for regulating air volume in blast furnaces, based on operational logic, expert knowledge, fundamental theories, and other relevant information. The system enables automatic analysis of the blast furnace's state and intelligent reasoning of the foreman's operational methods, laying the foundation for achieving closed-loop control. The system unifies the control philosophy and stabilizes the control methods for regulating air volume in blast furnaces. This achieves standardization of operation and proceduralization of cause analysis. The system enhances adaptability by creating an information feedback mechanism, increasing acceptance among blast furnace operators, and continuously resolving various anomalies in practical applications. The system currently maintains a true hit rate of over 95%, enabling effective reduction of operational misjudgments, intelligent control of airflow adjustment, and promotion of stable and smooth blast furnace operation.

Many-Objective Grasshopper Optimization Algorithm (MaOGOA): A New Many-Objective Optimization Technique for Solving Engineering Design Problems

In metaheuristic multi-objective optimization, the term effectiveness is used to describe the performance of a metaheuristic algorithm in achieving two main goals—converging its solutions towards the Pareto front and ensuring these solutions are well-spread across the front. Achieving these objectives is particularly challenging in optimization problems with more than three objectives, known as many-objective optimization problems. Multi-objective algorithms often fall short in exerting adequate selection pressure towards the Pareto front in these scenarios and difficult to keep solutions evenly distributed, especially in cases with irregular Pareto fronts. In this study, the focus is on overcoming these challenges by developing an innovative and efficient a novel Many-Objective Grasshopper Optimisation Algorithm (MaOGOA). MaOGOA incorporates reference point, niche preserve and information feedback mechanism (IFM) for superior convergence and diversity. A comprehensive array of quality metrics is utilized to characterize the preferred attributes of Pareto Front approximations, focusing on convergence, uniformity and expansiveness diversity in terms of IGD, HV and RT metrics. It acknowledged that MaOGOA algorithm is efficient for many-objective optimization challenges. These findings confirm the approach effectiveness and competitive performance. The MaOGOA efficiency is thoroughly examined on WFG1-WFG9 benchmark problem with 5, 7 and 9 objectives and five real-world (RWMaOP1- RWMaOP5) problem, contrasting it with MaOSCA, MaOPSO, MOEA/DD, NSGA-III, KnEA, RvEA and GrEA algorithms. The findings demonstrate MaOGOA superior performance against these algorithms.

"Inspired to be a teacher seriously": An autoethnography of student engagement in a Vietnamese TESOL training programme

TESOL (Teaching English to Speakers of Other Languages) training programmes in Vietnam often emphasise the significant alignment of academic knowledge with practical classroom methods. However, an intricate yet underexplored topic is understanding the dynamic engagement of student teachers in those programmes to investigate the complexities of such alignment. Therefore, this research examines factors influencing student teachers’ in-class engagement following a 120-hour TESOL training programme at an institution in Vietnam. This autoethnographic study analysed a TESOL teacher trainer’s reflections on student teachers’ engagement in the programme, using artefacts in the form of anonymous and open-ended short-text feedback from 30 students across approximately eight months. The reflection and feedback responses were analysed thematically, anchored in a framework emphasising the three facets of in-class engagement, i.e., cognitive, emotional, and behavioural dimensions. Through the analysis, three themes were constructed: (1) theoretical-practical synthesis: how TESOL-related concepts are blended with concrete teaching examples; (2) pedagogical climate: the teacher educator’s critical role in creating a receptive and engaging learning environment; and (3) professional pathway clarity: the student teachers’ understanding of their future roles and trajectories in the TESOL arena. The research’s findings provide TESOL educators with crucial insights into student teachers’ engagement with teaching methods that synthesise both theoretical and practical components. Moreover, the research enriches the academic discourse, underscoring the potential of using the cognitive, emotional, and behavioural engagement triad as a diagnostic tool to understand students’ learning experiences in TESOL training programmes.

StreetLines: A Smart and Scalable Tourism Platform Based on Efficient Knowledge-Mining

Identifying and understanding visitor needs and expectations is of the utmost importance for a number of stakeholders and policymakers involved in the touristic domain. Apart from traditional forms of feedback, an abundance of related information exists online, scattered across various data sources like online social media, tourism-related platforms, traveling blogs, forums, etc. Retrieving and analyzing the aforementioned content is not a straightforward task and in order to address this challenge, we have developed the StreetLines platform, a novel information system that is able to collect, analyze and produce insights from the available tourism-related data. Its highly modular architecture allows for the continuous monitoring of varying pools of heterogeneous data sources whose contents are subsequently stored, after preprocessing, in a data repository. Following that, the aforementioned data feed a number of independent and parallel processing modules that extract useful information for all individuals involved in the tourism domain, like place recommendation for visitors and sentiment analysis and keyword extraction reports for professionals in the tourism industry. The presented platform is an outcome of the StreetLines project and apart from the contributions of its individual components, its novelty lies in the holistic approach to knowledge extraction and tourism data mining.

Neodymium oxide concentration state recognition model in neodymium molten salt electrolysis process based on flame image features

Accurate recognition of the concentration state of neodymium-oxide (Nd2O3) in the neodymium (Nd) molten salt electrolysis process provides crucial feedback information for online adjustment of process parameters during Nd metal batch production. This paper proposes a Nd2O3 concentration state recognition model based on flame image features. The model employs the lightweight flame segmentation algorithm (FEC-Net) to accurately segment the flame regions in the collected Nd electrolysis cell flame images. Then, using image processing techniques, geometric and color features of the flame regions are extracted. Finally, a Support Vector Machine (SVM) is used to establish a nonlinear mapping model between the flame features and Nd2O3 concentration states. This model classifies the collected flame image dataset to verify the Nd2O3 concentration state during a certain period of Nd molten salt electrolysis. Experiments demonstrate that the recognition accuracy of SVM reaches 96.09%, meeting the monitoring requirements of the Nd molten salt electrolysis process.

Student teachers’ reactions to formative teacher and peer feedback

ABSTRACT Research on students’ perceptions of feedback in higher education has largely focused on students’ general preferences, with little insight into the kind of feedback that students experience. Against this backdrop, the current study investigates students’ reactions to a specific intervention which aimed, using research-informed strategies, to promote teacher and peer formative feedback with two groups of students at a teacher education institution in Norway. The qualitative analysis of 188 written reflections revealed that the students were overwhelmingly positive towards teacher feedback. Peer feedback was valued, though less favourably, suggesting that the role of peer feedback in higher education may need to be reconceptualised to recognise its strengths and acknowledge its limits. Opportunities to engage in feedback dialogue with their instructors were not exploited by the students, leading to the conclusion that such processes may need to be more formally structured and initiated by course instructors.

Controlling Markovianity with Chiral Giant Atoms.

Giant artificial atoms are promising and flexible building blocks for the implementation of analog quantum simulators. They are realized via a multilocal pattern of couplings of two-level systems to a waveguide, or to a two-dimensional photonic bath. A hallmark of giant-atom physics is their non-Markovian character in the form of self-coherent feedback, leading, e.g., to nonexponential atomic decay. The timescale of their non-Markovianity is essentially given by the time delay proportional to the distance between the various coupling points. In parallel, with the state-of-the-art experimental setups, it is possible to engineer complex phases in the atom-light couplings. Such phases simulate an artificial magnetic field, yielding a chiral behavior of the atom-light system. Here, we report a surprising connection between these two seemingly unrelated features of giant atoms, showing that the chirality of a giant atom controls its Markovianity. In particular, by adjusting the couplings' phases, a giant atom can, counterintuitively, enter an exact Markovian regime, irrespectively of any inherent time delay. We illustrate this mechanism as an interference process and via a collision model picture. Our findings significantly advance the understanding of giant atom physics, and open new avenues for the control of quantum nanophotonic networks.

Behavior-induced phase transitions with far from equilibrium patterning in a SIS epidemic model: Global vs non-local feedback

Here, we explore the phase transitions triggered by the implementation of social distancing in a basic spatiotemporal model of a qualitative SIS-type infectious disease. We consider human decisions made based on spatiotemporal information regarding the disease spread. This information can be either local, nonlocal with a finite range, or global in scope.We show that nonlocal and global feedbacks, while resulting in the same spatially homogeneous equilibria, lead to a dynamic behavior that is fundamentally distinct from what is observed when decisions are made based on local information.Various phenomena arise due to the nonlocal nature of the feedback: (i) Instabilization of Otherwise Stable Homogeneous Equilibria; (ii) Nucleation/Invasion Phenomena; (iii) Onset of Standard and Generalized Traveling Waves, which can incur in wave-pinning; iv) in case of Global Information Feedback, onset of locally stable Far From Equilibrium Patterns that coexist with a locally stable disease-elimination equilibrium. Thus, the nonlocal nature of the human behavior-related feedback introduces a rich array of dynamic behaviors and patterns in the system.

Student Experiences With Peer Review and Revision for Writing-to-Learn in a Chemistry Course Context

Peer review is useful for providing students with formative feedback, yet it is used less frequently in STEM classrooms and for supporting writing-to-learn (WTL). While research indicates the benefits of incorporating peer review into classrooms, less research is focused on students’ perceptions thereof. Such research is important as it speaks to the mechanisms whereby peer review can support learning. This study examines students’ self-reported approaches to and perceptions of peer review and revision associated with WTL assignments implemented in an organic chemistry course. Students responded to a survey covering how they approached peer review and revision and the benefits they perceived from participating in each. Findings indicate that the assignment materials guided students’ approaches during both peer review and revision. Furthermore, students described various ways both receiving feedback from their peers and reading their peers’ drafts were beneficial, but primarily connected their revisions to receiving feedback.

"Praise in Public; Criticize in Private": Unwritable Assessment Comments and the Performance Information That Resists Being Written.

Written assessment comments are needed to archive feedback and inform decisions. Regrettably, comments are often impoverished, leaving performance-relevant information undocumented. Research has focused on content and supervisor's ability and motivation to write it but has not sufficiently examined how well the undocumented information lends itself to being written as comments. Because missing information threatens the validity of assessment processes, this study examined the performance information that resists being written. Two sequential data collection methods and multiple elicitation techniques were used to triangulate unwritten assessment comments. Between November 2022 and January 2023, physicians in Canada were recruited by email and social media to describe experiences with wanting to convey assessment information but feeling unable to express it in writing. Fifty supervisors shared examples via survey. From January to May 2023, a subset of 13 participants were then interviewed to further explain what information resisted being written and why it seemed impossible to express in writing and to write comments in response to a video prompt or for their own "unwritable" example. Constructivist grounded theory guided data collection and analysis. Not all performance-relevant information was equally writable. Information resisted being written as assessment comments when it would require an essay to be expressed in writing, belonged in a conversation and not in writing, or was potentially irrelevant and unverifiable. In particular, disclosing sensitive information discussed in a feedback conversation required extensive recoding to protect the learner and supervisor-learner relationship. When written comment requests to document performance information are viewed as an act of disclosure, it becomes clear why supervisors may feel compelled to leave some comments unwritten. Although supervisors can be supported in writing better assessment comments, their failure to write invites a reexamination of expectations for documenting feedback and performance information as written comments on assessment forms.