Error Correction Feedback Research Articles

Transfer effects of recursive self-feedback on connected speech production in patients with chronic nonfluent aphasia: Preliminary results

ABSTRACT Background Persons with nonfluent aphasia (PWNA) have deficits with online feedback for speech error detection and correction which have debilitating effects on language relearning in learned and novel contexts. Previous studies have shown that aphasia treatments that combine PWNA’s offline self-feedback and external feedback from speech-language pathologists (SLPs) improve language production in learned and novel contexts. However, it remains unclear whether PWNA can use their offline self-feedback alone during treatments that generalizes to improvement in connected speech production. Here, we examine generalization effects of recursive self-feedback on PWNA’s connected speech production. Recursive self-feedback utilizes offline self-feedback loops alone to help PWNA optimize their error monitoring and correction abilities for language production in learned and novel contexts. Method A crossover design was used to investigate generalization effects of two treatments on connected speech production in four PWNA. These treatments comprised script production with recursive self-feedback and script production with external feedback. Employing a mobile health approach, treatments were remotely administered to participants within the comfort of their homes. Practice of both treatment blocks occurred intensively over two hours per day, five days per week, spanning two to three weeks. Each treatment block featured pretreatment and posttreatment assessment phases, with the sequencing of treatment blocks evenly counterbalanced across all participants. Following the initial treatment block, a two-week period devoid of treatment preceded the commencement of the second treatment block. Untrained narrative elicitation tasks were utilized to prompt connected speech production samples from all participants during the assessment phases of each treatment block. Effect sizes per participant were computed using within-case standard mean difference analysis. Results PWNA exhibited variability in performance, showing improvement in microlinguistic measures of connected speech following both script production with recursive self-feedback and script production with external feedback. Particularly, script production with recursive self-feedback demonstrated marginally superior enhancement in connected speech measures compared to its counterpart. Conclusion The study provides preliminary evidence for generalization effects of recursive self-feedback training and external feedback training on PWNA’s connected speech production. Further research is required to corroborate the findings and to implement recursive self-feedback procedures optimized specifically for spontaneous speech.

Optimizing video feedback for snatch technical error correction in young weightlifters: Comparing the effectiveness of different video playback speeds

Researchers are actively recommending optimal modes of usage for techno-pedagogical tools to ensure that athletes reap the benefits of technology in their training. In this study, we investigated the most effective video feedback viewing speed among normal-speed (NS), half-speed (HS), and quarter-speed (QS), for technical error correction in young weightlifters during the snatch movement. A total of 37 weightlifters (25 boys and 12 girls), aged 11–12 years, were randomly divided into three groups, namely the normal-speed (control group), the half-speed, and the quarter-speed group. Participants completed a pretest (T0), a seven-week snatch learning unit, and a posttest (T1), as well as a retention test one week later (T2). Video-mediated technical analysis of the snatch movement was conducted using the Kinovea motion analysis software. The main results showed that weightlifters who viewed their feedback videos at a quarter of the normal speed (QS) achieved significantly greater improvements in the displacement of the bar in the first pull Dx2 (T1 vs. T0: 27.41 ± 26.10%, Hedges’ g = 0.87, p < 0.05; T2 vs. T0: 24.34 ± 27.11%, Hedges’ g = 1.07, p < 0.05) and the vertical displacement VTR (T1 vs. T0: 22.89 ± 14.16%, Hedges’ g = 1.16, p < 0.05) compared to those who viewed the videos at NS or HS. These findings suggest that slowing down video feedback playback to a quarter of the normal speed can be an effective strategy for enhancing technical error correction in young weightlifters.

Learner interaction with, and response to, AI-programmed automated writing evaluation feedback in EFL writing: An exploratory study

Recently, artificial intelligence (AI)-programmed automated writing evaluation (AWE) has attracted increasing attention in language research. Using a small data set arising from an analysis of five Chinese university-level English as a foreign language (EFL) students’ submissions, this paper examined in detail how EFL students interacted with the feedback of Pigai, the largest AI-programmed AWE in China. The analysis started with the intention of capturing the machine feedback on the five students’ submissions and the exchanges between the participants and Pigai over repeated submissions, ranging from 3 to 12 submissions. The analysis showed that the learners’ interactions with Pigai focused on error corrective feedback in the initial two submissions. In the case of one student who had 12 submissions, the non-error corrective feedback increased gradually over time, providing rich linguistic resources but without examples and contextual information. The students’ take-up rates of feedback with linguistic resources were much lower than that of error corrective and general feedback. A terrain model to map the stages and nature of student responses showed a more complete dynamic process, in which students’ responses changed from the initial mechanical responses at the discrete language level to more considered approaches in response to machine feedback. The findings of this study have implications for both language pedagogy and the future design and development of AWE for second or foreign language learning.

The Effect of Error Correction on Taiwanese EFL Students’ Writing Accuracy

This paper aims to investigate the effect of teacher’s error correction feedback on EFL students’ ability to correct their own writing errors for better accuracy. It intends to find out whether the instructor’s explicit error feedback followed by students’ extensive revisions, has any effect on students’ ability in revising their errors with their own writing pieces. A group of nineteen EFL Taiwanese college students, with low to intermediate English level proficiency, participated in this study. The results indicated that the effect of teachers’ error feedback on students’ ability to self-correct was not significant. Most of the errors, after given extensive feedback and revision, were not significantly revised after a three-month interval. The result of this case study tends to support the claim that teachers’ error feedback does not help much with EFL students improving their writing accuracy. Other findings regarding students’ interpretation towards their writing errors and unsatisfactory self-correction results and teacher’s perspective and observation are discussed.

Improved Short-Term Wind Power Forecasts: Low-Latency Feedback Error Correction Using Ramp Prediction and Data From Nearby Farms

Improved Short-Term Wind Power Forecasts: Low-Latency Feedback Error Correction Using Ramp Prediction and Data From Nearby Farms

Optimal combination of forward error correction and selective state feedback for wireless feedback control systems

In wireless feedback control systems, loss of control packets due to unreliable wireless channels is one of the most important problems. To cope with this problem, we have proposed a novel concept that combines forward error correction (FEC) and selection of important state feedback while keeping a fixed packet length. In this paper, we provide its optimization based on a control layer’s theorem. Numerical results show that the proposed method can achieve the best control performance against communication channel errors.

Role of Instructor Qualifications, Assessment and Pedagogical Practices in EFL Students’ Grammar and Writing Proficiency

Three groups of EFL freshman students were concurrently enrolled in a grammar and a writing course. One group was taught the grammar and writing courses by the same instructor; the other two groups were taught grammar and writing by two different instructors using the same textbook but different instructional and assessment techniques. The study aims to find out which group made higher gains in grammatical knowledge and writing skill development. It also aimed to find out the effects of instructor qualifications, assessment, and pedagogical variables on students’ grammatical competence and writing skill development. Comparisons of the grammar and writing post-tests showed significant differences between the three groups in the writing and grammar post-test mean scores. There were strong correlations between the grammar and writing post-test scores. Performance of the Group that received a combination of writing and grammar instruction by the same instructor (Instructor A) was the highest. The relationship between grammar and writing instruction seems to be reciprocal: writing instruction affects grammatical competence and grammatical knowledge affects writing skill development. Better achievements were made when both courses were taught by the same instructor as she can make the right connections between what is taught in both courses, which specific structures and skills should be emphasized. The instructors’ qualifications, pedagogical system, educational and professional experience, the integration of online instruction, the type of error correction and instant feedback given to the students and the formative assessment technique used were significantly more effective than writing/grammar instruction that depended on the textbook alone. These variables proved to be important for enhancing the grammatical knowledge and writing quality of unskilled, low ability EFL students and resulted in a significant improvement in their grammar and writing post-test scores.

STUDENTS’ PREFERENCES OF THE RESEARCH PROPOSAL WRITING FEEDBACK

Students' feedback preferences are essential in the research proposal writing process. This research aims to reveal the students' preferences toward the supervisor has written feedback and the types of written feedback provided by the supervisors in the students' research proposal in terms of the error correction feedback and the comment feedback. This research employed a mixed-method design. There were 39 samples chosen purposively to gain the quantitative data and 16 documents chosen from five random students to gain the qualitative data. Based on the data analysis, the type of error correction feedback and comment feedback preferred by the students respectively are the direct error correction feedback with the score of 155 (38,46%) and the directive comment feedback with 293 (22,37%). Besides, the type of error correction feedback and comment feedback provided by the supervisors respectively are the direct error correction feedback with 79 (51,97%) scores and the referential comment feedback with the scores of 206 (63,00%). This study implies that various feedback should address the students' preferences and learning styles since the outputs are their academic writing achievement.

A classroom research study on use of oral corrective feedback at an EFL university

This study aims to investigate which types of errors lead to which types of corrective feedback and their distribution in university preparatory school speaking classes. Discourse analytic principles were used to analyze the learners' errors and types of oral corrective feedback in communicatively oriented speaking classes. The frequency and distribution of error types and corrective feedback are examined. Three instructors teaching English speaking courses at B1 level of the Common European Framework of Reference for Languages in different classes participated in the study. The data, consisting of six videotaped lessons, were transcribed for coding and analysis according to the system proposed by Lyster and Ranta (1997). First, four error types and seven types of corrective feedback were coded and then, the relationship between the feedback type and error type was examined. The results showed that the most commonly used feedback type is recast. This is followed by a translation and explicit correction. Metalinguistic feedback, elicitation, clarification requests, and repetitions are not common feedback types. Looking at the relationship between the type of corrective feedback and the type of error, grammatical errors were the most common type, but were corrected the least. On the other hand, lexical errors were the least frequent but were the most frequently corrected error type.

Coherent Ising Machines with Optical Error Correction Circuits

AbstractA coherent Ising machine (CIM) comprising a network of open‐dissipative quantum oscillators with optical error correction circuits is proposed. In the proposed network, the squeezed/anti‐squeezed vacuum states of the constituent optical parametric oscillators establish quantum correlations below the threshold through optical mutual coupling and collective symmetry breaking is induced above the threshold as a decision‐making process. This initial search process is followed by a chaotic solution search step facilitated by optical error correction feedback. The particular algorithm used by the proposed network is derived from the truncated Wigner stochastic differential equation. As an optical hardware technology, the proposed CIM has several unique features, including programmable all‐to‐all Ising coupling in the optical domain, directional coupling ()‐induced chaotic behavior, and the ability to operate at low power at room temperature. The proposed CIM is evaluated in terms of its performance and how this scales at different problem sizes. It is shown that the various CIMs discussed in this paper are effective at solving many problem types, although the optimal algorithm depends on the problem case. It is further shown that the proposed optical implementations can be achieved with low energy consumption on thin‐film LiNbO3 platforms.

Predictive coding feedback results in perceived illusory contours in a recurrent neural network

Modern feedforward convolutional neural networks (CNNs) can now solve some computer vision tasks at super-human levels. However, these networks only roughly mimic human visual perception. One difference from human vision is that they do not appear to perceive illusory contours (e.g. Kanizsa squares) in the same way humans do. Physiological evidence from visual cortex suggests that the perception of illusory contours could involve feedback connections. Would recurrent feedback neural networks perceive illusory contours like humans? In this work we equip a deep feedforward convolutional network with brain-inspired recurrent dynamics. The network was first pretrained with an unsupervised reconstruction objective on a natural image dataset, to expose it to natural object contour statistics. Then, a classification decision head was added and the model was finetuned on a form discrimination task: squares vs. randomly oriented inducer shapes (no illusory contour). Finally, the model was tested with the unfamiliar “illusory contour” configuration: inducer shapes oriented to form an illusory square. Compared with feedforward baselines, the iterative “predictive coding” feedback resulted in more illusory contours being classified as physical squares. The perception of the illusory contour was measurable in the luminance profile of the image reconstructions produced by the model, demonstrating that the model really “sees” the illusion. Ablation studies revealed that natural image pretraining and feedback error correction are both critical to the perception of the illusion. Finally we validated our conclusions in a deeper network (VGG): adding the same predictive coding feedback dynamics again leads to the perception of illusory contours.

Day‐ahead and intra‐day wind power forecasting based on feedback error correction

The major hindrance in the development of large-scale grid integration of wind energy into the power system is the production of intermittent and variable power. A largescale integration requires a forecasting mechanism to support the power system operators while operating the grids. This study forecasts the day-ahead and intra-day wind power using the wavelet decomposition, followed by the autoregressive integrated moving average. The forecasting has been attempted on two datasets, actual and error wind power. The forecasting using the wavelet decomposition employs the discrete wavelets consisting of 16 wavelets, grouped into 5 families. The optimum length of the past data used for the model formulation has also been examined for the various scenarios. The forecasting results have been compared based on various performance metrics. The results of the forecasted values have been compared with the reference ARIMA model to see the effectiveness of the proposed wavelet-ARIMA model. The results indicate that the feedback mechanism used in the error dataset have improved the forecasting efficiency over the use of actual data in both the day-ahead and intra-day forecasting. Also, it has been observed that some of the wavelet families outperformed the other families in terms of accuracy and speed.

How effectively can EFL students use automated written corrective feedback (AWCF) in research writing?

AWCF can facilitate academic writing development, especially for novice writers of English as a foreign language (EFL). Existing AWCF studies mainly focus on teacher and learner perceptions; fewer have investigated the error-correction effect of AWCF and factors related to the effect. Especially lacking is research on how successfully students can use AWCF to correct errors in source-based academic writing. Meanwhile, Grammarly, an automated writing evaluation (AWE) tool, is under-represented in AWCF studies despite its extensive use in EFL classrooms and its significant advantages. Correspondingly, we evaluated how effectively EFL students could use Grammarly-provided feedback for error correction in research writing and what factors were related to user responses (i.e., revision operations) and response accuracy. The results show that the error scores decreased significantly after revision and the participants correctly addressed 85% of the Grammarly-flagged usages. The error-correction success was impressive, considering how the technical nature of research writing might affect feedback accuracy and user responses, both related to response accuracy. In fact, feedback accuracy contributed to response accuracy both directly and indirectly (via user responses). The findings have implications for source-based academic writing instruction and AWE tool development.

Joint Image Dehazing and Super-Resolution: Closed Shared Source Residual Attention Fusion Network

In real world, due to the existence of floating particles such as smoke and dust in the atmosphere, images taken by camera are susceptible to different levels of blurring, low contrast, color distortion and visual degradation, which would be amplified when enlarging the image resolution. Therefore, it is a new trend to join the image dehazing and image super-resolution tasks. To generate sharp high-resolution images from low-resolution images with severe haze, a common way is to connect the dehazing network and the super-resolution network in series. However, two-stage joint approach easily introduces blurring artifacts and is time-consuming. In addition, although there are a few existing one-stage methods, their training modes are relatively complicated and the restoration effects on some texture details are still blurry. In this paper, we focus on exploring one-stage joint model and propose a back-projection network based on shared source attention fusion (BPSAF), which forms a closed frame through back-projection mechanism. BPSAF can remove non-uniform haze and extend the resolution simultaneously. Specifically, a shared source attention fusion (SAF) module is presented to fuse high-frequency information of different level features using shared source skip connections more effectively, which filters out abundant thin haze and low-frequency information from merged images. To enhance the definition of restored images, a feedback error correction module based on error attention mechanism (FEC-EA) is designed to further correct distorted texture details by eliminating the feedback error from initial super-resolution result to the input hazy image. Experimental results demonstrate that our back-projection framework is superior to other existing methods in terms of quantitative indicators and visual quality.

A study on using corrective feedbacks in teaching essays at school of foreign languages, Thai Nguyen university

The ability of writing is considered as a main communication skill and “a unique asset” in SLA (Chastain, 1998) that language learners should be fully aware of. Methodology in teaching writing therefore has experienced considerable changes in the approach to teaching and assessing learners. Written corrective feedback as a response channel to students’ writings in SLA classrooms has been a topic of inclusive debates and inquiries amongst the scholarly sphere. Contributing to this bulk of controversy, the present study investigates teachers’ perceptions and their students’ attitudes and evaluations as to the practice of error corrective feedback. To collect data, two different questionnaires of suitable reliability were delivered to sample respondents of 12 teachers and 34 students respectively to elicit data catering the study’s purposes. Findings were also triangulated with 5 participant teachers invited for follow up interviews and a comparative reference to previous studies on written corrective feedbacks. The results revealed that there are no dramatic differences in teachers’ attitudes towards the usefulness of written corrective feedbacks. However, when it comes to types and amount of errors they should comment on, teachers’ responses and preference cover a wide spectrum.

The Relation of Articulatory and Vocal Auditory-Motor Control in Typical Speakers.

Purpose The purpose of this study was to explore the relationship between feedback and feedforward control of articulation and voice by measuring reflexive and adaptive responses to first formant (F 1) and fundamental frequency (f o) perturbations. In addition, perception of F 1 and f o perturbation was estimated using passive (listening) and active (speaking) just noticeable difference paradigms to assess the relation of auditory acuity to reflexive and adaptive responses. Method Twenty healthy women produced single words and sustained vowels while the F 1 or f o of their auditory feedback was suddenly and unpredictably perturbed to assess reflexive responses or gradually and predictably perturbed to assess adaptive responses. Results Typical speakers' reflexive responses to sudden perturbation of F 1 were related to their adaptive responses to gradual perturbation of F 1. Specifically, speakers with larger reflexive responses to sudden perturbation of F 1 had larger adaptive responses to gradual perturbation of F 1. Furthermore, their reflexive responses to sudden perturbation of F 1 were associated with their passive auditory acuity to F 1 such that speakers with better auditory acuity to F 1 produced larger reflexive responses to sudden perturbations of F 1. Typical speakers' adaptive responses to gradual perturbation of F 1 were not associated with their auditory acuity to F 1. Speakers' reflexive and adaptive responses to perturbation of f o were not related, nor were their responses related to either measure of auditory acuity to f o. Conclusion These findings indicate that there may be disparate feedback and feedforward control mechanisms for articulatory and vocal error correction based on auditory feedback.

Coherent Ising machines—Quantum optics and neural network Perspectives

A coherent Ising machine (CIM) is a network of optical parametric oscillators (OPOs), in which the “strongest” collective mode of oscillation at well above threshold corresponds to an optimum solution of a given Ising problem. When a pump rate or network coupling rate is increased from below to above threshold, however, the eigenvectors with the smallest eigenvalue of the Ising coupling matrix [Jij] appear near threshold and impede the machine to relax to true ground states. Two complementary approaches to attack this problem are described here. One approach is to utilize the squeezed/anti-squeezed vacuum noise of OPOs below threshold to produce coherent spreading over numerous local minima via quantum noise correlation, which could enable the machine to access either true ground states or excited states with eigen-energies close enough to that of ground states above threshold. The other approach is to implement a real-time error correction feedback loop so that the machine migrates from one local minimum to another during an explorative search for ground states. Finally, a set of qualitative analogies connecting the CIM and traditional computer science techniques are pointed out. In particular, belief propagation and survey propagation used in combinatorial optimization are touched upon.

Coherent Ising Machines with Error Correction Feedback

AbstractA nonequilibrium open‐dissipative neural network, such as a coherent Ising machine based on mutually coupled optical parametric oscillators, has been proposed and demonstrated as a novel computing machine for hard combinatorial optimization problems. However, there is a challenge in the previously proposed approach: The machine can be trapped by local minima which increases exponentially with a problem size. This leads to erroneous solutions rather than correct answers. In this paper, it is shown that it is possible to overcome this problem partially by introducing error detection and correction feedback mechanism. The proposed machine achieves efficient sampling of degenerate ground states and low‐energy excited states via its inherent exploration property during a solution search process.

Punctuation Errors in Writing: A Comparative Study of Students’ Performance from Different Pakistani Universities

The study aimed at exploring the different types of punctuation errors made by students in their writings, the reasons behind these errors, and the reasons behind the differences in the frequency of punctuation errors made by students from two different sets of universities, with one set belonging to backward areas and the other set to well-developed areas. The universities selected from the backward areas were Kohat University of Science and Technology (KUST) Kohat, University of Malakand (UoM), Shaheed Benazir Bhutto University (SBBU), Sheringal University (SU) and Khushal Khan Khattak University (KKKU), Karak and the universities selected from developed areas were National University of Modern Languages, (NUML) Islamabad, International Islamic University (IIU), Islamabad, University of Sargodha (UoS) and Gomal University(GU), Dera Ismail Khan. The study used Corder (1975)’s Error Analysis approach for analysing the errors. The study used mixed-method research design. The sample included a total of 200 students, out of which 25 students were selected from each university through simple random sampling technique. Test and interviews were used as instruments for data collection. For the identification of punctuation errors, the students were made to take a punctuation test. A probe was made into the possible reasons behind the punctuation errors by interviewing the students. The data collected was analysed by using content analysis technique. The study revealed that the most frequent errors were errors related to comma, apostrophe, and capitalization. The analysis of the interviews showed that the lack of practice on punctuation marks, lack of teaching punctuation within context, lack of checking of punctuation errors and lack of error corrective feedback on the punctuation errors were the major reasons behind the differences in the frequency of punctuation errors.

EFL Teachers’ Practice and Learners Preferences for Oral Error Corrective Feedback in EFL Speaking Class

By using descriptive research design with quantitative and qualitative data gathering method, this study attempted to asses EFL (English as a Foreign Language) teachers practice of giving oral error corrective feedback and learners preferences for oral error correction. In doing so, data were gathered from grade 11 students and their English language teachers. Three English languages teachers were included for observation and interview by using comprehensive sampling technique and eight students were also selected for interview by using purposive sampling technique. Each teacher was observed three times and a total of nine classroom observations were made on four classes while EFL teachers teach speaking skills, and the data were recorded for three hundred sixty minutes. To gather quantitative data, questionnaires consists of four major parts were used. On the other hand data from classroom observations, teachers’ and students’ interview were analyzed qualitatively. Findings of the study revealed that EFL teachers always give oral corrective feedback on learners’ oral error. Teachers were found using explicit correction strategies most of the time. Learners prefer to be corrected by their teacher always and teachers were also found to be the dominant corrector of learners’ oral error. This indicated that EFL teachers’ actual classroom practice is divorced with some scholarly suggested pedagogical consideration. Keywords: Oral error, corrective feedback, practice, preferences DOI: 10.7176/JLLL/66-01 Publication date: March 31 st 2020