This thesis explores the impact of peer feedback on two secondary level classrooms studying English as a foreign language in Taiwan. The effectiveness of teacher-led feedback has consistently been the focus of the relevant literature but relatively fewer studies have experimentally investigated the impact of peer-led feedback on learning. This research is based on the belief that the investigation of the process of peer-led feedback, as well as the effectiveness of peer-led correction, will enhance our understanding of learners’ communicative interactions. These data will allow us the opportunity to provide suggestions for successful second/foreign language learning. This study was conducted following a mixed-methods quasi-experimental design involving a variety of data collection and analysis techniques. Observations of peer-peer dialogues taken from a Year 7 and a Year 8 class were analysed using content analysis, in order to classify the types of peer feedback provided by the Year 7 and Year 8 learners. Pre-and post-measures, including English speaking tests, questionnaires, and checklists, were examined with non-parametric statistical tests used to explore any changes in relation to the learners’ speaking development after the quasi-experiment. Key findings included frequency and distribution of seven types of peer feedback, as used by the Year 7 and Year 8 learners, and the statistical results that revealed the differences between the pre-and post-measures. Among the seven types of peer feedback (translation, confirmation, completion, explicit indication, explicit correction, explanation and recasts), explicit correction and translation were the two techniques used most frequently by the learners. Post-test results indicated an improvement in the learners’ speaking performance. The results of pre- and post-questionnaires and pre- and post-checklists showed different levels of change in the learners’ self-evaluation of their own ability to speak English, as well as their attitudes towards corrective feedback. These results allow us to gain insight into the nature of peer interaction in communicative speaking activities as well as learners’ motives behind their feedback behaviours. Additionally, the results shed light on learners’ opinions towards corrective feedback that they received or provided in peer interaction. Further, the results yield a deepened understanding of impacts of peer feedback on L2 development by examining changes in learners’ speaking performance, self-confidence in speaking English and self-evaluation of their own ability to speak English after a peer-led correction treatment. In conclusion, the study suggests that adolescent learners are willing and able to provide each other with feedback in peer interaction. The feedback that they delivered successfully helps their peers to attend to form and has positive impacts on their peers’ English- speaking performance. Moreover, the study provides explanations for learners’ preference for certain types of feedback techniques, which hopefully helps to tackle the mismatch between teachers’ intentions and learners’ expectations of corrective feedback in the L2 classrooms.

Current research in stuttering suggests that individuals who stutter (IWS) may have a hyperactive error-monitoring system, leading to the exacerbation and anticipation of verbal dysfluencies. Using a neurophysiological marker of error processing known as the feedback error-related negativity, the current thesis involved three studies. First, a pilot study was conducted to ensure that word feedback cues were usable in the current paradigm. Second, a classic virtual T-maze task was used to assess the generic error processing mechanism of IWS. Third, an adaptation of the T-maze was used to assess the integrity of the reinforcement learning system of IWS and their ability to associate reward and error information of personalized problem words with predictive cues. Results suggest preliminary evidence for functional generic error processing in IWS and disrupted error processing when conditioned predictive cues are needed to predict fluent versus dysfluent outcomes. / Graduate

One of the fundamental limitations of mobile radio communications is their time-varying fading channel. This thesis addresses the efficient use of channel state information to improve the communication systems, with a particular emphasis on practical issues such as compatibility with the existing wireless systems and low complexity implementation. The closed-loop transmit diversity technique is used to improve the performance of the downlink channel in MIMO communication systems. For example, the WCDMA standard endorsed by 3GPP adopts a mode of downlink closed-loop scheme based on partial channel state information known as mode 1 of 3GPP. Channel state information is fed back from the mobile unit to the base station through a low-rate uncoded feedback bit stream. In these closed-loop systems, feedback error and feedback delay, as well as the sub-optimum reconstruction of the quantized feedback data, are the usual sources of deficiency. In this thesis, we address the efficient reconstruction of the beamforming weights in the presence of the feedback imperfections, by exploiting the residual redundancies in the feedback stream. We propose a number of algorithms for reconstruction of beamforming weights at the base-station, with the constraint of a constant transmit power. The issue of the decoding at the receiver is also addressed. In one of the proposed algorithms, channel fading prediction is utilized to combat the feedback delay. We introduce the concept of Blind Antenna Verification which can substitute the conventional Antenna Weight Verification process without the need for any training data. The closed-loop mode 1 of 3GPP is used as a benchmark, and the performance is examined within a WCDMA simulation framework. It is demonstrated that the proposed algorithms have substantial gain over the conventional method at all mobile speeds, and are suitable for the implementation in practice. The proposed approach is applicable to other closed-loop schemes as well. The problem of (long-range) prediction of the fading channel is also considered, which is a key element for many fading-compensation techniques. A linear approach, usually used to model the time evolution of the fading process, does not perform well for long-range prediction applications. We propose an adaptive algorithm using a state-space approach for the fading process based on the sum-sinusoidal model. Also to enhance the widely-used linear approach, we propose a tracking method for a multi-step linear predictor. Comparing the two methods in our simulations shows that the proposed algorithm significantly outperforms the linear method, for both stationary and non-stationary fading processes, especially for long-range predictions. The robust structure, as well as the reasonable computational complexity, makes the proposed algorithm appealing for practical applications.

One of the fundamental limitations of mobile radio communications is their time-varying fading channel. This thesis addresses the efficient use of channel state information to improve the communication systems, with a particular emphasis on practical issues such as compatibility with the existing wireless systems and low complexity implementation. The closed-loop transmit diversity technique is used to improve the performance of the downlink channel in MIMO communication systems. For example, the WCDMA standard endorsed by 3GPP adopts a mode of downlink closed-loop scheme based on partial channel state information known as mode 1 of 3GPP. Channel state information is fed back from the mobile unit to the base station through a low-rate uncoded feedback bit stream. In these closed-loop systems, feedback error and feedback delay, as well as the sub-optimum reconstruction of the quantized feedback data, are the usual sources of deficiency. In this thesis, we address the efficient reconstruction of the beamforming weights in the presence of the feedback imperfections, by exploiting the residual redundancies in the feedback stream. We propose a number of algorithms for reconstruction of beamforming weights at the base-station, with the constraint of a constant transmit power. The issue of the decoding at the receiver is also addressed. In one of the proposed algorithms, channel fading prediction is utilized to combat the feedback delay. We introduce the concept of Blind Antenna Verification which can substitute the conventional Antenna Weight Verification process without the need for any training data. The closed-loop mode 1 of 3GPP is used as a benchmark, and the performance is examined within a WCDMA simulation framework. It is demonstrated that the proposed algorithms have substantial gain over the conventional method at all mobile speeds, and are suitable for the implementation in practice. The proposed approach is applicable to other closed-loop schemes as well. The problem of (long-range) prediction of the fading channel is also considered, which is a key element for many fading-compensation techniques. A linear approach, usually used to model the time evolution of the fading process, does not perform well for long-range prediction applications. We propose an adaptive algorithm using a state-space approach for the fading process based on the sum-sinusoidal model. Also to enhance the widely-used linear approach, we propose a tracking method for a multi-step linear predictor. Comparing the two methods in our simulations shows that the proposed algorithm significantly outperforms the linear method, for both stationary and non-stationary fading processes, especially for long-range predictions. The robust structure, as well as the reasonable computational complexity, makes the proposed algorithm appealing for practical applications.