Earticle

The purpose of this study is to explore the effects of peer feedback combined with different task sequences on written performance in actual large-sized classrooms motivated by several problems in previous peer feedback studies—validity concerns in research design, peer feedback as only productoriented activity, the lack of effects of feedback on detailed written performance, and primary focus on affective and writing quality. A total of 89 undergraduates were divided into two groups: peer feedback in simple-complex task sequence (PSC) and peer feedback in complex-simple task sequence (PCS). The study employed eleven general and specific measure indices of syntactic complexity, accuracy, and fluency. The findings were that peer feedback influenced accuracy and fluency, and task sequence influenced syntactic complexity. The PSC increased general and specific accuracy, but decreased fluency, whereas the PCS increased general and specific syntactic complexity, specific accuracy, and fluency. Overall, peer feedback in a simple-complex task sequence improved accuracy in an extended manner, and peer feedback in complex-simple task sequence improved various aspects of written performance. The study suggests peer feedback could be a feasible way to improve actual written performance even in large writing classes when task sequences and task complexity are involved with peer feedback.

Purpose: Implicit motor learning is the capacity to acquire skill through physical practice without conscious awareness of what elements of performance improved. This study investigated whether subacute stroke patients can implicitly learn a perceptual-motor task. Methods: We recruited 12 patients with subacute stroke and 12 age-matched controls. All participants performed a perceptual-motor task that involved pressing a button corresponding with colored circles (blue, green, yellow, red) on a computer screen. The task consists of 7 blocks composed of 10 repetitions for a repeating 12-element sequence (total 120 responses). Results: Both groups demonstrated significant improvement in acquisition performance. Reaction times deceased in both groups at similar rate within the sequential block trials (2-5 blocks), and reaction times increased at a similar rate when the task paradigm was transferred from the sequential block trial to the random block trial (5-6-7 blocks). Conclusion: The results of this study suggest that patients with sub-actue stroke can implicitly learn a perceptual motor skill. Although explicit instructions should be used to focus the learner's attention rather than provide information about the task, the application of implicit motor learning strategies in the rehabilitation setting may be beneficial.

This study examines the effects of the sequence of increasing task complexity in different modalities on the learning of the English past tense of Korean secondary learners. Robinson’s (2007) Cognition Hypothesis argued that learners pay more attention to grammatical forms in complex tasks than in less complex tasks. He suggested that tasks should be sequenced in such a way that resource-dispersing dimensions are first increased in complexity followed by an increase in the complexity of resource-directing dimensions. However, little empirical research has been done on how tasks are sequenced according to their cognitive complexity and how task modality affects second language development in the sequence. Fifty-four learners were divided into an integrated (writing with oral interaction) task group (EG 1), an oral-only task group (EG 2) and a comparison group (CG). After the sequence of six tasks was completed, one-way ANOVA revealed the EGs outperformed the CG significantly on the posttest. The mean score of EG 1 was the highest, while the improvement rate of EG 2 was the highest among the three groups. It is hoped that this result will contribute to building a solid basis on which practitioners can make decisions about sequencing tasks and implementing task modality.

본 연구팀은 프레스 공정의 협소공간에서 작업이 가능한 6자유도 로봇을 개발하고 있으며, 본 논문은 개발된 로봇의 작업 시간을 최소화하기 위한 작업 시퀀스 최적화 방법을 제안하였다. 우선 6 자유도 로봇의 기구학을 모델링하고 작업 시간 예측 방법을 기술하였다. 그리고 작업 시퀀스 최적화를 위하여 수학적 모델을 제시하고, 이를 바탕으로 개미 집단 시스템(ant colony system), 시뮬레이트 어니일링(simulated annealing), 유전자 알고리즘(genetic algorithm)의 세 가지 최적화 방법을 적용하고 결과를 비교 분석하였다. 시뮬레이션 결과 유전자 알고리즘이 가장 좋은 결과를 보임을 확인할 수 있었으며, 계산 속도 측면에서도 가장 빨리 최적값에 수렴하였다. 또한, 개미집단시스템과 시뮬레이티드 어니일링의 경우 여러 파라미터 값들의 설정에 따라 수렴된 최적값의 편차가 비교적 큰 것에 비하여, 유전자 알고리즘은 파라미터 값에 상관없이 안정적으로 근사 최적값을 찾을 수 있었다. 마지막으로, 로봇의 작업시퀀스 최적화 방법을 시각적으로 검증하기 위하여 Mathworks 사의 Matlab과 Coppelia Robotics 사의 V-REP (virtual robot experimentation platform)를 사용한 시뮬레이션을 수행하였다.

Our research team is developing a 6-DOF manipulator that is adequate for the narrow workspace of press forming processes. This paper addresses the task sequence optimization methods for the manipulator to minimize the task-finishing time. First, a kinematic model of the manipulator is presented, and the anticipated times for moving among the task locations are computed. Then, a mathematical model of the task sequence optimization problem is presented, followed by a comparison of three meta-heuristic methods to solve the optimization problem: an ant colony system, simulated annealing, and a genetic algorithm. The simulation shows that the genetic algorithm is robust to the parameter settings and has the best performance in both minimizing the task-finishing time and the computing time compared to the other methods. Finally, the algorithms were implemented and validated through a simulation using Mathworks' Matlab and Coppelia Robotics' V-REP (virtual robot experimentation platform).

MSC는 통산 소프트웨어에서의 병행 수행 테스크들 사이의 상호작용을 기술하기 위해서 많이 사용되어져 왔다. 요구사항 단계에서 검증된 MSC 명세는 상태 기반의 설계 모델을 합성하는데 사용될 수 있을 뿐만 아니라, 테스크 시퀀스 생성에 사용될 수도 있다. 지금까지는 MSC에 기술된 각 이벤트의 위치 정보만을 이용하여 전체 상태 그래프를 생성함으로써 검증을 수행하였다. 본 논문에서는 MSC의 조건문을 시나리오 활성화 조건과 상태 변경을 기술할 수 있도록 확장하고, 이를 이용하여 전체 상태 그래프를 생성함으로써 테스크 시퀀스 생성에 이용한다. 생성된 전체 상태 그래프인 GFSM은 시스템의 의미 있는 상태 정보와 가능한 메시지 시퀀스만을 가지게 된다. 생성된 GFSM에 기존인 FSM 기반의 테스팅 기법을 적용하여 테스크 시퀀스를 추출할 수 있다.

Message Sequence Charts(MSC) has been used to describe the interactions of numerous concurrent tasks in telecommunication software. After the MSC specification is verified in requirement analysis phase, it can be used not only to synthesize state-based design models, but also to generate test sequences. Until now, the verification is accomplished by generating global state transition graph using the location information only. In this paper, we extend the condition statement of MSC to describe the activation condition of scenarios and the change of state variables, and propose an approach to construct global finite state machine (GFSM) using this information. The GFSM only includes feasible states and transitions of the system. We can generate the test sequences using the existing FSM-based test sequence generation technology.