Teacher-mediated classroom assessment might have significant impacts on learners' academic achievements and teachers' development. The current study investigated teachers' assessment literacy and its impact on their current assessment practices and learners' writing outcomes. The study sought to gain an understanding of the extent to which teachers' assessment literacy affects their practices and their learners' outcomes. To conduct the study and gather the required data, the researchers employed teachers' assessment literacy inventory, semi-structured interview, non-participatory observation, and Writing Competence Rating Scale (WCRS). Ten male EFL instructors and 75 male sophomores from Iranian EFL contexts were selected from four language schools in Iran. The results of the study indicated that teachers' assessment literacy has a statistically significant impact on learners' writing achievements and teachers' assessment awareness leads teaching environments into effective and motivated assessment design. These findings suggest language educators considering teachers' assessment awareness in their teacher education programs.

In this paper, a novel constructive-optimizer neural network (CONN) is proposed for the traveling salesman problem (TSP). CONN uses a feedback structure similar to Hopfield-type neural networks and a competitive training algorithm similar to the Kohonen-type self-organizing maps (K-SOMs). Consequently, CONN is composed of a constructive part, which grows the tour and an optimizer part to optimize it. In the training algorithm, an initial tour is created first and introduced to CONN. Then, it is trained in the constructive phase for adding a number of cities to the tour. Next, the training algorithm switches to the optimizer phase for optimizing the current tour by displacing the tour cities. After convergence in this phase, the training algorithm switches to the constructive phase anew and is continued until all cities are added to the tour. Furthermore, we investigate a relationship between the number of TSP cities and the number of cities to be added in each constructive phase. CONN was tested on nine sets of benchmark TSPs from TSPLIB to demonstrate its performance and efficiency. It performed better than several typical Neural networks (NNs), including KNIES_TSP_Local, KNIES_TSP_Global, Budinich's SOM, Co-Adaptive Net, and multivalued Hopfield network as wall as computationally comparable variants of the simulated annealing algorithm, in terms of both CPU time and accuracy. Furthermore, CONN converged considerably faster than expanding SOM and evolved integrated SOM and generated shorter tours compared to KNIES_DECOMPOSE. Although CONN is not yet comparable in terms of accuracy with some sophisticated computationally intensive algorithms, it converges significantly faster than they do. Generally speaking, CONN provides the best compromise between CPU time and accuracy among currently reported NNs for TSP.

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Peer evaluation and technology-based instruction as the various domains of language teaching perspectives might affect language development. Group work in a technology-based environment might be more successful when learners are involved in developing the assessment process particularly peer assessment. This study investigated the effectiveness of peer evaluation in technology-based language environment and its effects on English writing ability. To reach this goal, 70 Iranian learners were participated in English language writing context. They were divided into two groups, one group assigned to CMC (Computer-Mediated Communication) language learning context and the other assigned to a traditional learning environment. Both groups were encouraged to evaluate their classmates' writing tasks. In addition, interviews were conducted with two learners. Comparing these two groups provides comprehensive guidelines for teachers as well as curriculum designers to set adjusted writing language environment for more effective and creative language teaching and learning. E-collaboration classroom tasks have high intrinsic motivation as well as significant effects on learners' outcomes. Cooperative tasks specifically in technology-based environment lead learners to group working and consequently group learning. Computer-Mediated Communication is meaningful, especially in contexts in which teachers stimulate group work activities.