task-based language Teaching (TBLT) has occupied the pertinent literature for some long years. However, the role of specific task type in developing specific skill type seems to be amongst the intact issues in the literature. To shed more light on this issue, the present study was conducted to compare the effect of jigsaw and decision-making tasks on improving listening and speaking abilities of EFL learners. To this end, 75 female Iranian EFL learners, assumed homogenous based on their performance on the Nelson Test, were employed as the participants. Their listening and speaking abilities were also measured both before and after the treatment based on the listening and speaking subtests of the PET. Then, they were assigned to two groups of experimental A and B. The experimental group A received decision-making-based listening and speaking instruction for 12 sessions of 45 minutes, and the experimental group B received jigsaw-based listening and speaking instruction. In order to analyze the data, descriptive statistics and multiple inferential statistical analyses were conducted. The results revealed that those participants who experienced jigsaw listening and speaking tasks outperformed those who received decision-making-based instruction. The findings, then, bear certain theoretical implications for stakeholders.

Efficient distribution of service requests between fog and cloud nodes considering user mobility and fog nodes’ overload is an important issue of fog computing. This paper proposes a heuristic method for task placement considering the mobility of users, aiming to serve a higher number of requested services and minimize their response time. This method introduces a formula to overload prediction based on the entry-exit ratio of users and the estimated time required to perform current requests that are waiting in the queue of a fog node. Then, it provides a solution to avoid the predicted overloading of fog nodes by sending all delay-tolerant requests in the overloaded fog node’s queue to the cloud to reduce the time required for servicing delay-sensitive requests and to increase their acceptance rate. In addition, to prevent requests from being rejected when the mobile user leaves the coverage area of the current fog node, the requests in the current fog node’s queue will be transferred to the destination fog node. Simulation results indicate that the proposed method is effective in avoiding the overloading of the fog nodes and outperforms the existing methods in terms of response time and acceptance rate.

The present study investigated whether word learning and retention in a second language are contingent upon a task's involvement load, i. e., the amount of need, search, and evaluation the task imposes. Laufer and Hulstijn (2001) contend that tasks with higher degrees of these three components induce higher involvement load, and are, therefore, more effective for word learning. To test this claim, 64 Iranian intermediate EFL learners were selected based on their performance on the Preliminary English Test (PET). The participants were randomly assigned to two equal groups. Each group completed different vocabulary learning tasks that varied in the amount of involvement they induced. The tasks were jigsaw task (Group A) and information gap task (Group B). During the ten treatment sessions, recall and retention of the 100 unfamiliar target words were tested through immediate and delayed posttest. Data were analyzed using repeated measure ANOVA. The results indicated that learners benefited more from jigsaw task with higher involvement load. This study supported the Involvement Load Hypothesis, suggesting that higher involvement induced by the task resulted in more effective recall; however, no significant difference was observed between the two tasks in the retention of the unknown words.

Drawing on the tenets of task-Based Language Teaching (TBLT), this study aimed to investigate the impact of dictogloss and jigsaw tasks, facilitated by Mobile-Assisted Language Learning (MALL), on the acquisition of conditional sentences and perceptions among Iranian intermediate EFL learners. The participants included 75 learners aged 13 to 20. Following the results of an Oxford Quick Placement Test (OQPT) to ensure homogeneity, the participants were divided into two experimental groups (dictogloss, n = 25; jigsaw, n = 25) and one control group (n = 25). The experimental groups were provided with dictogloss and jigsaw tasks through Telegram. They were expected to produce the target grammatical forms while they were communicating with their peers. The results of the paired samples t-test and one-way ANOVA revealed that using dictogloss and jigsaw tasks through MALL, namely receiving instruction on mobile devices via the Telegram application, which supports both textual and voice messaging, resulted in significant improvement for the EFL learners compared to the control group. In addition, no significant difference was detected between the two experimental groups’ grammar learning. The results of the semi-structured interview uncovered that learners favored mobile-assisted TBLT due to its prominent benefits, namely engagement, motivation, interactivity, and collaboration. On the implications side, it is suggested that incorporating MALL into dictogloss and jigsaw tasks allows learners to engage with the language, collaborate with peers, and receive immediate feedback. This can help improve their overall grammar skills.

Background: Educational achievement is related to positive and negative feelings. One of the important purposes of educational systems is to enhance students' academic self-concept. Objectives This study aimed to assess the effect of the jigsaw approach on improving self-concept among university students of educational sciences. Methods: This quasi-experimental study had a pretest-posttest design with a control group. A total of 60 undergraduate students of educational sciences at Farhangian University in Sistan-Baluchestan province were selected and divided into two equal groups of 30 each, i. e. an experimental group and a control group. Liu and Wang academic self-concept scale was applied as a data collection tool and twelve 90-minute sessions of the jigsaw approach were collaboratively conducted on the students who met the inclusion criteria in 6 weeks (two sessions per week). Data were analyzed using a multivariate analysis of covariance. Results: Results of the one-way analysis of covariance show that academic self-concept and the subscales of academic confidence and academic effort are significantly different between the control and experimental groups (error level < 5%). The jigsaw approach had a direct effect on academic effort and improved students' academic self-concept. Conclusions: Academic self-concept plays an essential role in students' achievement. Some students do not know how to act and learn in groups, so they isolate themselves. This isolation can lead to feelings of loneliness or fear of others, but collaborative and cooperative approaches such as jigsaw technique help shape students' self-concept and communicate with others.