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Showing 5 results for Academic Engagement

En Ezatolah Ghadampour, En Parvaneh Radmehr, En Leila Yousefvand,
Volume 3, Issue 33 (2-2017)
Abstract

The aim of the present study was to examine the effect of group training based on schnyder hope theory on level academic engagement and hardiness girl students in first grade. The present study was method of sup-experimental with pre-test - post-test and follow-up design with control group. This study population included all high school girl students in first grade of Khorramabad city the academic 2015-16. Sample size of 50 individuals (25individuals' experimentation and 25 individuals 'control group) using multi-stage random cluster were selected. The only experimental group was group training based on schnyder hope theory, after the training Meetings, from both the experimental and control groups post-test and again two months later, both groups were followed up. In this study measuring tool, questionnaire academic engagement Schafeli et al (2001) and academic hardiness Khobasa et al (1982) . Analysis of the data was done using SPSS-19 and descriptive and inferential tests such as covariance analysis were conducted. The results study showed that training of group training based on schnyder hope theory had a significant effect on academic engagement (P<0/001) and academic hardiness (P<0/01). Findings were also preserved in the follow up Phase.


Masoud Siyami, Shahla Rostami, ,
Volume 4, Issue 35 (9-2017)
Abstract

 
This study was carried out to provide a structural model for illustrating the structural relationships between the amount of mobile phone usage and academic engagement with mediating role of attention in students at the University of Birjand. The statistical population of this study included all students studying at Birjand University in the academic year 2015-2016. Sample included 200 students from Birjand University who were selected using cluster sampling. The instruments used in this study were Jafarzadeh mobile phone addiction questionnaire (2012), Schofield et al engagement questionnaire (1996) and Wechsler inverse number test. Data was tested by path analysis. The findings showed that the amount of mobile phone usage, influences students' attention. In other words, the amount of students' academic attention and engagement decreases with increasing use of mobile phones. These findings show the need for serious attention from the authorities on the negative consequences of students’ mobile phone usage. It showed that the use of mobile phones to be a good predictor of student academic engagement.
 


Elham Heidari, Rahmatalah Marzoghi,
Volume 6, Issue 39 (12-2019)
Abstract

The purpose of this study was to assessment of the effect of supervisor's supervision quality on academic engagement and student's procrastination to do Ph.D dissertation. The research method was descriptive correlational method. The research sample consisted of 201 students of Shiraz University who were selected by Stratified random sampling. The research tools consist of supervisor's supervision quality measurement scale (Herman et al., 2014), academic engagement (Shafley and Bucker, 2006), and academic procrastination (McCullozy, 2011) that after calculating their validity and reliability, they were distributed among the samples and the data were analyzed using structural equation model. The findings showed that the supervisor's supervision quality has a positive and significant effect on the student's academic engagement. However, students' academic engagement has a negative and significant effect on the student's procrastination in doing Ph.D dissertation. Also, the supervisor's supervision quality has a negative and significant effect on the student's procrastination in doing Ph.D. dissertation.

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Volume 10, Issue 44 (4-2022)
Abstract

The aim of this study was to investigate the effectiveness of academic aid strategies on academic well-being, academic engagement and academic achievement of students. In this quasi-experimental study, a population of 721 people from Payame Noor Khalkhal University in the second semester of 2020-2021, using single-stage cluster sampling method and in order to determine the sample size in accordance with the research plan of the number 60 people were randomly replaced in two groups of 30 people, one experimental group and one control group. To collect information, the educational package of Alon et al.'s (2006) help-seeking strategies, Tominen-Svini et al. (2012) academic welfare questionnaire, Zarang (2012) and Pham and Taylor (1999) academic performance scale were used. Finally, multivariate analysis of covariance based on SPSS software version 22 was used to analyze the data. The results showed that the mean scores of post-test of academic well-being in the experimental group were significantly higher than the control group (p <0.01 and F = 18.582 (1, 57)). There was no difference in the academic engagement test in the experimental and control groups, and the mean scores of the academic performance post-test in the experimental group were higher than the control group (p <0.01 and F = 18.809 (57 and 1). The final result shows that academic help strategies as an intervention approach along with the psychological structures of academic well-being and academic engagement, if well designed, planned and implemented, can affect academic performance.
 
Mrs Narges Aeenevand, Dr Ahmad Zandvanian, Dr Maryam Zare,
Volume 12, Issue 46 (9-2023)
Abstract

Students, as one of the main axes of the education system, play the most important role in the learning process. It is obvious that students' academic performance depends on the degree of their acquired or learned abilities in school subjects, and this variable itself is also influenced by factors. The aim of the present study was to investigate the predictive role of implicit intelligence and multiple intelligences in student`s academic performance with the mediating role of academic engagement. The research method was a descriptive and correlation study. Statistical population was including the entire students in the high school in Ashkzar city in 2020-2021 that 245 individuals were selected through voluntary sampling method. To collect data from questionnaires implicit intelligence, multiple intelligence and academic engagement scales was used. The results showed that both components of implicit intelligence (incremental beliefs and entity beliefs) and the components of logical – mathematical intelligence, interpersonal intelligence and musical intelligence from the multiple intelligence variable, are able to indirectly predict academic performance. In other words, the results showed that incremental beliefs (0.06), entity beliefs (0.03), logical-mathematical intelligence (0.12) and interpersonal intelligence (0.04) predict academic performance positively, by mediating academic engagement and musical intelligence (-0.04) predict academic performance negatively, by mediating academic engagement in high school students. So, based on these results, increasing beliefs of intelligence can increase academic performance and on the other hand, some types of intelligence can play a positive and negative role on academic performance.
 

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