درخت حوزه‌های تخصصی

The purpose of this research is to design a profit maximization model for companies using the theory of constraints. To collect information, library and field studies were used, according to the method of data collection, documents, interviews and questionnaires were used, so the current research method is mixed (qualitative and quantitative). The statistical population of the research in the qualitative part included experts, professors and specialists in the field of management accounting, 10 of whom wereselected by snowball sampling until theoretical saturation was reached, and primary data were collected through interviews and a questionnaire was designed. A questionnaire was included in the quantitative part as well. All managers and assistants of the finance and accounting departments of manufacturing companies admitted to the Tehran Stock Exchange were an unknown number. According to Cochran's second formula, 385 people were selected by available sampling. A questionnaire with 78 questions was used tocheck the research variables. Cronbach's alpha coefficient confirmed the reliability of the questionnaires, 10 interviewees confirmed the content validity of the questionnaires, and their construct validity was confirmed by confirmatory factor analysis. Then, the data obtained from the questionnaire was analyzed in two sections: descriptive statistics and inferential statistics. In the section on inferential statistics, the Kolmogorov-Smirnov test was used to check the type of data distribution in terms ofnormality or not, and then confirmatory factor analysis by LISREL 8.80 software. In order to check the construct validity of the questionnaire and to test the structural equation model with the help of Lisrel SmartPLS.03 software, it has been used to answer the research questions. The most important findings of the research showed that the components of identifying the limits of profit maximization, exploiting the limits of profit maximization, spreading the effect of profit maximization decisions, removing system limitations, and the process of continuous improvement of profit maximization, respectively, with a path coefficient of 0.41, 39 0.0, 0.43, 0.37, 0.40 have a positive effect on the theory of limitations

Artificial intelligence (AI) is changing language education through personalized and interactive practice. However, its impact on language achievement and emotional aspects of learning is unclear. Therefore, this mixed-methods study investigated the effects of Chatbot-Assisted Language Learning (CHALL) on learners’ English language achievement and sense of metavolvement—the deepest level of metacognitive engagement. In phase 1, the Sense of Metavolvement Scale (SOMS) was developed and validated. In phase 2, following a quasi-experimental design, 44 intermediate Iranian EFL learners were divided into an experimental group (n=22, using the AI chatbot Pi) and a control group (n=22, receiving conventional classroom instruction). Both groups had pre- and post-tests for language achievement and metavolvement, and the experimental group sat for semi-structured interviews post-intervention. There were significant gains in the experimental group’s in-class metavolvement and language achievement. There were also significant differences between the two groups in post-test metavolvement, while there was no significant difference in their post-test language achievement. Furthermore, interview data illustrated CHALL as a low-anxiety practice context with cultural and pragmatic limitations. Therefore, CHALL can complement but not replace conventional instruction.

This study aimed to explore the digital literacy needs, challenges, and support preferences of adolescents with intellectual disabilities to inform inclusive educational practices and policy interventions. A qualitative research design was employed using semi-structured focus group interviews with 20 adolescents aged 13–18 years diagnosed with mild to moderate intellectual disabilities in Taiwan. Participants were recruited through purposive sampling from both inclusive mainstream schools and special education centers. Data collection was conducted through four focus groups, each comprising five participants. The interviews were audio-recorded, transcribed verbatim, and analyzed thematically using NVivo 14 software. Thematic saturation guided the completion of data collection. Trustworthiness was enhanced through triangulated coding, member checking, and maintaining an audit trail. Analysis revealed four overarching themes: (1) access to digital tools and infrastructure, (2) digital skills and usage patterns, (3) social and emotional factors, and (4) support systems and educational strategies. Participants reported limited and unequal access to digital devices, inadequate school resources, and lack of individualized digital instruction. While many adolescents demonstrated basic digital engagement (e.g., opening apps, watching videos), they struggled with more complex tasks such as evaluating online content or engaging in digital communication. Emotional barriers included fear of making mistakes and social comparison with peers. Support from family members and peers emerged as critical, while participants emphasized a need for gamified, visual, and hands-on digital training tailored to their learning styles. Adolescents with intellectual disabilities experience significant barriers to digital inclusion, stemming from infrastructural, cognitive, emotional, and instructional gaps. Addressing these challenges requires context-sensitive, learner-centered interventions and greater collaboration among educators, families, and policymakers to ensure equitable access to digital literacy education.