Badralsadat Sahafi; Zahra Jamebozorg
Abstract
Purpose: The primary objective of this research was to integrate ChatGPT, an advanced artificial intelligence language model, into distance science education. By addressing the specific challenges inherent in online learning environments, this study aims to investigate how technological advancements, ...
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Purpose: The primary objective of this research was to integrate ChatGPT, an advanced artificial intelligence language model, into distance science education. By addressing the specific challenges inherent in online learning environments, this study aims to investigate how technological advancements, such as ChatGPT, can effectively enhance the management and overall quality of distance education experiences.
Method: This qualitative, exploratory study aimed to provide a comprehensive understanding of the potential applications of ChatGPT in distance science education. This study identifies the various interactions that can occur in distance education and describes and evaluates the input and output instructions associated with each interaction. The chat bot used is https://chatbot.theb.ai and A biology tutoring platform uses ChatGPT to provide personalized support to students working on biology issues or concepts.
Findings: Based on the results, the artificial intelligence can play an important role in improving distance science education. Furthermore, this study highlights the importance of developing metacognitive skills among learners and encourages educators to seek professional development opportunities to enhance the quality and engagement of distance science education. This study emphasizes the need for careful planning, research, design, evaluation, management, and responsible application of AI technology in distance education.
Conclusion: This study was concluded that ChatGPT could be very useful for both learners and educators in distance education. This research showcases the innovative results facilitated by ChatGPT and provides valuable insights and practical guidance for educators, researchers, and policy makers on the effective use of AI technologies in distance science education.
Zahra Gholamzadeh; Abbas Khamseh; Mohammadreza Parsanejad
Abstract
Purpose: The purpose of the current research is to extract the components and dimensions of digital transformation and determine the levels and sequence of dimensions in Iran's education and upbringing, for the planning and implementation roadmap.Method: This research has a mixed approach (qualitative-quantitative). ...
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Purpose: The purpose of the current research is to extract the components and dimensions of digital transformation and determine the levels and sequence of dimensions in Iran's education and upbringing, for the planning and implementation roadmap.Method: This research has a mixed approach (qualitative-quantitative). The qualitative section was able to extract the components of digital transformation by searching for authentic Persian and English articles published in the last ten years. With the help of seven experts, the digital transformation components were classified into eight dimensions in the form of 109 identified sub-components using the ISM method. Dimension levels were determined by SSIM matrix calculations in the quantitative part. MICMAC software version 5.3.0 was used to calculate the impact of relationships.Findings: Based on the opinion of experts and the results of ISM calculations, the identified dimensions including: institutional, education, technology, infrastructural, social, cultural and economic were placed in four levels.Conclusion: According to experts, the institutional dimension, being placed at the fourth level, has the greatest impact on digital transformation in Iran's education. Therefore, it is one of the key dimensions to achieve digital educational transformation that is placed at the first level of the model. According to the results of ISM, the economic and cultural dimensions were placed at the third level. Also, in analyzing the impact of relationships between dimensions using MICMAC software, the results indicate that the institutional dimension has a significant impact on infrastructure development.
Mohammad Javad Shooshtari; Hossein Etemadfard; Rouzbeh Shad
Abstract
The widespread deployment of social media has helped researchers access an enormous amount of data in various domains, including the the COVID-19 pandemic. This study draws on a heuristic approach to classify Commercial Instagram Posts (CIPs) and explores how the businesses around the Holy Shrine were ...
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The widespread deployment of social media has helped researchers access an enormous amount of data in various domains, including the the COVID-19 pandemic. This study draws on a heuristic approach to classify Commercial Instagram Posts (CIPs) and explores how the businesses around the Holy Shrine were impacted by the pandemic. Two datasets of Instagram posts (one gathered data from March 14th to April 10th, 2020, when Holy Shrine and nearby shops were closed, and one extracted data from the same period in 2019), two word embedding models – aimed at vectorizing associated caption of each post, and two neural networks – multi-layer perceptron and convolutional neural network – were employed to classify CIPs in 2019. Among the scenarios defined for the 2019 CIPs classification, the results revealed that the combination of MLP and CBoW achieved the best performance, which was then used for the 2020 CIPs classification. It was found out that the fraction of CIPs to total Instagram posts has increased from 5.58% in 2019 to 8.08% in 2020, meaning that business owners were using Instagram to increase their sales and continue their commercial activities to compensate for the closure of their stores during the pandemic. Moreover, the portion of non-commercial Instagram posts (NCIPs) in total posts has decreased from 94.42% in 2019 to 91.92% in 2020, implying the fact that since the Holy Shrine was closed, Mashhad residents and tourists could not visit it and take photos to post on their Instagram accounts.
