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Showing posts with the label Educators

Exploring the Economic Impact of University Entrance Exam in Kabul City

 Abstract This research presents an assessment of the economic impact of Kankor examinations in Kabul city. Economic impact is viewed as direct impact areas attributable to Kankor examinations in terms of employment, income, GDP contribution, and accumulation of tax revenues to the government. The study shows that Kankor examinations as a national product has significant direct economic impact on Kabul city. The estimates that are made based on collection of primary data from a sample size of more than 16,450 students in Kabul city indicates that the conduct of Kankor examinations contributes approximately 2 billion AFN to the GDP. In addition, our study shows that the employment contribution of Kankor examination in Kabul city is more than 950 job created. Furthermore, the conduct of Kankor examinations added more than 1.3 billion AFN factor income in Kabul city and potentially as much as AFN 260 million to the government in taxes annually. Exploring the Economic Impact of Univers...

Unmasking AI-Generated Text: Solutions for Educators

 The use of AI-generated text in the academic sector presents a number of challenges, as well as opportunities, for educators and students. On the one hand, AI systems are capable of generating text that is coherent, logical, and well-written, which can be a valuable resource for students and researchers. However, there is also a concern that AI-generated text may be difficult to distinguish from human-generated text, which could make it difficult for teachers and other educators to determine the authenticity of a given assignment or piece of work. https://youtu.be/EzOII7nEefU Additionally, the ability to distinguish between human- and AI-generated text is a complex and evolving area of research. As AI technology continues to advance, it is likely that AI systems will become increasingly sophisticated and able to produce text that is indistinguishable from human-generated text. In such cases, it may be difficult for even advanced language models to accurately determine the source...