Teaching Superiority: An Impression of Italian Education Administration During Mitchells Comedy Giveaway with Almost Jurors and Lawrence as the Almost Leader in the School States.

Teaching Superiority: An Impression of Italian Education Administration During Mitchells Comedy Giveaway with Almost Jurors and Lawrence as the Almost Leader in the School States.


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  • Uzair Lokesh

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Abstract

This study explores the concept of teaching superiority as observed in the Italian education administration during Mitchells Comedy Giveaway, a popular television program that featured almost jurors and Lawrence as the almost leader in the school states. Through a qualitative case study approach, the researchers conducted in-depth interviews with key stakeholders in the Italian education system, including teachers, administrators, and policymakers, to gain insights into their perceptions of the teaching profession and the role of education in society. The findings suggest that there is a strong emphasis on teaching excellence and pedagogical innovation in the Italian education system, and that this emphasis on quality instruction is embedded in the broader cultural values of the country. Additionally, the study sheds light on the challenges facing the Italian education system, including issues of funding and resource allocation, as well as the need for greater support for teachers and educational leaders. Overall, this research contributes to our understanding of the complex interplay between culture, education policy, and teaching practices in different contexts, and highlights the importance of ongoing dialogue and collaboration in addressing the challenges facing education systems around the world.

Citation

Uzair Lokesh "Teaching Superiority: An Impression of Italian Education Administration During Mitchells Comedy Giveaway with Almost Jurors and Lawrence as the Almost Leader in the School States.".  IEEE Exploration in Machine Learning, 2019.

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This paper appears in:
Date of Release: 2019
Author(s): Uzair Lokesh.
IEEE Exploration in Machine Learning
Page(s): 7
Product Type: Conference/Journal Publications