Political Literacy of Generation Z Voters Towards 2024^s Election
Eka Vidya Putra, Reno Fernandes and Abdi Azzara

Universitas Negeri Padang
Jalan Prof. Hamka Air TawarPadang Sumatera Barat

Abstract

This article aims to determine the level of political literacy of Generation Z voters towards 2024 General Election and also analyze the role of school institutions to improve political literacy. The background of this article is that more than 60 percent of voters in the 2024 General Election are Generation Z. One indicator of a quality election is the literacy level of the voters. Knowing the literacy level of voters early is very useful for quality preparation for the 2024 General Election. The result can be a recommendation for many parties, one of which is the school. As education providers, schools can play a role in building critical awareness. Especially for students, who incidentally will become voters in the 2024 General Election. The method used in data collection is the mix method. The level of political literacy is carried out quantitatively while the role of schools is carried out qualitatively. Related to the first question, the four findings are: first, Generation Z^s political knowledge is more on political issues than substantial matters- second, the response to the political issues of Generation Z is more cynical and apathetic- third, interest in political issues depends on conversations that go viral on social media- Fourth, TikTok and Instagram, the two applications that are most often used as sources of information. While the second question resulted in three important findings, namely. first, online learning brings students and teachers closer to digital, this situation can be an opportunity to produce creative content with political literacy content- and second, curricular programs with specialization pathways can be developed and directed to increase students^ analytical skills in political literacy.

Keywords: political literacy, Generation Z generation, the role of school institutions

Topic: Optimization Research Based on Local Resources