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1 – 2 of 2Ilkka Koiranen, Aki Koivula, Anna Kuusela and Arttu Saarinen
The study utilises unique survey data gathered from 12,427 party members. The dependent variable measures party members’ in-party commitment and is based on willingness to donate…
Abstract
Purpose
The study utilises unique survey data gathered from 12,427 party members. The dependent variable measures party members’ in-party commitment and is based on willingness to donate money, to contribute effort, the feeling of belonging in the party network and social trust in the party network.
Design/methodology/approach
In this article, we study how different extra-parliamentary online and offline activities are associated with in-party commitment amongst political party members from the six largest Finnish parties. We especially delve into the differences between members of the Finnish parties.
Findings
We found that extra-parliamentary political activity, including connective action through social media networks and collective action through civic organisations, is highly associated with members’ in-party commitment. Additionally, members of the newer identity parties more effectively utilised social media networks, whilst the traditional interest parties were still more linked to traditional forms of extra-parliamentary political action.
Originality/value
By employing the sociological network theory perspective, the study contributes to ongoing discussions surrounding the impact of social media on political participation amongst party members, both within and beyond the confines of political parties.
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Keywords
Sarah Sidani and Rawan Hassoun
This section outlines a framework for incorporating Artificial Intelligence (AI) and digital transformation (DT) into education, focusing on how they can transform teaching…
Abstract
This section outlines a framework for incorporating Artificial Intelligence (AI) and digital transformation (DT) into education, focusing on how they can transform teaching methods, curriculum development, and academic evaluations. It traces the evolution of AI from rule-based systems to learning technologies, highlighting the move toward education and innovative curricula. The framework considers both the benefits of using AI to improve practices and the challenges it brings, such as issues and the potential for creating a digital divide. This balanced perspective is crucial in shaping how DT is adopted in education, promoting a fair educational environment that harnesses the advancements in AI and DT. Aimed at policymakers, administrators, and educators, this section is a road map for navigating the complexities of integrating technology into education, contributing to an adaptable and enriched landscape.
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