Digital Tools for Job Search and Integration: Mapping and Evaluating Services for International Students in Finland
Li, Jingfan (2024)
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2024111328125
https://urn.fi/URN:NBN:fi:amk-2024111328125
Tiivistelmä
The rapid growth of international student enrollment in Finnish higher education, coupled with recent policy changes affecting post-graduation employment, has created pressing challenges for student integration into the workforce. While digital job search platforms serve as crucial tools for these students, their effectiveness in addressing international students' unique needs remains understudied. This research, conducted as part of Haaga-Helia's INTEGRA project initiated in January 2024, examines how digital tools and services facilitate international students' integration into Finnish society and the job market, with the primary objective of evaluating their effectiveness and identifying key areas for improvement.
The study's scope is specifically demarcated to digital platforms and services used by international higher education students in Finland for job searching and workplace integration. The theoretical framework synthesizes multiple perspectives, including Cultural Adaptation Theory, Technology Acceptance Model, Flow Theory, and User Experience frameworks, providing a comprehensive lens for analysis. The research implemented a mixed-methods approach from September 6 to October 6, 2024, combining quantitative and qualitative data collection through an online survey at Haaga-Helia University of Applied Sciences. The methodology involved analyzing 48 valid responses from 62 submissions, utilizing Tableau for quantitative analysis and NVivo for qualitative content analysis.
Key findings revealed that while general platforms like LinkedIn demonstrated high user satisfaction, significant challenges persisted across all platforms. Language barriers, particularly with Finnish language requirements, emerged as a primary obstacle. The study found that platforms offering multilingual support and enhanced filtering options correlated with higher job search success rates. User journey maps and personas were created to illustrate the distinct challenges faced by international students, pointing to critical opportunities for improving the digital job search ecosystem.
The research concludes with a simplified model for enhancing digital job search platforms. This model highlights basic improvements such as better language support, more advanced filtering options, and resources for cultural adaptation. Evaluation criteria are also proposed, focusing on platform usability, engagement, and relevance to international students' integration needs. The implications of this study extend beyond platform development, offering policy recommendations for educational institutions and employers, and contributing to the broader dialogue on international student integration in Finland. Future research is recommended to expand this study across multiple institutions and incorporate longitudinal analysis of integration outcomes.
The study's scope is specifically demarcated to digital platforms and services used by international higher education students in Finland for job searching and workplace integration. The theoretical framework synthesizes multiple perspectives, including Cultural Adaptation Theory, Technology Acceptance Model, Flow Theory, and User Experience frameworks, providing a comprehensive lens for analysis. The research implemented a mixed-methods approach from September 6 to October 6, 2024, combining quantitative and qualitative data collection through an online survey at Haaga-Helia University of Applied Sciences. The methodology involved analyzing 48 valid responses from 62 submissions, utilizing Tableau for quantitative analysis and NVivo for qualitative content analysis.
Key findings revealed that while general platforms like LinkedIn demonstrated high user satisfaction, significant challenges persisted across all platforms. Language barriers, particularly with Finnish language requirements, emerged as a primary obstacle. The study found that platforms offering multilingual support and enhanced filtering options correlated with higher job search success rates. User journey maps and personas were created to illustrate the distinct challenges faced by international students, pointing to critical opportunities for improving the digital job search ecosystem.
The research concludes with a simplified model for enhancing digital job search platforms. This model highlights basic improvements such as better language support, more advanced filtering options, and resources for cultural adaptation. Evaluation criteria are also proposed, focusing on platform usability, engagement, and relevance to international students' integration needs. The implications of this study extend beyond platform development, offering policy recommendations for educational institutions and employers, and contributing to the broader dialogue on international student integration in Finland. Future research is recommended to expand this study across multiple institutions and incorporate longitudinal analysis of integration outcomes.