From Score-Driven to Value-Sharing: Understanding Chinese Family Use of AI to Support Decision Making of College Applications
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| Main Authors: | , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866910863213985792 |
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| author | Chen, Si Xie, Jingyi Wang, Ge Wang, Haizhou Cheng, Haocong Huang, Yun |
| author_facet | Chen, Si Xie, Jingyi Wang, Ge Wang, Haizhou Cheng, Haocong Huang, Yun |
| contents | This study investigates how 18-year-old students, parents, and experts in China utilize artificial intelligence (AI) tools to support decision-making in college applications during college entrance exam -- a highly competitive, score-driven, annual national exam. Through 32 interviews, we examine the use of Quark GaoKao, an AI tool that generates college application lists and acceptance probabilities based on exam scores, historical data, preferred locations, etc. Our findings show that AI tools are predominantly used by parents with limited involvement from students, and often focus on immediate exam results, failing to address long-term career goals. We also identify challenges such as misleading AI recommendations, and irresponsible use of AI by third-party consultant agencies. Finally, we offer design insights to better support multi-stakeholders' decision-making in families, especially in the Chinese context, and discuss how emerging AI tools create barriers for families with fewer resources. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2411_10280 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | From Score-Driven to Value-Sharing: Understanding Chinese Family Use of AI to Support Decision Making of College Applications Chen, Si Xie, Jingyi Wang, Ge Wang, Haizhou Cheng, Haocong Huang, Yun Human-Computer Interaction This study investigates how 18-year-old students, parents, and experts in China utilize artificial intelligence (AI) tools to support decision-making in college applications during college entrance exam -- a highly competitive, score-driven, annual national exam. Through 32 interviews, we examine the use of Quark GaoKao, an AI tool that generates college application lists and acceptance probabilities based on exam scores, historical data, preferred locations, etc. Our findings show that AI tools are predominantly used by parents with limited involvement from students, and often focus on immediate exam results, failing to address long-term career goals. We also identify challenges such as misleading AI recommendations, and irresponsible use of AI by third-party consultant agencies. Finally, we offer design insights to better support multi-stakeholders' decision-making in families, especially in the Chinese context, and discuss how emerging AI tools create barriers for families with fewer resources. |
| title | From Score-Driven to Value-Sharing: Understanding Chinese Family Use of AI to Support Decision Making of College Applications |
| topic | Human-Computer Interaction |
| url | https://arxiv.org/abs/2411.10280 |