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Towards Characterizing Trust in Generative Artificial Intelligence among Students.

M. Amoozadeh, D. Daniels, S. Chen, D. Nam, A. Kumar, M. Hilton, M. Alipour, и S. Ragavan. ICER (2), стр. 3-4. ACM, (2023)

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Abdul-Hakim Dayeh

Maria Dayen

Abdul-Hakim Dayeh

Hamid Abou Dayé

Jin Nam

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Trust in Generative AI among students: An Exploratory Study.M. Amoozadeh, D. Daniels, D. Nam, S. Chen, M. Hilton, S. Ragavan, и M. Alipour. CoRR, (2023)EVA: a tool for visualizing software architectural evolution.D. Nam, Y. Lee, и N. Medvidovic. ICSE (Companion Volume), стр. 53-56. ACM, (2018)SEALANT: a detection and visualization tool for inter-app security vulnerabilities in Android.Y. Lee, P. Yoodee, A. Shahbazian, D. Nam, и N. Medvidovic. ASE, стр. 883-888. IEEE Computer Society, (2017)Toward predicting architectural significance of implementation issues.A. Shahbazian, D. Nam, и N. Medvidovic. MSR, стр. 215-219. ACM, (2018)The Long Tail: Understanding the Discoverability of API Functionality.A. Horvath, S. Grover, S. Dong, E. Zhou, F. Voichick, M. Kery, S. Shinju, D. Nam, M. Nagy, и B. Myers. VL/HCC, стр. 157-161. IEEE Computer Society, (2019)Towards Characterizing Trust in Generative Artificial Intelligence among Students.M. Amoozadeh, D. Daniels, S. Chen, D. Nam, A. Kumar, M. Hilton, M. Alipour, и S. Ragavan. ICER (2), стр. 3-4. ACM, (2023)Trust in Generative AI among Students: An exploratory study.M. Amoozadeh, D. Daniels, D. Nam, A. Kumar, S. Chen, M. Hilton, S. Ragavan, и M. Alipour. SIGCSE (1), стр. 67-73. ACM, (2024)Improving API Knowledge Discovery with ML: A Case Study of Comparable API Methods.D. Nam, B. Myers, B. Vasilescu, и V. Hellendoorn. ICSE, стр. 1890-1906. IEEE, (2023)MARBLE: Mining for Boilerplate Code to Identify API Usability Problems.D. Nam, A. Horvath, A. Macvean, B. Myers, и B. Vasilescu. ASE, стр. 615-627. IEEE, (2019)API Design Implications of Boilerplate Client Code.D. Nam. ASE, стр. 1253-1255. IEEE, (2019)