سواد هوش مصنوعی برای یادگیرندگان قرن بیست و یکم: چارچوبی برای ارزیابی و اعتبارسنجی
الموضوعات : سامانه‌های پردازشی و ارتباطی چندرسانه‌ای هوشمند
1 - دانشجوی دکتری، تکنولوژی آموزشی، دانشگاه علامه طباطبائی، تهران، ایران
الکلمات المفتاحية: هوش مصنوعی, سواد هوش مصنوعی, روان سنجی, دانشجویان.,
ملخص المقالة :
چکیده: با کاربرد هوش مصنوعی در بخش‌های مختلفی مانند آموزش، پزشکی، مهندسی و امور مالی، تقاضا برای سواد هوش مصنوعی که شامل ارزیابی انتقادی، همکاری مؤثر و درک مفاهیم و پیامدهای اخلاقی هوش مصنوعی می‌شود شدت گرفته است. در آموزش عالی، سواد هوش مصنوعی به عنوان ستونی اساسی شناخته می‌شود که دانش و مهارت‌های لازم برای انجام مؤثر وظایف عملی مورد انتظار از هر دو مدرس و دانشجو در بستر آموزشی با استفاده از هوش مصنوعی را در بر می‌گیرد. سواد هوش مصنوعی (AI) امروزه در صدر دستور کار آموزش برای توسعه دانش، مهارت، نگرش و ارزش‌های دانش‌آموزان در قرن بیست و یکم قرار دارد. با این حال، ابزارهای تحقیقاتی تایید شده کمی برای ارزیابان آموزشی جهت بررسی چگونگی توسعه و درک دانشجویان از نتایج یادگیری‌شان وجود دارد. هدف از پژوهش حاضر ساخت و اعتباریابی مقیاس سواد هوش مصنوعی در دانشجویان بود. روش تحقیق توصیفی-پیمایشی بود. جامعه آماری شامل 150 نفر از دانشجویان کارشناسی رشته علوم تربیتی دانشگاه پیام نور کرمان می باشد که با روش نمونه گیری در دسترس انتخاب شدند. ابزار گردآوری پژوهش شامل پرسشنامه 32 سوالی سواد هوش مصنوعی ان جی و همکاران (2023) بود . داده ها با استفاده از تحلیل عاملی تاییدی تجزیه و تحلیل شدند. یافته های پژوهش نشان داد با توجه به نتایج حاصل از بررسی شاخص‌های ارزیابی براش مدل که همگی در دامنه قابل قبول قرار دارند، مدل سواد هوش مصنوعی از برازش لازم برخوردار است (RMSEA=0.06،NFI=0.94،CFI=0.92). لذا با توجه به این یافته‌ها می‌توان گفت که مدل آزمون شده از برازش مناسبی برخوردار است و پرسشنامه پژوهش از روایی سازه مطلوبی برخوردار است. نتیجه‌گیری ما این است که سواد هوش مصنوعی مستلزم برخورداری دانشجویان از نه تنها دانش و مهارت های فنی، بلکه همچنین دانش و مهارت های عاطفی، رفتاری و اخلاقی است.
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[1] Chiu TK. “The impact of Generative AI (GenAI) on practices, policies and research direction in education: A case of ChatGPT and Midjourney”. Interactive Learning Environments. 2023 Sep 2:1-7.
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[3] Banele, S. D. “The students' cognitive discrepancies in artificial intelligences utilization: A case of higher learning institutions”. SocioEdu: Sociological Education, 4(2), 2023; 53-61.
[4] Ng DT, Chu SK. “Motivating Students to Learn AI Through Social Networking Sites: A Case Study in Hong Kong”. Online Learning. 2021 Mar;25(1):195-208.
[5] Kong SC, Cheung WM, Zhang G. “Evaluation of an artificial intelligence literacy course for university students with diverse study backgrounds”. Computers and Education: Artificial Intelligence. 2021 Jan 1;2:100026.
[6] Southworth J, Migliaccio K, Glover J, Reed D, McCarty C, Brendemuhl J, Thomas A. “Developing a model for AI Across the curriculum: Transforming the higher education landscape via innovation in AI literacy”. Computers and Education: Artificial Intelligence. 2023 Jan 1;4:100127.
[7] Chu HC, Hwang GH, Tu YF, Yang KH. “Roles and research trends of artificial intelligence in higher education: A systematic review of the top 50 most-cited articles”. Australasian Journal of Educational Technology. 2022 Apr 19;38(3):22-42.
[8] Crompton H, Burke D. “Artificial intelligence in higher education: the state of the field”. International Journal of Educational Technology in Higher Education. 2023 Apr 24;20(1):22.
[9] Laupichler MC, Aster A, Schirch J, Raupach T. “Artificial intelligence literacy in higher and adult education: A scoping literature review”. Computers and Education: Artificial Intelligence. 2022 Jan 1;3:100101.
[10] Long D, Magerko B. “What is AI literacy? Competencies and design considerations”. InProceedings of the 2020 CHI conference on human factors in computing systems 2020 Apr 21 (pp. 1-16).
[11] Markauskaite L, Marrone R, Poquet O, Knight S, Martinez-Maldonado R, Howard S, Tondeur J, De Laat M, Shum SB, Gašević D, Siemens G. “Rethinking the entwinement between artificial intelligence and human learning: What capabilities do learners need for a world with AI?”. Computers and Education: Artificial Intelligence. 2022 Jan 1;3:100056.
[12] Tenório K, Olari V, Chikobava M, Romeike R. “Artificial intelligence literacy research field: a bibliometric analysis from 1989 to 2021”. InProceedings of the 54th ACM Technical Symposium on Computer Science Education V. 1 2023 Mar 2 (pp. 1083-1089).
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