Esplorare l'esperienza degli studenti universitari con strumenti educativi basati sull'IA: Il caso di un sistema di allerta precoce
DOI:
https://doi.org/10.7346/-fei-XXII-01-24_09Parole chiave:
Esperienze degli studenti, Intelligenza Artificiale, Sistema di Allerta Precoce, Alta formazione, Analisi tematicaAbstract
Gli strumenti educativi alimentati dall'intelligenza artificiale (AIEd) includono sistemi di allerta precoce (EWS) per identificare gli studenti universitari a rischio, offrendo assistenza personalizzata. Rivelare le esperienze soggettive degli studenti con gli EWS potrebbe contribuire a una comprensione più profonda di cosa significhi interagire con l'IA in aree della vita umana quali l'insegnamento e l'apprendimento. La nostra indagine ha quindi esplorato le esperienze soggettive degli studenti con gli EWS, caratterizzandole secondo i profili degli studenti, l'autoefficacia, l'esperienza pregressa e la prospettiva sull'etica dei dati. I risultati mostrano che gli studenti, per lo più lavoratori senior con forte autoefficacia accademica, avevano esperienze limitate con questo metodo e aspettative minime. Ciononostante, l'utilizzo degli EWS ha ispirato riflessioni significative. Nonostante ciò, un confronto tra le discipline di Informatica ed Economia ha dimostrato una maggiore fiducia e aspettativa riguardo al sistema e all'IA per la prima. Lo studio ha sottolineato l'importanza di aiutare gli studenti a maturare ulteriori esperienze e comprensioni mentre si avvalgono dei sistemi AI nell'educazione per garantire la qualità, la rilevanza e l'equità della loro esperienza educativa complessiva.
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