The introduction of artificial intelligence (AI) into education represents a significant step toward the evolution of educational models, fostering a shift toward more innovative approaches. AI acts as an engine for personalizing learning (Roll & Wylie 2016; Kokku et al., 2018), helping to make educational processes more efficient and tailored to each student (Panciroli, Fabbri & Macauda, 2022). With the expansion and growing impact of artificial intelligence (AI) in education, more and more researchers and practitioners in the field are beginning to recognize that the traditional model of teaching and learning could undergo significant transformations (Pedro, Subosa, Rivas & Valverde, 2019). Through the analysis of study modes adopted by a group of 118 students at the end of secondary education, this research investigates the influence of digital technologies (with a focus on the application of AI) on learning dynamics. In particular, adopting a hands-on laboratory approach, we investigate students’ metacognitive skills and study techniques in information processing. This is accomplished through the analysis of cognitive autobiographies and activities aimed at knowledge visualization, both with and without the use of digital technologies (Huang et al., 2023) (including AI-based ones). The aim of this study is to explore the different plausible scenarios that have emerged with the introduction of artificial intelligence (AI) in the educational sector and to raise students' awareness of critical awareness in knowledge management and representation, in order to foster the development of innovative teaching methodologies that optimize the use of digital technologies in the educational process. Through these directions, it is intended to foster a balanced integration of artificial intelligence that can enrich the educational landscape without compromising the core values of teaching and human engagement (Panciroli, Rivoltella, Gabbrielli & Richter, 2020).
Learning and teaching in the age of digital technologies: teaching strategies and new research directions
Iannaccone, S.
2025-01-01
Abstract
The introduction of artificial intelligence (AI) into education represents a significant step toward the evolution of educational models, fostering a shift toward more innovative approaches. AI acts as an engine for personalizing learning (Roll & Wylie 2016; Kokku et al., 2018), helping to make educational processes more efficient and tailored to each student (Panciroli, Fabbri & Macauda, 2022). With the expansion and growing impact of artificial intelligence (AI) in education, more and more researchers and practitioners in the field are beginning to recognize that the traditional model of teaching and learning could undergo significant transformations (Pedro, Subosa, Rivas & Valverde, 2019). Through the analysis of study modes adopted by a group of 118 students at the end of secondary education, this research investigates the influence of digital technologies (with a focus on the application of AI) on learning dynamics. In particular, adopting a hands-on laboratory approach, we investigate students’ metacognitive skills and study techniques in information processing. This is accomplished through the analysis of cognitive autobiographies and activities aimed at knowledge visualization, both with and without the use of digital technologies (Huang et al., 2023) (including AI-based ones). The aim of this study is to explore the different plausible scenarios that have emerged with the introduction of artificial intelligence (AI) in the educational sector and to raise students' awareness of critical awareness in knowledge management and representation, in order to foster the development of innovative teaching methodologies that optimize the use of digital technologies in the educational process. Through these directions, it is intended to foster a balanced integration of artificial intelligence that can enrich the educational landscape without compromising the core values of teaching and human engagement (Panciroli, Rivoltella, Gabbrielli & Richter, 2020).I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
