TY - JOUR
T1 - Impacts of artificial intelligence (AI) in teaching and learning of built environment students in a developing country
AU - Ibrahim, Kabir
AU - Osuizugbo, Innocent Chigozie
AU - Eze, Emmanuel Chidiebere
AU - Ibrahim, AbdulHafeez
AU - Oshodi, Olalekan S.
AU - Adewolu, Adeoye Olugbenga
PY - 2025/10/24
Y1 - 2025/10/24
N2 - Artificial intelligence (AI) has shown its transformative ability, and its integration into education has become a necessity for enhancing teaching and learning. Meanwhile, not much research has been done in the African context, such as Nigeria, to understand the impact of AI usage on students learning and teaching. Hence, this study investigated the positive and negative impacts of AI on teaching and learning of built environment students using a questionnaire, which was distributed to built environment students and the collected data was analysed using descriptive and inferential statistical techniques. The results revealed “AI expediting the research process by sourcing and organising data, particularly valuable for students with limited access to physical libraries and resources as the top positive impact of AI on teaching and learning. Again, the study revealed that “devaluing traditional research methodologies by relying solely on AI-generated information, potentially compromises research quality”, as the top most negative impacts of AI on teaching and learning. Overall, the study provides valuable insights into the positive and negative impacts of AI on teaching and learning of built environment students in Nigeria.
AB - Artificial intelligence (AI) has shown its transformative ability, and its integration into education has become a necessity for enhancing teaching and learning. Meanwhile, not much research has been done in the African context, such as Nigeria, to understand the impact of AI usage on students learning and teaching. Hence, this study investigated the positive and negative impacts of AI on teaching and learning of built environment students using a questionnaire, which was distributed to built environment students and the collected data was analysed using descriptive and inferential statistical techniques. The results revealed “AI expediting the research process by sourcing and organising data, particularly valuable for students with limited access to physical libraries and resources as the top positive impact of AI on teaching and learning. Again, the study revealed that “devaluing traditional research methodologies by relying solely on AI-generated information, potentially compromises research quality”, as the top most negative impacts of AI on teaching and learning. Overall, the study provides valuable insights into the positive and negative impacts of AI on teaching and learning of built environment students in Nigeria.
KW - Artificial intelligence
KW - built environment students
KW - developing country
KW - impacts
KW - learning
KW - teaching
UR - https://www.scopus.com/pages/publications/105019670763
U2 - 10.1080/10494820.2025.2575010
DO - 10.1080/10494820.2025.2575010
M3 - Article
SN - 1049-4820
SP - 1
EP - 19
JO - Interactive Learning Environments
JF - Interactive Learning Environments
ER -