Author
Listed:
- Abdulrahman M. Al-Zahrani
Abstract
This study examines the impact of Artificial Intelligence (AI) chatbots on the loss of human connection and emotional support among higher education students. To do so, a quantitative research design is employed. An online survey questionnaire is distributed to a sample of 819 higher education students, assessing concerns about human connection, experiences with chatbots, and satisfaction levels. The research findings reveal participants’ concerns about the diminished sense of human connection and emotional support when interacting with chatbots. However, participants also acknowledge the benefits of chatbots in terms of personalized assistance, enhanced learning experiences, and improved access to information and resources. The regression analysis demonstrates a significant association between participants’ concerns of human connection and their experiences with chatbots and satisfaction with chatbot interactions. Higher levels of experiences with chatbots and greater satisfaction with chatbot interactions are positively correlated with increased concerns of human connection and emotional support. The study highlights the need for a balanced approach to the integration of chatbots in educational settings, considering the potential impact on human connection and emotional support. It emphasizes the importance of developing policies and guidelines that address the ethical use of chatbots and promote meaningful interpersonal relationships among students. Strategies for practice implementation, such as incorporating collaborative activities and providing training and support for students and faculty, are recommended. Also, instructional designers are encouraged to design chatbot interactions that go beyond information provision and focus on social presence and emotional support.
Suggested Citation
Abdulrahman M. Al-Zahrani, 2025.
"Exploring the Impact of Artificial Intelligence Chatbots on Human Connection and Emotional Support Among Higher Education Students,"
SAGE Open, , vol. 15(2), pages 21582440251, May.
Handle:
RePEc:sae:sagope:v:15:y:2025:i:2:p:21582440251340615
DOI: 10.1177/21582440251340615
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