The Academic Anti-Procrastination Approach: Combining Peer Motivation and Personalized Artificial Intelligence Reminders

Authors

  • Xiaojiao Duan Claremont Graduate University, Claremont, USA https://orcid.org/0009-0005-3040-991X
  • Zhaoxia Yi, Claremont Graduate University, Claremont, USA https://orcid.org/0009-0007-3901-7554
  • Yongjia Sun Claremont Graduate University, Claremont, USA
  • Itamar Shabtai Claremont Graduate University, Claremont, USA

DOI:

https://doi.org/10.34190/icair.4.1.3222

Keywords:

Procrastination, Peer motivation, Artificial intelligence, Reminders, Social Interaction, College students

Abstract

Academic procrastination is a pervasive issue that significantly affects college students, leading to increased anxiety, stress, and reduced study efficiency and performance. Despite numerous studies exploring the causes and solutions to reduce procrastination, including the positive effects of peer motivation and technological interventions, the integration of artificial intelligence (AI) interventions through peer motivation and smart reminders remains underexplored. In this study, we conducted a systematic literature review on the causes of academic procrastination, the influence of social motivation, and technical interventions aimed at reducing procrastination. Our review revealed a significant research gap regarding the use of AI reminders and peer motivation to help students mitigate procrastination and enhance productivity. To address this gap, we propose an Academic Anti-Procrastination Approach that integrates peer motivation, social interaction, and AI-driven reminders. This approach utilizes the social networks of college students and incorporates AI tools to create a support system designed to reduce procrastination. We conducted an experiment to evaluate the effectiveness of this approach, using a mixed-methods methodology to analyze the results. Our findings suggest that the approach effectively reduces academic procrastination by harnessing the synergistic effects of peer motivation and AI-driven interventions. Quantitative results showed a p-value of 0.0017 in the experimental group, indicating a statistically significant decrease in procrastination scores after the intervention. Qualitative semi-structured interview results revealed that all participants found the personalized AI reminders helpful, with 87% stating that social motivation and interaction motivated them to complete tasks. Additionally, 80% of participants indicated that the concepts behind the approach would be useful in combating procrastination and expressed a willingness to use the approach and join a peer group to reduce their academic procrastination. This study offers practical contributions for combating academic procrastination in college environments. Students can utilize this method to create supportive peer groups and leverage personalized technological support, helping them overcome low efficiency and maintain focus on academic tasks.

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Published

2024-12-04