The impact of human-AIGC tools collaboration on the learning effect of college students: a key factor for future education?

Purpose

The maturity of artificial intelligence technology and the emergence of AI-generated content (AIGC) tools have endowed college students with a human-AIGC tools collaboration learning mode. However, there is still a great controversy about its impact on learning effect. This paper is aimed at investigating the impact of the human-AIGC tools collaboration on the learning effect of college students.

Design/methodology/approach

In this paper, a hypothesized model was constructed to investigate the effects of dependence, usage purpose, trust level, frequency, and proficiency of using AIGC tools on the learning effect, respectively. This paper distributed questionnaires through random sampling. Then, the improved Analytic Hierarchy Process (AHP) was used to assign weights and normalize data. Lastly, one-way ANOVA and multiple linear regression analyses were used to measure and analyze variables, revealing the mechanism of influence.

Findings

The usage purpose, frequency, and proficiency of using AIGC tools have a significant positive effect on learning. Being clear about the usage purpose of AIGC tools and matching the specific study tasks will enhance the learning effect. College students should organically integrate AIGC tools into each learning process, which is conducive to building a learning flow applicable to oneself, improving efficiency, and then enhancing learning effects. The trust level in AIGC tools is significant, but positively and weakly correlated, indicating that college students need to screen the generated content based on their knowledge system framework and view it dialectically. The dependence on AIGC tools has a negative and significant effect on learning effect. College students are supposed to systematically combine self-reflection and the use of AIGC tools to avoid overdependence on them.

Research limitations/implications

Based on the findings, the learning suggestions for college students in human-machine collaboration in the AIGC era are proposed to provide ideas for the future information-based education system. For further research, scholars can expand on different groups, professions, and fields of study.

Originality/value

Previous studies have focused more on the impact of AIGC on the education system. This paper analyzed the impact of the various factors of using AIGC tools in the learning process on the learning effect from the perspective of college students.