Artificial Intelligence (AI) applications in different fields are developing rapidly, among which AI painting technology, as an emerging technology, has received wide attention from users for its creativity and efficiency. This study aimed to investigate the factors that influence user acceptance of the use of AIBPS by proposing an extended model that combines the Extended Technology Acceptance Model (ETAM) with an AI-based Painting System (AIBPS). A questionnaire was administered to 528 Chinese participants, and validated factor analysis data and Structural Equation Modeling (SEM) were used to test our hypotheses. The findings showed that Hedonic Motivation (HM) and Perceived Trust (PE) had a positive effect (+) on users’ Perceived Usefulness (PU) and Perceived Ease of Use (PEOU), while Previous Experience (PE) and Technical Features (TF) had no effect (−) on users’ Perceived Usefulness (PU). This study provides an important contribution to the literature on AIBPS and the evaluation of systems of the same type, which helps to promote the sustainable development of AI in different domains and provides a possible space for the further extension of TAM, thus helping to improve the user experience of AIBPS. The results of this study provide insights for system developers and enterprises to better motivate users to use AIBPS.

Self-regulated Learning has become one of educational psychology's most critical research areas. Contemporary research indicates that student creativity is crucial to the success of arts education. However, there is limited research on creativity in arts education in Self-regulated Learning. Therefore, this study aims to define the creativity characteristics that determine the quality of students’ work. This study implemented a creative competition in painting and composition for first-year undergraduates. It evaluated the characteristics of creativity during the three main phases of the task: planning, execution, and completion. We discovered through semi-open questionnaires (n=178)，and using the content analysis method. According to the competition results, the students with the highest scores in Flow, Inspiration, and Idea Generation in the Performance phase had the best quality work. In the Forethought phase, Analogical Thinking and Idea Generation worked best for most students, while in the Performance phase, Flow Sense, Idea Generation, and Idea Manipulation worked best.Data on creativity characteristics at different work phases and final quality might adequately guide and organize educational procedures. These findings can serve as a theoretical foundation for quantifying the creativity phase in Self-regulated Learning and offer arts educators a reference for creativity instruction.

Contemporary research indicates that student creativity is crucial to the success of arts education. Self-regulated learning has become one of educational psychology’s most critical research areas. However, there is limited research on creativity in arts education in self-regulated learning. Therefore, this study aims to define the creativity characteristics that determine the quality of students’ work. This study implemented a creative competition in painting and composition for first-year undergraduates. It was conducted at a Chinese university with the participation of 178 first-year students aged 18 to 26. It evaluated the characteristics of creativity during the three main phases of the task: planning, execution, and completion. We investigated the subject by employing semi-open questionnaires (n = 178) and using the content analysis method and quantitative analysis. According to the competition results, the students with the highest scores in flow, inspiration, and idea generation in the performance phase had the best quality work. In the forethought phase, analogical thinking and idea generation worked best for most students, while in the performance phase, flow sense, idea generation, and idea manipulation worked best. Data on creativity characteristics at different work phases and final quality might adequately guide and organize educational procedures. These findings can serve as a theoretical foundation for quantifying the creativity phase in self-regulated learning and offer arts educators a reference for creativity instruction.

Artificial intelligence (AI) applications in different fields are developing rapidly, among which AI painting technology, as an emerging technology, has received wide attention from users for its creativity and efficiency. This study aimed to investigate the factors that influence user acceptance of the use of AIBPS by proposing an extended model that combines the Extended Technology Acceptance Model (ETAM) with the AI-based Painting System (AIBPS).A questionnaire was administered to 528 Chinese participants, using validated factor analysis data and Structural Equation Modeling (SEM) was used to test the hypotheses. The findings showed that hedonic motivation (HM) and perceived trust (PE) had a positive effect (+) on users' perceived usefulness (PU) and perceived ease of use (PEOU), while previous experience (PE) and technical features (TF) had no effect (-) on users' perceived usefulness (PU). This study provides an important contribution to the literature on AIBPS and the evaluation of systems of the same type, which helps to promote the sustainable development of AI in different domains and provides a possible space for further extension of TAM, thus helping to improve the user experience of AIBPS. The results of the study provide insights for system developers and enterprises to better motivate users to use AIBPS.