A Study of the Effects of Interactive AI Image Processing Functions on Children’s Painting Education

Sun, Jie; Gu, Chao; Chen, Jiangjie; Wei, Wei; Yang, Chun; Jiang, Qianling

doi:10.1007/978-3-031-05581-2_8

Cited by 1 publication

(1 citation statement)

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“…For example, Timms (2016) claimed that anthropomorphic robots could communicate with humans through visual, auditory, and sensory systems to facilitate human-machine interaction; Yang and Zhang (2019) noted that incorporating AI technologies into robots could allow them to take on the role of teachers primarily. Additionally, artificial intelligence has significantly advanced technology for robots, such as speech recognition systems (Benkerzaz et al, 2019) and picture recognition systems (Sun et al, 2022). In the past, the majority of research on educational robotics has focused on the education of children (Fridin, 2014;Kewalramani et al, 2021).…”

Section: Artificial Intelligence Education Robotmentioning

confidence: 99%

Developing a gamified artificial intelligence educational robot to promote learning effectiveness and behavior in laboratory safety courses for undergraduate students

Yang

Lian

Zhao

2023

Int J Educ Technol High Educ

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According to previous studies, traditional laboratory safety courses are delivered in a classroom setting where the instructor teaches and the students listen and read the course materials passively. The course content is also uninspiring and dull. Additionally, the teaching period is spread out, which adds to the instructor's workload. As a result, students become less motivated to learn. In contrast, artificially intelligent educational robots (AIERs), help students learn while lessening the workload on instructors by enhancing teaching strategies, using robots to substitute for teachers, giving students access to a variety of instructional content, and improving interaction with students through the use of intelligent voice interactions and Q&A systems to promote student engagement in learning. If the robot is used for a long time for learning, it may lead to a decrease in students' interest in learning. Therefore, this study introduces the GAFCC model (the theory-driven gamification goal, access, feedback, challenge, collaboration design model) as an instructional design model to guide the development of a gamified AIER system, aiming to improve students' motivation and learning effectiveness for laboratory safety courses. To test the effectiveness of the system, this study conducted an experimental study at a university in China in the summer of 2022. 53 participants participated in the research, with a random sample taken from each group. Each participant was able to choose the time of their free time to engage in the experiment. There were 18, 19, and 16 participants in experimental group 1, experimental group 2, and the traditional group, respectively. Students in experimental group 1 learned using the gamified AIER system, students in experimental group 2 learned on a general anthropomorphic robot system and the control group received traditional classroom learning. The experimental results showed that compared to the other two groups, the gamified AIER system guided by the GAFCC model significantly improved students' learning achievement and enhanced their learning motivation, flow experience, and problem-solving tendency. In addition, students who adopted this approach exhibited more positive behaviors and reduced cognitive load in the learning process.

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