Learning design to support student-AI collaboration: perspectives of leading teachers for AI in education

Jinhee Kim,Young Hoan Cho,Hyunkyung Lee

doi:10.1007/s10639-021-10831-6

Jinhee Kim, Young Hoan Cho + Show 1 more

Open Access

https://doi.org/10.1007/s10639-021-10831-6

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Abstract

Preparing students to collaborate with AI remains a challenging goal. As AI technologies are new to K-12 schools, there is a lack of studies that inform how to design learning when AI is introduced as a collaborative learning agent to classrooms. The present study, therefore, aimed to explore teachers’ perspectives on what (1) curriculum design, (2) student-AI interaction, and (3) learning environments are required to design student-AI collaboration (SAC) in learning and (4) how SAC would evolve. Through in-depth interviews with 10 Korean leading teachers in AI in Education (AIED), the study found that teachers perceived capacity and subject-matter knowledge building as the optimal learning goals for SAC. SAC can be facilitated through interdisciplinary learning, authentic problem solving, and creative tasks in tandem with process-oriented assessment and collaboration performance assessment. While teachers expressed instruction on AI principles, data literacy, error analysis, AI ethics, and AI experiences in daily life were crucial support, AI needs to offer an instructional scaffolding and possess attributes as a learning mate to enhance student-AI interaction. In addition, teachers highlighted systematic AIED policy, flexible school system, the culture of collaborative learning, and a safe to fail environment are significant. Teachers further anticipated students would develop collaboration with AI through three stages: (1) learn about AI, (2) learn from AI, and (3) learn together. These findings can provide a more holistic understanding of the AIED and implications for the educational policies, educational AI design as well as instructional design that are aimed at enhancing SAC in learning.

Highlights

One of the most profound areas of technological progress within the past decade has been in the development of artificial intelligence (AI) and its increased integration across multiple industries
In recognition of teachers’ beliefs and views will decide the actual curriculum at the ground level and are critical in the planning of educational practice for sustainability (Chiu, 2017), this study aims to examine the views of leading teachers in AI in Education (AIED) on key considerations for the design and implementation of student-AI collaboration (SAC) in learning for K-12 schools
Teachers in the study designed SAC on a learning task in their class while they aimed to augment students’ competencies that go well beyond the knowledge and skills typically measured by schools’ standardized tests. These competencies include improved understanding of complex concepts in the subject, connections among ideas, processes, and learning strategies, as well as the development of problem-solving, visualization, data management, communication, and collaboration skills. These findings echo with the concept of intelligence augmentation (IA) coined by Engelbart (1962), highlighting that AI should be developed to supplement or support human intelligence rather than attempt to imitate/replicate or replace human cognitive functions and operate independently

Summary

Introduction

One of the most profound areas of technological progress within the past decade has been in the development of artificial intelligence (AI) and its increased integration across multiple industries. Communicative AI such as conversational agents and embodied social robots interact with students, not limited to supporting students’ cognitive development, serve as an empathic peer/tutor to support affective development such as improving learning interest, motivation, self-regulation, and sense of empathy and collaboration (Chin et al, 2014). AI is increasingly permeating the education ecosystem by increasingly interacting and collaborating with students, building and maintaining social relationships, and offering personalized instruction. This indicates that the educational field has integrated nonhuman agents as collaborative agents serving roles of tutors/teachers, assistants, advisors, and even learning peers (Lee & Kim, 2020; Kim et al, 2020)

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