The impact of artificial intelligence on learner–instructor interaction in online learning

Abstract

Artificial intelligence (AI) systems offer effective support for online learning and teaching, including personalizing learning for students, automating instructors’ routine tasks, and powering adaptive assessments. However, while the opportunities for AI are promising, the impact of AI systems on the culture of, norms in, and expectations about interactions between students and instructors are still elusive. In online learning, learner–instructor interaction (inter alia, communication, support, and presence) has a profound impact on students’ satisfaction and learning outcomes. Thus, identifying how students and instructors perceive the impact of AI systems on their interaction is important to identify any gaps, challenges, or barriers preventing AI systems from achieving their intended potential and risking the safety of these interactions. To address this need for forward-looking decisions, we used Speed Dating with storyboards to analyze the authentic voices of 12 students and 11 instructors on diverse use cases of possible AI systems in online learning. Findings show that participants envision adopting AI systems in online learning can enable personalized learner–instructor interaction at scale but at the risk of violating social boundaries. Although AI systems have been positively recognized for improving the quantity and quality of communication, for providing just-in-time, personalized support for large-scale settings, and for improving the feeling of connection, there were concerns about responsibility, agency, and surveillance issues. These findings have implications for the design of AI systems to ensure explainability, human-in-the-loop, and careful data collection and presentation. Overall, contributions of this study include the design of AI system storyboards which are technically feasible and positively support learner–instructor interaction, capturing students’ and instructors’ concerns of AI systems through Speed Dating, and suggesting practical implications for maximizing the positive impact of AI systems while minimizing the negative ones.

Teachers’ AI digital competencies and twenty-first century skills in the post-pandemic world

“…A major part of teachers’ responsibilities is to create meaningful learning environments to deepen students’ learning experiences and boost their capacities. However, teachers may not be digitally ready to use AI-driven educational applications for teaching and learning purposes (e.g., Ally, 2019 ; Seo et al, 2021 ). They may lack technological experience to conduct data analysis, or to set rules to automatically generate assignments and feedback for students via AI-driven tools (Seo et al, 2021 ).…”

“…However, teachers may not be digitally ready to use AI-driven educational applications for teaching and learning purposes (e.g., Ally, 2019 ; Seo et al, 2021 ). They may lack technological experience to conduct data analysis, or to set rules to automatically generate assignments and feedback for students via AI-driven tools (Seo et al, 2021 ). Challenges such as AI-based misunderstanding, misleadingness, limitations, and hidden ethical issues behind different platforms have been identified (Akgun & Greenhow, 2021 ; Sijing & Lan, 2018 ).…”

The Impact of AI on Teaching and Learning in Higher Education Technology

“…It's been shown in other studies that teamviewer applications, simulation, and gamification have significant benefits to instructional quality, alongside being closely linked to VR and 3-D or even using the techniques to increase performance and effectiveness through the use of AI. Another study looked at how humanoid robots that can talk and converse can improve the quality of instruction by increasing student involvement because of human-like appearances, as well as enhanced capabilities (Seo et al, 2021).…”

“…If a listener cannot tell whether they are hearing a human conversation or one with a machine, then we can say that we have an intelligent system, or artificial intelligence, thanks to Turing's imitation game. McCarthy provided one of the earliest and most influential definitions of artificial intelligence in 1956: "The study (of artificial intelligence) is to proceed on the basis of the conjecture that every aspect of learning or any other feature of intelligence can in principle be so precisely described that a machine can be made to simulate it," he said (Popenici & Kerr, 2017;Seo et al, 2021). The ability of computing systems to engage in human (processes) like learning, adaptation, synthesis, self-correction, and data use for intricate computation duties can be defined as AI.…”

How learner engagement impacts non-formal online learning outcomes through value co-creation: an empirical analysis

“…As stated by Larson (2009) from the Massachusetts Institute of Technology, "Education as a service industry has always been in urgent need of serious study. " With the advancement of technology, Seo et al (2021) introduced artificial intelligence systems into online learning to meet the interaction between learners and instructors, and provide online service for them. Online learners are online service users, so the background of online learning is service science.…”