The Role Of Artificial Intelligence In Instructional Design



AI In ID: How Artificial Intelligence Can Transform Instructional Design

The rapid growth of Artificial Intelligence (AI) is expected to disrupt many sectors, including education. The traditional information and communications technology (ICT) tools were intended to facilitate improvements in teaching and learning. Unfortunately, the reality is that many priorities in the country’s education system remain unmet. Cardona et al. (2023) contend that educators desire technology-enhanced approaches that address these priorities but remain safe, effective, efficient, and scalable. AI is broadly seen as the answer to addressing the needs of the modern learning and teaching environment, as it is poised to revolutionize Instructional Design (ID) and transform how educators design, develop, and deliver instructional content.

AI’s Role In Instructional Design

1. Achieve Educational Priorities More Effectively

Among the top reasons for AI in the education industry, as Cardona et al. (2023) document, is its ability to facilitate the attainment of educational priorities in a greater, scalable, and cost-effective manner. Since the pandemic, advancing teaching to meet the needs of distance and hybrid learning has been a policy priority. Cardona et al. (2023) view AI as a solution to adapting learning resources to meet students’ needs and strengths. AI tools such as automated assistants will provide teachers with greater assistance and extend the support teachers provide to individual students when they run out of time. In addition, AI can help develop resources that meet the unique cultural needs and experiences of different learners. In other words, AI can provide for greater customizability of curricular resources.

2. Improve Content Creation

Knowing what courses to offer and when can be a complex process for learning institutions. The market today is dynamic, and what is trending now may become irrelevant in the future. So, Klutka et al. (2020) cite that AI tools, such as Stellic, can be instrumental in optimizing course offerings by helping administrators understand what courses to offer in the future and when to offer certain courses to meet student demands and ensure effective learning. AI-powered program planning can be useful in budgeting and improving student retention.

Besides course planning, AI has proven invaluable in curating content for learning materials. In the world of AI and Machine Learning, content curation is data-driven, where AI systems examine various resources to help Instructional Designers (IDs) focus on essential information and learning needs. AI tools can quickly analyze large datasets in real time and identify patterns and trends that IDs may not otherwise notice, creating more informed and effective instructional materials. So, AI does not only help plan what courses to offer but also contributes to curating content for these courses.

3. Strengthen Formative Assessments

The importance of feedback loops in improving teaching and learning has seen formative assessment become a key use of educational technology (EdTech). According to Cardona et al. (2023), AI models and AI-powered systems keep users in the loop, meaning focusing on parties involved in formative assessments, from teachers, students, school administrators, and families/caregivers, among others. In other words, AI has the potential to revolutionize formative assessments and adapt ID to meet learning needs. The assessment process can be automated using AI algorithms, and feedback can be provided immediately where it would otherwise not be possible using the traditional assessment approaches.

Moreover, AI tools can reduce teachers’ load related to formative assessments and allow them to focus their specialized judgment on important qualities. Formative assessment is already a complex and time-consuming process. Cardona et al. (2023) note that a typical formative assessment encompasses seven dimensions—enabling questions, measuring competencies, real-time feedback, accessibility, adapting to learner ability, embedded assessment in the learning process, and assessing ongoing learning. The authors suggest that embedding AI tools in the learning process to provide ongoing feedback as learning continues rather than later can better support learning by granting instructors more time to teach.

The role of AI models in formative assessments is expected to extend beyond just assessing learning outcomes. As Niemi et al. (2023) point out, AI systems, through wearable technologies, can be used to create models for assessing student well-being. The model would include learning outcomes, physical, emotional, and psychological wellness, social and emotional skills, and social relationships (Niemi et al., 2023). Besides student well-being assessment, intelligent AI applications can also be instrumental in enhancing student well-being, with the most common example being chatbots or conversational agents. Niemi et al. (2023) explain that these tools leverage language processing techniques with psychological canceling methods to respond to students’ questions and requests and reduce their health problems.

4. Empower Simulation-Based Learning

AI solutions are taking simulation-based learning to the next level. A recent study by Dai and Ke (2022) shows that AI has a variety of applications in simulation-based learning, including Intelligent Tutoring Systems (ITSs), Virtual Reality, simulation games, medical simulations, and smart edutainment. The growing need for personalized learning in today’s internet-based or hybrid learning models has popularized AI-enabled virtual agents. Dai and Ke (2022) further point out that virtual AI agents are crucial in serving as conversational partners, information brokers, instructional experts, and expert systems in a simulation-based learning environment. Fully functional AI-powered instructional simulations give students concrete formats of what it means to work like a professional.

5. Shift In Traditional Roles

AI is poised to change how IDs work by facilitating collaboration, high-order thinking, and creativity. Many fear that introducing AI and automating some of the tasks and processes in ID will lead to job losses. AI replacing roles in the traditional ID system is only a misconception. Instead of the threat of job losses, AI will allow for the roles of IDs to evolve. For instance, the technology will see IDs become consultants and utilize AI solutions to plan and create content and align learning objectives with the most appropriate and customizable instructional strategies. At the same time, learning institutions will be able to work closely with AI systems to ensure learning content is quality, accurate, and relevant.

Conclusion

Integrating AI in ID is changing how educators design, develop, and deliver instructional content. AI systems are perceived as the modern solutions to the modern problems in the education system. Face-to-face contact between students and teachers and among students themselves is becoming more limited as online and hybrid learning models become more widespread. So, AI systems play a huge role in offering personalized learning experiences for more engaging, efficient, and effective teaching and learning. The technology has forced IDs to rethink their approaches to ID and fuse instructional environments with immersive and interactional AI-powered educational technologies.

References

  • Cardona, M. A., Rodriguez, R. J. & Ishmael K. 2023. “Artificial Intelligence and the Future of Teaching and Learning: Insights and Recommendations.” U.S. Department of Education, Office of Educational Technology, Washington, DC, May 2023.
  • Dai, C. P., & Ke, F. 2022. “Educational applications of artificial intelligence in simulation-based learning: A systematic mapping review.” Computers and Education: Artificial Intelligence, Vol. 3, 100087.
  • Klutka, J., Ackerly, N. & Magda A. 2020. “Artificial Intelligence in Higher Education: Current Uses and Future Applications.” LearningHouse: A Wiley Brand. Wiley Education Services.
  • Niemi, H., Pea, R. D., & Lu, Y. 2023. AI in Learning: Designing the Future. New York: Springer International Publishing, 345.



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