Introduction
Technology has affected diverse facets of life by transforming how people generate, process, and use information. The education sector has been impacted in the same way with varying effects reported in different facets of learning and among selected stakeholder groups (Zhang, King and Prior, 2021). As part of the changing face of modern technology, Artificial Intelligence (AI) is changing how students and teachers interact with learning content digitally. According to Oracle (2022), AI refers to the use of machine intelligence, as opposed to biological intelligence, to complete educational tasks. Its use in the education sector is active because learning institutions are stuck at various levels of AI adoption (Zhang, King and Prior, 2021). In light of these gaps in implementation, comprehensive data is yet to be generated to understand the holistic impact of machine learning in the education sector.
The above statements form the basis for undertaking the current study. The live nature of AI adoption in the education sector will help to generate data regarding ongoing transformations in the field for policymakers and practitioners. They can use this information to predict the impact of AI on the education sector (United Nations Educational, Scientific, and Cultural Organization, 2022). Based on an analysis of current scholarly research in this field, the insights provided in this document will demonstrate that the impact of AI on the education sector has been largely positive. This statement is affirmed to the extent that machine learning has expanded the freedom to learn, boosted the effectiveness of teachers in conveying learning content to students, and minimized inequality in the education sector.
Efficiency in the Provision of Education Services
The success of the education sector depends on a myriad of factors influencing the effectiveness of students and teachers in learning. From an efficiency management perspective, the use of AI in supporting educational programs has transformed how students and teachers interact and engage with learning material (Zhang, King and Prior, 2021). Studies that have investigated the impact of AI adoption on teachers’ experiences in learning have demonstrated positive outcomes through improved effectiveness (Madanipour and Cohrssen, 2020; Zhang, King and Prior, 2021). This result is a product of the increased empowerment of teachers using AI to understand how their students learn (Oracle, 2022). The additional information about student learning, generated using AI, has enabled instructors to develop learning content that suits distinct learning styles (Rexford, 2018). The result has been increased levels of effectiveness in the manner teachers convey their learning content to students
Part of the successes of AI adoption in improving the effectiveness of teachers in conveying learning content to students stems from the generation of high-quality information about student learning processes. For example, preliminary research studies that have investigated the adoption of AI in the education sector demonstrate that AI adoption has enabled teachers to identify student weaknesses (Zhang, King and Prior, 2021). For instance, AI adoption in education has enabled teachers to detect knowledge gaps in students’ cognitive processes (Rexford, 2018). This information has enabled teachers to identify weak points in student cognitive processes and recalibrate their learning content to address them.
To provide customized solutions to students’ learning challenges, AI contains unique techniques that teachers may find relevant in evaluating educational outcomes. For example, machine learning equips instructors with data and techniques required to identify cognitive weaknesses and estimate students’ learning capabilities (Madanipour and Cohrssen, 2020). Machine learning offers various modalities for teachers to obtain quality information about their student’s learning behaviors. For example, machine learning enables teachers to examine login details on class board discussions to predict students’ interests in specific educational subjects (Zhang, King and Prior, 2021). Similarly, they can use AI-driven technologies to identify learning content that the students struggle to understand (United Nations Educational, Scientific, and Cultural Organization, 2022). This objective is achievable by analyzing the number of times students play or click on specific videos when interacting with learning content online.
The findings mentioned above are important in addressing problems affecting learners. The contribution of AI to learning could improve the effectiveness of teachers in diagnosing and solving learning challenges (Greenhalgh-Spencer and Jerbi, 2017). This way, they can develop personalized learning solutions to realize better educational outcomes (Rexford, 2018). The benefits accrued have been achieved through automation and improved data management methods (United Nations Educational, Scientific, and Cultural Organization, 2022). Broadly, these statements demonstrate that additional competencies brought by AI to the education sector affirm an increased efficiency in education services provided to students. Overall, these developments demonstrate that the adoption of AI in the education sector has increased the effectiveness of teachers in conveying learning content to their students.
Increased Flexibility to Accommodate Varying Needs of Learners
Flexibility in learning supports educational content development because it shapes how learners interact with educational materials. In this discussion, the definition of flexibility in learning is borrowed from the United Nations Educational, Scientific, and Cultural Organization (2022), which refers to the ability of educational staff to change learning content to suit varying student needs. AI has made these changes possible by empowering educators to modify their learning content. This strategy has significantly impacted students’ learning outcomes and satisfaction levels with education programs (Seo et al., 2021). The ability of AI-backed technology to accommodate the varying needs of learners has been investigated from the experiences of students and teachers in online learning (Greenhalgh-Spencer and Jerbi, 2017). Researchers suggest that AI has changed the cultural norms and expectations of students and teachers in this educational context because of the fluidity of virtual interactions (Seo et al., 2021). Therefore, technology has increased flexibility in disseminating education services to suit the varying needs of learners.
Overall, adopting AI in the education sector portends multiple benefits to both students and teachers. However, its adoption needs to be guided by the principles of equity and inclusivity because the failure to observe these principles could promote inequity in education (Greenhalgh-Spencer and Jerbi, 2017). Studies suggest that the future of AI adoption in learning will result in the development of individualized curricula (Piletic, 2022). Predictions indicate that some of the first groups of students to benefit will be those who speak foreign languages (Piletic, 2022). This statement is based on the assumption that AI will provide translation services to students who do not understand English or any other language of choice (Piletic, 2022). The same technology allows AI-backed technology to change the type of vocabulary used by foreigners based on their understanding levels (Seo et al., 2021). Automated grading systems make it possible for students to perform self-evaluations and monitor their progress. Thus, the insights highlighted above demonstrate that AI increases flexibility in learning, thereby making it possible to accommodate the varying needs of learners.
Minimizing Inequity in Education
Ideally, the provision of education services should demonstrate equity and fairness in access to information and resources. However, many countries cannot meet this standard of expectation because of geographical, infrastructural, financial, and policy limitations (United Nations Educational, Scientific, and Cultural Organization, 2022). Consequently, some governments have been unable to provide equal access to educational opportunities for all. AI has the potential to minimize these gaps in service delivery by increasing access to quality information and promoting cultural diversity in the provision of education services (Huang and Rust, 2018). These contributions are likely to minimize inequity when providing education services. The motive for using AI this way stems from the promise that AI should benefit all.
The potential of AI to eliminate inequalities and unfairness in the education system complements global initiatives to improve access to education. The United Nations Educational, Scientific, and Cultural Organization (2022) has spearheaded some of these initiatives. Stated differently, it has lent support to member countries intending to adopt AI in their education systems by equipping them with skills to assess their capacities and preparedness for the initiative. The promise aligns with the Sustainable Development Goals (SDG)-4, which seeks to enhance human capabilities through learning (United Nations Educational, Scientific, and Cultural Organization, 2022). This goal provides a broader framework for countries to use in employing AI to improve their educational outcomes (United Nations Educational, Scientific, and Cultural Organization, 2022). The strategy may improve their ranking in the human development index.
The findings highlighted above highlight the importance of preparedness before AI adoption. This is a precondition for its effective deployment in the education sector. Retraining is necessary to reskill workers because AI requires users to have the technical knowledge to interpret the output (Madanipour and Cohrssen, 2020). Consequently, it is prudent for education institutions to retrain their teachers to use this technology in their learning processes.
Retraining teachers for AI use will ensure they are equipped to manage the challenges of using new technology. Therefore, it is vital to develop a skilled workforce and student population to use this technology and improve learning outcomes (Madanipour and Cohrssen, 2020; Walsh, 2017). Overall, the insights highlighted above demonstrate that AI can minimize inequalities in the education system and promote fairness if implemented correctly. In the end, there needs to be a robust plan of implementation to manage the challenges posed by AI use in an unequal society.
Conclusion
The findings presented in this paper demonstrate that the impact of AI on education is positive. This outcome has been affirmed by the potential of AI to increase the efficiency of education services offered to students. Additionally, AI has increased flexibility when providing or consuming educational content to both students and teachers. This contribution has created degrees of engagement between students and teachers to suit varying learner needs. Broadly, the insights contained in this document affirm that the impact of AI on education has been largely positive, to the extent that it increases the efficiency of education services and makes teaching flexible to accommodate varying learner needs. Overall, this study’s findings may help identify the strengths of AI that could be exploited to realize maximum gains in the education sector.
Reference List
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