Introduction
Rooted in computer science, Artificial Intelligence (AI) is defined by the development of digital systems that can perform tasks, which are dependent on human intelligence (Rexford, 2018). Interest in the adoption of AI in the education sector started in the 1980s when researchers were exploring the possibilities of adopting robotic technologies in learning (Mikropoulos, 2018).
Their mission was to help learners to study conveniently and efficiently. Today, some of the events and impact of AI on the education sector are concentrated in the fields of online learning, task automation, and personalization learning (Chen, Chen and Lin, 2020). The COVID-19 pandemic is a recent news event that has drawn attention to AI and its role in facilitating online learning among other virtual educational programs. This paper seeks to find out the possible impact of artificial intelligence on the education sector from the perspectives of teachers and learners.
AI’s Impact on Education
Technology has transformed the education sector in unique ways and AI is no exception. As highlighted above, AI is a relatively new area of technological development, which has attracted global interest in academic and teaching circles. Increased awareness of the benefits of AI in the education sector and the integration of high-performance computing systems in administrative work have accelerated the pace of transformation in the field (Fengchun et al., 2021). This change has affected different facets of learning to the extent that government agencies and companies are looking to replicate the same success in their respective fields (IBM, 2020). However, while the advantages of AI are widely reported in the corporate scene, few people understand its impact on the interactions between students and teachers. This research gap can be filled by understanding the impact of AI on the education sector, as a holistic ecosystem of learning.
As these gaps in education are minimized, AI is contributing to the growth of the education sector. Particularly, it has increased the number of online learning platforms using big data intelligence systems (Chen, Chen and Lin, 2020). This outcome has been achieved by exploiting opportunities in big data analysis to enhance educational outcomes (IBM, 2020). Overall, the positive contributions that AI has had to the education sector mean that it has expanded opportunities for growth and development in the education sector (Rexford, 2018). Therefore, teachers are likely to benefit from increased opportunities for learning and growth that would emerge from the adoption of AI in the education system.
The Impact of AI on Teachers
The impact of AI on teachers can be estimated by examining its effects on the learning environment. Some of the positive outcomes that teachers have associated with AI adoption include increased work efficiency, expanded opportunities for career growth, and an improved rate of innovation adoption (Chen, Chen and Lin, 2020). These benefits are achievable because AI makes it possible to automate learning activities. This process gives teachers the freedom to complete supplementary tasks that support their core activities. At the same time, the freedom they enjoy may be used to enhance creativity and innovation in their teaching practice. Despite the positive outcomes of AI adoption in learning, it undermines the relevance of teachers as educators (Fengchun et al., 2021). This concern is shared among educators because the increased reliance on robotics and automation through AI adoption has created conditions for learning to occur without human input. Therefore, there is a risk that teacher participation may be replaced by machine input.
Performance Evaluation emerges as a critical area where teachers can benefit from AI adoption. This outcome is feasible because AI empowers teachers to monitor the behaviors of their learners and the differences in their scores over a specific time (Mikropoulos, 2018). This comparative analysis is achievable using advanced data management techniques in AI-backed performance appraisal systems (Fengchun et al., 2021). Researchers have used these systems to enhance adaptive group formation programs where groups of students are formed based on a balance of the strengths and weaknesses of the members (Live Tiles, 2021). The information collected using AI-backed data analysis techniques can be recalibrated to capture different types of data. For example, teachers have used AI to understand students’ learning patterns and the correlation between these configurations with the individual understanding of learning concepts (Rexford, 2018). Furthermore, advanced biometric techniques in AI have made it possible for teachers to assess their student’s learning attentiveness.
Overall, the contributions of AI to the teaching practice empower teachers to redesign their learning programs to fill the gaps identified in the performance assessments. Employing the capabilities of AI in their teaching programs has also made it possible to personalize their curriculums to empower students to learn more effectively (Live Tiles, 2021). Nonetheless, the benefits of AI to teachers could be undermined by the possibility of job losses due to the replacement of human labor with machines and robots (Gulson et al., 2018). These fears are yet to materialize but indications suggest that AI adoption may elevate the importance of machines above those of human beings in learning.
The Impact of AI on Students
The benefits of AI to teachers can be replicated in student learning because learners are recipients of the teaching strategies adopted by teachers. In this regard, AI has created unique benefits for different groups of learners based on the supportive role it plays in the education sector (Fengchun et al., 2021). For example, it has created conditions necessary for the use of virtual reality in learning. This development has created an opportunity for students to learn at their pace (Live Tiles, 2021). Allowing students to learn at their pace has enhanced their learning experiences because of varied learning speeds. The creation of virtual reality using AI learning has played a significant role in promoting equality in learning by adapting to different learning needs (Live Tiles, 2021). For example, it has helped students to better track their performances at home and identify areas of improvement in the process. In this regard, the adoption of AI in learning has allowed for the customization of learning styles to improve students’ attention and involvement in learning.
AI also benefits students by personalizing education activities to suit different learning styles and competencies. In this analysis, AI holds the promise to develop personalized learning at scale by customizing tools and features of learning in contemporary education systems (du Boulay, 2016). Personalized learning offers several benefits to students, including a reduction in learning time, increased levels of engagement with teachers, improved knowledge retention, and increased motivation to study (Fengchun et al., 2021). The presence of these benefits means that AI enriches students’ learning experiences. Furthermore, AI shares the promise of expanding educational opportunities for people who would have otherwise been unable to access learning opportunities. For example, disabled people are unable to access the same quality of education as ordinary students do. Today, technology has made it possible for these underserved learners to access education services.
Based on the findings highlighted above, AI has made it possible to customize education services to suit the needs of unique groups of learners. By extension, AI has made it possible for teachers to select the most appropriate teaching methods to use for these student groups (du Boulay, 2016). Teachers have reported positive outcomes of using AI to meet the needs of these underserved learners (Fengchun et al., 2021). For example, through online learning, some of them have learned to be more patient and tolerant when interacting with disabled students (Fengchun et al., 2021). AI has also made it possible to integrate the educational and curriculum development plans of disabled and mainstream students, thereby standardizing the education outcomes across the divide. Broadly, these statements indicate that the expansion of opportunities via AI adoption has increased access to education services for underserved groups of learners.
Overall, AI holds the promise to solve most educational challenges that affect the world today. UNESCO (2021) affirms this statement by saying that AI can address most problems in learning through innovation. Therefore, there is hope that the adoption of new technology would accelerate the process of streamlining the education sector. This outcome could be achieved by improving the design of AI learning programs to make them more effective in meeting student and teachers’ needs. This contribution to learning will help to maximize the positive impact and minimize the negative effects of AI on both parties.
Conclusion
The findings of this study demonstrate that the application of AI in education has a largely positive impact on students and teachers. The positive effects are summarized as follows: improved access to education for underserved populations improved teaching practices/instructional learning, and enhanced enthusiasm for students to stay in school. Despite the existence of these positive views, negative outcomes have also been highlighted in this paper. They include the potential for job losses, an increase in education inequalities, and the high cost of installing AI systems. These concerns are relevant to the adoption of AI in the education sector but the benefits of integration outweigh them. Therefore, there should be more support given to educational institutions that intend to adopt AI. Overall, this study demonstrates that AI is beneficial to the education sector. It will improve the quality of teaching, help students to understand knowledge quickly, and spread knowledge via the expansion of educational opportunities.
Reference List
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