Artificial Intelligence in Education: A Review

Last Updated on: 4th June 2024, 12:45 pm

RAKESH KUMAR¹, HITESH PURI², AND SHIVAM KUMAR³

¹Student of Master of Computer Application, Chandigarh Group of Colleges, Landran Mohali, India

² Student of Master of Computer Application, Chandigarh Group of Colleges, Landran Mohali, India

³ Student of Master of Computer Application, Chandigarh Group of Colleges, Landran Mohali, India

ABSTRACT The purpose of this study was to assess the impact of Artificial Intelligence (AI) on education. Premised on a narrative and framework for assessing AI identified from a preliminary analysis, the scope of the study was limited to the application and effects of AI in administration, instruction, and learning. A qualitative research approach, leveraging the use of literature review as a research design and approach was used and effectively facilitated the realization of the study purpose. Artificial intelligence is a field of study and the resulting innovations and developments that have culminated in computers, machines, and other artifacts having human-like intelligence characterized by cognitive abilities, learning, adaptability, and decision-making capabilities. The study ascertained that AI has extensively been adopted and used in education, particularly by education institutions, in different forms. AI initially took the form of computer and computer related technologies, transitioning to web-based and online intelligent education systems, and ultimately with the use of embedded computer systems, together with other technologies, the use of humanoid robots and web-based chatbots to perform instructors’ duties and functions independently or with instructors. Using these platforms, instructors have been able to perform different administrative functions, such as reviewing and grading students’ assignments more effectively and efficiently, and achieve higher quality in their teaching activities. On the other hand, because the systems leverage machine learning and adaptability, curriculum and content has been customized and personalized in line with students’ needs, which has fostered uptake and retention, thereby improving learners experience and overall quality of learning.

INDEX TERMS Education, artificial intelligence, leaner.

I. INTRODUCTION

As illustrated by Henry Ford in the analogy, innovation does not mean working that the society should work only with what has been the norm, such as finding ways of making horses faster. Sometimes, it is necessary to search beyond the norm, develop new ways of doing things. Instead of making horses faster, build the automobile, which will be faster than the horse and take a person from Point A to Point B faster. These principles and approaches have driven the rapid developments in technology experienced over the years, particularly in the education sector.

The year is 1950. Dr. Potter, a tenured professor at a local university shuffles to a class, a heavy load of papers under his arm. He has just marked all the papers, after reading

and assessing the grammar and content of each of the papers handed in by the 40 students in his class. Going through some of the papers, Dr. Potter felt that the content in there had been plagiarized from other sources, but he had no sure way of ascertaining from where the student had copied the content materials. Fast forward, in 2019, Dr. Potter now walks into a class, barely carrying any papers, but having read, flagged incidents of plagiarism for disciplinary action, and graded papers for an even larger number of students. Sometimes, when he is off campus, he can dial-in or video conference into the class and can still perform his duties and responsibilities leveraging technology. The introduction, advancements, and proliferation of technology, more particularly, artificial intelligence, has made it easier for instructors to dispense their duties more effectively and efficiently. These technological innovations have also permeated other sectors of the academia, fostering effectiveness and efficiency.

Prior to the introduction of computers and other related technologies, instructors and students, engaged in instructions and learning mechanically, or through the pure application of natural human effort. With the introduction of microcomputers, and by extension, personal computers in the 1970s, which according to Flamm, provided more computing power and marked an important transition to electronic computers for the mass market [1]. In agreement, CampbellKelly opined that with developments of the electronic computers, more particularly, and the availability of the same for different entities across different sectors of the economy, was precipitated by the developments of personal computers in the 1970s [2]. Personal computers development made it possible for individuals and other non-governmental entities to own and use computers for different reasons. These transitions harbingered the proliferation of computers in different sectors of the economy and society.

Leveraging earlier research into programmed instructions from the mid-1900s, developments in computers and related computing technologies saw the use of computers in different

parts of the education sector, more specifically, different departments in educational institutions, such as the development of computer aided instruction and learning (CAI/L) in classroom interactions [3]. Later developments in computers and computer related technologies, including networking, the internet, the world wide web, and increased processing, computing, and other capabilities, including different programs and software packages that are task oriented, have seen the increased application of computers in different ways in the education sector. More specifically, in different departments in education institutions.

Computer and information communication technologies have over the years continued to evolve, leading to the development of artificial intelligence. Artificial intelligence, according to Coppin, is the ability of machines to adapt to new situations, deal with emerging situations, solve problems, answer questions, device plans, and perform various other functions that require some level of intelligence typically evident in human beings [4] (p.4). In another definition, Whitby defined artificial intelligence as the study of intelligence behavior in human beings, animals, and machines and endeavoring to engineer such behavior into an artifact, such as computers and computer-related technologies [5] (p.1). Drawing from these definitions, it is evident that artificial intelligence is the culmination of computers, computer-related technologies, machines, and information communication technology innovations and developments, giving computers the ability to perform near or human-like functions. In line with the adoption and use of new technologies in education, artificial intelligence has also been extensively leveraged in the education sector.

For example, Devedžić observed that Web Intelligence (WI) and Artificial Intelligence (AI) research and development focuses on different elements, including machine learning to create distributed intelligence and creating a balance between Web technology and intelligent agent technology, agent self-organization, learning, and adaptation among other aspects of WI and AI that enable it to adapt to its environment and perform intelligent functions, which should be leveraged to foster improvements in the education sector [6] (p.29). Indeed, artificial intelligence has been adopted and permeated various areas of the education sector, or departments in educational institutions. Use of artificial intelligence in education has had a major impact, including improved efficiency, global learning, customized/personalized learning, smarter content, and improved effectiveness and efficiency in education administration among others [7]. Artificial intelligence continues to develop, and new ways of application in education emerge.

1. ARTIFICIAL INTELLIGENCE IN CURRENT EDUCATION

The mention of artificial intelligence brings to mind a supercomputer, a computer with immense processing capabilities, including adaptive behaviour, such as inclusion of sensors, and other capabilities, that enable it to have human-like cognition and functional abilities, and indeed, which improve the supercomputers interaction with human beings. Indeed, different motion pictures have been made to showcase the abilities of AI, such as in smart buildings, such as the ability to manage air quality in a building, temperatures, and or playing music depending on the sensed mood of the occupants of the space. Within the education sector, there has been increased application of artificial intelligence, going over and above the conventional understanding of AI as a supercomputer to include embedded computer systems.

For example, embedded into robots, AI, or computers and supporting equipment enable the creation of robots that improve the learning experience of the student, from the most basic unit of education, early childhood education. Indeed, Timms posited that Robots or the application of robots, working together with teachers or colleague robots (Robots) are being applied to teach children routine tasks, including spelling and pronunciation and adjusting to the students’ abilities [7]–[9]. Similarly, the web-based and online education, as enumerated in different studies, has transitioned from simply availing materials online or on the web for students to simply download, study, and do assignments to just pass, to include intelligent and adaptive web-based systems that learn instructor and learner behavior to adjust accordingly, to enrich the educational experience [6], [11], [18], [19]. Artificial intelligence in education, according to Chassignol et al. has been incorporated into administration, instruction or teaching, and learning [11]. These areas, which Chassignol et al. identify as the framework for analyzing and understanding artificial intelligence in education, will form the scope of this study.

The application of AI algorithms and systems in education are gaining increased interest year by year. Fig. 1 shows the rising number of papers published in the topics ‘‘AI’’ and ‘‘Education’’ from Web of Science and Google scholar since 2010. Note that the papers published in 2015-2019 accounted for a large proportion, i.e., 70% of all the papers

FIGURE 1. Papers in Web of Science and Google Scholar in the last ten year with key words ‘‘AI’’ and ‘‘Education’’.

indexed. As education evolves, researchers are trying to apply advanced AI techniques, i.e., deep learning, data mining, to deal with complex issues and customize teaching method for individual student.

1. PURPOSE OF THE STUDY

With the continued application or use of information technology, it is inevitable that it has impacted the education in different ways. This study seeks to assess how the use of AI, in its different forms, in education, has impacted or affected different aspects of education. More particularly, the study will seek to assess how AI has affected teaching, learning, and administration and management areas of education. It is anticipated that the study will ascertain that AI has fostered effectiveness and efficiency in the performance of administrative tasks in education, and overall fostered improved instructional and learning effectiveness in education.

This study will benefit various stakeholders in the education sector. It will contribute to the growing study and development of knowledge, theory, and empirical findings that identify and discuss the different ways in which AI has affected education. It will benefit scholars, professionals, and policy makers, such as administrators, management and leadership of educational institutions and the education sector, by fostering evidence-based decision-making and management and leadership practices in the sector. The findings will also augment the findings by other studies and inform government policy and actions aimed at fostering meaningful use of information technology, particularly, AI, in the education sector. For example, with an understanding of the impact of AI on education sector, and an evaluation of the exact nature of such impact, including improved instructional and learning effectiveness, the government, working with educational institutions can develop a policy, strategy, and initiatives that promote the beneficial impact or effects and mitigate the possible adverse effects of AI on education.

1. REVIEW STRATEGY

1) MATERIALS AND METHODS

The study seeks to assess the impact of AI on education. More particularly, it seeks to ascertain how AI has affected education, looking at various aspects of education, including administration, instruction, and learning. Accordingly, the study takes a retrogressive approach, entailing assessing secondary data and materials or studies that have been undertaken. Indeed, Snyder posited that a systematic or semi systematic literature review, a review of secondary data, provides a deeper understanding of the study phenomenon [8]. This approach ensures that the study is premised on empirical or is evidence backed because only studies, including meta analysis, that have been conducted on the subject matter, support the identification, analysis, understanding, and synthesis of the ways in which AI has affected and impacted education. Generally, a qualitative research design, incorporating qualitative content and thematic analysis is used to assess the different ways. Thematic and content analysis entails undertaking a thorough critique of each piece of text and identifying recurring themes from a review of different texts, which then form the basis for inferences and conclusions for descriptive studies [10]. It is an appropriate research design and strategy considering the aim of this study, to assess the impact of AI on education.

2) SEARCH STRATEGY

Key words and search strings will be used to search different databases, including EBSCOhost, ProQuest,Web of Science. In addition, the key words and search strings are used to search Google Scholar to identify articles from different journals that have focused on researching the impact of AI on education. The journals containing the articles are then searched on Scimago and the journals with an H-Index of 20 and above are included in the study. An H-Index is an author level measure of scientific productivity in terms of publications and citations and by extension, contribution to science and scholarly pursuits; and the higher the H-Index, the more reputable the journal and the authors published in the journal are. A total of more than forty articles, including journal articles, professional publications, and government and institutional reports were selected after the use of an eliminative process.

1. ARTIFICIAL INTELLIGENCE IN EDUCATION From a review of the convergence of AI with education as discussed by Chassignol et al., the scope of this study will cover the impact of AI on the administration and management, instruction or teaching, and learning functions or areas in the education sector. This section of the report provides an overview and brief discussion of the results of the study from a review of various articles that have assessed the nature and impact of artificial intelligence in the education sector.
2. NATURE OF ARTIFICIAL INTELLIGENCE

Artificial intelligence (AI) is conventionally heavily associated with computers. However, it is evident, from a review of the various articles, particularly within the context of the education sector, that while computers may have formed the basis the development of artificial intelligence, there is a gravitation away from the computer alone, the hardware and software, or the equipment, as being artificial intelligence. Embedded computers, sensors, and other emerging technologies have facilitated the transfer of artificial intelligence to machines and other items, such as buildings and robots [11]. Indeed, Chassignol et al. provides a two-faceted definition and description of AI. They define AI as a field and a theory. As a field of study, they define AI as a study area in computer science whose pursuits are aimed at solving different cognitive problems commonly associated with the human intelligence, such as learning, problem solving, and pattern recognition, and subsequently adapting [11]. As a theory, Chassignol et al. defined AI as a theoretical framework guiding the development and use of computer systems with the capabilities of human beings, more particularly, intelligence and the ability to perform tasks that require human intelligence, including visual perception, speech recognition, decision-making, and translation between languages [11]

(p.17).

Recently, AI and machine learning are widely studied to be applied in mobile devices, which aim to enhance computation quality and create possibilities for new applications, such as face unlock, speech recognition, natural language translation, and virtual reality. However, machine learning requires huge computation capability to perform complex training and learning. To address this issue, someplatforms for running computationally efficiently were proposed. In 2016, Qualcomm introduced the Snapdragon Neural Processing Engine to accelerate the execution of neural networks with their GPU processors. HiSilicon proposed the HiAI platform for running neural networks. It should be noted that Android Neural Networks API was designed to quickly execute machine learning models on mobile devices [37]. This API brings a lot of utility to the mobile by reducing network latency and complexity. With respect to AI-related learning network, SqueezeNet, MobileNet, and Shufflenet are well developed for mobile phones [38]. The technical development of AI in mobile devices takes mobile education to the higher level, which provides convenience by helping student in less time and achieves interactive and personalized learning. For instance, virtual reality facilitates the learning process beyond the learning space to create a global classroom since AI can connect students to the virtual classroom. In addition, AI-based chatbots provide a personalized online learning, and also turn instructor into chat conversations. This technology can assess the students’ level of understanding.

1. TECHNICAL ASPECTS OF AI IN EDUCATION

AI-aided education includes intelligent education, innovative virtual learning, and data analysis and prediction. Major scenarios of AI in education and key technologies supporting are listed in Table 1. Note that AI-enable education is playing a more important role as learning requirements promotes [12]. Intelligent education systems provide timely and personalized instruction and feedback for both instructors and learners. They are designed to improve learning value and efficiency by multiple computing technologies, especially machine learning related technologies [18], which are closely related to statistics model and cognitive learning theory.

1) AI EDUCATION MODEL

In AI learning system, learner model is critical for improving independent learning capabilities. It is established based on behavior data of learners generated from the learning process. Learners’ thinking and capability is analyzed to assess their learning abilities. Then knowledge analysis are mapped to obtain learners’ knowledge mastery. Learner modeling establishes connections between learning results and various factors including learning materials, resources and teaching behaviours [39]. Knowledge model establishes knowledge structure map with detailed learning contents, usually including expert knowledge, rules of making mistakes often made by learners and misunderstanding [44]. Combining knowledge field model and learner model, teaching model determines the rules to access knowledge field, which enables instructors to tailor teaching strategies and actions. As education evolves, learners are likely to behavior positively, take actions or seek for help. AI system can always be prepared to offer aid from tutoring model’s built-in teaching theories. User interface explains learners’ performance through multiple input media (voice, typing and click) and provides output (texts, figures, cartoons and agencies). The advanced human machine interface provides AI-related functions including natural language interaction, speech recognition and learners’ emotion detection.

TABLE 1. Techniques for scenarios of AI education.

FIGURE 2. Technological structure of AI education.

2) INTELLIGENT EDUCATION TECHNOLOGIES

Machine learning, learning analytics, and data mining are closely related technologies for education. At present, two communities have evolved based on learning analytics and educational data mining. They overlap in objectives and techniques and benefit from a variety of disciplines, including machine learning, data mining, psychometrics of statistics, and data modelling [41]. The field of learning analytics is more focused on learning content management systems and large-scale test results. Data mining originates from the community of intelligent tutoring systems, work on very smallscale cognition.

a: MACHINE LEARNING

The core of machine learning is knowledge discovery, the process of parsing based on sampling data set known as ‘‘training data’’, generating meaningful patterns and a structured knowledge. For instance, machine learning can help create recommendations for students as they select classes, even choose universities. It leverages achievements data, aspirations, preferences of students to ‘‘match-make’’ institutions where they can be best developed. Moreover, this every concept is being digested by students [42]. In this way, instructors can adjust the teaching method to work well based on students’ cumulative records, which may help students grasp course material better. In particular, for student assessment, image recognition and prediction of machine learning can be used to grade student assignments and exams, with faster and more reliable results than human being. It should be noted that deep learning, the subfield of machine learning, attracts much attention. This widely used techniques includes decision tree learning, inductive logic programming, clustering, reinforcement learning and Bayesian networks. From technique perspective, deep learning emphasizes on increasingly meaningful representations from learning successive layers. These layer features are extracted via models called neural networks structured in literal layers stacked on top of each other.

c: DATA MINING

Educational data mining tries to generate systematic and automated responses to learners. AI-based educational data mining aims for developing inherent association rules, and offering knowledge objects to students to meet their personal needs. For instance, students’ demographic characteristic data and grading data can be analysed from a small number of written assignments [44]. It can be achieved by a machine learning regression method that can be also used to predict a student’s future performance. Furthermore, data mining is becoming a powerful tool to improve the learning process and knowledge mastery, leading to a better understanding of the educational settings and learners. In other words, data mining can be seen as pattern discovery and predictive modelling applied in extract hidden knowledge, which allows instructors to make adjustments to improve curriculum development in educational system. One of important applications is that data mining-based AI can achieve personalized learning from knowledge field data, where students perform their own learning, at their own pace and deciding their own learning method aided by AI. Ideally, using personalized learning, students choose what they’re interested in, and instructors adjust teaching course and method to the students’ interests [43]. With data mining, AI can build its intelligence (e.g., using machine learning) more accurately and outcome is more reliable.

1. THE ROLE OF AI IN EDUCATION

Timms makes an interesting observation, AI is very powerful and has the potential to permeate and heavily cause changes in different sectors of the society, with the education sector being one that is likely to be majorly impacted by AI. Indeed, from the different articles reviewed, it is evident that AI has been adopted and applied in the education sector, where it has fostered improvements in different areas of the sector. More specifically, within the context of the narrative and framework proposed by Chassignol et al., which also forms the scope of the study, it is evident that AI has been applied in education, more particularly in administration and teaching, and subsequently, influencing or impact students’ learning.

Indeed, even from a review of other works, there is evidence of AI, in the context of application in the education sector, going over and above the conventional perception of AIs as computer systems only. Pokrivcakova’s definition and description of AI in education provides an overview and summary of the nature of application of the same in education [14]. Pokrivcakova posited that the design and implementation of AI brings together different professionals, including system designers, data scientists, product designers, statisticians, linguists, cognitive scientists, psychologists, education experts and many other professionals [14] (p.138). The implication therefore is that AI, in education, is designed to perform more than just the normal computers and computerrelated functions. Indeed, Sharma posited that AI, in its entirety, supersedes the conventional understanding of the different technological applications in education, web-based, online, distance, and computer-assisted instruction courses and learning.

More specific application of AI in education, as evidenced form the different articles reviewed takes different forms. Chassignol et al. highlighted the extensive application of AI in different areas, including content development, teaching methods, student assessment, and communication between teacher and students [11] (p. 22). For example, according to the study by Chassignol et al. AI has been extensively applied in curriculum development and content personalization, teaching and pedagogical methods, assessment, and communication exchanges between teachers and students. Chassignol et al. provide examples of different platforms and applications of AI, such as Interactive learning environments (ILEs), which are used to manage performance and provide feedback and exchanges between teachers and students; Intelligent tutoring systems, such as ACTIVE Math, MATHia, Why2Atlas, Comet, and Viper which have been used at different levels of the education system to by educators or instructors for different subjects at different levels of education, as well as extensive use in learning assessment to track performance and improve the available pedagogical tools [11]. Similar applications are evident in other studies.

Making similar observations and arguments, Sharma et al. observed that AI in education has taken the form of adaptive learning systems, intelligent tutoring systems, and other systems that improve the quality of administrative processes, instructions, and learning [13]. In agreement, Pokrivcakova observed that in education, AI takes the form of intelligent systems with adaptive capabilities [14]. These tenets andcharacteristics of the systems enable AI in education to perform a wide range of tasks traditionally or conventionally performed by instructors, while at the same time improving students’ learning experiences through coaching students and customizing learning to students’ expectations and needs [14]. Mikropoulos and Natsis in their article, also describe another aspect of AI in instructions, virtual reality (VR) and three dimension (3-D) technology, observing that VR presents immense opportunities for the learning process, integration of simulation and 3-D technology because it enables simulation and provides learners with an opportunity for experiential learning.

Indeed, it is evident, as the United Nations Education Scientific and Cultural Organization (UNESCO) observed, that AI has permeated various sectors of the society, more particularly, the education sector, as discussed for example, instructions or teaching methods, approaches, and tools [16]. Other areas or ways in which AI has been implemented in education include learning and administration, which has been precipitated by changes in the general environment. Indeed, according to Wartman and Combs education is changing in tandem with changes in the employment or professional world, necessitating the incorporation of AI in instruction and learning [17]. For example, there is heavy use of AI in the medical profession, which necessitates exposing students to AI through use of the technology in medical education to prepare them for the experiences in the real world [17]. The trend and argument identified and presented by Wartman and Combs are echoed in other studies and publications, which demonstrate other applications of AI in education.

1) AI IN EDUCATION ADMINISTRATION

In this section, a summary of the findings on the application of AI in education, with a particular focus on administrative functions is presented. One of the key areas in education, identified as likely to be impacted by AI, is the performance of different administrative tasks in the education process, such as students’ assignments and papers reviews, grading, and providing feedback to students. According to Sharma et al. AI in education, particularly in distance and online education, where AI has enhanced efficiencies in institutional and administrative services [13]. Indeed, specific programs, such as Knewton, ease the burden on instructors because they provide a platform for feedback to students premised on the interaction on the platforms. Similar positions are evident in other studies and publications, which discuss systems that make the administrative tasks easier.

For example, Rus et al. posited that intelligent tutoring systems (ITSs) perform a wide range of functions, including grading and providing students with feedback on their work [12]. Instructors, working with ITS achieve improved efficiencies in various administrative tasks, as well as their core responsibilities, providing guidance and instructions to help students excel in their studies. The findings and arguments by Mikropoulos and Natsis augment the arguments and findings in these studies; leveraging and using AI in education has fostered effectiveness and efficiency in the performance of administrative tasks, such as grading of students’ assignments [15]. Indeed, a scrutiny of the online learning environment today, shows programs that make it possible for instructors to perform various administrative tasks, such as TurnItIn and Ecree, which give suggestive grading and check plagiarism on students’ assignments. AI has improved efficiencies in the performance of different administrative tasks that instructors, would require a lot of time to perform in the absence of AI.

and highly interactive simulation as a pedagogical tool, which helps students have a better understanding of demonstrated concepts [15]. Similarly, Wartman and Combs highlight the use of AI, in the form of virtual reality and  simulation in medical education, which takes medical students through practical aspects of their education, such as operations and understanding human anatomy, among other subjects.

Other studies have also highlighted the integration of AI into machines or robots and creation of powerful instructional tools and improvement of the quality of the applied pedagogical strategies. Indeed, Timms highlights that another key form of application of AI in education as an instruction tool is the integration of AI in education principles in robots, the development and use of robots as teacher assistants and colleagues, Robots, which can be used to undertake basic and even advanced teaching tasks, such as teaching students to read and pronounce words [7]. Indeed, Sharma et al. observed that the integration or the use of AI in education, more particularly, integration with other technologies and use as instructional tools, has resulted in the development and use of better teaching tools [13]. On the other hand, Pokrivcakova also highlights the integration of AI into computer programs, and the development and use of chatbots, or online computerbased robots with conversational and dialogue abilities to answer routine student queries, and in some instances, disseminate instructional materials[14].AI equips the humanoid or other robots with cognitive and decision-making abilities, as well as dialogue and conversation abilities, and subsequently, enable their use as instructional and pedagogical tools.

3) AI IN LEARNING

Learning, which is an integral part of education, is another aspect of education that is within the scope of the study. From an evaluation and analysis of the different articles included in the study, different ways in which AI has been adopted and implemented or leveraged in fostering students’ learning were identified. Further, specific programs or applications that leverage AI to improve student learning were identified. An important way in which AI has been applied in improving students’ learning is the customization and personalization of curriculum and content in line with the learners needs, abilities, and capabilities [15]. Other approaches give learners a more pleasant and involving or experiential learning experience, therefore improving the learners’ uptake and retention of information, the foundation of learning [15], [17]. From another perspective, AI in education has also eliminated some barriers to access to learning opportunities, such as national and international borders, enabling global access to learning through online and web-based platforms [13], [15].

IV. DISCUSSION OF THE RESULTS

From the different articles and studies reviewed, it is evident that with technological innovations and advancements, computersandcomputerrelatedtechnologies,andotherinnovations have encouraged the development of artificial intelligence, which has permeated different sectors of the society, and will potentially have a major impact on different industries in which it is used. One of these areas in which AI has been applied, and is resulting in a major impact, is the education sector. As a foundation, and basis for understanding how AI has impacted education, a definition and description of AI was deemed essential. Different tenets and characteristics and nature of AI were gleaned from the different definitions derived from the studies evaluated. A key characteristic and tenet of AI, as the name intimates, is having some level of intelligence, a characteristic that has only been the preserve of human beings until the onset of AI [4], [5], [7], [11], [16], [24], [35]. Intelligence gives the AI, computers and by extension, embedded systems, such as robots and facilities, with human like abilities, including cognition, learning, adaptability, and decision-making functions [6], [13], [16], [19], [22]. The innovations and developments, culminating in the development and use of AI, have accorded the education sector, more particularly, academic institutions, with an opportunity to leverage and use of AI.

Indeed, as adduced from the different sources reviewed and analyzed, the uptake and use of AI in education has taken various forms. AI in education was initially in the form of computers and computer related technologies, used to perform a wide range of administrative tasks, instruction, and to foster learning among students, scope areas determined from the description of AI application in technology [11], [15], [19]. Continuous developments and innovations, particularly, with the transitioning of AI from computers only, to include embedded systems, as well as online and web-based platforms, harbingered the development and use of AI in web-based platforms and online platforms, and robotics, evidenced by the development and use of humanoid robots (Robots and chatbots), which perform, independently or working with human instructors, educators’ duties, including dissemination of learning materials to learners at various levels of education. In addition, from the analysis, and the descriptions of the platforms provided in the different evaluated articles, it is apparent AI application, in education, in its different forms, has accorded learners a richer and more rewarding learning experience [19], [22], [25], [31], [34], [35].

V. CONCLUSION

The objective or the purpose of this study was to assess the impact of AI on education. A qualitative research study, leveraging literature review as a research design and method was used. Journal articles, professional publications, and professional conference reports were identified and used in an analysis that facilitated the realization of the study purpose. The development and use of computers and computer related technologies harbingered research and innovations that have led to the development and use of AI in different sectors. Particularly, the development of the personal computers, and later developments that have increasing the processing and computing capabilities, as well as the ability to integrate or embed computer technologies in different machines, equipment, and platforms, have encouraged the development and use of AI, which has been shown to have a major impact on the sectors it permeates. AI has been extensively adopted and used in the education sector, particularly, in education institutions, which were the focus of this study. The analysis focused on evaluating the impact of AI on administrative, instruction, and learning aspect of education, with a focus on assessing how AI has been applied and the effects it has had.

AI in education initially took the form of computers and computer-related systems, and later, the form of web-based and online education platform. Embedded systems have made it possible to use robots, in the form of robots or humanoid robots as teacher colleagues or independent instructors, as well as chatbots to perform teacher or instructor-like functions. The use of these platforms and tools have enabled or improved teacher effectiveness and efficiency, resulting in richer or improved instructional quality. Similarly, AI has provided students with improved learning experiences because AI has enabled the customization and personalization of learning materials to the needs and capabilities of students. Overall, AI has had a major impact on education, particularly, on administration, instruction, and learning areas of the education sector or within the context of individual learning institutions.

REFERENCES

• Flamm, Creating the Computer: Government, Industry, and High Technology. Washington, DC, USA: Brookings Institution Press, 1988.
• Campbell-Kelly, Computer, Student Economy Edition: A History of the Information Machine. Evanston, IL, USA: Routledge, 2018.
• M. L. Cairns ‘‘Computers in education: The impact on schools and classrooms,’’ in Life Schools Classrooms. Singapore: Springer, 2017, pp. 603–617.
• Coppin, Artificial Intelligence Illuminated. Boston, MA, USA: Jones and Bartlett, 2004.
• Whitby, Artificial Intelligence: A Beginner’s Guide. Oxford, U.K.: Oneworld, 2008.
• Devedžic, ‘‘Web intelligence and artificial intelligence in education,’’ Educ. Technol. Soc., vol. 7, no. 4, pp. 29–39, 2004.
• J. Timms, ‘‘Letting artificial intelligence in education out of the box: EducationalRobotsandsmartclassrooms,’’Int.J.Artif.Intell.Edu.,vol.26, no. 2, pp. 701–712, Jan. 2016.
• Snyder, ‘‘Literature review as a research methodology: An overview and guidelines,’’ J. Bus. Res., vol. 104, pp. 333–339, Nov. 2019.
• Fang, P. Chen, G. Cai, F. C. M. Lau, S. C. Liew, and G. Han, ‘‘Outagelimit-approaching channel coding for future wireless communications: Root-protograph low-density parity-check codes,’’ IEEE Veh. Technol. Mag., vol. 14, no. 2, pp. 85–93, Jun. 2019.
• Vaismoradi, H. Turunen, and T. Bondas, ‘‘Content analysis and thematic analysis: Implications for conducting a qualitative descriptive study,’’ Nursing Health Sci., vol. 15, no. 3, pp. 398–405, Mar. 2013.
• Chassignol, A. Khoroshavin, A. Klimova, and A. Bilyatdinova, ‘‘Artificial intelligence trends in education: A narrative overview,’’ Procedia Comput. Sci., vol. 136, pp. 16–24, Jan. 2018.
• Rus, S. D’Mello, X. Hu, and A. Graesser, ‘‘Recent advances in conversational intelligent tutoring systems,’’ AI Mag., vol. 34, no. 3, pp. 42–54, Sep. 2013.
• C. Sharma, P. Kawachi, and A Bozkurt, ‘‘The landscape of artificial intelligence in open, online and distance education: Promises and concerns,’’ Asian J. Distance Educ., vol. 14, no. 2, pp. 1–2, 2019.
• Pokrivcakova, ‘‘Preparing teachers for the application of AI-powered technologies in foreign language education,’’ J. Lang. Cultural Edu., vol. 7, no. 3, pp. 135–153, Dec. 2019.
• A. Mikropoulos and A. Natsis, ‘‘Educational virtual environments: A ten-year review of empirical research (1999–2009),’’ Comput. Edu., vol. 56, no. 3, pp. 769–780, Apr. 2011.

RAKESH KUMAR received the B.C.A degree from Panjab University and pursing M.C.A degree from Chandigarh Group of colleges, India in 2021 and 2023, respectively. His researches include art, design, education, and the advanced digital techniques.

HITESH PURI received the B.C.A degree from Panjab University and pursing M.C.A degree from Chandigarh Group of colleges, India in 2021 and 2023, respectively.

His primary research interests include artificial intelligence, wireless communication, and computer communions.

SHIVAM KUMAR received the B.C.A degree from Panjab University and pursing M.C.A degree from Chandigarh Group of colleges, India in 2021 and 2023, respectively. His current research interests include D2D communications, D2D caching.