The Impact of AI on Teaching and Learning in Higher Education Technology
人工智能对高等教育技术教学的影响

Thanks to AI, students may now study whenever and wherever they like. Personalized feedback on assignments, quizzes, and other assessments can be generated using AI algorithms and utilised as a teaching tool to help students succeed. This study examined the impact of artificial intelligence in higher education teaching and learning. This study focuses on the impact of new technologies on student learning and educational institutions. With the rapid adoption of new technologies in higher education, as well as recent technological advancements, it is possible to forecast the future of higher education in a world where artificial intelligence is ubiquitous. Administration, student support, teaching, and learning can all benefit from the use of these technologies; we identify some challenges that higher education institutions and students may face, and we consider potential research directions.
有了人工智能，学生现在可以随时随地学习。关于作业、测验和其他评估的个性化反馈可以利用人工智能算法生成，并作为教学工具帮助学生取得成功。本研究探讨了人工智能对高等教育教学的影响。本研究的重点是新技术对学生学习和教育机构的影响。随着新技术在高等教育中的快速应用以及最近的技术进步，我们可以预测在人工智能无处不在的世界中高等教育的未来。行政管理、学生支持、教学和学习都能从这些技术的使用中受益；我们指出了高等教育机构和学生可能面临的一些挑战，并考虑了潜在的研究方向。

Keywords: artificial intelligence, machine learning, higher education technology, teaching, learning analytics
关键词：人工智能、机器学习、高等教育技术、教学、学习分析

The future of higher education is inextricably linked to the development of new technologies and computing power of new intelligent machines. AI-based applications have become an integral part of our daily life, making it clear that technology is becoming increasingly important (Rodríguez-Hernández et al., 2021). An increasing number of educational applications for artificial intelligence have emerged in the last few years. Due to advancements in artificial intelligence, there are new possibilities and challenges for teaching and learning in higher education that have the potential to fundamentally alter the governance and internal architecture of higher education institutions. The importance of artificial intelligence (AI) and adaptive learning technology systems (ALTS) in education cannot be overstated (Holmes et al., 2021a; Pardamean et al., 2022). Many people have misunderstood or are afraid of AI's power, which will require a fundamental shift in the definition of expertise and the nature of future technological advancements.
高等教育的未来与新技术的发展和新型智能机器的计算能力密不可分。基于人工智能的应用已成为我们日常生活中不可或缺的一部分，这表明技术正变得越来越重要（Rodríguez-Hernández et al.）最近几年，人工智能的教育应用越来越多。由于人工智能的进步，高等教育的教与学有了新的可能性和挑战，有可能从根本上改变高等教育机构的管理和内部架构。人工智能（AI）和自适应学习技术系统（ALTS）在教育领域的重要性怎么强调都不为过（Holmes 等人，2021a；Pardamean 等人，2022）。许多人误解或惧怕人工智能的力量，这需要从根本上转变专业知识的定义和未来技术进步的性质。

To address the question of what constitutes an "intelligent" system created by a human, Alan Turing put forth a solution in the 1950s (Gomede et al., 2018). 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
为了解决什么是人类创造的 "智能 "系统这一问题，阿兰-图灵在 20 世纪 50 年代提出了一个解决方案（Gomede et al.）如果听者无法分辨自己听到的是人类对话还是机器对话，那么我们就可以说，由于图灵的模仿游戏，我们拥有了一个智能系统，或者说人工智能。麦卡锡在 1956 年给出了人工智能最早、最有影响力的定义之一："（人工智能）研究的基础是这样一种猜想，即智能的每一个学习方面或任何其他特征原则上都可以这样进行
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.
他说（Popenici & Kerr, 2017; Seo et al.）计算系统参与人类（过程）的能力，如学习、适应、综合、自我修正和数据使用，以完成复杂的计算任务，可定义为人工智能。

Higher education's services are already being profoundly altered by the rapid advancement of artificial intelligence.
人工智能的飞速发展已经深刻地改变了高等教育的服务。

The term AI conjures up images of supercomputers, machines with enormous processing power and the ability to adapt to their environment through the use of sensors and other features (Cox, 2021; Popenici & Kerr, 2017). These features give supercomputers human-like cognition and functionality, which in turn enhances their human interactions. In films, artificial intelligence has been used in a variety of ways, including smart buildings, where it can control the temperature, air quality, and music in a space based on its occupants' moods. An increasing number of educational applications of the traditional definition of artificial intelligence as a supercomputer has expanded to include embedded computer systems. Examples include robots that can help students learn from the earliest stages of education, such as in early childhood education, by incorporating AI, computers, and other supporting equipment (Bates et al., 2020; Niemi & Liu, 2021). As Timms claims, children are taught routine tasks using cobots, including punctuation and pronunciation and adapting to the abilities of the students, with the help of robots working in tandem with teachers or cobots. As various studies have demonstrated, web-based and online education have evolved from simply providing materials online or on the web for students to download, study, and complete assignments in order to pass, to intelligent and adaptive web-based systems that learn from instructor and learner behaviour and adjust accordingly to enhance the learning experience. Artificial intelligence is being used in education to assist with administration, instruction, and learning. The scope of this study will be to analyse and understand artificial intelligence in education by focusing on these three areas (Muñoz-merino, 2011).
人工智能一词让人联想到超级计算机，这些机器拥有巨大的处理能力，并能通过使用传感器和其他功能来适应环境（Cox，2021；Popenici & Kerr，2017）。这些特性赋予了超级计算机类似人类的认知和功能，进而增强了它们与人类的互动。在电影中，人工智能的应用方式多种多样，包括智能楼宇，它可以根据居住者的情绪控制空间内的温度、空气质量和音乐。人工智能的传统定义是超级计算机，而现在越来越多的教育应用已扩展到嵌入式计算机系统。例如，机器人可以通过集成人工智能、计算机和其他辅助设备，帮助学生从教育的最初阶段（如幼儿教育）开始学习（Bates 等人，2020 年；Niemi & Liu，2021 年）。正如蒂姆斯所言，在与教师或机器人协同工作的机器人的帮助下，使用机器人教授儿童日常任务，包括标点符号和发音，并适应学生的能力。各种研究表明，网络教育和在线教育已经从简单地在网上或网络上提供材料，供学生下载、学习和完成作业以通过考试，发展到基于网络的智能自适应系统，该系统可从教师和学生的行为中学习，并做出相应调整，以增强学习体验。人工智能正被用于教育领域，以协助管理、教学和学习。本研究将围绕这三个领域，分析和理解人工智能在教育领域的应用（Muñoz-merino，2011）。

It is inevitable that education has been impacted in a variety of ways by the continued use or application of information technology. The scope of this study is to ascertain the extent to which various forms of AI have impacted or impacted various facets of education. In particular, the research will look at how AI has impacted the fields of education administration and management, as well as teaching and learning (S. Dadhich et al., 2021; Hiran et al., 2021; Ramasamy & Doshi, 2022). The study is expected to show that AI has improved the efficiency and effectiveness of administrative tasks in education, as well as the overall effectiveness of instruction and learning. This research will be useful to a wide range of people involved in education. Contributing to the growing body of knowledge, theories, and empirical findings on how artificial intelligence (AI) has impacted education will be a major accomplishment for this project's authors. Evidence-based practises in decision-making and leadership will be fostered in Institutions of higher education and the education sector for the benefit of academics, professionals, and policymakers (Hiran et al., 2014; Kakish & Pollacia, 2018). In addition, the findings will be used to enhance the findings of other studies and for government policy and actions to promote the use of information technology, particularly AI, in the educational sector. Additionally, educational institutions and government agencies can develop policies and strategies that promote AI's positive impact on education while mitigating its possible negative impact on education.
信息技术的持续使用或应用不可避免地对教育产生了各种影响。本研究的范围是确定各种形式的人工智能在多大程度上影响或冲击了教育的各个方面。特别是，本研究将探讨人工智能如何影响教育行政和管理以及教学领域（S. Dadhich 等人，2021 年；Hiran 等人，2021 年；Ramasamy & Doshi，2022 年）。这项研究有望表明，人工智能提高了教育行政工作的效率和效果，也提高了教学和学习的整体效果。这项研究将对广大教育工作者有所帮助。对于本项目的作者来说，为人工智能（AI）如何影响教育这一日益增长的知识、理论和实证研究成果做出贡献将是一项重大成就。以实证为基础的决策和领导力实践将在高等教育机构和教育部门得到推广，使学术界、专业人士和政策制定者受益（Hiran 等人，2014；Kakish & Pollacia，2018）。此外，研究结果还将用于加强其他研究结果，并用于政府政策和行动，以促进信息技术，尤其是人工智能在教育领域的应用。此外，教育机构和政府机构可以制定政策和战略，促进人工智能对教育的积极影响，同时减轻其对教育可能产生的负面影响。

Data analysis and prediction are all components of AI-assisted education. Intelligent education is also part of this category, as is innovative virtual learning. Listed in Table 1 are some of the most common uses of AI in education, as well as some of the most important technologies that support them. It's worth noting
数据分析和预测都是人工智能辅助教育的组成部分。智能教育和创新虚拟学习也属于这一范畴。表 1 列出了人工智能在教育领域最常见的一些用途，以及支持这些用途的一些最重要的技术。值得注意的是
that, as the demand for education rises, learning with the help of AI is becoming more and more important. Instructors and students benefit from timely and personalised instruction from intelligent education systems (Hiran, 2021b, 2021a). Multiple computing technologies, particularly those related to machine learning and the theory of cognitive learning, are used to improve the educational value and efficiency of these tools.
随着教育需求的增加，借助人工智能进行学习变得越来越重要。教师和学生都能从智能教育系统的及时和个性化教学中受益（Hiran，2021b，2021a）。多种计算技术，特别是与机器学习和认知学习理论相关的技术，被用来提高这些工具的教育价值和效率。

TABLE 1 表 1

AI AND EDUCATION 人工智能与教育

AI IN EDUCATION 人工智能在教育中的应用

Knowledge models, data mining, and Machine learning are used in an AI system to analyse, recommend, understand, and acquire new knowledge. Intelligent technologies and system model are the two main components of an AI education system that includes teaching content, data and an intelligent algorithm. Figure1 illustrates the importance of using a model to help build a data map, which establishes the structure and associational laws for educational information. The model serves as the brain of an AI system, which is powered by various technologies.
人工智能系统利用知识模型、数据挖掘和机器学习来分析、推荐、理解和获取新知识。智能技术和系统模型是人工智能教育系统的两个主要组成部分，其中包括教学内容、数据和智能算法。图1说明了使用模型帮助建立数据地图的重要性，数据地图建立了教育信息的结构和关联规律。模型是人工智能系统的大脑，由各种技术驱动。

Learning analytics, machine learning, and data mining are all educational technologies that share a lot of similarities. Educational data mining and learning analytics have spawned two distinct communities at this time (Peprah et al., 2020). They share goals and methods and can draw on a wide range of disciplines, along with data mining, machine learning, statistics-based, and data modelling, to achieve their goals.
学习分析、机器学习和数据挖掘都是教育技术，它们有很多相似之处。目前，教育数据挖掘和学习分析已经形成了两个不同的群体（Peprah et al.）它们有着共同的目标和方法，可以利用数据挖掘、机器学习、统计和数据建模等多种学科来实现目标。

Learning management systems (LMS) and results from large-scale testing are at the heart of the field of learning analytics. Small-scale cognition is where data mining comes from in the intelligent tutoring systems community (Kakish & Pollacia, 2018).
学习管理系统（LMS）和大规模测试结果是学习分析领域的核心。小规模认知是智能辅导系统界数据挖掘的源头（Kakish & Pollacia, 2018）。

"Training data" is a sampling data set that is used to parse and generate meaningful patterns and structured knowledge at the heart of machine learning. Consider the case of creating for students in the process of choosing courses and universities, too, are affected using machine learning. Student achievements, aspirations, preferences, and "match-making" preferences are used to identify the institutions where students can be most successful (Frempong & Hiran, 2014; Hiran & Henten, 2020; Lakhwani, Somwanshi, et al., 2020). Furthermore, teachers can use this technology to get a better sense of how their students are processing information. Students' cumulative records can be used by instructors to fine-tune their teaching methods, which may lead to a better understanding of the material by their students. Using machine learning and image recognition, it is possible to grade student projects and assignments more quickly and accurately than a human being can (Barua et al., 2020; Hiran, K. K., Jain, R. K., Lakhwani, K., & Doshi, 2021). In terms of machine learning, the subfield of deep learning is getting a lot of attention. Techniques like decision trees, inductive logic programming and clustering are among the most commonly used. With deep learning, we focus on creating increasingly meaningful representations from the learning of successive layers. Models known as neural networks are used to extract the layer features, which are organised into stacked layers (Kant Hiran et al., 2014; Yeboah et al., 2015).
"训练数据 "是一个采样数据集，用于解析和生成有意义的模式和结构化知识，是机器学习的核心。考虑到在选课过程中为学生创建的案例，大学也会受到机器学习的影响。学生的成绩、愿望、偏好和 "匹配 "偏好被用来确定学生最能取得成功的院校（Frempong & Hiran, 2014; Hiran & Henten, 2020; Lakhwani, Somwanshi, et al.）此外，教师可以利用这项技术更好地了解学生处理信息的情况。教师可以利用学生的累积记录来调整教学方法，从而使学生更好地理解教材。利用机器学习和图像识别，可以比人类更快、更准确地对学生的项目和作业进行评分（Barua 等人，2020；Hiran, K. K., Jain, R. K., Lakhwani, K., & Doshi, 2021）。在机器学习方面，深度学习子领域受到广泛关注。决策树、归纳逻辑编程和聚类等技术是最常用的技术。在深度学习中，我们的重点是通过对连续层的学习来创建越来越有意义的表征。被称为神经网络的模型用于提取层特征，这些特征被组织成堆叠层（Kant Hiran 等人，2014 年；Yeboah 等人，2015 年）。

For learning analytics, students' characteristics and knowledge objects are analysed using learner models and knowledge fields models. New technology, such as machine learning, is introduced to a nontechnical world like education through the concept of learning analytics (M. Dadhich, Hiran, et al., 2021; Patel et al., 2021). For example, if a student is at risk, a teacher may intervene or provide feedback and instructional content to help them improve. Machine learning, data visualisation, learning sciences, and semantics all play a role in its development (M. Dadhich et al., 2022; Nankani et al., 2022). Competency learning powered by AI can, for example, help institutions anticipate the skills their students will need in the future. This data allows them to take proactive measures to ensure their students are prepared. Learning analytics make use of AI's capacity to learn in a variety of ways in addition to competency-based education (Hiran et al., 2021; Khazanchi et al., 2021). Those who are on the verge of failing can be categorised using various parameters, informing the institutions with early warning systems and advanced analytics. With a broader focus on interpersonal skills, arts, and literature, learning analytics will have to take on new levels of difficulty when it comes to assessing learners' abilities and progress. When it comes to implementing learning analytics, it can be difficult to find solutions that are both specific to a single learning environment and universally applicable to many different settings (Hiran et al., 2018; Lakhwani, Bhargava, Somwanshi, et al., 2020; Saini et al., 2021). Students, instructors, administrators, and institutions will all benefit from the use of advanced learning analytics techniques in the future.
在学习分析中，使用学习者模型和知识领域模型对学生的特征和知识对象进行分析。通过学习分析的概念，机器学习等新技术被引入到教育这样一个非技术领域（M. Dadhich、Hiran 等人，2021 年；Patel 等人，2021 年）。例如，如果一名学生处于危险之中，教师可以进行干预或提供反馈和教学内容，帮助他们提高学习成绩。机器学习、数据可视化、学习科学和语义学都在其发展过程中发挥着作用（M. Dadhich 等人，2022；Nankani 等人，2022）。例如，由人工智能驱动的能力学习可以帮助院校预测学生未来需要的技能。通过这些数据，院校可以采取积极措施，确保学生做好准备。除了基于能力的教育之外，学习分析还利用了人工智能的多种学习能力（Hiran 等人，2021 年；Khazanchi 等人，2021 年）。可以利用各种参数对濒临失败的学生进行分类，并通过预警系统和高级分析技术向教育机构提供信息。随着对人际交往技能、艺术和文学的更广泛关注，学习分析在评估学习者的能力和进步方面将面临新的困难。在实施学习分析时，很难找到既能针对单一学习环境，又能普遍适用于多种不同环境的解决方案（Hiran 等人，2018；Lakhwani、Bhargava、Somwanshi 等人，2020；Saini 等人，2021）。未来，学生、教师、管理者和机构都将受益于先进学习分析技术的使用。

The goal of educational data mining is to provide learners with automated and systematic responses. Learning data mining using AI aims to build in-built rules of association, and to provide students with knowledge objects that meet their individual needs (Lakhwani, Bhargava, Hiran, et al., 2020; Mehul Mahrishi et al., 2020; Tyagi et al., 2020). A small sample of written assignments was chosen for analysis, for example, students' demographic characteristics and grades can be analysed. It is also possible to predict a student's academic progress using a machine learning regression method. Thus, data mining is becoming a powerful tool for improving learning and knowledge mastery, leading to a better understanding of educational settings and students (Allayarova, 2019; Bakhromovich, 2020). A combination of pattern discovery and predictive modelling can be used to extract hidden knowledge that educators can use to make changes to curriculum development (Acheampong et al., 2018; Priyadarshi et al., 2021). This is how it is
教育数据挖掘的目标是为学习者提供自动化和系统化的回应。利用人工智能进行学习数据挖掘的目的是建立内置的关联规则，为学生提供满足其个性化需求的知识对象（Lakhwani, Bhargava, Hiran, et al., 2020; Mehul Mahrishi et al., 2020; Tyagi et al., 2020）。选择少量书面作业样本进行分析，例如，可以分析学生的人口统计特征和成绩。还可以利用机器学习回归法预测学生的学业进展。因此，数据挖掘正成为改善学习和掌握知识的有力工具，从而更好地了解教育环境和学生（Allayarova，2019；Bakhromovich，2020）。模式发现和预测建模相结合，可用于提取隐藏的知识，教育工作者可利用这些知识对课程开发做出改变（Acheampong 等人，2018；Priyadarshi 等人，2021）。这就是
defined. For students to be able to learn at their own pace and choose their own method of study, data mining AI can be used to mine the knowledge field data and produce personalised learning experiences. For students to be able to learn at their own pace and choose their own method of study, data mining AI can be used to mine the knowledge field data and produce personalised learning experiences. This is an important application. Instructors should be able to tailor their courses and methods to the interests of their students when using personalised learning. Machine learning, for example, can be improved with data mining to produce more accurate and reliable results (Holmes et al., 2021a).
定义。为了让学生能够按照自己的节奏学习，选择适合自己的学习方法，可以利用人工智能数据挖掘技术挖掘知识领域的数据，生成个性化的学习体验。为了让学生能够按照自己的节奏学习并选择适合自己的学习方法，可以利用人工智能数据挖掘来挖掘知识领域的数据，并生成个性化的学习体验。这是一项重要的应用。在使用个性化学习时，教师应该能够根据学生的兴趣定制课程和方法。例如，机器学习可以通过数据挖掘得到改进，从而产生更准确、更可靠的结果（Holmes 等人，2021a）。

AI has the potential to change many aspects of society, including the education sector, according to Timms. From the numerous studies conducted, it's clear that artificial intelligence is already being used in the education sector, where it has led to advancements in a wide range of areas (Pardamean et al., 2022; Rodríguez-Hernández et al., 2021).
蒂姆斯认为，人工智能有可能改变社会的许多方面，包括教育领域。从大量研究中可以看出，人工智能已被应用于教育领域，并在多个领域取得了进步（Pardamean 等人，2022 年；Rodríguez-Hernández 等人，2021 年）。

TABLE 2 表 2

THE POTENTIAL OF ARTIFICIAL INTELLIGENCE (AI) IN EDUCATION
人工智能（AI）在教育领域的潜力

To sum up, the study's goal is to determine the impact of AI on education. AI has been used in education in a variety of ways, but the evaluation of these methods only partially answers the research question at hand. According to Sharma et al., the application of AI in education has the potential to transform a variety of facets of the educational process (Gomede et al., 2018; Niemi & Liu, 2021). An examination of AI's various applications reveals some of the ways in which AI will affect education. Based on the findings from the articles analysed, this section takes a closer look at how AI affects administering, educating, and (educating oneself) learning (Bakhromovich, 2020; Chassignol et al., 2018).
总之，本研究的目标是确定人工智能对教育的影响。人工智能在教育领域的应用方式多种多样，但对这些方法的评估只能部分回答手头的研究问题。Sharma 等人认为，人工智能在教育中的应用有可能改变教育过程的方方面面（Gomede 等人，2018；Niemi & Liu，2021）。对人工智能各种应用的研究揭示了人工智能影响教育的一些方式。根据所分析文章的结论，本节将进一步探讨人工智能如何影响管理、教育和（自我教育）学习（Bakhromovich，2020；Chassignol 等人，2018）。

The efficiency of educational administration and management has been greatly improved as a result of the application of artificial intelligence in the field of education. It has made administrative tasks like
人工智能在教育领域的应用大大提高了教育行政和管理的效率。它使诸如
grading and providing feedback to students much easier for educators. AIWBE's programmes have added features that teachers can grade students' work and provide feedback more easily with these tools (Bates et al., 2020; Porayska-Pomsta, 2016; Timonen & Ruokamo, 2021). Knewton, for example, has built-in functionalities that allow instructors to ensure that students' progress is monitored by assessing their performance, assigning grades, and giving them feedback. The use of AI has made administrative tasks easier and more effective for teachers and instructors, allowing them to better instruct and guide students. In addition to grading and providing feedback, instructors can use intelligent tutoring systems for a wide range of administrative duties (Muñoz-merino, 2011; Timonen & Ruokamo, 2021). Programs with AI like PaperRater and Grammarly allow instructors options, including plagiarism checking, grading and providing feedback to students on their weaknesses. As a result of AI, instructors have been able to devote more time to their primary responsibilities, such as teaching and disseminating materials and content in accordance with the institution's or the country's curriculum. There was evidence that administrative processes and tasks had improved in quality, as well as the effectiveness and efficiency of instructors or educators in the performance of various administrative tasks despite this topic not being the primary focus of many articles evaluated (L. Chen et al., 2020).
对于教育工作者来说，为学生评分和提供反馈更加容易。全英文教学法的程序增加了一些功能，教师可以利用这些工具更轻松地对学生的作业进行评分和提供反馈（Bates et al.，2020；Porayska-Pomsta，2016；Timonen & Ruokamo，2021）。例如，Knewton 的内置功能可让教师通过评估学生的表现、给学生打分和提供反馈，确保学生的学习进度得到监控。人工智能的使用使教师和讲师的管理任务变得更简单、更有效，使他们能够更好地指导和引导学生。除了评分和提供反馈外，教师还可以利用智能辅导系统来完成各种管理任务（Muñoz-merino，2011；Timonen & Ruokamo，2021）。像 PaperRater 和 Grammarly 这样的人工智能程序允许教师进行选择，包括剽窃检查、评分和针对学生的弱点提供反馈。有了人工智能，教师可以将更多的时间投入到他们的主要职责中，如根据学校或国家的课程设置教授和传播教材和内容。有证据表明，行政程序和任务的质量有所提高，教员或教育工作者执行各种行政任务的效果和效率也有所提高，尽管这一主题在许多评估文章中并不是主要重点（L. Chen 等人，2020 年）。

The use of artificial intelligence (AI) in education was also examined in this study. A summary of a number of articles revealed that instructors are quickly adopting and utilising artificial intelligence (AI) in various forms as an instructional aid or pedagogical tool. Artificial Intelligence has had a significant impact on this field when used for educational purposes or as a teaching too (Cheng et al., 2020; Steinbauer et al., 2021)I. Various publications reviewed and analysed show that the quality, instructors' productivity, effectiveness, and efficiency have all gone up (Chatterjee & Bhattacharjee, 2020; X. Chen, 2020). Efficiencies and quality are assessed by how well students or learners are able to absorb, retain, or demonstrate what they've learned, while effectiveness is evaluated by how well students or learners demonstrate what they've learned. Because of these operational definitions and descriptions of effectiveness, quality, and efficiency in instruction, the study's findings show that AI has aided in their realisation. Instructions have become more effective thanks to AI (M. Dadhich, Doshi, et al., 2021). According to Rus et al, ITS uses evidence-based or empirical evidence-backed practises, such as the extensive use of cognition and learning models, to achieve optimal learning for students. In fact, programmes like DeepTutor and AutoTutor put the learner at the centre of the process, allowing for the creation of content that is tailored to the individual's specific abilities and interests (Fernández-Martínez et al., 2021; Kandlhofer & Steinbauer, 2021; Popenici & Kerr, 2017). Artificial Intelligence (AI) has improved instructional quality and effectiveness, as Pokrivcakova argues, because modern systems are technologybased adaptive systems, the materials or content presented are determined by the learners' needs, which ensures an optimal learning experience. When it comes to platforms for web-based and online education and the application of AI ensures that course content is better disseminated. In fact, according to Mikropoulos and Natsis, the development and use of AI, particularly in web-based and online education, has led to improvements in instruction because improved educational resources for these platforms have been made possible by AI (Estevez et al., 2019; Holmes et al., 2021b; W. H. Kim & Kim, 2020). Other studies have noted the same advantages or enhancements to learning. Computer-Based Training (CBT), Computer-Aided Learning (CAL), and Individualized Student Training (ITS) all take a generalised put it all on the web approach, which may not address the student's learning needs in the same way as ITS. To improve the quality of education, tutoring and instructional systems have been developed to address the various challenges that face one-on-one teacher/student tutoring, as summarised by Roll and Wylie in their discussion of AI (Cox, 2021; Dogmus et al., 2015; Renz & Hilbig, 2020), particularly in education. An additional important theme that emerged from the research was how AI has impacted the quality of instructors' work. According to a few researches on the topic, academic integrity can be improved through the use of plagiarism checkers, proctoring, or monitoring of students' activities via online platforms like Grammarly, TurnItIn or White Smoke (J. Kim et al., 2022). It's been shown in other studies that teamviewer applications, simulation, and gamification have significant benefits to instructional quality,
本研究还探讨了人工智能（AI）在教育中的应用。对一些文章的总结显示，教师正在迅速采用和利用各种形式的人工智能（AI）作为教学辅助工具或教学工具。人工智能在用于教育目的或作为教学手段时，对这一领域产生了重大影响（Cheng 等人，2020 年；Steinbauer 等人，2021 年）I。经审查和分析的各种出版物表明，教学质量、教师的生产力、有效性和效率都有所提高（Chatterjee & Bhattacharjee, 2020; X. Chen, 2020）。效率和质量是通过学生或学习者吸收、保留或展示所学知识的能力来评估的，而有效性则是通过学生或学习者展示所学知识的能力来评估的。由于对教学效果、质量和效率有了这些可操作的定义和描述，研究结果表明，人工智能有助于实现这些定义和描述。得益于人工智能，教学变得更加有效（M. Dadhich、Doshi 等人，2021 年）。根据 Rus 等人的观点，ITS 采用基于证据或经验证据支持的做法，如广泛使用认知和学习模型，以实现学生的最佳学习效果。事实上，DeepTutor 和 AutoTutor 等程序将学习者置于学习过程的中心，允许根据个人的具体能力和兴趣创建内容（Fernández-Martínez 等人，2021 年；Kandlhofer & Steinbauer，2021 年；Popenici & Kerr，2017 年）。人工智能（AI）提高了教学质量和效果，正如 Pokrivcakova 所说，因为现代系统是基于技术的自适应系统，所呈现的材料或内容由学习者的需求决定，这确保了最佳的学习体验。说到基于网络和在线教育的平台，人工智能的应用可以确保课程内容得到更好的传播。事实上，根据 Mikropoulos 和 Natsis 的说法，人工智能的发展和使用，尤其是在网络教育和在线教育中的发展和使用，已经带来了教学的改进，因为人工智能使这些平台的教育资源得到了改善（Estevez 等人，2019；Holmes 等人，2021b；W. H. Kim & Kim，2020）。其他研究也指出了同样的优势或对学习的促进作用。基于计算机的培训（CBT）、计算机辅助学习（CAL）和个性化学生培训（ITS）都采用了一种将所有内容都放在网络上的通用方法，这种方法可能无法像ITS那样满足学生的学习需求。 为了提高教育质量，人们开发了辅导和教学系统，以应对教师/学生一对一辅导所面临的各种挑战，Roll 和 Wylie 在讨论人工智能时对此进行了总结（Cox，2021 年；Dogmus 等人，2015 年；Renz & Hilbig，2020 年），尤其是在教育领域。研究中出现的另一个重要主题是人工智能如何影响教师的工作质量。根据一些相关研究，通过使用抄袭检查器、监考或通过在线平台（如 Grammarly、TurnItIn 或 White Smoke）监控学生的活动，可以提高学术诚信度（J. Kim 等人，2022 年）。其他研究表明，团队浏览器应用、模拟和游戏化对提高教学质量大有裨益、
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).
此外，机器人还与虚拟现实和三维技术密切相关，甚至可以通过使用人工智能技术来提高性能和效率。另一项研究探讨了能够说话和交谈的仿人机器人如何通过提高学生的参与度来提高教学质量，因为机器人的外形与人类相似，而且功能也得到了增强（Seo 等人，2021 年）。

AI has had a significant impact on students' educational experiences, which are included in this study's scope of work. As Rus et al. summarised the impact of AI on learning, they found that ITS fosters deep learning by probing and prodding students until they are able to adequately explain their position and the rationale behind it, thus enhancing the comprehension and retention of the information they are providing (J. Kim et al., 2022; Tedre et al., 2021; Zawacki-Richter et al., 2019a). ITS is an integral component of the system. This and other studies illustrate the numerous advantages that AI can provide to students' educational experiences in various ways. It is possible to track a student's progress in terms of knowledge and understanding thanks to artificial intelligence (AI). In order to better meet the needs of individual students, the system makes use of this data. When it comes to learning, Pokrivcakova noted that adaptive content and intelligent learning systems such as virtual reality have been made possible by AI, and this has been shown to have a positive effect on student achievement. When it comes to learning, Mikropoulos and Natsis point out that modelling and related tools and methods give students the hands-on experience and experiential learning they need, which enhances the quality of their education. The research they cited in their article also points out how VR and 3-D technology can enhance education by enhancing usability and student enjoyment (Celik et al., 2022; S. Raj, 2019). Other studies focusing on web-based platforms highlight the benefits of AI and its impact on learning quality. AI web based components such as Class monitoring, adaptive hypermedia, collaborative learning, and information filtering encourage students to collaborate and interact with each other and to learn, as Kahraman points out. According to Peredo et al, a web-based platform has the same advantages as a brick-and-mortar classroom because it adapts and tailors' instruction to the needs of the learner (Khare et al., 2018; Verdú et al., 2008; Zakirova & Zunnunova, 2020). As an example, the StudentTracker middleware utilises learner-specific data found online, such as completed activities, learning tracker tracking time, and other components, to adapt the AI web based pedagogical approach to learning. Web-based platforms and proven benefits to learning include promoting global access to education and affordability. Overall, these platforms have provided a more enjoyable educational experience (Chaudhry & Kazim, 2021). A number of other studies have demonstrated the benefits and ramifications of artificial intelligence (AI) in the classroom. Academic integrity and honesty have been promoted through the use of TurnItIn tools like revision helper and Pearson's Write-to-Learn tools, as well as other revision and writing assistants like AI. Other studies, on the other hand, have raised concerns about AI's potential negative impact on learning. Because of the ease with which sites that generate a lot of paper and paper mills and can be used by students, Crowe et al. found that AI may promote dishonesty and jeopardise academic integrity. The advantages of AI in education outweigh the disadvantages, as evidenced by a number of other studies (Chaudhry & Kazim, 2021; Khan et al., 2022).
人工智能对学生的教育体验产生了重大影响，这也是本研究的工作范围。正如 Rus 等人在总结人工智能对学习的影响时发现，智能学习系统通过探究和催促学生，直到他们能够充分解释自己的立场及其背后的理由，从而加强对所提供信息的理解和保留，从而促进学生的深度学习（J. Kim 等人，2022；Tedre 等人，2021；Zawacki-Richter 等人，2019a）。ITS 是该系统不可或缺的组成部分。这项研究和其他研究表明，人工智能能以各种方式为学生的教育体验带来诸多优势。借助人工智能（AI），可以跟踪学生在知识和理解方面的进步。为了更好地满足每个学生的需求，系统会利用这些数据。在学习方面，波克里夫卡科娃指出，人工智能使自适应内容和虚拟现实等智能学习系统成为可能，这已被证明对学生的成绩有积极影响。谈到学习，Mikropoulos 和 Natsis 指出，建模及相关工具和方法为学生提供了所需的实践经验和体验式学习，从而提高了教育质量。他们在文章中引用的研究还指出了 VR 和 3-D 技术如何通过提高可用性和学生的乐趣来加强教育（Celik 等人，2022 年；S. Raj，2019 年）。其他以网络平台为重点的研究强调了人工智能的优势及其对学习质量的影响。正如Kahraman指出的那样，基于人工智能的网络组件，如班级监控、自适应超媒体、协作学习和信息过滤，鼓励学生相互协作、互动和学习。佩雷多等人认为，基于网络的平台具有与实体教室相同的优势，因为它能根据学习者的需求调整和定制教学（Khare 等人，2018；Verdú 等人，2008；Zakirova & Zunnunova，2020）。例如，StudentTracker 中间件利用网上找到的学习者特定数据，如已完成的活动、学习跟踪器跟踪时间和其他组件，来调整基于人工智能的网络教学方法。基于网络的平台已被证明对学习有益，包括促进全球受教育的机会和可负担性。总体而言，这些平台提供了更愉快的教育体验（Chaudhry & Kazim，2021 年）。其他一些研究也证明了人工智能（AI）在课堂教学中的益处和影响。 通过使用TurnItIn工具（如复习助手和培生的Write-to-Learn工具）以及其他复习和写作助手（如人工智能），学术诚信和诚实得到了提升。另一方面，其他研究则对人工智能对学习的潜在负面影响表示担忧。Crowe 等人发现，人工智能可能会助长不诚实行为，危害学术诚信。其他一些研究（Chaudhry & Kazim, 2021; Khan et al.）

Seeing how artificial intelligence affects both the instructor and student in the classroom as systems with intelligence will be interesting to watch. There is a growing need for AI systems to help teachers deal with the increased workload. Course material and syllabus can be analysed by AI systems to help instructors create personalised content. After analysing, it is also possible to use these systems to create and grade exams (Hwang et al., 2020; Upala & Wong, 2019). Teachers would be able to focus on more pressing issues, such as raising student achievement, if this were to occur. When it comes to individualised instruction and self-directed learning, artificial intelligence (AI) solutions can help instructors better analyse the data they collect from their students. AI bias in education is also becoming an issue because of human bias. To eliminate unfairness, an AI solution can assign grades based on predefined rubrics and benchmarks. Handwritten papers can be read and recognised by AI systems based on computer vision (Aguirre et al., 2021; Kakish & Pollacia, 2018). Additionally, these systems prevent students from cheating and
人工智能作为具有智能的系统，将如何影响课堂上的教师和学生，这将是一个有趣的观察点。现在越来越需要人工智能系统来帮助教师应对增加的工作量。人工智能系统可以分析课程材料和教学大纲，帮助教师创建个性化内容。在分析之后，还可以利用这些系统来创建和评分考试（Hwang 等人，2020 年；Upala & Wong，2019 年）。如果能做到这一点，教师就能专注于更紧迫的问题，如提高学生成绩。在个性化教学和自主学习方面，人工智能（AI）解决方案可以帮助教师更好地分析从学生那里收集到的数据。由于人类的偏见，教育中的人工智能偏差也正在成为一个问题。为了消除不公平现象，人工智能解决方案可以根据预定义的评分标准和基准来评定成绩。基于计算机视觉的人工智能系统可以阅读和识别手写论文（Aguirre 等人，2021 年；Kakish & Pollacia，2018 年）。此外，这些系统还能防止学生作弊和
plagiarising, reducing bias. By analysing student data, AI systems have been able to identify students' learning deficiencies and intervene at an early stage. The majority of students in the traditional educational system are treated in a similar manner. Thus, it is impossible to teach all students using the same method. Based on a student's personality, strengths, and complementary skills, Using AI, teachers could better tailor their instruction to the needs of their individual students (Sruthi & Mukherjee, 2020; Wakelam et al., 2020). As a result, all students will be able to improve their performance and have fun while doing so in this manner. As an outcome, students' ability to learn, develop good study habits, and express their own ideas grows while increasing their knowledge. AI systems are also able to analysis of the student's study habits, which in turn allows universities to tailor their course offerings for each student's specific needs. Individual ability and career path can be taken into account to help students achieve better grades and gain relevant skills. In light of the information presented above, artificial intelligence (AI) holds great promise for streamlining and automating administrative processes at educational institutions and in the classroom. By automating homework and essay evaluation, instructors can spend more time one-on-one time with students (Hatzilygeroudis et al., 2005; Kelly & Tangney, 2006; Nuria, Pedro, 2021). Exams and papers are being graded in new ways as well that are being developed by AI developers. For learning materials, AI creates customizable digital interfaces that can be used by students of all ages and grade levels to learn. According to Brightspace's creator Nick Oddson, AI can help instructors gain insights from students on the basis of all the available learning tools. Based on a learner's struggles with class material, AI systems can help them improve their grades. When students needed help from their professors in the past, they had only a limited amount of time to do so, such as during office hours or by emailing them. Carnegie Learning, for example, is a smart tutoring system that makes use of student data to give personalised feedback and work closely with individual students. Eventually, AI will be able to assist both teachers and students in the classroom, adapting to a wide range of learning styles. To be more specific, it aids educators and students in a wide range of educational endeavours (Ahmad, 2020; Kalmuratov, 2020; Huang et al., 2021; Zawacki-Richter et al., 2019b).
抄袭，减少偏见。通过分析学生数据，人工智能系统能够发现学生的学习缺陷，并在早期阶段进行干预。在传统教育系统中，大多数学生都受到类似的对待。因此，不可能用同样的方法教所有学生。利用人工智能，教师可以根据学生的个性、优势和互补技能，更好地因材施教（Sruthi & Mukherjee, 2020; Wakelam et al.）因此，所有学生都能通过这种方式提高成绩，并从中获得乐趣。其结果是，学生的学习能力、良好的学习习惯和表达自己想法的能力都会在增长知识的同时得到提高。人工智能系统还能对学生的学习习惯进行分析，从而使大学能够根据每个学生的具体需求来定制课程。个人能力和职业发展方向可以纳入考虑范围，帮助学生取得更好的成绩，获得相关技能。鉴于上述信息，人工智能（AI）在简化教育机构和课堂的管理流程并使之自动化方面大有可为。通过自动化作业和论文评估，教师可以花更多时间与学生一对一地交流（Hatzilygeroudis et al.）人工智能开发人员正在开发新的考试和论文评分方式。在学习材料方面，人工智能创建了可定制的数字界面，供不同年龄和年级的学生学习使用。根据 Brightspace 的创建者尼克-奥德森（Nick Oddson）的说法，人工智能可以帮助教师在所有可用学习工具的基础上获得学生的见解。根据学习者在课堂材料方面的困难，人工智能系统可以帮助他们提高成绩。过去，当学生需要教授提供帮助时，他们只有有限的时间，比如在办公时间或通过电子邮件向教授求助。例如，卡内基学习系统（Carnegie Learning）就是一个智能辅导系统，它利用学生数据提供个性化反馈，并与个别学生密切合作。最终，人工智能将能在课堂上为教师和学生提供帮助，适应各种学习风格。更具体地说，它能帮助教育工作者和学生开展各种教育工作（Ahmad，2020；Kalmuratov，2020；Huang 等人，2021；Zawacki-Richter 等人，2019b）。

Artificial intelligence, which has spread throughout society and could have a significant impact on various industries, has been influenced by computer and computer-related technology advancements, along with other technological advances. For example, AI has had a profound effect on the field of education. A definition and description of artificial intelligence (AI) was deemed necessary in order to understand how AI has affected education. It was found that different definitions of AI yielded different tenets, characteristics, and the nature of AI. It was only recently that computers and computer-related technologies started being used in education to handle a wide range of administrative and instructional tasks, as well as to encourage student learning.
人工智能已在全社会普及，并可能对各行各业产生重大影响，它受到计算机和计算机相关技术进步以及其他技术进步的影响。例如，人工智能对教育领域产生了深远的影响。为了了解人工智能对教育的影响，有必要对人工智能（AI）进行定义和描述。研究发现，对人工智能的不同定义会产生不同的信条、特征和人工智能的性质。直到最近，计算机和计算机相关技术才开始用于教育领域，以处理广泛的行政和教学任务，并鼓励学生学习。

An early sign of AI's future development and application on web-based platforms and online platforms is the use of robots resembling humanoid forms, which can perform a variety of educational tasks either independently or in conjunction with humans. To add to that, it's clear that artificial intelligence (AI) applications in education - no matter what form they take - have given students a more engaging and rewarding educational experience.
人工智能未来在网络平台和在线平台上发展和应用的一个早期迹象就是使用类似人形的机器人，它们可以独立或与人类共同完成各种教育任务。除此之外，人工智能（AI）在教育领域的应用--无论采取何种形式--显然都给学生带来了更有吸引力、更有价值的教育体验。

As a result, AI has had a remarkable effect on teaching. As a result, artificial intelligence (AI) has had a remarkable effect on teaching., in general, and in particular, on the use of the technology at specific educational institutions. With the help of artificial intelligence (AI), teachers are able to complete administrative tasks, such as grading assignments and providing feedback to students, more quickly and effectively. The quality of instruction can be improved by utilising various forms of artificial intelligence such as cooperative robotic agents (CORA), and chatbots (Chat). A better and richer learning experience is possible for students thanks to AI's ability to assess their abilities and needs, and then develop and distribute personalised or customised content, which ensures greater uptake and retention and thus improves learning.
因此，人工智能对教学产生了显著的影响。因此，人工智能（AI）对教学产生了显著的影响。在人工智能（AI）的帮助下，教师能够更快、更有效地完成管理任务，如批改作业和向学生提供反馈。利用合作机器人代理（CORA）和聊天机器人（Chat）等各种形式的人工智能，可以提高教学质量。由于人工智能能够评估学生的能力和需求，然后开发和发布个性化或定制化的内容，从而确保学生能够更好地吸收和保留知识，进而提高学习效果，因此学生可以获得更好、更丰富的学习体验。

However, as the needs of students change, AI-enhanced education will play an increasingly important role in the classroom. To date, it only offers courses ranging in difficulty, and it hasn't yet reached the
然而，随着学生需求的变化，人工智能强化教育将在课堂上发挥越来越重要的作用。迄今为止，它只提供难度不等的课程，而且还没有达到
highest level of intelligence in intelligent education. A probability model and a knowledge map in AI education has been studied. More and more data will be generated by AI systems as they interact with the educational process on a more frequent basis, allowing for more accurate information recommendation. Teachers and students will benefit from high-quality content provided by AI systems, which will be quantified using learner analytics, machine learning, and data mining. At this point, users will be able to choose from a variety of methods to arrive at the correct answer to their query. By analysing students' learning styles, emotional states, and self-direction, the ideal AI system will help students develop their imaginative and creative capacities while also stimulating students' own initiative. Students' natural talents, knowledge deep understanding, level of academic achievement, and career development will all benefit from the increased use of artificial intelligence systems, which is expected to go beyond simply assisting students in grasping specific knowledge.
智能教育中的最高智能水平。研究了人工智能教育中的概率模型和知识图谱。随着人工智能系统与教育过程的互动越来越频繁，人工智能系统将产生越来越多的数据，从而实现更准确的信息推荐。教师和学生将从人工智能系统提供的高质量内容中受益，这些内容将通过学习者分析、机器学习和数据挖掘进行量化。在这一点上，用户将能够从多种方法中进行选择，以获得查询的正确答案。通过分析学生的学习风格、情绪状态和自主学习能力，理想的人工智能系统将帮助学生发展想象力和创造力，同时激发学生的主观能动性。学生的天赋、对知识的深刻理解、学业成绩水平和职业发展都将受益于人工智能系统的增加使用，而人工智能系统有望超越单纯帮助学生掌握特定知识的范畴。

The purpose of this research was to find out how AI will influence education. A qualitative research study based on a literature review was carried out. Magazine articles, Research paper publications, and conference proceedings from professional gatherings were all used in the study's analysis to help achieve its goals. Artificial Intelligence (AI) has been developed and used in a variety of industries thanks to advancements in the field of computer science and technology. With the advent of personal computers and subsequent developments that increased processing and computing power while also allowing for more seamless integration into other devices, platforms, and devices in their various stages of development, artificial intelligence (AI) has seen an uptick in its use across a wide range of industries. AI was already adopted and used in educational institutions, which is the focus of this research. AI's impact on education's administrative, instructional, and learning aspects was examined in depth in order to determine how and what effects it has had. AI education began with the use of computers and computer-related systems, then moved to online and web-based platforms. Now, thanks to embedded systems, teachers and instructors can collaborate with robots in the form of cobots or humanoid robots and chatbots can perform teacher or instructor-like functions. The use of these platforms and tools has improved or enabled the effectiveness and efficiency of teachers, resulting in better or richer educational content. Artificial intelligence (AI) has improved educational outcomes for students by allowing instructors to create lessons that are tailored to the needs and abilities of specific students. An overall impact of AI on education can be seen in administration, instruction and learning at educational institutions as well as in the education sector as a whole.
本研究的目的是了解人工智能将如何影响教育。我们在文献综述的基础上开展了一项定性研究。杂志文章、研究论文出版物和专业会议的会议记录都被用于研究分析，以帮助实现研究目标。得益于计算机科学与技术领域的进步，人工智能（AI）已在各行各业得到开发和应用。随着个人电脑的出现以及随后的发展，处理能力和计算能力不断提高，同时还能与其他处于不同发展阶段的设备、平台和装置进行更无缝的集成，人工智能（AI）在各行各业的应用也随之增加。人工智能已经被教育机构采用和使用，这也是本研究的重点。我们深入研究了人工智能对教育的管理、教学和学习方面的影响，以确定它是如何产生影响的以及产生了哪些影响。人工智能教育从使用计算机和计算机相关系统开始，然后转向在线和基于网络的平台。现在，由于有了嵌入式系统，教师和讲师可以与机器人（cobots 或仿人机器人）合作，聊天机器人也可以执行类似教师或讲师的功能。这些平台和工具的使用提高或实现了教师的有效性和效率，从而产生了更好或更丰富的教育内容。人工智能（AI）允许教师根据特定学生的需求和能力量身打造课程，从而改善了学生的教育成果。人工智能对教育的总体影响体现在教育机构以及整个教育部门的行政、教学和学习方面。

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