Artificial Intelligence! Nowadays, it is a phrase used  like a chewing gum for every occasion. It fits everywhere, as most consider it the solution to their worries. Above all, AI fills the knowledge gap people have, just with one question! Hence, AI platforms gain both supporters and opponents every day that passes. The massive influence that Artificial Intelligence impacts on? Education! Education has always been modifying its practices and teaching methods/ approaches, incorporating digital media into the conventional teaching practices. However, AI technology  has emerged as an innovation for drastic changes in the field of education. Yet, it has already incorporated contrasting conventional practices. Is it an ally or not?

Many result in the following question: what is AI actually? A well-educated Chabot. According to Cambridge dictionary, artificial intelligence is the use or study of computer systems or machines that have some of the qualities that the human brain has, such as the ability to interpret and produce language in a way that seems human, recognize or create images, solve problems, and learn from data supplied to them. To simplify it, AI is a computer program that aggregates users’ data. In sequence, this data is used to humanize chatbots as well as AI platforms such as ChatGPT, Magic AI , Free Image/voice  AI and many more. In general, AI platforms are famous among students  presented as a solution to their assignments, questions even they offer advice to them. However, the power of making AI an assistant lies on the educators. 

In the modern era, AI is an innovation which has brought about alterations in education. Currently, a broad range of AI technologies, from Intelligent Tutoring Systems (ITS) offering one to one tutoring to virtual teaching assistants, is being employed in education. In their review of AI research in education, Goksel & Bozkurt (2019) identified three primary themes that have garnered significant attention from researchers: adaptive learning, expert systems and ITS, and the future role of AI in educational processes. These themes also highlight the prevailing trends in AI development within the field of education. AI has already administered its assistance in writing, completing and correcting assignments. Yet the unique capability and  dynamic of the human brain is thinking.  Thinking capacity enables humans to be inventive as well as to seek solutions  even in the worst case scenarios in their life. Developing thinking capacity is one of the primary cores of education, coupled with enriching and acquiring knowledge. Moreover, thinking capacity is cultivated when people, in this case students, become creators using technology and AI in order to construct something or list solutions. Generally, constructionist activity has been addressed from early on as a social activity where typically students discuss and argue over working with a microworld (Hoyles and Sutherland 1989; Hoyles et al. 1992). Meaning generation is afforded by a conjunction of noticing computer feedback, using the representations and the semantics of the microworld and generating a language to express arguments in the context of this kind of activity. It has taken some time for the wider education research community to notice that constructionism was not perceived as an individualistic learning theory, and at the same time for constructionists to develop more explicit language and frameworks for the social discursive aspect of this kind of learning (Artigue 2009a, b; Kynigos and Theodossopoulou 2001). 

In case teachers are ever replaced by humanoid robots for education, the power would still be in the people's hands. People are those who educate robots to resemble them. Their primary goal is to ensure an effortless life, viewing AI as assistance, not as threat. Yet, AI technology can be perceived negatively, unless students are taught how to use AI platforms like ChatGPT responsibly, without becoming dependent on them for every answer and solution. This is the role of educators. Teachers can incorporate AI during lessons, serving as role models, demonstrating the way it can be used positively. They should encourage students to use AI and technology creatively, becoming constructionists under their guidance. Thus, students will learn to use technology as a tool for creating meaning in their projects, contributing to outcomes, or generating their own. Thus, students will learn to use technology as a tool for creating meaning in their projects, contributing to outcomes, or generating their own. In addition to traditional computer-based AI systems, innovative technologies such as humanoid robots, chat bots, and virtual reality systems are being integrated into the educational process (Chen, Chen & Lin, 2020; ThinkML Team, 2022; UNESCO, 2021). These technologies can enhance student engagement by providing interactive, personalized, and immersive learning environments (Malik, Tayal & Vij, 2019; Chen, Chen & Lin, 2020). Yet, it requires educators to acquire sufficient AI literacy skills with the aim to achieve that to students. Specifically, teachers need to allocate a certain amount of time in handling administrative tasks such as attendance checking, assignment and classroom monitoring, and paperwork. AI has eased such duties for educators. Compelling evidence is found in the article ‘The AI Revolution in Education: Will AI Replace or Assist Teachers in Higher Education?’ stressing that both educators and learners state their negative opinion concerning the replacement of humans by AI robots, enumerating the reasons, to a great extent. The primary one is their lack of socio-emotional skills despite their humanized behavior.

AI is a new innovation with both opportunities and challenges. On the one hand, it threatens to take charge of the educator’s duties. Yet, a proposed solution mentioned above is to train students to construct meaning through technology . It addresses this concern. On the other hand, AI is a highly equipped tool that contrasts outdated educational practices. To be honest, the practice of teaching nowadays has integrated digital media in the process, making the lessons more interactive and attention-grabbing to learners. For about twenty years the Intelligent Tutoring Systems paradigm has dominated the field of AI and Education. It formed the answer to the supposedly unintelligent Computer Based Learning systems which had prefixed teaching scenarios and no reasoning capacity at all. Additionally, ITS systems touched upon all main AI topics: knowledge representation, reasoning, explanation, machine learning, natural language, and planning. However, today it is time to consider new educational paradigms in which AI can play a part, albeit in a different form than in classical ITSs. New views on education and new technologies offer new challenges for AI. AI is known as a modeling science, developing, applying and investigating formalized models of salient aspects pertaining to learning and instruction, thereby giving the models in use a dynamic flavor. Broadly speaking, intelligent educational technology requires models of knowledge and models of processes to be used during the execution of instructional assignments. These models no longer need always to include a tutor role or detailed student model, but instead may often need to reflect several partner roles. Generally, with reference to the article ‘Where is Education Heading and How About AI?, the use of ITSs in education all these years serves some of the following trends in the educational process: more emphasis on open domains, taking into account the learning environment, collaboration as a didactic strategy and use of information databases. Namely, it has contributed in broadening students’ horizons in learning to a great extent. Computers in teaching have assisted learners to enrich their knowledge through promoting domain knowledge, interactive learning environment, collaborative learning as well as a plethora of sources. We have witnessed a shift in attention towards open domains (writing an essay about constructivism) and conceptual understanding (being able to reason about domain concepts and their relations). This development moves away from traditional ITS-research, with its regular emphasis being on tutoring relatively often-procedural tasks in relatively closed domains. Likewise the learners’ occupation with interactive learning materials transfers the responsibility for the learning process from the instructor to the learner. Exploratory learning studies, though, have cast some doubt on the capabilities of students to take on this responsibility (e.g. van Joolingen, 1993). 

Similarly, AI has developed new trends to be implemented in education as different scenarios: transmission, studio, and negotiation. Transmission refers mostly to the conventional way of teaching such as lectures, photocopies and testing. The use of computers is assistive in exercises. Hence, the use of AI reflects the production and transmission of universal, objective knowledge, and the diminishing of local, subjective, and personal knowledge. Facts are strictly segregated from opinions. The studio scenario focuses on the fact that responsibility for learning should reside more with the student. The more constructive efforts are undertaken by a student, the more they will learn. However, students often feel uncertain in this environment and seek more feedback and guidance. Tutors have to decide how much feedback and guidance is necessary for each student or each group of students. Concerning negotiation scenarios, there exists the belief that the goal of education is to acquire the flexibility to participate in the discourses of several communities of practice, that is, specific groups of professionals acting and communicating in specific ways. The learning goal, in terms of domain knowledge or skills to operate on domain knowledge, may even be lacking. The initial learning goal that forms the starting point for discussion and negotiation may itself become subject of the negotiation process.

Generally, the use of AI in education with regard to these emerging trends could be characterized as revolutionary related to the traditional paradigm in both teaching and learning. AI-techniques serve to model specific aspects (both static and dynamic) of human or agent reasoning and problem solving relevant for learning. Broadly speaking, intelligent educational technology requires models of knowledge and models of processes to be used during the execution of instructional assignments. These models no longer need always to include a tutor role or detailed student model, but instead may often need to reflect several partner roles. Hence, the article offers an analytical framework of the differences these AI educational trends present concerning the learning process. 

A conclusion to be drawn, AI in education is viewed mostly as a proponent to teachers rather than a threat in need of being addressed immediately. Most scholars support AI as a valuable contribution in teaching. They do, however, express concerns regarding full replacement. A proposed measure to eliminate  this ‘threat ’is to integrate digital technologies and AI to  constructionist activity for learning. Namely, AI seems to be the bridge, the  in-between contribution in education, against the traditional teaching practices.

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