The Rise of Artificial Intelligence (AI) In the Education Industry
Education Focus
Zeina AlbuainainAssociate,Corporate Commercial
Shouq Al MajaliTrainee Solicitor,Dispute Resolution
Artificial intelligence (AI) is steadily affecting and revolutionising every aspect of human endeavour. From how we live, work, do business, and play, AI is poised to be the ultimate game changer. The education industry is one of many industries impacted by AI’s transformative potential. Educators, students, and industry experts are receiving a paradigm shift regarding AI’s possibilities in this vital sector.
A new research report by Global Market Insights projects the value of AI in the education industry to reach $30 billion by 2032. This figure offers some perspective as to the size of AI’s impact in this sector. Set out below are some examples of which AI changes - and will continue to change - the education industry.
1. TutoringTeachers play a pivotal role in the education system and will always be needed. However, the advancement in AI will inevitably continue to have an impact on their roles. Intelligent systems can perform tasks such as evaluating assessments and providing personalised help to learners. Further, AI-powered chatbots can offer additional support to students outside the classroom setting. That is not to say however that AI should be seen as a replacement; rather, it can be a tool that simply optimises the learning experience. Teachers can gradually take on facilitative roles, bringing additional support to AI lessons and offering hands-on experience when needed. Combining the intelligence AI offers with the unique contributions of human educators can lead to a more effective and impactful learning environment.
2. Performance EvaluationAI systems can analyse and assess a wealth of information, providing valuable insights into students’ progress, strengths and areas for improvement. Through automating the performance evaluation process, AI could potentially minimise bias in this respect and ensure consistent standards across assessments.
Some of the most common features offered by AI-powered performance evaluations include:
Plagiarism Detection – This typical example has been an integral part of academic institutions for decades. Through the use of sophisticated algorithms, it helps ensure the authenticity and originality of students’ work. This analyses students’ written or typed responses, and can be used to evaluate written feedback and self-assessments to identify patterns related to performance.
Automated Grading - Machine learning systems can mimic and replicate a teacher’s grading style, eliminating human mistakes or biases.
3. Adaptive and Personalised Learning Students vary in their individual progression, which can sometimes hinder the teaching pace. AI offers a solution to this challenge, using adaptive learning models. These models allow students of different aptitude levels and/or unique learning needs to learn together. Teachers play a supervisory role and offer guidance when needed. Adaptive learning algorithms collect and analyse information on the student’s strengths, weaknesses, learning styles and pace, in order to tailor course content to the specific needs of the student. These algorithms enable students to engage in personalised learning paths, enabling them to have the best possible educational experience and learn more effectively.
4. Enhanced Student InteractionIt is not uncommon for AI systems to incorporate games, virtual reality, and simulations into the learning environment, offering an immersive experience which students may find stimulating. Such games would typically incorporate elements such as problem-solving, critical thinking and collaboration, whereas simulations would replicate real-life scenarios, enabling hands-on learning. Gamifying the learning process is generally considered as an efficient method for increasing student motivation and participation. These games and simulations would use algorithms to (among other things) adapt the difficulty level and content, based on the students’ skills and learning needs.
5. Administrative DutiesAI systems have the ability to streamline administrative processes, enhancing operational efficiency and freeing up valuable time and resources for educators. For example, AI technologies can assist school administrations in changing curricula, taking attendance, generating progress reports, and managing student records. AI chatbots can also handle routine inquiries and provide immediate support to students and parents, offering timely and accurate information.
Notwithstanding the aforementioned benefits of AI in education, the implementation of AI in the education industry presents challenges and complexities that should not be overlooked. The most notable among them include:
1. Privacy in AI-Enabled Edtech With the rapid advancement of AI systems and the widespread use of data, it is essential to understand their ramifications on our surrounding environment. Given that AI systems rely heavily on data to enable them to learn and make predictions, it is important to prioritise the ethical collection and usage of data. This includes ensuring that data is obtained through lawful and transparent means where personal data is involved (which is often the case, especially in the field of edtech). To ensure the responsible handling of data, other considerations such as data quality, accuracy and security will also need to be borne in mind.
2. AI-Driven Decision-MakingIn addition to the generality of the above-mentioned privacy concerns, there are strict regulations concerning automated individual-decision making (i.e., with no human involvement) under privacy laws. This would specifically be of relevance when making decisions on matters such as student evaluation, admission, or disciplinary actions. Depending on the applicable laws, students may have the right to transparent, explainable, and fair AI-based decisions that impact their educational journeys. Students may also have the right to object to AI-driven decisions under certain circumstances.
3. Inaccuracies and Biases Noting the large amounts of materials and content that can be generated through AI systems, it is important to ensure that this information is accurate and relevant. If the ‘training data’ is flawed or biased (thereby leading to misinformation or reinforcement of existing biases), this could potentially lead to legal ramifications for the developers, providers, or educational institutions involved. It is therefore imperative implement quality control mechanisms to ensure that the system is equipped with reliable and accurate content. From a practical legal viewpoint, a clear term of service and/or user agreement should be put in place which outlines the limitations of the system and responsibilities of all parties involved.
Artificial intelligence systems are gradually revolutionising the education industry. These systems open up possibilities for advanced access to information and personalised learning. Traditional teaching and learning methods are already evolving, and educational institutions are taking steps to incorporate AI systems into their learning and administrative operations. However, issues relating to the use of AI remain, and addressing these challenges is essential to maximising its potential. Either way, the AI revolution has come to stay, and exciting times are indeed ahead in the education industry.
For further information,please contact Zeina Albuainain.
Published in September 2023
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