How AI Has Been Shaping Classrooms 

By. Liliana Kotval

 

In AI’s relatively short developmental span, it has accomplished extremely impressive feats. From predicting trends in the stock market to creating songs with vocals of deceased artists, AI is becoming more and more sophisticated and a part of daily life. We have started to implement AI in virtual assistants in smartphones and in the IoT, in web browsers, in classrooms, in chatbots for customer service, in facial recognition in security systems, and in medical diagnostics and healthcare systems. Particularly, in the field of academia, we are seeing a huge impact in personalized instruction and learning. Learning has never been so catered to students nor has lesson planning been so efficient. Sitting all day in a classroom while an instructor writes notes on a whiteboard is neither engaging nor effective. AI has the power to challenge standardized teaching methods and curate an individual’s learning preferences and needs. 

Before we get further into the details of how AI has shaped learning and research techniques, let’s better understand what AI really is. The first cultural awareness of the term AI can be traced back to the 1968 film “2001: A Space Odyssey”, where a human-like spaceship helped an astronaut in his journey through space (3). Back then, the idea of human-like technology was something of the imagination. Now, just 56 years later, AI is nothing imaginary at all- it is very real. Today’s concept of AI is only slightly different to the film’s portrayal. We still identify AI as human-like in the ways that it can simulate human intelligence processing and can talk back to us, look up information, etc.; however, the way AI performs these tasks is through an unemotional and uncritical processing of information, contrary to as humans would.  AI systems work by ingesting large amounts of labeled training data, then analyzing this data for patterns, and finally using these patterns to make predictions. AI programming uses 4 main cognitive skills (10): 

  1. Learning: Algorithms are created through the acquisition of data and the creation of rules. These algorithms provide devices with step-by-step instructions on how to complete a task. 
  2. Reasoning: The appropriate algorithm is chosen depending on the situation. 
  3. Self-correction: Algorithms are continuously changing to ensure the most accurate results. 
  4. Creativity: Neural networks, rule-based systems, and statistical methods are used to generate new images, text and ideas. 

An example of this process is when a chatbot is fed examples of appropriate text to use as a response to specific learned triggers in customer inquiries. More sophisticated generative AI can create realistic artwork, music or images. On the other hand, it could be argued that in some ways AI is like us, in that it uses learned information and thousands of examples (personal experience, in human terms) to generate a response. But these programmed responses are not genuine and lack personalization and emotions that only a human could give. Nevertheless, we may see AI with the ability of self-awareness and consciousness soon. 

Now that the concept of AI has been introduced, let’s move back to the topic of academia. Many adults would agree that educators used outdated, redundant, and ineffective learning techniques when they were in school.  From a survey taken in 2016, 59% of young people in the EU said their national education is well adapted to the current world of work (5). Across the pond, with an even lower rating, only 43% of US adults were found to be satisfied with the U.S. education system in a 2010 poll (2). These numbers could certainly be improved through the integration of AI tools, albeit not the only option, as Finland has shown the world their highly successful learning methods through more conventional methods. However, Finland has several other contributing factors to its educational success, such as a competitive education sector and low poverty levels, that other countries may never achieve having. In this case and in other examples of countries where completely changing the educational sector seems impossible, AI may be the answer. Where there is technology, there is AI. AI can be easily integrated into the classroom using online platforms or software, such as ChatGPT or OpenAI.  

Although the first uses of AI in education can be traced back to the 1970’s, the use of AI in classrooms particularly skyrocketed in the past year. A 2023 Forbes survey found that 60% of U.S. educators use AI in their classrooms and 55% stated that AI resulted in improved educational outcomes (7). Newly emerging trends in the adaptation of AI in classrooms include improved student retention, an increase in accessibility, highly personalized content, and immersive classrooms (12). Administrators can use AI to identify undergraduates most likely to leave and take proactive measures to improve their quality of education. A bad learning experience may cause a student to never want to enroll again, but the administration that understands everyone’s needs will improve the school’s welcomeness. Furthermore, AI-powered services allow teachers to quickly and efficiently correct student work, plan lessons specific to each student’s needs, and increase support to those with disabilities or learning difficulties. AI systems can analyze a student’s data, such as their strengths, weaknesses, and learning preferences to offer tailored lesson plans. Feedback on student work is made instantly and improvement made easier with virtual assistants that can provide on-the-spot information on any topic. Additionally, immersive classrooms can simulate virtual labs that a school may not have the budget to do physically. For some, education is a privilege, not a right, and AI has the possibility of crossing language barriers and catering to diverse learning needs, no matter the background of the student.   

Referencing recent case studies on the effectiveness of AI in educational institutions, although the use of AI in schools is relatively new, we are already seeing improvements in educational efficiency. First, in a Stanford research study, an AI program was used to monitor Ugandan students’ English learning and offer them a solution when they were stuck on a question (1). It was found that the AI system offered the same solution to the struggling students as a human would, demonstrating that AI can cater to each student’s personal needs, especially when there is a large group of students and not enough teachers. Secondly, in a study by the adaptive-learning website, Knewton, found that students using their AI-powered adaptive learning program improved their test scores by 62% compared to the students who did not use the program (8). Personalized feedback and recommendations by AI can motivate students and aid them while preparing for an exam.  Third, in an example from the Georgia Institute of Technology, an AI-powered chatbot developed by IBM’s Watson was employed as a teaching assistant for a course with 300 students. The chatbot was able to respond to 10,000 student inquiries with a 97% accuracy rate, which would otherwise be overwhelming for a single instructor (9). In the next example, AI was used to predict a student’s final grade and prevent them from failing. The Ivy Tech Community College in Indiana identified 16,000 students at risk of failing in the first two weeks of the semester and worked to improve their learning (6). In the end, 98% of the contacted students received at least a C grade (73-76%). Finally, AI has become an essential tool for grading, as AI has shown to reduce the amount of time teachers spend on grading by 70% (4). The platform Gradescope allows students to upload assignments and are then graded and insights on the student’s performance are sent to both the educator and student. AI systems are bringing numerous benefits to academia, as seen in these studies, including improved learning and grades, responding to student inquiries instantly and accurately, and significantly reducing correction time. The AI educational market is continuously expanding and its benefits widening; AI is surely to become an essential aspect of every classroom soon. 

With everything there comes a risk, and with AI, teachers and students must be aware of the data privacy and security concerns with AI having access to detailed personalized data. This goes beyond the conventional student records, gradebooks, and rosters that we have been used to (3). Now a student’s profile will not only contain his personal information, but it will also be online and contain surveillance details about his specific learning abilities. Furthermore, the use of AI could hinder students’ abilities to create original work, as since late 2022, the public has been able to use AI chatbots to write essays, artwork, and download text summaries rather than reading them. I am sure we have all had the conversation with an older family member about how we are so lucky to have technology now while studying, as all they had back in the day were books and their own imagination to reference. However, we must be careful to not let AI get in the way of abilities to generate unique ideas by creating systematic students. Both educators and students will have to work together to ensure the learning methods are still effective and encourage independent thinking that does not come from AI. AI could be used to create a summary of a book chapter, for instance, yet the critical thinking and synthesis of the chapter should be done by the student himself. A further potential problem with AI could be that if AI takes the personalization of learning too far, and the pace is much slower for those students with lower grades, there could be wide achievement gaps. This would fall under the classification of algorithmic discrimination, where AI algorithms could use historical data, such as cheating incidents, to cause bias in future learning (3). It is very important that the introduction of AI to schooling is understood and controlled now, before its impact becomes too great to reverse. There are several obvious benefits to the use of AI in classrooms, however these benefits may be meaningless if students feel unsafe and incapable of generating original work. 

AI in the education market is expected to cross $20 billion by 2027 (11). We have already seen several examples of AI being implemented in classrooms, such as through test correction and individualized lesson plans, and not only this, but we are also seeing genuine improvements to students’ learning. Its implementation will create an open and diverse learning environment, however, potentially at the risk of students’ ability to think originally. Educators and students will have to work together to ensure that the learning experience is rewarding, effective, and encourages unique mindsets. 

More information on this topic will be discussed during CYBERSEC CEE EXPO & FORUM 2024. 

 

References: 

  1. Andrews, Edmund L. “Using Artificial Intelligence to Understand Why Students are Struggling”. Stanford University. July 2021. https://hai.stanford.edu/news/using-artificial-intelligence-understand-why-students-are-struggling  
  2. Brenan, Megan. “K-12 Education Satisfaction in U.S. Ties Record Low”. Gallup. August 2023. https://news.gallup.com/poll/510401/education-satisfaction-ties-record-low.aspx#:~:text=8%25%20of%20U.S.%20adults%20and,%25%20of%20K%2D12%20parents 
  3. Cardona, Miguel A. et al. “Artificial Intelligence and the Future of Teaching and Learning”. Office of Educational Technology. May 2023. https://tech.ed.gov/files/2023/05/ai-future-of-teaching-and-learning-report.pdf  
  4. Crockett, Emma. “How AI is Being Used in Education”. Datamation. March 2023. https://www.datamation.com/artificial-intelligence/how-ai-is-being-used-in-education/  
  5. Eurobarometer. “European Youth in 2016”. https://europa.eu/eurobarometer/surveys/detail/2372  
  6. Google. “Ivy Tech Develops Machine Learning Algorithm to Identify At-Risk Students and Provide Early Intervention”. https://edu.google.com/why-google/customer-stories/ivytech-gcp/  
  7. Hamilton, Ilana. “Artificial Intelligence in Education: Teachers’ Opinions on AI in the Classroom”. Forbes. December 2023. https://www.forbes.com/advisor/education/it-and-tech/artificial-intelligence-in-school/#:~:text=60%25%20of%20Educators%20Use%20AI,reporting%20the%20highest%20usage%20rates 
  8. Harvard University. “Knewton Personalizes Learning with the Power of AI”. April 2021. https://d3.harvard.edu/platform-digit/submission/knewton-personalizes-learning-with-the-power-of-ai/  
  9. Korn, Melissa. “Imagine Discovering That Your Teaching Assistant Really is a Robot”. The Wall Street Journal. May 2016. https://www.wsj.com/articles/if-your-teacher-sounds-like-a-robot-you-might-be-on-to-something-1462546621  
  10. Laskowski, Nicole, et al. “Artificial Intelligence (AI)”. TechTarget. https://www.techtarget.com/searchenterpriseai/definition/AI-Artificial-Intelligence  
  11. PR Newswire. “AI in Education Market Revenue to Cross $20B by 2027; Global Market Insights, Inc.”. June 2021. https://www.prnewswire.com/news-releases/ai-in-education-market-revenue-to-cross-20b-by-2027-global-market-insights-inc-301318889.html  
  12. Schiller. “The Impact of Artificial Intelligence on Higher Education: How it is Transforming Learning”. August 2023. https://schiller.edu/blog/the-impact-of-artificial-intelligence-on-higher-education-how-it-is-transforming-learning#:~:text=AI%20systems%20can%20analyze%20student,it%2C%20enhancing%20their%20learning%20experience 

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