AI in the classroom – tracking the trends

Digital transformation, 4^th industrial revolution, Artificial Intelligence, AR/VR and now Metaverse, all those buzzwords shake the world, and education is not left behind. Even before the Covid times it was predicted that AI market in education sector would grow for about 50% in three years. The international agencies and think tanks that analyze the impact of AI on the on skills development and TVET sector found that in some economically advanced countries TVET institutions are already practicing “‘hollowing out’ of intermediate-level skills and the integration of flexible learning pathways”.

^{Image source: Intelligent classroom AI monitoring system}

While before the pandemic it was easier if not to ignore, but to a certain extent to neglect and postpone implementation of the new digital systems in schools and classrooms, Covid-19 has leveraged the priority of the technology in education advancement everywhere.

We have discussed Emergency Remote Teaching and its impact on the education in six Eastern European countries in our webinar.  Now let’s touch the topic of applications of AI in education, that includes also classroom monitoring systems.

Several trends were already identified, researched and supported by the academics, companies and startups in the field. What are the benefits and caveats of AI in education? The Edtech Magazine has identified 5 key roles for AI in K-12 classrooms: Automation of straightforward tasks, Integration with other IT initiatives, Acclimation to the pace of technological change, Delineation of the new critical trends in education to help teachers design effective learning, and Identification of the important areas of student and teacher performance with AI analytics.

Among common benefits, Personalization is also often mentioned. That means more opportunities for students to get individualized learning paths better tuned to their prior experiences and current needs. Also, that allows teachers to respond selectively to the individual learning gaps and create the intervention measures.

Another frequently mentioned domain is automation of answering to the common questions. Chatbots and more advanced AI that have access to the pool of answers to specific questions or can smartly design the most efficient answers based on the databases and the student profiles could save lots of precious time for teachers and learners. Of course, teachers have to have access to these human-machine communication and consider them in further learning activities. Routine and mundane questions responded by the bots could also provide additional material for meta-analyzing the trends and finding probable gaps in the education process that require creative attention of the teacher.

In addition, more flexible access to education and automation of the administrative tasks are cited among the common benefits associated with the AI in education.

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Classroom monitoring systems is also another big domain, that sometimes is experimental and triggers heated response. These systems could vary from the large commercial offerings or government supported projects to private initiatives or DIY (Do it Yourself) guides based on Arduinos and Raspberries. It could also include Biometric sensors and sets of cameras with face-recognition features.

While the face and emotion recognition algorithms are maturing, meaning that they are trained on millions of examples, the question is: how this helps the educator in the classroom?

The classroom and student monitoring systems existed even before the AI advancement, that often implied 1-1 education models, meaning that each student used to have own PC, tablet or a smartphone. In that scenario the tasks accomplished on the own device are being reported to the dashboard on the teacher’s computer, that allows timely and individual response to students and the ability to analyze the overall class performance.

Offering personal Chromebooks or pads for all students to use also at home could be considered an expansion of that direction. In Georgia all first graders in the public schools are receiving a netbook for personal educational usage that comes with installed programs and classroom management through Microsoft Teams, while the personal profile of each student is managed by the Education Management Information System.

As reported, school districts in the US use proprietary monitoring systems that allow administrators and teachers to track the physical location and also each word searched on Google by each student. That allows not only to prevent accessing inappropriate content, but also could get signals about the mental health of the students, e.g. by responding to alarming search queries and generating alerts. It’s up to the educator or school to decide how to act on the reports, and often psychologists are involved. At the same time there are concerns about the intrusion into students’ privacy, and it’s not yet clear how the right balance should be found.

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Apart of the attendance control systems, current trends of the classroom monitoring are more inclined towards analysis of the biometric data acquired from the smart cameras that try to estimate the learners engagement and emotion in real-time based on the eye control, face patterns recognition and posture analysis. Even though the advancements in AI allow reaching about 97% of accuracy in faces recognition, that is still two times less accurate than the human’s capabilities. Still, with that level of accuracy the existing AI frameworks could generate reports concerning the students involvement and attitudes towards the particular educational activity. As one scholarly paper states: “Analyzing students’ emotions from classroom videos can help both teachers and parents quickly know the engagement of students in class” (source: EmotionCues: Emotion-Oriented Visual Summarization of Classroom Videos). That could be particularly useful in the distance learning mode, when it’s impossible to extract all emotional markers from the tiled screen of the synchronous lesson.

Of course, not everyone is comfortable with the perceived loss of privacy. Even though it’s argued that classroom is a public space, still the constant monitoring could cause adverse effects such as fear of mistakes and suppression of creativity. It also true that, students now leak much more personal information through social media (especially with the new tools emerging each decade – e.g. TikTok for Generation Z). Consequently, teachers want “to observe students and created methods that are more suited to Gen Z”.

However, the sense of exposure puts more responsibility and pressure on the student.

^{Source: Vladimir Soloviev publication.}

Teachers also might not want to be monitored all the time, feeling that every step they take could be controlled and evaluated. Whilst, overall, teachers seem to be supportive to gaining more control on their student’s progress with the new tools, and valuing the opportunity to intervene where necessary, they’d rather opt for having the decision power and flexibility, instead of being monitored all the time.

The counter measures that are often implemented to prevent the personal data leakages include filtering/hiding the personal details and storing the collected data on the school/educational institution network that is not connected to the Internet.

With the hype of AI around us probably the best way to meet the new needs and demands of the labour market and information societies is to know more about what AI and monitoring could and could not do, and what the connected precautions and ethical considerations are. However, if properly designed and applied the new data driven analytics could lead to the enhancement and personalization of the learning experiences for many of our students, that could already be considered much more integrated into the brave new world.

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What are your thoughts related to AI in education?

Do you think that benefits outweigh threats?

Do you already practice AI based classroom monitoring?

Please, share your ideas in the comments.