Computer Vision and Deep Learning for Education

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Table of Contents

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Computer Vision and Deep Learning for Education

This is the last of a 5-lesson course: CV and DL for Industrial and Big Business Applications 102.

1. Computer Vision and Deep Learning for Oil and Gas
2. Computer Vision and Deep Learning for Transportation
3. Computer Vision and Deep Learning for Logistics
4. Computer Vision and Deep Learning for Healthcare
5. Computer Vision and Deep Learning for Education (this tutorial)

An educated population is critical for every country’s economic success as they contribute to its gross domestic product (GDP). Yet, globally, it is estimated that around 750 million adults are still functionally illiterate, primarily women living in Africa and South Asia. Global youth are particularly concerned as more than 64 million are currently unemployed worldwide (Figure 1). These numbers illustrate the tremendous challenge of adequately preparing the workforce for rapid technological change requiring continual reskilling.

You might also enjoy our tutorial deep learning for computer vision.

Even though Artificial Intelligence (AI) is likely to replace millions of workers, it has great potential to enable them to keep up with changing technologies and remain valuable to the country.

In emerging markets, AI has the potential to provide affordable post-secondary education, make learning exciting and fun, and make the content personalized to individual students’ needs. Further, the adoption of AI in education can accelerate with the evolving digital technologies, smartphones, and desktops becoming common in households these days.

The global market for AI-based educational products is growing quickly and is estimated to reach about $10 billion by 2026 at a compound annual rate of 45.1%. This series is about CV and DL for Industrial and Big Business Applications. This last blog of the series will cover the benefits, applications, challenges, and tradeoffs of using deep learning in the education sector.

To learn about Computer Vision and Deep Learning for Education, just keep reading.

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Computer Vision and Deep Learning for Education

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Benefits

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Smart Content

Artificial Intelligence can help teachers and research experts create innovative and personalized content for their students. AI-based content creation can stimulate real-life experience by providing audio-visual experience, thus assisting students in perceiving information in numerous ways. Further, AI can generate bit-size learning via low-storage study materials and other lessons in digital format. Personalized content can also be developed and adapted based on how students perceive various lessons, thus focusing on every individual’s requirement through features like games, programs, etc. (Figure 2).

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Task Automation

AI software can easily handle repetitive, manual tasks (e.g., checking homework, grading tests, organizing research papers, maintaining reports, and making presentations/notes). For example, they can scan test papers with the help of natural language processing (NLP) algorithms to detect correct answers and grade them accordingly. Further, by analyzing grades, the software can analyze where individual students are lacking and how they can improve the learning process.

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Closing Skill Gap

With rapidly changing technologies, upskilling students is valuable for the growth of a business and economy (Figure 3). This ensures that the population remains employable and beneficial to the country. AI- and ML-powered software can deliver widely available and affordable opportunities for students to upskill. Further, deep learning can help learning and development by analyzing how people acquire skills. As soon as the system adapts to human wants, it automates the learning process accordingly.

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Applications

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Student Learning and Welfare

Artificial intelligence can enhance the learning experience and improve outcomes for students of all ages and socio-economic backgrounds. Most of the data required is already being collected (e.g., grades, school and state examinations results, attendance, punctuality, comparison reports, classroom notes, student feedback, etc.). In addition, with emerging cognitive solutions, it is now possible to extract information from handwritten notes and audio or video recordings.

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Personalized Learning

Intelligent Tutoring Systems can teach learners by providing immediate and personalized feedback and providing insights into their progression. AI’s ability to connect different data sources can help identify areas where real-time interventions are needed. Further, they can tailor and individualize the learning pathway such that it is specifically designed to accommodate their strengths, weaknesses, talents, and challenges (Figure 4). These personalized tutoring systems can also aid learners inside and outside classrooms.

This kind of learning will help teachers focus on other critical tasks like interventions with empathy and nurturing creativity, which humans are inherently better at than machines. In addition, such personalized learning provides students with an optimal learning environment where they can focus on their strengths and weaknesses to achieve their full potential. This improves their academic performance, attitude toward school, engagement level, and the sense of being cared for and valued. Besides that, general well-being and happiness are also likely to improve.

Netex Learning (Figure 5) is developing electronic curricula for various devices by leveraging an AI interface. This technology, “smart” classrooms, and other immersive educational experiences provide new and more effective ways to teach science, geography, and other subjects.

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Social, Emotional Growth, and Well-Being

Social and emotional well-being is increasingly becoming important in the education sector as interpersonal skills, empathy, and creativity are essential for tomorrow’s jobs. In addition, social skills like collaboration and problem-solving are necessary for a labor market. As students’ exposure to the internet and social media is increasing, they need to link their outlook and moods to their ability to interact and collaborate with others and their capacity to learn. Fake news, disturbing images, stories, peer pressure, cyberbullying, health and welfare disorders, eating disorders, depression, and anxiety can significantly impact learning.

AI and multimodal social computing can help improve cognitive, social, and emotional skills by allowing educators to personalize instruction and analyze qualitative and quantitative data to assess and assist a student’s mastery of these skills. In addition, AI can help predict and prevent crises in student well-being or welfare. For example, it can ingest data from various sources (e.g., performance reports, attendance, and reports from teachers and counselors). It can also create a dashboard and alerts that help the institution plan and allocate resources to support early interventions for students in need of assistance, in danger of dropping out, or undergoing mental health, academic, or personal life crises.

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Acquiring 21st-Century Skills

The 21st-century skills are a set of competencies and capabilities that students will require upon graduation to achieve their full potential. Although the list can vary, core skills include creativity, collaboration, critical thinking, perseverance, problem-solving, self-direction, awareness, and digital literacy (Figure 6). AI can help students develop skills in all these areas by orchestrating and personalizing learning delivery.

AI can assess progress against a large and disparate set of measures, ingest data from all learning pathways, and generate insights that provide a holistic view of each student’s progress that most clearly illustrates AI’s value in improving learning outputs. Assisting a cohort of students in developing a broad range of 21st-century skills requires collecting and analyzing vast amounts of data (sometimes called Big Data). AI is required if valuable insights are to be exposed, which will assist them in that journey. As the organizational theorist Geoffrey Moore puts it, “Without big data, you are blind and deaf and in the middle of a freeway.”

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Educators

AI and analytics can help educators deliver immersive and engaging educational content to their students and build personalized learning experiences for each of them. As a result, AI can increase teaching effectiveness and assist teachers and institutions in providing students with the ideal environment to learn and grow.

By helping teachers create personalized learning pathways, AI can save them a significant amount of time which they can spend more on other empathy and creative tasks where machines don’t excel. In addition, by providing them with detailed insights into the behavior and progress of each student, they can quickly identify the gaps in their learning method and improve them. AI can also create real-time performance reports, which can be made available to institutions and parents. These reports can be more accurate and up-to-date than traditional reports by reflecting past performance at set points in time during an academic year.

A California-based startup, Gradescope (Figure 7), is offering AI-assisted grading technology to group similar test answers into batches that a teacher can scan through, review, and grade more efficiently. Their AI algorithm learns to grade students’ submissions based on a small number of answers provided by the teacher.

Data analytics can provide insights that can support teamwork across a school. Teachers, department heads, counselors, and leadership can contribute their efforts and collaborate to deliver individualized support programs and enhanced curricula based on a similar set of learnings and indicators. AI can help the department and teachers identify their current curriculum’s strengths and weaknesses and structure it properly. Further, best practices that improve learning outcomes can be identified and shared. Finally, mentorships and peer coaching relationships can be enhanced by ready and ongoing access to quantitative and qualitative data.

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Parent Engagement

Parents play an essential role in the learning journey of a student. Active engagement and participation of parents in their child’s learning process can teach the punctuality of attending school and curiosity in the child. This will inspire them to take advanced lessons and excel in their academics. Such students also tend to have better social skills.

Schools and institutions can also benefit from the active engagement of parents. By prioritizing parent-teacher relationships, the learning environment for the students can be improved, thus leading to better outcomes. AI can help enforce parent engagement by allowing them to become participants rather than just reviewers in their child’s academic journey. They can ensure that they have access to data and insights from it. By providing parents with insights into their child’s progress, AI can help them reinforce the importance of education to their children.

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School and Institution Management

School leaders must ensure that their institutions continue to operate and provide their services even in unexpected circumstances. Sudden expenses for building repairs, absent teaching staff, and peaks and troughs in student enrollment numbers can impose stress and financial constraints on the institution, which can impact the quality of its service. Predictive analytics can help school leaders proactively manage and predict issues before they occur. These AI solutions can lower energy costs, manage staff absence, optimize resources, etc.

Retaining and attracting talent is also one of the biggest challenges school leaders face. The World Bank can recognize the global shortage of quality teachers leading to a teaching and learning crisis. Even though AI cannot create and replace teachers, it can help school leaders understand and manage attrition by addressing the root causes and by providing teachers the autonomy to develop their personalized learning paths, identify student needs, and generate automation. In real-time reports, AI can reduce teachers’ frustrations by enabling them to do what they love best in a more effective and rewarding way.

AI can interrogate and identify a specific individual needing help. For example, AI adds context to internet searches, avoids cybersecurity breaches, and protects sensitive student data. It can also generate an alert if it notices a student searching for self-harm.

The school curriculum needs to evolve in response to changing pedagogies and skills in demand. Shortages of essential skills and proficiencies can hold economies and societies back, stalling or halting their nations’ progress. AI can help the people in charge of the school curriculum by interrogating large datasets, analyzing and generating insights, and displaying them via dashboards. This will improve the quality and accuracy of the information available during curriculum design (Figure 8).

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Challenges

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Lack of Expertise and Literacy

Compared to AI use in industry and agriculture, AI is in its infancy in the education sector of emerging economies. Most educational institutions need a formal data management strategy to support their use of AI capabilities, and educators generally need more understanding to implement such a strategy practically. The lack of technical expertise required to integrate AI solutions that involve complex algorithms has also hampered the growth of the AI market. As is often the case with AI technologies, data is the source of discrepancies due to a lack of diversity in observed populations or groups of people datasets.

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The Ethical Dimension

Ethical frameworks will be required during the development and deployment phase for everyone to reap the benefits of AI in education and not get exploited (Figure 9). AI in education will raise concerns regarding student data privacy, protection, and ethical use. Such a framework of ethics needs to ensure that gender, socio-economic, and ability biases are not introduced at the development level. It needs to ensure that cultural stereotypes are not promulgated and that all learners receive the same quality of content irrespective of where they live. Transparency and oversight will be required to strengthen fundamental human rights.

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Equality and Access

According to a global report on internet penetration, more than 40% of people do not have access to the internet. This disparity varies widely between regions. For example, in Northern America, 95% of people have access to the internet, unlike in Middle Africa, where only 12% have this accessibility. Not having decent smartphones and internet access can disadvantage students in this digital age. With no smartphones, access to the information required to train unbiased machine learning models will be limited. This may be disadvantageous when building personalized learning pathways that adequately identify and address their needs.

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Dependence on Technology

Relying entirely on AI for education can be dangerous as our dependence on these machines increases. Students who rely on AI will lose their ability to think creatively. Perhaps those dependent on AI for calculations become less skilled at mental arithmetic. Hence, the appropriate and effective use of AI will always require human input. Therefore, the educator’s role will likely be enhanced rather than displaced by technology.

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Summary

An educated population is critical for every country’s economic success as they contribute to its GDP. In emerging markets, AI has the potential to provide affordable post-secondary education, make learning exciting and fun, and make the content personalized to individual students’ needs. The education sector can adopt AI in the following ways:

• Personalized Learning: Intelligent tutoring systems can teach learners by giving them immediate and personalized feedback and providing insights into their progression. They can tailor and individualize the learning pathway such that it is specifically designed to accommodate their strengths, weaknesses, talents, and challenges.
• Well-Being: AI can ingest data from sources like performance reports, attendance, and reports from teachers and counselors and create alerts that can help the institution provide support to students in need of assistance, in danger of dropping out, or undergoing mental health, academic, or personal life crisis.
• Time-Saving: By helping teachers create personalized learning pathways, AI can save them a significant amount of time, allowing them to spend more time on other empathy and creative tasks where machines don’t excel.
• Parent Engagement: AI can help enforce parent engagement by allowing them to become participants rather than just reviewers in their child’s academic journey. They can ensure that they have access to data and insights from it. By providing parents with insights into their child’s progress, AI can help them reinforce the importance of education to their children.
• School Management: AI can help the people in charge of the school curriculum by integrating large datasets, analyzing and generating insights, and displaying them via dashboards. This will improve the quality and accuracy of the information available during curriculum design.

However, AI in the education sector comes with its challenges.

• Lack of Expertise: The lack of technical expertise required to integrate AI solutions that involve complex algorithms has also hampered the growth of the AI market. As is often the case with AI technologies, data is the source of discrepancies due to a lack of diversity in observed populations or groups of people datasets.
• Ethical Issues: AI in education will raise concerns regarding student data privacy, protection, and ethical use. Such a framework of ethics needs to ensure that gender, socio-economic, and ability biases are not introduced at the development level.
• Equality and Access: Not having decent smartphones and internet access can disadvantage students in this digital age. With no smartphones, access to the information required to train unbiased machine learning models will be limited.

We hope this post helped you understand the benefits, applications, challenges, and tradeoffs of using deep learning in the education sector. This concludes the series on CV and DL for Industrial and Big Business Applications. Thanks for sticking through to the end, and stay tuned for another new series.

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Citation Information

Mangla, P. “Computer Vision and Deep Learning for Education,” PyImageSearch, P. Chugh, A. R. Gosthipaty, S. Huot, K. Kidriavsteva, and R. Raha, eds., 2023, https://pyimg.co/0pjrx

@incollection{Mangla_2023_CVDLE,
  author = {Puneet Mangla},
  title = {Computer Vision and Deep Learning for Education},
  booktitle = {PyImageSearch},
  editor = {Puneet Chugh and Aritra Roy Gosthipaty and Susan Huot and Kseniia Kidriavsteva and Ritwik Raha},
  year = {2023},
  url = {https://pyimg.co/0pjrx},
}

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