The days of going to libraries to make
exhaustive photocopies for school projects are long gone. The internet has
replaced books as children's main source of information as they grow up in the
digital era. According to a 2019 survey, American youngsters between the ages
of 8 and 12 spend about five hours per day in front of screens, while teenagers
spend more than seven hours per day, not counting schooling. Since the
beginning of the COVID-19 pandemic and the accompanying social restrictions in
lockdowns, the amount of time spent learning from chalkboards in actual
classrooms has also dramatically decreased. Education remains one of many evolving sectors
due to emerging technologies like artificial intelligence (AI), machine
learning (ML), and robots.
The need for AI expertise is increasing. The U.S. Bureau of Labor Statistics projected that by 2031, data science occupations are
expected to expand by 36%, which is much more than the average rate. A growing
demand for data scientists and AI professionals is being caused by the growth
of technology, which is fostering data operations, analytical complexity, and
AI usage. Beyond its use in decision-making and dialogue, AI's transformational
impact on learning is sometimes underestimated. Technology is advancing
significantly in the field of education, with AI and ML playing important roles
that go beyond grading exams. Both teachers and students stand to gain greatly
from these technologies. However, integrating digital resources for
cutting-edge teaching strategies is a challenge for many institutions.
Three Ways AI and Education Technology Are Transforming
Education
The days of going to libraries to make exhaustive photocopies for school projects are long gone. The internet has replaced books as children's main source of information as they grow up in the digital era. According to a 2019 survey, American youngsters between the ages of 8 and 12 spend about five hours per day in front of screens, while teenagers spend more than seven hours per day, not counting schooling. Since the beginning of the COVID-19 pandemic and the accompanying social restrictions in lockdowns, the amount of time spent learning from chalkboards in actual classrooms has also dramatically decreased. Education remains one of many evolving sectors due to emerging technologies like artificial intelligence (AI), machine learning (ML), and robots.
The need for AI expertise is increasing. The U.S. Bureau of Labor Statistics projected that by 2031, data science occupations are expected to expand by 36%, which is much more than the average rate. A growing demand for data scientists and AI professionals is being caused by the growth of technology, which is fostering data operations, analytical complexity, and AI usage. Beyond its use in decision-making and dialogue, AI's transformational impact on learning is sometimes underestimated. Technology is advancing significantly in the field of education, with AI and ML playing important roles that go beyond grading exams. Both teachers and students stand to gain greatly from these technologies. However, integrating digital resources for cutting-edge teaching strategies is a challenge for many institutions.
Implementing AI in Education: Overcoming Challenges
• Personalized Learning: Because each student learns at a different speed
and with different preferences, they receive different levels of attention and
instruction. AI provides personalized, adaptive learning that takes into
account each person's requirements, objectives, and skills. With the help of
personalized programs, pupils who are falling behind may catch up, and those
who are ahead can keep moving forward.
• Automation: It is now possible to automate tedious, time-consuming
procedures, which will relieve teachers' stress and increase productivity.
Classrooms become more interesting as a result of teachers' increased freedom
to modify procedures as necessary.
• Chatbots driven by AI: These chatbots offer 24/7 learning accessible from any location. To meet the growing need for self-service and student support, these interactive bots provide immediate replies and frequent updates. By simplifying support, chatbots improve the learning experience for both students and teachers.
Many educational institutions have obstacles, such as costs, time, or
knowledge gaps, even as AI usage rises. Institutions must manage these
difficulties if they want to gain from AI. The first stage is to develop a
creative knowledge of AI's capabilities and determine the issues it can
address. Start with basic implementations, get feedback, and then progressively
increase. Make clear the resources—budget, equipment, and bandwidth—that are
necessary for initiatives to succeed.
A better future is promised by AI. Its potential to lessen teachers'
workloads around the globe is clear. However, there are still reservations
about AI completely replacing teachers. Fortunately, it appears doubtful that
this will occur. While AI can teach math and reading, only humans are capable
of imparting social and emotional knowledge in a subtle way.
The World Economic Forum predicts that by 2025, many companies will have embraced
technology like machine learning (ML). To meet the upcoming demand, they
fervently urge governments and educational institutions to improve education
and skills in STEM fields as well as non-cognitive soft skills. The workforce
will see enormous disruptions as a result of technological breakthroughs, with
automation having the potential to replace up to 50% of current occupations in
the United States alone. According to Microsoft's research,
to graduate, students must be proficient in two crucial facets of this
new era. AI powered by machine learning has tremendous potential since
computers can learn and get better over time, especially when working with
large, multi-layered data sets.
Machine learning-based AI systems may perform a wide range of activities
in the field of education, including tracking students' behaviour and developing
models that correctly forecast student outcomes. Even while machine
learning-based AI is still in its infancy, it has already produced impressive
outcomes for difficult problems that are not constrained by established rules,
such as grading student-written replies or analyzing enormous, complicated
datasets. Numerous crucial disparities within the AI field are mostly driven by
technical application cases.
Natural language processing is an important subfield that employs
computers to understand text. Natural language processing is used by
technologies like automated essay scoring to assess written essays. Recommender
and prediction systems that use data-driven forecasting are also essential in
AI. Netflix, for instance, uses an AI-based recommender system to recommend new
movies to its subscribers. Another crucial area that aids in evaluation is
vision-based AI. Several evaluation teams rate students' work using optical
systems. A machine can assess a student's written arithmetic problem instead of
the instructor having to grade it by hand. Instead, the teacher can take a
photo of the equation.
Lastly, there are voice recognition-based AI systems that serve as the
brains behind devices like Siri and Alexa. Experts have been investigating how
to diagnose reading and other academic difficulties using voice-based AI.
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