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Home Machine Learning

What is the future of virtual learning in Pakistan?

April 16, 2020
in Machine Learning
What is the future of virtual learning in Pakistan?
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In contemporary era, integration of artificial intelligence and education is a very popular and emerging field. With the COVID-19 crisis, the world has experienced a situation which wasn’t anticipated and which it wasn’t ready for. Like other systems, education systems also received a severe blow. Schools shifted from traditional classroom settings to remote learning modules. In places where there wasn’t an access to technology, the process of formal teaching and learning came to an abrupt halt. In places where there was access to technology, teachers began to wrestle with the struggles of adapting their pedagogical skills to a technology-oriented classroom. In these virtual learning settings, the role played by artificial intelligence becomes even more significant.

According to Murphy, Artificial Intelligence refers to those techniques and algorithms which allow a computer to simulate the human perception processing and decision-making abilities. In the domain of education, there are presently two broad uses of AI. The first use is comprised of rule-based applications. These applications are used to run instructional educational software. The second use comprises machine learning. This type of narrow AI supports automated scoring systems.

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Rule-Based Applications:

In educational spheres, a very common application of rule-based expert systems is the intelligent tutoring systems.

Intelligent Tutoring Systems (ITS)

The first ITS made its appearance in the beginning of 1980. It sought to simulate a human student-teacher interaction. An ITS basically replicates the instructional experience for a student. It adapts the instructional content according to the individual student’s needs and level of skill development. Accommodating a diverse array of ability levels in a heterogeneous classroom can be very challenging. Since an ITS is a very personalized tool, it can address the problem of skill differentiation effectively. ITS applications can vary according to the purpose of their use. Some of them tend to serve as a primary instructional tool; whereas, others are meant to be used as a supplementary tool in the classroom for homework or other activities.

No matter what the purpose of an ITS may be, they do share some common features. Almost all of the ITSs out there allow learning to be self-paced. Instructional content is usually adapted to the individual student’s learning needs. There is mastery of learning involved, i.e., the ITS requires a certain level of a course’s lesson’s sequences to be mastered before it moves on to the next level. There is frequent assessment of skill development and knowledge acquisition. Moreover, each task is followed by automated feedback for the student. The precise architecture of an ITS application may vary, but most of them such as ALEKS, Dreambox learning, Moby Max, and IXL adhere to these common features.

Machine Learning

One of the most effective ways in which machine learning can be deployed in the domain of education includes the use of automated scoring systems.

Automated Scoring Systems

Automated Essay Scoring (AES) is a very mature AI application which first appeared on the market in 1990s. AES has been very popular in language classrooms because scoring/grading written essays and exams can be a tedious and time-consuming process. Owing to this reason, teachers are generally hesitant to assign extended writing assignments too. However, AES makes that task easier for teachers, allowing them to focus on other things. Originally automated scoring systems would merely give a holistic, overall score. Some of the present systems though, now provide students with individual feedback and guidance too. These systems may even provide writing samples for learners to model their writing after. Some examples of these systems include Turnitin’s Revision Assistant, Grammaly, Pearson’ Write to Learn and Chegg’s WriteLab (Murphy, 2019, p.9).

The Future of Artificial Intelligence in Pakistan

Though Pakistan has taken steps to use AI-based solutions in a number of arenas such as environment conservation, water conservation, human interaction, medical advancement, digital optimization and business profitability, yet, education appears to be an area which has been overlooked for the most part. Although, the Higher Education of Pakistan (in collaboration with the government of Pakistan) has begun an AI project worth 1.1 billion rupees whereby it has partnered with six leading universities of the country, however, no efforts have yet been taken to bring this technology into classrooms.

Private organizations such as Jazz have started initiatives along these lines, but Pakistan needs to dig deeper into this field and investigate ways in which AI tools can become accessible and can fill gaps in Pakistan’s education system.

These gaps seem even more apparent in the crisis which befalls us all today. No country in the world was prepared for this global pandemic but developing countries like Pakistan seem the least equipped to battle this storm. In the wake of this storm, however, we will have several lessons to learn. One of those lessons should be to make our educational system technologically competent and to make our people digitally literate. AI tools have a crucial role to play in this regard. Policy makers, educators, software developers and researchers all need to butt their heads together and think of ways in which our education system can reap the most benefits out of artificial intelligence and technology.


Credit: Google News

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