The future is sooner than you would have expected – it is now. Contrary to concerns about Artificial Intelligence (AI) in everyday activities, ethical AI can enhance a balanced, accessible, scalable, and inclusive learning system. With the increasingly limited resources and restrictions but high expectations on student outcomes for higher institutions, any institution looking to thrive in this current age will have these factors to consider.
In light of the recent happenings, the only sure thing is: Things Will Change.
Sometime in March 2020, most states in the USA implemented remote work and school. The concept of working and schooling from home was quite strange and frustrating. The whole work-day dynamics changed so drastically without any warning or form of preparation. Many understandably struggled to balance family and work, and some scrambled to acquire new skills to make them more relevant in the digital world. It is impressive, though, that many companies stepped up to provide free learning resources ranging from Music to Math and virtual Zoo and Museum tours.
A plethora of new changes, involving many parts at a speed we did not envisage or prepare for, re-emphasized the changing mindset. This change ignited a level of adaptation we wouldn’t have adopted willfully, and people began to do things they didn’t envision they could do in light-years.
- People are starting to solve problems and demand solutions or services differently.
- Businesses with no online presence went online, delivery services and curb pick-ups sprang up, and non-essential procedures or services got canceled.
- Age-old policies changed in minutes over video conferences which made the decision-making process very informal.
Yet, a new saying was birthed – “The New Normal”.
[Case Study] How the University of Alabama at Bimingham Amped Up Organization-Wide Performance with Data Analysis
Read how the University of Alabama at Birmingham was able to leverage Tableau, a data visualization & analysis tool, to enhance performance of each department and program. Learn More
The New Normal for Education
Just as we know big data for businesses, we also have humongous data for learning with an increasing number of useful resources for students. There has been an increase in the creation of smart content. Learning materials and resources are condensed in a more precise and digitized format. This makes learning much faster and easily accessible.
With a more concise and digitized learning format, students will have the flexibility of choosing to work remotely or not. Even though this is already in practice, it will take on a larger scale and extend to many other programs. This will gradually reduce the cost of education, remove global boundaries, and make learning possible from anywhere.
With more people opting for remote learning, the mode of delivery will gradually change. The medium to teach will shift from the sole traditional class delivery or operations to creating a hybrid of integrated AI with augmented reality and the conventional classroom.
Learning will take on a more adaptive approach and become even more personalized. It will then become even more challenging to sustain a manual method to measure engagement, pace, and effectiveness of the teacher. Different measures to measure this for early intervention will become paramount, which will further require more use of technology.
Online learning platforms provide instant learning work emphasizing on weak points for improvement and recommending other topics to learn. Educators can see specific struggle areas and the number of attempts, contrary to the traditional learning format. It will be a lot of work for teachers to provide personalized learning track and almost impossible to trace specific struggle areas for every student at once.
Machines cannot replace the role of an educator because it goes beyond helping students garner academic knowledge or handling administrative tasks like grading or marking attendance. These tasks can be automated to enable educators to gain deeper insights into students’ behavior and provide detailed and individualized feedback. Everything is done in a fraction of time with more accuracy, thus providing more time for mentorship and guidance.
The Role of Institutions
These are critical areas institutions need to look into to enable them to compete in the new era of AI-enhanced higher education.
1. Data Mining/Engineering
Many higher institutions already have processes in place to handle data processing. The difference, however, is there will be more data, mostly unstructured, that will require near real-time processing and accessibility to more users.
Remember, the data will no longer be in a standard format that can be easily generalized. Institutions will require a more creative approach and a tweak to existing data processing pipelines to accommodate these rapid changes.
2. Realtime Monitoring
Monitoring academic, financial, and operational outcomes will even become more critical. The ability to successfully pull this off is dependent on the data mining process. With a gradual blur on education boundary, the competition will be more fierce, so real-time monitoring is essential to early intervention for improved outcomes and to stay ahead of the curve.
“Syntelli helped us deliver Tableau dashboards which had some complex inner workings that were ultimately well-received by our administrators and deans. The Syntelli team were easy to work with and their analysts overcame some challenging problems in a very short period of time. I really appreciated how Syntelli always came prepared with alternative solutions to difficult or seemingly impossible user requirements.”Eva W. Lewis
3. Predictive/Prescriptive Analytics
Using all the metrics monitored and data gathered,
- Identify key indicators of student performance.
- Measure the effectiveness of teaching resources.
- Evaluate the quality of education
Institutions can deploy predictive and prescriptive analytics to understand factors they have control over that can yield desired outcomes. These are also methods to ensure early intervention for remedial actions to steer the students in the right direction. Waiting to see the results of tests and exams will be of no help and could be damaging to the school’s reputation.
The role of Artificial Intelligence is very significant in education advancement, and it does not imply that institutions should rid themselves of real and in-person opportunities either for academics or non-academics.
A well-deployed AI system should serve as a level ground for all students and provide more time for more meaningful engagements.
Syntelli Solutions is continually doing research and development to help institutions make the most of the resources available to them. Contact us to learn more.
Moyosore Lawal, Sr Analytics Associate
Providing solutions that enhance business competitiveness and enable companies achieve their goals leveraging on data is what Moyo stands for. She has worked with data in a number of ways and has a well-grounded understanding of the data lifecycle.
As a Data Scientist/Engineer, she has managed several successful projects building and implementing predictive models. She earned her M.S. in Data Science and Business Analytics degree from the University of North Carolina at Charlotte.
Why Public Cloud Services Will Become Essential for Data and Analytics Innovation
Cloud computing services started as a niche area for tech companies and savvy young professionals. Storing files and data "in the cloud" was originally subject to file size restrictions and technical limitations that kept it from catching on with companies in most...read more
The Rise of Decision Intelligence: AI-Optimized Decision Making
The use of artificial intelligence in business continues to evolve as massive increases in computing capacity accommodate more complex programs than ever before. Decision intelligence, the intersection of technology and business needs, helps companies think on a...read more
Achieving Smarter AI with NLP
Experts predict that 30% of companies will base decisions on graph technologies by 2023. This change and a shift to operationalizing AI may cause an increase in streaming data and analytics infrastructures. Several AI techniques, including machine learning (ML),...read more