Leveraging Data Analytics & GenAI: Maximise Course Revenue and Enhance Learner Experiences
As the education sector evolves, institutions that harness the power of data science, Generative AI (GenAI), and blockchain technology can enhance their competitive edge and also build unparalleled trust and transparency. Leading educational institutions have already adopted data-driven strategies and verifiable credentials —they recognise that these are essential for success.
Let’s explore how data analytics and GenAI can transform your institution into a beacon of excellence and efficiency.
How Data Analytics and GenAI can transform your institution:
Traditionally, course feedback consists of both qualitative and quantitative aspects. Due to the large number of courses administered, administrators typically prioritise the review of students’ quantitative scores over qualitative feedback. Qualitative feedback is only examined if the scores are exceptionally high or low, leading to an underutilisation of valuable data.
With GenAI technologies, qualitative feedback can now be easily summarised, and common themes can be highlighted across a substantial volume of these feedback. This allows for more effective use of students’ feedback to improve course content and identify gaps. GenAI can also be used to analyse teaching materials and course content, customising them to an individual student’s needs and learning pace. This improves the student’s learning experience and chances of success in their courses.
Enhancing learners’ experiences using GenAI will lead to lower churn rates, higher enrolment, and increased revenue. This technology is now available, and unique customisations of learning are being explored globally. Institutions that pioneer these innovations will gain a significant first-mover advantage over their competitors.
![[11:24] Rachel Lim 2. Possessing the capability to critically assess performance helps boost revenue.](https://www.accredify.io/wp-content/uploads/2024/06/Screenshot-2024-06-28-at-12.05.22 PM-1024x283.png)
Data science and internal analytics facilitate the development of this capability, enabling institutions to gain valuable insights. This, in turn, facilitates informed decision-making and strategic planning, ultimately boosting revenue and operational efficiencies.
Data analytics play an important role in a performance evaluation feedback loop as seen below:
5 Steps Process for Effective Internal Data Analytics
1. Evaluate Performance.
With data analytics, institutions can optimise performance, firstly by evaluating metrics they deem important for success such as:
1. Students’ Retention
Identify students at risk of leaving school and understand the underlying reasons for their potential departure.
By detecting patterns in student behaviour that may signal a likelihood of dropping out, targeted interventions can be implemented to help retain these students.
2. Student Experiences
Gain insights into how students are utilising the educational technologies subscribed to by your organisation. This will help you better understand the effectiveness of these tools in meeting students’ needs.
3. Faculty Experience & Management
Identify professors who are teaching too many classes or experiencing high dropout rates among their students. Additionally, analytics can pinpoint which professors receive the highest ratings from students and uncover the underlying reasons for their success.
4. Facility & Resource Management
Determine which buildings, vocational practice rooms, recording studios and so on, are most frequently utilised and identify departments with varying occupancy rates. Additionally, they can monitor campus energy consumption.
5. Enrolment and Drop-out Rate
Identify which courses have the highest or lowest enrolment or drop-out rate.
6. Budget Management
Gain a comprehensive understanding of revenue generation and expenditure allocation.
2. Identify reasons underlying good performance or lack thereof.
After evaluating the metrics that are important to your organisation, use them to conduct a comprehensive deep dive and identify the reasons behind good or poor performance. For example, after identifying courses with high enrolment rates, you can use additional data points—such as whether the course was taught by a highly rated professor or held in a well-equipped classroom—to identify potential reasons for its success.
3. Replicate success to other courses and address areas requiring improvement.
After thoroughly examining the reasons behind the success, you now have a clearer understanding of how to replicate this success in other courses. Additionally, you can identify the next steps needed to address areas requiring improvement.
4. Implement data-driven strategies and optimise budget by highlighting areas for more efficient resource allocation.
Now that you have a clear understanding on what needs to be done, an overall plan can be created and implemented effectively. With areas of improvement and gaps highlighted in your analysis, your organisation can now optimise budget for more efficient allocation, which in turn, helps reduce expenses and increase revenue.
5. Monitor new processes and evaluate outcomes.
In addition to using data analytics to evaluate internal performance, it can also be leveraged for external analysis, such as industry benchmarking.
This encompasses the following:
1. Identify courses that are popular in the industry.
External data analytics can be leveraged to identify and stay current with courses that are popular in the economy.
By pinpointing popular courses, your institution can develop similar offerings to meet industry demands and capture a larger market share.
2. Identify emerging trends and demands of courses.
Once you have identified popular courses, you can begin to spot emerging trends in the markets and be better equipped to make strategic decisions for your organisation. For example, a rise in course offerings in sustainability indicate that industries are facing a “green transition” and careers specialising in green solutions will likely be in demand in the near future.
3. Benchmark performance of similar courses with competitors.
It is important to be aware of what your competitors are doing to maintain a competitive edge. External data analytics can be used for competitor benchmarking to identify their popular courses as well as compare how your organisation is performing against them.
4. Make strategic decisions to improve course offerings and market position.
With access to critical information such as popular courses in the industry, emerging trends and competitors research, you are now better equipped to develop comprehensive strategic plans, both short and long term, aimed at boosting revenue and improving your institution’s market position.
Leverage experts to effectively harness data analytics and GenAI.
As industry data is not publicly available, both large and small institutions may struggle to conduct this analysis independently. However, external consultants can assist institutions in this area.
On top of providing internal and external data analytics, external consultants are also able to provide customised data consultancy services such as understanding an institution’s unique needs and generating customised business insights for problem solving.
How Data Analytics and GenAI can value-add to any organisation
For example, Accredify, with its proprietary data analysis process and trusted issuance data covering over 300 institutions – representing 97% of all certificate issuance in Singapore – can provide valuable insights. Accredify offers clients an in-depth view of the demand and supply of training courses in Singapore, which can also be used for competitor benchmarking.
To learn more:
To effectively leverage data analytics and GenAI, legitimate data inputs are key.
Data serves as the foundation for GenAI models; therefore, ensuring the accuracy and authenticity of data is essential to minimise flawed or biased outcomes. By using verified, true-to-source data, we can mitigate GenAI hallucination, an increasing issue where a GenAI model, such as a large language model (LLM) or Generative Adversarial Networks (GANs), produces outputs that are incorrect, nonsensical, or completely fabricated. This occurs when AI generates information that appears plausible but is not grounded in factual data or reality. If institutions act on these incorrect outputs, it will not be impactful in, or even detrimental to, improving course revenue and learner experience.
Thus, it is imperative to ensure the legitimacy of all documents and information, and one way to do that is by using verifiable credentials.
Verifiable credentials provide a reliable method to ensure the accuracy of generated and issued data, offering a straightforward and efficient means to establish trust.
Features of verifiable credentials:
1. Tamper-proof– Verifiable Credentials cannot be modified without detection.
2. Dynamic– Verifications will always show the latest status of the credentials, including whether it has been revoked.
3. Instantly Verifiable– Anyone can verify a verifiable credential with a QR code scan or a drag-and drop verification portal.
4. Customisable- Design your verifiable credentials to carry your logo and branding.
5. Storable in digital wallets- Your verifiable credentials can be stored on digital wallets such as Apple and Google wallet.
6. Easily Shareable- Verifiable credentials can be shared via direct link, email, social media, and messaging apps.
7. Privacy-preserving- When sharing, owners of verifiable credentials can choose to obfuscate sensitive personal data, such as National ID numbers.
Verifiable Credentials can be presented in many different formats such as:
1. Certificates and Transcripts– Degrees, diplomas, transcripts, statements of attainment, and more.
2. Licenses and Permits- Vocational licenses, permits to work, entry permits, and other related documents.
3. Digital Badges- Verifiable digital badges to support micro-credentialing initiatives, gamify education, and enhance learner motivation.
4. ID Cards- ID cards to facilitate faculty and student entry into restricted areas, access to campus services, and more.
5. External Performance Reports- Documents such as internal or external performance reports.
These verifiable credentials can be used as inputs for any GenAI model. Since they are accurate and verified, they will aid in mitigating GenAI hallucinations.
By leveraging internal and external analytics, verifiable credentials, and GenAI, institutions can significantly enhance their revenue streams and course offerings. Internal analytics offer insights for self-improvement, while external analytics enable industry and competitive benchmarking. Verifiable credentials establish digital trust and streamline verification processes, while GenAI enhances students’ learning experiences.
Embracing these advanced data-driven strategies enables institutions not only to maintain competitiveness but also to deliver unparalleled value and innovation in education, ultimately driving growth and revenue.
Reach out to our team today to learn more about how data analytics can benefit and increase revenue for your business.
What Can We Do For You Today?
Whether you are looking to transform your business, have questions about our solution, or curious to explore new use cases with verifiable information, we are always happy to chat!