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The Impact of Generative and Predictive AI on Higher Education: Revolutionizing Administration, and Student Success and Student and Faculty Satisfaction

Generative and Predictive AI continues to emerge as a transformative force across multiple sectors, including higher education. With its ability to understand, learn, and create content, AI offers powerful solutions to streamline administrative processes, boost student success, and improve student and faculty satisfaction. 

Optimizing Administrative Operations

Higher education institutions manage a wide range of administrative tasks, often leading to inefficiencies. AI can automate many of these processes—such as scheduling, data analysis, and report creation. For example, AI solutions can: 

This automation not only alleviates administrative workloads but also enhances the speed and accuracy of decision-making.

Student and Faculty Satisfaction

AI can automate and optimize an institution’s course catalog, resulting in improved student and faculty satisfaction. As a result, Gen AI is capable of:

  • Generating and updating course descriptions, prerequisites, and availability
  • Analyzing students’ academic history and interests to recommend courses
  • Chatbots to answer questions and assist with course selection
  • Optimizing course scheduling by analyzing faculty availability and room capacity
  • Managing real-time catalog updates, tracking changes, and maintaining version control
  • Translating the catalog into multiple languages
  • Forecasting course demand based on enrollment patterns

Supporting Student Success

Improving student success through one-to-one support and early interventions is a key factor to success and retention. Predictive analytics leveraging AI can:

  • Identify at-risk students based on factors such as attendance, grades, and engagement
  • Early detection allows institutions to implement targeted interventions—such as tutoring or counseling—leading to higher retention rates and greater student satisfaction

Conclusion

In conclusion, Generative and Predictive AI continue to rapidly transform higher education by enhancing administrative efficiency, student success, and overall satisfaction for both students and faculty. By automating tasks, optimizing course offerings, and providing early intervention for at-risk students, AI-driven solutions streamline institutional processes while improving academic outcomes.

As AI continues to evolve, its role in higher education will only deepen, allowing institutions to operate more effectively, enhance student experiences, and ultimately support the achievement of educational goals on a broader scale.

If you want to learn more about Generative and Predictive AI, Datatelligent now offers a cost-effective training course specifically designed for higher education.

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Blog Higher Education Industry Snowflake

Unified Cloud Data Platform in Just 90-Days

Unified Cloud Data Platform in Just 90-Days

INTRODUCTION

In today’s data-informed landscape, educational institutions face a dual challenge. They must manage vast amounts of information while ensuring seamless access and security. The promise of a unified cloud data platform—a centralized hub for data storage, processing, and analytics—holds immense potential. But can it truly be deployed within a tight 90-day window?

This article delves into the intricacies of integrating a unified cloud data platform specifically tailored for higher education. We’ll explore the critical components, address common roadblocks, and provide a roadmap to success. IT administrators, data scientists, and academic leaders must understand the nuances of this transformational journey to ensure a successful implementation.

So, fasten your seatbelt as we embark on a 90-day adventure—a sprint toward data unification that promises efficiency, insights, and a competitive edge. Let’s explore how proper planning, strategic execution, and collaboration can make this ambitious goal a reality.

ASSESS AND PLAN

First, meet with the key academic, administrative, and IT stakeholders and rank-order their priorities, needs, and desired outcomes. For example, one goal may be to improve student retention by 15%. You would then determine the data and data sets required to track each student’s retention.

SPONSORSHIP FROM THE LEADERSHIP AND FUNDING

Once the priorities and desired outcomes have been determined (e.g., improved student retention, analysis of the admission funnel to improve enrollment, a better understanding of enrollment, prediction of when a faculty member or advisor should engage with an at-risk student, etc.), sponsorship will be a critical success factor in this initiative. Most data initiatives fail partly due to a lack of leadership support; enlisting operational leaders to champion the project will help smooth over any obstacles you may face during the project, including obtaining the necessary funds. After you secure funding for the 90-day project, consider requesting funding for the nine months remaining in the year to develop the analytic solutions that will deliver the desired outcomes. Obtaining funding for the full 12 months is ideal to avoid going back to the well for additional dollars.

SET UP THE DATA PIPELINES AND THE CLOUD DATA PLATFORM
Next, select the tools and technologies needed to integrate the data and build the data platform. For data pipeline tools, consider Azure Data Factory and Logic Apps, which work well with student information systems (SIS) platforms such as Banner, Jenzabar, Workday, Colleague, Slate, and PowerFAIDS. These tools are also compatible with learning management systems (LMS) like Canvas, Blackboard, and Moodle, and data stored in operational data stores (ODS), Excel, and SharePoint. These platforms accommodate diverse data sources, including dining hall swipe data, to determine if students are socially connected. Third-party sources such as National Student Clearinghouse, IPEDS, student surveys, faculty evaluations, Google Analytics, and social data for recruitment channel analysis can also be integrated.
 
The number of data sources is not limited, but keep in mind that the goal is to have the data lake live in 90 days, so you will want to limit the number of data sources in this initial 90-day period.
 
For the cloud data platform, consider Snowflake. It works great with Tableau and Power BI because you can get insights from data sets of all sizes. Additionally, Snowflake’s pay-as-you-go model means you only pay for the storage and compute that you use, making it very cost-effective compared to traditional data warehouses.
 
SET UP THE DATA LAKE IN THE CLOUD PLATFORM

Once the tools are connected, set up the data lake in the cloud data platform. To meet your 90-day goal and desired outcomes, take only the necessary tables from the SIS, LMS, CRM, etc., to deliver the desired analytic outcomes. Once the data is in the data lake, you can now perform data transformations, creating the datasets that will drive your analytic solutions.

RESULTS, VALUES, AND ACCEPTANCE

As you approach the 90-day initiative’s conclusion, reconnecting with the stakeholders and leadership to share the results is crucial. Here’s a summary of the key achievements:

  • Successful Setup
    • Data Pipelines: Establish robust data pipelines.
    • Cloud Data Platform: Implemented a scalable cloud data platform.
    • Data Lake: Created a centralized data lake.
  • Data Integration:
    • Connected 2-3 key data sources,
    • Configured data pipelines to automatically refresh the data lake regularly.
  • Centralized Repository:
    • Developed a single data lake repository for the centralization and collection of data.
  • Preparation for Analytics:
    • Prepared datasets with predefined key metrics that will automatically feed into analytics solutions in the next phase (e.g., admissions funnel, enrollment trends, at-risk students, student success, etc.) running in Tableau or Power BI.

Sharing these accomplishments not only highlights the progress made but also sets the stage for the next phase of development. This will ensure continued momentum and support from leadership and stakeholders.

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Blog Higher Education Student Retention

How a Customer Service Approach Can Drive Student Success

How a Customer Service Approach Can Drive Student Success

I had the opportunity to attend Educause’s 2022 annual conference, which brought together IT leaders, technology professionals, and campus stakeholders in the higher education community. I was overwhelmed with the amount of excitement, ingenuity, and creativity on hand—whether in the breakout sessions, panel discussions, or hallway conversations and meetings, I came out of the conference energized and ready to tackle 2023.

But what has gotten me so excited? It’s the untapped opportunity we have to harness data to improve student retention, academic success, student financial health, student LMS engagement, and learning outcomes.

And there was one statement that kickstarted this train of thought:

During a panel discussion, one of the speakers stated that early in the semester, a large number of their students had not even been to class. Many hadn’t even been to the cafeteria.

What does this say about student success? Or their journey?

It brought me back to some ideas that have been on my mind. We need to start applying the lessons learned in other industries to our work in higher education.

I spent a big part of my career working with financial institutions. The number one topic is always customer retention: understanding a customer’s journey within the financial institution, working to retain them, and knowing the triggers that might cause them to leave.

The way to help hold on to that customer is by making your relationship more sticky, which can be accomplished by:

  • Establishing a solid relationship with that customer and helping with their financial needs
  • Cross-selling to that customer. The more services you provide, the less likely they are to leave.
  • Understanding not only the individual customer but their whole household

When I think about the word retention in higher education, I see parallels from other industries. And I see opportunities to apply those learnings in new and innovative ways using data.

I see retention as the byproduct of student success. If we better support the student’s journey from the point of enrollment, their persistence/retention is far more likely.

Having a data-first approach is essential to making this a reality. Colleges and universities that have built a solid data analytics foundation are able to better understand the student journey by stitching together data from disparate systems. This unification of data helps identify broad macro trends and also addresses student needs at the individual level. They are able to pinpoint early warning signs and begin intervention efforts to address issues before they are catastrophic.

For example, we at Datatelligent have been working with numerous colleges and universities to develop Student Success & Retention Solutions that integrate data from throughout the institution — academics, housing, student financial health, etc. — and help identify at-risk students. The solution’s dashboards are highly visual and easy to use, allowing advisors and other staff members quick and efficient access to information essential to improving student success.

These analytics dashboards empower staff to intervene at the student level and help them identify broader trends or issues. School administration is now armed with the information they need to make data-driven decisions, can spend less time cobbling together reports, and can allocate their time to improving the student experience at their schools.

Learn more about Datatelligent’s Student Success & Retention offerings and see how our clients are using this custom solution to identify and retain at-risk students. 

 Visit www.datatelligent.ai for more information on our higher education offerings and learn how our clients are becoming data-driven.

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Blog Events & Webinars Higher Education Other

6 Takeaways from the 2022 AIR Forum Conference

6 Takeaways From The 2022 AIR Forum Conference

A team from Datatelligent ascended on Phoenix for the 2022 AIR Forum Conference, the first in-person event for us since 2019. Bringing together higher education professionals, specifically institution researchers, with data and analytics leaders, AIR Forum was well attended and full of energy. 

The conference also allowed us to reflect on the current and future state of data across the higher education space based on the sessions we attended and the meeting and discussions we had with leaders. With that, here are our top 6 takeaways from 2022 AIR Forum.  

1. It was Great to be Back in Person 

Conference attendees, myself included, were excited to see one other, to share ideas, and to catch up. AIR Forum provided opportunities for networking, brainstorming, and problem-solving.  

The coffee shop in the convention center was a regular hot-bed of connections and conversations, and it served as a good reminder that connecting face-to-face is an unparalleled experience.  Virtual conferences have proven to be extremely effective when it comes to delivering great content, but I think we can all agree that nothing replaces those spontaneous hallway discussions. It sure was  great to be back in person!  

2. Data Literacy & Maturity are Critical 

Data literacy is the ability to explore, understand, communicate and tell stories with data.  

The good news is that from the discussion we had at AIR Forum, higher education institutions truly understand that data is the ultimate differentiator and that data literacy is the key to unlocking the value of your data and technology investments.  

Understanding your institution’s data maturity in terms of your data and analytics vision, as well as your data sources and KPIs, is critical to advancing your maturity.  

We met with several leaders and discussed data maturity. Through this, we learned that there is a wide spectrum across organizations, ranging from data aware to data proficient and then further up the spectrum to data savvy and ultimately data driven. 

3. There’s a Severe Data Staffing Challenge… and Options 

We can all agree that it’s difficult trying to find the right talent for the job, regardless of the job. But when you add in the need for specialized data skills, the challenge becomes even more cumbersome. On top of that, as we potentially head into a global recession, the outlook becomes grim. 

It’s not surprising that we heard from several higher education leaders who said they were actively looking to get creative and “future-proof” their workforce in the face of: 

  • Not being able to hire due to a shortage of data workers  
  • Declining retention due to employee turnover  
  • Economic uncertainty in the face of a possible recession 
  • Inability to keep good talent due to the high demand for highly skilled data workers

One way to circumvent the hiring challenge was to actually not hire directly. Instead of hiring, leading higher education institutions that are looking to reduce risk while also increasing efficiency are turning to Datatelligent’s Data Analytics as Service (DAaaS) model, an alternative option to staffing and building your data team. 

For the cost of just one senior data architect, with our DAaaS model, you can get a whole team to support your data needs—from solutions, strategy, to detailed expertise. We bring use of our leading-edge solutions to help grow your business—all under one unique subscription as a service solution. 

4. Virtualization was Everywhere 

For institutions looking for a new way to combine data from different sources that make it easier to access, understand and share across your organization, conference attendees didn’t have to look far. Virtualization was everywhere. 

There were several sessions about virtualization and how to easily connect to data stored anywhere, in any format. Our technology partner, Tableau, was on hand at AIR Forum sharing how they can help institutions quickly perform ad hoc analyses that reveal hidden opportunities using drag and drop functionality to create interactive dashboards with advanced visual analytics. If you have questions about virtualization, let me know. I can help.  

5. The Future for Data Inclusion & Equity is Now 

For data solutions to be relevant and sustainable, they must be designed in collaboration with the communities they are intended to represent and support.  

We are seeing organizations be intentional about their data. From what we saw at AIR Forum and the meetings that we continue to have, I think that higher education institutions are on the precipice of ensuring data is more inclusive, representative, and effective. In fact, viewing data as a strategic asset and committing to an organizational culture of data inclusion can lead to discussions about policies and how higher education institutions can and should invest in their communities into the future.   

6. Student Recruitment, Retention & Success was a Hot Topic 

Did you attend our session at AIR Forum? Titled “How Tableau Can You Go? Increasing Data Access for Decision-Making,” our own Larry Blackburn, Chief Solutions Officer, was joined by Deborah Phelps, Executive Director of Institutional Effectiveness at Cowley College during a session at AIR Forum. They shared how Cowley College has dramatically improved student recruitment and retention by successfully evaluating and reimagining their data analytics infrastructure to become a more data-driven organization. They also reviewed Cowley’s implementation of Tableau, a data visualization application.  

If you missed our session at AIR Forum and would like a copy of the presentation slides, just email me. I’d also be happy to review the presentation with you detailing what we did to improve student success at Cowley College. 

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Impact of Generative and Predictive AI
Blog

The Impact of Generative and Predictive AI on Higher Education: Revolutionizing Administration, and Student Success and Student and Faculty Satisfaction

This article highlights the profound influence of generative and predictive AI on higher education. It discusses how these technologies are streamlining administrative tasks, enhancing student success through early interventions, and improving overall satisfaction for both students and faculty. Institutions are leveraging AI for better decision-making, personalized learning experiences, and optimized course offerings, all of which contribute to a more efficient and effective educational environment.

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