5 Ways AI Will Transform Scholarship Management in 2024

Webinar recap/recording

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5 Ways AI Will Transform Scholarship Management in 2024

On November 30, 2022, OpenAI (ChatGPT) changed the game for scholarship providers forever.


Before this date – scholarship providers relied on scholarship essays and personal storytelling to separate scholarship applicants from raw metrics such as test scores and academic accolades. They were a way for students to showcase their unique qualities and personalities – separating them from the thousands of other applicants in the competitive scholarship ecosystem.


So what happened on November 30th? OpenAI released an early demo of ChatGPT resulting in the A.I. chatbot going mainstream. Instagram and TikTok were flooded with people recording innovative ways to leverage ChatGPT to streamline tedious tasks such as travel planning, writing computer code, and more. Google search trends went crazy.


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Fast forward less than 2 years and scholarship providers are now facing challenges never seen before – A.I. generated scholarship applications and essays. What was once a way to separate qualified applicants from a crowded room of other qualified applicants for limited resources is now a game of cat and mouse to identify authenticity. And while we are 17 months removed from the introduction of ChatGPT – we are only at the precedent of how A.I. will impact scholarships in the coming years. This Google search trend looks awfully familiar.


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Understanding A.I. and its Current Impact on Scholarship Management

Artificial Intelligence (A.I.) operates by analyzing large amounts of data and learning from patterns to make decisions or generate content. Scholarship applicants frequently use A.I. for writing by inputting prompts or topics, allowing the A.I. to assist in structuring essays or solely writing them for the applicant. In recent research amongst scholarship providers, we have identified a significant concern of scholarship essays being written with the assistance of A.I. tools like ChatGPT. This research highlights a growing reliance on A.I. for enhancing the quality of submissions, although there is a crucial distinction to be made between using A.I. as a supportive framework versus having it generate content from scratch. 

So, what does the current state of A.I. utilization look like in scholarships?

Ok, so scholarship applicants copy and pasting essay prompts into tools such as ChatGPT and using the results as their own work is probably not what scholarship providers are looking for. But in what ways can A.I. be leveraged for good in scholarship management?

The 5 Ways AI Will Transform Scholarship Management in 2024

Graphic from the webinar, 5 ways A.I. will transform scholarship management in 2024. This image shows where we are currently at with A.I. being used in scholarships and where the future looks like.

1. Intelligent Automation

Scholarship recommendation and matching

Scholarship providers offer scholarships with a wide range of criteria, eligibility, and requirements. Often, applicants may not be aware of the opportunities available to them resulting in unfunded scholarships or applicants applying for everything, and anything, resulting in wasted time and energy from both the applicant and the scholarship provider.

  • Leverage scholarship recommendation and matching tools that based on data provided by the scholarship applicant, presents scholarship opportunities that align.
  • Conduct real-time eligibility and requirement checks bases on content submitted by the scholarship applicant.
    • Scholars that are not eligibility no longer waste time and energy submitting for an opportunity they are ineligible for.
    • Scholarship providers no longer waste time and energy vetting applications that should not be included.
Create a personalized experience

Capturing essential information from scholarship applicants equips scholarship providers with the data necessary to create a personalized experience that enhances the applicant experience and strengthens data integrity.

  • When an applicant goes through the scholarship recommendation and matching process we can begin crafting custom questions relevant to the scholarship opportunity.
  • Example: A scholarship applicant pursuing a path in surgical oncology may have different application questions, deliverables, deadlines, and review committees than an applicant applying for a career in the arts.
Eligibility screening and qualification

In a world of competitive scholarships, program managers and scholarship providers are looking for ways to narrow down the initial applicant pool to a smaller number for a more indepth and thorough review.

  • Automatically allow candidates to proceed, or not, based on program eligibility. This ensures only those that match the scholarship requirement may proceed.
  • Set clear requirements for deliverables and only allow completed applications to proceed that have those deliverables added.
    • Allow candidates to access scholarship information, add deliverables, and return as often as they desire before fully submitting.
    • Once ready to submit, check for completion preventing anyone that is missing a requirement from entering the completed que.
  • Auto-rank candidates based on applicant profile information such as GPA, volunteer hours, etc.

Reviewr’s intelligent automation in action

Intelligent Automation

2. Enhanced Content Creation

While leveraging A.I. to completely write essays or personal stories is advised against – using A.I. to assist with generating content that empowers the applicant be the best version of themselves and position themselves for success is promoted.

Empower creation, not duplication
  • A.I. can be used for Idea generation.
  • Assist candidates in creating the best scholarship content as possible.
  • Create a framework for personalization.
  • Provide spell check, grammar suggestions, and structure.
Lower the barrier – increasing application rates
    • Scholarship applicants WILL utilize A.I. to assist with content creation.
      • Provide a structured and controlled environment.
      • This creates an even playing field for scholarship applicants to share the same resources.
      • Increase application rates by eliminating “writers block”.
      • Enhance the quality scholarship applications and essays.
Carryover data for multiple opportunities
  • Reduce the redundant nature of scholarship applications where things like personal information, grades, etc do not change from one scholarship opportunity to another.
  • Carry over scholarship applicant data and only require them to submit the unique data requirements for that particular opportunity.
Mock Interviews
  • Personal interviews are going to play a critical role in scholarship workflows with the rise of A.I. assisted scholarship applications. The only way to measure true authenticity is human interaction.
    • Create an environment of success for applicants by providing A.I. driven mock interviews.
    • Tools such as Final Round AI can be leveraged to create interview prompts as well as practice responses that impact follow up questions. Final Round AI: Interview Copilot


3. AI and Plagiarism Content Detection

Finally, the elephant in the room. We know scholarship applicants WILL A.I. to assist with their scholarship content creation. We also are PROMOTING the usage of A.I. to help generate the framework for a well structured scholarship application and essay – so where do we draw the line? How much A.I. is too much? 

Ultimately, this is a decision and question scholarship providers must ask themselves. Here are some themes to consider:

  • Allowing applicants to leverage A.I. to build the framework of a personalized essay is ok.
  • An argument can be made that the applicant’s ability to leverage A.I. and modify prompts to craft a personalized response should be awarded – this is what the future workforce looks like anyways.
  • 100% A.I. generated or plagiarized content is grounds for dismissal.

So, what can we do to better identify the utilization of A.I. generated content and plagiarized material? Reviewr is excited to announce “Sidekick”, an integrated A.I./plagiarism detection tool for scholarships powered by Reviewr.

Sidekick is intended to flag applicants for scholarship providers and provide them the resources needed to make data driven decisions.

Detects what percentage of scholarship content is A.I. generated.

    • Detects what percentage of content was plagiarized 
    • Can view what percentage was used on a per-question basis.
    • Organizations can view what is plagiarized and the source it came from 
  • Ex: if the applicant pulled sentences from Wikipedia.com you can see which sentences and the exact article they took the writing from.

See a teaser of “Sidekick” in action.

See Sidekick A.I. in Action

4. Streamline Administrative Workflows

Artificial intelligence streamlines administrative workflows by automating routine tasks and optimizing data management. This enhances efficiency and accuracy, empowering scholarship providers to spend less energy managing, and more energy making an impact.

Auto-group and categorize entries 
  • Leverage intelligent automation to read scholarship applications and categorize them.
    • Scholarship opportunity
    • Theme
    • Location
    • Much more.
Summarize application content
  • Seamless initial vetting with condensed applications into summarized format. 
  • Create an applicant synopsis to be used to compare to other scholarship applicants.
  • From here, narrow the applicant pool to a more manageable number for more in depth review and selection.
  • This should be stated in the proof of process so all applicants know how they are being evaluated.


5. Ensuring a fair, non-biased Selection

At it’s core, Reviewr was developed to not only streamline administrative scholarship management efforts, but more importantly, enhance the experience for both applicants and review teams. This means ensuring each applicant gets the fair change they deserve by eliminating potential bias reviews and unstructured review workflows. Gone are the days of applicants landing in spam and not getting included in the review or being unfairly evaluated based on personal bias.

Matching judges with applicants for evaluation
  • Group applicants based on the judge’s expertise and matched interests with applicants.
  • Randomly distribute scholarship applicants to review teams.
    • Ensure compliant review and selection with randomization.
    • Reduce review team workload limits by only allocating a manageable number of of submissions to review.
    • Stay compliant with proof of process.
  • Auto redact personal information from the scholarship application from the review teams view to avoid any personal bias.
Tabulate the selection
  • Auto allocate point values to an applicants profile by pulling content from the application form that matches desired scholar requirements.
    • Example, assign point values for hitting specific GPA or volunteer hour thresholds.
  • Seamless online review and selection rubrics.
  • Auto tabulate results eliminating human error and the need for “crunching numbers”.
  • Real-time “leaderboards” track progress and results.
Normalization of results 

Another component of “Sidekick” – Evaluation Normalization.

I love the show Shark Tank and “Mr Wonderful” is easily my favorite shark. But what if the entrepreneurs pitching their business ideas got judged by different judges than one another? For example, what if I landed Mr Wonderful but someone else got Barbara? What if the scorecards they used were on a scale of 1-30 and Mr. Wonderful gave me a 19 and Barbara gave someone a 30? What if Mr. Wonderful never gives a 20 – does that make getting a 19 bad? If the show used total and average scores than anyone that Mr. Wonderful scored would naturally be lower in the rankings – is this fair?

Introducing “Evaluation Normalization” This. Is. Big.

  • Did we mention this is big?
  • Reviewr is excited to introduce “Normalized evaluation reporting”
    • Identify judges/reviewers who score on a stricter (or easier) scale than others.
    • Normalize the results to account for a judges particular evaluating habits.
    • Level the playing field for applicants by creating a fair baseline.
    • Identify each judges average score.
    • Set the baseline as 1.
    • If a judge evaluates someone higher than 1, it was better than their average.
    • If a judge evaluates lower than a 1, it was lower than their average score.
    • Take this new normalized average for decision making.
Intelligent Automation


“Hey Sidekick, how’d we do”?

Screenshot 2024 05 02 at 1.50.28 PM

Not too shabby. The landscape of scholarship management is rapidly evolving with the integration of AI technologies. As demonstrated, AI brings about transformative changes across various aspects of scholarship management, from intelligent automation to enhanced content creation, plagiarism detection, streamlined administrative workflows, and ensuring fair, non-biased selection processes.

The utilization of AI in scholarship management introduces efficiency and accuracy by automating routine tasks, matching applicants with relevant opportunities, and facilitating personalized experiences. Moreover, AI aids in content creation by empowering applicants to generate high-quality submissions while mitigating the risk of plagiarism through innovative detention methods.

Furthermore, AI-driven systems streamline administrative workflows by categorizing and summarizing applications, ensuring fair evaluations by matching judges with applicants, and normalizing evaluation results to eliminate bias. These advancements not only enhance the efficiency of scholarship management but also uphold fairness and integrity in the selection process.

As we embrace the future of scholarship management in 2024, it becomes evident that AI will continue to play a pivotal role in revolutionizing how scholarships are administered, ensuring equitable opportunities for all deserving applicants while optimizing resource allocation for scholarship providers.

Bonus: If you’re interested in using “Sidekick” sign up for our waitlist and preview the tool. By signing up you are not obligated to using Reviewr, but you will be locked into the current pricing model before changes are made in the coming months.

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