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For Counselors: Admission Intelligence FAQ
We're excited to share Admission Intelligence to all Scoir customers. 🚀
Admission Intelligence—or, as we like to call it, Scoir AI—are data-informed tools to help balance college lists and demystify acceptance chances, powered by tens of millions of de-identified outcome records.
Here are a few tools you can now access:
Balanced List Scores: Streamline the creation and evaluation of college lists, quickly identify students in need of support, and effectively track their progress from early list building to application planning. Learn more
Intelligent Match: Save time and set personalized acceptance likelihood at scale for all students and colleges with Intelligent Match. Learn more
Predictive Chances: Beyond Scattergrams, you'll be able to view predicted outcomes based on tens of millions of de-identified application records from real, validated students on the Scoir network. Learn more
Now, let's dive into your questions.
General Questions
What is Admission Intelligence?
Admission Intelligence—or, as we like to call it, Scoir AI—are data-informed tools to help balance college lists and demystify acceptance chances, powered by tens of millions of de-identified outcome records.
Scoir AI does the time-consuming, manual aspect of data collection and initial analysis for you by compiling mountains of verified data for you, providing real-time insights tailored to each student’s unique academic profile.
It's designed to bring clarity and confidence to acceptance chances by providing credible, predictive insights inside the platform you're already using to support informed decision-making.
Balanced List Scores: Streamline the creation and evaluation of college lists, quickly identify students in need of support, and effectively track their progress from early list building to application planning.
Intelligent Match: Save time and set personalized acceptance likelihood at scale for all students and colleges with Intelligent Match.
Predictive Chances: Beyond Scattergrams, you'll be able to view predicted outcomes based on tens of millions of de-identified application records from real, validated students on the Scoir network.
Scoir AI does the time-consuming, manual aspect of data collection and initial analysis for you by compiling mountains of verified data for you, providing real-time insights tailored to each student’s unique academic profile.
It's designed to bring clarity and confidence to acceptance chances by providing credible, predictive insights inside the platform you're already using to support informed decision-making.
Balanced List Scores: Streamline the creation and evaluation of college lists, quickly identify students in need of support, and effectively track their progress from early list building to application planning.
Intelligent Match: Save time and set personalized acceptance likelihood at scale for all students and colleges with Intelligent Match.
Predictive Chances: Beyond Scattergrams, you'll be able to view predicted outcomes based on tens of millions of de-identified application records from real, validated students on the Scoir network.
Why is Scoir adding AI to the platform?
Students and families often encounter conflicting information from various online sources about their acceptance chances, leading to confusion and uncertainty about which data to trust.
Scoir built Admission Intelligence to bring clarity and confidence to this process and incorporated predictive insights directly within the platform.
With tens of millions of validated outcome records, and a multidimensional modeling approach, Scoir AI empowers counselors with trusted insights to guide families toward informed application strategies and decision-making.
Scoir built Admission Intelligence to bring clarity and confidence to this process and incorporated predictive insights directly within the platform.
With tens of millions of validated outcome records, and a multidimensional modeling approach, Scoir AI empowers counselors with trusted insights to guide families toward informed application strategies and decision-making.
What control do counselors have over when students can use these experiences?
These tools have been designed to fit into your unique processes. You will have the control to define balanced list requirements, and determine when you introduce balanced lists or automate their scoring.
Predictive Chances will be presented alongside Scattergrams in your view. Currently, you have the option to display or hide Predictive Chances to students and parents. However, please note this setting for Predictive Chances is subject to change after an evaluation period.
With customizable settings, you choose when, who, and which class years gain access to these new capabilities, keeping you in control while guiding students and their parents.
Predictive Chances will be presented alongside Scattergrams in your view. Currently, you have the option to display or hide Predictive Chances to students and parents. However, please note this setting for Predictive Chances is subject to change after an evaluation period.
With customizable settings, you choose when, who, and which class years gain access to these new capabilities, keeping you in control while guiding students and their parents.
Has Scoir AI been tested?
Yes. Over 100 high schools have been part of our Early Access program to help test Scoir AI and share feedback.
Counselor feedback has been overwhelmingly positive as they’ve harnessed validated application outcome data from more than just their high school, but from millions of similar de-identified students, helping make college list building and management more efficient.
We’ve loved hearing how our early adopters found best practices to fit their school’s needs, and can’t wait to hear how you all leverage these enhancements as well!
Counselor feedback has been overwhelmingly positive as they’ve harnessed validated application outcome data from more than just their high school, but from millions of similar de-identified students, helping make college list building and management more efficient.
We’ve loved hearing how our early adopters found best practices to fit their school’s needs, and can’t wait to hear how you all leverage these enhancements as well!
What's the best way to get started with Scoir AI?
We encourage you to the review the blog For Counselors: Introducing Admission Intelligence to get a lay of the land.
Once you have a better understanding of the tools you can now access, you can begin by configuring your settings and familiarizing yourself with the tools.
Once you have a better understanding of the tools you can now access, you can begin by configuring your settings and familiarizing yourself with the tools.
Can I opt out of Admission Intelligence?
We’ve customized the experience in a way that you can learn and implement these tools at a pace that works for you and doesn’t disrupt your workflow, so there’s no need to opt out.
If you’d like to start implementing the tools as soon as they’re released, you can! But, if you want to hold on utilizing Scoir AI until you have more time to explore and learn, you have that option as well.
If you’d like to start implementing the tools as soon as they’re released, you can! But, if you want to hold on utilizing Scoir AI until you have more time to explore and learn, you have that option as well.
How do I leave feedback?
We encourage you to leave feedback about the direction we’re taking Admission Intelligence in Scoir, and you don’t have to wait until it’s released. Feel free to share your thoughts about what you’ve learned so far by filling out this form.
Data Questions
What data is driving these predictions?
Tens of millions of de-identified application outcome records from real, validated students across the Scoir network.
How is Scoir protecting student data and privacy?
We continue to protect student PII. The models used to inform Admission Intelligence de-identify the student by stripping any personally identifiable information.
Intelligent Match Questions
What is a student’s “Match Level”?
Match Level represents the selectivity category of schools that are considered a "Level" fit (as opposed to “Reach” or “Likely”) for a given student based on their profile. Match Levels are used to assign an acceptance likelihood by comparing the assigned Match Level to the college’s Selectivity Level.
There are 6 Match Levels, corresponding to college selectivity levels, listed from most to least selective: Most Selective, Highly Selective, Very Selective, Selective, Somewhat Selective, Open Admission.
There are 6 Match Levels, corresponding to college selectivity levels, listed from most to least selective: Most Selective, Highly Selective, Very Selective, Selective, Somewhat Selective, Open Admission.
How does Intelligent Match predict a student’s match level?
Intelligent Match can predict a student’s match level by comparing the student’s profile to historical applicants with similar profiles and the selectivity of schools they were accepted. Counselors do not need to use Scoir AI to predict a student’s Match Level - they have the ability to manually enter Match Level as well.
What is acceptance likelihood?
Acceptance likelihood is a classification of colleges representing the selectivity or competitiveness of that college for each student.
There are 5 acceptance likelihood categories: Far Reach, Reach, Level, Likely, Very Likely. These labels can be adjusted within high school settings.
There are 5 acceptance likelihood categories: Far Reach, Reach, Level, Likely, Very Likely. These labels can be adjusted within high school settings.
How can acceptance likelihood be assigned to a college on a student’s list?
Intelligent Match can automatically calculate acceptance likelihood for all colleges by assigning a Match Level to each student. Alternatively, acceptance likelihood can be manually assigned by a counselor or student (if the high school allows students to do this). Manually assigned values will be preserved over any predictions made by Scoir AI.
Does the model consider individual factors like course selection, rigor or extracurricular activities?
Not yet.
Please note: The adoption of tools like Secondary School Reports will enrich our models’ view of an applicant and afford more comprehensive predictions in the future.
Please note: The adoption of tools like Secondary School Reports will enrich our models’ view of an applicant and afford more comprehensive predictions in the future.
What if I disagree with the predictions from Intelligent Match?
Scoir offers a number of overrides available to allow for individual differences.
1) A student’s academic profile may be more or less competitive than Scoir might predict. In these cases a counselor may choose to override the students Match Level, which will cascade adjustments to the acceptance likelihood for all colleges making them more or less competitive.
2) A student might have a hook for a particular college, influencing the acceptance likelihood for a single school. In such cases, a counselor (or student if configured to allow) may adjust the acceptance likelihood for that individual college.
3) A high school may be a “feeder” school with acceptance trends that deviate from the average.. While Scoir attempts to account for such conditions, a counselor may still choose to adjust the College Selectivity Level, cascading to all students, making it more or less selective.
1) A student’s academic profile may be more or less competitive than Scoir might predict. In these cases a counselor may choose to override the students Match Level, which will cascade adjustments to the acceptance likelihood for all colleges making them more or less competitive.
2) A student might have a hook for a particular college, influencing the acceptance likelihood for a single school. In such cases, a counselor (or student if configured to allow) may adjust the acceptance likelihood for that individual college.
3) A high school may be a “feeder” school with acceptance trends that deviate from the average.. While Scoir attempts to account for such conditions, a counselor may still choose to adjust the College Selectivity Level, cascading to all students, making it more or less selective.
List Score Questions
What is a List Score?
A List Score is a personalized grade for a student's college list allowing counselors to easily identify students with balanced or imbalanced lists. Each student’s List Score is calculated by evaluating the student's college list to ensure it includes an appropriate mix of "Reach," "Level," and "Likely" schools.
Can I adjust “balanced list” requirements?
Yes. Scoir’s default is 2 likely or very likely, 3 level, and 2 reach or far reach schools. The high school may choose to adjust the minimums within each of those three buckets. Learn how
Can I control who sees balanced list scores?
Yes. The high school can choose if and when balanced list experiences are displayed to students and parents. We do encourage that high schools enable the features for all parties and leverage it as an accelerator to build a list, and a tool to inform consultation. Coupled with tasks and assignments, counselors could assign list building tasks to encourage all students to build an A-grade list by a deadline. Learn how
What colleges are included in the list score calculation?
By default, list scores consider colleges in Following, Applying or Applied states, within a student’s My Colleges list.
Can I choose to score just the application list?
Counselors can decide when it’s time to focus on building an application list, at which point the student’s list score will be calculated based on those schools in Applying and Applied states within MyColleges. Learn how
Predictive Chances Questions
How does Scoir derive Predictive Chances?
Scoir has created machine-learning models for a large percentage of colleges based on de-identified historical application records created on Scoir or imported into Scoir as part of the high school onboarding process.
These de-identified records contain a variety of details about each applicant, their school, the round they apply to and the outcomes. When returning Predictive Chances for a student, the model considers details about that student, comparing outcomes for similar students within similar high schools and presents personalized Predictive Chances for each application round currently offered by that college.
These de-identified records contain a variety of details about each applicant, their school, the round they apply to and the outcomes. When returning Predictive Chances for a student, the model considers details about that student, comparing outcomes for similar students within similar high schools and presents personalized Predictive Chances for each application round currently offered by that college.
Are the Predictive Chances unique to my school?
Yes, Scoir’s models prioritize predictions based on your school's historical outcomes, while also considering your school’s type (e.g., public or private) and location to identify similar schools and refine the results.
Do Predictive Chances consider just the GPA and standardized test scores?
No, Scoir’s models use a broad approach that goes beyond academic factors like GPA and test scores. The models also take into account characteristics such as first-generation status, geographic location, race/ethnicity, sex, and high school profile, ensuring a more comprehensive prediction.
Do Predictive Chances consider the student’s location?
Yes, Scoir considers the student’s and college’s location, including in-state and out-of-state admission trends. These trends are not specifically programmed into the model but are a result of analyzing historical outcomes that include the applicant’s state. This approach allows the model to naturally reflect location-based patterns in admissions without relying on preset rules.
Do Predictive Chances consider individual factors like course selection, rigor or extracurricular activities?
Not yet.
Please note: The adoption of tools like Secondary School Reports will enrich our models’ view of an applicant and afford more comprehensive predictions in the future.
Please note: The adoption of tools like Secondary School Reports will enrich our models’ view of an applicant and afford more comprehensive predictions in the future.
What’s the difference between Predictive Chances and Scattergram?
While they’re both outputs of historical outcomes data, Predictive Chances leverages millions of records to offer predicted chances of acceptance based on the outcomes of students with similar profiles. Scattergrams plot only the individual high school’s application outcomes.
Additional Resources
We hope this FAQ was useful in helping you better understand Scoir AI. Here are some additional resources to help manage your account and support students at every stage of their journey.
