# Designing and Running a Direct Admissions Program > Higher Education · ibl.ai > Source: https://ibl.ai/courses/higher-education/direct-admissions-program > Last updated: 2026-11-14 *From data you hold to an enrollment* **A higher education course from ibl.ai (self-paced, 10 to 12 hours, free).** Design and run a direct admissions program: eligibility rules, data, offer messaging, yield and evaluation, grounded in Idaho, Common App and RCT evidence. - **Price:** Free - **Format:** Self-paced, online - **Time:** 10 to 12 hours - **Pace:** 3 hours per week - **Level:** Intermediate - **Language:** English - **Subject:** Enrollment [Enroll](https://lms.ibl.ai/platform/highereducation/courses/course-v1:highereducation+direct-admissions-program+self-paced) ## Course description A direct admissions program admits students before they apply, using data the institution or state already holds, and then does the harder work of turning an unrequested offer into an enrollment. This course is for the people who have to design and run one. It covers eligibility rules, data sourcing and staffing, the offer itself, the post-offer yield sequence, and an evaluation plan that can tell you whether the program moved enrollment or only applications. The evidence is taken seriously: Idaho's statewide system raised first-time enrollment by an estimated 4 to 8 percent, concentrated at community colleges, while a four-state randomized trial raised applications by 2.7 percentage points and found no enrollment gain. The timing is right. Common App's program grows to 234 institutions for 2026-27, state programs keep expanding, and admissions offices are being asked to run these programs on flat budgets. You will leave with a charter, a rule sheet, an offer letter, a yield playbook and a measurement plan you can put in front of your provost. ### About this course A direct admissions program admits students before they apply, using data the institution or state already holds, and then does the harder work of turning an unrequested offer into an enrollment. This course is for the people who have to design and run one. It covers eligibility rules, data sourcing and staffing, the offer itself, the post-offer yield sequence, and an evaluation plan that can tell you whether the program moved enrollment or only applications. The evidence is taken seriously: Idaho's statewide system raised first-time enrollment by an estimated 4 to 8 percent, concentrated at community colleges, while a four-state randomized trial raised applications by 2.7 percentage points and found no enrollment gain. The timing is right. Common App's program grows to 234 institutions for 2026-27, state programs keep expanding, and admissions offices are being asked to run these programs on flat budgets. You will leave with a charter, a rule sheet, an offer letter, a yield playbook and a measurement plan you can put in front of your provost. ### What you will be able to do - Explain the difference between the application effect and the enrollment effect of direct admissions, citing the Idaho estimate (+4 to 8 percent first-time enrollment) and the four-state RCT result (+2.7 percentage points in applications, no enrollment gain). - Write a program charter that names the data source, the eligibility criteria, the owning work group and the staffing plan, following the SHEEO panel's lessons. - Encode eligibility criteria as explicit, testable rules and validate them against a sample student file with zero ambiguous cases. - Draft a compliant, plain-language offer letter and a post-offer yield sequence with a defined owner and cadence for each step. - Design an evaluation that can detect an enrollment effect, including a comparison group and pre-registered outcome metrics. - Configure and critique an AI agent that drafts post-offer outreach from a sample admitted-student file, and state what it may and may not do without a human. ### Who this course is for **Roles:** admissions directors and VPs of enrollment; system-office and state-agency staff who run or fund statewide programs; institutional research and data staff who supply the eligibility files; CRM and communications leads who own the post-offer sequence. **Institutions:** public universities and community colleges in or considering a state program; private institutions in the Common App direct admissions program; state higher-education agencies and systems. **Before you start:** working knowledge of an admissions funnel (inquiry, application, admit, deposit, enroll) and of where your applicant and admitted-student data lives. No statistics beyond reading a percentage-point difference. No coding. ### Format - Estimated time: 10 to 12 hours. - Level: intermediate practitioner. - Hands-on: one eligibility-rules worked example on a sample file, one AI-agent lab that drafts post-offer outreach from a sample admitted-student file, three templates (charter and rule sheet, offer letter, evaluation plan), two discussions, and a capstone. - Structure: 4 sections, each ending in an AI conversation assessment, then a capstone assessment. Self-paced. Every lesson is taught by an AI tutor that opens with a short story and works through one idea and one question at a time. Each section ends with an AI conversation assessment, and the course closes with a capstone assessment. Section assessments count for 60% and the capstone for 40%; 70% passes. There are no multiple-choice quizzes. ## Outline ### Section 0 · Start here - 0.1 Orientation ### Section 1 · What direct admissions is and what the evidence says - 1.1 The model and where it runs - 1.2 What the research shows - 1.3 Section 1 assessment ### Section 2 · Designing the program - 2.1 Governance, eligibility and the rule sheet - 2.2 Data sources and staffing - 2.3 The offer - 2.4 Section 2 assessment ### Section 3 · Running the program from offer to enrollment - 3.1 The yield sequence - 3.2 Affordability and the students the offer does not reach - 3.3 Section 3 assessment ### Section 4 · Measuring and improving the program - 4.1 Evaluation design - 4.2 Reporting and iteration - 4.3 Section 4 assessment ### Section 5 · Capstone & wrap-up - 5.1 Capstone - 5.2 Capstone assessment - 5.3 Wrap-up ## Instructors - ibl.ai Higher Education, Course team (ibl.ai) ## More higher education courses - [AI in Enrollment Management: Yield, Summer Melt and Admit-to-Enroll Outreach](https://ibl.ai/courses/higher-education/ai-enrollment-yield-and-summer-melt) - [ADA Title II Digital Accessibility for Course Content: The 2027 Deadline](https://ibl.ai/courses/higher-education/ada-title-ii-course-accessibility) - [AI Academic Advising at Scale: Caseload Triage, Proactive Outreach and Human Handoffs](https://ibl.ai/courses/higher-education/ai-academic-advising-caseload-management) - [AI Agents Inside the Trusted Research Environment: Sandboxed Code Execution on NIH, CUI and DUA-Governed Data](https://ibl.ai/courses/higher-education/ai-agents-trusted-research-environment)