ASPIRATION
Literature Adaptation Mentorship Program

ASPIRATION Mentorship Program
AI-Guided Scientist-Mentored Primary Literature Adaptation for STEMM Education (ASPIRATION)

Join as a Mentor (complete this form here)

We are building a vibrant community of mentors who are passionate about inspiring the next generation of thinkers and innovators—high school students.

We warmly invite scientists, PhD students, medical students, postdocs, physicians, and professionals at all career stages to join us as mentors in the ASPIRATION Program.

As a mentor, you will play a meaningful role in shaping how high school students engage with real science—helping them move beyond textbooks to explore, interpret, and communicate scientific discoveries in clear, accessible, and creative ways.

Mentor Role:

• Guide a small group of 3–5 students through a scientific research paper (this may be your own work or a paper you are familiar with)

• Meet with your group weekly (1-2 times virtually) over the 8-week program (June 6 – July 31) at a time convenient for you to support their progress

• Mentor students in developing their final product—an infographic—and help them prepare for a presentation at our scientific symposium based on their adapted article

• Participate in a mentor information session prior to the program start early June

The ASPIRATION leadership team will provide guidance and resources for mentors, along with structured training for students on how to analyze scientific literature and create high-quality final projects.

Program Description

The AI-Guided Scientist-Mentored Primary Literature Adaptation for STEMM Education (ASPIRATION) Program is an 8-week virtual summer research and science communication program designed for high school students interested in science, medicine, and research. The program combines AI-guided tools with one-on-one scientist mentorship to help students learn how to read, interpret, and translate primary scientific literature into clear, accessible multimedia science communication products. 

Through structured training and mentorship, students gain experience in: Scientific literature comprehension, AI-guided tools for simplification and adaptation, Multimedia science communication. 

Please see our publication describing the development of this program. 

Key dates and information

Application deadline:                                 April 10, 2026
Selected students will be notified by:       April 19, 2026
Registration Deadline if selected:             May 5, 2026
Program Dates:                                           June 6 - July 31, 2026
Location:         Virtual
Estimate time per week:                            10-20 hours, zoom meetings with mentors once or twice a week plus self-study remotely.
Estimate meeting schedule: Scheduled after 5 PM on weekdays or on Saturdays. 

Symposium Participation

All students complete the program with a polished final product will have the opportunity (if elect to do so) to present their work at the end-of-summer High School Student Symposium.

Symposium day:  August 8, Saturday, University of Houston 

Application Process and Program Expectations for Students

Students apply to the ASPIRATION Program through an application process. Selected students participate in structured small group virtual training and mentorship. 

Program Expectations:

Time Commitment: ~10–20 hours per week, require full commitment

Weekly 1–2 Zoom meetings with mentors

Independent study and project development (remote)

Students are expected to participate fully throughout the program. Repeated absences or lack of communication with mentors may result in not being listed as a co-author on the final simplified paper and/or not participating in the final presentation. 

Additional Details: 

Mentoring & Literature Adaptation

Each selected student is paired with a group of students and a scientist mentor and will:

• Learn how to read and interpret a selected primary research article. 

• Use AI-supported tools to clarify complex scientific concepts

• Adapt scientific publications into simplified, student-friendly content

• Create a science communication product with simplified figures.

• Tailor content for audiences with varying literacy levels

This collaboration models how AI and human expertise work together to improve science communication for education and public outreach.