HRC1404620 Statement of Work.pdf

80NSSC24HRC1404620

Request for Information

Revised July 16, 2024

Gen AI ILT for NASA’s Glenn Research Center

Sections in this document are listed in the table shown below.

Sections in this Request for Information

Statement of Work Additional Requirements

Background Target Audience

Prerequisite Period of Performance

Objectives Responses

Scope of Work Questionnaire

Deliverables Questions and Answers

Government-Furnished Property Example Scenario

Instructor Requirements Submission Details

Course Structure Terms of Request

The Onsite Training Purchases Team at the NASA Shared Services Center is requesting information from vendors for the following business opportunity:

Statement of Work

NASA’s Glenn Research Center (Glenn) in Cleveland is seeking a qualified vendor to deliver a comprehensive instructor-led-training program on generative AI (Gen AI) for 25 researchers and engineers. This program will leverage a flipped classroom approach to equip participants with the knowledge and skills necessary to utilize Gen AI for tasks such as document summarization, content creation, code assistance, and research support.

Background

The course shall provide introductory training on generative AI, which is AI capable of generating text, images, videos, or other data using generative models, often in response to prompts. Generative AI models learn the patterns and structure of their input training data and then generate new data with similar characteristics.

Prerequisite

Instructors must be well-versed in generative AI. The instructor must have experience facilitating courses using a flipped learning model.

Objectives

Upon completion, students shall have knowledge of the following course topics:

1. Foundations of Generative AI

• Definitions, key concepts, and historical development

• Differences from traditional machine learning

2. Applications and Use Cases

• Applications in art, biology, emotional support, learning, and business

• Real-world business challenges addressed by Gen AI

3. Prompt Engineering

• Basics of prompt engineering and writing effective prompts

• Enhancing productivity with prompt engineering techniques

4. Project Lifecycle

• Overview of developing a generative AI project

• Tools for building Gen AI applications (within NASA restrictions)

5. Ethics and Risks

• Ethical considerations and responsible use

• Compliance and risk management

6. Opportunities and Limitations

• Career enhancement and workplace improvements with Gen AI

• Understanding the potential and limitations of Gen AI

Scope of Work

The course is intended to educate NASA employees interested in using generative AI for their work. Students are not expected to have previous experience with Gen AI.

The course will be delivered in the format of a flipped learning course. The vendor is to provide hands-on work as much as needed and as appropriate.

Deliverables

1. Vendor will deliver course syllabus 2 weeks before training start date.

2. Vendor will deliver course lesson plans before training start date.

3. Vendor will deliver course materials before training start date.

4. Vendor will deliver a list of training tools 4 weeks before training start date.

5. Vendor will deliver a list of instructors 2 weeks before training start date.

6. Vendor will use only course materials that are Section 508 compliant.

7. Vendor will deliver all training sessions before October 30, 2024.

Government-Furnished Property

1. NASA will provide training facility.

2. NASA will provide network access.

3. NASA will provide visual equipment.

4. NASA will provide computers for students.

5. NASA will provide access badge for instructors.

Instructor Requirements

Citizenship: U.S. citizen or permanent resident Team Composition: Minimum of 3 instructors for in-person sessions. One instructor must possess extensive experience and knowledge in the statement of work topics.

This lead instructor should demonstrate:

1. Flipped Learning Expertise: Proven track record of conducting flipped learning classes specifically tailored to the target audience.

2. Gen AI Proficiency: Experience teaching individuals with no prior knowledge of Generative Artificial Intelligence (Gen AI).

3. Public Sector Training: A history of successfully training engineers, scientists, and business personnel within the public sector.

4. Subject Matter Mastery: Deep understanding of the topics covered in the statement of work.

5. Course Content Authority: In-depth knowledge and ability to convey the course material effectively.

Availability: The lead instructor will be remotely available to answer student questions during the breaks between in-person sessions. Open office hours will be held for a minimum of 4 hours per week, from either 10:00 AM to 2:00 PM or 11:00 AM to 3:00 PM Eastern Time (ET). Breaks will be at least 2 but not longer than 3 weeks between in-person sessions.

Course Structure

Flipped Learning Approach: The course will utilize a flipped learning model, where students engage with pre-session work (readings, assignments) followed by in-person sessions focused on reviewing, applying, and solidifying the learned concepts.

In-Person Sessions:

• Minimum Duration: A total of 24 hours will be dedicated to in-person instruction spread across 3-4 facilitated training sessions.

• Focus: Each in-person session will center around reviewing course assignments, assigned reading, and viewing materials

• Facilitate: Engaging discussions to substantiate understanding.

Course Work:

• Workload: The course workload is designed to be manageable, requiring a maximum of 4 hours per week per participant to complete the pre-session work (lessons, problems, and assignments).

• Completion: All course work must be finished before each in-person session to maximize the benefit of the interactive learning environment.

• Materials: The course will provide a comprehensive set of materials, including clear and concise lessons, relevant problems and exercises, challenging assignments with solutions, and real-world, practical examples to ensure hands-on practice with the learned concepts.

Additional Requirement

Instructors must possess excellent communication skills, enabling them to explain complex technical content in a clear, understandable, and relevant manner. This ensures all participants, regardless of their prior knowledge of Gen AI, can effectively grasp the course material and apply it to real-world scenarios.

Target Audience

25 researchers and engineers in a wide variety of disciplines. The vendor can assume that the students will no prior knowledge about generative AI.

Place of Performance

The in-person training sessions will be held at NASA Glenn Research Center.

21000 Brookpark Road Cleveland, OH 44135

Period of Performance

August 1, 2024, through October 30, 2024

The course must be taught anytime between Tuesday, August 1, 2024, and Wednesday, October 30. 2024.

Responses

The following criteria will be considered when reviewing responses:

1. Course outline and curriculum

2. Course schedule and session durations

3. Education and training of instructor

4. Past performance and experience

Questionnaire

1. What experience does the instructor have using Gen AI for science or engineering applications?

2. What experience does the vendor have conducting Gen AI training courses?

3. What is the process for selecting qualified, alternative teachers if a substitute instructor is needed?

4. What experience does the instructor have with facilitating training in a non-academic setting?

5. What platforms and other tools are recommended for assignments and coursework?

6. What datasets are recommended for assignments and coursework?

7. Provide references for previous Gen AI courses that have been taught.

8. Describe experience with teaching in a non-academic setting.

9. What platforms and tools would students use for assignments and course work?

10. Syllabus and course curriculum for previous courses is optional but welcome.

Questions Received from Vendors

Please see the answers shown below in response to questions received via email from an interested vendor on Tuesday, July 16, 2024.

Q1: What is the typical role/background of the 25 attendees for this course (ex.

Admin, researchers, OCIO, MSFC, engineering, etc.)?

The target audience for this training event will include researchers and engineers.

Q2: Does the government expect the 25 attendees would be expected to complete assignments and testing outside of the three 8-hour sessions?

Yes, the program will utilize a flipped classroom model. Coursework will be completed before each in-person session, ensuring participants arrive prepared for discussions and exercises. The coursework should be manageable and no more than 4 hours per week for each participant.

Q3: Does the government expect a grade or pass/fail for the completion of this course?

No, the participants will receive a complete or incomplete which will be determined by the total attendance time. If participants attend 80% or more (i.e., at least 2 sessions), they will receive a learning credit of course completion. If participants attend 79% or less (i.e., one session), they will receive a learning credit of course incompletion.

Q4: Does the government expect a ‘certificate of completion’ provided by the vendor or NASA at the completion of this course?

No, participants will receive a certificate of completion via the agency’s learning management system.

Q5: Is the government open to either a hybrid or virtual training sessions as well? This would support cost efficiencies with respect to travel and allow for increased touchpoints/sessions.

Yes, the government is open to recommendations for a hybrid environment;

however, it is intended that all in-person sessions will be held onsite at Glenn Research Center in Cleveland, OH.

Q6: Does the government have an identified budgetary range for this requirement?

Yes, the budget for this course is less than $25,000.

Q7: Does the government expect the number of attendees to increase beyond 25 attendees? If so, what is the expected maximum number of attendees expected?

No, it is expected that only 25 participants will attend, and the same 25 participants will attend each session.

Example Scenario

A flipped classroom for learning Gen AI fundamentals may look something like this:

Pre-work Session:

• Readings/Videos: Participants might watch pre-recorded lectures or online tutorials explaining core concepts like machine learning, neural networks, and different types of generative models.

• Interactive Exercises: Online platforms could offer interactive exercises where participants experiment with basic Gen AI tools to get a feel for the technology.

• Preparation Questions: The instructor might provide a set of questions encouraging participants to reflect on the pre-session materials and consider how Gen AI relates to their field or interests.

In-person Session:

• Review and Discussion: The instructor would lead a discussion to clarify any confusion about the pre-session material and address student questions.

• Hands-on Activities: Participants could work in groups on practical exercises using Gen AI tools to generate text, images, or code. This allows for exploration, problem-solving, and applying learned concepts.

• Case Studies: The instructor might present real-world examples of how Gen AI is used in various fields relevant to the class participants. This can spark discussions about the potential applications and limitations of the technology.

Additional Considerations:

• Open Office Hours: As mentioned, instructor availability during dedicated open office hours allows participants to address specific challenges or gain further clarification on topics covered in pre-session work.

• Course Materials: Well-designed assignments and projects could involve applying Gen AI to a specific problem or dataset related to a case study or a participant’s field of work. This promotes deeper understanding and potential real-world application.

Overall, the flipped classroom for Gen AI fundamentals aims to equip participants with the foundational knowledge outside of class. Class sessions then become a space for actively engaging with the concepts, practicing skills, and exploring the practical applications of this evolving technology.

Submission Details

Responses should be submitted to nssc-hr-support@mail.nasa.gov. Please include “Ref:MSG98896917” in the body of your email response and note HRC1404620 in the subject line.

You will receive an e-mail notification when your response has been submitted to the course point of contact for review.

Terms of this Request

The purpose of this RFI is to collect additional information about the subject training request and identify the willingness and capabilities of potential vendors to service the subject training request. This RFI is issued solely for information or planning purposes and does not constitute a request for proposal (RFP). The information provided in the RFI is subject to change and is not binding on the government. NASA has not made a commitment to purchase any of the items discussed, and release of this RFI should not be construed as such a commitment or as authorization to incur cost for which reimbursement would be required or sought. All submissions become government property and will not be returned.

Questions

If you have questions, please send an email to nssc-hr-support@mail.nasa.gov.

Please include “Ref:MSG98896917” in the body of your email response and note HRC1404620 in the subject line. If you do not receive a response to your email within 1 business day, please call the NASA Shared Services Center at 1-877- 677-2123 and request to speak with the Onsite Training Purchases Team.

Thank you, NSSC Training Purchases Team Onsite Training Purchases Team mailto:nssc-hr-support@mail.nasa.gov mailto:nssc-hr-support@mail.nasa.gov