01. Resources - old

C3L & Human Systems: Orientation meeting

Stream 1

Stream 1. Data Architecture: Data mesh and infrastructure

Purpose: Engineering the data environment and mapping out data contracts for all partners
Involved: Srecko, Damien, Ken, Tom

See here for a high-level overview

Timeline:

• December 15, 2023 (version 1)
• May 1, 2024 (all MVP-related services)

Stream 2

Stream 2. Profile Blueprint for MVP

Purpose: Confirm the constructs to be included in the MVP version of the learner profiles, support and engage Figaro in LLM work
Involved: Abhinava, Andrew, Vita

See here for more details

Timeline:

• November 24, 2023 (version 1)
• May 1, 2024 (all MVP-related services)

Stream 3

Stream 3. AI Ops: Algorithms and models

Purpose: AI algorithms and models used in education that are relevant for personalization and adaptation of learning
Involved: Haiyue, Andrew, Abhinava, Mat, Sidarth, Tom, Kevin

See here for starting thoughts

Timeline:

• November 12, 2023 (version 1)
• May 1, 2024 (all MVP-related services)

Stream 4

Stream 4. Interventions

Purpose: Mapping high-impact interventions
Involved: Shihoko, Leon, Flo, Caitlin, Tanya

See here for initial thoughts

Timeline:

• December 15, 2023 (version 1)
• May 1, 2024 (all MVP-related services)

Stream 5

Stream 5. Data privacy, ethics, and explainability

Purpose: Draft “promises to users” and equity/fairness/ethical/legal considerations
Involved: Damien, SNHU: Matt, Evan, external legal

Timeline:

• December 15, 2023 (version 1)
• May 1, 2024 (all MVP-related services)

Documents

1. Readings, Podcasts, Videos, and One Online Course Recommended by You!
2. We delve deep into the data to reveal excellence
3. Human Systems - Reference Architecture & Design Document
4. Event Data Mesh Data Schema
5. How will we get Wellness data from Learners?
6. Learner Profiles Blueprint
7. AI in Learning

Other Resources

1. Abacus AI
2. xAPI officially Becomes a Published IEEE Standard
3. Data Points & Workplace/Soft Skills Permission required
4. Construct - Intervention Table (requires log in)
5. Indicator = constellation of variables Permission required
6. Gretel Demo Day: A Synthetic Data Deep Dive
7. A highly scalable, extremely fast, easy-to-use embeddable graph database
8. SATURN of githbu official website
9. AWS + Gretel Synthetic Data Accelerator Program for Generative AI
   Imagine seamlessly training, testing, and fine-tuning bespoke ML / AI models, without risking privacy or breaching trade secrets.
   With this program customers get access to:
   • Direct support from Gretel and AWS technical experts.
   • Early access to Gretel's Tabular LLM, the first AI system designed for generating ML and AI quality data for editing, and augmenting tabular data via natural language or SQL prompts leveraging #Sagemaker, #S3, and Redshift.
   • A chance to share research and insights at a generative AI workshop series.
     Interested in being part of this amazing initiative? Applications are now open for startups and enterprises everywhere. Sign up and let’s build together.
10. Synthetic data: Anthropic’s CAI, from fine-tuning to pretraining, OpenAI’s Superalignment, tips, types, and open examples

Papers

1. Motifs in Temporal Networks
2. Motifs in Temporal Networks (Graphs)
3. Motifs in Temporal Networks (PDF Paper)
4. Using online learner trace data to understand the cohesion ofteams in higher education
5. Modeling the interaction between resilience and ability in assessments with allowances for multiple attempts