A LEARNING VISIBILITY & CREDENTIALING WORKSHOP MODULE
Talent Tree & Connected Learning Evidence:
Turn Fragmented Records Into Meaningful Relationships
Institutions collect extensive evidence about student learning. But courses, projects, assessments, credentials, experiences, activities, and skills often remain separated across systems and record formats.
The result is not a complete picture of the learner. It is a collection of disconnected facts.
Connected learning evidence reveals how experiences develop capabilities, how skills have been applied, and what the learner may be prepared to pursue next.
Does this sound familiar?
Evidence lives in separate systems
Courses, assessments, projects, credentials, advising records, experiential learning, and student reflections remain divided across platforms.
Skills appear without their origins
A student may be associated with a skill, but the record does not show where it was developed, practiced, demonstrated, or recognized.
Experiences lose their meaning
Internships, service, employment, research, leadership, and extracurricular activities appear as titles without showing what the learner actually did.
Credentials become isolated endpoints
Badges, certificates, and degrees confirm achievement but may not connect clearly to the evidence and capabilities behind them.
Students repeatedly rebuild their story
Learners reinterpret the same experiences for advising, applications, transfer, employment, and continuing education.
Institutions cannot see the whole learner
Programs can report credits and outcomes but struggle to understand how learning accumulates across contexts and over time.
What is connected learning evidence?
Connected learning evidence is information about a learner’s courses, projects, assessments, activities, experiences, skills, accomplishments, and credentials that retains the relationships among those elements.
Instead of recording only that a learner possesses a skill, connected evidence can explain where it developed, which activities required it, how it was applied, what supports it, who recognized it, which credential includes it, and what it may support next.
Connected evidence does not require every student record to be combined into one institutional database. It requires meaningful, supported, usable relationships that the learner can understand and appropriately share.
The problem is not missing data. It is missing context.
Institutions already produce extensive learning data, but it is commonly organized around courses, departments, systems, and transactions rather than the learner’s developing body of experience.
A transcript may show completion. A badge may identify a competency. A portfolio may hold an artifact. An internship record may name an employer. Viewed separately, none may explain how the pieces relate.
Connecting learning experiences, activities, capabilities, evidence, recognition, credentials, goals, and learner interpretation transforms separate records into evidence that can support reflection, advising, progression, recognition, and opportunity.
See the relationships—not just the records.
Learning Sources
- Courses and programs
- Projects and research
- Work and internships
- Service and leadership
- Independent learning
Activities
- Problems addressed
- Responsibilities held
- Methods applied
- Tools used
- Contributions made
Capabilities
- Knowledge developed
- Technical skills
- Human skills
- Judgment and agency
- Emerging strengths
Evidence & Recognition
- Assessments
- Artifacts
- Demonstrations
- Endorsements
- Credentials
Goals & Opportunities
- Academic progression
- Career exploration
- Further learning
- Employment
- Community contribution
Connected evidence helps learners and authorized audiences understand not only what appears in a record, but how learning experiences, activities, capabilities, evidence, and future possibilities relate.
How learning evidence becomes fragmented
STAGE 1
Learning happens across contexts
Students develop knowledge and capability through courses, projects, work, service, research, leadership, and independent exploration.
STAGE 2
Each system captures a fragment
Learning platforms, student systems, assessment tools, credential platforms, portfolios, and departments record different parts of the experience.
STAGE 3
Meaning is reduced to fields
Rich experiences become course codes, grades, titles, completion records, badges, or disconnected artifacts.
STAGE 4
The learner reconstructs the story
Students and authorized audiences must infer relationships that the institution never made visible.
A collection of records is not yet a connected learning story.
Each record may be valid while still revealing very little about how learning developed. A relationship-centered approach preserves the experiences, activities, evidence, recognition, and purposes that give each record meaning.
Connected evidence can help answer:
Connect a course, project, job, or experience to the learner’s activities, contributions, tools, and responsibilities.
Trace knowledge and skills to the experiences in which they developed and were applied.
Link capabilities to artifacts, assessments, accomplishments, credentials, endorsements, and other appropriate evidence.
Preserve whether information was issued, assessed, verified, endorsed, inferred, or described by the learner.
Show repeated use, development across experiences, emerging capabilities, and relevant recency.
Create purposeful views for academic progress, recognition, continued learning, transfer, employment, or another opportunity.
A Talent Tree shows how a learner’s evidence connects and grows.
Where capabilities came from
Connect skills and knowledge to courses, projects, employment, service, research, personal experiences, and other sources.
How capabilities have been used
Show the activities, responsibilities, problems, tools, and environments in which a capability was applied.
What supports each claim
Link capabilities to artifacts, assessments, accomplishments, credentials, endorsements, and other evidence.
How learning has developed
Reveal repeated use, growth across experiences, newly emerging capabilities, and areas still developing.
What matters to the learner
Include interests, motivations, goals, passions, voice, and learner-developed context where appropriate.
What could happen next
Create purposeful views for academic progression, recognition, continued learning, employment, and opportunity.
Fragmented records
A record-centered approach may show:
- Course titles and credits
- Grades and completion dates
- Badge or credential names
- Uploaded files
- Internship titles
- Lists of skills
- Assessment results
- Separate portfolio entries
Each item may be valid while revealing little about how learning developed.
Connected evidence
A relationship-centered approach can show:
- Activities within an experience
- Skills those activities required
- Where knowledge was applied
- Artifacts demonstrating the work
- Development over time
- Who assessed or recognized it
- Credentials incorporating it
- How it supports a next step
The purpose is to preserve enough context for evidence to become understandable and useful.
A learner is more than a list of skills.
Two learners may possess similar skills while differing in the experiences through which they developed them, the depth and recency of their application, the responsibilities they accepted, the evidence supporting their claims, and the opportunities they want next.
A Talent Tree should preserve these distinctions. It is not a definitive representation of a person. It helps the learner develop a richer, evidence-supported account that can continue to change over time.
Connected evidence must preserve meaning, authority, and learner control.
A relationship in a data model is not automatically proof of a claim. The source, meaning, confidence, authorization, and limitations of the evidence must remain understandable.
Institutions must distinguish authoritative records, assessed evidence, external credentials, endorsements, inferences, and learner-provided information. Learners should be able to see, understand, correct, contextualize, and appropriately share their information.
Connect experiences, activities, capabilities,
evidence, credentials, and goals.
Build a Talent Tree that can grow with the learner.
THE MATCHING WORKSHOP MODULE
Module 5: Talent Tree & Connected Learning Evidence
This module helps participants determine how learning experiences, activities, capabilities, evidence, credentials, and learner goals should connect.
Participants examine existing records, identify relationships that are currently missing, and define a bounded model for making evidence more meaningful and reusable.
This module helps your team:
- Map learning evidence across systems and experiences
- Connect skills and knowledge to their origins
- Describe activities within courses and experiences
- Link claims to artifacts, assessments, and recognition
- Identify relationships that should remain learner-provided
- Distinguish verified, assessed, endorsed, and self-described information
- Clarify how evidence develops over time
- Design purposeful views for learner decisions
- Identify technical, policy, and governance questions
- Develop a connected learning model
What should happen to each part of the learning record?
Not every record requires the same treatment. The institution should decide how each element contributes to a meaningful and responsible view of learning.
Connect
Link evidence to the experience, activity, capability, credential, goal, or decision it helps explain.
Enrich
Supplement an existing record with activities, descriptions, evidence, reflections, or other needed context.
Verify
Determine which information can be confirmed by an institution, issuer, assessor, employer, or other authorized source.
Translate
Express institutional records in language and structures learners and authorized audiences can use.
Separate
Avoid combining records when their sources, meanings, confidence, ownership, or permitted uses differ.
Investigate
Resolve uncertainty through evidence, technical review, governance decisions, or specialist judgment.
These categories organize evidence and workflow decisions. They do not prove a capability, determine learner potential, predict success, award credit, or replace authorized human judgment.
What should a connected evidence review examine?
The experience
Where did the learning occur, and what was the learner’s actual context?
The activity
What did the learner do, create, solve, practice, manage, investigate, or contribute?
The capability
What knowledge, skill, judgment, or other capability did the activity require or develop?
The evidence
What artifact, assessment, observation, result, reflection, or record supports the relationship?
The recognition
Who issued, assessed, verified, endorsed, or described the information—and what does that mean?
The intended use
What learner decision, institutional process, or authorized purpose should the evidence support?
Move from the institutional Talent Tree to an individual learner view.
TalentSync EDU is intended to let an authorized educator move from a combined institutional, program, cohort, or team Talent Tree into a view filtered to one learner.
The individual view would use the same underlying relationships while distinguishing what the institution has observed from broader evidence the learner has chosen to share.
STEP 1
Select the learner
Filter the broader Talent Tree to the experiences, activities, evidence, and capabilities connected to one authorized individual.
STEP 2
View institution-observed evidence
See learning demonstrated through courses, projects, assessments, advising, work-based learning, and other institutional activity.
STEP 3
View learner-shared evidence
Add relevant prior learning, employment, credentials, projects, interests, and other evidence the learner chooses to share from TalentPass.
STEP 4
Connect the two views
Understand the institutionally relevant picture without flattening the difference between observed and learner-controlled evidence.
STEP 5
Preserve provenance
Show whether each element is institution-observed, learner-confirmed, institution-verified, externally verified, inferred for review, or unsupported.
STEP 6
Use a purposeful profile
Select relevant evidence for advising, progression, recognition, transfer, employment, or another bounded human decision.
The individual Talent Tree should be a filtered view of the connected evidence—not a separate duplicate record. It should help an educator understand a learner while preserving source, permission, uncertainty, and learner control.
- Institution-observed view
- Learner-shared view
- Connected view
- Visible provenance and status
- Purpose-specific access
- Learner review and control
TALENTPASS + TALENTSYNC EDU
Connect the learner-owned and institution-observed Talent Trees.
TalentPass is designed to help an individual develop and control a reusable Talent Tree spanning education, employment, activities, skills, credentials, projects, evidence, interests, and goals.
TalentSync EDU is intended to give an authorized institution a complementary individual view: the learning and talent it has observed, combined—when the learner chooses—with relevant evidence shared from TalentPass.
Together, these views can reveal both the capabilities already visible within the institution and relevant latent talent that conventional academic records may miss.
Product status: The individual learner Talent Tree described here is an intended TalentSync EDU configuration and is not presented as a currently available feature. It builds on the existing Talent Tree, evidence, Profiles, and filtering architecture but still requires product design, implementation, testing, and appropriate institutional controls.
PRODUCT AND DECISION BOUNDARIES
An individual Talent Tree supports understanding. It does not define the learner.
TalentPass, TalentSync EDU, and the Talent Tree should not be presented as producing a definitive model of a person, automatically proving every capability, predicting success, assigning a universal talent score, determining the best program or opportunity, replacing human judgment, eliminating bias, or requiring every learner to disclose every record.
The system can organize information, identify relationships, develop evidence, and create purposeful views. Learners and authorized human decision-makers remain responsible for interpretation and consequential decisions. Privacy, accessibility, records governance, consent, cybersecurity, intellectual property, and other questions may require qualified specialist review. TalentPass is not designed for use by minors.
What to bring into the conversation
You do not need a complete institutional data model or fully integrated learner record system.
We begin with a bounded learner decision and the records, artifacts, and relationships most relevant to it.
Useful inputs may include:
- Sample transcripts and course records
- Program and course learning outcomes
- Competency or skills frameworks
- Projects, portfolios, and student work
- Assessment records and rubrics
- Experiential and work-based learning records
- Badges, certificates, licenses, and credentials
- Advising and degree-planning information
- Co-curricular and extracurricular records
- Existing learner profiles
- Data dictionaries and integration diagrams
- Credential and interoperability standards
- Stakeholder observations
- Consent, access, correction, and retention practices
The Decision Foundation establishes the learner outcome, evidence boundary, and institutional decision this module should support.
What this module can help clarify
Which relationships matter
Identify how experiences, activities, capabilities, evidence, credentials, goals, and opportunities should connect.
What context is missing
Reveal where existing records are valid but insufficient for learners or authorized audiences to interpret.
What can be confirmed
Distinguish institutional records, assessed evidence, external credentials, endorsements, and learner-provided information.
How the Talent Tree should grow
Define a bounded structure that allows learning evidence to become richer and more useful over time.
Final outputs depend on the modules selected and the learner-centered decision established through the workshop’s required Decision Foundation.
Where might the work lead next?
Connected evidence often reveals related challenges in student visibility, prior learning, credential design, interoperability, and opportunity translation.
Student Learning Visibility
Connect fragmented institutional learning records into purposeful views for students, educators, and authorized partners.
Prior Learning Discovery
Help learners identify knowledge, skills, and experience developed beyond conventional academic records.
PLA Evidence & Recognition Readiness
Prepare learning evidence and institutional review for an appropriate recognition process.
Learning & Credential Data Interoperability
Examine how records, credentials, profiles, wallets, and systems can exchange structured information responsibly.
Questions institutions ask about connected learning evidence.
A Talent Tree is a structured view of relationships among a person’s experiences, activities, capabilities, evidence, credentials, interests, motivations, and goals.
A profile presents selected information for a purpose. The Talent Tree provides the connected underlying structure from which different profiles can be created.
A skills graph centers relationships among skills and other entities. A Talent Tree centers the person and connects skills to actual experiences, activities, evidence, credentials, interests, and goals.
Activities show what the learner did, the problems involved, the tools used, the context, and the responsibility held. They make skill labels more interpretable.
No. Information may be official, assessed, endorsed, externally issued, inferred for review, or learner-described. Its source and meaning should remain clear.
AI may suggest possible activities, capabilities, or relationships, but those suggestions require confirmation, context, and appropriate human judgment.
The learner controls the information developed and shared through TalentPass. Institutions remain authoritative for their own records and control appropriate institutional observations, while access inside TalentSync EDU must follow defined permissions and purposes.
Yes. A learner can create different bounded views for advising, transfer, recognition, employment, continued learning, or another purpose.
No. It complements the transcript by connecting formal records to projects, activities, capabilities, artifacts, experiences, credentials, and learner goals.
That is the intended configuration described by this module. An authorized educator could filter the broader institutional Talent Tree to one learner and switch among institution-observed, learner-shared, and connected evidence views. This individual view still requires product design and implementation.
The recommended design is one individual Talent Tree with filters rather than duplicate trees. Institution-observed evidence functions like active talent, while learner-shared evidence may reveal relevant latent talent. A connected view can display both with clear provenance.
Not necessarily. Existing institutional systems may remain authoritative while a bounded set of records and relationships is connected around a specific learner decision.
It should retain appropriate information about source, date, context, development, and relevance without pretending that every part of the record is permanent or equally current.
Not automatically. The learner should choose what is shared for an authorized purpose, often through a selected profile rather than unrestricted access.
It can help identify where relevant capabilities developed and what evidence may support them, preparing the learner for an institution’s established assessment process.
The Decision Foundation establishes the learner outcome and bounded decision. This module can then connect experiences, activities, capabilities, evidence, credentials, and goals around it.
MAKE THE CONNECTIONS VISIBLE
Turn separate learning records into a Talent Tree that can grow with the learner.
Connect experiences to activities, capabilities, evidence, credentials, and goals—then create purposeful views that help learning become understandable and useful.
This module is part of Gobekli’s configurable Learning Visibility & Credentialing Workshop.