STUDY PORTFOLIO

Studies With Visible Research Status

These records cover learning, teaching, and research practice. Completed evidence records show what was reviewed and what it can support. Planned studies show methods, safeguards, and the decisions still ahead.

Portfolio status

Portfolio records
6
Two completed evidence records and four planned studies
Completed
2
Public evidence and methods syntheses
Planned
4
No recruitment or data collection
Last reviewed
28 August 2026
Public status register

CONTROLLED LIFECYCLE

A Stage Is a Claim That Must Be Supported

Each record states what was reviewed or what would be tested, which learning outcomes matter, and where uncertainty remains. Completed syntheses do not become intervention findings, and planned methods do not become results before observation.

01

Concept

Question, learning context, intended decision, and feasibility

02

Protocol drafting

Design, outcomes, implementation, and analysis decisions

03

Review

Scientific, education, ethics, privacy, accessibility, and security determinations

04

Registration and execution

Time-stamped record, recruitment, and data collection

05

Analysis and reporting

Results, uncertainty, limitations, artifacts, and corrections

COMPLETED RECORDS

Evidence already reviewed

These records synthesize public sources and methods guidance. They report bounded conclusions, not new participant outcomes.

SL-005Stage 05: Analysis and reporting
Completed evidence synthesis

What higher-education AI tutoring studies actually measure

Research question

What can controlled studies tell educators about AI tutoring, learning time, and learner experience in higher education?

Synthesis method

Completed rapid evidence synthesis of publicly available controlled higher-education studies, with a focal randomized crossover trial and supporting research standards.

Target population or material

Published higher-education studies of AI tutoring and active learning. No Santaros participants, recruitment, or proprietary learner data were used.

Comparison frame

AI tutoring conditions compared with active-learning or instructor-led teaching in the reported source studies. Design differences were retained rather than pooled.

Main validity limits

Single focal randomized trial, one course context, intervention specificity, outcome alignment, unmeasured educator effects, and publication or selection bias.

Public record

Completed evidence brief, extraction table, source links, limitations register, and a bounded replication question list.

Synthesis outcomes

  • Learning performance
  • Time on task
  • Engagement and motivation
  • Study design quality
  • Transfer and generalizability limits
SL-006Stage 05: Analysis and reporting
Completed methods synthesis

Teaching reproducible research as a learning outcome

Research question

Which teaching and reporting practices make reproducibility teachable, assessable, and useful to scientific learners?

Synthesis method

Completed cross-standard methods synthesis of education research, data stewardship, evidence-synthesis, and research-reporting guidance.

Target population or material

Public standards and guidance relevant to research-methods, data-science, and research-software teaching. No human participants or learner records were analyzed.

Comparison frame

Outcome, provenance, uncertainty, and sharing requirements compared across standards. This record makes no causal comparison between curricula.

Main validity limits

Standards are normative guidance rather than learner-effect estimates; terminology, discipline, licensing, and institutional requirements vary.

Public record

Completed teaching checklist, cross-standard comparison, implementation prompts, and a planned learner study specification.

Synthesis outcomes

  • Outcome definition
  • Provenance completeness
  • Environment recoverability
  • Evidence traceability
  • Learner transfer requirements

PLANNED STUDIES

Questions still to be tested

These prospective records are not findings. Recruitment, ethics determinations, and registration will be shown when they exist.

SL-001Stage 02: Protocol drafting
Planned intervention study

Scientific reasoning instruction with AI assistance

Research question

Can structured AI-assisted instruction improve how graduate learners generate, test, and revise scientific hypotheses?

Candidate method

Proposed counterbalanced learning study using matched hypothesis-generation, critique, and transfer tasks.

Target population or material

Graduate learners and early-career researchers in participating science programs. Disciplines, eligibility, and sample-size rationale are not yet specified.

Candidate comparison

Matched instructional tasks completed with a structured AI tutor and with instructor-authored resources, with task order counterbalanced where feasible.

Main validity risks

Task equivalence, prior AI experience, instructor effects, disciplinary heterogeneity, rater reliability, and benchmark contamination.

Planned public artifacts

Public protocol, lesson specification, scoring rubric, de-identified learner responses where permitted, and analysis code.

Candidate outcome measures

  • Hypothesis testability
  • Evidence-to-claim alignment
  • Confidence calibration
  • Delayed transfer
  • Inter-rater agreement
SL-002Stage 02: Protocol drafting
Planned intervention study

Reproducible analysis training with AI assistance

Research question

Can learners produce a more reproducible scientific analysis when AI assistance is embedded inside explicit provenance instruction?

Candidate method

Proposed blinded reproduction challenge embedded in a graduate quantitative-methods module using open datasets and containerized environments.

Target population or material

Graduate learners, research software trainees, and early-career analysts. Expertise thresholds and scientific domains are not yet specified.

Candidate comparison

Provenance-first AI-assisted workflow instruction compared with conventional worked examples and documentation.

Main validity risks

Dataset familiarity, environment drift, instructor assistance, reproducer expertise, tolerance definitions, and hidden manual steps.

Planned public artifacts

Teaching protocol, provenance schema, reproducibility checklist, benchmark tasks, reference containers, and model-configuration record.

Candidate outcome measures

  • Reproduction success
  • Trace completeness
  • Decision justification
  • Delayed transfer
  • Environment portability
SL-003Stage 02: Protocol drafting
Planned intervention study

Teaching evidence synthesis under scientific disagreement

Research question

Can structured AI-assisted instruction improve how learners represent consensus, uncertainty, contradiction, and evidence quality?

Candidate method

Proposed expert-annotated learning benchmark using source packets with supporting, null, conflicting, indirect, and lower-certainty evidence.

Target population or material

Graduate learners and early-career researchers in evidence-intensive disciplines. Domains and prerequisite knowledge are not yet selected.

Candidate comparison

Structured AI-assisted synthesis instruction compared with a conventional critical-appraisal worksheet using the same source packets.

Main validity risks

Source-selection bias, expert disagreement, domain knowledge, benchmark leakage, rubric sensitivity, and construct-irrelevant writing ability.

Planned public artifacts

Teaching protocol, licensed source packets, expert annotations, learner rubric, error taxonomy, and benchmark harness.

Candidate outcome measures

  • Citation support
  • Contradiction detection
  • Evidence certainty
  • Selective omission
  • Delayed transfer
SL-004Stage 01: Concept and scoping
Planned field study

Mentored team learning in shared AI research workspaces

Research question

How do shared AI workspaces affect teaching, feedback, coordination, and accountability in research teams?

Candidate method

Proposed prospective mixed-method field study with baseline, adoption, and follow-up periods across mentored research teams.

Target population or material

Small research teams that include a mentor or instructor and graduate or early-career researchers. Recruitment and institutions are not yet specified.

Candidate comparison

Within-team baseline and workspace-use periods, with staggered adoption or comparison teams considered during protocol development.

Main validity risks

Tool novelty, self-selection, group-level clustering, mentor style, confidential work, maturation, and observer effects.

Planned public artifacts

Study protocol, event-log specification, mentoring observation guide, governance template, and de-identified implementation case reports.

Candidate outcome measures

  • Feedback latency
  • Decision traceability
  • Researcher learning
  • Duplicate work
  • Appropriate escalation

GOVERNANCE

Human-Participant Work Requires a Documented Determination

Sample sizes, recruitment channels, participating institutions, and review bodies are not named because they have not been verified for publication.

Before any human-participant work begins, the responsible institution or authorized review body must document the required review, exemption, waiver, consent, privacy, security, and data-sharing conditions.

CONTRIBUTE TO A STUDY

Bring Domain Expertise Into Protocol Development

We welcome scientific collaborators who can improve tasks, outcome definitions, validity checks, and real-world constraints before a protocol is finalized.

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Participation, authorship, data access, and governance are documented before research begins.