SL-007Stage 01: Concept and scopingPlanned Lithuania context study

AI literacy and teacher judgment in Lithuanian classrooms

Research questionHow can Lithuanian teachers use AI in ways that strengthen learning, assessment, and critical thinking without transferring responsibility from the teacher to the tool?

Review the design View source context

SL-007 public status

Current stage: Concept and scoping
Recruitment: Not started
Results: None
Last reviewed: 28 August 2026

PLANNED STUDY CASE FILE

A Learning Question With a Testable Decision

This planned case file situates learning-science research in Lithuania without claiming a partnership or local result. It asks how teachers can evaluate AI use in Lithuanian-language and multilingual classrooms, how learners can disclose assistance, and how classroom evidence can remain useful to teachers rather than becoming a technology adoption scorecard. The study would treat teacher judgment and learner agency as outcomes in their own right.

Learning context: Lithuanian general-education schools, including lower-secondary and gymnasium contexts, where teachers work within national curriculum expectations, local school rules, and the practical constraints of language, access, time, and support.
Decision this study should support: Help Lithuanian schools decide which AI-supported teaching practices deserve further evaluation, which safeguards are needed, and which claims should not be generalized across subjects or communities.

Protocol objectives

01
Describe how teachers interpret responsible AI-use guidance when planning Lithuanian-language lessons and assessments.
02
Measure whether professional learning improves the quality of teacher decisions about when AI adds educational value and when it should not be used.
03
Assess learner reasoning, source checking, disclosure, and independent transfer separately from AI-assisted task completion.
04
Identify access, language, disability, workload, privacy, and school-governance conditions that shape implementation.

DESIGN CANDIDATE

What Would Be Tested

Every element remains provisional until the protocol is registered. Unknowns are shown as unknowns instead of being filled with unsupported precision.

Design candidate: Mixed-method professional-learning study with classroom cases and independent learner tasks
Setting: Lithuanian general-education schools; municipality and school sampling remain to be specified
Language frame: Lithuanian-language materials, with multilingual and language-access checks where relevant
Comparison: Structured AI-use and disclosure learning compared with existing professional-learning practice if assignment is defensible
Sample size: Not set. School clustering, teacher workload, learner nesting, and precision requirements must be resolved first
Governance: School-level rules, consent, data minimization, access controls, and required institutional review precede observation

Learning sequence

Locate

Map a lesson to its learning objective, Lithuanian-language context, curriculum decision, and learner access conditions before selecting a tool.

Judge

Ask whether AI adds clear educational value, what the teacher remains responsible for, and what information must remain private.

Disclose

Teach learners and teachers to state when AI assisted ideation, language support, feedback, or drafting, and what human checking followed.

Transfer

Assess whether learners can reason, verify sources, and complete a related task independently without the original AI support.

MEASUREMENT

Outcomes Defined Before Observation

Candidate roles may change during protocol review. Any primary outcome will be fixed before data collection or access to relevant outcome data.

Outcome	Role	Operational definition	Timing
Teacher AI-use judgment	Candidate primary	Rubric score for choosing, configuring, limiting, disclosing, and reviewing AI use against a stated learning objective.	Before and after professional learning
Lithuanian-language source support	Candidate secondary	Whether AI-assisted explanations and citations remain faithful to a source in Lithuanian and any comparison language used in the lesson.	Sampled lesson artifacts
Learner reasoning	Candidate learning outcome	Independent rubric score for explanation, evidence checking, uncertainty, and critical revision on a related task.	Baseline and follow-up
Disclosure and escalation	Safety outcome	Whether material AI assistance is identified and low-confidence, private, or high-impact decisions are referred to a qualified teacher.	During lesson and artifact review
Implementation burden	Context outcome	Teacher time, preparation load, technical friction, and support required to use the framework responsibly.	Throughout implementation

ANALYSIS DISCIPLINE

A Plan That Can Report Unfavorable Results

Final estimands, models, exclusions, missing-data rules, multiplicity decisions, and stopping conditions will be specified in the registered protocol where applicable.

01
Prespecify a teacher-level and, only if justified, learner-level estimand before selecting a clustered or stepped design.
02
Model school and classroom clustering, baseline digital competence, prior AI use, subject, language context, and missingness when supported by the design.
03
Use Lithuanian and English scoring materials only after translation, back-translation, and cognitive review establish measurement comparability.
04
Report teacher judgment, learner reasoning, disclosure, and task completion as separate outcomes rather than a single adoption score.
05
Publish negative cases, implementation burden, access constraints, and deviations, and avoid ranking schools or teachers.

RESEARCH INTEGRITY

Implementation, Access, and AI Disclosure

The record must be detailed enough to audit what learners experienced, what the AI system could do, and where qualified humans remained responsible.

Implementation record

School and municipality sampling frame, invitation route, eligibility, consent, and non-coercive participation plan
Lithuanian and English lesson materials, translation decisions, accessibility checks, and teacher-facing guidance
AI tools, model versions, permitted data, retention settings, prompts, and school-level approval rules
Professional-learning attendance, adaptations, technical failures, support requests, and workload record
Learner artifact, disclosure, source-checking, and independent-transfer procedures with privacy-preserving identifiers

Equity and access

Include urban, regional, and rural implementation conditions only when sampling and precision make comparisons interpretable.
Review Lithuanian-language, multilingual, disability, device, connectivity, and assistive-technology access before attributing differences to instruction.
Do not use learner AI traces for grading, discipline, or selection without a separate governance decision and clear consent.
Provide accessible materials, teacher alternatives that do not require a paid tool, and private routes for raising safety or workload concerns.

AI-system disclosure

The study would report provider, model, version, access date, retention configuration, prompts, tools, and retrieval sources.
Teacher and learner materials would distinguish AI assistance for language support, ideation, feedback, drafting, and analysis.
Human review remains responsible for curriculum alignment, assessment decisions, source verification, privacy, and learner welfare.
Any Lithuanian-language quality claim would be limited to the tested task, source set, model configuration, and scoring procedure.

VALIDITY REGISTER

Main Risks and Planned Responses

These responses reduce specific risks. They do not eliminate uncertainty or guarantee that the final design will support a causal claim.

R01

Policy mistaken for effectiveness

Treat national or school guidance as context and measure teacher judgment and learner outcomes directly.

R02

Language construct confounding

Use translation review, bilingual scoring checks, and separate language support from the target learning construct.

R03

School self-selection

Record invitation and participation flows, compare baseline context, and limit causal claims when assignment is not credible.

R04

Surveillance pressure

Minimize logs, keep teacher and learner data out of employment or grading decisions, and offer private participation routes.

R05

Workload and access inequity

Measure preparation time, technical burden, devices, connectivity, and no-tool alternatives as implementation outcomes.

STUDY GATES

Status Changes Require an Exit Record

A stage label is a public claim. The record moves forward only when its stated exit condition is documented.

Concept

Current

Lithuanian learning context, intended decision, language frame, and initial risks are recorded.

Protocol drafting

Not started

Sampling, outcomes, translation checks, governance, and analysis plan are fixed.

Review

Not started

Education, ethics, privacy, accessibility, security, and school-governance determinations are documented.

Registration and execution

Not started

Protocol, school permissions, consent materials, and scoring rules are time-stamped before observation.

Reporting

Not started

Teacher and learner outcomes, access conditions, uncertainty, deviations, and artifacts are released where permitted.

EVIDENCE CONTEXT

Real Sources That Inform the Protocol

These external sources provide context for design decisions. They are not Santaros Labs outputs, endorsements, or evidence that this proposed study has been completed.

Lithuania Ministry of Education, Science and Sport · 2026

Guidelines on the use of AI have been developed to help each school set its own rules

Describes Lithuania's school-level AI guidance, teacher responsibility, privacy boundaries, disclosure expectations, and the requirement that AI add clear educational value.

Open source

National Agency for Education EdTech Centre · Current programme information

Digital Competencies

Provides context on educator digital competence development, DigCompEdu, inclusive innovation, and Lithuanian teacher learning support.

Open source

Lithuania Ministry of Education, Science and Sport · 2021

Agreement on National Education Policy (2021-2030)

Frames accessible education, research-informed development, digital transformation, and competencies for complex real-world problems.

Open source

National Agency for Education · 2017

Digital Competence Framework for Citizens, Lithuanian translation

Provides a Lithuanian-language reference for information and data literacy, communication, content creation, safety, and problem solving.

Open source

OPEN SCIENCE PLAN

Planned Public Open

Preregistered protocol
Lithuanian and English lesson materials
Teacher decision rubric
Translation and accessibility record
Analysis code and governed data statement
School-facing implementation guide

Availability will depend on consent, ethics review, licensing, privacy, security, and institutional requirements. A restriction will be explained rather than presented as open access.

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METHODS COLLABORATION

Improve This Study Before Registration

We welcome educators, learning scientists, domain researchers, statisticians, research software specialists, and governance reviewers who can strengthen the protocol.

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A research inquiry does not imply study enrollment, institutional approval, funding, or authorship.