Informatics in Education

1. What “research” means in INFEDU

In INFEDU, research is systematic scholarly work that produces a new and defensible insight about learning/teaching computing (informatics / computer science education) or a clearly scoped computing in education problem. Research is not defined simply by “having data.” A manuscript becomes publishable when it makes a novel claim and provides a credible justification for that claim.

Research in INFEDU may be:

Empirical — quantitative, qualitative, or mixed-method evidence from data.
Design & evaluation — educational engineering / DBR with an explicit design rationale and evaluation logic.
Methodological / measurement — a validity argument for an instrument, rubric, metric, coding scheme, or analytic method.
Theoretical / conceptual — rigorous conceptual work, not unsupported opinion.
Review research — systematic, scoping, mapping, or meta-analytic synthesis with a transparent corpus and reproducible method.

Common non-publishable pattern: a manuscript has data, a tool, a framework, or a list of prior studies, but does not make a clear contribution claim or does not show how the evidence supports that claim.

2. Make the research logic visible

Regardless of method, a publishable INFEDU paper should allow a reader to trace a straight line from the initial problem to the final contribution. A practical way to test this is to check whether the manuscript makes the following chain visible:

Problem: What educational problem in computing/informatics is being addressed, and why does it matter?
Gap or motivation: What is missing from prior work?
Aim and contribution claim: What exactly does the paper add that is new?
Framing: What constructs, theory, design rationale, or conceptual model guide the work?
Research questions / hypotheses / aims: Are they answerable by the chosen design?
Operationalization: How are constructs turned into evidence?
Analysis or evaluation logic: How will the evidence support — or fail to support — the claim?
Results: What is the evidence?
Discussion: What do the results mean, how do they compare with prior work, and what alternative explanations remain?
Limitations and boundary conditions: What cannot be concluded?
Conclusion: What is the final bounded contribution?

3. Choose the right manuscript type and state it clearly

Authors should choose the manuscript type that matches the primary contribution and state that choice clearly in the manuscript and/or cover materials. INFEDU can keep a compact public taxonomy while still allowing different subtypes within it.

Research Article

Use for Empirical, Design & evaluation, Methodological / measurement, Theoretical / conceptual, or Replication / null-results contributions.

Review

Use for Systematic, Scoping, Systematic mapping, or Meta-analysis papers that produce new synthesis knowledge.

If a manuscript sits in a recurring edge configuration — for example a hybrid empirical + measurement paper, a formative framework paper, a narrow-topic review with layered evidence, or an AI-assisted programming case — authors should also consult the INFEDU Casebook.

4. What a publishable manuscript must contain

Introduction

State the educational problem and why it matters for informatics/computing education.
Identify the specific gap in prior work.
State the aim and the contribution clearly.
Use field-relevant constructs and define them.

Method or approach

State the design clearly.
Describe participants, context, materials, instruments, tasks, datasets, or corpus-building procedures.
Show how each construct or question is operationalized.
Explain the analysis, evaluation, or synthesis method in enough detail for review.

Results or synthesis

Present the evidence that directly answers the research questions or supports the contribution claim.
Keep tables, appendices, rubrics, search strings, scoring rules, or codebooks reviewable and internally consistent.
Report uncertainty and avoid visually or rhetorically inflating weak evidence.

Discussion

Interpret what the evidence means rather than repeating results.
Compare your results with prior work in computing/informatics education.
Consider alternative explanations, confounds, or transfer limits.
Derive implications that remain traceable to measured evidence.

Conclusions

State the final contribution in bounded form.
Distinguish what has been established now from what still requires future validation.

5. Keep claims proportionate to evidence

INFEDU looks closely at whether claim strength matches design, evidence, and reporting. A manuscript often fails at editorial screening not because the topic is unimportant, but because it claims more than the study can justify.

What claim discipline means

Descriptive or cross-sectional evidence supports descriptive or associational claims, not strong causal claims.
Self-report measures support claims about perceptions, beliefs, confidence, or self-efficacy unless performance was also measured directly.
Formative expert review or walkthrough evidence supports feasibility, coherence, usability, or design rationale — not learning effectiveness or full validation.
Output-quality evaluation of an AI/NLP system does not by itself establish learner comprehension or classroom effectiveness.
Adjacent literature can inform comparison or interpretation, but should not be presented as stronger direct evidence than it is.

When to consult the Casebook

The paper combines two contribution types.
The evidence base is mixed, indirect, formative, or proxy-based.
The manuscript relies on special materials such as rubrics, walkthrough protocols, transcripts, prompts, or search strings.
The topic is in scope, but the exact inference level needs careful claim-bounding.

6. What makes a Discussion publishable

A publishable Discussion is an interpretive synthesis, not a repetition of findings. A simple check is whether a reader can follow this map:

Question: briefly restate the research question, hypothesis, or aim.
Result: point to the key evidence that answers it.
Interpretation: explain what the result means and why it may have occurred.
Literature comparison: show how the result aligns with, extends, or conflicts with prior work.
Alternative explanations: identify plausible confounds or rival interpretations.
Limitations and boundary conditions: state what remains uncertain and what the study cannot show.
Bounded implications: derive implications that are traceable to the evidence actually produced.

Common return-before-review problem: the manuscript has results but no real Discussion, or it uses a “key findings” list instead of an interpretive synthesis.

7. Transparency, ethics, and disclosure

In INFEDU, transparency and ethics are part of research quality. Missing or vague reporting in this area often leads to delay or return before review.

Ethics basis: approval, exemption, waiver, or no-review-required basis, as applicable.
Consent / assent: who agreed, how they agreed, and how voluntariness was protected.
Data protection: what was collected, what identifiers were involved, how data were minimized, and how privacy was safeguarded.
Required statements: conflicts of interest, funding, data/material availability, and AI disclosure where applicable.
Blind review: identifying ethics committee, institutional, funding, and author details should be kept out of the anonymised review manuscript and placed in the non-review title page or cover materials when required by workflow.

Important: If human participants or human-related data are involved, authors should read the dedicated Research Ethics page. If generative AI or AI-assisted tools were used, authors remain fully responsible for accuracy, originality, citation integrity, and confidentiality.

8. Abstracts and keywords

An INFEDU abstract is not a teaser. It should be a compact, stand-alone version of the manuscript’s logic.

Length: 150–250 words.
Language: English.
Format: one paragraph.
Keywords: 4–6 keywords immediately after the abstract.
Do not include: references, footnotes, tables, figures, unexplained abbreviations, or unsupported claims.

For most papers, the abstract should include:

Background or problem.
Aim, question, or contribution.
Method or approach.
Main findings or synthesis result.
Principal conclusion or contribution.

For conceptual/theoretical papers, replace method/results with approach/argument and main insight.

9. Before you submit

Is the manuscript clearly in scope for learning/teaching computing or a clearly defined computing-in-education problem?
Is the primary manuscript type and subtype stated clearly?
Can a reader see the logic chain from problem to contribution?
Does the Discussion interpret the evidence instead of merely repeating findings?
Are the claims bounded to what the design and measures justify?
Are all required ethics, disclosure, and transparency elements available and placed correctly for blind review?
Are key materials auditable: instruments, rubrics, prompts, search strings, codebooks, scoring rules, or appendices?
If the paper fits a recurring edge pattern, has the author checked the INFEDU Casebook?