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education-research-assistant

Writing & research

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Updated 10-15 21:35

About this skill

Research Assistant

Overview

Supports academic research and paper writing. Provides data collection and analysis, literature review, research design, academic paper drafting, citation and reference management, peer review preparation, reflection of 2026 edtech and AI education trends, and Bloom's Taxonomy-based research methodology.

Trigger Keywords

research, paper, academic paper, data collection, data analysis, report, literature review, peer review, research design, research methodology, survey, statistical analysis

Workflow

Step 1: Confirm Research Topic

Research purpose:

  • Clarify research question (RQ)
  • Target readers and publication venue (academic journal, thesis, report)
  • Contribution and novelty of the research

Research scope:

  • Research subjects (population, sample)
  • Research period
  • Methodology to use (quantitative, qualitative, mixed)

Step 2: Literature Search Plan

Major domestic academic databases:

DB URL Features
RISS riss.kr Free search of domestic theses, academic journals, and monographs. Operated by the Korea Education and Research Information Service under the Ministry of Education
DBpia dbpia.co.kr Focused on domestic academic journal articles. Many recent papers in AI literacy and edtech
KISS kiss.kstudy.com Korean academic information DB. Strong in humanities and social sciences
NDSL ndsl.kr Korea Institute of Science and Technology Information. Focused on science and engineering

International databases:

  • Google Scholar (scholar.google.com)
  • PubMed (pubmed.ncbi.nlm.nih.gov) — medicine and life sciences
  • IEEE Xplore (ieeexplore.ieee.org) — engineering
  • JSTOR (jstor.org) — humanities and social sciences

Search strategy:

  • Extract core keywords
  • Expand synonyms and related terms
  • Use Boolean operators (AND, OR, NOT)
  • Filter by publication year (last 5 years recommended)

Step 3: Analyze Materials

Classify literature:

  • Topic clustering
  • Identify trends by period
  • Classify by research methodology
  • Derive arguments

Data analysis:

  • Quantitative research: statistical analysis (descriptive statistics, t-test, ANOVA, regression analysis)
  • Qualitative research: content analysis, thematic analysis, case study
  • Mixed research: integration of quantitative and qualitative

2026 edtech and AI education trends (latest paper trends in DBpia and RISS):

  • AI literacy research: increase in papers exploring AI awareness and competencies of language education majors
  • Learner modeling: active research on designing personalized learning paths based on AI courseware
  • AI ethics: Growing discourse on the ethical use of big data-based edtech
  • AI courseware: Digital textbooks + AI integration, automated grading, error clinic, and learning analytics combined
  • Hyper-personalized learning: PwC Samil Accounting Corporation report — the core of edtech is 'one-to-one customized learning'

Step 4: Designing the paper structure

Standard structure of an academic paper:

  1. Introduction

    • Research background and purpose
    • Research question (RQ)
    • Necessity and novelty of the research

  2. Literature Review

    • Review of major prior research
    • Identification of research gap
    • Positioning of this study

  3. Methodology

    • Research design
    • Data collection method
    • Analysis method

  4. Results

    • Data analysis results
    • Statistical significance
    • Visualization (tables, graphs)

  5. Discussion

    • Interpretation of results
    • Comparison with prior research
    • Implications

  6. Conclusion

    • Summary of the research
    • Limitations of the research
    • Suggestions for follow-up research

References:

  • Citation styles such as APA, MLA, Chicago, etc.
  • Reference management tools (Zotero, EndNote)

Step 5: Drafting and review

Drafting:

  • Draft each section
  • Check logical flow
  • Verify citation format

Preparing for peer review:

  • Validity of the research methodology
  • Reliability of the results
  • Depth of the discussion
  • Clarity of contribution

Using Bloom's Taxonomy

Application of Bloom's Taxonomy of Educational Objectives in edtech and AI education design:

Cognitive level Description AI usage method
Remember Memorizing facts Flashcards, automated quizzes
Understand Explaining concepts Chatbot Q&A, summary generation
Apply Actual use Simulations, hands-on tasks
Analyze Identifying structure Data analysis, comparison
Evaluate Judgment and critique AI feedback, peer review
Create New output Projects, portfolios

→ Recommended structure: AI automates lower cognitive levels (Remember–Apply), while teachers focus on guiding higher levels (Analyze–Create)

Usage examples

Example 1: "Write a literature review report on the effectiveness of AI education" → Topic analysis → Literature search → Clustering → Report writing

Example 2: "Analyze survey data and derive insights" → Data loading → Descriptive statistics → t-test/ANOVA → Interpretation of results

Example 3: "Lay out the structure of a master's thesis research proposal" → Clarify research question (RQ) → Prior research → Research design → Thesis structure

Example 4: "Organize references in APA format" → Collect source information → Apply APA style → Reference list

Deliverables

  • Literature review report
  • Data analysis report
  • Research proposal draft
  • Academic paper draft
  • Reference list (APA, MLA, Chicago)

Precautions

Access to educational materials:

  • If you tell us the range of accessible materials, we will analyze as much as possible within that range

When learning objectives are unclear:

  • Start with the process of specifying the research question (RQ) together

When raw data is unavailable:

  • Switch to a meta-analysis of existing prior research or a literature review direction

When submission guidelines differ by journal:

  • If you tell us the target journal name, we will adjust to match its submission guidelines

Related skills

  • moai-coworker/education-curriculum-designer: Curriculum design, defining learning objectives
  • moai-coworker/education-assessment-creator: Creating exam and assessment questions
  • moai-coworker:ai-slop-reviewer — Final deliverable AI slop review (post-review, required)
  • moai-writer:korean-humanize — Remove Korean AI tells (required after slop review)

When not to use this skill

  • Curriculum and lecture design → The moai-tutor:education-curriculum-designer skill is more suitable
  • Exam question creation → Use the moai-tutor:education-assessment-creator skill
  • Market research and business research → The moai-consultant:consult-market skill is more suitable
  • Actual data collection (sending surveys, conducting interviews) → Use the relevant tool (Google Forms, Kakao Forms, etc.) directly

References

File Load conditions
references/research-assistant.md When supporting academic research such as literature search, reading notes, critical synthesis, and reference management
references/academic-paper.md When designing research, managing experiments, analyzing statistics, writing academic papers, and preparing submissions
references/thesis-advisor.md When selecting topics, reviewing literature, choosing research methodology, and guiding thesis proofreading