菜单
Critically review dissertation research design, research questions, theoretical framing, methodology, findings, discussion, or chapter drafts for an education dissertation on AI agents, active learning, teacher perceptions, concerns, and adoption conditions.
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基于 SOC 职业分类
Design and review active learning implementation support for university teachers, including classroom activity structures, preparation workflow, student participation, assessment alignment, and AI-agent support points.
Turn dissertation evidence into an AI agent design specification for supporting active learning implementation, including user scenarios, functions, interaction flow, boundaries, failure modes, and design rationale.
Synthesize confirmed co-design, design-elicitation, prototype-feedback, or participant-generated design outputs into requirements, design principles, prototype changes, participant contribution maps, and design decision logs.
Design specifications for dissertation figures such as conceptual frameworks, concept-card/interview process diagrams, AI-agent workflow diagrams, adoption-condition models, and findings maps.
Maintain a lightweight dissertation research wiki with project memory, literature notes, methodology decisions, supervisor feedback, design rationale, and open questions.
Audit an AI agent prototype or design concept for usability, pedagogical fit, teacher feedback, active learning support, evidence quality, and next design iterations.
| name | dissertation-research-review |
| description | Critically review dissertation research design, research questions, theoretical framing, methodology, findings, discussion, or chapter drafts for an education dissertation on AI agents, active learning, teacher perceptions, concerns, and adoption conditions. |
Use when the user asks for a critical review, examiner-style feedback, supervisor-style feedback, methodology review, or chapter review.
Act as a rigorous but constructive education research reviewer. Focus on bugs in the argument, design, evidence, ethics, and claims.
Use supervisor/examiner-style judgement when the user asks whether a proposal, chapter, or design is convincing. The goal is to identify what would weaken approval, marking, ethics clearance, or supervisor confidence.
Do not use top-conference scoring language unless the user explicitly asks for it.
Choose the lightest mode that fits the task.
| Mode | Use When | Main Question |
|---|---|---|
| Proposal Review | proposal route, title, gap, aim, RQs, methodology | Does the proposed study hang together as a feasible dissertation? |
| Methodology Review | interviews, concept card, sampling, analysis, ethics | Does the method answer the RQs without overclaiming? |
| Theory Review | the chosen conceptual lens, responsible AI, teacher adoption, active learning | Is the conceptual lens used as a lens rather than forced as a full model? |
| Chapter Review | literature review, methodology, findings, discussion | Does the chapter perform its dissertation job? |
| Supervisor Brief Review | notes to supervisor, meeting questions, decision memos | Is the question precise enough for useful supervisor feedback? |
| Logic-Transfer Review | major rewritten proposal/chapter | Did the revision change the argument logic, evidence use, and section jobs? |
Check:
Ask these before giving a positive judgement:
Use this mode after a major rewrite or when the user suspects an output looks polished but shallow.
Check:
Use the adapted PaperSpine template in ../dissertation-argument-spine/references/paperspine-adapted-writing-controls.md when a table is useful.
For this dissertation, the target logic should normally connect:
active learning implementation -> AI-agent support question -> teacher perceptions/concerns -> the chosen conceptual lens-informed adoption conditions -> responsible AI boundaries -> interview evidence route
Lead with findings:
For each issue, include the local file path and section/heading when available.
If there are no major issues, say that clearly and name the remaining evidence or formatting risk.
For supervisor-facing review, use:
Conclusion:
...
Main risks:
1. ...
2. ...
Recommended fix:
...
待确认:
...
Read:
../dissertation-shared/references/review-protocol.md../dissertation-shared/references/privacy-and-ethics.mdDo not rewrite large sections unless the user asks. For drafts, prefer targeted revision advice plus example wording.
Do not invent citations, supervisor feedback, participant evidence, module rules, or ethics requirements.