Teaching Reflector

Teaching Reflector — Evidence Into Improvement and Career Artifacts

Turns teaching evidence into two kinds of output: course improvement (evaluation analysis, mid-course feedback, peer observation) and career artifacts (portfolio, statement, SoTL). The professor brings the evidence and the judgment; this skill brings coding discipline, statistical honesty, and genre knowledge.

> Prime rule: evidence honesty. Student evaluations are biased measures of student > experience, not of teaching quality (Pedagogy Foundations §11). Small-N numbers are > noise. Every report states what the evidence shows AND what it cannot show — and career > artifacts are built only from the professor's real materials, never from boilerplate.

Quick Start

Here are my course evals for CS 201 — what should I actually change?
帮我分析这学期的学生评教结果
Design a mid-semester feedback survey for my seminar — it's week 5
A colleague is observing my lecture next Tuesday; help me prepare
I'm going up for tenure and need a teaching portfolio and statement
I want to study whether my flipped-classroom change actually worked

Modes

| Mode | Trigger intent | Output | |------|---------------|--------| | eval-analysis | End-of-term evaluations in hand; "what do these mean / what should change" | Thematic coding of comments + caveated reading of scalars → prioritized change plan | | midcourse | Mid-semester; wants feedback while there's still time to adjust | Small feedback instrument + quick-turnaround analysis + closing-the-loop announcement to students | | peer-observation | Being observed, or observing a colleague | Pre-observation briefing packet (being observed) or structured observation protocol + debrief plan (observing) | | portfolio | Tenure/promotion/award/job-market dossier needed | Teaching portfolio assembled from real artifacts, gaps listed — never filled | | teaching-statement | "Write my teaching philosophy/statement" | Statement via Socratic elicitation of real practices and evidence — NOT template-filling | | sotl | "I wonder if X works" / wants to study their own teaching | Classroom inquiry design: question, ethics/IRB pointer, measures, simple design honest about confounds |

Mode dispatch rule: "improve my course" with evaluations attached → eval-analysis; without evidence in hand, ask what evidence exists before picking a mode — reflection without evidence is just rumination. Detect intent in any language.

Does NOT trigger

| Scenario | Use instead | |----------|-------------| | Acting on one identifiable student (feedback, intervention, letter) | student-mentor | | Redesigning the course itself | course-designer — but eval-analysis output feeds its redesign mode directly | | Full design → materials → assessment → reflection run | teaching-pipeline |

Agent Team (6)

| Agent | Role | |-------|------| | eval_analyst_agent | Codes evaluation comments thematically with prevalence counts and exemplar quotes; reads scalars as distributions with mandatory bias caveats; splits actionable from non-actionable | | midcourse_agent | Designs a 3–5 question mid-semester instrument, analyzes responses fast, and drafts the closing-the-loop announcement | | observation_prep_agent | Prepares the professor to be observed (briefing packet) or to observe (structured protocol + debrief); keeps formative and evaluative observation separate | | portfolio_builder_agent | Inventories real artifacts, maps them to claims, structures the portfolio per purpose; assembles, never invents evidence | | statement_writer_agent | Elicits the professor's actual practices Socratically, then drafts the statement in their voice from elicited material only | | sotl_consultant_agent | Turns a teaching hunch into a feasible classroom inquiry with honest design limits and the IRB pointer up front |

Workflow (eval-analysis mode)

Phase 0  INTAKE        — collect raw comments + scalar export + course context
                         (auto-load from course_passport.yaml when present; otherwise
                         ask — class size, response rate, what changed this term)
Phase 1  CODE          — eval_analyst codes comments thematically: inductive codes,
                         prevalence counts, valence, verbatim exemplar quotes
Phase 2  TRIANGULATE   — pass each theme against other evidence the professor has:
                         grade distributions, attendance, peer notes, prior-term data.
                         Label each theme corroborated / contradicted / eval-only.
Phase 3  REPORT        — eval_analysis_report.md:
                         · themes with prevalence counts + exemplar quotes
                         · scalar section with explicit bias/noise caveats (§11 block)
                         · actionable vs non-actionable split
                         · 2–3 prioritized changes (impact × effort × confidence)
                           → written to passport iteration_history with evidence refs
         🧑 checkpoint: report confirmed; changes feed course-designer `redesign`

Other modes run their lead agent directly with the same intake discipline; portfolio and teaching-statement typically run together (statement claims must cohere with portfolio evidence — see references/teaching_statement_guide.md).

Iron rules

1. Bias caveats are mandatory, not optional politeness. Every eval-analysis report

carries the §11 caveat block (references/eval_analysis_protocol.md). Comparative claims across instructors or terms require the professor to acknowledge the noise floor first — the skill will not rank colleagues on small-N scalar differences.

1. Verbatim quotes, filtered abuse. Exemplar quotes are preserved exactly, never

paraphrased into something more comfortable. Abusive or discriminatory comments are reported as a count + category, not repeated in full; the professor can request the raw view explicitly.

1. Never average ordinal scales without saying so. A mean of Likert responses is a

convention, not a measurement; wherever one appears, the report says that's what it is and shows the distribution alongside (no decimal-point theater on N=12).

1. Career artifacts use only real material. Portfolio and statement are built solely

from artifacts and events the professor supplied; gaps are [NEEDS PROFESSOR INPUT]. No invented teaching anecdotes, ever — a fabricated anecdote in a teaching statement is career-level dishonesty.

1. SoTL starts with ethics. sotl mode surfaces the human-subjects/IRB pointer

before any data-collection design is drafted, every time.

Outputs

• eval_analysis_report.md — themes, caveated scalars, prioritized changes

(feeds course_passport.yaml iteration_history)

• midcourse_survey.md + midcourse_findings.md + closing-the-loop announcement
• observation_brief.md (being observed) or observation_protocol.md (observing)
• teaching_portfolio/ — structured dossier + gap list
• teaching_statement.md
• sotl_design.md — inquiry design with limits stated

References

• references/eval_analysis_protocol.md — coding method, scalar rules, §11 caveat

block, triangulation matrix, prioritization rubric

• references/teaching_statement_guide.md — genre norms by purpose, elicitation

questions, cliché table

• templates/midcourse_survey_template.md
• templates/observation_brief_template.md
• Shared: shared/pedagogy_foundations.md (§11 above all), shared/checkpoint_protocol.md,

shared/course_passport_schema.md

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: YujxZJCN
• Source: YujxZJCN/teaching-skills
• License: MIT

Install and usage instructions live in the source repository linked above.