Some graduate students teach more than the occasional covered lecture: a run of lectures in a course, a block of the term, or a whole course as a teaching associate or graduate instructor. That is a different job from covering one class. You plan across weeks, build or adapt materials at a sustainable pace, keep up with the syllabus, collect feedback as you go, and work with the TAs who run the sections. This page covers planning the run, a weekly preparation rhythm, a lecture template, building practice across lectures, what to do when you fall behind, and working with your TA team. For a single lecture, see Covering a Lecture.
Defaults that work. If you only take four things from this page:
- Cap preparation at about two hours per hour of lecture, spread over several days.
- Adapt before you build: start from existing slides and open course materials, and credit them.
- Keep the active learning when you're behind; cut content instead.
- Ask for feedback every week, and answer it at the start of the next lecture.
Plan the run
- Write four to six outcomes for your block of lectures, and tag each lecture with the outcome it serves (Writing Learning Outcomes).
- List everything you could cover, then cut to what matters. Too much content leaves no time for practice.
- Order topics so each builds on the last.
- Leave buffer time, for example one open slot every four or five lectures, and check holidays and exam dates before you commit.
Materials
- Adapt before you build. Start from the course's existing slides, MIT OpenCourseWare, or another public course site.
- Check the license and credit the source. OpenCourseWare, for example, uses a Creative Commons license that requires attribution, noncommercial use, and sharing adaptations under the same terms.
- Borrow questions: peer-instruction question banks for CS and tested assignments from Nifty Assignments save hours.
- Post slides before class in an accessible format (Accessible Teaching Materials).
A sustainable preparation rhythm
New instructors often over-prepare: in Robert Boice's studies of new faculty, many spent close to 20 hours a week on course preparation, while the "quick starters" who thrived spent modest time on preparation and left room for students to participate. A common rule of thumb drawn from that work is to cap preparation at about two hours per hour of lecture, and to prepare in short sessions over several days rather than one long night.
A made-up example week with two 75-minute lectures (about five to six hours of preparation):
| When | What |
|---|---|
| Friday, 45 min | Read the week's feedback cards; note what to revisit; sketch outcomes for next week |
| Monday, 90 min | Build Tuesday's lecture from adapted slides; send it to the TAs |
| Tuesday, 20 min before | Run through the live-coding demo |
| Tuesday, 30 min after | Notes on what ran long; read the one-minute papers |
| Wednesday, 90 min | Build Thursday's lecture; send it to the TAs; staff meeting |
| Thursday, before and after | Run through; then notes, and post slides and recording |
A lecture template
| Minutes | Segment (75 minutes) |
|---|---|
| 0 to 5 | Warm-up: two questions on earlier material, answered from memory |
| 5 to 8 | Today's goals; answer last week's most common confusion |
| 8 to 23 | Part 1: the idea, then a worked example |
| 23 to 30 | Concept question: vote, discuss with a neighbor, vote again |
| 30 to 45 | Part 2: live coding, mistakes included |
| 45 to 52 | Pairs solve a problem like the worked example, with fewer steps given |
| 52 to 65 | Part 3: extend the idea, or contrast it with a related one |
| 65 to 70 | A question that mixes today's material with an earlier topic |
| 70 to 75 | Summary, preview, one-minute paper |
Build learning across lectures
- Retrieval: start lectures with a few questions on earlier material. Practice testing is one of the two best-supported study techniques in a large review of learning research.
- Spacing: bring back topics from one to three weeks earlier in warm-ups and problems. Spaced practice is the other.
- Mixing: once students have learned several kinds of problem, mix them, so students practice choosing the method, not just applying it.
- Worked examples, then fading: show a fully worked example, then give problems with fewer steps supplied, until students do them alone.
- Active learning every lecture. Across 225 studies in STEM, students in classes with active learning did better on exams and were less likely to fail than students in traditional lectures. In computing courses, peer instruction has cut fail rates substantially.
Feedback as you go
Collect a one-minute paper or "muddiest point" every week, and open the next lecture by answering the most common one. Run your own midsemester survey around weeks five or six, and tell students what you'll change. Getting Feedback on Your Teaching has a survey you can use.
When you fall behind
- Use the buffer slot first.
- Still behind? Cut by priority. Keep what is assessed or needed later; move "nice to know" material to a short reading or video.
- Don't save time by dropping the active learning. The evidence for it is the strongest you have.
- Tell the TAs and the course lead within a day, and update the schedule on the course site.
- Tell students the new plan, and which assignments or exams it affects.
- Merge lectures only when both topics serve the same outcome.
Working with your TAs
- Send them each lecture's goals and slides a couple of days ahead.
- Ask what students struggled with in section, and use it.
- Share results from in-class questions so sections can target the weak spots.
- Agree how questions about lecture content are answered, so students hear one answer.
Further reading
Planning and lecturing
- CMU Eberly Center, Course Content and Schedule: cutting to essentials and building in buffer time.
- CMU Eberly Center, Lectures.
- CMU Eberly Center, Using Classroom Assessment Techniques.
- UC Berkeley Center for Teaching & Learning, Designing Your Course.
- Cornell Center for Teaching Innovation, Active Learning.
- Columbia CTL, Accessibility in Teaching and Learning.
New instructors
- Boice, "New Faculty as Teachers" (Journal of Higher Education, 1991).
- Brent and Felder, "Turning New Faculty Members into Quick Starters" (2007) (PDF): a short summary of Boice's findings.
- University of Michigan CRLT, handout on planning an academic career (PDF): includes the two-hours-per-lecture-hour guideline.
How learning works
- Dunlosky et al., "Improving Students' Learning With Effective Learning Techniques" (2013), and a plain-language summary from APS.
- Atkinson et al., "Learning from Examples: Instructional Principles from the Worked Examples Research" (2000).
- Sweller and Cooper, "The Use of Worked Examples as a Substitute for Problem Solving in Learning Algebra" (1985).
- Freeman et al., "Active learning increases student performance in science, engineering, and mathematics" (PNAS, 2014).
- Porter, Bailey Lee and Simon, "Halving fail rates using peer instruction" (SIGCSE 2013).
Materials to adapt
- MIT OpenCourseWare and its Creative Commons license.
- Peer Instruction for Computer Science.
- Nifty Assignments.
- The Carpentries, Live Coding is a Skill.
- Public course sites, for example Harvard CS50x, Berkeley CS 61A and Stanford CS 106B.
Related pages: Covering a Lecture, Running a Discussion Section or Lab and Teaching Statements and Portfolios.