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Bi23 Sec1: Learning Across Species: Foundations and Frontiers in the Ethology of Learning

California Institute of Technology / Caltech / Undergraduates

Course overview

This undergraduate tutorial introduced students to how non-human animals learn, beginning with foundational ethology by Tinbergen and Lorenz, behaviorism by Thorndike and Skinner, and moving toward modern neuroethology, computational ethology, and biological intelligence. Students read primary research papers and textbook materials, attended guest lectures from scholars in the field. They learned how to study animal behavior across field and laboratory settings, and completed a mini ethology project through guided fieldwork.

Poster for Bi23 Learning Across Species.
Course poster from the original Bi23 teaching page.

Responsibilities

  • Designed and taught a weekly 3-unit undergraduate tutorial.
  • Built lectures and reading assignments around animal learning, ethology, behaviorism, and modern behavior research.
  • Organized a campus fieldwork project and student presentations.
  • Designed a pass/fail course structure emphasizing attendance, reading, participation, assignments, and fieldwork.
  • Coordinated course materials and communication through Canvas.

Student Feedback

Comments from students in Caltech Teaching Quality Feedback Reports

Jieyu was very fun and funny and cares a lot about her students. She is passionate and knowledgable about the subjects she taught, and takes great animal videos and photos, which makes going to lecture very fun.

The section I was in was ethology. You should take it if you like animals and animal documentaries and stuff like that. It's a very fun and chill class, and I joined it because I like learning about animals and observing their behaviors, and that's basically what we do in this class. Jieyu is so, so nice and funny, and very passionate and knowledgable about the subject matter. It's just 1 hr of class a week (go through a couple lecture slides and watch animal videos), plus some reading and short answer assignments. We do a fieldwork project at the end where we observe animals on campus. I actually learned a lot more than I was expecting to from this class about learning and animal behavior, so I really enjoyed it.

Syllabus

Instructor: Jieyu Zheng, PhD Candidate in Neurobiology, Meister Lab

Course Description

This tutorial offers an engaging exploration of ethology, focusing on how non-human animals learn. We begin with foundational theories from Charles Darwin and continue into modern ethology, established by Nobel laureates Nikolaas Tinbergen and Konrad Lorenz. The course also covers behaviorism, including work from Ivan Pavlov and B.F. Skinner, and introduces current advances in neuroethology, computational ethology, and the intersection of biological intelligence and artificial intelligence.

Throughout the term, students read about animal behavior in field and laboratory settings. The course concludes with a mini ethology project through expert-guided fieldwork. Students leave with an overview of the science of learning, an appreciation of behavior as a language of nature, and perhaps even a skillset for teaching their pets new tricks.

Learning Goals

  • Foundations of ethology: understand the history and evolution of ethology as a scientific discipline, plus key methods for observing, studying, and analyzing animal behavior.
  • Critical reading and literature review: develop skills in evaluating academic literature and taking organized notes through assigned readings from scientific journals and textbook chapters.
  • Project design and research collaboration: design hypothesis-driven research, develop project proposals, apply course research methods, and collaborate on project design and reporting.
  • Presentation and peer evaluation: present project findings and practice scientific communication and constructive feedback.

Lecture Topics

  1. What is learning? An introduction to learning, its definitions, and its role in animal behavior.
  2. Charles Darwin and theory of evolution: the evolutionary basis of behavior in humans and animals.
  3. Modern ethology: foundational work by Tinbergen and Lorenz.
  4. Behaviorism: classical and operant conditioning as frameworks for studying behavior.
  5. Computational ethology and neuroethology: computational tools and neuroscience for studying behavior at multiple levels.
  6. Fieldwork and presentations: campus-based field studies and student presentations synthesizing course concepts and findings.

Format

  • Course meetings: 55-minute weekly meetings held in Chen 240A on a schedule discussed at the organizational meeting.
  • Weekly assignments: assignments for most weeks, due the night before the scheduled class meeting.
  • Fieldwork project: a February fieldwork project during lecture time, followed by an oral presentation or short written report.

Lecture Outline

  • Week 2: Define learning and ethology.
  • Week 3: How to study behaviors.
  • Week 4: Field ethology and innate behaviors.
  • Week 5: Important research questions in ethology and guest speakers.
  • Week 6: Study of behaviors in the laboratory, intro to behaviorism.
  • Week 7: Behaviorism continued and animal training.
  • Week 8: Complex learning: navigation, language, and social learning.
  • Week 9: Computational ethology and neuroethology with guest speakers.
  • Week 10: Fieldwork project.
  • Final exam week: project presentation.

Grading

This is a pass/fail tutorial with a light workload. Attendance is crucial because it directly impacts the collective learning experience.

  • Attendance: 50%. Attendance is mandatory for all lecture sessions, and active engagement during class is expected.
  • Assignments: 30%. Reading assignments and small written tasks are assigned most weeks.
  • Fieldwork project: 20%. The final grade includes attendance for the fieldwork lecture and project planning and presentations.
  • In short: students who attend all lectures, including fieldwork, are guaranteed to pass the class.

Time Management

  • Students with foreseeable commitments should plan ahead and may submit assignments early.
  • Students who wish to work significantly ahead of schedule may petition the instructor to access materials in advance.

Extensions and Missed Lectures

  • For severe circumstances that prevent work completion or lecture attendance, notify the instructor at least two days in advance.
  • Missing four or more lectures may lead to a failing grade unless extraordinary circumstances are discussed with the instructor.

Communication

  • Course materials and communication are handled through Canvas.
  • The instructor responds to email during weekdays, usually with same-day turnaround.
  • There are no office hours for this course.

Collaboration Policy

  • Collaboration on homework assignments is encouraged unless explicitly stated otherwise.
  • Students may consult with peers or outside reference materials.
  • Any use of external references, including AI tools, must be properly cited.
  • Submitted work must be written independently and reflect the student's understanding at the time of submission.