Tag: talks-to-k-12-students

A brief introduction to reinforcement learning

We spend a lot of time talking about supervised learning when discussing ML with students, but I find reinforcement learning just as interesting and useful.

I developed a talk on reinforcement learning for high school participants in SAIL ON, the year-round diversity and high school outreach program of the Stanford AI Lab that I initiated and led, which follows the SAILORS intensive two-week AI summer camp.

We discuss how reinforcement learning works, how to make decisions given Bayesian bounds, touchstone RL problems and recent applications, and where RL tends to succeed and fail.

My First AI (or: Decision Trees & Language Modeling for Middle Schoolers)

I gave the keynote address at Byte Sized, a workshop for middle school girls spearheaded by SAIL ON students. My First AI (or: Decision Trees & Language Modeling for Middle Schoolers) solidified the basics of artificial intelligence and the if/else statements taught the previous day.

The talk introduces the language identification problem within AI, teaches about decision trees, and then asks students to write decision trees in small groups to distinguish between Hmong, Balinese, Zulu, and other languages. After a debrief on why computers are might be more effective than human-written rules, it briefly ties in themes of feature extraction and gradient descent via GBMs.

Modeling with Naive Bayes

As the progenitor and leader of SAIL ON, the Stanford AI Lab’s year-round effort to attract and keep underrepresented minorities in the field of Artificial Intelligence, I engage high schoolers about artificial intelligence, machine learning, and the positive social impacts of our field.  SAIL ON meets once a month in the Computer Science building at Stanford.  Its trifold focus allows past participants in the SAILORS two-week summer camp to continue to learn about AI, to nurture strong relationships with each other, and to lead outreach projects that bring the technical, humanistic, and diversity missions of the AI outreach program to the wider community.

Screenshot of title slide of deck

As the educational component of the October meeting of SAIL ON, we discussed and applied Naive Bayes modeling.  Like other machine learning methods, Naive Bayes is a generic approach to learning from specific data such that we can make predictions in the future.  Whether the application is predicting cancer/whether you’ll care about an email/who will win an election, we can use the mathematics of Naive Bayes to connect a set of input variables to a target output variable.  (Of course, some problems are harder than others!)

We focused on the derivation of Naive Bayes with a chalk-and-talk discussion (slides), identifying why Naive Bayes is mathematically justified and posing some deeper thought questions.  We checked understanding with a hand-calculation of a Naive Bayes problem (handout): does a shy student received an A in a class, given some observations about her and some observations about more forthcoming students?  We then turned to a Jupyter Notebook that applies the same methods on a larger scale, working on the Titanic challenge from Kaggle with an applied introduction to pandas and sklearn: given passenger manifest records, can we predict who survived?

By providing this basis, I hope to increase appreciation for applications of what students are seeing in their math classes, and to facilitate students moving further on their own with applied machine learning before November’s meeting.

Screenshot of worksheet
Screenshot of Jupyter notebook on github

Introduction to ASL Theoretical Linguistics

One of my favorite parts of studying linguistics was being presented with data and being asked to find the system within it. Language data, with linguistic theory’s insistence that everything must make sense, make the most excellent data and logic puzzles.

Screenshot of ASL Linguistics Problems

As part of preparing for a spatial grammar-heavy meeting of the Montgomery Blair High School Linguistics Club, I developed three American Sign Language morphology problems.  These problems illustrate interesting properties of American Sign Language that spoken languages do not have (non-manual markers, spatial agreement, and a rich temporal inflection system based in manual phonology).

Try your hand at doing the problems if you’re interested in any of the following:

  • What it means to do theoretical linguistics (or the sort of logic skills that linguists develop)
  • Unique properties of spatial languages
  • Basic American Sign Language linguistics
  • Similarities between American Sign Language and other world languages

Unlike most materials on ASL linguistics, the problems don’t assume that readers are fluent in American Sign Language or in linguistic theory — I developed these problems because I couldn’t find any resources aimed at an intelligent lay non-Deaf audience.  The problems deliberately walk users through the steps to answer a question, whereas most theoretical linguistics problem sets jump straight to the questions at hand and assume existing familiarity with linguistic features not observed in English.

Once the club and I meet, I’ll post the answer sheet as well.

Introduction to ASL Linguistics

During the discussion we focused on introducing different non-voiced communication forms and on linguistic anthropology/linguistic creativity.  We postponed theoretical linguistics until another time (in which we did some experiential learning on morphology). This page consists of a set of links, prepared videos, and notes designed to support real-time interaction with students at the linguistics club at Montgomery Blair High School.

The big take-away is that American Sign Language is not “English on the hands”.  ASL is independent from English both in grammar and linguistic culture.


  • Caveats for posterity: I’m hearing, I don’t possess native-like fluency in ASL, and I don’t have an advanced degree in this; I do have general and ASL linguistic training, I read widely, and I’m more or less aware of what I don’t know
  • What are some ways deaf people communicate? [YouTube]
  • Compare ASL structure [.avi | .ogv | .gif] with PSE structure [.avi | .ogv | .gif] with English structure [.txt]
  • Charts might help [fingerspelling: ASL | BSL | LSF] [cued speech]

Anthropological Linguistics

  • Big idea: Linguistic creativity
  • ABC stories [YouTube]
  • Sign jokes [King Kong, “please but”, environments, CODAs]
  • Music & poetry [YouTube]
    • Rhyme (handshape, movement path, location, non-manual markers)
    • Rhythm (movement, handedness)
    • Meter (heavy & light syllables)
  • Also, Black ASL [WaPo | HuffPost | YouTube (uncaptioned but 5:37 has a chart)]

Theoretical Linguistics [postponed]

  • Big idea: Spatial grammar
  • Basic structure
    • English consonants have place and manner of articulation, plus voicing [IPA chart]
      • Place of articulation (cat/tat/pat)
      • Manner of articulation (pat/bat/mat)
    • ASL signs have five “parameters”
      • Handshape (think/know) *
      • Location (summer/dry) *
      • Palm orientation (sock/star)
      • Movement (sit/chair) *
      • Nonmanual markers (late/not yet)
  • The movement piece is more complicated (Christian/Congress, one-handed children/die) –> movement-hold theory
    • M (always)
    • H (color, study)
    • M H (think, know, my, sit)
    • H M H (week, guess)
    • M H M H (Congress, flower)
    • M M M H (chair, school, paper)
    • Other structures are possible, but not any other structure (e.g., exclude H M)
  • Nonmanual markers are extremely important grammatical markers; they are frequently unrecognized by hearing people
    • Questions (yes-no/wh)
    • Rhetorical questions
    • Adjectives and adverbs (mm, th, cha, cs — more in a .doc)
    • Topicalization
  • Grammatical use of space of ASL (verb classes, classifiers, aspect, etc.)

Further Resources

  • Deaf people with linguistics training
  • ASL [language | grammar]
  • Gallaudet University [map]
    • 10th-12th grade summer ASL immersion [link]
    • Linguistics department [dept. | event blog]
    • Center for Continuing Studies teaches ASL courses for $230/credit (most classes are 3 credits) [dept.]
    • Theatre performances are captioned or voice-interpreted [link]
  • Books
    • Linguistics of American Sign Language by Valli et al. (ASL linguistics textbook)
    • Signing Naturally (ASL language textbook series)
    • The American Sign Language Handshape Dictionary by Tennant and Brown (dictionary)
    • For Hearing People Only by Moore and Levitan (deaf culture/language in context)
  • Apps
    • ASL Dictionary — 5000 signs [Android | iPhone]
    • ASL spelling game — beginner’s fingerspelling app [Android]
    • Marlee signs — phrases and words [iPhone]
  • Media
    • “Switched at Birth” (ABC Family)
    • YouTube has a variety of performances, lectures and vlogs