Geoff Hollis, PhD, MA

Science Instructor, Faculty of Science - Computing Science

Contact

Science Instructor, Faculty of Science - Computing Science
Email
hollis@ualberta.ca

Overview

About

What do a gourmet hotdog, a funny joke, and a good computer program have in common? I think they all require creativity to make. I like to create things. I create many things, but these are three of my favourite things to create.


Research

My primary research interests are:

  • How human languages change over time.
  • How humans and other animals learn.
  • How learning processes can be simulated with computers.
  • How science measures complicated, unobservable ideas like feelings.

Teaching

Learning new concepts requires large amounts of practice and a willingness to fail. For university students, this means doing regular homework, attempting to solve problems on your own before looking for answers, and always asking yourself "how would I know if I were wrong?" whenever you think you understand something. I try to design my courses with these beliefs in mind.

My teaching experience and interests are broad.

Currently I teach courses on:

  • Introductory computer programming (CMPUT 174, 175)
  • The ethics of modern technologies (CMPUT 300)
  • How to effectively transition from university to a career (INT D 400)

Previously I have taught courses on:

  • Introductory Psychology (PSYCO 104, 105)
  • How to design scientific experiments (PSYCHO 212)
  • How social situations affect our behavior (PSYCHO 241)
  • How we think (PSYCHO 258)
  • How our senses work (PSYCHO 267)
  • The history of psychology (PSYCHO 300)
  • The evolution of human behavior (PSYCHO 391)

I would like to teach courses on:

  • How humans learn language
  • How computers learn language
  • How science works


Publications

Learning about things that never happened: a critique and refinement of the Rescorla-Wagner model when many outcomes are possible.
Author(s): Hollis, G.
Publication Date: 2019
Publication: Memory and Cognition
Volume: 47
Issue: 7
Page Numbers: 1-16
External Link: https://sites.ualberta.ca/~hollis/files/HollisRW.pdf
Wriggly, squiffy, lummox, and boobs: What makes some words funny?
Author(s): Westbury C.F., Hollis G.
Publication Date: 2019
Publication: The Journal of Experimental Psychology: General
Volume: In Press
External Link: https://sites.ualberta.ca/~hollis/files/funny_words.pdf
Scoring best/worst data in unbalanced, many-item designs, with applications to crowdsourcing semantic judgments
Author(s): Hollis G.
Publication Date: 2018
Publication: Behavior Research Methods
Volume: 50
Issue: 2
Page Numbers: 711-729
External Link: https://sites.ualberta.ca/~hollis/files/bestworst.pdf
When is best-worst best?: A comparison of best-worst scaling, numeric estimation, and rating scales for collection of semantic norms.
Author(s): Hollis G., Westbury C.F.
Publication Date: 2018
Publication: Behavior Research Methods
Volume: 50
Issue: 1
Page Numbers: 115-133
External Link: https://sites.ualberta.ca/~hollis/files/bestworst2.pdf
Estimating the average need of semantic knowledge from distributional models of semantic memory
Author(s): Hollis G.
Publication Date: 2017
Publication: Memory and Cognition
Volume: 48
Issue: 8
Page Numbers: 1350-1370
External Link: https://sites.ualberta.ca/~hollis/files/AverageNeed.pdf