[CogSci] Postdoc in Dynamic Enhancement & Personalization of Educational Technology through Experimentation: University of Toronto Computer Science

[Joseph Jay Williams]

Multiple postdoctoral positions are immediately available for research that
designs interventions and experiments to dynamically enhance and
personalize real-world educational technologies, spanning K12, university
courses, MOOCs, and learning by crowd workers.

The postdoc will set the agenda for research questions in
collaboration with Joseph
Jay Williams <http://www.josephjaywilliams.com/research-overview>, who is
particularly interested in creating systems that combine rigorous
randomized experiments with crowdsourcing and human computation,
applications of statistical machine learning (e.g. bandits & reinforcement
learning, NLP, recommender systems), and theories from cognitive, clinical
and social psychology (e.g. self-explanation, analogical comparison, growth
mindset, teaching cognitive behavior therapy).

The postdoc will be based at University of Toronto's Computer Science
department, working with Joseph Jay Williams, and with opportunities to
collaborate with faculty in U of T's Computer Science Education research
group <https://uoftcsed.github.io/>, the Machine Learning group
<http://www.cs.toronto.edu:40292/>, and HCI people at DGP
<http://www.dgp.toronto.edu/home/>. Examples of other faculty the postdoc
can collaborate with are Ashton Anderson
<http://www.cs.toronto.edu/~ashton/>, David Duvenaud
<https://www.cs.toronto.edu/~duvenaud/>, Tovi Grossman
<http://www.tovigrossman.com/>, and Fanny Chevalier
<http://fannychevalier.net/>.



The appointment is for one year, with the possibility of renewal based on
mutual interest.



The postdoc will play a key role in deciding which projects are pursued,
but illustrative examples of potential research directions are:

> Computer Science Education, research into enhancing teaching of
introductory programming, motivating broader involvement, end-user
programming.

> Developing new systems for crowdsourcing the design of online problems
and lessons, using multi-stage workflows that incorporate input from
students, crowd workers, instructors, and learning scientists.

> Creating and evaluating tools that enable collaboration between
instructors and researchers, such as co-design of interventions and
personalized lessons, and coordinated analysis of data about learning
outcomes for students with different characteristics.

> Investigating why and when prompting students to explain text/video
lectures promotes learning, and understanding the effect of multi-modal
interfaces that incorporate writing, speaking, and video creation. Teaching
metacognitive skills and self-regulated learning of study behaviors, taking
a user-centered approach to designing social-psychological interventions
for enhancing motivation such as Growth Mindset and Wise Feedback.

> Enhancing student wellness and mental health by testing interventions for
encouraging people to exercise, monitor stress, apply principles from
Cognitive Behavior Therapy to managing emotions. Investigating how to
support online peer-to-peer interactions for having discussions around
issues like managing anxiety or developing socio-emotional skills.

> Interpretable and Interactive Machine Learning Systems for dynamically
enhancing and personalizing instruction, especially from the perspective of
combining human computation with techniques from multi-armed
bandits/reinforcement learning, Bayesian optimization, applications of deep
learning to natural language processing.

Application Instructions

If you might be interested, provide your email and other information using
this form
<https://docs.google.com/forms/d/e/1FAIpQLSeHPhhLG7CHYMqs2aAzRRhhdmwJGBsQBbdwNE6MqL4hr2_tgA/viewform>
.

Then, to apply for the position, please email Joseph Jay Williams (
williams at cs.toronto.edu) with the subject line "Postdoc in Dynamically
Enhancing & Personalizing Educational Technology – [Your name]", with the
following as attachments:

(1) Curriculum Vitae.

(2) Names and contact information of 3 references who are familiar with
your research. We will follow up with your references to secure their
recommendation letters on your behalf.

In your email application, please include a brief explanation of your
research interests and how they fit with this position (in lieu of a formal
cover letter). Applications will be accepted on a rolling basis until the
position is filled.


Joseph


Joseph Jay Williams
www.josephjaywilliams.com
Assistant Professor
(July 2018 onwards), Department of Computer Science, University of Toronto
(Until June 2018) Department of Information Systems & Analytics, School of
Computing, National University of Singapore
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