Teaching artificial intelligence is effective if the experience is a visual and interactive one, with educational materials that utilize combinations of various content types such as text, math, and code into an integrated experience. Unfortunately, easy-to-use tools for creating such pedagogical resources are not available to the educators, resulting in most courses being taught using a disconnected set of static materials, which is not only ineffective for learning AI, but further, requires repeated and redundant effort for the instructor. In this paper, we introduce Moro, a software tool for easily creating and presenting AI-friendly teaching materials. Moro notebooks integrate content of different types (text, math, code, images), allow realtime interactions via modifiable and executable code blocks, and are viewable in browsers both as long-form pages and as presentations. Creating notebooks is easy and intuitive; the creation tool is also in-browser, is WYSIWYG for quick iterations of editing, and supports a variety of shortcuts and customizations for efficiency. We present three deployed case studies of Moro that widely differ from each other, demonstrating its utility in a variety of scenarios such as in-class teaching and conference tutorials.
[1]
David R. McIntyre,et al.
An experiment with WWW interactive learning in university education
,
1998,
Comput. Educ..
[2]
Thomas L. Naps,et al.
Exploring the role of visualization and engagement in computer science education
,
2003,
ITiCSE-WGR '02.
[3]
Martin Odersky,et al.
An Overview of the Scala Programming Language
,
2004
.
[4]
Björn Stierand.
Reveal.js: The HTML Presentation Framework
,
2017
.
[5]
Brian E. Granger,et al.
IPython: A System for Interactive Scientific Computing
,
2007,
Computing in Science & Engineering.
[6]
Leslie Lamport,et al.
Latex : A Document Preparation System
,
1985
.
[7]
Lynn Andrea Stein.
Interactive programming: revolutionizing introductory computer science
,
1996,
CSUR.
[8]
Vivek Srikumar,et al.
WOLFE: Strength Reduction and Approximate Programming for Probabilistic Programming
,
2014,
AAAI Workshop: Statistical Relational Artificial Intelligence.
[9]
Douglas S. Blank,et al.
Computational Notebooks for AI Education
,
2015,
FLAIRS.