An Interactive Electronic Textbook for Python Programming and Data Science Courses

More details on the Award can be found here.

Overview

Student reading content on a digital textbook platform or online learning platform usually are distracted away from understanding the details to specific programming examples or worked examples provided in the textbook. This work explores the use of smart content allocation at different sections / pages of the textbook covering concepts all and only the concepts covered in the textbook upto that page / section while leaving the examples with concepts that are covered later to be allocated to a later section / page of the textbook.

Motivation

The goal of the work is two--fold: 1) allocating content that is relevant to a specific page in terms of the concepts covered only up to that page / section, 2) engaging students in the process of learning to code or explore related examples related to the topic or concept.

Preliminary Implementation

In this work we used 2 different digital textbook platforms to allocate specific smart content that can be loaded upto that point using the concepts covered in the textbook.

The system uses 2 components:

1. A python parser that generates concepts for the examples presented in the book at that page

2. The same parser is used to generate concepts for all the smart content available in the systems at PAWS Lab -- refer "Smart Learning Content for Computing Education"

3. The smart content as a list of links in the tab on the side of the page for students to load and view.

Publications

Chau, Hung, Jordan Barria-Pineda, and Peter Brusilovsky. "Course-adaptive content recommender for course authoring." In Lifelong Technology-Enhanced Learning: 13th European Conference on Technology Enhanced Learning, EC-TEL 2018, Leeds, UK, September 3-5, 2018, Proceedings 13, pp. 437-451. Springer International Publishing, 2018.

Barria-Pineda, Jordan, Arun Balajiee Lekshmi Narayanan, and Peter Brusilovsky. "Augmenting Digital Textbooks with Reusable Smart Learning Content: Solutions and Challenges." iTextbooks@ AIED. 2022.

Sabet, A. J., Alpizar-Chacon, I., Barria-Pineda, J., Brusilovsky, P., & Sosnovsky, S. (2022). Enriching Intelligent Textbooks with Interactivity: When Smart Content Allocation Goes Wrong. iTextbooks 2022, 3192.