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Project Overview Thriving in Our Digital World is a problem-based- learning pedagogical model for teaching computer science in blended environments. It is a result of design- based research and iterative development. Teaching Computer Science Through Problems George Veletsianos, Tara Craig, Greg Russell, Bradley Beth, & Calvin Lin University of Texas at Austin Learning Technologies & Computer Science Design Principles Authentic problem/project drives module and instruction Information delivery for foundational content Student-centered, inquiry activities for higher-order skills Technology-supported instruction and learning Purpose & Goals Engage students with computer science Develop a PBL pedagogical model for computer science education Support teachers’ implementations of a pilot course based on such a model Emerging Research Results Narratives were engaging and memorable, but inauthentic Extraneous materials distracted from the core curriculum rather than enhancing it Teachers and students worked almost exclusively on computers and rarely ‘offline’ Usability of the online environment and digital tools was critical to the degree of technology integration Teachers relied on traditional instructional practices Each teacher’s implementation of the curriculum was unique Teachers required extra prep time to prepare for the pilot course Accrediting multiple implementations required criterion-based assessments in addition to PBL assessments Example Module: Artificial Intelligence Chatterbots, like Apple’s Siri, can converse with humans, but is artificial intelligence ‘smart’ enough to make us think they’re human? Your job is to design and conduct a Turing Test capable of distinguishing a chatterbot from a human via conversation. The Course Anchor Video This Poster Our Team

Teaching Computer Science Through Problems

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Page 1: Teaching Computer Science Through Problems

Project Overview

Thriving in Our Digital World is a problem-based-learning pedagogical model for teaching computer

science in blended environments. It is a result of design-based research and iterative development.

Teaching Computer Science Through ProblemsGeorge Veletsianos, Tara Craig, Greg Russell, Bradley Beth, & Calvin Lin

University of Texas at Austin – Learning Technologies & Computer Science

Design Principles

•Authentic problem/project drives module and instruction

•Information delivery for foundational content

•Student-centered, inquiry activities for higher-order skills

•Technology-supported instruction and learning

Purpose & Goals

•Engage students with computer science•Develop a PBL pedagogical model for

computer science education•Support teachers’ implementations of a

pilot course based on such a model

Emerging Research Results

• Narratives were engaging and memorable, but inauthentic

• Extraneous materials distracted from the core curriculum rather than enhancing it

• Teachers and students worked almost exclusively on computers and rarely ‘offline’

• Usability of the online environment and digital tools was critical to the degree of technology integration

• Teachers relied on traditional instructional practices

• Each teacher’s implementation of the curriculum was unique

• Teachers required extra prep time to prepare for the pilot course

• Accrediting multiple implementations required criterion-based assessments in addition to PBL assessments

Example Module: Artificial Intelligence

Chatterbots, like Apple’s Siri, can converse with humans, but is artificial intelligence ‘smart’

enough to make us think they’re human? Your job is to design and conduct a Turing Test capable of

distinguishing a chatterbot from a human via conversation.

The Course

Anchor VideoThis Poster

Our Team