An Animated Pedagogical Agent For Assisting Novice Programmers Within A Desktop Computer Environment

Abstract

Learning to program for the first time can be a daunting process, fraught with difficulty and
setback. The novice learner is faced with learning two skills at the same time each that depends on
the other; they are how a program needs to be constructed to solve a problem and how the structures
of a program work towards solving a problem. In addition the learner has to develop practical
skills such as how to design a solution, how to use the programming development environment, how to
recognise errors, how to diagnose their cause and how to successfully correct them. The nature of
learning how to program a computer can cause frustration to many and some to disengage before they
have a chance to progress. Numerous authorities have observed that novice programmers make the same
mistakes and encounter the same problems when learning their first programming language. The
learner errors are usually from a fixed set of misconceptions that are easily corrected by
experience and with appropriate guidance.

This thesis demonstrates how a virtual animated pedagogical agent, called MRCHIPS, can extend the
Beliefs-Desires-Intentions model of agency to provide mentoring and coaching support to novice
programmers learning their first programming language, Python. The Cognitive Apprenticeship
pedagogy provides the theoretical underpinning of the agent mentoring strategy. Case-Based
Reasoning is also used to support MRCHIPS reasoning, coaching and interacting with the learner. The
results indicate that in a small controlled study when novice learners are assisted by MRCHIPS they
are more productive than those working without the assistance, and are better at problem solving
exercises, there are also manifestations of higher of degree of engagement and learning of the
language syntax.