Learning-by-teaching is a powerful approach that enhances students to think deeply,
orally and repeatedly. Several computer-based systems have been implemented where students
play the teacher role and virtual agents play the tutee role. The existing systems focus on various
domains, but none of them has considered programming problem solving. Additionally, the
majority of these systems did not provide metacognitive support. They only focus on providing
feedback as correct answers, and this type of feedback is called knowledge of correct response.
However, this paper explores the influence of guided metacognitive feedback on novice
programmers in a teachable agent environment. For that, a computer-based learning environment
is built to enable the novice programmers to teach programming problem solving to an animated
agent. It combines learning-by-teaching technique and metacognitive support in order to assist
those beginners to acquire comprehensive learning on how to solve unfamiliar problems and
prepare those programmers for future learning tasks. We conduct an experiment to compare the
effect of the aforementioned feedbacks on the novice programmers’ performance in learning-byteaching paradigm. The results show that the metacognitive feedback has positive effect on novice
programmers’ achievement of solving problems. In addition, providing metacognitive feedback
as explicit feedback in learning-by-teaching paradigm improves the novices' abilities to estimate
what they know and what they do not know about how to solve new programming problems.