This paper reports on the findings from a quantitative research study into the use of a software tool that was built to support a part-complete solution method (PCSM) for the learning of computer programming. The use of part-complete solutions to programming problems is one of the methods that can be used to reduce the cognitive load that students experience during their learning. The tool that was built is a code restructuring tool known as CORT. It permits the display of a part-complete solution to a programming task together with a set of possible lines of code that can be used to "fill-in" the solution. Students can then easily manipulate the programming lines within CORT and then test their solutions within a traditional development environment such as Microsoft's Visual Studio. An inquiry into CORT's effect on student learning outcomes took place over a period of 14 weeks at an Australian university. Two student groups participated in an introductory programming unit, one of which utilized the CORT system whilst the other acted as a control group. Data were collected on student background, time taken to complete programming tasks, the amount of help that students required, and student learning outcomes. The data were analysed using a statistical package, and it was found that there was no significant difference in the relative levels of achievement between students in the two groups. However the results did indicate that students in the CORT group spent significantly less time and required significantly less help than the students in the control group. This suggests that if the CORT students had spent extra time on further programming tasks such that their overall time had been equal to that of the non-CORT students, then they may have achieved higher learning outcomes. Also the fact that the CORT students required less help than the control group suggests that the use of CORT might be beneficial to students studying programming in external mode where access to tutor help is more problematic. The data were also analysed to determine if there were any differences with respect to student achievement between the sub-groups of: previous achievement level; age; computer literacy level; previous programming experience; and gender. The analysis revealed that the CORT students who were either younger, only moderately computer literate, or without any previous programming experience, performed at a lower level than their non-CORT counterparts in reading and comprehending computer programs. This might be because these sub-groups have ill-developed mental models of program execution and therefore have greater difficulty comprehending code. It suggests that such students completed their programs relatively quickly with CORT, with less experimentation, and that this hindered their mental model development. (Contains 25 tables and 6 figures.)