Developing solutions to recurring algorithmic and design problems in various contexts constitutes a fundamental part of computer science (CS) and software engineering. A main principle in software development is the transfer of solutions from previously solved problems to novel ones. The ability to abstract similarities and apply previous productive experiences to new situations relates to analogical reasoning - one of the most important problem-solving heuristics.However, some of the major difficulties that CS students encounter with algorithmic problem-solving involve poor analogical reasoning skills. This paper describes a Pattern-Oriented-Instruction (POI) approach to a computer science fundamentals course. The main principles governing the POI approach lie in defining Algorithmic Patterns - solutions to basic algorithmic problems - and in organizing course problem-solving activities around them. The POI approach is grounded in cognitive theories that deal with an individual's knowledge organization in memory. The knowledge structure is assumed to have implications with regard to problem-solving performance. The aim of our research is to explore how a course designed according to the POI approach affects students' analogical reasoning when they analyze an algorithmic problem and design a solution.