This paper describes an action research for developing better algorithmic thinking in introductory programming courses. Enhancing algorithmic thinking and improving problem solving skills are the main objectives of such courses and are considered a significant success factor in future courses as well as future work achievements. Furthermore, failing to develop these skills, usually leads to failures in these introductory courses as well as the courses that follow. As part of this action research, that was performed during four semesters several course structures and learning tactics were examined. The evaluation methodology was simple and based only on the percentage of failing students. The success achieved was attributed to two main factors (1) using a visualization environment (Micro-world) for the whole duration of the course, which helped in understanding the more complex and abstract issues, and (2) using individual assignments that enforced better learning habits and development of individual algorithmic thinking. The paper describes the various attempts, as well as the final structure, that reduced the failing students by over 77%. This paper describes an action research for developing better algorithmic thinking in introductory programming courses. Enhancing algorithmic thinking and improving problem solving skills are the main objectives of such courses and are considered a significant success factor in future courses as well as future work achievements. Furthermore, failing to develop these skills, usually leads to failures in these introductory courses as well as the courses that follow. As part of this action research, that was performed during four semesters several course structures and learning tactics were examined. The evaluation methodology was simple and based only on the percentage of failing students. The success achieved was attributed to two main factors (1) using a visualization environment (Micro-world) for the whole duration of the course, which helped in understanding the more complex and abstract issues, and (2) using individual assignments that enforced better learning habits and development of individual algorithmic thinking. The paper describes the various attempts, as well as the final structure, that reduced the failing students by over 77%.

E-learning, Technology, evaluation