**Type:** Empirical

**Purpose:** To determine which cognitive factors and fundamental algorithms that have been previously researched can be used to assess the aptitude of students taking an introductory programming and algorithm course. A second purpose for the study is to find out which cognitive factors and fundamental algorithms can be used in devising strategies for more effective learning in introductory CS courses. The main focus throughout is to find correlations between cognitive factors, algorithmic skills and actual class performance of novice learners around the topic of algorithms.

**Findings:** The moderate correlation (.566, p=.000) between Induction and Spatial Scanning corresponds to Factor 4 Correlated Cognitive. The high correlation (r=.859, p=.000) between Linear Search and Binary Search, small correlation (r=.390, p=.013) between Linear Search and Maze Tracing, and moderate correlation (r=.465, p=.002) between Binary Search and Maze Tracing corresponds to the Time factor. A moderate correlation (.511, p=.001) between Insertion Sort and Selection Sort corresponds to Factor 1 Related Algorithm.

**Recommendations:** Authors were investigating the correlations of cognitive factors, fundamental algorithms, and class performance regarding algorithms. The results may be used to assess the aptitude of students enrolled in an introductory programming and algorithm course ti predict success in the course.

**Sample Size:** 40

**Participant Type:** Participants in this study were high school students enrolled in an Information Systems Course at Tokyo Tech H.S.