Let’s do a quick recap - map out the skills/knowledge attributes tested in the ACT/SAT, determine what proficiency levels lead to what scores, determine what interventions are most effective for a given skill gap in a given attribute, determine the student’s target score, determine his current proficiency levels in all the attributes, determine target proficiency levels (derived from target scores), determine the skill gap and finally determine the required interventions.

A caveat, however, is that this process will not be completely analytical and mathematically deterministic. A lot of “understanding” of the the student’s learning style, goals and objectives and personality will come in play and hence the role of “academic thinking” cannot be neglected in the favor of pure analysis.

After the intervention steps are determined and the delivery of the same starts, it is very important to periodically gauge the effectiveness of each of them and the actual improvement that is happening. The findings will help in mid way course correction, if required, as well as help in making the complete mapping process more robust. In a sense, this engine will be a dynamic set of activities which will “learn” from itself as it is applied to more and more students.

Thus, the perfect test prep engine has to be a dynamic combination of cold analysis, warm understanding and an ability of the engine itself to imbibe learnings from its experiences and make itself stronger in terms of determining the right set of interventions which will lead to the desired score improvement with minimum expenditure in terms of time, money and teacher/student effort.

This engine is, as of today, a theoretical concept - but it is doable. the benefits are so immense it justifies investment in such an idea. It is powerful as it combines the best in analytics with the human side of teaching and makes the system self-improving.

Concluded.