Description: Article describes best practices for teaching a course module that involves multiple parameters. A good example is hypothesis testing which requires consideration of the parameters, sample-size, population distribution, known variance and has as consequences whether a normal or t distribution should be used or whether non parametric methods are used. The articles recommends use of the Prime Implicant Normal Form as a means of teaching. It shows the superiority of this method over other forms such as heuristics, complete rules, or graduated approaches.

Description: A typical course has some "hard" parts. These "hard" parts are the places where weaker students begin to fail, lose interest, and give up. The paper introduces a metric by which to evaluate each course topic. High metric values indicate "hard parts" of courses. The paper recommends spending more course time on hard parts and less course time on easy parts. The paper also recommends using disclosure: Tell students - this part of the course is "hard" and they may feel uncomfortable which is why more time is being spent on it." This approach to hard parts works! Failure rates are significantly reduced, while retention, satisfaction, and student scores improve.

Description: This presentation proposes a solution to the student actuarial paradox “I mastered the syllabus but failed the exam,” by utilizing the two-dimensional syllabus vehicle which pedagogically focuses on the two dimensions of content and problem difficulty. This presentation advocates the PMR characterization of three levels of problems difficulty: Plug-ins (easy), Monkey-wrench (intermediate), and Research-type(hard) questions. PMR was developed by examining difficulty levels in SOA exams, and problems of various software vendors. The author's students routinely score high on the SOA FM exam; it is hoped that these methods will assist other instructors in their quest for good pedagogy. Very briefly: “Plug-ins,” refer to multi-part problems, for example, calculating the price of an annuity that is first increasing and then level; “Monkey-wrench” problems specifically refer to plug-in multi-part problems where one component is a monkey-wrench, an issue the candidate has not previously encountered. It might be a non-typical modeling or it might be a non-typical algebraic simplification or it might be an unexpected integration of distinct modules in a manner that the candidate has not yet seen. “Research-type questions” refer to problems requiring some type of experimentation for example, looking at initial cases, seeing a pattern and then applying methods