Description: This is an image of an example table from a MS Access database.

Description: Author advocates reconsidering the 2005 education syllabus to include the study of modern finance in the syllabus for all actuarial students, not just those specializing in finance, investments, or risk management.

Description: The Drake Risk and Insurance Workshop on Catastrophe Risk took place virtually on February 19, 2021, hosted by the School of Actuarial Science & Risk Management in the College of Business and Public Administration at Drake University. The purpose of this article is to share with the actuarial science community some experience in organizing this event amidst the COVID-19 pandemic.

Description: This article studies several pedagogical uses of tables, particularly as they apply to actuarial teaching.

Description: Report on a panel presentation in which options to maintain the solvency of Social Security are discussed.

Description: Discusses the Validation by Education Experience and how to achieve credit.

Description: This article looks at an extensive integrated collection of financial mathematical modeling packages available in R, a language and environment for statistical computing.

Description: In this article, the author discusses his transition to working as a practicing actuary to an academic.

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