Forecasting Periodic Trends: A Semester-Long Team Exercise for Nonscience Majors

Team learning is an effective means of teaching that can contribute toward increased student interest. This article describes a team learning exercise developed for a course for nonscience majors. Students are randomly assigned numbers (atomic numbers) the first day of class. Each student builds a portfolio of information for their element. In the third week of the course the students meet in their teams and identify any trends that they observe from the collective data. The following week the teams present their data to the class. Between weeks three and six, the students in a team use Excel to plot a number of relationships—or example, atomic number versus atomic mass and atomic number versus atomic radii—for their chemical group. Each team uses curve fitting and statistical capabilities of spreadsheet software to produce a best-fit equation for each plot. In the second phase of the project, the formulas obtained are then used to predict missing data, such as first ionization energy, density, and so on, for elements at the bottom of their group. Further, the same sets of equations are used to complete a full profile of properties for elements yet to be discovered in the periodic table. The exercise culminates in the 12th week of the semester when, in a second student PowerPoint presentation to faculty and peers, the students demonstrate the calculated physical properties for the new elements.