The Design, Creation, and Cognitive Evaluation of Ranking Tasks in Introductory Astronomy

Authors

Emily A. Welch, University of Nebraska - LincolnFollow

First Advisor

Kevin M. Lee

Date of this Version

8-2021

Document Type

Article

Citation

Welch, E., 2021, The Design, Creation, and Cognitive Evaluation of Ranking Tasks in Introductory Astronomy. Thesis (M.S.). University of Nebrasksa - Lincoln.

Comments

A THESIS Presented to the Faculty of The Graduate College at the University of Nebraska In Partial Fulfillment of Requirements For the Degree of Master of Science, Major: Physics & Astronomy, Under the Supervision of Professor Kevin M. Lee. Lincoln, Nebraska: August, 2021

Copyright © 2021 Emily A. Welch

Abstract

Ranking tasks are a type of interactive formative assessment. They allow students to explore a concept by ranking similar situations for a specified variable, preferably without computation of that variable. I created two sets of introductory astronomy ranking tasks: the first connects the Hertzsprung–Russell (HR) diagram and the Stephan-Boltzmann luminosity equation; the second uses the transit method (TM) to rank exoplanets by comparing the depth, duration, and frequency of transits.

These tasks are designed within the constructivist pedagogical framework. They require students to call upon their own relevant schema to establish an assessment rule by which to rank the tasks. Any new information encountered in the tasks, background, or feedback must be actively assimilated or accommodated as students construct mental models of the luminosity relationship, and the nature of transiting exoplanets.

Data-driven decision making is at the heart of a good curriculum design process.I evaluated students’ use of the ranking tasks through the think-aloud method, in which students verbalize, without interpreting, their cognitive processes. This data then directed the improvement of the tasks and the fit of the cognitive model of physics problem-solving to the process of ranking. These ranking tasks are published online at https://astro.unl.edu, with many other ranking tasks that are free to use.

Adviser: Kevin M. Lee