Using a Ranking Task coupled with Think-Aloud Interviews to Characterize Upper-Division Students' Use of Scientific Models and Model Components in Quantum Chemistry

Co-Author(s)

Beck, Jordan

Research Mentor(s)

Muniz, Marc

Description

The development of students' modeling practices is crucial for their success as future professionals in the scientific community. Quantum chemistry is a domain in which there are many challenges for learners including, but not limited to, the abstract nature of the subject and the high levels of mathematization required to fully engage in the modeling practice. Our initial work on characterizing students' scientific modeling practices in this domain has uncovered significant fragmentation of students' understanding, and general difficulties related to choosing appropriate model components (e.g. mathematical expressions). Based on these findings, we have developed and piloted a quantum chemistry ranking task which asks participants to use a four-point Likert scale to characterize the applicability of various models and model components to quantum mechanical problems at the physical chemistry level. Participants were asked to explain their selections for each item immediately after they completed it. The participants consisted of upper-division students in quantum chemistry at a large, public regional comprehensive university, as well as faculty members who are content experts. Descriptive statistics were employed to compare novice vs. expert responses, and literature-grounded coding scheme was used to generate qualitative descriptions of the data. Results were interpreted through the lenses of theoretical frameworks for fragmented knowledge structures and novice/expert approaches to organizing knowledge.

Document Type

Event

Start Date

18-5-2017 12:00 PM

End Date

18-5-2017 3:00 PM

Department

Chemistry

Genre/Form

student projects; posters

Subjects – Topical (LCSH)

Quantum chemistry; Knowledge management

Type

Image

Rights

Copying of this document in whole or in part is allowable only for scholarly purposes. It is understood, however, that any copying or publication of this documentation for commercial purposes, or for financial gain, shall not be allowed without the author's written permission.

Language

English

Format

application/pdf

This document is currently not available here.

Share

COinS
 
May 18th, 12:00 PM May 18th, 3:00 PM

Using a Ranking Task coupled with Think-Aloud Interviews to Characterize Upper-Division Students' Use of Scientific Models and Model Components in Quantum Chemistry

The development of students' modeling practices is crucial for their success as future professionals in the scientific community. Quantum chemistry is a domain in which there are many challenges for learners including, but not limited to, the abstract nature of the subject and the high levels of mathematization required to fully engage in the modeling practice. Our initial work on characterizing students' scientific modeling practices in this domain has uncovered significant fragmentation of students' understanding, and general difficulties related to choosing appropriate model components (e.g. mathematical expressions). Based on these findings, we have developed and piloted a quantum chemistry ranking task which asks participants to use a four-point Likert scale to characterize the applicability of various models and model components to quantum mechanical problems at the physical chemistry level. Participants were asked to explain their selections for each item immediately after they completed it. The participants consisted of upper-division students in quantum chemistry at a large, public regional comprehensive university, as well as faculty members who are content experts. Descriptive statistics were employed to compare novice vs. expert responses, and literature-grounded coding scheme was used to generate qualitative descriptions of the data. Results were interpreted through the lenses of theoretical frameworks for fragmented knowledge structures and novice/expert approaches to organizing knowledge.