xA: The dynamics of student reasoning during an interview
Sessions: PA (8:45 - 10) and RA (2 - 3:15)
Organizer: Sanjay Rebello, Kansas State University
Presenters:
Alicia R. Allbaugh, Kansas State University
Paula V. Engelhardt, Kansas State University
Kara E. Gray, Kansas State University
Zdeslav Hrepic, Kansas State University
Salomon F. Itza-Ortiz, Kansas State University
Luanna G. Ortiz, Arizona State University
Andy Terrel, Texas Tech University
Beth Ann Thacker, Texas Tech UniversityDiscussant
N. Sanjay Rebello, Kansas State University
Researchers have long used interviews to investigate students’ internal knowledge structures. In an interview it sometimes seems that a student is building her/his reasoning on the spot, often adopting and rejecting explanations. A student’s response may be a product of the interaction of her/his internal knowledge structure with external cues from the interview materials and/or interviewer. An interview may be an effective way to study the dynamics of students’ reasoning.
In this targeted poster session we discuss the processes by which university students’ reasoning patterns evolve during an interview. Our research spans several topical areas and our research participants include physical science, life-science, engineering and non-science majors in at least three different institutions. We focus on the ways in which students assemble various knowledge elements in a dynamic process of knowledge construction during an interview. These sense-making processes are examined in contexts that include situations similar to textbook problems, demonstrations, experiments, applications to real-world devices, and everyday phenomena.
Many researchers have used theoretical frameworks spanning a wide range of grain sizes to describe student knowledge from disjointed phenomenological primitives to comprehensive theories. We examine whether and how these frameworks can be adapted to explain the dynamics of student reasoning.
In summary, this targeted poster session is an attempt toward better understanding the process of how student piece together their reasoning during an interview. The posters together will address the following research questions.
Individual abstracts:
"Student reasoning during an interview: A possible framework & implications"*
Alicia R. Allbaugh, Kansas State University
Paula V. Engelhardt, Kansas State University
Kara E. Gray, Kansas State University
Zdeslav Hrepic, Kansas State University
Salomon F. Itza-Ortiz, Kansas State UniversityThis poster set proposes a framework to characterize the processes of student reasoning during an interview, and discusses implications of the framework. The interviews on which this framework is based were conducted by five researchers, with different research goals. The research participants are enrolled in various introductory physics courses at KSU.
From our interview transcripts we have constructed a framework involving four aspects: [1] External Inputs (e.g. questions asked, verbal, graphic and other cues) from the interviewer and interview environment; [2] Tools (e.g. memorized and familiar formulae, laws and definitions, prior experiences) that the student brings to the interview; [3] Workbench encompassing mental processes (e.g. induction, accommodation) that incorporate the aforementioned inputs and tools; and [4] Answer given by the student.
We have used a coding scheme to map out reasoning paths through the four aspects of our framework. Our analysis finds remarkable commonality between students’ reasoning paths in different contexts as well as interesting patterns depending upon the question type, topical area etc. Based on these observed patterns we discuss the implications of our framework to elucidate the dynamics of student reasoning and its potential to inform the construction of interview protocols.
* Supported in part by National Science Foundation grants REC-0087788 and REC-0133621.
"Prompting students to be consistent during individual demonstration interviews"*
Luanna G. Ortiz, Arizona State University
Individual demonstration interviews often involve simple physical demonstrations, about which students are asked to make predictions. The interviews typically have a predetermined protocol, with a series of specific questions that are asked of all participants. As part of an investigation conducted at the University of Washington on student understanding of rotational dynamics, we have included questions that we envision using in instructional materials on the equilibrium of rigid bodies [1]. Student responses have been analyzed to determine the effectiveness of the questions [2]. In this presentation, I will focus my analysis on the degree of consistency retained by science and engineering majors over the course of such an interview. Generalizations of apparent reasoning processes identified among the students will be discussed.
*This research has been conducted by the Physics Education Group at the University of Washington and supported in part by the NSF Grants DUE 9354501 and DUE 9727648, which include support from the Division of Undergraduate Education, other Divisions of EHR and the Physics Division of MPS.
[1] Ortiz, L.G., “Identifying and addressing student difficulties with rotational dynamics,” Ph.D. Dissertation, Department of Physics, University of Washington, 2001, (unpublished).
[2] See, for example, McDermott, L.C., “Research on conceptual understanding in mechanics,” Phys. Today 37, 24 (1984), as well as papers on empirical studies that appear in McDermott, L.C. & Redish, E.F., “Resource Letter: PER-1: Physics Education Research,” Amer. J. Phys. 67, 755 (1999).
"Exploring the structure and dynamics of students’ reasoning during interviews on topics in modern physics"
Andy Terrel, Texas Tech University
Beth Ann Thacker, Texas Tech UniversityKnowledge structures that students assemble to explain physical phenomena have been proposed to consist of knowledge elements (building blocks) of various grain sizes. We have analyzed interviews of students in a modern physics class to see if we can identify knowledge elements of various types and grain sizes that students use in an attempt to construct a coherent knowledge structure. We also examine the process by which students assemble various knowledge elements, to see if we can gain insight into the dynamics of knowledge construction, focusing on the context and cues that trigger various cognitive elements.
"A framework for student reasoning in an interview"*
Paula V. Engelhardt, Kara E. Gray, Zdeslav Hrepic, Salomon F. Itza-Ortiz, Alicia R. Allbaugh, N. Sanjay Rebello & Dean A. Zollman, Kansas State University
We propose a framework to characterize students’ reasoning in an interview. The framework is based on interview data collected by five researchers, with different research goals. The participants were enrolled in various introductory physics courses at Kansas State University. Our framework includes external inputs (e.g. questions asked, verbal, graphic and other cues) from the interviewer and interview environment; tools (e.g. memorized or familiar formulae, laws and definitions, prior experiences) that the student brings to the interview; a workbench encompassing mental processes (e.g. induction, accommodation) that incorporate the inputs and tools; and the answer given by the student. We describe how the framework can be used to analyze interview data.
* Supported in part by NSF Grants REC-0087788 and REC-0133621.
"Implications of a framework for student reasoning in an interview"*
Kara E. Gray, Zdeslav Hrepic, Salomon F. Itza-Ortiz, Alicia R. Allbaugh, Paula V. Engelhardt, N. Sanjay Rebello & Dean A. Zollman, Kansas State University
We discuss the implications of a framework to characterize student reasoning in an interview. Our framework, described in a previous paper, enables a researcher to identify various cognitive elements used by a student during an interview. Here we demonstrate how this framework can help identify reasoning paths used by the students. We describe the underpinnings of our framework in cognitive psychology. We also discuss how this framework can be applied to both a coarse and fine grain analysis of reasoning and how it can also be used to infer implicit reasoning processes used by a student.
* Supported in part by NSF Grants REC-0087788 and REC-0133621.
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