Model analysis of fine structures of student models: An example with Newton’s third law

Bao, Lei; Hogg, Kirsten; Zollman, Dean

doi:10.1119/1.1484152

Cited by 87 publications

(89 citation statements)

References 17 publications

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“…6,27,30,31 To study the dynamical process of students' applying their models, we first define two important concepts: common models and student model states.…”

Section: B Organization Of Long-term Memorymentioning

confidence: 99%

Model analysis: Representing and assessing the dynamics of student learning

Bao

Redish

2006

Phys. Rev. ST Phys. Educ. Res.

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136

149

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Decades of education research have shown that students can simultaneously possess alternate knowledge frameworks and that the development and use of such knowledge are context dependent. As a result of extensive qualitative research, standardized multiple-choice tests such as Force Concept Inventory and ForceMotion Concept Evaluation tests provide instructors tools to probe their students' conceptual knowledge of physics. However, many existing quantitative analysis methods often focus on a binary question of whether a student answers a question correctly or not. This greatly limits the capacity of using the standardized multiplechoice tests in assessing students' alternative knowledge. In addition, the context dependence issue, which suggests that a student may apply the correct knowledge in some situations and revert to use alternative types of knowledge in others, is often treated as random noise in current analyses. In this paper, we present a model analysis, which applies qualitative research to establish a quantitative representation framework. With this method, students' alternative knowledge and the probabilities for students to use such knowledge in a range of equivalent contexts can be quantitatively assessed. This provides a way to analyze research-based multiple choice questions, which can generate much richer information than what is available from score-based analysis.

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“…6,27,30,31 To study the dynamical process of students' applying their models, we first define two important concepts: common models and student model states.…”

Section: B Organization Of Long-term Memorymentioning

confidence: 99%

Model analysis: Representing and assessing the dynamics of student learning

Bao

Redish

2006

Phys. Rev. ST Phys. Educ. Res.

Self Cite

136

149

View full text Add to dashboard Cite

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“…On the other hand, the dynamic group focuses on students' understanding about the cases in which bodies are moving. For example, cases in contact include the collision situation between a car and a small truck, or between a bomb and a missile, or between two identical marbles, as well as the pushing situation in which a small car pushes a large one or a student on rollers pushes another student (Watts & Zylberszajn, 1981;Brown, 1989;Gamble, 1989;Kruger, Summers & Palacio, 1990a, 1990bSummers, 1992;Thijs, 1992;Montanero, Perez & Suero, 1995;Trumper, 1996;Heywood & Parker, 2001;Bao, Hogg, & Zollman, 2002;Savinainen, & Scott, 2002;Savinainen, Scott, & Viiri, 2005). While, there are some studies referring to interaction objects at distant, e.g.…”

Section: Literature Reviewmentioning

confidence: 99%

Students’ Understanding on Newton’s Third Law in Identifying the Reaction Force in Gravity Interactions

Zhou

Zhang

Xiao

2015

EURASIA J MATH SCI T

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In the past three decades, previous researches showed that students had various misconceptions of Newton's Third Law. The present study focused on students' difficulties in identifying the third-law force pair in gravity interaction situations. An instrument involving contexts with gravity and non-gravity associated interactions was designed and conducted among students in junior secondary school, senior high school and university. The finding revealed that students in all grades did statistically worse in gravity interaction contexts and had general difficulties in distinguishing interaction forces and balanced forces. However, students improved their reasoning on third-law force pair with the increase of grade level irrespective of contexts. Special difficulties for junior secondary school students in understanding gravity interaction were also addressed. It is important to emphasize that the educational contexts of gravity interactions should be paid more attention to.

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“…Both of these outcomes would produce subpopulations of students who apply both the correct model and an incorrect model depending on the situation. Work on characterizing the subgroup structure of classes [34] and understanding the features of the misconceptions that influence that structure [35] are evolving, so specific implications for instruction for the above cases do not yet exist. It would be very interesting to determine the features of a course that produces this shift in consistency.…”

Section: Implications For Instructionmentioning

confidence: 99%

“…IV offers a rich platform for investigating model analysis. The following uses the notation introduced by Bao in [37] and summarized in Bao et al [35].…”

Section: A Model Analysismentioning

confidence: 99%

“…It was found that 74%-82% of the students were associated with a single subgroup for both the pretest and the posttest in both a course using traditional instruction and a course using modified instruction; however, the students in the nontraditional course much more consistently applied the correct model than the students in the traditional course. The method was also used to explore the structure of students' understanding of Newton's third law, and it was found that detailed features of Newton's third law problems involving whether the objects were stationary, moving, or accelerating generated student subgroups with very different properties [35].…”

Section: Introductionmentioning

confidence: 99%

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Using cluster analysis to identify patterns in students’ responses to contextually different conceptual problems

Stewart

Miller

Audo

2012

Phys. Rev. ST Phys. Educ. Res.

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This study examined the evolution of student responses to seven contextually different versions of two Force Concept Inventory questions in an introductory physics course at the University of Arkansas. The consistency in answering the closely related questions evolved little over the seven-question exam. A model for the state of student knowledge involving the probability of selecting one of the multiple-choice answers was developed. Criteria for using clustering algorithms to extract model parameters were explored and it was found that the overlap between the probability distributions of the model vectors was an important parameter in characterizing the cluster models. The course data were then clustered and the extracted model showed that students largely fit into two groups both pre-and postinstruction: one that answered all questions correctly with high probability and one that selected the distracter representing the same misconception with high probability. For the course studied, 14% of the students were left with persistent misconceptions post instruction on a static force problem and 30% on a dynamic Newton's third law problem. These students selected the answer representing the predominant misconception slightly more consistently postinstruction, indicating that the course studied had been ineffective at moving this subgroup of students nearer a Newtonian force concept and had instead moved them slightly farther away from a correct conceptual understanding of these two problems. The consistency in answering pairs of problems with varied physical contexts is shown to be an important supplementary statistic to the score on the problems and suggests that the inclusion of such problem pairs in future conceptual inventories would be efficacious. Multiple, contextually varied questions further probe the structure of students' knowledge. To allow working instructors to make use of the additional insight gained from cluster analysis, it is our hope that the physics education research community will make these methods available though their Web sites.

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Model analysis of fine structures of student models: An example with Newton’s third law

Cited by 87 publications

References 17 publications

Model analysis: Representing and assessing the dynamics of student learning

Model analysis: Representing and assessing the dynamics of student learning

Students’ Understanding on Newton’s Third Law in Identifying the Reaction Force in Gravity Interactions

Using cluster analysis to identify patterns in students’ responses to contextually different conceptual problems

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