Development and validation of a university students’ progression in learning quantum mechanics through exploratory factor analysis and Rasch analysis

Testa, Italo; Capasso, Gianmarco; Colantonio, Arturo; Galano, Silvia; Marzoli, Irene; Uccio, U. Scotti di; Trani, F.; Zappia, Alessandro

doi:10.1080/09500693.2018.1556414

Cited by 22 publications

(17 citation statements)

References 72 publications

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“…One possible conclusion is that the participants did not think about the spectrum experiment as purely quantummechanical. This would align with previous work showing that many university students at a variety of educational levels apply mixed quantum and classical concepts in thinking about models that explain atomic spectra [7,15,16]. Indeed, participants drew on measurement principles and physical limitations in the spectrum experiment with similar frequency to the ball-drop experiment and on measurement limitations and physical principles similarly to the single-slit experiment.…”

Section: Discussionsupporting

confidence: 68%

Student reasoning about sources of experimental measurement uncertainty in quantum versus classical mechanics

Stump¹,

White²,

Passante³

et al. 2020

2020 Physics Education Research Conference Proceedings

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Measurement uncertainty and experimental error are important concepts taught in undergraduate physics laboratories. Although student ideas about error and uncertainty in introductory classical mechanics lab experiments have been studied extensively, there is relatively limited research on student thinking about experimental measurement uncertainty in quantum mechanics. In this work, we used semi-structured interviews to study advanced physics students' interpretations of fictitious data distributions from two common undergraduate laboratory experiments in quantum mechanics and one in classical mechanics. To analyze these interpretations, we developed a coding scheme that classifies student responses based on what factors they believe create uncertainty and differentiates between different types of uncertainty (e.g. imprecision, inaccuracy). We found that participants in our study expressed a variety of ideas about measurement uncertainty that varied with the context (classical/quantum) and the type of uncertainty.

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Section: Discussionsupporting

confidence: 68%

Student reasoning about sources of experimental measurement uncertainty in quantum versus classical mechanics

Stump¹,

White²,

Passante³

et al. 2020

2020 Physics Education Research Conference Proceedings

View full text Add to dashboard Cite

show abstract

“…To provide complementary information about the psychometric properties of the SaPS-SF, both confirmatory factor analysis (CFA) and Rasch analysis (Rasch, 1960) were employed. This approach has been used in many empirical studies (e.g., Deneen et al, 2013;Hart et al, 2013;Primi et al, 2014;Yan, 2016;West et al, 2018;Testa et al, 2019) for the benefit of providing comprehensive scrutiny of the psychometric qualities of instruments.…”

Section: Discussionmentioning

confidence: 99%

Developing a Short Form of the Self-Assessment Practices Scale: Psychometric Evidence

Yan

2020

Front. Educ.

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This research aimed to develop a short form of the Self-assessment Practices Scale (SaPS). Guided by a process model of self-assessment, the SaPS scale was designed to assess the actions students engage in during the self-assessment process. The data used for developing the original 20-item SaPS (SaPS-20), i.e., 1,416 Hong Kong students ranging from Primary 4 to Secondary 3, were reanalyzed, and a 12-item short form (SaPS-SF) was developed. Factor analysis and Rasch analysis were applied in complementary ways to examine the psychometric properties of the SaPS-SF. The results showed that factor structure of the original scale held in the SaPS-SF, and all items fitted the Rasch model requirements sufficiently and measured the constructs as theorized. The findings presented in this study facilitate the measurement of self-assessment practice in a parsimonious and effective way.

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“…This combined analytical approach has been used in recent empirical studies (e.g. Hart et al ., 2013; Primi et al ., 2014; Testa et al ., 2019; West et al ., 2018; Yan, 2018b, 2020a) for the benefit of providing supplementary information about the psychometric properties of instruments.…”

Section: Methodsmentioning

confidence: 99%

Psychometric properties of the Self‐assessment Practice Scale for professional training contexts: evidence from confirmatory factor analysis and Rasch analysis

Yan

Brubacher

Boud

et al. 2020

Int J Training Development

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Self-assessment is a fundamental skill for professionals because self-assessment can promote self-regulated learning and professional development. However, studies reporting the use of self-assessment instruments in the professional training context are scarce. This study aimed to re-evaluate the psychometric properties of the Self-assessment Practice Scale (SaPS), which was originally developed in the school context, and extend its use to the professional training context. A sample of 200 investigative interviewer trainees from Australia and North America were invited to complete the modified SaPS. After removing misfitting items, the confirmatory factor analysis results confirmed a first-order four-factor solution. The multidimensional Rasch analysis demonstrated that the resultant 16 items had satisfactory fit to the Rasch model. In general, the results supported the use of the 16-item modified SaPS as a valid measure for the sample in this study. The potential of using the SaPS in professional training contexts is discussed.

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Development and validation of a university students’ progression in learning quantum mechanics through exploratory factor analysis and Rasch analysis

Cited by 22 publications

References 72 publications

Student reasoning about sources of experimental measurement uncertainty in quantum versus classical mechanics

Student reasoning about sources of experimental measurement uncertainty in quantum versus classical mechanics

Developing a Short Form of the Self-Assessment Practices Scale: Psychometric Evidence

Psychometric properties of the Self‐assessment Practice Scale for professional training contexts: evidence from confirmatory factor analysis and Rasch analysis

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