Item response curve analysis of Likert scale on learning attitudes towards physics

Reyes, M G; Rakkapao, S

doi:10.1088/1361-6404/ab805c

Cited by 4 publications

(3 citation statements)

References 50 publications

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“…Gray et al found that students were least successful at identifying "physicist" responses for these two items, and that item 12 had the lowest consistency among experts [4]. Reyes and Rakkapao removed item 8 from their Item Response Curve analysis; 75% of students in their sample chose the non-expert-like response, and an expert-like response on this item correlated with less expert-like attitudes overall [21].…”

Section: B Irt Resultsmentioning

confidence: 99%

Exploring the CLASS with Item Response Theory

Christman¹,

Miller²,

Stewart³

2020

2020 Physics Education Research Conference Proceedings

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This work applied exploratory factor analysis (EFA) and graded Item Response Theory (IRT) to a large sample (N = 4522) of Colorado Learning Attitudes about Science Survey (CLASS) post-test scores. EFA failed to reproduce the factor structure suggested by the authors of the CLASS and strongly supported the alternate 3-factor model suggested by Douglas et al. Graded IRT allowed an examination of the progression from nonexpert-like to expert-like beliefs. This progression was generally uniform with a linear relation between the difficulty of each step in the progression. Some items within the factors identified by Douglas et al. had difficulty and discrimination parameters substantially different from other items in the factor suggesting the subscale is not unidimensional. The expert-like latent ability trait estimated by IRT correlated more strongly with measures of physics performance than measures of general academic performance indicating that expert-like beliefs are not a general property of high performing students.

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Section: B Irt Resultsmentioning

confidence: 99%

Exploring the CLASS with Item Response Theory

Christman¹,

Miller²,

Stewart³

2020

2020 Physics Education Research Conference Proceedings

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“…The technique also enables educators able to recognize that some correct answers are better than others. This is a very useful technique and has been used for analysing concept items for different CIs used in introductory physics, in different culture, language and educational systems (Ishimoto et al, 2017;Mashood, 2014;Morris et al, 2006;Morris et al 2012;Rakkapao et al, 2016;Reyes & Rakkapao, 2020;Richardson et al, 2021). This study also utilised the item analysis method.…”

Section: The Item Response Curvesmentioning

confidence: 99%

Development of a Circular Motion Concept Inventory for Use in Ugandan Science Education

Kirya¹,

Mashood²,

Yadav³

2024

tused

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In this study, we administered and evaluated circular motion concept question items with a view to developing an inventory suitable for the Ugandan context. Before administering the circular concept items, six physics experts and ten undergraduate physics students carried out the face and content validation. One hundred eighteen undergraduate students responded to the 42 circular motion concept items. The data were analysed using the classical test theory (CTT) and item response curve (IRC) analyses. We calculated the difficulty level and index of discrimination and gauged the distraction efficiency of items. The IRCs revealed insights that were not evident from those provided by the CTT. Based on the IRCs, the circular concept items are classified into three categories: efficient, moderately efficient, and inefficient. This helped us better evaluate the quality of the items and their appropriateness for the population under consideration. We ended up with 22 circular motion concept question items which we call the circular motion concept inventory (CMCI). This inventory is particularly relevant to Ugandan context and may be useful to other countries in the East African region which share similar syllabi.

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“…There has been much discussion of whether or how to quantify and summarize Likert scale data [22,23]. Given the preliminary nature of this paper, we take the admittedly simplistic approach of simply stating the percentage of students who choose "Agree" or "Strongly Agree" for each question.…”

Section: B Students' Attitudesmentioning

confidence: 99%

Physics students' reactions to an abrupt shift in instruction during the COVID-19 pandemic

Gavrin¹

2020

2020 Physics Education Research Conference Proceedings

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We present a preliminary analysis of the effect of the COVID-19 pandemic on students in the context of a large enrollment introductory physics course. During the spring of 2020, ours was one of thousands of courses forced to change abruptly from face-to-face instruction to online delivery. We report the effects of this change on students through the lenses initially available to us, including our online homework system, an online forum, and the course evaluations. While preliminary, our results suggest that students were generally unhappy with the transition, but this disappointment did not translate into significantly reduced effort or success. Their primary concerns were not technological but stemmed from behavioral considerations either internal to themselves or external, from the instructor. Although the event probed here was the pandemic, our observations and conclusions may be applicable to other situations in which instruction changes suddenly due to natural or human-caused disasters.

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Item response curve analysis of Likert scale on learning attitudes towards physics

Cited by 4 publications

References 50 publications

Exploring the CLASS with Item Response Theory

Exploring the CLASS with Item Response Theory

Development of a Circular Motion Concept Inventory for Use in Ugandan Science Education

Physics students' reactions to an abrupt shift in instruction during the COVID-19 pandemic

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