Comparing student science performance between hands-on and traditional item types: A many-facet Rasch analysis

Chi, Shaohui; Liu, Xiufeng; Wang, Zuhao

doi:10.1016/j.stueduc.2021.100998

Cited by 6 publications

(8 citation statements)

References 48 publications

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“…Similarly, the results obtained from the student learning achievement test at the end of the implementation of the model showed that SAS models met all the criteria. Chi, Xiu, and Zuhao (2021) conducted a study related to comparing student science and had found similar results…”

Section: Discussionmentioning

confidence: 76%

Authentic assessment development science to assess student competency

Tawil

Said²,

Suryansari³

2023

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This study aimed to examine authentic models of science assessment in assessing the competence of senior high school students who met the criteria of validity, practicality, and effectiveness. The methodology applied was an evaluation and developmental research. Research was conducted in senior high school in accordance with the needs of the development of authentic Statistical Analysis System (SAS) models. The participants were students of class X senior high school Gowa in South Sulawesi academic year 2020/2021. The instruments comprised (1) SAS model validation sheet; (2) science achievement test; (3) questionnaires; and (4) observation sheet. The findings of the quality authentic science assessment model met the validity and effectiveness criteria for high category learning outcomes with positive student responses. The practicality implications of the SAS model were also very worthy of applied science in teaching science for assessing the competence of senior high school students.

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Section: Discussionmentioning

confidence: 76%

Authentic assessment development science to assess student competency

Tawil

Said²,

Suryansari³

2023

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“…Therefore, as suggested by Linacre (1989Linacre ( , 2014, we applied the many-faceted Rasch measurement (MFRM) [also called manyfacet Rasch model (see Eckes, 2015) or multi-faceted Rasch model (see Boone et al, 2014)] that could deal with clustered testing tasks. MFRM allows test scores to be clustered according to shared features such as item type, examinee gender, raters who assigned scores to student performance (Chi et al, 2021;Eckes, 2015). MFRM can estimate each facet independently and simultaneously so that one can compare multiple facets at the same scale.…”

Section: Discussionmentioning

confidence: 99%

Assessing high‐school students' modeling performance on Newtonian mechanics

Zhai

2022

J Res Sci Teach

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Assessing scientific modeling competence (SMC) is challenging because of the multi-dimensionality of the construct and the potential variability of student performance across tasks. To deal with the challenges, this study applied Kane's validity framework to assess highschool students' SMC in Newtonian mechanics and examined how students' performance depended on tasks. We first specified students' SMC in three dimensions: Conceptualization, Deploying Scientific Knowledge, and Representation, incorporating 11 components (e.g., conceptualization of objects). We assessed 305 high-school students' modeling performance on

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“…In other words, it involves translating abstract concepts into concrete data through a standardized and unified approach for empirical measurement (Neuman, 2014). The obtained data were further analyzed quantitatively using the partial credit Rasch model analysis (Chi et al, 2021(Chi et al, , 2022.…”

Section: Methods Research Designmentioning

confidence: 99%

“…Secondly, the instruments listed above typically use multiple-choice questions or Likert-type scale items, while Rasch analysis involves analyzing the responses to each item in relation to the overall performance of individuals on the test or questionnaire. Rasch analysis also allows for the examination of item fit statistics, item difficulty, person ability, and other psychometric properties, which may not be directly assessed by the instruments listed above (Chan et al, 2021;Chi et al, 2021, Sumintono & Widhiarso, 2014. Rasch has been used to develop a number of student oriented instruments in multiple areas of science such as computational thinking, biology, and physics (Malone et al, 2021;Salibašić Glamočić et al, 2021;Sovey et al, 2022).…”

Section: Contribution To the Literaturementioning

confidence: 99%

Evaluating students’ ability in constructing scientific explanations on chemical phenomena

Laliyo,

Utina,

Husain

et al. 2023

EURASIA J Math Sci Tech Ed

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Evaluation of students’ ability in constructing scientific explanations on scientific phenomena is essential as an effort to obtain information and feedback for innovation in learning process and curriculum development. Unfortunately, this issue is still left unexplored by researchers in chemistry education. Such is presumed to occur due to validated instruments, measurements, analysis techniques, and diverse epistemological values that leave much space to be investigated. Employing a Rasch model, we intended to validate test of ability in constructing scientific explanations on chemical phenomena, examine data fit with the Rasch model, evaluate difference in the students’ ability in constructing scientific explanations, investigate items with different functions, and diagnose causes for difference in item difficulty level. The respondents were 550 students from seven senior high schools in three regencies/cities and 153 university students in Sulawesi, Indonesia. Data were collected by 30 test items; each item consisted of three questions measuring students’ ability in proposing their knowledge (Q1), evidence (Q2), and reasoning (Q3). Their responses were assessed on criteria and analyzed using the Rasch partial credit model. This model applies an individual-centered statistical approach allowing researchers to measure up to item and individual level. Results suggested that data fit the Rasch model measurement. Also, students’ ability in constructing scientific explanations varied significantly. We found no items with different functions, signifying that sex and hometown do not influence students’ ability. However, based on item logit value grouping, it was discovered that item difficulty level also varied among students. This was particularly due to students’ lack of chemistry concepts mastery that lowered their ability and accuracy in constructing scientific explanation. This shows lack of epistemological engagement of students in learning process. In conclusion, this study provides valuable insights into students’ ability to construct scientific explanations and sheds light on factors that influence their performance in this area. Findings highlight need for targeted interventions that address students’ conceptual understanding and engagement with chemistry concepts, as well as promote critical thinking and scientific reasoning skills. This has important implications for science education and can inform curriculum development and evaluation policies.

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Comparing student science performance between hands-on and traditional item types: A many-facet Rasch analysis

Cited by 6 publications

References 48 publications

Authentic assessment development science to assess student competency

Authentic assessment development science to assess student competency

Assessing high‐school students' modeling performance on Newtonian mechanics

Evaluating students’ ability in constructing scientific explanations on chemical phenomena

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