Validating the Research-Based Early Math Assessment (REMA) among rural children in Southwest United States

Alkhadim, Ghadah S.; Cimetta, Adriana; Marx, Ronald W.; Cutshaw, Christina A.; Yaden, David B.

doi:10.1016/j.stueduc.2020.100944

Cited by 8 publications

(7 citation statements)

References 17 publications

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“…It may be worthwhile investigating whether deleting these elements improves the measuring qualities of the ZSTD scores in future investigations. However, the fulfilment of other measures suggested the neglect of the high ZSTD score (Alkhadim et al, 2021). In the adopted STEM application constructs, the Rasch modelling results likewise revealed a considerable dispersion of measures over the logit scale in item difficulty level.…”

Section: Discussionmentioning

confidence: 94%

“…The examination of item fit statistics, such as mean square (MNSQ) and correlation points (Pt Mean Corr), provides evidence of construct validity (Table 4). Mean square (MNSQ) indicated the size of the discrepancies (i.e., randomness) while correlation points (Pt Mean Corr) tested the partial correlation of each item with the total measure score, separation statistics and item reliability (Alkhadim et al, 2021). For MNSQ, a value of 0.5-1.5 was accepted, and for Point Measure Right, a score of 0.4-0.85 was accepted.…”

Section: Item Fit Statisticsmentioning

confidence: 99%

See 1 more Smart Citation

Rasch Validation of Instrument Measuring Gen-Z Science, Technology, Engineering, and Mathematics (STEM) Application in Teaching during the Pandemic

Qudratuddarsi

Hidayat

Shah

et al. 2022

IJLTER

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The impact of the Covid-19 pandemic has had a far-reaching effect on higher education institutions, and individual student assessments have garnered much attention during the pandemic. This study aimed to validate Science, Technology, Engineering, and Mathematics (STEM) application instruments using the Rasch analysis employing Winsteps version 3.73. A survey was conducted with 201 respondents from two provinces in Indonesia. The students were selected by convenience sampling and answered the adopted STEM application instrument. The STEM application instruments were adapted, and these were divided into seven sub-constructs derived from STEM disciplines. Rasch Modelling was employed for data analysis using Winsteps version 3.7.3 to analyse reliability, separation, item fit statistics, unidimensionality, and rating scale calibration. Each sub-construct fulfilled a minimum of 0.65 for Cronbach alpha, item, and person reliability, and most of them had more than 1.5 person and item separation. In general, each item had a good score of the mean square, Z-tolerated standard, and point measure correlation, indicating fulfilment of the Rasch measurement model. The analysis also showed unidimensionality assumption and an excellent rating scale. This study contributed to the body of STEM knowledge by using Rasch Modelling to test the validity and reliability of STEM application instruments.

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Section: Discussionmentioning

confidence: 94%

Section: Item Fit Statisticsmentioning

confidence: 99%

Rasch Validation of Instrument Measuring Gen-Z Science, Technology, Engineering, and Mathematics (STEM) Application in Teaching during the Pandemic

Qudratuddarsi

Hidayat

Shah

et al. 2022

IJLTER

View full text Add to dashboard Cite

show abstract

“…The items would be flagged if the items were wrongly answered by the students with an ability equivalent to the difficulty measure of the items. Thus, infit reflects the construct validity of the test (Alkhadim et al, 2021). The outfit statistic is sensitive to the discrepancies of responses on the items with difficulty far away from students' ability due to carelessness or guessing.…”

Section: Discussionmentioning

confidence: 99%

Validating the Cognitive Diagnostic Assessment and Assessing Students’ Mastery of ‘Parallel and Perpendicular Lines’ Using the Rasch Model

Chin

Meng

Yew

et al. 2022

Participatory Educational Research

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‘Parallel and Perpendicular Lines’ is an important topic that serves as a basis for the learning of a more advanced geometric concept in later years. Yet, this topic is hard to master by the students. To pinpoint students’ weaknesses in this topic, this study sought to develop a cognitive diagnostic assessment (CDA) to assess students’ mastery of ‘Parallel and Perpendicular Lines’. The validation of the CDA and the use of CDA in measuring students’ mastery of ‘Parallel and Perpendicular Lines’ was documented in this article. The content validation involved two subject matter experts, while the pilot test involved 154 Year Four students from Kedah state of Malaysia selected using cluster sampling. The experts' consensus on the relevancy of test items was captured by calculating the content validity index. The psychometric properties of items and reliability of assessment were analysed based on Rasch Measurement Model. The validity of the assessment content was supported with an acceptable content validity index of 1.00 (>.80). The findings of Rasch analysis span across all ranges of abilities level and hence fit students’ competence well. With an acceptable person separation index of 1.58 (> 1.50), person separation reliability of .74 (>.70), and KR-20 coefficient of .78 (>.70), the CDA developed is reliable. The findings of assessing students’ mastery level highlighted their weaknesses in defining the properties of perpendicular lines and drawing perpendicular lines. The findings of this study would encourage practitioners to utilise it in the mathematics classroom for diagnosing students’ weaknesses and hence plan for remedial instruction.

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“…The evaluation of item fit statistics is the evidence of construct validity namely mean square (MNSQ) and Correlation Points (Pt Mean Corr). The former fit statistics showed the size of the discrepancies (i.e., randomness) and the latter examined the partial correlation of each item with the total measure score, item reliability, and separation statistics (Alkhadim et al, 2021). The accepted score is .5-1.5 for MNSQ and 0.4-0.85 for Pt Measure Right (Boone et al, 2014).…”

Section: Item Fit Statisticsmentioning

confidence: 99%

“…The high outfit MNSQ reflected the lucky guesses (i.e., correct response to hard items) or careless mistakes (i.e., incorrect response to easy items). To fulfil the misfit detection, it is reported that the mathematical modelling attitude scale in the Malaysian context measures correlation ranging from .51-.83, indicating the alignment between students' attitudes and responses to the item (Alkhadim et al, 2021).…”

Section: Item Fit Statisticsmentioning

confidence: 99%

Validation of the Mathematical Modeling Attitude Scale for Malaysian Mathematics Teachers

Hidayat

Idris

Qudratuddarsi

et al. 2021

EURASIA J Math Sci Tech Ed

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This work sets out to examine the validity and reliability of the Mathematical Modeling Attitude Scale (MMAS), a instrument measuring teachers' attitude towards mathematical modeling. A cross-sectional survey research was utilised to describe the validity and reliability of the MMAS. The population of the present study focused on Malaysian mathematics teacher in primary and secondary schools (N = 171) and this was achieved using convenience sampling. Exploratory factor analysis (EFA), confirmatory factor analysis (CFA) and Rasch analysis were utilised in analysing the data in the present work. EFA revealed that the data from the teachers had a fourfactor structure: constructivism, relevance and real-life, understanding and motivation and interest. The CFA confirmed that the model fit indices established the four-factor structure of the first-and second-order model. Although the Rasch analysis generally supported the finding of EFA and CFA, there was still room for improvement in terms of the rating scale and DIF criterion.

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Validating the Research-Based Early Math Assessment (REMA) among rural children in Southwest United States

Cited by 8 publications

References 17 publications

Rasch Validation of Instrument Measuring Gen-Z Science, Technology, Engineering, and Mathematics (STEM) Application in Teaching during the Pandemic

Rasch Validation of Instrument Measuring Gen-Z Science, Technology, Engineering, and Mathematics (STEM) Application in Teaching during the Pandemic

Validating the Cognitive Diagnostic Assessment and Assessing Students’ Mastery of ‘Parallel and Perpendicular Lines’ Using the Rasch Model

Validation of the Mathematical Modeling Attitude Scale for Malaysian Mathematics Teachers

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