Informing Learning and Teaching Using Feedback from Assessment Data: Hong Kong Teachers’ Attitudes Towards Rasch Measurement

Ho, Chi Ming; Leung, Anthony Wai Chi; Mok, Magdalena Mo Ching; Cheung, Paisley Tsz Mei

doi:10.1007/978-94-007-4507-0_17

Cited by 3 publications

(1 citation statement)

References 25 publications

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“…The value of the current study is in its relevance to small scale studies, where, for example, a teacher needs to identify guessers in a school exam to consider remedial work for students who may be experiencing difficulties. (The work of Ho et al (2012) in using Rasch measurement with Hong Kong teachers is instructive here) Another area of possible use in where teachers are pretesting exam material, and only want to include answers by 'bona fide' respondents. Being able to eliminate certain guessers would enable pretest results to be seen to have greater validity.…”

Section: Discussionmentioning

confidence: 99%

Identifying Guessing in English Language Tests via Rasch Fit Statistics: An Exploratory Study

Coniam¹,

Lee²,

Lampropoulou³

2021

ELT

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This article explores the issue of identifying guessers – with a specific focus on multiple-choice tests. Guessing has long been considered a problem due to the fact that it compromises validity. A test taker scoring higher than they should through guessing does not provide a picture of their actual ability. After an initial description of issues associated with guessing, the article then outlines approaches which have been taken to either discourage test takers from guessing or which attempt statistically to handle the problem. From this, the article moves to a novel way of identifying potential guessers: from the post hoc use of Rasch fit statistics. Two datasets, each consisting of approximately 200 beginner level English language test takers were split into two. In each dataset, half the test takers’ answers were randomised – to approximate guessing. Results obtained via a Rasch analysis of the data was then passed to an analyst who used the Rasch fit statistics to identify possible guessers. On each dataset, 80% of guessers were identified.

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Section: Discussionmentioning

confidence: 99%

Identifying Guessing in English Language Tests via Rasch Fit Statistics: An Exploratory Study

Coniam¹,

Lee²,

Lampropoulou³

2021

ELT

View full text Add to dashboard Cite

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Student–Facing Assessment Analytics Dashboards Based on Rasch Measurement Theory

Aydın,

Bayrak,

Yurdugül

2024

Assessment Analytics in Education

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Measuring university teachers’ teaching quality: a Rasch modelling approach

Noben

Maulana

Deinum

et al. 2020

Learning Environ Res

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Insights into how university teachers develop their teaching can strengthen the effectiveness of professional learning activities. Professional learning initiatives aim to support teachers in developing a teaching profile that is focused on student learning. However, university teachers often report a combination of content- and student-focused approaches to teaching and are not systematically focused on the learning outcomes of students. Teacher development theories hypothesise teaching growth as a hierarchy in which the development of more-complex skills (student-centred teaching) is based on the easier ones. This cumulative development of university teachers’ teaching has not yet been examined in authentic learning environments. We explored whether the hierarchy can also be found in observed teaching behaviour. Rasch analysis of 203 classroom observations revealed a stage-wise ordering of the teaching skills from basic to complex, consistent with the theorised development of teaching in the literature. University teachers develop from teacher-centred to student-centred teaching by increasingly acknowledging the student in the teaching and learning process. At the same time, they aim first to gain comfort in a stage (self-focused) before improving their teaching in that development stage (focus on task). As teachers develop, they move on to student-learning focused skills, such as teaching–learning strategies.

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Informing Learning and Teaching Using Feedback from Assessment Data: Hong Kong Teachers’ Attitudes Towards Rasch Measurement

Cited by 3 publications

References 25 publications

Identifying Guessing in English Language Tests via Rasch Fit Statistics: An Exploratory Study

Identifying Guessing in English Language Tests via Rasch Fit Statistics: An Exploratory Study

Student–Facing Assessment Analytics Dashboards Based on Rasch Measurement Theory

Measuring university teachers’ teaching quality: a Rasch modelling approach

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