
Metrologically coherent assessment for learning: what, why and how
Author(s) -
Emily Pey-Tee Oon,
U. Hoi-Ka,
William P. Fisher
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1379/1/012040
Subject(s) - formative assessment , context (archaeology) , construct (python library) , metric (unit) , class (philosophy) , mathematics education , psychology , assessment for learning , educational assessment , computer science , artificial intelligence , paleontology , operations management , economics , biology , programming language
Assessment for learning aims to improve learning by feeding back information on the attainment of intended learning objectives to students and teachers. In this form of assessment, the student acts as a measuring instrument and learning attainment is the quantity to be measured. Current practices in classroom assessment, unfortunately, often are not grounded and have been focused on total correct scores without reference to the evidence hidden within them concerning the attainment of learning objectives. Our goal in this study is to clarify what assessment for learning is, why it is important, and how it works in a metrologically coherent context of equated assessments administered from calibrated item banks. The main focus lies in how item content can be framed according to intended learning outcomes that are meaningfully interpreted using a construct map. An example involves empirical datasets of 283 secondary three students from two formative tests designed by two science teachers. Coherent formative assessment of this kind applies a scientific model that belongs to the same class metrologists consider as defining measurement. The results illuminate the potential for establishing item banks that enable teachers to more efficiently and effectively assess and improve the attainment of learning objectives across different cohorts of students in a common metric.