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Dynamic Assessment, Intelligence and Measurement

Raegan Murphy

University College Cork, Ireland

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To George and Memory Murphy. We are, none of us, victims of our biographies!

About the Author

Raegan Murphy is a lecturer in the School of Applied Psychology at University College Cork, Ireland. A native South African, she moved to Ireland in 2008 after leaving her position as lecturer in the Department of Psychology at University of Pretoria, South Africa.

She is a registered research psychologist and psychometrist in South Africa and a registered psychologist in Ireland and the United Kingdom. She lectures Individual Differences, Organizational Psychology and Research Methods to undergraduates and Multivariate Data Analysis to postgraduates.

She is currently undertaking research in the area of intelligence, dynamic assessment, measurement and neuropsychological performance of executive functioning. She has published in peer reviewed journals and has presented across the globe.

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My initial interest in dynamic assessment was spurred by the realization that although the field of intelligence research has a venerable history in the psychological literature, intelligence as a concept is still fuzzy. This is not necessarily a bad thing. When I engaged with the literature in dynamic assessment I found a similar fuzziness pervading it. Intelligence is a construct that is measured and dynamic assessment is a method of assessment. Conceptually, they are different. Dynamic assessment is a tool, intelligence is the area studied and measurement is the manner in which intelligence is measured. It became evident that in order to study the nature of assessment properly and its measurement techniques and the domain of application, an exploration of these concerns was necessary.

Dynamic assessment as an alternative process-based assessment is currently at a crossroads chiefly characterized by, at times, a vague conceptualization of terminology, blurred demarcation as to its model and theory status and, at times, an ill-defined fundamental philosophy. As a movement in modern psychological assessment within the broader field of intelligence, dynamic assessment does not present with a coherent unifying theory as such and, due to its lack of clarity in a number of key areas, its eventual disuse might well be the final outcome of this method and its unique history and methodology. In this book assessment models and theories are critically explored by means of a meta-theory largely inspired by the work K. B. Madsen, a Danish meta-theorist and pioneer in theoretical psychology. Madsen’s meta-theory is attenuated to better analysis of dynamic assessment within intelligence research and assessment.

The book builds on a foundation of epistemological and ontological considerations within science in general and the social sciences and psychology in particular. Dynamic assessment and intelligence are discussed and a brief digression into the history of Soviet psychology is offered as it is pertinent to the work of Lev Vygotsky and his subsequent influence within process-based assessment. Theory and model development within science and the social sciences are described from a philosophy of science vantage point. Psychological assessment’s prime considerations are critically explored and the discussion highlights the role played by the philosophical aspects of mathematics and statistical foundations as leveraging measurement within assessment.

Particular attention is paid to the perennial controversy surrounding null hypothesis significance testing and the possible future directions that can be explored by and within dynamic assessment, which lends itself to approaches less restrictive than those offered by mainstream statistics. Various concerns within the mathematical, statistical and measurement foundations are critically explored in terms of how best dynamic assessment can manoeuvre within the current mainstream psychological assessment system and how new models of item-response theory suited to change-based assessment can be explored as a possible way of handling the gain score issue, itself a paradoxical state of affairs in classical and modern test theory.

Dynamic assessment’s past has in large part been dictated by mainstream considerations in the areas mentioned and, in order to place it on an alternative path, these considerations are critically assessed in terms of dynamic assessment’s future path. Dynamic assessment and its place within the broader intelligence assessment field are then investigated by means of the meta-theory developed. It is envisaged that the intuitive appeal of dynamic assessment will continue to gain support from practitioners across the globe, specifically those trained in countries outside the traditional stronghold of Western psychological theory.

However, the position taken in this argument is that, in order to ensure its survival, it will need to make a decision in terms of its future progress: either to branch off from mainstream assessment altogether or become fixed within mainstream assessment. The ‘best of both worlds’ scenario has obviously not worked out in the way originally envisaged. In conclusion, a meta-theoretical exploration of dynamic assessment within intelligence is discussed by utilizing a sample of current models. The application of the attenuated Madsenian framework seeks to explore, place and ascertain the nature of each model regarding the ontological and philosophical status of the approach: the nature of the hypothetical terminology, scientific hypotheses and hypothesis system utilized and the nature of the abstract data, concrete data and prime considerations as implicit concerns within the varied approaches.

A hypothesis quotient score is calculated for each such model and is a partial indicator of the testability (verifiability or falsifiability) of the model in question. The models are thus couched in meta-, hypothetical and data strata and can be positioned on a continuum of sorts according to which tentative claims can be made regarding the veracity of the approach behind each model. It is hoped that this text will aid in aligning dynamic assessment in a manner such that its eventual place in psychological assessment will be solidly grounded, theoretically defensible and viable as alternative manner of assessment.

Raegan Murphy

Cork, Ireland


ACFS (application of cognitive functions scale)
ACIL (adaptive computer-assisted intelligence learning test battery)
ADAFI (adaptive sequential learning test)
ADANA (adaptive analogy learning test)
APA (American Psychological Association)
ARLT (analogical reasoning learning test)
AZAFO (adaptive number sequence learning test)
CAT (computer adaptive testing)
CMB (cognitive modifiability battery)
CTT (classical test theory)
DA (dynamic assessment)
DN (deductive-nomological)
g (general intelligence factor)
HQ (hypothesis quotient)
IQ (intelligence quotient)
IRT (item-response theory)
LEM (learning potential test for ethnic minorities)
LIR (learning potential for inductive reasoning)
LLRA (linear logistic latent trait model with relaxed assumptions)
LLT (Leipzig learning test)
LPAD (Learning Propensity Assessment Device)
LPCM (Linear Partial Credit Model)
MDS (multidimensional scaling)
MLE (mediated learning experience)
MRMLC (multidimensional Rasch model for learning and change)
NHST (null hypothesis significance testing)
PBI (process-based instruction)
Raven’s (Raven Advanced Progressive Matrix Test)
RCMLM (random coefficients multinomial logit model)
SCM (structural cognitive modifiability)
S-CPT (Swanson-cognitive processing test)
TFSI (Task Force on Statistical Inference)
WM (working memory)
WSSA (weighted smallest space analysis)
ZPD (zone of proximal development)