Application of Network Analysis to Description and Prediction of Assessment Outcomes

Periodical
Measurement: Interdisciplinary Research and Perspectives
Volume
20
Year
2022
Issue number
3
Page range
121-138
Access date
May 31, 2023
Relates to study/studies
PIAAC Cycle 1

Application of Network Analysis to Description and Prediction of Assessment Outcomes

Abstract

With the use of computerized testing, ordinary assessments can capture both answer accuracy and answer response time. For the Canadian Programme for the International Assessment of Adult Competencies (PIAAC) numeracy and literacy subtests, person ability, person speed, question difficulty, question time intensity, fluency (rate), person fluency (skill), question fluency (load), pace (rank of response time within question), and person pace were assessed. Undirected Gaussian Graphical Model networks of the measures based on partial correlations were predictive of the measures as nodes. The population-based model extrapolated well to individual person estimations. Finally, it was shown that the “training” Canadian model generalized with minor differences to four other English-speaking PIAAC assessments (USA, Great Britain, Ireland, and New Zealand). Thus, the undirected network approach provides a heuristic that is both descriptive and predictive. However, the model is not causal and can be taken as an example of “mutualism.”