Design and Validation of Procedurally Generated Personalised Spatial Reasoning Tests

Spatial intelligence is an important predictor of success in STEM subjects, and training it has been shown to improve students' achievements in STEM subjects. It is important to assess students' spatial reasoning skills, e.g., for measuring improvements or applying targeted interventions. However, traditional spatial intelligence tests are often paper-based, are not suitable for repeated use since answers can be learned, and do not take users' abilities and limitations into account. In this paper we present a computer graphics-based approach for procedurally generating spatial intelligence tests with adjustable difficulty level. Our validation shows that the resulting tests are feasible and correlate well with traditional spatial intelligence tests. Our research will enable simplified, repeated, and personalised spatial intelligence testing and that way enable educators, developers, and decision-makers to created targeted interventions helping students to succeed in STEM subjects.

Authors

Institutions

Publication Details

Published
2024-12-04
DOI
https://doi.org/10.1109/ivcnz64857.2024.10794488
Primary Topic
Spatial Cognition and Navigation
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Design and Validation of Procedurally Generated Personalised Spatial Reasoning Tests

Nasser Giacaman, Zixuan Wang, Tim Li, Burkhard Claus Wünsche et al.
Spatial Cognition and Navigation
article

Design and Validation of Procedurally Generated Personalised Spatial Reasoning Tests

Nasser Giacaman, Zixuan Wang, Tim Li, Burkhard Claus Wünsche, Owen Xu
article en

Abstract

Spatial intelligence is an important predictor of success in STEM subjects, and training it has been shown to improve students' achievements in STEM subjects. It is important to assess students' spatial reasoning skills, e.g., for measuring improvements or applying targeted interventions. However, traditional spatial intelligence tests are often paper-based, are not suitable for repeated use since answers can be learned, and do not take users' abilities and limitations into account. In this paper we present a computer graphics-based approach for procedurally generating spatial intelligence tests with adjustable difficulty level. Our validation shows that the resulting tests are feasible and correlate well with traditional spatial intelligence tests. Our research will enable simplified, repeated, and personalised spatial intelligence testing and that way enable educators, developers, and decision-makers to created targeted interventions helping students to succeed in STEM subjects.

University of Auckland (NZ)
Openalex Percentile: Top 74%
Spatial Cognition and Navigation
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Design and Validation of Procedurally Generated Personalised Spatial Reasoning Tests — Nasser Giacaman, Zixuan Wang, et al. · (2024) | TGRS Research Map | TGRS