Max van der Velde, Wieke Harmsen, Bernard P Veldkamp, Remco Feskens, Jos Keuning, Nicole Swart
{"title":"Speech Enabled Reading Fluency Assessment: a Validation Study.","authors":"Max van der Velde, Wieke Harmsen, Bernard P Veldkamp, Remco Feskens, Jos Keuning, Nicole Swart","doi":"10.1007/s40593-025-00480-y","DOIUrl":null,"url":null,"abstract":"<p><p>Although the ability to comprehend what one is reading is one of the most fundamental necessities to function within society, the reading comprehension skills of students have recently been on the decline in many countries. An essential prerequisite to reading comprehension is the ability to read fluently, which is defined as the ability to read (aloud) with accuracy, speed, automaticity and prosody. Current oral reading fluency assessment instruments seldom provide detailed diagnostics however, and bestow a heavy testing burden on practitioners. Recent developments in Artificial Intelligence-based assessment methodology might provide a solution to current assessment issues, but thorough validations of such procedures have proven scarce. This study evaluates whether valid word decoding and passage reading measures (accuracy, speed and automaticity) can be generated for a semi-transparent language, using an automatic speech recognition (ASR) based oral reading fluency assessment instrument. A validation study was conducted, using the Argument-Based Approach to Validation. Data concerned 176 h of speech data, and the results of 569 and 622 oral word- and passage reading tests that are currently administered in primary schools, from 653 children attending the second- or third grade of Dutch primary education. The results of the validation indicate that it is possible to generate fluency metrics for a semi-transparent language, using an ASR-based oral reading fluency assessment instrument. Future researchers are advised to further optimize the ASR, evaluate its errors, and realize a prosody component, completing the envisioned reading fluency assessment instrument, thereby improving reading fluency assessment throughout primary education.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1007/s40593-025-00480-y.</p>","PeriodicalId":46637,"journal":{"name":"International Journal of Artificial Intelligence in Education","volume":"35 4","pages":"2569-2595"},"PeriodicalIF":10.1000,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12686063/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Artificial Intelligence in Education","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s40593-025-00480-y","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/5/14 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0
Abstract
Although the ability to comprehend what one is reading is one of the most fundamental necessities to function within society, the reading comprehension skills of students have recently been on the decline in many countries. An essential prerequisite to reading comprehension is the ability to read fluently, which is defined as the ability to read (aloud) with accuracy, speed, automaticity and prosody. Current oral reading fluency assessment instruments seldom provide detailed diagnostics however, and bestow a heavy testing burden on practitioners. Recent developments in Artificial Intelligence-based assessment methodology might provide a solution to current assessment issues, but thorough validations of such procedures have proven scarce. This study evaluates whether valid word decoding and passage reading measures (accuracy, speed and automaticity) can be generated for a semi-transparent language, using an automatic speech recognition (ASR) based oral reading fluency assessment instrument. A validation study was conducted, using the Argument-Based Approach to Validation. Data concerned 176 h of speech data, and the results of 569 and 622 oral word- and passage reading tests that are currently administered in primary schools, from 653 children attending the second- or third grade of Dutch primary education. The results of the validation indicate that it is possible to generate fluency metrics for a semi-transparent language, using an ASR-based oral reading fluency assessment instrument. Future researchers are advised to further optimize the ASR, evaluate its errors, and realize a prosody component, completing the envisioned reading fluency assessment instrument, thereby improving reading fluency assessment throughout primary education.
Supplementary information: The online version contains supplementary material available at 10.1007/s40593-025-00480-y.
期刊介绍:
IJAIED publishes papers concerned with the application of AI to education. It aims to help the development of principles for the design of computer-based learning systems. Its premise is that such principles involve the modelling and representation of relevant aspects of knowledge, before implementation or during execution, and hence require the application of AI techniques and concepts. IJAIED has a very broad notion of the scope of AI and of a ''computer-based learning system'', as indicated by the following list of topics considered to be within the scope of IJAIED: adaptive and intelligent multimedia and hypermedia systemsagent-based learning environmentsAIED and teacher educationarchitectures for AIED systemsassessment and testing of learning outcomesauthoring systems and shells for AIED systemsbayesian and statistical methodscase-based systemscognitive developmentcognitive models of problem-solvingcognitive tools for learningcomputer-assisted language learningcomputer-supported collaborative learningdialogue (argumentation, explanation, negotiation, etc.) discovery environments and microworldsdistributed learning environmentseducational roboticsembedded training systemsempirical studies to inform the design of learning environmentsenvironments to support the learning of programmingevaluation of AIED systemsformal models of components of AIED systemshelp and advice systemshuman factors and interface designinstructional design principlesinstructional planningintelligent agents on the internetintelligent courseware for computer-based trainingintelligent tutoring systemsknowledge and skill acquisitionknowledge representation for instructionmodelling metacognitive skillsmodelling pedagogical interactionsmotivationnatural language interfaces for instructional systemsnetworked learning and teaching systemsneural models applied to AIED systemsperformance support systemspractical, real-world applications of AIED systemsqualitative reasoning in simulationssituated learning and cognitive apprenticeshipsocial and cultural aspects of learningstudent modelling and cognitive diagnosissupport for knowledge building communitiessupport for networked communicationtheories of learning and conceptual changetools for administration and curriculum integrationtools for the guided exploration of information resources