Modern Psychometrics for Digital Assessment in Education
A special issue of Education Sciences (ISSN 2227-7102). This special issue belongs to the section "Education and Psychology".
Deadline for manuscript submissions: 31 December 2026 | Viewed by 477
Editors
Interests: diagnostic classification modelling; cognitive diagnosis assessment; differential item functioning; validation of achievement and psychological data
Interests: educational measurement and psychometrics; item response theory; cognitive diagnostic models; data science methods
Special Issue Information
Dear Colleagues,
Education Sciences is pleased to announce the Special Issue Modern Psychometrics for Digital Assessment in Education. The rapid expansion of digital learning environments, online testing platforms, and AI-driven educational technologies has created unprecedented opportunities—and challenges—for assessment in education. Traditional psychometric approaches are being reimagined to meet the demands of adaptive testing, large-scale online assessments, and data-rich digital ecosystems (e.g., response time).
This Special Issue aims to highlight cutting-edge research that applies modern psychometric theories and methods to digital assessment contexts. We invite authors to submit original research articles that explore methodological innovations, theoretical advances, and practical applications of psychometrics in technology-enhanced learning and assessment. Submissions should emphasize how psychometric approaches can improve validity, reliability, fairness, and equity in digital assessment contexts, while also addressing implications for practice in educational assessment.
We particularly encourage the submission of interdisciplinary work that bridges psychometrics, educational measurement, learning analytics, data science, and educational technology.
Research areas include, but are not limited to, the following:
- Application of modern psychometric models (e.g., IRT, Rasch, Bayesian approaches, diagnostic classification modelling) to digital assessments;
- Adaptive testing and computerized diagnostic assessment design;
- Response time modelling in digital testing environments;
- Validity and reliability studies in online and technology-enhanced testing environments;
- Psychometric approaches to large-scale digital achievement data (e.g., TIMSS, PISA, PIRLS, TALIS);
- Integration of learning analytics and psychometrics for personalized assessment;
- Equity, fairness, and bias detection in digital assessments;
- Methodological advances in automated scoring and AI-based assessment;
- Cross-cultural and multilingual psychometric studies in digital contexts;
- Practical implications of psychometric innovations in digital assessment.
Dr. Yi-Hsin Chen
Dr. Xin Qiao
Guest Editors
Emma E. Evudottir
Guest Editor Assistant
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a double-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Education Sciences is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- psychometrics
- digital assessment
- educational measurement
- adaptive testing
- item response theory
- rasch models
- bayesian methods
- learning analytics
- AI in psychometrics
- response time analysis
- fairness and equity
- validity and reliability
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