JOURNAL OF EDUCATIONAL MEASUREMENT
Scope & Guideline
Pioneering Research in Educational Measurement
Introduction
Aims and Scopes
- Psychometrics and Measurement Theory:
The journal emphasizes psychometric principles, exploring various models like Item Response Theory (IRT) and Diagnostic Classification Models to ensure reliable and valid assessments. - Innovative Assessment Methodologies:
It focuses on new methodologies for educational measurement, including adaptive testing, automated scoring systems, and the integration of AI and machine learning in assessment practices. - Validity and Reliability of Assessments:
A key area of interest is the validity and reliability of educational assessments, including discussions on argument-based validity and score comparability across different contexts. - Data Analysis Techniques:
The journal promotes advanced data analysis techniques for interpreting educational measurement data, including Bayesian methods, multilevel modeling, and response time analysis. - Equity in Assessment:
The journal addresses issues of fairness and equity in assessments, investigating differential item functioning (DIF) and the impact of cultural and demographic factors on test performance.
Trending and Emerging
- Automated and AI-Based Scoring Systems:
There is a growing interest in the development and validation of automated scoring systems, particularly those leveraging artificial intelligence, to enhance the efficiency and reliability of assessments. - Multimodal and Process Data Analysis:
Emerging methodologies that analyze multimodal data, including process data from digital assessments and the integration of eye-tracking and response time metrics, are becoming more prominent. - Differential Item Functioning (DIF) and Fairness:
Research on DIF remains a critical area of focus, with increasing attention to ensuring fairness in assessments across diverse populations, particularly in the context of high-stakes testing. - Cognitive Diagnostic Models (CDMs):
There is an upward trend in the application of cognitive diagnostic models to better understand student learning and to provide more nuanced feedback about their skills and knowledge. - Integration of Educational Technology in Assessment:
The journal highlights themes surrounding the integration of technology in educational assessments, focusing on how digital tools can enhance measurement accuracy and engagement.
Declining or Waning
- Traditional Measurement Models:
There has been a noticeable decline in publications focused solely on classical test theory (CTT) methods, as more researchers are gravitating towards modern approaches like IRT and Bayesian methods. - Generalized Linear Models (GLM):
The specific application of generalized linear models for educational assessments is less frequently discussed, with a shift towards more complex modeling techniques that incorporate multiple dimensions and covariates. - Item Analysis Techniques:
The focus on basic item analysis methods appears to be waning, as researchers increasingly explore sophisticated analyses involving response time and cognitive processes. - Standardized Testing Practices:
Research on traditional standardized testing practices is becoming less common, likely due to growing critiques and calls for more innovative and adaptive assessment strategies.
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