Educational Measurement-Issues and Practice

Scope & Guideline

Empowering Researchers to Enhance Measurement Practices.

Introduction

Immerse yourself in the scholarly insights of Educational Measurement-Issues and Practice with our comprehensive guidelines detailing its aims and scope. This page is your resource for understanding the journal's thematic priorities. Stay abreast of trending topics currently drawing significant attention and explore declining topics for a full picture of evolving interests. Our selection of highly cited topics and recent high-impact papers is curated within these guidelines to enhance your research impact.
LanguageEnglish
ISSN0731-1745
PublisherWILEY
Support Open AccessNo
CountryUnited Kingdom
TypeJournal
Convergefrom 1982 to 2024
AbbreviationEDUC MEAS-ISSUES PRA / Educ. Meas.-Issues Pract.
Frequency4 issues/year
Time To First Decision-
Time To Acceptance-
Acceptance Rate-
Home Page-
Address111 RIVER ST, HOBOKEN 07030-5774, NJ

Aims and Scopes

The journal 'Educational Measurement: Issues and Practice' is dedicated to advancing the field of educational measurement through rigorous research and practical applications. It encompasses a wide range of topics related to assessment theory, practice, and policy, making significant contributions to understanding and improving educational measurement processes.
  1. Educational Assessment Theory:
    Focuses on the foundational theories underpinning educational measurement, including validity, reliability, and fairness in assessments.
  2. Large-Scale Assessment Practices:
    Examines the methodologies and implications of large-scale assessments, including standardized testing and program evaluations.
  3. Technological Innovations in Measurement:
    Explores the integration of technology in educational assessment, such as automated item generation, machine learning applications, and digital assessment tools.
  4. Cultural and Social Considerations:
    Investigates the impact of cultural and social factors on educational assessment practices, promoting equity and inclusivity in measurement.
  5. Professional Development in Measurement:
    Addresses the training and competencies required for measurement professionals, emphasizing the importance of ongoing professional development in the field.
The journal has seen an increase in themes that reflect current trends and emerging issues in educational measurement. These areas highlight the evolving nature of the field and its response to contemporary challenges.
  1. Machine Learning and AI in Assessment:
    There is a growing interest in the application of machine learning and artificial intelligence in educational measurement, particularly in areas such as automated scoring and data analysis.
  2. Equity and Social Justice in Measurement:
    Recent publications emphasize the need for equity and social justice in educational assessments, addressing issues of bias and advocating for culturally responsive measurement practices.
  3. Impact of COVID-19 on Assessment Practices:
    The pandemic has generated significant research on the effects of remote assessments and the validity of different assessment methods during and after COVID-19, revealing new insights into educational measurement.
  4. Professional Competencies for Measurement Practitioners:
    An increasing focus on defining and developing foundational competencies for educational measurement professionals, highlighting the need for adaptive skills in a changing job market.
  5. Holistic Approaches to Assessment:
    Emerging themes include holistic and multidimensional approaches to assessment, which consider broader aspects of student learning and development beyond traditional score-based evaluations.

Declining or Waning

As the field of educational measurement evolves, certain themes have become less prominent in recent publications. This section highlights those areas that appear to be waning in relevance or frequency within the journal's focus.
  1. Traditional Assessment Formats:
    There is a noticeable decline in research focused solely on traditional assessment formats, such as paper-and-pencil tests, as the field shifts towards more innovative and technology-enhanced assessment methods.
  2. Generalized Assessment Models:
    The emphasis on generalized models of assessment is decreasing, with a greater focus on specific methodologies like machine learning and diagnostic classification models that provide more nuanced insights.
  3. Static Validity Arguments:
    Research centered on static validity arguments is becoming less common, as the field moves towards dynamic and contextualized approaches to validity that consider the complexities of educational settings.

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