Comparative characteristics of models and methods for assessing learning outcomes (based on materials from English-language studies of the 20th century)

Introduction. The development of assessment models since the 20th century has shown a promising direction in tracking students’ achievements and obtaining results for their further professional growth. As society’s needs evolve, so does the need for training and forming the necessary knowledge, skills and abilities in a specific field of activity (educational, scientific and research). Data on achievements under modern conditions can be obtained using assessment methods, which are most often used in combination. The research is devoted to the analysis of the characteristics of models and methods of assessing educational and scientific achievements in the context of the transformation of pedagogical approaches. Relevance is due to the need to adapt assessment to the requirements of the information society and the competence-based approach, which contributes to the development of critical thinking, motivation and competencies of students. Methods. Analytical and comparative methods, systematisation and classification of data, as well as theoretical analysis were used. Fundamental models (B. Bloom, E. G. Guba, D. Kirkpatrick, M. Scriven, D. L. Stufflebeam, R. Tyler, J. Phillips) and assessment methods (diagnostic, formative, self-assessment, mutual assessment, criterion-referenced, summative) were studied. Results. Each model and method have specific strengths and weaknesses. The combined use of methods such as diagnostic and formative assessment to support learning, self-assessment and mutual assessment to develop reflection, as well as criterion-referenced and summative assessment to ensure objectivity, creates effective hybrid assessment systems. Conclusion. The results underline the importance of an integrated approach to assessment to achieve educational goals. Future research prospects are linked to the integration of digital technologies and artificial intelligence for the personalisation of assessment processes.