Method for Measuring Physical-Virtual Learning Environments for Deep Learning in Science Education Nurul Qomariyah Ahmad (a), Iva Sarifah (a) and Wardani Rahayu (a)
(a) Research and Evaluation of Education Programme, Postgraduate School, Universitas Negeri Jakarta, Jakarta,Indonesia
Abstract
Physical-virtual learning environments such as blended learning and the flipped classroom are increasingly common in science education, but assessment methods for evaluating deep learning in these hybrid environments remain limited. This study systematically reviews existing measurement methods in accordance with the PRISMA 2020 guidelines. Following a structured search and screening of the Scopus database, eight relevant articles were identified for analysis. This review maps five main types of instruments, namely: self-report questionnaires, standardized tests, quantitative observation rubrics, Learning Management System (LMS) log analysis, and comprehensive multi-component assessment systems. These instruments measure the cognitive, intrapersonal, and learning strategy dimensions of deep learning, each possessing its own strengths and weaknesses in application. The primary gap identified is the scarcity of psychometrically validated instruments specifically designed for the unique dynamics of the blended physical-virtual context. These findings underscore the need for an integrated multimodal assessment approach, rather than merely adapting generic tools. By providing a roadmap for the development of more sensitive evaluation instruments, this study directly supports the advancement of high-quality, technology-adaptive assessment practices, in line with Sustainable Development Goal (SDG) 4.
Keywords: PRISMA, a physical-virtual learning environment, deep learning, science education, SDG 4
