SynthesisF1000Research2026
Systematic Review of Assessment in General Chemistry: Trends, Digital Innovations, and Integration of Theory-Laboratory Course.
Synthesis in F1000Research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Assessment in general chemistry plays an important role in supporting students' conceptual understanding and laboratory competencies. However, studies that systematically analyze and synthesize research findings related to assessment practices in both theoretical and laboratory-based general chemistry learning remain limited. Previous studies also indicate inconsistencies in the integration of assessment approaches across theoretical and practical learning contexts. Therefore, a comprehensive systematic literature review is needed to identify current trends, gaps, and future directions in general chemistry assessment research. Methods: This study employed the Systematic Literature Review (SLR) method using the PRISMA approach. Articles were collected from the Scopus database covering publications from 2020 to 2024 (n = 30). The review process included identification, screening, eligibility assessment, and inclusion of relevant studies based on predetermined criteria. The selected articles were analyzed to examine assessment strategies, assessment focus, technological innovations, and research trends in general chemistry education. Results: The findings revealed several significant trends and gaps in the literature. Research on assessment in general chemistry is still predominantly focused on theoretical learning assessment rather than laboratory assessment or the integration of both domains. In addition, summative assessment practices remain underrepresented in the reviewed studies. The review also identified the growing implementation of technology-based assessment innovations, including digital question banks, machine learning-assisted assessment systems, and interactive assessment platforms. These technologies are increasingly used to enhance assessment effectiveness, accessibility, and student engagement. Conclusion: This review highlights the need for more balanced and integrated assessment approaches that combine theoretical and laboratory learning in general chemistry education. Future studies should further explore comprehensive assessment models that incorporate both formative and summative dimensions supported by technological innovations. The findings of this study provide evidence-based insights for educators, researchers, and policy makers in designing more innovative, relevant, and inclusive assessment practices to improve learning outcomes in general chemistry education.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.