ArticleSe pu = Chinese journal of chromatography2024
[Transformation of scientific research results into teaching resources to improve the teaching effect: taking the teaching of the chromatographic method in the pharmaceutical analysis course as an example].
Article in Se pu = Chinese journal of chromatography, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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
2 citing papers in PubMed.
- [Self-designed experiment in instrumental analysis： online solid phase extraction-high performance liquid chromatography- post column derivatization for the determination of trace pesticide residues in vegetables].Se pu = Chinese journal of chromatography · 2026Article
- [Open experiment: quantitative proteomics analysis of thyroid-cancer tissue slices using ultra-high performance liquid chromatography-tandem mass spectrometry].Se pu = Chinese journal of chromatography · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The pharmaceutical analysis course is a three-dimensional knowledge network that connects several courses to form a new comprehensive knowledge node involving a large knowledge system and flexible knowledge structure. In this course, the subject of chromatography covers a wide range of topics. However, because accurate content is challenging to present, the teaching effect of this subject is poor. In this work, we sought to achieve the educational purpose of establishing morality and cultivating talent, as well as the goal of training highly skilled professionals, by taking the teaching of chromatography in the pharmaceutical analysis course as an example of transforming scientific research results into teaching resources. The resources obtained are integrated into the teaching process to provide innovative and scientific research ideas to students with the aim of not only helping them understand and master technical knowledge but also exercise their ability to raise and solve problems. Furthermore, we expound on how to introduce scientific development frontiers and formulate scientific problems through curriculum design. We also describe how our strategy can promote the teaching effect and achieve teaching objectives. Based on the characteristics of rapid knowledge update and equal emphasis on theory and practice in pharmaceutical analysis, the course is designed by introducing new advances in scientific development, formulating scientific problems, and adopting question- and problem-based learning methods for teaching. The teaching effect is then evaluated through diversified assessment, student feedback, and self-evaluation. The results show that the transformation of scientific research results into teaching resources plays a significant role in stimulating students' interest in learning, improving students' ability to solve problems, and achieving curriculum objectives, all of which greatly improve the teaching effect.
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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.