Of teachers and textbooks: lower secondary teachers' perceived importance and use of chemistry textbook components

数学教育 课程 一致性(知识库) 感知 化学 内容分析 心理学 计算机科学 教育学 社会学 社会科学 人工智能 神经科学
作者
Karel Vojíř,Martin Rusek
出处
期刊:Chemistry Education. Research and Practice [Royal Society of Chemistry]
卷期号:23 (4): 786-798 被引量:16
标识
DOI:10.1039/d2rp00083k
摘要

According to research findings from all over the world, textbooks play an important role for teachers in the choice of methods, content and educational goals. However, the open textbook market, where the state's influence is limited, results in a significant gap between the state (written) curriculum and actual classroom practice. To understand this phenomenon in more detail, teachers’ ( N = 387) conception of lower-secondary chemistry textbooks was evaluated, based on their perception and use of particular textbook components. Data obtained with an online questionnaire were subjected to a thorough analysis using CRISP-DM data mining methodology. The results showed a high consistency in chemistry teachers’ perception of textbooks and also that only a limited number of textbook components are frequently being used in teaching practice. The vast majority of teachers mentioned using textbook content to prepare lessons, which indicated textbooks’ influence over lesson content. The other most frequently used components are graphical representations, questions and tasks. Textbook components which can be used to apply a student-centred approach are considered less important by the majority of teachers, which confirms the persisting teacher-centred approach in chemistry teaching. The results also helped identify textbook components whose innovation could have the highest impact on education (educational illustrations, structured text, photographs and tasks). This study therefore sheds more light on chemistry teaching, as well as bringing important knowledge to new textbook authors. The data mining methodology proved useful in this sort of research, showing multiple relations which would not be considered in standard data analysis.
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