Development of Deep Learning-Based Student Worksheets for Christian Religious Education and Ethics in Shaping Critical and Creative Thinking Patterns in Senior High School
DOI:
https://doi.org/10.61132/ijcep.v3i2.551Keywords:
Christian Religious Education and Character Education, Creativity, Critical Thinking, Deep Learning, LKPDAbstract
Development research combined with the Rowntree model to produce a Student Worksheet product for Christian religious education and character education based on deep learning in forming critical and creative thinking patterns in phase F of class XI at SMAN 1 Sigi, aims to find out the steps for developing LKPD, the effectiveness and feasibility of LKPD in encouraging critical and creative thinking patterns of students consisting of three stages, namely planning, development, and evaluation. The product testing stage, starting with expert testing; material, language, and media. Then the product was tested on 4 students for one-on-one evaluation and 30 people for field evaluation. The results of the study showed an average value of material experts 4.2 considered very good, language experts 4.6 very good, and media experts 4.8 considered very good. The student trial stage, the average result of the individual test stage was 95.6% which means the product was considered very good, the field trial stage 83.69% very good. The results of the pretest and posttest showed an increase in the percentage of learning completeness of 30.79%. The percentage of divergent student creativity tests was 21.1%,critical reasoning tests were 21.1%, meaning that creativity and critical thinking skills had been formed and increased after studying the LKPD learning materials. The conclusion is that the LKPD learning materials for Christian religious education and character education based on deep learning are very good, suitable for use and need to be maintained because they can form critical thinking patterns and increase student creativity.
Keywords: LKPD; Christian Religious Education and Character Education; Deep Learning; Critical Thinking; Creativity
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