Analisis Pengetahuan Matematika, Didaktika, dan Teknologi Calon Guru Sekolah Dasar Menggunakan Rasch Model
DOI:
https://doi.org/10.31980/mosharafa.v10i3.667Keywords:
pengetahuan didaktika, pengetahuan matematika, pengetahuan teknologi, rasch model, didactical knowledge, mathematical knowledge, technological knowledgeAbstract
Pengetahuan matematika, didaktika, dan teknologi yang harus dimilik oleh calon guru dan guru, sebelumnya diukur dengan metode classical test theory (CTT), namun memiliki keterbatasan. Penelitian bertujuan mengetahui pengetahuan tersebut dengan metode yang diprekdiksi lebih akurat yaitu item response theory (IRT) dari rasch model. Metode penelitian meliputi survey pengetahuan matematika dan didaktika serta survey pengetahuan teknologi menggunakan angket. Subjek penelitian yaitu 38 mahasiswa tahun kedua calon guru sekolah dasar dari sebuah institusi pendidikan guru sekolah dasar di Pekanbaru. Hasil studi menunjukkan calon guru sekolah dasar memiliki pengetahuan matematika dan teknologi cukup baik, namun pengetahuan didaktika sangat rendah. Analisis pengetahuan calon guru menggunkan rasch model mampu memberikan gambaran tingkat kesulitan soal/item yang diberikan, tingkat pengetahuan responden, dan interaksi antar responden dan antar soal. Institusi pendidikan perlu mengembangkan pembelajaran bagi calon guru sekolah dasar yang mampu mendukung penguatan dan pengembangan pengetahuan matematika, didaktika, dan teknologi.
Knowledge of mathematics, didactics, and technology that must be owned by pre-service and in-service teachers, previously measured by the classical test theory (CTT) but has limitations. Study aims to determine that knowledge with a more accurate prediction method using the item response theory (IRT) from the Rasch model. Study used a survey of mathematical and didactic knowledge, and a survey of technological knowledge with a scale. The subjects were 38 second-year students from an elementary school teacher education institution in Pekanbaru. This study indicates that pre-service teachers have relatively sufficient mathematics and technological knowledge, but they lacked didactic knowledge. Analysis of pre-service teachers’ knowledge using the Rasch model can provide an overview of the difficulty level of the items given, the level of pre-service teachers’ knowledge, and the interaction between respondents and between questions. Institutions need to develop learning instruction for pre-service teachers that can support the strengthening and development of their mathematical, didactic, and technological knowledge.
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