Riyan Hidayat
Universiti Putra Malaysia, Selangor, Malaysia

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Development of mathematics learning based on computational thinking for primary school teachers Zetra Hainul Putra; Neni Hermita; Jesi Alexander Alim; Muhammad Fendrik; Riyan Hidayat; Zaldi Harfal; Lara Oktarisa; Nasri; Sahlan; Ucy Rahmayani Nursyam; Fatmawilda
Transformasi: Jurnal Pengabdian Masyarakat Vol. 19 No. 2 (2023): Transformasi Desember
Publisher : LP2M Universitas Islam Negeri Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20414/transformasi.v19i2.8430

Abstract

[Bahasa]: Keterampilan Computational Thinking (Berpikir Komputasi) merupakan salah satu keterampilan abad 21 yang perlu dimiliki oleh siswa sekolah dasar. Mengingat pentingnya CT dan masih banyak guru-guru yang belum mengetahui dan menguasai keterampilan ini, maka diperlukan kegiatan workshop yang dapat mendukung keterampilan CT guru dan juga mampu merancang pembelajaran matematika berbasis CT. Oleh karena itu, tim PkM FKIP UNRI berkolaborasi dengan UPM Malaysia melaksanakan workshop pengembangan pembelajaran matematika berbasis CT bagi guru-guru sekolah dasar di Kecamatan Tambang, Kabupaten Kampar, Provinsi Riau. Metode pelaksanaan PkM menggunakan Participatory Action Research (PAR) dengan pendekatan blended learning. Kegiatan workshop diikuti oleh 33 orang guru dari 3 sekolah dasar di Kecamatan Tambang. Kegiatan workshop ini mampu meningkatkan keterampilan CT guru-guru, namun perlu tindak lanjut kegiatan sehingga keterampilan CT guru bisa lebih optimal dan mampu menerapkannya dalam pembelajaran matematika di kelas masing-masing.  Kata Kunci: keterampilan computational thinking, pembelajaran matematika, workshop [English]: Computational Thinking (CT) skills are crucial for elementary school students in the 21st century. Recognizing the significance of CT and the prevalent lack of knowledge and mastery among teachers, there is a need for workshop activities that can support teachers in developing CT skills and enable them to design CT-based mathematics learning. To address this gap, the FKIP UNRI community service team collaborated with UPM Malaysia to conduct a workshop on CT-based mathematics learning development for elementary school teachers in the Tambang Sub-district, Kampar Regency, Riau Province. The implementation method of this community service utilized Participatory Action Research (PAR) with a blended learning approach. Thirty-three teachers from three elementary schools in the district participated in the workshop. While the workshop successfully enhanced teachers' CT skills, subsequent activities are essential to optimize these skills further and facilitate their application in mathematics learning within their respective classrooms. Keywords: computational thinking skills, mathematics learning, workshops
Evaluating Students’ Artificial Intelligence Literacy: Development of an Assessment Instrument Based on Experiential Learning Elements Ahmad Ahmad; Lasi Purwito; R. Anggia Listyaningrum; Riyan Hidayat
Indonesian Journal of Instruction Vol. 6 No. 3 (2025): September
Publisher : Universitas Pendidikan Ganesha

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23887/iji.v6i3.105603

Abstract

Artificial Intelligence (AI) literacy has become an essential competency for students in responding to rapid digital transformation across various fields. However, the limited availability of valid and reliable assessment instruments constrains the comprehensive evaluation of students’ AI literacy levels. This study aims to analyze, develop, and validate an AI literacy assessment instrument based on experiential learning elements and a deep learning approach. The study employed a Research and Development (R&D) design consisting of needs analysis, instrument design, development, validation testing, and data analysis stages. The research involved 500 students selected through multistage sampling techniques. Data were collected using an AI literacy questionnaire designed to measure three main components: knowledge, affective attitudes, and critical thinking skills, which are integrated with global competencies required in the 21st century. Construct validity was examined using factor analysis, while reliability was assessed through internal consistency analysis. The findings indicate that the developed instrument demonstrates strong validity and reliability and effectively represents the multidimensional structure of AI literacy. These results suggest that the instrument can function as a reliable assessment tool for evaluating students’ readiness to understand, utilize, and critically reflect on AI technologies in an ethical and responsible manner. The study provides important implications for higher education institutions in integrating AI literacy assessment into teaching practices and curriculum development.