Electronic Theses and Dissertation

Aja Nurkhalilah. (2026). Analisis Kemampuan Technological Pedagogical Content Knowledge (TPACK)-Artificial Intelligence (AI) Mahasiswa Pendidikan Kimia FKIP USK. [Skripsi. Universitas Syiah Kuala]. Di bawah bimbingan Drs. M. Nasir, M.Si dan Dr. Sri Winarni, S.Pd., M.Pd.

Tuntutan pendidikan abad ke-21 yang mengharuskan guru mengintegrasikan teknologi secara adaptif, namun rendahnya kemampuan adaptasi terhadap perkembangan digital sering kali membuat pembelajaran kimia terasa monoton dan kurang relevan. Penelitian ini bertujuan untuk menganalisis tingkat penguasaan komponen Technological Pedagogical Content Knowledge (TPACK) berbasis Artificial Intelligence (AI), mengidentifikasi komponen paling dominan dalam membentuk kemampuan tersebut, serta menganalisis perbedaan tingkat penguasaan antara komponen pengetahuan dasar (CK, PK, TK) dengan komponen pengetahuan terintegrasi (PCK, TCK, TPK, TPACK) pada mahasiswa Pendidikan Kimia FKIP USK. Jenis penelitian yang digunakan adalah kuantitatif. Populasi penelitian mencakup 71 mahasiswa, dengan sampel sebanyak 35 mahasiswa Angkatan 2021 yang telah menyelesaikan mata kuliah microteaching dan Pengenalan Lapangan Persekolahan (PLP), yang dipilih melalui purposive sampling. Instrument penelitian terdiri atas angket TPACK (35 butir pernyataan) dan lembar penilaian dokumentasi video pembelajaran yang telah dinyatakan valid melalui uji ahli dengan nilai CVI 0,92 dan koefisien IRA 76,9%. Data dianalisis menggunakan perangkat lunak SmartPLS 4. Hasil penelitian menunjukkan bahwa seluruh komponen TPACK mahasiswa berada pada kategori tinggi, dengan skor tertinggi pada Technological Content Knowledge (TCK) sebesar 4,102 dan Pedagogical Knowledge (PK) sebagai yang terendah sebesar 3,834. Analisis video pembelajaran menunjukkan keunggulan signifikan pada Kegiatan Inti (KI) dengan skor 4,82, namun menunjukkan kelemahan pada Kegiatan Penutup (KP). Hasil Path Coefficients membuktikan bahwa Technological Pedagogical Knowledge (TPK) merupakan faktor paling dominan dengan nilai sebesar 0,610. Berdasarkan hasil tersebut, mahasiswa Pendidikan Kimia USK dinyatakan memiliki kesiapan pengetahuan yang baik untuk mengintegrasikan AI dalam konteks pengajaran kimia, namun diperlukan penguatan lebih terarah pada aspek manajemen kelas, khususnya pada fase evaluasi dan refleksi pembelajaran.

Kata Kunci: Technological Pedagogical Content Knowledge (TPACK), Artificial Intelligence (AI), Pendidikan Kimia, SmartPLS4, Calon Guru, CVI, IRA

Aja Nurkhalilah. (2026). Analysis of the Technological Pedagogical Content Knowledge (TPACK)-Artificial Intelligence (AI) Competencies of Chemistry Education Students at FKIP USK. [Skripsi. Universitas Syiah Kuala]. Under Direction of Drs. M. Nasir, M.Si and Dr. Sri Winarni, S.Pd., M.Pd. The demands of 21st-century education, which require teachers to integrate technology adaptively, coupled with a lack of adaptability to digital developments, often make chemistry lessons feel monotonous and irrelevant. This study aims to analyse the level of mastery of Artificial Intelligence (AI)-based Technological Pedagogical Content Knowledge (TPACK) components, identify the most dominant components in shaping these abilities, and analyse the differences in the level of mastery between basic knowledge components (CK, PK, TK) and integrated knowledge components (PCK, TCK, TPK, TPACK) among Chemistry Education students at the Faculty of Teacher Training and Education, USK. The research design employed was quantitative. The study population comprised 71 students, with a sample of 35 students from the 2021 intake who had completed the microteaching and School Field Introduction (PLP) courses, selected via purposive sampling. The research instruments consisted of a TPACK questionnaire (35 items) and a video lesson documentation assessment sheet, both of which had been validated through expert review with a CVI value of 0.92 and an IRA coefficient of 76.9 per cent. The data were analysed using SmartPLS 4 software. The results of the study indicate that all components of the students’ TPACK fell into the high category, with the highest score in Technological Content Knowledge (TCK) at 4.102 and the lowest in Pedagogical Knowledge (PK) at 3.834. Analysis of the instructional videos revealed significant strengths in the Core Activities, with a score of 4.82, but indicated weaknesses in the Closing Activities. The results of the path coefficients confirm that Technological Pedagogical Knowledge (TPK) is the most dominant factor, with a value of 0.610. Based on these results, USK Chemistry Education students are deemed to possess a good level of knowledge readiness to integrate AI into the context of chemistry teaching; however, more targeted reinforcement is required in the area of classroom management, particularly during the evaluation and reflection phases of learning. Keywords: Technological Pedagogical Content Knowledge (TPACK), Artificial Intelligence (AI), Chemistry Education, SmartPLS4, Prospective Teachers, CVI, IRA