Syamsidar HS, Samsinar S

Efektivitas Artificial Intelegence (AI) pada Pembelajaran Sains dan Agama untuk Meningkatkan Kemandirian Belajar Mahasiswa

Introduction

Efektivitas artificial intelegence (ai) pada pembelajaran sains dan agama untuk meningkatkan kemandirian belajar mahasiswa. Kaji efektivitas AI (ChatGPT, Gemini) pada pembelajaran sains dan agama. AI positif tingkatkan kemandirian belajar, berpikir kritis, dan kreativitas mahasiswa. Temukan dampaknya!

Abstract

Pembelajaran sains dan agama menghadirkan tantangan bagi mahasiswa khususnya mahasiswa tingkat pertama dalam penggunaan teknologi terkini sebagai bentuk inovasi pembelajaran. Penelitian ini membantu mahasiswa untuk mengetahui keefektivan artificial intelligence (AI) yang dapat meningkatkan kemandirian belajar mahasiswa. Penelitian ini bertujuan untuk menganalisis dan mendeskripsikan pengaruh artificial intelligence (AI) terhadap kemandirian mahasiswa PGMI semester 2 dalam menyelesaikan tugas-tugasnya dalam perkuliahan. Teknik analisis data yang digunakan dalam penelitian ini adalah secara kuantitatif yang meliputi pembagian angket kepada mahasiswa dengan jumlah 50 orang. Hasil penelitian menunjukkan bahwa kemandirian belajar mahasiswa meliputi kemampuan berpikir kritis, kreatif dan inovatif, tidak mudah terpengaruh dengan orang lain, dan mampu menyelesaikan masalah melalui aplikasi gemini, chatbot, chat GPT, canva,CICI, online translator, google classroom, mengaji. ai. Hal tersebut memberikan pengaruh positif dan efektif dalam meningkatkan kemandirian mahasiswa berdasarkan nilai P diperoleh nilai 80%.

Review

This study explores a timely and highly relevant topic: the integration of Artificial Intelligence (AI) in education, specifically within the unique context of science and religion learning for first-year PGMI students. The stated aim to enhance "kemandirian belajar" (learning independence) is particularly commendable, addressing a critical skill deficit often observed in early university education, especially when grappling with new technologies and complex interdisciplinary subjects. The research posits that AI can serve as an innovative tool to overcome traditional learning challenges, positioning itself as a valuable contribution to the discourse on technology-enhanced learning in specialized academic fields. The methodology employed is quantitative, utilizing questionnaires distributed to a sample of 50 students to assess the impact of AI on their learning independence. The abstract highlights the use of a diverse array of AI tools, including Gemini, ChatGPT, Canva, and even specific educational platforms like 'mengaji.ai', which is a strength, demonstrating practical application across various functionalities. The identified components of learning independence—critical, creative, and innovative thinking, resilience to external influence, and problem-solving—are well-aligned with contemporary educational goals. However, a significant point of concern is the reporting of results: the statement "nilai P diperoleh nilai 80%" (P-value obtained 80%) is highly ambiguous and appears to misuse the statistical term 'P-value'. A P-value is typically a probability between 0 and 1, used to assess statistical significance, not a measure of effectiveness or percentage of agreement. This requires substantial clarification to ensure the rigor and correct interpretation of the study's findings. Despite the methodological reporting anomaly, the study offers initial insights into the potential of AI to positively influence student autonomy and skill development in a dual-discipline setting. To enhance its contribution, future revisions should thoroughly clarify the statistical reporting, perhaps indicating the percentage of students who perceived a positive impact or the effect size of the intervention. Furthermore, a deeper exploration into *how* each specific AI tool contributed to distinct facets of independence (e.g., how Gemini fostered critical thinking versus Canva for creativity) would provide richer insights. Incorporating qualitative data, such as interviews or focus groups, could further illuminate the student experience and the nuanced mechanisms through which AI influences learning independence, moving beyond surface-level effectiveness to a more comprehensive understanding of its pedagogical impact.

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