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Project-Based Learning and Numeracy Literacy in Vocational Education: A Systematic Review of Their Impact on Critical Thinking Husriawati, Waode; Ubaidah, Nila
Didactical Mathematics Vol. 8 No. 1 (2026): April 2026
Publisher : Program Studi Pendidikan Matematika, Universitas Majalengka

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31949/dm.v8i1.17987

Abstract

Despite growing interest in fostering critical thinking in mathematics education, existing studies tend to examine pedagogical approaches, cognitive competencies, and digital tools in isolation, resulting in a fragmented understanding of how these elements interact in vocational education contexts. This study addresses this gap by systematically synthesizing evidence on the interplay between Project-Based Learning (PBL), numeracy literacy, and digital tool integration in enhancing students’ critical thinking skills. A systematic literature review was conducted following the PRISMA framework, analyzing peer-reviewed articles indexed in Scopus, Web of Science, and ERIC published between 2015 and 2024. Studies were selected based on predefined inclusion criteria, including relevance to vocational education, explicit focus on critical thinking outcomes, and empirical or review-based evidence. A thematic synthesis approach was employed to identify patterns of interaction among pedagogical, cognitive, and technological dimensions. The findings reveal that PBL functions as the primary pedagogical driver structuring inquiry-based learning, while numeracy literacy serves as a cognitive mediator, enabling students to process, interpret, and apply mathematical reasoning. Digital tools, in turn, act as facilitating instruments that enhance engagement and support iterative problem-solving processes. The interaction of these three elements forms a complementary system that significantly strengthens the development of critical thinking, rather than contributing independently. This study contributes by proposing an integrative conceptual perspective that explicates the synergistic relationship between instructional design, cognitive development, and technological support in vocational mathematics education. The findings offer a more coherent framework for understanding how critical thinking can be systematically fostered through aligned pedagogical and technological practices.
Artificial Intelligence in Education and Its Conditional Impact on Critical Thinking: A Systematic Literature Review Maslan, Maslan; Ubaidah, Nila
Didactical Mathematics Vol. 8 No. 1 (2026): April 2026
Publisher : Program Studi Pendidikan Matematika, Universitas Majalengka

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31949/dm.v8i1.18001

Abstract

The integration of artificial intelligence (AI), particularly generative AI, has transformed contemporary educational practices, raising critical questions about its role in fostering higher-order thinking skills. This study aims to examine how AI influences critical thinking in educational contexts through a systematic literature review of empirical and supporting studies published between 2020 and 2026. Following PRISMA guidelines, 18 studies were selected and analyzed thematically. The findings indicate that AI can enhance critical thinking, problem-solving, and creativity, particularly when embedded in structured learning environments. However, the results also reveal a parallel risk of cognitive dependency, where learners rely on AI-generated outputs without sufficient evaluation. This dual effect highlights a central tension between AI as a cognitive support tool and as a potential substitute for independent reasoning. Furthermore, instructional design emerges as a key mediating factor. Approaches such as scaffolding, problem-based learning, and guided interaction significantly enhance AI's effectiveness in promoting higher-order thinking. The study concludes that AI does not inherently improve or hinder critical thinking; rather, its impact depends on pedagogical integration, learner engagement, and AI literacy. These findings contribute to a more nuanced understanding of AI in education and provide implications for designing learning environments that support meaningful cognitive development.