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Analysis of Students' Design Thinking in Creating 3D Creative Works Utilizing Mobile Technology within the Framework of Local Wisdom Ardi, Raden Fanny Printi; Bilad, Muhammad Roil; Mustofa, Hisbulloh Als; Maulachela, Adam Bachtiar
International Journal of Ethnoscience and Technology in Education Vol. 1 No. 1 (2024): March
Publisher : Faculty of Engineering and Applied Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33394/ijete.v1i1.10879

Abstract

This study investigated students' design thinking in creating 3D creative works using mobile technology in the framework of local wisdom. By employing a mixed-methods approach, the study compares the design thinking abilities of students who engaged with mobile technology in the context of local wisdom with those who donot. Quantitative analysis, involving sixty students, revealed that the experimental group, exposed to mobile technology and local wisdom, demonstrated significantly higher competencies in design thinking, particularly in areas such as comfort with uncertainty, human-centeredness, and collaborative work. Qualitative insights further illuminated the enriched learning experience, showcasing students' deepened engagement and connection to cultural heritage through the integration of local wisdom into their 3D creative projects. The findings underscore the pivotal role of mobile technology and local wisdom in fostering innovative design thinking, suggesting that this approach not only facilitates creative problem-solving but also instills a sense of cultural identity and pride among students. Despite its focused educational context and limited sample size, the study suggested broader implications for curriculum development, recommending the incorporation of these elements into design and creative courses to enhance students’ design skills and cultural understanding.
Integration of Artificial Intelligence (ChatGPT) into Science Teaching and Learning Mustofa, Hisbulloh Als; Kola, Aina Jacob; Owusu-Darko, Isaac
International Journal of Ethnoscience and Technology in Education Vol. 2 No. 1 (2025): March
Publisher : Faculty of Engineering and Applied Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33394/ijete.v2i1.14195

Abstract

The integration of artificial intelligence (AI) into science education is transforming teaching and learning by offering innovative solutions to complex challenges. This study aims to review current trends in AI utilization, particularly ChatGPT, and explore its potential to improve problem-solving in science education. A systematic literature review was conducted using PRISMA guidelines, complemented by experiential exploration and qualitative insights from a thermodynamics lecturer. The findings highlight AI’s ability to provide accurate explanations, generate diverse educational materials, and support interactive learning. However, limitations were identified, including inaccuracies in handling advanced or ambiguous problems and the potential for overreliance by students. Technical and ethical challenges, such as infrastructure requirements, educator preparedness, and concerns about bias, were also noted. These limitations underscore the importance of human oversight and critical evaluation of AI-generated content. The study recommends enhancing AI’s contextual understanding, visualization capabilities, and adaptability to individual learner needs. By harmonizing AI-driven innovations with traditional teaching methods, educators can leverage these tools to create inclusive and effective learning environments, advancing the transformative potential of AI in science education.
Analysis of Student Conceptions based on Cognitive Style on Newton Law Understandings Mustofa, Hisbulloh Als; Zain, Zahida Aliatu; Tsania, Hartami; Azman, Mohamed Nor Azhari; Marmoah, Sri; Masfuah, Siti
Jurnal Pendidikan IPA Indonesia Vol. 13 No. 2 (2024): June 2024
Publisher : Universitas Negeri Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.15294/mx0v4952

Abstract

Differences in students’ cognitive style aspects allow for differences in students’ conceptions of their understanding of Newton’s laws. This study aims to determine the profile of students’ conceptions in-depth based on their cognitive styles. This research used a qualitative method with a descriptive phenomenological design involving cognitive style tests with GEFT (Group Embedded Figured Test) on 30 students to be categorized based on their cognitive styles. From the 30 participants, three strongly field-dependent and three strongly field-independent students were selected. Six selected students were diagnosed using a four-tier diagnostic instrument for their understanding and conceptions. Semi-structured interviews were also conducted to investigate the students’ conceptions in depth. This study concludes that field-independent (FI) students frequently display an inclination toward analytical thinking by self-exploring. However, they frequently experience difficulties in analyzing concepts without a solid foundation in physics, which can result in certain theoretical misconceptions. Conversely, field-dependent (FD) students can receive a broader range of information but demonstrate difficulties in analytical tasks, such as interpreting graphs and establishing causal relationships between physical quantities, which can result in correlational misconceptions. To rectify this misconception, it is imperative to implement a bespoke pedagogical strategy that integrates efficacious elucidations, tangible exemplifications, structured scaffolding, inquiry, and methodical practical exercises.