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All Journal Jurnal Penelitian dan Pengkajian Ilmu Pendidikan: e-Saintika
Wirzal, Mohd Dzul Hakim
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Education Mathematics Physics Other

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Thermal Annealing Surface Modification: Effect on Surface and Performance of Electrospun Nylon 6,6 Nanofiber Membrane for Wastewater Treatment Mohd Asri, Muhammad Amir Nasrin; Abd Halim, Nur Syakinah; Wirzal, Mohd Dzul Hakim; Mohd Yusoff, Abdull Rahim; Bilad, Muhammad Roil
Jurnal Penelitian dan Pengkajian Ilmu Pendidikan: e-Saintika Vol. 5 No. 1: March 2021
Publisher : Lembaga Penelitian dan Pemberdayaan Masyarakat (LITPAM)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36312/e-saintika.v5i1.395

Abstract

As the forefront in fiber materials development, electrospun nanofiber membrane (NFM) is potentially reliable for wastewater treatment due to its excellent properties for instance; large surface area, high porosity, tuneable pore size, and has great flux as compared to other conventional membranes. However, fouling issue will lead to degradation of membrane performance. Fouling issue can be alleviated by applying membrane surface modification. In this study, thermal annealing is applied onto nylon 6,6 nanofiber membrane with three different temperatures (60°C, 80°C and 120°C). Results show that annealing causes membrane shrinkage and reduction of membrane fiber diameter where the fiber reduced from 138.5 nm to 108.5 nm when annealed at 120°C. The optimum annealing temperature for the membrane was found to be at 60˚C as the membrane shows the highest flux at 1200 L/m2.h at 75 minutes filtration time and took longer time to get fouled (>75 minutes) compared with un-annealed membrane (55 minutes). Nylon 6,6 nanofiber membrane is also proven to give more than 90% of COD and turbidity rejection.
Metacognition in Science Learning: Bibliometric Analysis of Last Two Decades Wirzal, Mohd Dzul Hakim; Halim, Nur Syakinah Abdul; Md Nordin, Nik Abdul Hadi; Bustam, Mohamad Azmi
Jurnal Penelitian dan Pengkajian Ilmu Pendidikan: e-Saintika Vol. 6 No. 1: March 2022
Publisher : Lembaga Penelitian dan Pemberdayaan Masyarakat (LITPAM)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36312/esaintika.v6i1.665

Abstract

The main objective of this study was to map (1) the research of metacognition in science learning; (2) learning interventions used and metacognition’s key components that learned, integrated, and investigated; and (3) future research recommendations of metacognition research in science learning. We analyzed 438 scientific documents published in journals and books indexed in the Scopus database using VOSviewer software to visualize research trends and main keywords investigated of metacognition in science learning. The research findings show that research in the field of metacognition in science learning through the metacognition as attribution that integrated into learning interventions and as a learning outcome has increased in the last two decades. Scientific concepts understanding, critical thinking skills, motivation, and attention are the main goals in metacognition research. Inquiry-based learning, such as problem-based learning, is the most frequently used intervention to teach students metacognition. The research gaps found are (1) the cognitive regulations are the most investigated aspect, while cognitive aspects such as declarative knowledge, procedural knowledge, and conditional knowledge have not been widely investigated in science learning; (2) metacognition research on college students has a high frequency compared to school students; and (3) the integration of metacognition in online learning is still less investigated, this is indicated by the recommendations of several research results that encourage the integration of self-regulated learning into online learning.
Generative AI in Science Education: A Learning Revolution or a Threat to Academic Integrity? A Bibliometric Analysis Wirzal, Mohd Dzul Hakim; Md Nordin, Nik Abdul Hadi; Abd Halim, Nur Syakinah; Bustam , Mohamad Azmi
Jurnal Penelitian dan Pengkajian Ilmu Pendidikan: e-Saintika Vol. 8 No. 3: November 2024
Publisher : Lembaga Penelitian dan Pemberdayaan Masyarakat (LITPAM)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36312/e-saintika.v8i3.2127

Abstract

The integration of generative artificial intelligence (AI) in Science, Technology, Engineering, and Mathematics (STEM) education presents transformative opportunities alongside significant challenges. This study investigates the dual impact of generative AI on STEM learning outcomes and academic integrity through a comprehensive bibliometric analysis employing co-citation, keyword analysis, and trend mapping. The results reveal that AI tools such as ChatGPT have revolutionized personalized learning by offering tailored feedback, enhancing critical thinking, and improving student engagement. However, these advancements are tempered by concerns over academic misconduct, particularly plagiarism, and the erosion of essential cognitive skills due to overreliance on AI-generated content. Ethical considerations remain critical, necessitating the development of robust policies and ethical frameworks to safeguard academic integrity. Beyond educational settings, the findings suggest broader applicability to professional training and skills development, as the benefits and challenges of AI extend beyond coursework. This research provides valuable insights for educators, policymakers, and researchers, advocating for a balanced approach to AI integration that maximizes its potential while preserving educational standards.
Co-Authors Abd Halim, Nur Syakinah Abdull Rahim Mohd Yusoff Bilad, Muhammad Roil Bustam , Mohamad Azmi Bustam, Mohamad Azmi Halim, Nur Syakinah Abdul Md Nordin, Nik Abdul Hadi Mohd Asri, Muhammad Amir Nasrin