PENERAPAN METODE PEMBELAJARAN COOPERATIF LEARNING TIPE ZIGSAW UNTUK MENINGKATKAN MOTIVASI DAN HASIL BELAJAR SISWA KELAS VI SD RK NOMOR 3 SIBOLGA PADA SUB TEMA TUMBUHAN SAHABATKU

Tujuan Penelitian ini adalah untuk meningkatkan motivasi dan hasil belajar siswa melalui metode pembelajaran Cooperatif Learning Tipe Zigsaw pada sub tema tumbuhan sahabatku kelas VI SD RK Nomor 3 Sibolga. Jenis penelitian adalah penelitian tindakan kelas (Classroom Action Research). Penelitian dilaksanakan dengan kolaborasi antara peneliti, guru dan melibatkan keaktifan belajar siswa. Subjek penelitian siswa kelas VI SD RK Nomor 3 Sibolga tahun pelajaran 2018/2019 yang berjumlah 32 siswa. Teknik pengumpulan data menggunakan observasi dan angket sederhana. Prosedur penelitian meliputi tahap: (a) perencanaan tindakan, (b) pelaksanaan tindakan, (c) observasi dan interpretasi, dan (d) analisis dan refleksi. Berdasarkan hasil penelitian, metode pembelajaran Cooperatif Learning Tipe Zigsaw dapat meningkatkan motivasi belajar siswa. Penerapan metode pembelajaran Cooperatif Learning Tipe Zigsaw Berdasarkan hasil penelitian tindakan kelas yang telah dilakukan di kelas VI SD RK Nomor 3 Sibolga dapat disimpulan bahwa penerapan pembelajaran kooperatif Jigsaw dapat meningkatkan motivasi belajar siswa pada sub tema tumbuhan sahabatku. Kesimpulan hipotesis dapat diterima

MultiCellDS : a community-developed standard for curating microenvironment-dependent multicellular data

Exchanging and understanding scientific data and their context represents a significant barrier to advancing research, especially with respect to information siloing. Maintaining information provenance and providing data curation and quality control help overcome common concerns and barriers to the effective sharing of scientific data. To address these problems in and the unique challenges of multicellular systems, we assembled a panel composed of investigators from several disciplines to create the MultiCellular Data Standard (MultiCellDS) with a use-case driven development process. The standard includes (1) digital cell lines, which are analogous to traditional biological cell lines, to record metadata, cellular microenvironment, and cellular phenotype variables of a biological cell line, (2) digital snapshots to consistently record simulation, experimental, and clinical data for multicellular systems, and (3) collections that can logically group digital cell lines and snapshots. We have created a MultiCellular DataBase (MultiCellDB) to store digital snapshots and the 200+ digital cell lines we have generated. MultiCellDS, by having a fixed standard, enables discoverability, extensibility, maintainability, searchability, and sustainability of data, creating biological applicability and clinical utility that permits us to identify upcoming challenges to uplift biology and strategies and therapies for improving human health

MultiCellDS: a community-developed standard for curating microenvironment-dependent multicellular data

Exchanging and understanding scientific data and their context represents a significant barrier to advancing research, especially with respect to information siloing. Maintaining information provenance and providing data curation and quality control help overcome common concerns and barriers to the effective sharing of scientific data. To address these problems in and the unique challenges of multicellular systems, we assembled a panel composed of investigators from several disciplines to create the MultiCellular Data Standard (MultiCellDS) with a use-case driven development process. The standard includes (1) digital cell lines, which are analogous to traditional biological cell lines, to record metadata, cellular microenvironment, and cellular phenotype variables of a biological cell line, (2) digital snapshots to consistently record simulation, experimental, and clinical data for multicellular systems, and (3) collections that can logically group digital cell lines and snapshots. We have created a MultiCellular DataBase (MultiCellDB) to store digital snapshots and the 200+ digital cell lines we have generated. MultiCellDS, by having a fixed standard, enables discoverability, extensibility, maintainability, searchability, and sustainability of data, creating biological applicability and clinical utility that permits us to identify upcoming challenges to uplift biology and strategies and therapies for improving human health

MultiCellDS: a standard and a community for sharing multicellular data

Cell biology is increasingly focused on cellular heterogeneity and multicellular systems. To make the fullest use of experimental, clinical, and computational efforts, we need standardized data formats, community-curated "public data libraries", and tools to combine and analyze shared data. To address these needs, our multidisciplinary community created MultiCellDS (MultiCellular Data Standard): an extensible standard, a library of digital cell lines and tissue snapshots, and support software. With the help of experimentalists, clinicians, modelers, and data and library scientists, we can grow this seed into a community-owned ecosystem of shared data and tools, to the benefit of basic science, engineering, and human health