KEMAMPUAN MENYUSUN KARYA TULIS ILMIAH MAHASISWA PGSD PADA MATA KULIAH BAHASA INDONESIA
Abstract
Penelitian yang dilakukan bertujuan mendeskripsikan kemampuan menyusun karya tuis ilmiah. Adapun jenisnya adalah, menulis teks proposal penelitian pada mahasiswa PGSD angkatan 2017 kelas A dan B pada mata kuliah Bahasa Indonesia. Metode yang digunakan adalah deskriptif kuantitatif dengan menganalisis skor yang didapatkan mahasiswa pada hasil portofolio berupa proposal penelitian. Skor didapatkan dari penyusunan BAB I, BAB II, dan BAB III. Prosedur penelitian ini dilakukan melalui tiga tahap dengan kegiatan, pembelajaran, pemberian tugas portofolio, dan analisis hasil portofolio. Instrumen penelitian yang digunakan adalah lembar penskoran kemampuan menulis teks proposal penelitian. Adapun penilaian yang dilakukan mengacu pada hasil skor dari 6 indikator penilaian pada BAB I, 4 indikator pada BAB II, dan 7 indikator penilaian di BAB III. Adapun Data yang dianalisis adalah, persentase tiap bab pada proposal penelitian dan persentase secara klasikal. Hasil analisis menunjukkan kemampuan menulis teks proposal penelitian pada kelas A yang berjumlah 35 mahasiswa pada BAB I sebesar 66,90%, BAB II sebesar 46,78%, dan BAB III 65,10% sedangkan persentase secara klasikal sebesar 61,47%. Pada kelas B dengan jumlah 40 mahasiswa persentase BAB I sebesar 83,09%, BAB II 58,92%, dan BAB III 81,73%, dan persentase klasikal mencapai 76,13%.
Downloads
License and Copyright Agreement
In submitting the manuscript to the journal, the authors certify that:
- They are authorized by their co-authors to enter into these arrangements.
- The work described has not been formally published before, except in the form of an abstract or as part of a published lecture, review, thesis, or overlay journal.
- That it is not under consideration for publication elsewhere,
- That its publication has been approved by all the author(s) and by the responsible authorities – tacitly or explicitly – of the institutes where the work has been carried out.
- They secure the right to reproduce any material that has already been published or copyrighted elsewhere.
- They agree to the following license and copyright agreement.
Copyright
Authors who publish with DIDAKTIKA: Jurnal Pemikiran Pendidikan agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License (CC BY-SA 4.0) that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.
Licensing for Data Publication
Open Data and Software Publishing and Sharing
The journal strives to maximize the replicability of the research published in it. Authors are thus required to share all data, code or protocols underlying the research reported in their articles. Exceptions are permitted but have to be justified in a written public statement accompanying the article.
Datasets and software should be deposited and permanently archived inappropriate, trusted, general, or domain-specific repositories (please consult http://service.re3data.org and/or software repositories such as GitHub, GitLab, Bioinformatics.org, or equivalent). The associated persistent identifiers (e.g. DOI, or others) of the dataset(s) must be included in the data or software resources section of the article. Reference(s) to datasets and software should also be included in the reference list of the article with DOIs (where available). Where no domain-specific data repository exists, authors should deposit their datasets in a general repository such as ZENODO, Dryad, Dataverse, or others.
Small data may also be published as data files or packages supplementary to a research article, however, the authors should prefer in all cases a deposition in data repositories.
