Module designation | Data and Libraries |
Semester(s) in which the module is taught | 1st Semester |
Person responsible for the module | Dr. Diah Indriani, S.Si., M.Si. |
Language | Indonesian |
Relation to curriculum | Compulsory |
Teaching methods | Working in Teams, Discourse Project based Learning |
Workload | Total workload: 3.2 ECTS Contact hours: 1,400 minutes = 23.33 hours Self-study hours: 3,360 minutes = 56 hours |
Credit Points | 3.2 ECTS |
Required and recommended prerequisites for joining the module | – |
Module objectives/ intended learning outcome | Students are able to use data and scientific references to make decisions and persuade |
Content | This course aims to encourage students to learn to understand how to interpret and use data properly and responsibly, so that students can develop strong and coherent arguments, as well as equip students with the ability to evaluate the quality of arguments of other parties/people. Not everyone will become a scientist who has to plan research designs, collect data, analyze it and draw conclusions, but data literacy will help students to make decisions in everyday life that are guided by data. In addition, students are encouraged to practice searching, reading, evaluating, and sorting claims or information contained in scientific literature. In this course, students are also given the opportunity to practice organizing scientific references with the help of a reference manager application. |
Examination forms | Midterm Exam, Mini Literatur Review |
Study and examination requirements | Student must have at least 75% of attendance out of total meetings |
Reading list | 1. Bailey, J. (2008). First step in qualitative data analysis: transcribing. Family Practice, 25(2), 127-131. doi: https://doi.org/10.1093/fampra/cmn003 2. Bowen, M. & Bartley, A. (2014). The Basics of Data Literacy. Arlington: NSTA Press. 3. Davidson, C. (2009). Transcription: Imperatives for qualitative research. International Journal of Qualitative Methods, 8(2), 35-52. doi: https://doi.org/10.1177/160940690900800206 4. Durbin, C.G. (2009). How to read a scientific research paper. Respiratory Care, 54(10), 1366-1371. 5. Field, A. (2016). An Adventure in Statistics: The Reality Enigma. London: SAGE Publications. 6. Fosmire, A. (2013). How to read a scientific paper. Purdue University Library. Diakses dari https://www.lib.purdue.edu/sites/default/files/libraries/e ngr/Tutorials/Newest%20Scientific%20Paper.pdf 7. Leonelli, S. (2020). Scientific Research and Big Data. The Stanford Encyclopedia of Philosophy. Diakses dari https://plato.stanford.edu/entries/science-big-data/ 8. Morrison, R. (2020). Don’t just “Google it”: 3 ways students can get the most from searching online. The Conversation. Diakses dari |
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