The subtle difference between data and information
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Kliping bahan-bahan untuk menyusun RPS ELDA melalui upaya memahami tantangan dan garis besar upaya solusi secara universal. PDCA, ADDIE, Gagne's 9 events of instruction, ABET Risk: Dunning-Kruger effects, Science of stupid Search engine: Apakah atom dan elektron itu benar ada? Evolution (model atom, mobile phone, computers, laptop) Correlation vs Causation (Joko Widodo & musibah crane) Science: “I Wonder” circle, How to Think Like Leonardo da Vinci, Science process skills, Critical thinking skills, Scientific reasoning skills, Experiment stages (engineering projects), Critical thinking, The scientific method, Theories vs Laws (Theories of electricity)
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The subtle difference between data and information
- 1. Acuan dasar kegiatan kuliah Elektronika Daya teori dan eksperimen D III Teknik Listrik Laboratorium Elektronika Daya Semester V dan VI Compiler: Sunu Pradana Versi dokumen: 2015c Cited from various sources Bagian: Tantangan, peluang dan solusi
- 2. 2 Hanya untuk keperluan pendidikan Semua slide yang dikumpulkan dari berbagai sumber ( mash-up“ ” ) diberi keterangan. File ini disusun semata untuk memudahkan penyimpanan dan transfer pengetahuan. File gabungan dipisah-pisah untuk memudahkan pembacaan, karenanya beberapa slide diulang.
- 3. 3 Garis besar isi: ● Goal pendidikan politeknik ● Standar nasional ● Definisi engineering ● Data vs Informasi ● Kondisi objektif (tantangan) ● MEA ● Berita buruh China ● Generation era ● OECD PISA ● Happiness vs test score ● Filosofi pengembangan ● PDCA ● ADDIE ● Gagne's 9 events of instruction ● ABET ● Risk: Dunning-Kruger effects ● Science of stupid ● Search engine: Apakah atom dan elektron itu benar ada? ● Evolution ● Atom model, mobile phone, computers, laptop ● Correlation vs Causation ● Joko Widodo & musibah crane ● Science ● “I Wonder” circle ● How to Think Like Leonardo da Vinci ● Science process skills ● Critical thinking skills ● Scientific reasoning skills ● Experiment stages ● Engineering projects ● Critical thinking ● The scientific method ● Theories vs Laws ● Theories of electricity ● Literatur (hanya bagian A1)
- 4. 4 “The main goal of polytechnic education is to prepare students for employment in the working industry.” Tan, S.-E. (2012). Authentic assessment for Fundamental Electronics. In 2012 IEEE International Conference on Teaching, Assessment and Learning for Engineering (TALE) (pp. W1A–11–W1A–16). doi:10.1109/TALE.2012.6360397
- 5. 5 http://www.unsika.ac.id/sites/default/files/File%20Ruang%20Informasi/STANDAR-PENDIDIKAN-TINGGI-2014ringkas.pdf Standar Nasional Pendidikan, adalah kriteria minimal tentang pembelajaran pada jenjang pendidikan tinggi di perguruan tinggi di seluruh wilayah hukum Negara Kesatuan Republik Indonesia. 11 Juni 2014
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- 7. 7 DIREKTORAT PEMBELAJARAN DAN KEMAHASISWAAN DIREKTORAT JENDERAL PENDIDIKAN TINGGI KEMENTERIAN PENDIDIKAN DAN KEBUDAYAANhttp://pditt.belajar.kemdikbud.go.id/pluginfile.php/1038/block_html/content/Final%20Draft%20Buku-K-DIKTI-18-8-2014-Revisi%20Hotel%20Ibis.pdf
- 8. 8 Menindak lanjuti Undang-Undang Republik Indonesia Nomor 12 Tahun 2012 tentang Pendidikan Tinggi khususnya mengenai Kurikulum, Peraturan Presiden Republik Indonesia Nomor 8 Tahun 2012 tentang Kerangka Kualifikasi Nasional Indonesia, Peraturan Menteri Pendidikan dan Kebudayaan Republik Indonesia Nomor 73 Tahun 2013 tentang Penerapan Kerangka Kualifikasi Nasional Indonesia Bidang Pendidikan Tinggi, serta Peraturan Menteri Pendidikan dan Kebudayaan Republik Indonesia Nomor 49 Tahun 2014 tentang Standar Nasional Pendidikan Tinggi (SN- DIKTI), maka Direktorat Jenderal Pendidikan Tinggi menerbitkan buku Kurikulum Pendidikan Tinggi. Buku ini merupakan panduan ringkas yang dapat memfasilitasi dan memberdayakan perguruan tinggi pengelola berbagai jenis pendidikan dalam upaya penyusunan kurikulum yang merujuk pada SN-DIKTI dan KKNI. Jakarta, Agustus 2014 Direktur Jenderal Pendidikan Tinggi Djoko Santoso http://pditt.belajar.kemdikbud.go.id/pluginfile.php/1038/block_html/content/Final%20Draft%20Buku-K-DIKTI-18-8-2014-Revisi%20Hotel%20Ibis.pdf
- 9. 9 Buku ini berisi serangkaian bab yang dimulai dengan hal yang melatar belakangi perubahan kurikulum dan proses menuju perubahan ke Kurikulum Pendidikan Tinggi yang berkualitas. Kemudian dilanjutkan dengan pemaparan implementasi dan evaluasi kurikulum pada pendidikan tinggi baik di Universitas, Institut, Sekolah Tinggi, Politeknik, dan Akademi. Jakarta, Agustus 2014 Direktur Pembelajaran dan Kemahasiswaan Illah Sailah http://pditt.belajar.kemdikbud.go.id/pluginfile.php/1038/block_html/content/Final%20Draft%20Buku-K-DIKTI-18-8-2014-Revisi%20Hotel%20Ibis.pdf
- 10. 10 Engineering is defined by Webster’s II dictionary as “The application of scientific principles to practical ends.” (Braun, 1995) >>American Psychological Association 6th Edition Braun, C. G. (1995). Making things real in electronics laboratories. In Frontiers in Education Conference, 1995. Proceedings., 1995 (Vol. 2, pp. 4c2.10–4c2.13 vol.2). doi:10.1109/FIE.1995.483212 >>IEEE [1] C. G. Braun, “Making things real in electronics laboratories,” in Frontiers in Education Conference, 1995. Proceedings., 1995, 1995, vol. 2, pp. 4c2.10–4c2.13 vol.2. >>Chicago Manual of Style (Note) Braun, C.G. “Making Things Real in Electronics Laboratories.” In Frontiers in Education Conference, 1995. Proceedings., 1995, 2:4c2.10–14c2.13 vol.2, 1995. doi:10.1109/FIE.1995.483212. >>Elsevier Harvard (with titles) Braun, C.G., 1995. Making things real in electronics laboratories, in: Frontiers in Education Conference, 1995. Proceedings., 1995. Presented at the Frontiers in Education Conference, 1995. Proceedings., 1995, pp. 4c2.10–4c2.13 vol.2. doi:10.1109/FIE.1995.483212
- 11. 11 There is a subtle difference between data and information. Data are the facts or details from which information is derived. Individual pieces of data are rarely useful alone. For data to become information, data needs to be put into context. Data vs Information - Difference and Comparison | Diffen. (n.d.). Retrieved February 8, 2015, from http://www.diffen.com/difference/Data_vs_Information
- 12. 12 Tantangan yang mendorong pada perubahan
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- 58. 58 PUIL 2010
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- 62. 62 http://indonesiana.tempo.co/read/44021/2015/07/11/ditahan/kenapa-banyak-hoax-bertebaran Dua puluh tahun lalu, McArthur Wheeler memutuskan merampok bank. Wheeler, warga Pitshburg US [sic ~> Pittsburgh], yang kala itu umur 44 tahun dengan pede merampok bank dengan bekal utama perasan air lemon. Hipotesis Wheeler sederhana, air perasan lemon, bisa digunakan sebagai tinta yang tak terlihat (invisible ink). Jika perasan air lemon dituliskan pada sebuah kertas, maka tulisannya tak terbaca. Tulisan itu baru bisa dibaca kalau didekatkan dengan panas. Nah, Wheeler melumuri kepalanya dengan perasan air lemon. Dalam benak Wheeler, wajahnya jadi tak terlihat jika dilumuri perasan air lemon. Sebagai percobaan, ia mengambil swafoto (selfie) dengan kamera Polaroid. Entah kameranya yang sedang rusak, atau sebab lain, tapi hasil foto itu tak bisa menampilkan wajah Wheeler. Wheeler makin yakin dan percaya absolut dengan resepnya. Walau dia tak paham dengan kimia, dia mantap merampok bank dengan perasan air lemon. Di hari itu, Wheeler akhirnya merampok bank. Tanpa topeng apalagi penutup kepala. Tak hanya merampok satu bank, tapi dua sekalian. Wheeler bisa membawa banyak uang. Sekaligus terkenal. Sebab, kamera pengintai bank bisa merekam wajahnya. Selang beberapa jam usai beraksi, wajahnya sudah nongol di layar kaca, dengan jelas. Alhasil, wajah itu mudah dikenali sebagai McArthur Wheeler. Di hari yang sama, polisi bisa menangkap Wheeler dengan mudah.
- 63. 63 http://indonesiana.tempo.co/read/44021/2015/07/11/ditahan/kenapa-banyak-hoax-bertebaran Kebodohan Wheeler ini menarik dua peneliti psikologi sosial dari Cornell University; David Dunning dan Justin Kruger. Keduanya tertarik, apa yang menyebabkan Wheeler begitu percaya diri merampok bank hanya dengan melumuri wajahnya dengan air lemon. Apa yang membuatnya yakin sukses merampok bank, padahal tak punya pengetahuan tentang kimia? Hasil penelitian mereka menunjukkan, dalam konteks psikologis, makin minim pengetahuan atau pengalaman seseorang di suatu bidang, justru makin tinggi rasa percaya diri. Bahkan level kepedeannya, melebihi para ahli. Orang-orang menengah, justru rasa percaya dirinya paling rendah. Para ahli, justru tak sepede dengan orang-orang minim pengetahuan ini. Fenomena ini dikenal dengan Dunning-Kruger effect... http://awesci.com/the-astonishingly-funny-story-of-mr-mcarthur-wheeler/ Apa solusinya?
- 64. 64 http://blogs.agu.org/wildwildscience/2015/02/15/reliable -vaccine-treat-dunning-krueger-syndrome/
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- 77. 77 Hukum Ohm?
- 78. 78 Hukum Ohm?
- 79. 79 Hukum Ohm?
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- 82. 82 http://www.sciencecompanion.com/wp-content/uploads/IWC-and-NGSS-Practices-11x17_4c-1024x662.jpg
- 87. 87 Good scientists, both young and old, frequently use a process to study what they see in the world. This process has been referred as the'Scientific Method' or more recently as the'Inquiry Cycle'. The following stages listed below will help you produce a good scientific experiment: 1. Be curious, choose a limited subject, ask a question; identify or originate/define a problem. It is important that this question be a'testable' question - one in which data is taken and used to find the answer. A testable question can further be identified as one in which one or more variables can be identified and tested to see the impact of that variable on the original set of conditions. The question should not merely be an'information' question where the answer is obtainable through literature research. 2. Review published materials related to your problem or question. This is called background research. 3. Evaluate possible solutions and guess why you think it will happen (hypothesis). 4. Experimental design (procedure). In designing the experiment, it is critical that only one variable - a condition that may effect the results of the experiment - is changed at a time. This makes the experiment a'controlled' experiment. 5. Challenge and test your hypothesis through your procedure of experimentation (data collection) and analysis of your data. Use graphs to help see patterns in the data. 6. Draw conclusions based on empirical evidence from the experiment. 7. Prepare your report and exhibit. 8. Review and discuss the findings with peer group/ professional scientists 9. New question(s)may arise from your discussions. http://hsaelpaso.org/sciencefair/research.html
- 88. 88 This sets the stage for another research project as new questions are raised from others and the process repeats itself. The hypothesis often changes during the course of the experiment. Supporting or not supporting your hypothesis is secondary to what is learned and discovered during the research. Non Inquiry Based Research Not all areas of study are best served by scientific method based research. Because engineers, inventors, mathematicians, theoretical physicists, and computer programmers have different objectives than those of other scientists, they follow a different process in their work. The process that they use to answer a question or solve a problem is different depending on their area of study. Each one uses their own criteria to arrive at a solution. Engineering Projects "Scientists try to understand how nature works; engineers create things that never were." An engineering project should state the engineering goals, the development process and the evaluation of improvements. Engineering projects may include the following: 1. Define a need or"How can I make this better?" 2. Develop or establish design criteria (could be more than one) 3. Do background research and search the literature to see what has already been done or what products already exist that fill a similar need. What make them good and what makes them weak? 4. Prepare preliminary designs and a materials list. Consider costs, manufacturing and user requirements. 5. Build and test a prototype of your best design. Consider reliability, repair and servicing. 6. Retest and redesign as necessary. Product testing. 7. Present results http://hsaelpaso.org/sciencefair/research.html
- 89. 89 Computer Science Projects These often involve creating and writing new algorithms to solve a problem or improve on an existing algorithm. Simulations, models or'virtual reality' are other areas on which to conduct research. Mathematics Projects These involve proofs, solving equations, etc. Math is the language of science and is used to explain existing phenomena or prove new concepts and ideas. Theoretical Projects These projects may involve a thought experiment, development of new theories and explanations, concept formation or designing a mathematical model. Getting Started 1) Pick your topic: This is perhaps the most difficult part. Get an idea of what you want to study or learn about. Ideas should come from things in your area of interest. A hobby might lead you to a good topic. What is going on in the world that you would like to know more about? Most importantly, pick a question or problem that is not too broad and that can be answered through scientific investigation. 2) Research your topic: Go to the library or internet to learn more about your topic. Always ask Why or What if…. Look for unexplained or unexpected results. Also, talk to professionals in the field. 3) Organize: Organize everything you have learned about your topic. At this point, you should narrow your thinking by focusing on a particular idea. http://hsaelpaso.org/sciencefair/research.html
- 90. 90 Theoretical Projects. 4) Make a time table: Choose a topic that not only interests you, but can be done in the amount of time you have. Identify your'testable question'. Develop a time line to manage your time efficiently. You will need time to fill out the necessary forms and to review the Research Plan with your sponsor. Certain projects will require more time because they need prior Scientific Review Committee (SRC) or Institutional Review Board (IRB) approval. Allow plenty of time to experiment and collect data. You will also need time to write a paper and put together a display or'board'. 5) Plan Your Experiment: Give careful thought to experimental design. Once you have a feasible project idea, write a research plan. This plan should explain how you will do your experiments and exactly what will be involved. Remember you must design your experiment so that it is a'controlled' experiment. This is one in which only one variable is changed at a time. The results are then compared to the'standard' data you take originally before you change that one variable. Thus, you have designed an investigation with adequate control and limited variables to investigate a question. Also, in your experimental design, make sure you include sufficient numbers in both control ( if applicable) and experimental groups to be statistically valid. The experimental design should also include a list of materials. Once finished with the experimental design (called'procedure') all students are required to fill out the appropriate forms. 6) Consult with Your Adult Sponsor and get Approvals: You are required to discuss your research plan with an Adult Sponsor and obtain a signature of approval. In reviewing your research plan, you should determine if additional forms and prior approval are needed. http://hsaelpaso.org/sciencefair/research.html
- 91. 91 Theoretical Projects. 7) Conduct your experiment: During experimentation, keep detailed notes of each and every experiment, measurement and observation in a log book. Do not rely on memory. Besides, judges love logbooks! Use data tables or charts to record your quantitative data. 8) Analyze Your Results: When you complete your experiments, examine and organize your findings. Use appropriate graphs to make'pictures' of your data. Identify patterns from the graphs. This will help you answer your testable question. Did your experiments give you the expected results? Why or why not? Was your experiment preformed with the exact same steps each time? Are there other explanations that you had not considered or observed? Were there experimental errors in your data taking, experimental design or observations? Remember, that understanding errors is a key skill scientists must develop. In addition, reporting that a suspected variable did not change the results can be valuable information. That is just as much a'discovery' as if there was some change due to the variable. In addition, statistically analyze your data using the statistics that you can understand and explain their meaning. 9) Draw Conclusions: Did the variable(s) tested cause a change when compared to the standard you are using? What patterns do you see from your graph analysis that exist between your variables? Which variables are important? Did you collect enough data? Do you need to conduct more experimentation? Keep an open mind - never alter results to fit a theory. If your results do not support your hypothesis, that's ok and in some cases good! Try to explain why you obtained different results than your literature research predicted for you. Were there sources of error that may have caused these differences? If so, identify them. Even if the results do differ, you still have accomplished successful scientific research because you have taken a question and attempted to discover the answer through quantitative testing. This is the way knowledge is obtained in the world of science. Think of practical applications that can be made from this research. How could this project be used in the real world? Finally, explain how you would improve the experiment and what would you do differently. http://hsaelpaso.org/sciencefair/research.html
- 101. 101 https://mentone-educational.com.au/var/files/uploads/images/ee0fa9beb463c938b4eb69244dc60f65.png
- 131. 131 A. Makalah jurnal dan konfrensi Untuk dapat menyusun RPS mata kuliah elektronika daya (power electronics) yang baik dan mencerminkan kesesuaian dengan perkembangan ilmu pengetahuan dan teknologi serta pola pengajarannya di negara-negara yang lebih maju, maka sumber-sumber berikut ini perlu dijadikan sebagai pembanding dan acuan. 1. Tinjauan sejarah dan proyeksi masa depan bidang elektronika daya B. K. Bose, “The past, present, and future of power electronics [Guest Introduction],” IEEE Industrial Electronics Magazine, vol. 3, no. 2, pp. 7–11, 14, Jun. 2009. J. D. van Wyk and F. C. Lee, “On a Future for Power Electronics,” IEEE Journal of Emerging and Selected Topics in Power Electronics, vol. 1, no. 2, pp. 59–72, 2013. J. D. van Wyk, “Power electronics quo vadis?,” in Power Electronics and Motion Control Conference (EPE/PEMC), 2012 15th International, 2012, pp. Session 1–1–Session 1–9. B. K. Bose, “Global Energy Scenario and Impact of Power Electronics in 21st Century,” IEEE Transactions on Industrial Electronics, vol. 60, no. 7, pp. 2638–2651, Jul. 2013. H. Shigekane, T. Fujihira, K. Sasagawa, Y. Seki, Y. Takahashi, and A. Takai, “Macro- trend and a future expectation of innovations in power electronics and power devices,” in Power Electronics and Motion Control Conference, 2009. IPEMC ’09. IEEE 6th International, 2009, pp. 35–39.
- 132. 132 Versi rilis dokumen: Sunu Pradana JShot