Minat Belajar Mahasiswa Prodi Pendidikan Bahasa dan Sastra Indonesia Melalui Mobile Learning di Masa Pandemi Covid-19

Author(s):  
R. Panji Hermoyo ◽  
Himmatul Mursyidah

Dosen dan mahasiswa harus melaksanakan proses belajar mengajar dari rumah masing-masing atau pembelajaran jarak jauh pada masa pandemi Covid-19. Hal tersebut membuat dosen harus bisa menumbuhkan minat belajar mahasiswa. Di sisi lain, pembelajaran di rumah secara otomatis harus menggunakan teknologi untuk mempermudah prosesnya. Salah satu alat yang dapat digunakan untuk pembelajaran jarak jauh pada masa pandemi Covid-19 adalah telepon genggam atau seluler. Metode pembelajaran menggunakan seluler dikenal sebagai mobile learning atau m-learning. Pengguna m-learning dapat berinteraksi dan berkomunikasi dengan sumber daya pendidikan yang berada jauh, dari yang biasanya belajar di kelas ataupun menggunakan personal computer. Penelitian ini bertujuan untuk mengetahui minat belajar melalui m-learning bagi mahasiswa Prodi Pendidikan Bahasa dan Sastra Indonesia (PBSI) pada masa pandemi Covid-19. Metode penelitian yang digunakan adalah kualitatif deskriptif dengan teknik survei. Penelitian dibatasi pada kelas teori belajar dengan jumlah 40 mahasiswa PBSI semester 1 tahun akademik 2020-2021. Hasil penelitian diperoleh bahwa minat belajar mahasiswa PBSI menggunakan m-learning selama pandemi Covid-19 adalah baik. Hal tersebut ditunjukkan dengan rata-rata lebih dari 50% mahasiswa merespon positif terhadap m-learning, yaitu merasa bersemangat, mudah mencapai tujuan pembelajaran, mudah memahami, menjadikan lebih kreatif, mudah mempelajari materi, senang, merasa bermanfaat, mudah mengumpulkan tugas, berdampak positif pada aspek kejujuran, dan menghemat biaya. 

Author(s):  
Gianluigi Botton ◽  
Gilles L'espérance

As interest for parallel EELS spectrum imaging grows in laboratories equipped with commercial spectrometers, different approaches were used in recent years by a few research groups in the development of the technique of spectrum imaging as reported in the literature. Either by controlling, with a personal computer both the microsope and the spectrometer or using more powerful workstations interfaced to conventional multichannel analysers with commercially available programs to control the microscope and the spectrometer, spectrum images can now be obtained. Work on the limits of the technique, in terms of the quantitative performance was reported, however, by the present author where a systematic study of artifacts detection limits, statistical errors as a function of desired spatial resolution and range of chemical elements to be studied in a map was carried out The aim of the present paper is to show an application of quantitative parallel EELS spectrum imaging where statistical analysis is performed at each pixel and interpretation is carried out using criteria established from the statistical analysis and variations in composition are analyzed with the help of information retreived from t/γ maps so that artifacts are avoided.


Author(s):  
Stuart McKernan

For many years the concept of quantitative diffraction contrast experiments might have consisted of the determination of dislocation Burgers vectors using a g.b = 0 criterion from several different 2-beam images. Since the advent of the personal computer revolution, the available computing power for performing image-processing and image-simulation calculations is enormous and ubiquitous. Several programs now exist to perform simulations of diffraction contrast images using various approximations. The most common approximations are the use of only 2-beams or a single systematic row to calculate the image contrast, or calculating the image using a column approximation. The increasing amount of literature showing comparisons of experimental and simulated images shows that it is possible to obtain very close agreement between the two images; although the choice of parameters used, and the assumptions made, in performing the calculation must be properly dealt with. The simulation of the images of defects in materials has, in many cases, therefore become a tractable problem.


Author(s):  
F. Hosokawa ◽  
Y. Kondo ◽  
T. Honda ◽  
Y. Ishida ◽  
M. Kersker

High-resolution transmission electron microscopy must attain utmost accuracy in the alignment of incident beam direction and in astigmatism correction, and that, in the shortest possible time. As a method to eliminate this troublesome work, an automatic alignment system using the Slow-Scan CCD camera has been introduced recently. In this method, diffractograms of amorphous images are calculated and analyzed to detect misalignment and astigmatism automatically. In the present study, we also examined diffractogram analysis using a personal computer and digitized TV images, and found that TV images provided enough quality for the on-line alignment procedure of high-resolution work in TEM. Fig. 1 shows a block diagram of our system. The averaged image is digitized by a TV board and is transported to a computer memory, then a diffractogram is calculated using an FFT board, and the feedback parameters which are determined by diffractogram analysis are sent to the microscope(JEM- 2010) through the RS232C interface. The on-line correction system has the following three modes.


2018 ◽  
Vol 1 (2) ◽  
pp. 1-17
Author(s):  
Tedi Budiman

One example of the growing information technology today is mobile learning, mobile learning which refers to mobile technology as a learning medium. Mobile learning is learning that is unique for each student to access learning materials anywhere, anytime. Mobile learning is suitable as a model of learning for the students to make it easier to get an understanding of a given subject, such as math is pretty complicated and always using formulas.The design method that I use is the case study method, namely, learning, searching and collecting data related to the study. While the development of engineering design software application programs that will be used by the author is the method of Rapid Application Development (RAD), which consists of 4 stages: Requirements Planning Phase, User Design Phase, Construction Phase and Phase Cotuver.


Author(s):  
Oliver Montenbruck ◽  
Thomas Pfleger
Keyword(s):  

1995 ◽  
Vol 32 (4) ◽  
pp. 677
Author(s):  
M J Shin ◽  
G W Kim ◽  
T J Chun ◽  
W H Ahn ◽  
S K Balk ◽  
...  

Author(s):  
Oliver Montenbruck ◽  
Thomas Pfleger
Keyword(s):  

2016 ◽  
Vol 22 (2) ◽  
pp. 325-349
Author(s):  
Yujin Park ◽  
Sunyoung Keum ◽  
Myungsun Kim ◽  
Ilju Rha

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