Is My Classroom Flipped? Using Process Mining to Avoid Subjective Perception

Flipped classroom is an active learning method that encourages students to access study material prior to class time. Ensuring the flipping process took place, understanding how it occurred, and verifying whether it produced positive results has been a challenge for lecturers. In this article, we analyze a flipped classroom scenario through process mining techniques. Process mining was applied to an event log provided by a learning management system that supported a particular undergraduate course offering. The outcomes provide evidence for the flip of the classroom, adding precision and reliability to lecturer analyses.

PEMBELAJARAN AKTIF PADA PELATIHAN GURU MATEMATIKA MADRASAH IBTIDAIYAH

This study aims to determine the impact MIKiR active learning method in training of Madrasah Ibtidaiyah mathematics teachers training. The research is Pre experimental design using one class as an experiment without a control class with a sample of 30 people. The data collection methods are observation and test. Data were analyed through descriptive statistics. The results showed that after using the MIKiR methode the average score of affective is89.60, the average score of knowledge is 90.17 and the average score of skillsis 89.88. Overall, an average of 89.94 was obtained. Researcher recommends conducting further research to measure the effectiveness of the method. Abstrak Penelitian ini bertujuan untuk mengetahui dampak pembelajaran aktif MIKiR pada Pelatihan Guru Matematika Madrasah Ibtidaiyah. Jenis penelitian yang digunakan adalah Pre-Experimental Design dengan menggunakan satu kelas sebagai eksperimen tanpa kelas kontrol dengan sampel sebanyak 30 orang. Metode pengumpulan data yang digunakan adalah metode pengamatan dan tes. Tteknik analisis data yang digunakan adalah statistik deskriptif dengan menggunakan rata-rata dan prosentase. Hasil penelitian menunjukkan bahwa pembelajaran aktif MIKiR berhasil meningkatkan kompetensi peserta pelatihan aspek sikap dengan rata-rata 89,60, pengetahuan dengan rata-rata 90,17 dan keterampilan dengan rata-rata 89,88. Secara keseluruhan diperoleh rata-rata 89,94. Selanjutnta direkomendasikan untuk menguji metode ini secara experiment.

Education Reconstruction: A Collaboration of Quiz Team and Kahoot Methods in Learning Arabic

The purpose of this paper is to start from an educational reconstruction paradigm to support teachers to always innovate in creating innovative teaching methods, especially in learning Arabic, especially in learning that uses technology, given that education is already in the era of the industrial revolution 4.0, where every Human are required to be technology literate. This study uses experimental research Borg & Gall, the focus is to determine the level of influence of treatment on behavior that arises as a result of the treatment and or as a systematic method to build relationships that contain causal-effect relationships. Based on the results of this study it was found that; First, the combination of the Quiz Team-type Active Learning method with Kahoot is the right ingredient to make it easier for students to learn Arabic by training the four maharah or language skills, namely: listening (istima'), reading (qirā'ah), speaking (kalām). , and write (kitābah) at the same time; Second, the results of this study are in the form of design designs, and the role of educators in implementing the collaboration of the quiz team and Kahoot methods in learning Arabic.

Enhancing Students' English Language Skills through Active Learning at an Islamic University

English is the most widely used international language in the world. Mastering English skills in this modern era is, therefore, crucial. Consequently, English needs to be sufficiently taught to students of all educational levels. In response to the issue, this study aims to investigate the active learning strategy (intense involvement of students in learning processes) employed in the Faculty of Islamic Da'wah and Communication at an Islamic Institute in Lumajang, East Java. This study was designed as a case study with in-depth interviews and observations as the main data collection. The results of this study indicate that although the active learning method was successfully implemented in this faculty, the strategies and learning activities should be varied.

K-Nearest Robust Active Learning on Big Data and Application in Epitope Prediction

B-cells that induce antigen-specific immune responses in vivo produce large numbers of antigen-specific antibodies by recognizing subregions (epitopes) of antigenic proteins, in which they can inhibit the function of antigen protein. Epitope region prediction facilitates the design and development of vaccines that induce the production of antigen-specific antibodies. There are many diseases which are difficult to treat without vaccines. And the COVID-19 has destroyed many people’s lives. Therefore, making vaccines to COVID-19 is very important. Making vaccines needs a large number of experiments to get labeled targets. However, obtaining tremendous labeled data from experiments is a challenge for humans. Big data analysis has proposed some solutions to deal with this challenge. Big data technology has developed very fast and has been applied in many areas. In the bioinformatics area, big data analysis solves a large number of problems, particularly in the area of active learning. Active learning is a method of building more predictive models with less labeled data. Active learning establishes models with less data by asking the oracle (human) for the most valuable samples to train models. Hence, active learning’s application in making vaccines is meaningful that the scientists do not need to do tremendous experiments. This paper proposed a more robust active learning method based on uncertainty sampling and K-nearest density and applies it to the vaccine manufacture. This paper evaluates the new algorithm with accuracy and robustness. In order to evaluate the robustness of active learners, a new robustness index is designed in this paper. And this paper compares the new algorithm with a pool-based active learning algorithm, density-weighted active learning algorithm, and traditional machine learning algorithm. Finally, the new algorithm is applied to epitope prediction of B-cell data, which is significant to making vaccines.

Developing the imagination skills among students with learning disabilities in English language

This study explored the effect of active learning on developing imagination skills among students with learning disabilities in English language in Irbid city, Jordan. The study used the experimental approach and was applied to a sample of 60 female and male students, who were chosen purposefully. The sample was divided into two groups, an experimental, which was taught using the active learning method, and a control group, which was taught according to the traditional method. The results revealed the existence of significant differences between the performance of the experimental group and the control group on the post-imagination test in favor of the experimental group. The findings also showed statistically significant differences between the scores of the two study groups on the post-imagination test due to the gender variable, and the difference was in favor of males. In light of the findings of the study, the researcher recommended preparing training programs on active learning and preparing a guide for teachers, which can be used to teach and learn reading, writing, and imagination skills in the basic stage.

Emotion recognition using fiducial points via deep learning

Emotion awareness is critical because of the function that emotions play in our daily lives. As a result, automatic emotion recognition aims to provide a machine with the human ability to interpret and comprehend a person's emotional state in order to predict his intents based on his facial expression. In this research, a new method for improving the accuracy of emotion recognition from facial expression is proposed, which is based solely on input attributes deduced from fiducial points. First, 1200 dynamic features representing the percentage of euclidean distances between facial fiducial points in the first frame and facial fiducial points in the last frame are extracted from image sequences. Second, just the most relevant features are chosen using active learning method. Finally, to categorise facial expression input into emotion, the selected features are provided to a ResNet classifier.

Upaya meningkatkan kemampuan motorik halus melalui kegiatan menjahit bervariasi dengan berbagai media di PAUD Alquran Az-Zahra Banyurip Alit

Various sewing activities are an appropriate step in improving children's fine motor skills, because they are used to express themselves. To produce interesting stitches really helps develop a child's imagination in improving their fine motor skills. PAUD Al-Quran Az-Zahra Banyurip Alit Pekalongan City on fine motor activities failed in various sewing materials, this can be seen from the work of children with a total of 20 children who got good grades only 5 children, only 4 children, and less than 11 children. The problem is the lack of physical fine motor skills of children in various sewing activities. This is because the media used is less varied so that children feel bored. So we need an active learning method using various media. The aim of this research is to improve children's fine motor skills in sewing with various media. The benefits are expected to contribute to the development of science. In carrying out the improvement of learning through two cycles. The results of observations and research in the second cycle increased more than the previous cycle. The results of the previous comparison had a success rate of only 45%, the first cycle was 65%, the second cycle reached a 95% success rate. So it can be concluded that sewing activities have a positive impact on fine motor development and can improve children's ability to sew with various media.

Assessing the outcomes of an active learning exercise

PurposeThe purpose of this study is to propose an alternative approach to the think-pair-share active learning method and assess it for outcomes.Design/methodology/approachThis paper evaluates student knowledge of the course content presented in the study (data analytics and artificial intelligence) using a pre- and post-test process with control (lecture-based) and test (active learning) groups. A mixed method approach was used. The quantitative portion included the test scores being analyzed statistically. The qualitative portion included analyzing the open-ended question on the post-test.FindingsThe results note that the active learning exercise improves student learning outcomes in a statistically significant manner (p < 0.001). The open-ended question on the post-test provides positive student feedback.Originality/valueThe active learning exercise used in this study offers an alternate approach to the “think” and “pair” portions of the think-pair-share method and determines whether learning outcomes are improved after implementation of the alternative method.