Enhancing the Quality of Argumentation in School Science

The research reported in this paper focussed on the design of learning environments that support the teaching and learning of argumentation in a scientific context. The research took place over two years between 1999 and 2001 in junior high schools in the greater London area. The research was conducted in two phases. In the first developmental phase, working with a group of 12 science teachers, the main emphasis was to develop sets of materials and strategies to support argumentation in the classroom and to assess teachers‘ development with teaching argumentation. Data were collected by videoing and audio recording the teachers attempts to implement these lessons at the beginning and end of the year. During this phase, analytical tools for evaluating the quality of argumentation were developed based on Toulmin‘s argument pattern. Analysis of the data shows that there was significant development in the majority of teachers use of argumentation across the year. Results indicate that the pattern of use of argumentation is teacher specific, as is the nature of the change. In the second phase of the project, teachers taught the experimental groups a minimum of nine lessons which involved socioscientific or scientific argumentation. In addition, these teachers taught similar lessons to a control group at the beginning and end of the year. Here the emphasis lay on assessing the progression in student capabilities with argumentation. Hence data were collected from several lessons of two groups of students engaging in argumentation. Using a framework for evaluating the nature of the discourse and its quality, the findings show that there was an improvement in the quality of students‘ argumentation. In addition, the research offers methodological developments for work in this field

Progress and prospects for accelerating materials science with automated and autonomous workflows

Accelerating materials research by integrating automation with artificial intelligence is increasingly recognized as a grand scientific challenge to discover and develop materials for emerging and future technologies. While the solid state materials science community has demonstrated a broad range of high throughput methods and effectively leveraged computational techniques to accelerate individual research tasks, revolutionary acceleration of materials discovery has yet to be fully realized. This perspective review presents a framework and ontology to outline a materials experiment lifecycle and visualize materials discovery workflows, providing a context for mapping the realized levels of automation and the next generation of autonomous loops in terms of scientific and automation complexity. Expanding autonomous loops to encompass larger portions of complex workflows will require integration of a range of experimental techniques as well as automation of expert decisions, including subtle reasoning about data quality, responses to unexpected data, and model design. Recent demonstrations of workflows that integrate multiple techniques and include autonomous loops, combined with emerging advancements in artificial intelligence and high throughput experimentation, signal the imminence of a revolution in materials discovery

PENGEMBANGAN BAHAN AJAR IPA TERPADU TIPE INTEGRATED TOPIK NAVIGASI MIGRASI HEWAN DALAM MENINGKATKAN PENGUASAAN KONSEP DAN KETERAMPILAN PROSES SAINS SISWA

The objective of this study is to find out the readability and feasibility of Integrated Science Teaching Materials, learning proses using the teaching materials, the improvement of students’ concept and skill of science processes, students’ and teacher’s responses towards the Integrated Science teaching materials in the topic of navigation of animal migration. This study was conducted to 9th grade students in one of Junior High School in Cianjur Regency in academic year 2016/2017. The research method in this study is mix methods embedded experimental design researchby combining quantitative and qualitative data. This study employed two classes; students in experimental class used Integrated Science Teaching Materials, while students in control class used the book available at school. The research instruments used in this study were instrument of teaching material readability (cloze test) and teaching material feasibility for the aspect of: content, presentation, material and validity, questions of concept mastery and skill of science process, questionnaire of teacher’s and students’ responses to the teaching materials. The rest result of teaching material readability was 82% and classified into independent category, meaning that the teaching materials can be used in the learning process. The test result of feasibility of content, presentation, material and validity was 71%, meaning that the quality of teaching materials is classified into very appropriate category. Data analysis on the concept and students’ skill mastery shows significant difference between experimental and control classes seen from the P-value of 0.001 which is lower than 0.05. Students’ responses to the Integrated Science Teaching Materials show that they are fond to use it since it is easy to learn and improving the attitude of caring the environment and curiosity. Meanwhile, teacher’s responses to the Integrated Science Teaching Materials show that generally the teaching materials are easy to use. Keywords: teaching materials, Integrated Science, student concept mastery, student skill of science process, navigation of animal migration, Penelitian ini bertujuan untuk mengetahui keterbacaan dan kelayakan bahan ajar IPA terpadu tipe integrated, proses pembelajaran menggunakan bahan ajar, peningkatan penguasaan konsep dan keterampilan proses sains siswa, tanggapan siswa dan guru terhadap bahan ajar IPA Terpadu tipe integrated pada topik navigasi migrasi hewan. Penelitian ini dilakukan pada siswa kelas IX di salah satu SMP di Kabupaten Cianjur pada tahun akademik 2016/2017. Metode yang digunakan adalah mix methods embedded experimental design research dengan menggabungkan data kualitatif dan data kuantitatif. Penelitian ini menggunakan dua kelas, siswa pada kelas eksperimen menggunakan bahan ajar IPA terpadu tipe integrated,sedangkan siswa kelas kontrol menggunakan buku yang ada di sekolah. Instrumen penelitian yang digunakan berupa instrumen keterbacaan bahan ajar (tes rumpang) dan kelayakan bahan ajar yang terdiri dariAspek:isi, penyajian, materi dan kebahasaan, soalpenguasaankonsep dan keterampilan proses sains, angkettanggapansiswadan guru terhadapbahan ajar. Hasil uji keterbacaan bahan ajar sebesar 82% kategori independen. Artinya bahan dapat digunakan dalam pembelajaran. Pada uji kelayakan isi,penyajian, materidankebahasaanadalah 71%. Hal ini menjadikan kualitas bahan ajar termasukdalamkategorisangat layak. Analisis data pada penguasaankonsepdan keterampilan proses siswa terdapat perbedaan yang signifikan antara kelasekperimen dan kelas kontrol dilihat dari nilai P-Value 0,001 yang lebih kecil dari 0,05. Tanggapansiswaterhadapbahan ajar IPA Terpadutipeintegratedinimerasa senang dalam menggunakannya, mudah dipelajari, lebih meningkatkan sikap peduli lingkungan,rasa ingin tahu. Tanggapan guru terhadap bahan ajar ini secara garis besar bahwa bahan ajar ini dapat digunakan dengan mudah. Kata-kata kunci: bahan ajar, IPA terpadu tipe integrated, penguasaan konsep siswa, keterampilan proses sains siswa, navigasi migrasi hewa

Progress and prospects for accelerating materials science with automated and autonomous workflows

Accelerating materials research by integrating automation with artificial intelligence is increasingly recognized as a grand scientific challenge to discover and develop materials for emerging and future technologies. While the solid state materials science community has demonstrated a broad range of high throughput methods and effectively leveraged computational techniques to accelerate individual research tasks, revolutionary acceleration of materials discovery has yet to be fully realized. This perspective review presents a framework and ontology to outline a materials experiment lifecycle and visualize materials discovery workflows, providing a context for mapping the realized levels of automation and the next generation of autonomous loops in terms of scientific and automation complexity. Expanding autonomous loops to encompass larger portions of complex workflows will require integration of a range of experimental techniques as well as automation of expert decisions, including subtle reasoning about data quality, responses to unexpected data, and model design. Recent demonstrations of workflows that integrate multiple techniques and include autonomous loops, combined with emerging advancements in artificial intelligence and high throughput experimentation, signal the imminence of a revolution in materials discovery

Improving the Quality of Science Learning in Sound Energy Materials through the Application of Experimental Scientific Learning Models in Class IV of SD Inpres Perumnas

The main factors in the success of science teaching are required to have professional knowledge and abilities in choosing and using appropriate learning methods and models according to the characteristics of students in delivering teaching materials well, so that learning objectives can be achieved. This study aims to describe the application of scientific learning models based on experimental methods to improve the quality of science learning outcomes in sound energy material in the fourth grade of SD Inpres Perumnas. The study method was a classroom action research. The research subjects were 25 students, consisting of 10 male students and 15 female students. The data collection technique was observation and test techniques. Data analysis was carried out by analyzing data qualitatively and quantitatively. The results of the study showed an increase in teacher activity and student activities. The activity of students in the first cycle is 70.45% or sufficient, increasing in the second cycle to 89.77% or very good. Teacher activity in the first cycle was 70.83% or good, and increased in the cycle to 91.67% or very good. Classical absorption (DSK) cycle I was 57.5% in the second cycle to 77.5%. Classical learning completeness (KBK) of the first cycle of 66% increased in the second cycle to 86%. Based on these results, it was concluded that the application of the scientific approach based on the experimental method improved the quality of science learning in the fourth grade of SD Inpres Perumnas

Keefektifan Konseling Kelompok Realita Teknik Wdep Untuk Meningkatkan Kedisiplinan Peserta Didik Kelas VIII SMP Islam Tanen Rejotangan Tahun Pelajaran 2016/2017

Counseling is one of the realities group counseling approach that can reduce student discipline violations are marked with a violation in terms of physical and violation of terms of behavior. With the reality of group counseling is expected students will be responsible for himself and become a person who does not ignore from the 3-R (right, Responsibility, reality). The purpose of this study was to obtain accurate information and data on the effectiveness of group counseling to improve discipline reality of class VIII SMP Islam Tanen Rejotangan Odd Semester Academic Year 2016/1017. This study used a technique quasy-experimental design (quasi-experimental) with a quantitative approach with research subjects eighth grade students of SMP Islam Tanen Rejotangan number of 10 students, divided into 2 groups: 5 students of grade control and 5th grade students experiment. The research was conducted in five counseling sessions, using the instrument scale pretest and posttest discipline students\u27 concentration. The results of the final data analysis is done by using a non-parametric statistical tests Wilcoxon signed rank test with the Sig. (2-tailed) 0.043 N 5 and probabilities indicate that the 0.05 level. As well as the probability value 0.043 <0.05, consequently Ha accepted and H0 is rejected, which means there is no difference between the control and experimental classes. Based on the research that has been done suggestions that should be mentioned is should the teacher guidance and counseling can be used as source materials science to improve the quality of guidance and counseling.   Key words: Reality Group Counseling, Discipline of Students

Artificial Intelligence based Approach for Rapid Material Discovery: From Chemical Synthesis to Quantum Materials

With the advent of machine learning (ML) in the field of Materials Science, it has become obvious that trained models are limited by the amount and quality of the data used for training. Where researchers do not have access to the breadth and depth of labeled data that fields like image processing and natural language processing enjoy. In the specific application of materials discovery, there is the issue of continuity in atomistic datasets. Often if one relies on experimental data mined from literature and patents this data is only available for the most favorable of atomistic data. This ultimately leads to bias in the training dataset. In providing a solution, this research focuses on investigating the deployment of ML models trained on synthetic data and the development of a language-based approach for synthetically generating training datasets. It has been applied to three material science-related problems to prove these approaches work. The first problem was the prediction of dielectric properties, the second problem was the synthetic generation of chemical reaction datasets, and the third problem was the synthetic generation of quantum material datasets. All three applications proved successful and demonstrated the ability to generate continuous datasets that resolve the issue of dataset bias. This first study investigated the synthetic generation of complex dielectric properties of granular powders and their ability to train a ML network. The neural network was trained using a supervised learning approach and a common backpropagation. The network was double-validated using experimental data collected from a coaxial airline experiment. The second study demonstrated the synthetic generation of a chemical reaction database. An artificial intelligence model based on a Variational Autoencoder (VAE) has been developed and investigated to synthetically generate continuous datasets. The approach involves sampling the latent space to generate new chemical reactions that were assembled into the synthetic dataset. This developed technique is demonstrated by generating over 7,000,000 new reactions from a training dataset containing only 7,000 reactions. The generated reactions include molecular species that are larger and more diverse than the training set. The third study investigated a similar variational autoencoder approach to the second study but with the application of generating a synthetic dataset for quantum materials focusing on quantum sensing applications. The specific quantum sensors of interest are two-level quantum molecules that exhibit dipole blockade. This study offers an improved sampling algorithm by continuously feeding newly generated materials into a sampling algorithm to help generate a more normally distributed dataset. This technique was able to generate over 1,000,000 new quantum materials from a small dataset of only 8,000 materials. From the generated dataset it was identified that several iodine-containing molecules are candidate quantum sensor materials for future studies

Experimental Studies in Learning Technology and Child–Computer Interaction

This book is about the ways in which experiments can be employed in the context of research on learning technologies and child–computer interaction (CCI). It is directed at researchers, supporting them to employ experimental studies while increasing their quality and rigor. The book provides a complete and comprehensive description on how to design, implement, and report experiments, with a focus on and examples from CCI and learning technology research. The topics covered include an introduction to CCI and learning technologies as interdisciplinary fields of research, how to design educational interfaces and visualizations that support experimental studies, the advantages and disadvantages of a variety of experiments, methodological decisions in designing and conducting experiments (e.g. devising hypotheses and selecting measures), and the reporting of results. As well, a brief introduction on how contemporary advances in data science, artificial intelligence, and sensor data have impacted learning technology and CCI research is presented. The book details three important issues that a learning technology and CCI researcher needs to be aware of: the importance of the context, ethical considerations, and working with children. The motivation behind and emphasis of this book is helping prospective CCI and learning technology researchers (a) to evaluate the circumstances that favor (or do not favor) the use of experiments, (b) to make the necessary methodological decisions about the type and features of the experiment, (c) to design the necessary “artifacts” (e.g., prototype systems, interfaces, materials, and procedures), (d) to operationalize and conduct experimental procedures to minimize potential bias, and (e) to report the results of their studies for successful dissemination in top-tier venues (such as journals and conferences). This book is an open access publication