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Journal articles on the topic 'Programing learning'
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Jakoš, Franc, and Domen Verber. "Learning Basic Programing Skills With Educational Games." Journal of Educational Computing Research 55, no. 5 (December 2, 2016): 673–98. http://dx.doi.org/10.1177/0735633116680219.
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This study aimed to investigate the effectiveness of using educational games for learning basic programing skills. For this, we designed the game “Aladdin and his flying carpet” with all pedagogical consideration in mind. We conducted the experiment with 107 sixth grade pupils with no prior knowledge of programing. The game was applied at the beginning of the course in a naturalistic classroom environment. The progress was monitored and evaluated with validated pre- and posttests. The knowledge gain was observed according to the set of learning objectives from the general curricula, and minimum knowledge standards were pursued within those. The result demonstrated that most of the pupils achieved all of the observed learning objectives. The biggest progress was observed with the “complete a program” objective. The least progress was observed with the tasks where “create a program” and “divide a problem” objectives were combined. Strong correlation was found between the final results of the posttest and the scores from playing the game, especially with the more challenging “divide a problem” learning objective. Finally, no significant difference was observed in the results between girls and boys.
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Meilasari, Venty. "Pengaruh Penerapan Collaborative Learning Berbantu Ispring Presenter terhadap Hasil Belajar Program Linear." Eksponen 9, no. 2 (September 26, 2019): 52–58. http://dx.doi.org/10.47637/eksponen.v9i2.60.
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This research was aimed to investigate the influence of implementation collaborative learning with ispring presenter toward linear programing outcomes. This research was quantitative research. This also used the pre-experimental design with one-group pretest-posttest design. The sample were all students of the 4th of mathematic departement of Universitas Muhammadiyah Kotabumi in academic year 2017/2018. The sample was taken using purposive sampling. The instruments used was linear programing outcomes test. The conclusions of this research was that there is positive influence of implementation collaborative learning with ispring presenter toward linear programing outcomes.
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Efendi, Yasin, Robinson Situmorang, and Diana Nomida Musnir. "How to Development Learning Models for Programing Algorithms E-Learning Assistance." Journal of Computational and Theoretical Nanoscience 17, no. 2 (February 1, 2020): 1523–33. http://dx.doi.org/10.1166/jctn.2020.8835.
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This research aims to develop a learning model of Programming Algorithms and the Data I Structure of e-learning assistance. Research and development of this model will produce products in the form of print modules, learning designs and e-learning assisted media for Algorithms and Data I Structure courses. Development of learning models for Programming Algorithms and Structure of Data I for e-learning assistance using the Dick and Carey model design modified with the Trollip and Alessi models. The steps taken in the development of this model are preliminary research, planning and model development, validation, evaluation and revision of the model, and implementation of the model. Validation results from experts consisting of 93% learning design experts, 95% material experts, and 87% of media experts recommend that this development model is used in learning Programming Algorithms and Structure of Data I. As for the implementation of individual trials are achieved 95% achievement, a small group trials reaching 95%, and a field test achieved 96% success. The conclusion of the expert validation process and the results of trials, that the development of learning models of Programming Algorithms and Structure of Data I for e-learning assistance is feasible to be used in learning.
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Milad, Khaled. "The Effectiveness Of Incorporating Interactive Learning Platforms To Programming Lectures." مجلة آفاق للدراسات الإنسانية والتطبيقية, no. 1 (April 18, 2024): 245–53. http://dx.doi.org/10.37376/ajhas.vi1.4845.
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Programming is one of the most important aspects of a computing course. Despite the significance of the programming as among core courses in studying computer science, its curriculum hours have been reduced over time in many faculties. Moreover, some new programming languages need a lot of time to learn and practice , and students do not find time through time of classes ,which compromised the students’ ability to learn and understand . Many studies have shown evidence of progressive interest of computer science students in using Interactive Learning Platform(ILP) in learning programing subjects, however there is still controversy about the positive impact of ILP on student performance and learning. The aim of this study was to investigate the impact and effectiveness of incorporating using ILP to the programming lectures on the performance of the computer science department students in faculty of arts and science Alabyar ,university of Benghazi. The results of this study revealed that students who were given lecture combined with ILP have shown enhancement in performance compared to others who were given ordinary lecture. KEY WORDS: programming languages teaching, programming learning, Interactive Learning Platform(ILP).
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Doyle, Antoinette, and Ling Li. "Family-Focused Early Learning Programing: Access, Opportunities, and Issues in one Canadian Context." SAGE Open 11, no. 4 (October 2021): 215824402110469. http://dx.doi.org/10.1177/21582440211046943.
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Family-focused early learning programs aim to assist parents in supporting their young children language and literacy development. This study examined program access and learning opportunities for diverse families across a wide range of community-based settings in one eastern Canadian province. As well, the study examined practitioners’ perspectives on issues related to program development and implementation. Primarily through surveys, practitioners provided data on more half of all community-based programs in the province. The findings of the study showed that most programs offered a form of parent and child focused drop-in play as the core of their programing. Few programs offered a more formalized parent-facilitator learning component as is sometimes found in other jurisdictions. The issues and challenges in programing identified by practitioners included attracting participants, maintaining funding and expanding program activities, and staff training to expand and enhance programing to meet the needs of families. These issues are discussed in light of current public policy and practice.
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Keandoungchun, Nantapong, Jitimon Angskun, and Thara Angskun. "Motivation to Learning Computer Programing Using a Game Application." International Journal of Information and Education Technology 13, no. 11 (2023): 1755–60. http://dx.doi.org/10.18178/ijiet.2023.13.11.1986.
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Computer programming is a course studied in almost all fields; nevertheless, the survey found that many students obtain low grades or withdraw from the computer programming course because the students lack the motivation to learn. This article proposes the development of a game application for motivating computer programming learning. The contents of computer programming lessons are designed in the game style. In addition, gamification concepts encourage the students to learn the lessons. This research assesses the student’s motivation to study the C language program. The sample consisted of 245 students studying C language. The motivation assessment questionnaire was divided into seven aspects, namely 1) a Future-oriented person, 2) an Ambitious person, 3) a Diligent person, 4) a Success-oriented person, 5) a Responsible person, 6) a Hardworking person, and 7) a Venturesome person. The evaluation results indicated that the game application encourages students to learn computer programming. When considering students’ motivation before and after learning using the game application, the results revealed that the average motivation in all seven aspects increased significantly. The aspect of ambitious person differed significantly at the 0.01 level, while the aspects of future-oriented, diligent, responsible, hardworking, and venturesome persons differed significantly at the 0.05 level.
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Qureshi, Muhammad Aasim, Muhammad Asif, and Faria Feroz. "Context-Free Grammar of a New Programming Language for Teaching and Learning." VFAST Transactions on Software Engineering 9, no. 4 (December 31, 2021): 160–66. http://dx.doi.org/10.21015/vtse.v9i4.1016.
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Learning how to be programmer and uralitize the programming languages are the crucial point in computer science education. Programming languages are used by the students to write the program. Any machine needs a program to behave artificially intelligent or to perform any specific task. Any computing device is a useless without these programs. As every program is written in some specific programming language. Researchers are putting efforts in devising new languages to meets the goals and requirements of the specific domain of the programs that is going to be written in that language. Every programming language has its own semantics, nuances, and syntax with its pros and cons. For the early stage programmers these language specific details including semantics and syntax are hard to memorize or to familiar with it. Teachers often witness that these language specific barriers e.g., tough and confusing syntax of the language give hard time to students. Students generally stuck in learning the syntax and unconsciously learning programming skills go in back ground. This paper is going to present a Context-Free Grammar of a new programming language for early stage programing learners. In this language the hard part of syntax is relaxed by bring it to something that is close to their day to day communication so that they concentrate on logic and not on syntax.
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A. Alhassan, Riyadh, and Yousef Y. Alfaifi. "The Effect of Using Flipped Classroom Strategy on Learning Computer Programing in Visual Basic and Students’ Attitudes Towards Learning Computer Programming." Journal of Educational & Psychological Sciences 19, no. 03 (September 3, 2018): 47–85. http://dx.doi.org/10.12785/jeps/190302.
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MANDARIA, George. "Methodology of Teaching Dynamic Programming." Journal of Technical Science and Technologies 3, no. 1 (September 16, 2014): 15–18. http://dx.doi.org/10.31578/jtst.v3i1.84.
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In this article the methodology of learning dynamic programing is described. Mentioned methodology is one of the main methods of solvingsome programming problems and foresees dividing one problem into such sub problems that using their solutions will be possible to build thesolution of initial problem. The realization of this method needs memorizing the solutions of sub problems, thus, the dynamic tables are used.As well as that the solutions of sub problems and recursive dependence are explained in this article. It is showed how to use recursive dependencein order to divide a problem into sub problems. Moreover, some sample problems and their solutions are included.
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Kawamura, Sadao, Norihisa Fukao, and Hiroaki Ichii. "Teaching and Programing for Robots. Teaching and Learning for Robot Manipulators." Journal of the Robotics Society of Japan 17, no. 2 (1999): 162–65. http://dx.doi.org/10.7210/jrsj.17.162.
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Chuang, Huan-Ming, and Chia-Cheng Lee. "Effects of Personal Construal Levels and Team Role Ambiguity on the Group Investigation of Junior High School Students’ Programming Ability." Sustainability 13, no. 19 (October 2, 2021): 10977. http://dx.doi.org/10.3390/su131910977.
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Concerns regarding the high demand for skilled personnel in the science, technology, engineering, and mathematics (STEM) fields underline the importance of developing advanced information technology (IT) and programming skills among job candidates. In the past 10 years, computer programming has regained considerable attention because of rapid developments in computer programming technology. Advocates claim that computer programming cultivates other skills, including problem solving, logical thinking, and creativity. Education systems worldwide are developing courses to instruct students in programming and computational thinking. Although the importance of computer programming has been widely recognized, the systematic evaluation of the effectiveness of teaching methods and conditions that promote the learning of programming knowledge and skills has received little scholarly attention. This study thus investigated the moderating roles of learners’ construal levels and their team role ambiguity in the context of group investigation in junior high school programing courses. In this study, junior high school students were divided into pairs to develop Arduino projects. Students applied programming abilities to complete a task involving the use of Arduino boards to simulate the operation of traffic lights. Major research findings indicate that construal levels play a significant role in moderating the relationship between programming ability and learning outcome; however, role ambiguity does not significantly affect this relationship. Theoretical implications are discussed, and managerial implications are suggested.
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Santos, Francisco Alan De Oliveira. "A Tool for Assisted Correction of Programming Exercises in Java Based in Computational Reflection." Journal on Computational Thinking (JCThink) 2, no. 1 (November 21, 2018): 51. http://dx.doi.org/10.14210/jcthink.v2.n1.p51.
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INTRODUCTION: This work reports on the creation and use of a tool to verify compliance in java programming exercises. The solution is based on the hypothesis that computational reflection can provide a way to automatically assess the programing competences of students. The work reflects the concern to make students learning a programming language have practical activities in parallel to what they learn in theoretical classes. OBJECTIVE: Attesting the effectiveness of using computational reflection to automatically correct programming exercises. Provide the teacher with a tool to support the follow-up of practical activities. Provide students with immediate feedback on their learning, so as to encourage them to behave more autonomously. METHOD: A case study was carried out with two classes of a computer sciencecourse. They answered five practical programming exercices and their responses for each activity were collected in source code format, which were used as the basis of solutions, totaling 100 responses.A comparative analysis was made between the notes obtained through CodeTeacher and the notes assigned by a group of teachers. RESULTS: Comparing the expected notes and the actual notes, the automatic correction obtained an accuracy of 90.17%. CONCLUSION: The use of computational reflection techniques for assisted correction in programming classes can bring beneficial result. Teachers can optimize their work and have performance reports of their students. Students can also be benefited by having an immediate feedback, so they can perceive themselves capable of achieving the learning objectives defined by the teacher.
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Mtaho, Adam B., Masoud M. Masoud, and Leonard J. Mselle. "РОЗРОБЛЕННЯ НАВЧАЛЬНОГО ІНСТРУМЕНТУ ПРОГРАМУВАННЯ CELIOTM ДЛЯ НАВЧАННЯ КОНЦЕПЦІЙ СТРУКТУР ДАНИХ У C++ ПРОГРАМІСТІВ-ПОЧАТКІВЦІВ." Information Technologies and Learning Tools 101, no. 3 (June 28, 2024): 42–70. http://dx.doi.org/10.33407/itlt.v101i3.5567.
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Programming is the core skill in computer science (CS) education. It is also a useful course in engineering and science-based courses. However, teaching and learning computer programming has not been an easy task. This is evidenced by the fact that majority of the students face challenges and difficulties in understanding programming concepts and how to apply them in real-life scenarios. The situation is worse for the Data Structures and algorithms (DSA) course, an advanced-level programming course that is mandatory for any CS student. The subject is too hard for novices to grasp due to its abstract and dynamic nature. To address such difficulties, several algorithm visualization (AV) tools have been introduced to help novices understand data structure. However, the pedagogical effectiveness of using such tools has not been successful because they are less engaging for learning DSA. This paper describes how the CeliotM programming learning tool was developed to facilitate learning data structure concepts in C++. The development of CeliotM was achieved by using reuse-oriented software engineering approach. CeliotM was developed by redesigning a Celiot program visualization (PV) tool-a programing learning tool that supporting learning programming in C++. Thus, by using Java as the language, the original version of Celiot was resigned to support compilation and visualization of various data structure elements in Memory Transfer Language (MTL) format; and incorporate several learner engagement features, including the inbuilt C++ compiler and animation explanations. The resulting tool is a CeliotM programming learning tool that visualizes and compiles data structure objects such as queues, stacks, and linked lists in C++ programming language. Empirical results on the evaluation of using CeliotM in teaching data structures and algorithmic concepts reveal that using such tool enhanced students’ programming comprehension and offered a more appealing learning experience for novice programmers. The greatest contribution of this work is to provide an education tool for teaching data structures in C++ that can work as a compiler, program and algorithm visualization tool in tandem. It also contributes a valuable resource to programming education, offering an effective and inspiring approach for novices to grasp fundamental programming and data structure concepts.
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Shiraishi, Junji. "C-programing for Image Processing: Introduction of the Experience-based E-learning." Japanese Journal of Radiological Technology 72, no. 10 (2016): 1049–51. http://dx.doi.org/10.6009/jjrt.2016_jsrt_72.10.1049.
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Yan, Yupei, Weimin Ma, Sengfat Wong, Xuemei Yin, Qiang Pan, Zhiwen Liao, and Xiaoxin Lin. "The Navigation of Home Service Robot Based on Deep Learning and Machine Learning." Journal of Robotics 2024 (February 12, 2024): 1–18. http://dx.doi.org/10.1155/2024/5928227.
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This paper discusses how to improve the accuracy of navigation for home service robot based on the deep learning and machine learning. First, the crawling programing is applied to collect enough images of fridge and washing machine on the web; a deep learning framework is proposed that can distinguish fridge and washing machine more accurately. Following, the data come from the robot operating system topics are collected and cleaned, the linear regression, decision tree, and linear SVR algorithms are applied and compared to predict the power consumption of the robot, and a conclusion is obtained that liner movement will consume more power, which provides a reference for the path planning of the robot. Lastly, the conclusions are proposed that a novel methodology is applied to distinguish different home appliances, which is useful for the accurate navigation of the robot; the liner movement will consume more power compared to turning left or right, which supplies a reference for the optimized path planning for the robot.
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Montesinos López, Osval A., Brandon Alejandro Mosqueda Gonzalez, Abelardo Montesinos-Lopez, and José Crossa. "Statistical Machine-Learning Methods for Genomic Prediction Using the SKM Library." Genes 14, no. 5 (April 28, 2023): 1003. http://dx.doi.org/10.3390/genes14051003.
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Genomic selection (GS) is revolutionizing plant breeding. However, because it is a predictive methodology, a basic understanding of statistical machine-learning methods is necessary for its successful implementation. This methodology uses a reference population that contains both the phenotypic and genotypic information of genotypes to train a statistical machine-learning method. After optimization, this method is used to make predictions of candidate lines for which only genotypic information is available. However, due to a lack of time and appropriate training, it is difficult for breeders and scientists of related fields to learn all the fundamentals of prediction algorithms. With smart or highly automated software, it is possible for these professionals to appropriately implement any state-of-the-art statistical machine-learning method for its collected data without the need for an exhaustive understanding of statistical machine-learning methods and programing. For this reason, we introduce state-of-the-art statistical machine-learning methods using the Sparse Kernel Methods (SKM) R library, with complete guidelines on how to implement seven statistical machine-learning methods that are available in this library for genomic prediction (random forest, Bayesian models, support vector machine, gradient boosted machine, generalized linear models, partial least squares, feed-forward artificial neural networks). This guide includes details of the functions required to implement each of the methods, as well as others for easily implementing different tuning strategies, cross-validation strategies, and metrics to evaluate the prediction performance and different summary functions that compute it. A toy dataset illustrates how to implement statistical machine-learning methods and facilitate their use by professionals who do not possess a strong background in machine learning and programing.
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Chiang, Tosti Hsu-Cheng. "Analysis of learning behavior in a flipped programing classroom adopting problem-solving strategies." Interactive Learning Environments 25, no. 2 (February 17, 2017): 189–202. http://dx.doi.org/10.1080/10494820.2016.1276084.
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Icha Amelia and Yahfizham Yahfizham. "Konsep Pembelajaran Mahasiswa Dalam Memahami Algoritma Melalui Komputer Pemograman." Jurnal Teknik Informatika dan Teknologi Informasi 3, no. 3 (November 15, 2023): 64–69. http://dx.doi.org/10.55606/jutiti.v3i3.2885.
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A programing algorithm means a number of activities to complate a process. Its done according to the procedure. Algorithm can be basis for the development of computer programs. The core of the science is algorithms.. The literary based on data metodology found in various refrences. The goal is tho get help students recognize and faciliate student understanding theeby increasing motivation in learning.
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Gashi, Syzana. "Enhancing Students’ Self-confidence in the EFL Classroom through Neuro-Linguistic Programing Technique - Reframing." Academicus International Scientific Journal 30 (July 2024): 138–52. http://dx.doi.org/10.7336/academicus.2024.30.10.
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This research paper deals with self-confidence and how the application of Neuro-Linguistic Programming (NLP) technique, six-step reframing, plays a crucial role in students’ self-confidence in the English as a foreign language (EFL) classroom. It analyses the effectiveness of incorporating NLP six-step reframing on students’ self-confidence levels across different age groups, cultural backgrounds, and academic settings. This provides an opportunity for learners to gain self-confidence, helping them to truly believe in themselves, and allowing them to feel ‘seen, heard, and understood’. Reframing, drawing from Neuro-Linguistic Programming (NLP), enables learners to see mistakes as an integral parts of learning process and also helps to refine their skills which are crucial for language acquisition. The research includes sixty-six students who differ based on criteria such as age, cultural backgrounds, and learning experience. Quantitative methods through questionnaires and qualitative methods, through observation and interviews, have been helpful in conducting this research paper. The results have shown a significant effect of incorporating NLP’s six-step reframing within the pedagogical framework, shedding light on its potential to empower students’ self-confidence challenges commonly encountered in language learning environments. The study has shown that, even students encounter difficulties or setbacks in language learning, the incorporation of six-step reframing technique has proven to be a transformative approach. By systematically identifying dissatisfaction, establishing clear signals, alternative behaviors, eliciting positive intentions, and encouraging students’ self-confidence in learning a foreign language. This psychological tool not only contributes to language proficiency but also empowers students to navigate the complexities of the EFL classroom with confidence and adaptability.
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Laksono, Joko. "Improving Student Learning Independence by Applying the Peer-Tutoring Method in Basic Programming Subjects for Vocational High School." Jurnal Guru Komputer 2, no. 1 (November 8, 2023): 19–26. http://dx.doi.org/10.17509/jgrkom.v2i1.63946.
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Learning method is a method or effort made by the process of educators so that the teaching and learning process of student is achieved in accordance with the objectives. This learning method is very important to do so that the teaching and learning process is fun and does not make the students too tired, and the student can easily grasp the knowledge of the educators. One learning method that can be used to improve student abilities is using the peer tutoring method. The peer tutoring method is a learning pattern in which a person or several clever students are appointed by the teacher to provide learning assistance for students who are less intelligent. In this study, using the peer tutoring method in basic programing subject was proven to increase the independence of student.
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Abbass, Mahmoud Abdelkader Bashery, and Hyun-Soo Kang. "Drone Elevation Control Based on Python-Unity Integrated Framework for Reinforcement Learning Applications." Drones 7, no. 4 (March 24, 2023): 225. http://dx.doi.org/10.3390/drones7040225.
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Reinforcement learning (RL) applications require a huge effort to become established in real-world environments, due to the injury and break down risks during interactions between the RL agent and the environment, in the online training process. In addition, the RL platform tools (e.g., Python OpenAI’s Gym, Unity ML-Agents, PyBullet, DART, MoJoCo, RaiSim, Isaac, and AirSim), that are required to reduce the real-world challenges, suffer from drawbacks (e.g., the limited number of examples and applications, and difficulties in implementation of the RL algorithms, due to difficulties with the programing language). This paper presents an integrated RL framework, based on Python–Unity interaction, to demonstrate the ability to create a new RL platform tool, based on making a stable user datagram protocol (UDP) communication between the RL agent algorithm (developed using the Python programing language as a server), and the simulation environment (created using the Unity simulation software as a client). This Python–Unity integration process, increases the advantage of the overall RL platform (i.e., flexibility, scalability, and robustness), with the ability to create different environment specifications. The challenge of RL algorithms’ implementation and development is also achieved. The proposed framework is validated by applying two popular deep RL algorithms (i.e., Vanilla Policy Gradient (VPG) and Actor-Critic (A2C)), on an elevation control challenge for a quadcopter drone. The validation results for these experimental tests, prove the innovation of the proposed framework, to be used in RL applications, because both implemented algorithms achieve high stability, by achieving convergence to the required performance through the semi-online training process.
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Felgueiras, Manuel Carlos, Dinis Areias, Andre Fidalgo, Clovis Petry, and Gustavo Alves. "Using Remote Lab for Enhancing E-Learning on FPAAs." International Journal of Online Engineering (iJOE) 12, no. 04 (April 28, 2016): 58. http://dx.doi.org/10.3991/ijoe.v12i04.5230.
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Analog and digital electronic subjects are part of the electronic engineer degree but its taught is not easy because they are founded in opposite methodologies. The electronic design in the digital field is centered in the use of microprocessor and FPGA based circuits using high level programing/configuring languages. The counterpart analog design is traditionally based in the use of elementary components associated with macroblocks such operational amplifiers in order to built-up the wanted mission circuit. Some few components, as the FPAA, are analogically configurable in a similar manner already used with the FPGA. However the use of this kind of components is not straightforward once is necessary acquire some concepts not taught in the traditionally analog electronic classes. The current work present an innovative remote lab to support teaching of the FPAAs.
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Field, Matthew, David Stirling, Zengxi Pan, and Fazel Naghdy. "Learning Trajectories for Robot Programing by Demonstration Using a Coordinated Mixture of Factor Analyzers." IEEE Transactions on Cybernetics 46, no. 3 (March 2016): 706–17. http://dx.doi.org/10.1109/tcyb.2015.2414277.
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Priwantoro, Soffi Widyanesti, and Syariful Fahmi. "DEVELOPMENT AND EFFECTIVENESS OF GEOGEBRA BASED LEARNING MEDIA REVIEWED FROM LEARNING RESULT AND SELF CONFIDENT." At-Taqaddum 11, no. 1 (July 31, 2019): 1. http://dx.doi.org/10.21580/at.v11i1.3202.
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<p class="EMAIL"><em>This study aims to develop Geogebra-based learning media in linear programing course for semester V students of Mathematics Education, Ahmad Dahlan University. The effectivenss of this learning media is measured based on student learning outcomes and confidence. The development model used is the borg and Gall development model that includes: (1) standard content analysis, (2) </em><em>multimedia reference collection, (3) multimedia design, and (4) manufacture of GeoGebra-based learning media in the form of applets. The revision of learning media assessed by the material and learning experts, media experts and tested on the students, both small and large classes, I,e 38 students of mathematics education university Ahmad Dahlan. Learning media generated have good quality (B) according to the assessment of material and learning experts, media experts, and 38 students, with an average score of 209.48 from a maximum score of 260. The effectiveness of instructional media viewed from two aspects: student confidence and results learn. Geogebra-based learning media is effective regarding student self-confidence and student learning outcomes in linear course.</em></p>
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Zabel, Robert K., and Anne M. Bauer. "Drug and Alcohol Exposed Children: Implications for Special Education for Students Identified as Behaviorally Disordered." Behavioral Disorders 17, no. 1 (November 1991): 72–79. http://dx.doi.org/10.1177/019874299101700101.
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Children who have been prenatally exposed to cocaine will soon be entering the educational system. This is occurring concurrently with a new awareness of the impact of fetal alcohol effects on children's learning. In this article, the literature on children prenatally exposed to drugs and alcohol is reviewed. The potential impact on the educational and social services systems is discussed. And implications for programing for children identified as behaviorally disordered are presented.
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Ali, Mehdi, Charles Tapley Hoyt, Daniel Domingo-Fernández, Jens Lehmann, and Hajira Jabeen. "BioKEEN: a library for learning and evaluating biological knowledge graph embeddings." Bioinformatics 35, no. 18 (February 15, 2019): 3538–40. http://dx.doi.org/10.1093/bioinformatics/btz117.
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Abstract Summary Knowledge graph embeddings (KGEs) have received significant attention in other domains due to their ability to predict links and create dense representations for graphs’ nodes and edges. However, the software ecosystem for their application to bioinformatics remains limited and inaccessible for users without expertise in programing and machine learning. Therefore, we developed BioKEEN (Biological KnowlEdge EmbeddiNgs) and PyKEEN (Python KnowlEdge EmbeddiNgs) to facilitate their easy use through an interactive command line interface. Finally, we present a case study in which we used a novel biological pathway mapping resource to predict links that represent pathway crosstalks and hierarchies. Availability and implementation BioKEEN and PyKEEN are open source Python packages publicly available under the MIT License at https://github.com/SmartDataAnalytics/BioKEEN and https://github.com/SmartDataAnalytics/PyKEEN Supplementary information Supplementary data are available at Bioinformatics online.
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Howley, Iris. "Adapting guided inquiry learning worksheets for emergency remote learning." Information and Learning Sciences 121, no. 7/8 (June 17, 2020): 549–57. http://dx.doi.org/10.1108/ils-04-2020-0086.
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Purpose Process-oriented guided inquiry learning (POGIL) is a series of learning activities building on student prior knowledge guiding them to construct their own understanding of new concepts in collaborative roles. This paper aims to illustrate how POGIL worksheets can be adapted for low bandwidth and low-computing environments to accommodate the largest swathe of learners in higher education, as was the case during the switch to emergency remote learning in 2020. Design/methodology/approach The POGIL worksheets in this paper scaffold the discovery of new concepts while providing sample computer program output, guiding students to make predictions about the connection between program input and program output. Answers are provided to these questions after completion so that students may check their understanding or look to the answers as worked examples. These POGIL worksheets were used for the past two years in an in-person classroom situation with minimal computing resources, replacing 4/5 of a classroom lecture doing POGILs collaboratively. In the midst of emergency remote learning, these worksheets were adapted to complement asynchronous lecture videos, and also serve as lecture replacement as needed. Findings This paper discusses an approach to adapting POGIL worksheets for introduction to computer science for students who may not have the necessary digital tools (programing software, bandwidth for streaming video, etc.). While the context for this paper is computer science, POGIL has a deep history in chemistry education and other natural sciences, suggesting an approach that may be adapted for situations where hands-on laboratory experiments may not be possible. Originality/value CS-POGIL has many materials available for computer science, but this paper discusses 23 new worksheets and how to adapt them to the novel situation of emergency remote teaching.
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Wheeler, MS, Monique, and Fiona Donovan. "Utilizing teachers to enhance student recovery through emergency educational programming: A case study analysis of Hurricane Maria." Journal of Emergency Management 20, no. 6 (November 1, 2022): 561–80. http://dx.doi.org/10.5055/jem.0726.
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Emergency educational programing after disasters contributes to the physical, cognitive, and psychological protection of students when they are at their most vulnerable. The Inter-Agency Network for Education in Emergencies Minimum Standards for Education in Emergencies framework details the need to incorporate specific domains throughout implementation and asserts that teachers and educational institutions play a significant role in supporting disaster-affected youth in the classroom. Following the detrimental impact of Hurricane Maria on Puerto Rico, teachers became critical agents for maintaining the well-being of children at school, so the goals of this analysis are to (1) examine teachers’ post-hurricane experiences to find out how the event impacted physical teaching environments and students’ learning capacity, (2) investigate how teachers adapted and developed lesson plans to facilitate students’ processing of the event, and (3) explore what resources, training, and emotional support teachers needed to continue their work in the classroom post-disaster. Findings reveal how teachers assumed the role of first responders to restore their physical learning spaces, improvised classroom activities, and discussions to aid in students’ cognitive and emotional recovery, and found ways to navigate and address the psychological needs of learners following this traumatic event. This research will contribute to an increased understanding of how teachers can be utilized to enhance students’ recovery through the successful implementation of emergency educational programing.
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Sabita, Hary, Fitria Fitria, and Riko Herwanto. "ANALISA DAN PREDIKSI IKLAN LOWONGAN KERJA PALSU DENGAN METODE NATURAL LANGUAGE PROGRAMING DAN MACHINE LEARNING." Jurnal Informatika 21, no. 1 (June 30, 2021): 14–22. http://dx.doi.org/10.30873/ji.v21i1.2865.
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This research was conducted using the data provided by Kaggle. This data contains features that describe job vacancies. This study used location-based data in the US, which covered 60% of all data. Job vacancies that are posted are categorized as real or fake. This research was conducted by following five stages, namely: defining the problem, collecting data, cleaning data (exploration and pre-processing) and modeling. The evaluation and validation models use Naïve Bayes as a baseline model and Small Group Discussion as end model. For the Naïve Bayes model, an accuracy value of 0.971 and an F1-score of 0.743 is obtained. While the Stochastic Gradient Descent obtained an accuracy value of 0.977 and an F1-score of 0.81. These final results indicate that SGD performs slightly better than Naïve Bayes.Keywords—NLP, Machine Learning, Naïve Bayes, SGD, Fake Jobs
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Tsuji, Tosio, Hiromasa Akamatsu, Kensue Harada, and Makoto Kaneko. "Teaching and Programing for Robots. On-line Learning of Robot Arm Impedance Using Neural Networks." Journal of the Robotics Society of Japan 17, no. 2 (1999): 234–41. http://dx.doi.org/10.7210/jrsj.17.234.
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De HAAS, Ivone, Juliana Selvina Molle, and Darma Andreas Ngilawajan. "PENINGKATAN HASIL BELAJAR SISWA PADA MATERI PROGRAM LINIER DENGAN MENGGUNAKAN MODEL PEMBELAJARAN PROBLEM BASED LEARNING." JUPITEK: Jurnal Pendidikan Matematika 3, no. 1 (May 21, 2020): 7–12. http://dx.doi.org/10.30598/jupitekvol3iss1pp7-12.
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The purpose of this research is to improve students’ learning outcome on the topic liniear programing by using Problem Based Learning. This research is conducted in 11th grade students of senior high school 1 Saparua in academic year 2019/ 2020. Total number students on experiment grup is 25. This research took 2 cycles in order to achieve passing grade by most students. Every cycle consists of two class meeting. Data collected by using essay tests on each cycle and observation sheet. Further more, data analyzed by using qualitative nd quantitative analysis. The results show that students’ achievement on cycle I which reached passing grade is 56% of total number students. Meanwhile, students’ achievement which reached passing grade on cycle II is 80% of total number of students. There can be concluded that students’ learning outcome has improved 24% through Problem Based Learning
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Katiyar, Dr Alok, Sajid Ali, and Sameer Ray. "Multiple Disease Prediction Using ML." International Journal of Recent Technology and Engineering (IJRTE) 12, no. 1 (May 30, 2023): 15–18. http://dx.doi.org/10.35940/ijrte.a7568.0512123.
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Accurate and on-time analysis of any health-related drawback is vital for the interference and treatment of the sickness. The normal method of diagnosing might not be sufficient within the case of a significant illness. Developing a medical diagnosing system supported machine learning (ML) algorithms for prediction of any unwellness will facilitate during a lot of correct diagnosis than the standard methodology. We've designed a disease prediction system using ML. Disease Prediction System using Machine Learning could be a system that predicts the sickness supported data or symptoms that he/she enter into the system and gives correct results supported that data. This predictive disease using Machine Learning is completed entirely with the assistance of Learning Machines and Python programing language with its Flask Interface and mistreatment antecedently offered databases with hospitals that use that we'll predict the unwellness.
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Mao, Lidan. "Application of Browser/Server Architecture in College English Online Learning System Design." International Journal of Emerging Technologies in Learning (iJET) 13, no. 03 (March 5, 2018): 129. http://dx.doi.org/10.3991/ijet.v13i03.8395.
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In order to realize the information management of college English learning, im-prove the management efficiency of college English teaching, and reform the tra-ditional applied teaching mode, this paper proposed to design a college English online learning system, which uses Browser/Server (B/S) as the architecture, JSP technology as the programing language, and MySQL database technology as the data storage and management database. Then, this paper fully analyzed the re-quirements of network English teaching and management and the demands of system users. On this basis, functional module, database design and overall sys-tem architecture were designed, with the relevant interface displayed. The design and implementation of the system can improve the efficiency and quality of Eng-lish teaching and effectively advance the teaching level of college English, which can be applied into extensive fields.
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Zhang, Renshan, Su Cao, Kuang Zhao, Huangchao Yu, and Yongyang Hu. "A Hybrid-Driven Optimization Framework for Fixed-Wing UAV Maneuvering Flight Planning." Electronics 10, no. 19 (September 23, 2021): 2330. http://dx.doi.org/10.3390/electronics10192330.
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Performing autonomous maneuvering flight planning and optimization remains a challenge for unmanned aerial vehicles (UAVs), especially for fixed-wing UAVs due to its high maneuverability and model complexity. A novel hybrid-driven fixed-wing UAV maneuver optimization framework, inspired by apprenticeship learning and nonlinear programing approaches, is proposed in this paper. The work consists of two main aspects: (1) Identifying the model parameters for a certain fixed-wing UAV based on the demonstrated flight data performed by human pilot. Then, the features of the maneuvers can be described by the positional/attitude/compound key-frames. Eventually, each of the maneuvers can be decomposed into several motion primitives. (2) Formulating the maneuver planning issue into a minimum-time optimization problem, a novel nonlinear programming algorithm was developed, which was unnecessary to determine the exact time for the UAV to pass by the key-frames. The simulation results illustrate the effectiveness of the proposed framework in several scenarios, as both the preservation of geometric features and the minimization of maneuver times were ensured.
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Kumari, Madhulata, Neeraj Tiwari, and Naidu Subbarao. "A genetic programming-based approach to identify potential inhibitors of serine protease of Mycobacterium tuberculosis." Future Medicinal Chemistry 12, no. 2 (January 2020): 147–59. http://dx.doi.org/10.4155/fmc-2018-0560.
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Aim: We applied genetic programming approaches to understand the impact of descriptors on inhibitory effects of serine protease inhibitors of Mycobacterium tuberculosis ( Mtb) and the discovery of new inhibitors as drug candidates. Materials & methods: The experimental dataset of serine protease inhibitors of Mtb descriptors was optimized by genetic algorithm (GA) along with the correlation-based feature selection (CFS) in order to develop predictive models using machine-learning algorithms. The best model was deployed on a library of 918 phytochemical compounds to screen potential serine protease inhibitors of Mtb. Quality and performance of the predictive models were evaluated using various standard statistical parameters. Result: The best random forest model with CFS-GA screened 126 anti-tubercular agents out of 918 phytochemical compounds. Also, genetic programing symbolic classification method is optimized descriptors and developed an equation for mathematical models. Conclusion: The use of CFS-GA with random forest-enhanced classification accuracy and predicted new serine protease inhibitors of Mtb, which can be used for better drug development against tuberculosis.
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Chen, David, and Jolon Faichney. "Flipping a Programing Class to Improve Student Performance and Student Satisfaction." International Journal of Adult Vocational Education and Technology 10, no. 1 (January 2019): 27–39. http://dx.doi.org/10.4018/ijavet.2019010103.
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Flipped classrooms are an instructional strategy that is becoming popular in educational contexts, particularly higher education. The principle of Flipped Classroom is that events that have traditionally taken place inside the classroom now take place outside the classroom and vice versa. Various studies have reported increased student performance and satisfaction after switching to a flipped classroom. However, most of these studies are based on students' perceptions of their own learning, not based on teachers' assessment of students' achievements. This article presents the results of flipping a computer programming course. It first describes how this course was flipped, then it presents the results of comparing the average marks awarded to students between those that took the course offering in flipped mode and those that took the course in the traditional mode. The comparison showed an increase in student performance in a flipped mode. Furthermore, the increase in student performance was sustained for 3 years, which is the full duration of this study. The comparison of student satisfaction showed an increase in student satisfaction in one campus, while the student satisfaction remained steady in another campus.
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Li, Xinrong, Dongfeng Liu, and Xiangyu Zhang. "A System Integrated with C# Programing and Real-Time 3D Observation for Learning Virtual Reality Technology." Open Journal of Social Sciences 07, no. 03 (2019): 127–35. http://dx.doi.org/10.4236/jss.2019.73009.
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Reeve, Doug, Greg Evans, Annie Simpson, Robin Sacks, Estelle Oliva-Fisher, Cindy Rottmann, and Patricia Sheridan. "Curricular and Co-curricular Leadership Learning for Engineering Students." Collected Essays on Learning and Teaching 8 (June 12, 2015): 1. http://dx.doi.org/10.22329/celt.v8i0.4283.
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In recent years engineering educators have been encouraged to blend technical and professional learning in their curricular and co-curricular programing (EC, 2009; NAE, 2004). Our paper describes a multifaceted leadership learning program developed to achieve this goal by infusing reflective, experiential learning into an otherwise technically oriented discipline. The program was designed by a collaborative team of educators and researchers with backgrounds in engineering, education, psychology, and industry and offers a range of learning experiences using diverse pedagogical strategies. The content covers four realms of leadership corresponding to four levels of analysis: self, team, organization, and society. Learning experiences include elective academic courses, co-curricular workshop programs, guest lectures in core courses, seminars, department based leadership groups, and panel discussions. In this paper, we describe the program goals, curricular and co-curricular initiatives and early research findings in order to scaffold an emerging discussion about engineering leadership education in Canada. Informal feedback from students who have participated in our program provide us with preliminary evidence that students are learning, that they value the learning opportunities afforded by our program and that our initiative is enabling significant personal growth.
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Laranjeiro, Dionísia. "Development of Game-Based M-Learning Apps for Preschoolers." Education Sciences 11, no. 5 (May 12, 2021): 229. http://dx.doi.org/10.3390/educsci11050229.
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Recent studies indicate tablets as the preferred devices of preschool children, due to portability, autonomy of use and variety of apps. There is also extensive evidence of the contributions of digital technologies in different areas of learning at these ages. The Aprender XXI project aimed to develop game-based learning apps, with content recommended in the Curriculum Guidelines for Pre-School Education (CGPE). The project used Design-Based Research (DBR) methodology, which combines scientific research and technological development. It was divided into three phases: preliminary study (literature review, search for existing apps, study of preschool curriculum), development (specifications, scriptwriting, design and programing) and evaluation (tests with users and conclusions). The preliminary study identified the needs to define robust apps. The evaluation with children and educator validated the development and defined improvements in the apps. As a result, we obtained four thematic apps—environment, health, citizenship and professions, composed of a set of games, suitable for autonomous use for children or for educational activities guided by educators in kindergarten. In addition, a website collects children’s play data, which is represented with flowers in a virtual world, to illustrate their participation/collaboration for a better future.
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Anasara, Muhamad Fauzil. "DESIGN OF ANDROID-BASED MUNA LANGUAGE DICTIONARY APPLICATION USING EXTREME PROGRAMMING METHOD." MATICS: Jurnal Ilmu Komputer dan Teknologi Informasi (Journal of Computer Science and Information Technology) 15, no. 1 (August 21, 2023): 51–57. http://dx.doi.org/10.18860/mat.v15i1.23151.
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Muna is one of the languages spoken by the Muna tribe in Southeast Sulawesi, Indonesia, which belongs to the Austronesian language family. Over time, Muna language began to be rarely used. Muna language learning in education also began to be rarely used and there are almost no Muna language lessons anymore, because people prefer to use foreign languages rather than using their own local languages. As a result, many people in the capital of Muna Regency do not understand or know the vocabulary of the Muna language. One way to preserve it is by utilizing existing technology through applications that can help search vocabulary as a substitute for conventional dictionaries that are large in size that can be carried and viewed at any time. Therefore, this research aims to preserve the Muna language through the design of the Muna language dictionary application by applying the Extreme Programming method. Extreme Programming method is a software development approach that emphasizes collaboration, flexibility, and responsiveness to change. The Muna language dictionary application will be designed with various features that make it easier for users to understand and use the Muna regional language. The Muna regional language dictionary application has also been tested using black box testing, where all the features in this application run well and in accordance with what is needed. Index Terms— Muna language, application, dictionary, Extreme programing.
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Weiss, Jasmine. "VTDITC: Hip Hop Studies at Virginia Tech and COVID-19." Undergraduate Journal of Service Learning & Community-Based Research 11 (April 4, 2021): 33–38. http://dx.doi.org/10.56421/ujslcbr.v11i0.333.
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VTDITC: Hip Hop Studies at Virginia Tech has a heavy focus on community-based learning, we make sure to support our communities’ interest in Hip Hop, and facilitate spaces where people can recognize Hip Hop as a scholarly practice. We have a variety of programs we offer including a monthly seminar, weekly studio hours, media literacy workshops, and live DJ mixes. COVID-19 emerged across the United States around March 2020 and directly impacted everyone's life in various ways. VTDITC programing has had to adjust because of our country’s new norms.
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Krohn, Kristina M., Michael A. Sundberg, Nasreen S. Quadri, William M. Stauffer, Adriana Dhawan, Hope Pogemiller, Viviane Tchonang Leuche, et al. "Global Health Education during the COVID-19 Pandemic: Challenges, Adaptations, and Lessons Learned." American Journal of Tropical Medicine and Hygiene 105, no. 6 (December 1, 2021): 1463–67. http://dx.doi.org/10.4269/ajtmh.21-0773.
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ABSTRACT. Global health education programs should strive continually to improve the quality of education, increase access, create communities that foster excellence in global health practices, and ensure sustainability. The COVID-19 pandemic forced the University of Minnesota’s extensive global health education programs, which includes a decade of hybrid online and in-person programing, to move completely online. We share our experience, a working framework for evaluating global health educational programming, and lessons learned. Over the decades we have moved from a predominantly passive, lecture-based, in-person course to a hybrid online (passive) course with an intensive hands-on 2-week requirement. The pandemic forced us to explore new active online learning models. We retained our on-demand, online passive didactics, which used experts’ time efficiently and was widely accessible and well received. In addition, we developed a highly effective synchronous online component that we felt replaced some of the hands-on activities effectively and led us to develop new and innovative “hands-on” experiences. This new, fully online model combining quality asynchronous and synchronous learning provided many unanticipated advantages, such as increasing access while decreasing our carbon footprint dramatically. By sharing our experience, lessons learned, and resources, we hope to inspire other programs likewise to innovate to improve quality, access, community, and sustainability in global health, especially if these innovations can help decrease negative aspects of global health education such as its environmental impact.
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Chang, Ray-I., Jia-Ying Lin, and Yu-Hsin Hung. "Cloud-Based Machine Learning Methods for Parameter Prediction in Textile Manufacturing." Sensors 24, no. 4 (February 18, 2024): 1304. http://dx.doi.org/10.3390/s24041304.
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In traditional textile manufacturing, downstream manufacturers use raw materials, such as Nylon and cotton yarns, to produce textile products. The manufacturing process involves warping, sizing, beaming, weaving, and inspection. Staff members typically use a trial-and-error approach to adjust the appropriate production parameters in the manufacturing process, which can be time consuming and a waste of resources. To enhance the efficiency and effectiveness of textile manufacturing economically, this study proposes a query-based learning method in regression analytics using existing manufacturing data. Query-based learning allows the model training to evolve its decision-making process through dynamic interactions with its solution space. In this study, predefined target parameters of quality factors were first used to validate the training results and create new training patterns. These new patterns were then imported into the solution space of the training model. In predicting product quality, the results show that the proposed query-based regression algorithm has a mean squared error of 0.0153, which is better than those of the original regression-related methods (Avg. mean squared error = 0.020). The trained model was deployed as an application programing interface (API) for cloud-based analytics and an extensive auto-notification service.
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Ekwealor, Oluchukwu, Chidi Betrand, Chiemeka Chukwudum, Charles Uchefuna, and Obinna Agbata. "Development of a Semantic Web-Ontology E-Learning Platform." American Journal of Computer Science and Technology 7, no. 4 (October 31, 2024): 176–82. http://dx.doi.org/10.11648/j.ajcst.20240704.15.
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This paper is focused on developing A Semantic Web-Ontology E-Learning Platform, which is a system that combines semantic web and ontology technology to guarantees a sophisticated learning environment that provides the learners with adaptable and customized learning resources based on learners’ knowledge requirement. With this system, learners can log in from their comfort zone anytime, to receive their online lesson as provided by their tutor. The system has an added advantage of providing a personalized learning to students through creation of intelligent search engine and ontology backbone consisting of learning data and their meta data. The learner, through this search engine, searches the ontology semantically for the learning materials that suits his/her profile. The system also has the capability of filtering the search results by matching them with the profile of a particular learner using inference engine, such that the result best suited for the user’s academic need is presented. This work will not only promote self-directed learning but will also facilitate quick search of learning materials, by narrowing the search based on specified learner’s interest. The methodology adopted for this work is Object-Oriented Analysis and Design Methodology (OOADM) and programing languages used are Php-Mysql and Java Script. The system will be of great benefit to schools, other learning institutions and organization seeking to educate their manpower.
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Lam, Michelle. "Effects of Canada’s Increasing Linguistic and Cultural Diversity on Educational Policy, Programming and Pedagogy." Journal of Contemporary Issues in Education 14, no. 2 (December 10, 2019): 16–32. http://dx.doi.org/10.20355/jcie29370.
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In Canada, 22.9% of people report a “mother tongue” that is not English or French (Government of Canada, 2017) and most of them are newcomers. Within Canadian primary and secondary school, there were 4.75 million students enrolled in the 2015/2016 school year (Statista, 2018), and 2.2 million children under age 15 who were foreign-born or who had at least one foreign-born parent (Government of Canada, 2017). Thirty-seven and a half percent of all Canadian children have an immigrant background (Government of Canada, 2017). These statistics point towards large numbers of students in Canadian schools who have a depth of linguistic resources and repertoire. This diversity has implications on educational policy, programming, and pedagogy. In order to ensure that the education provided to students in Canadian classrooms is relevant, future-focused, and honouring to the depth of linguistic and cultural resources represented within the classroom it is necessary for teachers and policy-makers to have a strong understanding of how English as an additional language (EAL) students learn language and literacy, and how they enrich the learning environment of the classroom as a whole. This article describes the effects of Canada’s increasing diversity on educational policy, programing and pedagogy.
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Felgueiras, Manuel Carlos, Jose Macedo, Andre Fidalgo, C. Petry, and Gustavo Alves. "How to Use Remote Labs for Enhancing E-Learning on PSoCs." International Journal of Online Engineering (iJOE) 12, no. 04 (April 28, 2016): 61. http://dx.doi.org/10.3991/ijoe.v12i04.5232.
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Electronic teaching is a task that intents to also prepare the student to understand and design analog and digital circuits. However the design flow in those two arenas are quite opposite as result of very different development state and also are the design methodologies, being challenging for both teachers and students. In fact, the electronic design in the digital field is centered in the use of components based in two kind of circuits (microprocessor and FPGA) using a relatively high level programing/configuring languages. In an opposite way, the analog design is traditionally founded in the use of elementary components (e.g. resistors and capacitors) associated with macroblocks (e.g. operational amplifiers) in order to built-up the wanted mission circuit. However they have just a few analog programmable components, as the PSoC that is analogically configurable in a similar manner that the one already used in the digital domain. The use of this kind of components, however, is not straightforward being necessary to get some concepts traditionally not taught in the analog electronic classes. The training using PSoC are then indispensable to verify if the programed analog circuit corresponds to the intended one. The current work present an innovative remote lab to support teaching of the PSoC.
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Horstman, Theresa, Gavin Tierney, and Carrie Tzou. "Design principles for creating digital badges to support learning." Information and Learning Sciences 121, no. 11/12 (October 19, 2020): 889–907. http://dx.doi.org/10.1108/ils-02-2020-0042.
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Purpose This paper aims to focus on two areas of digital badge design that impact learner experience: the value and meaning of badges outside of their original context and badge function and platform functionality that impact learner experience. Design/methodology/approach This research uses a design-based research approach. For this paper, components of badge systems were analyzed to identify the characteristics of learning experiences in each program. Findings Findings in this paper are from a National Science Foundation-funded project where digital badge systems were co-designed to connect informal science learning with college credit. The badge design principles presented to address the value of badges and badge function and platform functionality, as well as making program design more systematic and using badge design as a conceptual, organizing design framework for improved educational programs. Research limitations/implications Though this research is limited in the number of programs examined, the findings provide a framework for the language and standards to discuss and implement digitals badges. Practical implications This paper will be of use to programing developers seeking to integrate badges into their educational programs or simply reexamine their educational goals and opportunities for learners. Originality/value This paper challenges the conventional use of badges for simply increasing learner engagement by illustrating that the badge design and development process can improve program design and subsequent learner experience rather than serving purely as a learner motivational tool.
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Carr, William H. "Using the H5P digital platform as an active learning tool to build content-based critical thinking skills in an undergraduate immunology course." Journal of Immunology 206, no. 1_Supplement (May 1, 2021): 54.06. http://dx.doi.org/10.4049/jimmunol.206.supp.54.06.
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Abstract Recent studies have demonstrated that active learning or learning by doing has a more significant positive impact on learning outcomes than reading or watching videos. However the availability of free and open source tools for creating these active learning exercises has been limited by the requirement of computer programing skills. With the development of H5P technology, an open source, on-line tool, faculty and even undergraduate students can create interactive exercises that facilitate the learning process and promote formative learning. H5P is a plugin for existing publishing systems that enables the system to create interactive content, such as multiple-choice quizzes that provide feedback in real-time on quiz responses. Here are provided scaffolded assignments to enable implementation of this approach in an undergraduate immunology course that is taught online asynchronously. This activity was implemented at Medgar Evers College, City University of New York (Brooklyn, NY) in 2020–2021. These assignments enabled students to design interactive formative assessments, i.e., multiple choice questions, using the H5P digital platform (www.h5p.org). Results of undergraduate student surveys on their subjective impressions of using this tool are presented. Specifically, the learning outcome that this activity addressed was to increase understanding of the regulation of V(D)J recombination, which is often a difficult learning concept in undergraduate immunology courses. This is teaching innovation will also be presented as a workshop in the Education Session of Immunology 2021.
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Amin Benbouras, Mohammed, and Alexandru-Ionut Petrisor. "Prediction of Swelling Index Using Advanced Machine Learning Techniques for Cohesive Soils." Applied Sciences 11, no. 2 (January 7, 2021): 536. http://dx.doi.org/10.3390/app11020536.
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Several attempts have been made for estimating the vital swelling index parameter conducted by the expensive and time-consuming Oedometer test. However, they have only focused on the neuron network neglecting other advanced methods that could have increased the predictive capability of models. In order to overcome this limitation, the current study aims to elaborate an alternative model for estimating the swelling index from geotechnical physical parameters. The reliability of the approach is tested through several advanced machine learning methods like Extreme Learning Machine, Deep Neural Network, Support Vector Regression, Random Forest, LASSO regression, Partial Least Square Regression, Ridge Regression, Kernel Ridge, Stepwise Regression, Least Square Regression, and genetic Programing. These methods have been applied for modeling samples consisting of 875 Oedometer tests. Firstly, principal component analysis, Gamma test, and forward selection are utilized to reduce the input variable numbers. Afterward, the advanced techniques have been applied for modeling the proposed optimal inputs, and their accuracy models were evaluated through six statistical indicators and using K-fold cross validation approach. The comparative study shows the efficiency of FS-RF model. This elaborated model provided the most appropriate prediction, closest to the experimental values compared with other models and formulae proposed by the previous studies.
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Amin Benbouras, Mohammed, and Alexandru-Ionut Petrisor. "Prediction of Swelling Index Using Advanced Machine Learning Techniques for Cohesive Soils." Applied Sciences 11, no. 2 (January 7, 2021): 536. http://dx.doi.org/10.3390/app11020536.
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Several attempts have been made for estimating the vital swelling index parameter conducted by the expensive and time-consuming Oedometer test. However, they have only focused on the neuron network neglecting other advanced methods that could have increased the predictive capability of models. In order to overcome this limitation, the current study aims to elaborate an alternative model for estimating the swelling index from geotechnical physical parameters. The reliability of the approach is tested through several advanced machine learning methods like Extreme Learning Machine, Deep Neural Network, Support Vector Regression, Random Forest, LASSO regression, Partial Least Square Regression, Ridge Regression, Kernel Ridge, Stepwise Regression, Least Square Regression, and genetic Programing. These methods have been applied for modeling samples consisting of 875 Oedometer tests. Firstly, principal component analysis, Gamma test, and forward selection are utilized to reduce the input variable numbers. Afterward, the advanced techniques have been applied for modeling the proposed optimal inputs, and their accuracy models were evaluated through six statistical indicators and using K-fold cross validation approach. The comparative study shows the efficiency of FS-RF model. This elaborated model provided the most appropriate prediction, closest to the experimental values compared with other models and formulae proposed by the previous studies.