Relevant bibliographies by topics / Learning cycle models

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Learning cycle models'

Author: Grafiati
Published: 3 June 2025
Last updated: 31 July 2025

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Journal articles on the topic "Learning cycle models"

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Nursal, Yelliza. "Increasing Of Student Learning Activities In Sociological Learning Using Differential Learning Models." LANGGAM: International Journal of Social Science Education, Art and Culture 1, no. 04 (2023): 38–48. http://dx.doi.org/10.24036/langgam.v1i04.30.

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The problem of low student activity in participating Sociology learning process. The types of activities experienced are: Students pay attention to the teacher when explaining lessons; Willing the students to ask and answer the questions; Students' interest in doing assignments; Courage of students in group presentations; As well as student activities in collaboration. The purpose of this study is to increase the sociology learning activities of class XII IPS 1 student of SMAN 1 Ranah Pesisir using the Differentiated Learning Model for the 2022/2023 school year. This type of research is Classr
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Maslianti and Ulil Azmi. "IMPROVING STUDENT LEARNING OUTCOMES MATHEMATICS THROUGH LEARNING MODELS PROBLEM BASED LEARNING." Journal of Social Science 1, no. 4 (2024): 48–56. https://doi.org/10.61796/ijss.v1i4.30.

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Objective: This study aims to examine the effectiveness of the Problem-Based Learning (PBL) model in improving mathematics learning outcomes for third-grade students at SD Negeri 03 Benua Kayong by fostering critical thinking, active engagement, and problem-solving skills. Method: A qualitative descriptive approach was employed, utilizing direct observation techniques and observation sheets as instruments for data collection. The research was conducted in two cycles, with each cycle involving the implementation of PBL in thematic mathematics lessons. Results: The findings demonstrated a substa
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Nurhamidah, Ririn. "USE OF PROBLEM BASED LEARNING MODELS TO IMPROVE STUDENT LEARNING OUTCOMES AT SD NEGERI 1 BUMIRATU." Journal of Learning on History and Social Sciences 1, no. 6 (2024): 69–77. https://doi.org/10.61796/ejlhss.v1i6.664.

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This research activity is based on low mathematics learning outcomes. There were only 8 students who completed the KKM score, namely 65 out of 20 students. The aim of this research is to see the increase in students' grades at SD Negeri 1 Bumiratu. The type of research used is Classroom Action Research, in this research there are 2 cycles, each cycle has four stages, namely planning, action, observation and reflection. The model applied to improve student learning outcomes in this research is the Problem Based Learning model. The Problem Based Learning model is a learning model that encourages
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Efendi, Roy, Eri Sarimanah, Figiati Indra Dewi, and Syarifuddin. "Improving Exposition Writing Skills through Online-Based Cycle Learning Models." International Journal of Psychosocial Rehabilitation 24, no. 03 (2020): 2071–76. http://dx.doi.org/10.37200/ijpr/v24i3/pr200953.

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Shahab, Anisa Dwi Inayati. "Application of Problem Based Learning Models to Improve Magnetic Materials Learning Results." Social, Humanities, and Educational Studies (SHEs): Conference Series 3, no. 3 (2020): 892. http://dx.doi.org/10.20961/shes.v3i3.46084.

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<p><em>The purpose of this study was to improve the learning outcomes of Magnetics subject in elementary schools in grade VI by applying the Problem Based Learning (PBL) learning model. The research conducted was a Classroom Action Research (PTK) in three cycles, with each cycle consisting of 1 meeting. The stages of each cycle are planning, implementing, observing and reflecting. Each meeting is held an evaluation to determine the progress of learning outcomes. In cycle 1, students who completed after the evaluation were 51.61%. In cycle 2, students who completed after evaluation
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Rohayati, Rohayati. "Improving Thematic Learning Outcomes Using Problem Based Learning Models in Class III SD." Social, Humanities, and Educational Studies (SHEs): Conference Series 3, no. 4 (2021): 222. http://dx.doi.org/10.20961/shes.v3i4.53330.

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<p><em>This study aims to improve thematic learning outcomes by using the Problem Based Learning (PBL) model in class III SD Negeri Ketangan 02. In this study applying the type of classroom action research (CAR) using qualitative and quantitative approaches. The research subjects were third grade students of SD Negeri Ketangan 02 semester 2 for the 2019/2020 academic year with a total of 16 students. This research was conducted in two cycles. The results of the first cycle research on RPP an average of 81,48% (B), increased in the second cycle to 92.59% (SB), the implementation of
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Khasanah, Uswa. "Increasing Indonesian Language Learning Results Models of Cooperative Learning Talking Stick Type." Social, Humanities, and Educational Studies (SHEs): Conference Series 3, no. 3 (2020): 1118. http://dx.doi.org/10.20961/shes.v3i3.46171.

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<p><em>The purpose of this study was to improve the learning outcomes of students in the Indonesian language muple in grade II elementary schools with a cooperative talking stick learning model. The research carried out was to use two cycles of Classroom Action Research (CAR), with each cycle consisting of one meeting. The stages of each cycle are planning, implementing, observing and reflecting. Each meeting was conducted a knowledge test using formative tests and summative tests to determine the development of students. In the first cycle, the students who completed after carryin
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Rumyani, Ari. "Improved Learning Outcomes of Natural Science Lessons Through Google Meet Assisted Project Based Learning (PjBL) Learning Models." Social, Humanities, and Educational Studies (SHEs): Conference Series 3, no. 3 (2020): 1189. http://dx.doi.org/10.20961/shes.v3i3.46331.

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<em>The purpose of this research was to improve student learning outcomes in science grade V elementary schools with a Google meet assisted Project Based Learning (PjBL) learning model. The research conducted was a Classroom Action Research (PTK) with three cycles, with each cycle consisting of two meetings. The stages of each cycle are planning, implementing, observing and reflecting. Each meeting is carried out a pre test and post test to determine the progress of students. In the first cycle the students who completed after carrying out the post test were 74%. In the second cycle stud
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Rusdi, Muhammad. "IMPROVING LEARNING OUTCOMES THROUGH TEAM ASSISTED INDIVIDUALIZATION (TAI) COOPERATIVE LEARNING MODELS." Teaching English as a Foreign Language Overseas Journal 10, no. 3 (2022): 291–305. http://dx.doi.org/10.47178/teflo.v10i3.2377.

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The use of the Team Assisted Individualization (TAI) cooperative learning model can improve learning outcomes in students at SMA Muhammadiyah 5 Makassar. Classroom action research consisting of two cycles, where each cycle consists of two meetings, with activity stages including planning, implementing, observing, and reflecting. The subjects of this study were all fourth grade students at SMA Muhammadiyah 5 Makassar, Makassar, a total of 41 students consisting of 21 male students and 20 female students. The increase in learning outcomes through the Team Assisted Individualization (TAI) type co
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Rahmawati, Naning, Ziadoon Otaiwi, Warud Nakkhasen, and Nhãn Phan Thãnh. "Increasing Mathematics Learning Activities Through Numbered Heads Together (NHT) Cooperative Learning Models In Students." Interval: Indonesian Journal of Mathematical Education 1, no. 1 (2023): 1–7. http://dx.doi.org/10.37251/ijome.v1i1.608.

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The purpose of this study is to see an increase in mathematics learning activity through the cooperative learning model of the numbered heads together type in class VIID students of SMP Negeri 14 Surakarta. This study uses a type of classroom action research. The subjects in this study were teachers and students of class VIID at SMP Negeri 14 Surakarta. This study consisted of 3 cycles, namely cycle 1, cycle II, and cycle III. Sources of data in this study were obtained from observation sheets of students' learning activities in cycle I, cycle II, and cycle III, observation sheets of the learn
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Dissertations / Theses on the topic "Learning cycle models"

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Welby-Solomon, Vanessa. "The continuous learning cycle. Investigating possibilities for experiential learning." Thesis, University of the Western Cape, 2015. http://hdl.handle.net/11394/5357.

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Magister Educationis (Adult Learning and Global Change) - MEd(AL)<br>Scholars focusing on experiential learning argue that experience should be considered as critical for adult learning. This research paper frames experiential learning within a Constructivist framework. This paper focuses on an investigation into the ways that facilitators use the Continuous Learning Cycle, a model for learning based on Kolb's Learning Cycle, to facilitate learning through experience during the triad skills observation role-play in a workshop, which is part of an induction programme, for a retail bank. Indicat
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Bougaa, Mohammed. "Une approche basée sur les processus et dirigée par les compétences pour l'éducation en ingenierie des systèmes." Thesis, Université Paris-Saclay (ComUE), 2017. http://www.theses.fr/2017SACLC050/document.

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Au cours de cette thèse, nous avons examinée les pratiques actuelles en matière d'éducation en IS. Nous avons proposé une approche centrée sur l'utilisation des processus normalisés en IS, tout en faisant en sorte que le scénario d'apprentissage soit très adaptable et qu'il puisse être piloté par les compétences d'IS acquises ou à acquérir. Ensuite, une plateforme Web a été développée pour soutenir cette nouvelle approche d'apprentissage. En utilisant cette approche, les étudiants ne seront pas seulement en mesure de bien concevoir le système demandé de manière distante et collaborative, mais
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Takahara, Yoshie. "A management approach to successful international partnerships of universities : a phase- and principle-based management model and its implications for Japanese higher education." Thesis, University of Bath, 2018. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.761039.

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Universities, facing both pressures and opportunities created by globalisation, are currently seeking a way to reinforce their capabilities by enhancing their academic strength through internationalisation. In such a setting, the development of international partnerships has been increasingly recognised as a central strategy for the success of internationalisation. Understanding the increasing importance of international partnerships for universities, this study will attempt to understand what could make a successful partnership and identify which management approach is most likely to realise
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Akar, Elvan. "Effectiveness Of 5e Learning Cycle Model On Students&#039." Master's thesis, METU, 2005. http://etd.lib.metu.edu.tr/upload/12605747/index.pdf.

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The main purpose of this study was to compare the effectiveness of instruction based on 5E learning cycle model over traditionally designed chemistry instruction on tenth grade students&rsquo<br>understanding of acid-base concepts. Fifty- six tenth grade students from two classes of a chemistry course taught by the same teacher in Atat&uuml<br>rk Anatolian High School 2003-2004 spring semester were enrolled in the study. The classes were randomly assigned as control and experimental groups. Students in the control group were instructed by traditionally designed chemistry instruction whereas
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Aydemir, Nurdane. "Effectiveness Of 5e Learning Cycle Model On High School Students." Phd thesis, METU, 2012. http://etd.lib.metu.edu.tr/upload/12614340/index.pdf.

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The purpose of this study was to investigate the effect of instruction based on 5E learning cycle model (LCI) compared to Traditional Instruction (TI) and gender on 11th grade students&rsquo<br>understanding of solubility equilibrium concept, students&rsquo<br>perceived motivation, use of learning strategies, and attitudes towards chemistry. There were 53 students in the experimental group instructed by the LCI and 56 students in the control group instructed by the TI. Solution Concept Test and Science Process Skills Test were administered to students in both groups as a pre-test. Attitude Sca
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Kubin, Ingrid, and Thomas Zörner. "Human Capital in a Credit Cycle Model." WU Vienna University of Economics and Business, 2017. http://epub.wu.ac.at/5681/1/wp251.pdf.

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We augment a model of endogenous credit cycles by Matsuyama et al.(2016) with human capital to study the impact of human capital on the stability of central economic aggregates. Thus we offer a linkage between human capital formation and credit market instability on a macrolevel combined with an analysis of functional income distribution. Human capital is modelled as pure external effect of production following a learning-by-producing approach. Agents have access to two different investment projects, which differ substantially in their next generations spillover effects. Some generate pecuniar
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Bektas, Oktay. "The Effect Of 5e Learning Cycle Model On Tenth Grade Students." Phd thesis, METU, 2011. http://etd.lib.metu.edu.tr/upload/12613340/index.pdf.

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The purpose of this study is to probe whether there is a significant effect of 5E learning cycle model as compared to traditional instruction and gender on tenth grade students&rsquo<br>understanding in the particulate nature of matter concepts and their epistemological beliefs and to investigate whether there is an impact of 5E learning cycle model and traditional instruction in promoting the understanding of the nature of science. Pilot study was performed for the instruments in the between April and June 2009. Treatment was conducted between October and December 2009. Participants were 113
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Cetin, Dindar Ayla. "The Effect Of 5e Learning Cycle Model On Eleventh Grade Students." Phd thesis, METU, 2012. http://etd.lib.metu.edu.tr/upload/12614290/index.pdf.

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The purpose of this study was to investigate the effect of 5E learning cycle model compared to traditional teacher-centered instruction on eleventh grade students&rsquo<br>conceptual understanding of acids and bases concepts and student motivation to learn chemistry. The measuring tools were Three-tier Acids-Bases Test (TABT) and Chemistry Motivation Questionnaire (CMQ). There were two groups, which were the experimental and traditional group, consisting of 78 students. Before the implementation, the tools were administered as pre-tests to both groups and the semi-structured pre-interviews wer
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Akar, Elvan Supervisor :. Demircioğlu Hüsniye. "Effectiveness of 5E learning cycle model on students' understanding of acid-base concepts." Ankara : METU, 2005. http://etd.lib.metu.edu.tr/upload/12605747/index.pdf.

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Thesis (M.S.) -- Middle East Technical University, 2005.<br>Keywords: 5E learning cycle, traditionally designed chemistry instruction, acid-base, attitude towards chemistry as a school subject, science process skill.
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Mecit, Ozlem. "The Effect Of 7e Learning Cycle Model On The Improvement Of Fifth Grade Students." Phd thesis, METU, 2006. http://etd.lib.metu.edu.tr/upload/12607661/index.pdf.

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The main purpose of the present study was to investigate the effect of 7E learning cycle model as an inquiry-based learning on the improvement of 5th grade students&rsquo<br>critical thinking skills. This study was conducted during 2005-2006 spring semester in a private primary school in Sakarya. A total of 46 fifth grade students from two different classes of the same science teacher was involved in the study. Two classes were randomly assigned as experimental group and control group. While students in the control group were instructed with traditional method, inquiry-based learning was carri
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Books on the topic "Learning cycle models"

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Li, Kathy Yinuo. Learning predictive models from menstrual cycle data. [publisher not identified], 2022.

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Bouakez, Hafedh. Learning-by-doing or habit formation? Bank of Canada, 2005.

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Bouakez, Hafedh. Learning-by-doing or habit formation? Bank of Canada, 2005.

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W, Evans George. Convergence of recursive learning mechanisms to steady states and cycles in stochastic nonlinear models. LSE Financial Markets Group, 1990.

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W, Cooper Russell. Learning by doing and aggregate fluctuations. National Bureau of Economic Research, 1999.

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Rennie, Kriston R. The Destruction and Recovery of Monte Cassino, 529-1964. Amsterdam University Press, 2021. http://dx.doi.org/10.5117/9789463729130.

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Between the sixth and twentieth centuries, the Benedictine Abbey of Monte Cassino (est. 529) experienced a cycle of atrocities which forever transformed its identity. This book examines how such a tumultuous history has been constructed, remembered, and represented from the Middle Ages to the present day. It uses this singular and pivotal case to analyse the historical process of remembering and its impact on modern representations of the past. Exactly how Monte Cassino is remembered is distinctive and diagnostic. The abbey is recognizable today as a beacon of western civilization, culture, an
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Machine Learning Engineering with Python: Manage the Life Cycle of Machine Learning Models Using MLOps with Practical Examples. Packt Publishing, Limited, 2023.

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Machine Learning Engineering with Python: Manage the Production Life Cycle of Machine Learning Models Using MLOps with Practical Examples. Packt Publishing, Limited, 2021.

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Machine Learning Engineering with Python: Manage the Production Life Cycle of Machine Learning Models Using MLOps with Practical Examples. de Gruyter GmbH, Walter, 2021.

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Building Machine Learning Pipelines: Automating Model Life Cycles with TensorFlow. O'Reilly Media, Incorporated, 2020.

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Book chapters on the topic "Learning cycle models"

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Daou, H., W. Raphael, and F. Geara. "Evaluation of factors affecting long-term creep of concrete using machine learning regression models." In Bridge Safety, Maintenance, Management, Life-Cycle, Resilience and Sustainability. CRC Press, 2022. http://dx.doi.org/10.1201/9781003322641-144.

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Foltyn, Andreas, and Maximilian P. Oppelt. "Comprehensible AI for Multimodal State Detection." In Unlocking Artificial Intelligence. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-64832-8_11.

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AbstractAffective computing enables computers to recognize and respond to human emotions and cognitive states using multimodal state recognition. This chapter explores cognitive load estimation through a machine learning life cycle, addressing data collection and preparation, modeling, and deployment challenges. Experiments demonstrate effective unimodal and fusion models for predicting cognitive load. Applications in gaming, healthcare, and driver monitoring have been discussed, providing valuable insights for researchers in this field
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Dimara, Asimina, Stelios Krinidis, Dimosthenis Ioannidis, and Dimitrios Tzovaras. "Building Performance Simulation." In Disrupting Buildings. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-32309-6_4.

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AbstractSimulation is a proven technique that uses computational, mathematical, and machine learning models to represent the physical characteristics, expected or actual operation, and control strategies of a building and its energy systems. Simulations can be used in a number of tasks along the deep renovation life cycle, including: (a) integrating simulations with other knowledge-based systems to support decision-making, (b) using simulations to evaluate and compare design scenarios, (c) integrating simulations with real-time monitoring and diagnostic systems for building energy management a
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Tan, Chuheng, and Ximing Zhong. "A Rapid Wind Velocity Prediction Method in Built Environment Based on CycleGAN Model." In Computational Design and Robotic Fabrication. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-8637-6_22.

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AbstractAlthough the wind microclimate and wind environment play important roles in urban prediction, the time-consuming and complicated setup and process of wind simulation are widely regarded as challenges. There are several methods to use deep learning (DL) models for wind speed prediction by labeling pairs of wind simulation dataset samples. However, many wind simulation experiments are needed to obtain paired datasets, which is still time-consuming and cumbersome. Compared with previous studies, we propose a method to train a DL model without labelling paired data, which is based on Cycle
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Winn, John Michael, Christopher M. Bishop, Thomas Diethe, John Guiver, and Yordan Zaykov. "Interlude: the machine learning life cycle." In Model-Based Machine Learning. Chapman and Hall/CRC, 2023. http://dx.doi.org/10.1201/9780429192685-4.

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Doukari, Omar, Mohamad Kassem, and David Greenwood. "Building Information Modelling." In Disrupting Buildings. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-32309-6_3.

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AbstractFrom its origins as a computer-aided three-dimensional modelling tool, Building Information Modelling (BIM) has evolved to incorporate time scheduling, cost management, and ultimately an information management framework that has the potential to enhance decision-making throughout the whole life-cycle of built assets. This chapter summarises state-of-the-art BIM and its benefits. It then considers the particular characteristics of deep renovation projects, the challenges confronting their delivery, and the potential for using BIM to meet the challenges. This includes the application of
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Pacifico, Maria Giovanna, Maria Rita Pinto, and Antonio Novellino. "Digital—Twin for an Innovative Waterfront Management Strategy. Pilot Project DSH2030." In The Urban Book Series. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-29515-7_20.

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AbstractIn the era of smart cities, the digital twin of a settlement system allows not only the real-time control of the quality levers offers by the subsystems, but also the prediction of the future performance over the life cycle. This is feasible through the implementation of predictive models and the simulation of the impact that the design solutions can generate. The Digital and Sustainable Harbour 2030 (DSH2030) project, funded under the Liguria region’s POR FESR, sees the cooperation of the Innovation, Development, and Sustainability structure of the Porto Antico of Genoa, with ETT S.p.
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Sun, Guangzhen. "No Limit Cycle: Chen’s Learning Competition Model Revisited." In Complexity and Self-Organization in Social and Economic Systems. Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/978-3-642-48406-3_9.

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Behery, Mohamed, Philipp Brauner, Hans Aoyang Zhou, et al. "Actionable Artificial Intelligence for the Future of Production." In Internet of Production. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-030-98062-7_4-1.

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AbstractThe Internet of Production (IoP) promises to be the answer to major challenges facing the Industrial Internet of Things (IIoT) and Industry 4.0. The lack of inter-company communication channels and standards, the need for heightened safety in Human Robot Collaboration (HRC) scenarios, and the opacity of data-driven decision support systems are only a few of the challenges we tackle in this chapter. We outline the communication and data exchange within the World Wide Lab (WWL) and autonomous agents that query the WWL which is built on the Digital Shadows (DS). We categorize our approach
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Behery, Mohamed, Philipp Brauner, Hans Aoyang Zhou, et al. "Actionable Artificial Intelligence for the Future of Production." In Internet of Production. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-030-98062-7_4-2.

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AbstractThe Internet of Production (IoP) promises to be the answer to major challenges facing the Industrial Internet of Things (IIoT) and Industry 4.0. The lack of inter-company communication channels and standards, the need for heightened safety in Human Robot Collaboration (HRC) scenarios, and the opacity of data-driven decision support systems are only a few of the challenges we tackle in this chapter. We outline the communication and data exchange within the World Wide Lab (WWL) and autonomous agents that query the WWL which is built on the Digital Shadows (DS). We categorize our approach
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Conference papers on the topic "Learning cycle models"

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Patel, Ishan, and Gheorghe Bota. "Mechanistic Model as a Bias to Machine Learning Algorithm for Confident Prediction of Corrosion." In CONFERENCE 2023. AMPP, 2023. https://doi.org/10.5006/c2023-19108.

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Abstract Bayesian network is employed to estimate a risk-based life cycle cost of corrosion for assets. It has been highly recognized that inclusion of mechanistic models to a Bayesian network can increase the confidence in estimation of corrosion rates. However, coefficients of mechanistic models are often unknown, especially when complex rate processes are involved, which discourages the usage of the model. A methodology is proposed here, to introduce a mechanistic model as a bias to a regressive machine learning (ML) algorithm. No attempts have been made to obtain phenomenological coefficie
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Stefanakis, A. S., D. Kolokotsa, E. Kapartzianis, J. Bonis, and J. K. Kaldellis. "Novel PSE applications and knowledge transfer in joint industry - university energy-related postgraduate education." In The 35th European Symposium on Computer Aided Process Engineering. PSE Press, 2025. https://doi.org/10.69997/sct.164061.

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The field of Process Systems Engineering (PSE) is undergoing a renaissance through the integration of artificial intelligence (AI) and machine learning (ML). This transformation is driven by the vast availability of industrial data and advanced computing power, enabling the practical application of sophisticated ML models. These models enhance PSE capabilities in design, control, optimization, and safety. The progress of ML and ever-present data collection address previously intractable problems, particularly in system integration and life-cycle modeling. ML-powered predictive algorithms are a
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Zhang, Yifei, Jiajin Zhang, and Kaijun Guan. "Multi-test knowledge tracing prediction model based on learning cycle." In 2024 Sixth International Conference on Next Generation Data-driven Networks (NGDN). IEEE, 2024. http://dx.doi.org/10.1109/ngdn61651.2024.10744055.

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Sarfraz, Muhammad, Tao Xu, Lingxu Guo, and Tianhao Wang. "Battery Cycle Life Prediction by Harnessing Stacking Ensemble Learning Model." In 2024 IEEE Power & Energy Society General Meeting (PESGM). IEEE, 2024. http://dx.doi.org/10.1109/pesgm51994.2024.10760277.

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Erdagi, Ismet Goksad, Nemanja Dobrota, Slavica Gavric, and Aleksandar Stevanovic. "Cycle-by-cycle Delay Estimation at Signalized Intersections by using Machine Learning and Simulated Video Detection Data." In 2023 8th International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS). IEEE, 2023. http://dx.doi.org/10.1109/mt-its56129.2023.10241732.

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Williams, Zachary L., Prathik Meruva, and Daniel Christopher Bitsis. "Machine Learning and Genetic Algorithm Method for Powertrain Development: Rapid Generation of Engine Calibration Maps." In ASME 2022 ICE Forward Conference. American Society of Mechanical Engineers, 2022. http://dx.doi.org/10.1115/icef2022-91169.

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Abstract Meeting regulatory and customer demands requires detailed powertrain calibration which can be expensive and time-consuming. There is often a reliance on mathematical optimization tools to convert experimental learnings into a final calibration. This work focuses on developing multiple neural network machine learning (ML) models which were trained on different test-train data splits of test-cell recorded steady-state medium-duty (MD) diesel engine data. The output data was used to develop engine actuator maps by utilizing a genetic algorithm (GA). The genetic algorithm contains a fitne
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Atadeger, Aykut, Mustafa Onur, Soham Sheth, and Raj Banerjee. "Deep Learning-Based and Kernel-Based Proxy Models for Nonlinearly Constrained Life-Cycle Production Optimization." In SPE Reservoir Characterisation and Simulation Conference and Exhibition. SPE, 2023. http://dx.doi.org/10.2118/212690-ms.

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Abstract In this study, we investigate the use of deep learning-based and kernel-based proxy models in nonlinearly constrained production optimization and compare their performances with directly using the high-fidelity simulators (HFS) for such optimization in terms of computational cost and optimal results obtained. One of the proxy models is embed to control and observe (E2CO), a deep learning-based model, and the other model is a kernel-based proxy, least-squares support-vector regression (LS-SVR). Both proxies have the capability of predicting well outputs. The sequential quadratic progra
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Kodavasal, Janardhan, Ahmed Abdul Moiz, Muhsin Ameen, and Sibendu Som. "Machine Learning Analysis of Factors Impacting Cycle-to-Cycle Variation in a Gasoline Spark-Ignited Engine." In ASME 2017 Internal Combustion Engine Division Fall Technical Conference. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/icef2017-3604.

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In this work, we have applied a machine learning (ML) technique to provide insights into the underlying causes of cycle-to-cycle variation (CCV) in a gasoline spark-ignited (SI) engine. The analysis was performed on a set of large eddy simulation (LES) calculations of a single cylinder of a four-cylinder port-fueled SI engine. The operating condition studied was stoichiometric, without significant knock, and represents a load of 16 bar brake mean effective pressure (BMEP), at an engine speed of 2500 revolutions per minute. A total of 123 cycles was simulated. Of these, 49 were run in sequence,
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Brown, Ashland O. "Undergraduate Finite Element Instruction Using Commercial Finite Element Software Tutorials and the Kolb Learning Cycle." In ASME 2004 International Mechanical Engineering Congress and Exposition. ASMEDC, 2004. http://dx.doi.org/10.1115/imece2004-60756.

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As background, the Kolb learning cycle describes an entire cycle around which a learning experience progresses [1]. The goal, therefore, is to structure learning activities that will proceed completely around this cycle, providing the maximum opportunity for full student comprehension of the course material. This model has been used previously to evaluate and enhance teaching in engineering [2, 3, and 4]. Most college education is geared toward abstract conceptualiztion, but complete learning is enhanced by the use of all four learning stages Abstract Hypothesis and Conceptualization, Active E
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Dwi Suyanti, Retno, Mariaty P.Simanjutak, and Gulmah Sugiyarti. "The Effects of Collaborative Learning Oriented Project Based Learning (PjBL) and Learning Cycle Models using Animation Video on Students Problem Solving." In Proceedings of the 4th International Conference on Innovation in Education, Science and Culture, ICIESC 2022, 11 October 2022, Medan, Indonesia. EAI, 2022. http://dx.doi.org/10.4108/eai.11-10-2022.2325380.

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Reports on the topic "Learning cycle models"

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Hauzenberger, Niko, Florian Huber, Gary Koop, and James Mitchell. Bayesian modeling of time-varying parameters using regression trees. Federal Reserve Bank of Cleveland, 2023. http://dx.doi.org/10.26509/frbc-wp-202305.

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In light of widespread evidence of parameter instability in macroeconomic models, many time-varying parameter (TVP) models have been proposed. This paper proposes a nonparametric TVP-VAR model using Bayesian additive regression trees (BART). The novelty of this model stems from the fact that the law of motion driving the parameters is treated nonparametrically. This leads to great flexibility in the nature and extent of parameter change, both in the conditional mean and in the conditional variance. In contrast to other nonparametric and machine learning methods that are black box, inference us
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Acosta López, Juan Carlos. Unveiling hidden opportunities: a case study on the perception of affordances in informal english learning activities mediated by technology in a fl teacher-training program. Sello Editorial UNAD, 2023. http://dx.doi.org/10.22490/ecedu.8389.

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This qualitative single-case study explored the perceived affordances of informal activity systems mediated by online technologies for promoting English language learning among 115 FL teachers-in-training at UNAD. The study employed a word-based questionnaire administered to the entire sample, followed by small focus group interviews with 20 purposively selected participants, (Morgan &amp; Hoffman, 2018). The resulting data were analyzed using a dynamic and fluid 2-cycle coding procedure. The findings show that learners’ ability to per-ceive and engage with technological, social, metacognitive
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Oliveira, Lucas Gabriel Martins de. Which One Predicts Better?: Comparing Different GDP Nowcasting Methods Using Brazilian Data. Inter-American Development Bank, 2023. http://dx.doi.org/10.18235/0005004.

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The objective of this paper is to develop a basic framework for the implementation of a GDP nowcasting strategy using Brazilian data. Our goal is to identify a scalable strategy that allows us to project the Brazilian GDP in real time at any point during the current quarter. In the paper we detail the survey of classical techniques and also of techniques usually known by market practitioners as "machine learning methods". We survey the literature since the first work on estimating business cycles and document the evolution of this literature until the insertion of machine learning methods. Add
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Chachage, Kristeen, Saalim Koomar, Calvin Swai, et al. TCPD: Design-Based Implementation Research Cycle 2 Recommendations. EdTech Hub, 2024. http://dx.doi.org/10.53832/edtechhub.1013.

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MEWAKA (Mafunzo Endelevu kwa Walimu Kazini, or teacher continuous professional development [TCPD]) is a landmark teacher professional development programme being implemented by the Government of Tanzania. The research project, 'The Impact of a Tech-Supported, School-Based TPD Model on Learning Outcomes in Tanzania, using Design-Based Implementation Research (DBIR)', closely aligns with the Tanzania National TCPD implementation plan, to evaluate the implementation of MEWAKA at school level. This policy brief presents a summary of the key findings and recommendations from the second cycle of the
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Tang, Jinyun, William Riley, Qing Zhu, and Trevor Keenan. Using machine learning and artificial intelligence to improve model-data integrated earth system model predictions of water and carbon cycle extremes. Office of Scientific and Technical Information (OSTI), 2021. http://dx.doi.org/10.2172/1769794.

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Zhang, Caiyun, David Brodylo, Mizanur Rahman, Md Atiqur Rahman, Thomas Douglas, and Xavier Comas. Using an object-based machine learning ensemble approach to upscale evapotranspiration measured from eddy covariance towers in a subtropical wetland. Engineer Research and Development Center (U.S.), 2024. http://dx.doi.org/10.21079/11681/48056.

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Accurate prediction of evapotranspiration (ET) in wetlands is critical for understanding the coupling effects of water, carbon, and energy cycles in terrestrial ecosystems. Multiple years of eddy covariance (EC) tower ET measurements at five representative wetland ecosystems in the subtropical Big Cypress National Preserve (BCNP), Florida (USA) provide a unique opportunity to assess the performance of the Moderate Resolution Imaging Spectroradiometer (MODIS) ET operational product MOD16A2 and upscale tower measured ET to generate local/regional wetland ET maps. We developed an object-based mac
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Renchon, Alexandre, Roser Matamala, Miquel Gonzalez-Meler, et al. Predictabilityand feedbacks of the ocean-soil-plant-atmosphere water cycle: deep learning water conductance in Earth System Model. Office of Scientific and Technical Information (OSTI), 2021. http://dx.doi.org/10.2172/1769763.

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Markova, Oksana M., Serhiy O. Semerikov, Andrii M. Striuk, Hanna M. Shalatska, Pavlo P. Nechypurenko, and Vitaliy V. Tron. Implementation of cloud service models in training of future information technology specialists. [б. в.], 2019. http://dx.doi.org/10.31812/123456789/3270.

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Leading research directions are defined on the basis of self-analysis of the study results on the use of cloud technologies in training by employees of joint research laboratory “Сloud technologies in education” of Kryvyi Rih National University and Institute of Information Technology and Learning Aids of the NAES of Ukraine in 2009-2018: cloud learning technologies, cloud technologies of blended learning, cloud-oriented learning environments, cloud-oriented methodological systems of training, the provision of cloud-based educational services. The ways of implementation SaaS, PaaS, IaaS cloud
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Gutiérrez-Daza, Ángelo. Business Cycles when Consumers Learn by Shopping. Banco de México, 2024. http://dx.doi.org/10.36095/banxico/di.2024.12.

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Empirical evidence suggests consumers rely on their shopping experiences to form beliefs about inflation. In other words, they "learn by shopping". I introduce this empirical observation as an informational friction in the New Keynesian model and use it to study its consequences for the transmission of aggregate shocks and the design of monetary policy. Learning by shopping anchors households' beliefs about inflation to its past, causing disagreement with firms over the value of the real wage. The discrepancy allows nominal shocks to have real effects and makes the slope of the Phillips curve
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Prieto Martín, Pedro, Marina Apgar, Jiniya Afroze, et al. Bridging Learning and Action: How Did CLARISSA’s Participatory Adaptive Management Approach Foster Innovation, Effectiveness, and Stakeholder Empowerment? Institute of Development Studies, 2024. http://dx.doi.org/10.19088/clarissa.2024.007.

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Child Labour: Action-Research-Innovation in South and South-Eastern Asia (CLARISSA) is an evidence and innovation-generation programme funded by the United Kingdom’s Foreign, Commonwealth &amp; Development Office (FCDO), responding to the challenge of the worst forms of child labour (WFCL) in Bangladesh and Nepal. It is a challenge characterised by a poor understanding of its drivers and a lack of evidence on what works to combat it. To handle such fundamental uncertainty, the programme adopts a child-centric and participatory action research approach, which is supported by an adaptive managem
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