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Integrating AI-based adaptive learning into the flipped classroom model to enhance engagement and learning outcomes

computers and Education: Artificial Intelligence 2025年 8卷

作者： Katona, Jozsef Gyonyoru, Klara Ida Katonane Department of Software Development and Application Institute of Computer Engineering University of Dunaujvaros Dunaujvaros Hungary Institute of Electronics and Communication Systems Kandó Kálmán Faculty of Electrical Engineering Obuda University Budapest Hungary GAMF Faculty of Engineering and Computer Science John Von Neumann University Kecskemet Hungary Department of Applied Quantitative Methods Faculty of Finance and Accountancy Budapest University of Economics and Business Budapest Hungary Department of Organizational Development and Communication Science Institute of Social Sciences University of Dunaujvaros Dunaujvaros Hungary

This study explores the integration of the AI-powered adaptive learning system within the flipped classroom model and discusses programming education. The increasing demand for the acquisition of programming skills in the digital era generates the development of innovative pedagogical approaches to help students overcome the difficulties in mastering programming concepts. The study investigates how AI-based adaptive feedback influences student engagement, motivation, and learning outcomes. This study was conducted for 13 weeks, with two groups of undergraduate students. In one of the groups, tshe traditional flipped classroom model was applied, while in the other group, AI-driven adaptive learning tools were introduced. In this research methodology, a mixed-methods approach was adopted, integrating quantitative analyses with qualitative data. These showed that the experimental group demonstrated significant improvements in learning results and motivation, thereby realiszing the value of real-time, personalized feedback provided through the AI system. The qualitative findings revealed that with the AI system, there was an increase in student autonomy;thus, there is increased responsibility among students to collaborate in in-class participation, which helps enhance a more dynamic and cooperative learning environment. On the whole, these findings reveal important implications of the integration of AI into flipped classrooms, while at the same time, they reveal how to make the modernization of programming education achieve a better overall experience in student learning. © 2025 The Authors

关键词： Contrastive Learning

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AI and IoT-based Electric Vehicle Monitoring System 6

AI and IoT-based Electric Vehicle Monitoring System

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6th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2022

作者： Bharathi, M. Geetha, K. Mani, P.K. Nixon Samuel Vijayakumar, G. Srinivasan, K. Kumar, Kallakunta Ravi Sree Vidyanikethan Engineering College Department of Electronics and Communication Engineering Andhra Pradesh Tirupati517102 India Karpagam Academy of Higher Education Department of Computer Applications Tamil Nadu Coimbatore641021 India Vel Tech Multitech Dr. Rangarajan Dr. Sakunthala Engineering College Department of Electrical and Electronics Engineering Tamil Nadu Chennai600062 India R.M.K. Engineering College Department of Physics Tamil Nadu Kavaraipettai601206 India Tagore Engineering College Department of Electrical and Electronics Engineering Tamil Nadu Chennai600127 India Koneru Lakshmaiah Education Foundation Department of Electronics and Communication Engineering Andhra Pradesh Vaddeswaram522302 India

ISBN: (数字)9781665469418

ISBN: (纸本)9781665469418

In this technology world, technology is increasing by giving solutions to many problems. By using this technology, a solution for decreasing air pollution is implemented. The main cause of increasing air pollution is using various kinds of vehicles that run on combustion engines for transportation utilities. The implementation of Electric Vehicle (EVs) can resolve this air pollution problem and keeps the environment as pollution-free air and the world can survive in pure air. EVs are like machines that run on a charging battery. An EV's condition is depending on the battery's performance. The parameters for the battery's condition the voltage, current, and temperature. By using these parameters State of Charge (SOC) is determined. These performances are monitored as Battery Management System (BMS). In this paper, the EV monitoring system is implemented using the combination of Artificial Intelligence (AI) and Internet of Things (IoT) interfacing by the sensors in the vehicle's battery, and to the cloud. The performance of the battery is monitored using the mobile application of the cloud. © 2022 IEEE.

关键词： Internet of things

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Efficient, broadly-tunable source of megawatt pulses for multiphoton microscopy based on self-phase modulation in argon-filled hollow-core fiber

arXiv

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arXiv 2024年

作者： Eisenberg, Yishai Wang, Wenchao Zhao, Shitong Hebert, Eric S. Chen, Yi-Hao Ouzounov, Dimitre G. Takahashi, Hazuki Gruzdeva, Anna Laviolette, Aaron K. Labaz, Moshe Sidorenko, Pavel Antonio-Lopez, Enrique Amezcua-Correa, Rodrigo Yapici, Nilay Xu, Chris Wise, Frank School of Applied and Engineering Physics Cornell University IthacaNY14853 United States Department of Neurobiology and Behavior Cornell University IthacaNY14853 United States Department of Physics Solid-State Institute Technion Israel Institute of Technology Haifa32000 Israel Department of Electrical and Computer Engineering Solid-State Institute Technion Israel Institute of Technology Haifa32000 Israel CREOL The College of Optics and Photonics University of Central Florida OrlandoFL32816 United States

An exciting recent development for deep-tissue imaging with cellular resolution is three-photon fluorescence microscopy (3PM) with excitation at long wavelengths (1300 and 1700 nm). In the last few years, long-wavelength 3PM has driven rapid progress in deep-tissue imaging beyond the depth limit of two-photon microscopy, with impacts in neuroscience, immunology, and cancer biology. However, wide adoption of 3PM faces challenges. Three-photon excitation (3PE) is naturally weaker than two-photon excitation, which places a premium on ultrashort pulses with high peak power. The inefficiency, complexity, and cost of current sources of these pulses present major barriers to the use of 3PM in typical biomedical research labs. Here, we describe a fiber-based source of femtosecond pulses with multi-megawatt peak power, tunable from 850 nm to 1700 nm. Compressed pulses from a fiber amplifier at 1030 nm are launched into an antiresonant hollow-core fiber filled with argon. By varying only the gas pressure, pulses with hundreds of nanojoules of energy and sub-100 fs duration are obtained at wavelengths between 850 and 1700 nm. This approach is a new route to an efficient, robust, and potentially low-cost source for multiphoton deep-tissue imaging. In particular, 960-nJ and 50-fs pulses are generated at 1300 nm with a conversion efficiency of 10%. The nearly 20-MW peak power is an order of magnitude higher than the previous best from femtosecond fiber source at 1300 nm. As an example of the capabilities of the source, these pulses are used to image structure and neuronal activity in mouse brain as deep as 1.1 mm below the dura. © 2024, CC BY.

关键词： Fluorescence microscopy

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Measurement and interpretation of same-sign W boson pair production in association with two jets in pp collisions at (Formula presented.) TeV with the ATLAS detector

引用

Journal of High Energy physics 2024年第4期2024卷 26页

作者： Aad, G. Abbott, B. Abeling, K. Abicht, N.J. Abidi, S.H. Aboulhorma, A. Abramowicz, H. Abreu, H. Abulaiti, Y. Abusleme Hoffman, A.C. Acharya, B.S. Adam Bourdarios, C. Adamczyk, L. Adamek, L. Addepalli, S.V. Addison, M.J. Adelman, J. Adiguzel, A. Adye, T. Affolder, A.A. Afik, Y. Agaras, M.N. Agarwala, J. Aggarwal, A. Agheorghiesei, C. Ahmad, A. Ahmadov, F. Ahmed, W.S. Ahuja, S. Ai, X. Aielli, G. Aikot, A. Ait Tamlihat, M. Aitbenchikh, B. Aizenberg, I. Akbiyik, M. Åkesson, T.P.A. Akimov, A.V. Akiyama, D. Akolkar, N.N. Al Khoury, K. Alberghi, G.L. Albert, J. Albicocco, P. Albouy, G.L. Alderweireldt, S. Aleksa, M. Aleksandrov, I.N. Alexa, C. Alexopoulos, T. Alfonsi, F. Algren, M. Alhroob, M. Ali, B. Ali, H.M.J. Ali, S. Alibocus, S.W. Aliev, M. Alimonti, G. Alkakhi, W. Allaire, C. Allbrooke, B.M.M. Allen, J.F. Allendes Flores, C.A. Allport, P.P. Aloisio, A. Alonso, F. Alpigiani, C. Alvarez Estevez, M. Alvarez Fernandez, A. Alves Cardoso, M. Alviggi, M.G. Aly, M. Amaral Coutinho, Y. Ambler, A. Amelung, C. Amerl, M. Ames, C.G. Amidei, D. Amor Dos Santos, S.P. Amos, K.R. Ananiev, V. Anastopoulos, C. Andeen, T. Anders, J.K. Andrean, S.Y. Andreazza, A. Angelidakis, S. Angerami, A. Anisenkov, A.V. Annovi, A. Antel, C. Anthony, M.T. Antipov, E. Antonelli, M. Anulli, F. Aoki, M. Aoki, T. Aparisi Pozo, J.A. Aparo, M.A. Aperio Bella, L. Appelt, C. Apyan, A. Aranzabal, N. Arcangeletti, C. Arce, A.T.H. Arena, E. Arguin, J.-F. Argyropoulos, S. Arling, J.-H. Arnaez, O. Arnold, H. Artoni, G. Asada, H. Asai, K. Asai, S. Asbah, N.A. Assamagan, K. Astalos, R. Atashi, S. Atkin, R.J. Atkinson, M. Atmani, H. Atmasiddha, P.A. Augsten, K. Auricchio, S. Auriol, A.D. Austrup, V.A. Avolio, G. Axiotis, K. Azuelos, G. Babal, D. Bachacou, H. Bachas, K. Bachiu, A. Backman, F. Badea, A. Bagnaia, P. Bahmani, M. Bailey, A.J. Bailey, V.R. Baines, J.T. Baines, L. Bakalis, C. Baker, O.K. Bakos, E. Bakshi Gupta, D. Balakrishnan, V. Balasubramanian, R. Baldin, E.M. Balek, P. Ballabene, E. Balli, F. Baltes, L.M. Balunas, W.K. Balz, J. Banas, E. Bandieramont Department of Physics University of Adelaide Department of Physics University of Alberta Department of Physics Ankara University Division of Physics TOBB University of Economics and Technology LAPP Université Savoie Mont Blanc CNRS/IN2P3 APC Université Paris Cité CNRS/IN2P3 High Energy Physics Division Argonne National Laboratory Department of Physics University of Arizona Department of Physics University of Texas at Arlington Physics Department National and Kapodistrian University of Athens Physics Department National Technical University of Athens Department of Physics University of Texas at Austin Institute of Physics Azerbaijan Academy of Sciences Institut de Física d’Altes Energies (IFAE) Barcelona Institute of Science and Technology Institute of High Energy Physics Chinese Academy of Sciences Physics Department Tsinghua University Department of Physics Nanjing University School of Science Shenzhen Campus of Sun Yat-sen University University of Chinese Academy of Science (UCAS) Institute of Physics University of Belgrade Department for Physics and Technology University of Bergen Physics Division Lawrence Berkeley National Laboratory University of California Institut für Physik Humboldt Universität zu Berlin Albert Einstein Center for Fundamental Physics and Laboratory for High Energy Physics University of Bern School of Physics and Astronomy University of Birmingham Department of Physics Bogazici University Department of Physics Engineering Gaziantep University Department of Physics Istanbul University Facultad de Ciencias y Centro de Investigaciónes Universidad Antonio Nariño Departamento de Física Universidad Nacional de Colombia Dipartimento di Fisica e Astronomia A. Righi Università di Bologna INFN Sezione di Bologna Physikalisches Institut Universität Bonn Department of Physics Boston University Department of Physics Brandeis University Transilvania University of Brasov Horia Hulubei National Institute of Physics and Nuclear Engineering Department of Physics Alexandru

This paper presents the measurement of fiducial and differential cross sections for both the inclusive and electroweak production of a same-sign W-boson pair in association with two jets (W^±W^±jj) using 139 fb⁻¹ of proton-proton collision data recorded at a centre-of-mass energy of s = 13 TeV by the ATLAS detector at the Large Hadron Collider. The analysis is performed by selecting two same-charge leptons, electron or muon, and at least two jets with large invariant mass and a large rapidity difference. The measured fiducial cross sections for electroweak and inclusive W^±W^±jj production are 2.92 ± 0.22 (stat.) ± 0.19 (syst.) fb and 3.38 ± 0.22 (stat.) ± 0.19 (syst.) fb, respectively, in agreement with Standard Model predictions. The measurements are used to constrain anomalous quartic gauge couplings by extracting 95% confidence level intervals on dimension-8 operators. A search for doubly charged Higgs bosons H^±± that are produced in vector-boson fusion processes and decay into a same-sign W boson pair is performed. The largest deviation from the Standard Model occurs for an H^±± mass near 450 GeV, with a global significance of 2.5 standard deviations. © The Author(s) 2024.

关键词： Hadron-Hadron Scattering Vector Boson Production

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Entangling Intelligence: AI-Quantum Crossovers and Perspectives

Entangling Intelligence: AI-Quantum Crossovers and Perspecti...

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IEEE International Conference on Trust, Privacy and Security in Intelligent Systems and Applications (TPS-ISA)

作者： Zhuo Chen Di Luo Department of Physics Massachusetts Institute of Technology MA USA The NSF AI Institute for Artificial Intelligence and Fundamental Interactions University of California Los Angeles CA USA Department of Electrical and Computer Engineering University of California Los Angeles CA USA Department of Physics Harvard University Cambridge MA USA

ISBN: (数字)9798350386745

ISBN: (纸本)9798350386752

The intersection of artificial intelligence (AI) and quantum physics has sparked significant advancements in both fields. This paper first reviews the application of AI techniques, particularly neural networks, to quantum simulation. We discuss key developments in representing quantum states, efficient sampling methods, and optimization techniques for ground states and dynamics. The review also explores how quantum principles enhances AI algorithms, including quantum-inspired neural architectures and physics-based optimization methods. We highlight challenges and open questions in this rapidly evolving interdisciplinary field, emphasizing the potential for future innovations that combine AI and quantum approaches to address complex problems in both domains.

关键词： Technological innovation Quantum system Reviews Neural networks Stationary state Optimization methods Quantum state Sampling methods Security Artificial intelligence

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Optical Data Center Implementation within Data Center Networks Context Based on Mininet

Optical Data Center Implementation within Data Center Networ...

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electrical, Energy, and Artificial Intelligence (EICEEAI), International engineering Conference on

作者： Esraa Ali Abdulmahdi Adnan Hussein Ali Raed Khalid Ibrahim Ali Al-Askery Hayder Jasim Alhamdane Amal Ibrahim Mahmood Student at Dept. of Computer Engineering Techniques Electrical Engineering College Middle Technical University Baghdad Iraq Electrical Techniques Department Institute of Technology Middle Technical University Baghdad Iraq Department of Medical Instruments Engineering Techniques Al-Farahidi University Baghdad Iraq Department of Control and Automation Technical Engineering Electrical Engineering College Middle Technical University Baghdad Iraq College of Applied Arts Middle Technical University Baghdad Iraq Dept. of Computer Engineering Techniques Electrical Engineering College Middle Technical University Baghdad Iraq

ISBN: (数字)9798350373363

ISBN: (纸本)9798350373370

The technology of reconfigurable optical networks (RONs) is growing to be a promising solution to effectively cater to the rapidly increasing traffic generated by the digital society. Optical technology emerges as a viable alternative because to its capacity to offer a substantial bandwidth, little latency, and enhanced overall performance. Nevertheless, it is imperative to effectively manage the physical resources comprising a data center. This study provides an experimental demonstration of the RONs, which is enhanced by a control plane. The implementation relies on the monitoring of real-time network statistics. This enables the execution of various activities, including as network slice provisioning and reconfiguration, assignment of packet priority classes, and dynamic operations. These actions are performed to ensure the attainment of the desired Quality of Service level. The experimental results show the successfully implementation of RONs using Mininet Emulator and sFlow traffic monitoring technology. The results approve that optical datacenter has minimum delay with low OSNR even with long distance and fast switching time.

关键词： Data centers Optical switches Optical fiber networks Traffic control Real-time systems Service-oriented architecture Monitoring

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A Compact X-Ray Laser with Ion Source and Crystal Cavity

arXiv

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arXiv 2024年

作者： Li, Shuang School of Electrical and Optoelectronic Engineering West Anhui University Luan237012 China Institute of Applied Physics and Computational Mathematics Beijing100088 China Shanghai EBIT Lab Institute of Modern Physics Department of Nuclear Science and Technology Fudan University Shanghai200433 China

X-ray free-electron lasers (XFELs) are renowned for their high brightness, significantly impacting biology, chemistry, and nonlinear X-ray optics. However, current XFELs are large, expensive, and exhibit significant shot-to-shot instability. Here, we propose a novel compact apparatus for generating X-ray lasers. The setup integrates an ion source to produce highly charged ions as the gain medium. The X-ray optical cavity employs crystal Bragg diffraction for high reflectivity at large angles, and two parabolic compound refractive lenses (CRLs) focus the X-rays. Pumping is achieved through electron collision excitations. This X-ray laser offers compact dimensions, reduced costs, and enhanced coherence, positioning it as a promising seed for XFELs. With further optimization, this device has the potential to rival XFELs and revolutionize both scientific research and industrial applications. © 2024, CC BY-NC-ND.

关键词： X ray lasers

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Data-Driven Wireless Anomaly Detection Using Spectral Features

Data-Driven Wireless Anomaly Detection Using Spectral Featur...

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MILCOM, Military Communications Conference

作者： Stephan Frisbie Mohamed Younis The Johns Hopkins University Applied Physics Laboratory Laurel Maryland United States Department of Computer Science and Electrical Engineering University of Maryland Baltimore County Baltimore Maryland United States

In this work, we present an anomaly detection algorithm for wireless spectrum data and evaluate its ability to accurately detect interfering transmissions. The algorithm considers three types of interfering signals: a co-channel transmission, an interfering continuous-wave transmission, or an adversarial replay attack. At the core of each anomaly detector is a feature space transformation, which learns a compressed representation of the data, followed by various metrics on this representation. Four feature space transformations and four detection metrics are investigated, each of which represents different characterizations of the distribution of the data, totaling 16 configurations of the anomaly detector. Our algorithm is evaluated using Wi-Fi spectrum data from real-world radio frequency (RF) captures in both mild and harsh channel conditions. We present an analysis of the performance of the various configurations under each of the interference types at varying signal-to-interference ratios. Lastly, we discuss the implications of this performance on the the distribution of the data and the recommended model to detect each type of anomaly.

关键词： Training Spatial diversity Interference Detectors Feature extraction Extraterrestrial measurements Anomaly detection

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Deep Augmentation In 5G Scheduling Design Acquiring Knowledge from Concept to Application

Deep Augmentation In 5G Scheduling Design Acquiring Knowledg...

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Communication, Computing and Energy Efficient Technologies (I3CEET), International Conference on

作者： Ammar Hameed Shnain Heera Patwal Urinbaev Sharofiddin Amarjeet Kaur Manish Gupta Niharika Varshney Department of Computers Techniques Engineering College of Technical Engineering The Islamic University of Al Diwaniyah Al Diwaniyah Iraq Department of Computer Science & Engineering Graphic Era Hill University Bhimtal India Department of Physics and Chemistry Tashkent Institute of Irrigation and Agricultural Mechanization Engineers" National Research University Tashkent Uzbekistan Department of Electrical and Communication Engineering Chandigarh Engineering College Chandigarh Group of Colleges Mohali Punjab India Department of Electronics and Communication Engineering GLA University Mathura Department of Electrical Engineering Graphic Era Deemed to be University Dehradun India

ISBN: (数字)9798331541583

ISBN: (纸本)9798331541590

In this paper, we presented a knowledge base assisted deep reinforcement learning (DRL) solution for wireless programming of time-sensitive delivery in 5G cellular networks. Because the deep reliable policy grades mapping from queue and channel states (similar to a Q-learning) to scheduling actions, they may be used as an approximation of good schedule policies with parameterized weights. Unfortunately, the great is Thankfully a modest DD process that comes together with extreme consider for quality-of-service and performs as poorly when targeting this same unpredictable live 5G mobile networks it was supposed to run on. We propose an abstract directional light model to solve these problems, and then present a DRL decision algorithm built on the theoretical framework of wireless communications. We also offer an e-induction and training framework, that after being initialised offline with K-DDPG allows scheduler to be adapted in real-time due the imbalance between off-line (calculation) rewards agreed upon start-up point vs. reality anomaly present during a live system operating time (Utilization of High-Fix action). Simulation results demonstrate that our technique outperforms state-of-the-art schedules in service quality by orders of magnitude and drastically reduces the DDPG iteration time. Our method also reaches faster (in minutes of online fine-tuning consensus) the same higher initial QoS as reported in Table I, for off-line starting than random initialization [16].

关键词： Wireless communication Training Schedules 5G mobile communication Simulation Quality of service computer architecture Deep reinforcement learning Telecommunication computing Testing

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Highly efficient visible and near-IR photon pair generation with thin-film lithium niobate

Optica Quantum

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Optica Quantum 2024年第2期2卷 103-109页

作者： Nathan A. Harper Emily Y. Hwang Ryoto Sekine Luis Ledezma Christian Perez Alireza Marandi Scott K. Cushing Division of Chemistry and Chemical Engineering California Institute of Technologyhttps://***/05dxps055 Pasadena California 91125 USA Department of Applied Physics and Materials Science California Institute of Technology Pasadena California 91125 USA Department of Electrical Engineering California Institute of Technology Pasadena California 91125 USA California State University Los Angeles California 90032 USA

Efficient on-chip entangled photon pair generation at telecom wavelengths is an integral aspect of emerging quantum optical technologies, particularly for quantum communication and computing. However, moving to shorter wavelengths enables the use of more accessible silicon detector technology, and opens up applications in imaging and spectroscopy. Here, we present high brightness ((1.6 ± 0.3) × 10 9 pairs/s/mW/nm) visible–near-IR photon pair generation in a periodically poled lithium niobate nanophotonic waveguide. The degenerate spectrum of the photon pairs is centered at 811 nm with a bandwidth of 117 nm when pumped with a spectrally multimode laser diode. The measured on-chip source efficiency of (2.3 ± 0.5) × 10 11 pairs/s/mW is on par with source efficiencies at telecom wavelengths and is also orders of magnitude higher than the efficiencies of other visible sources implemented in bulk crystal or diffused waveguide-based technologies. Further improvements in the brightness and efficiencies are possible by pumping the device with a single-frequency laser, which would also shrink the pair bandwidth. These results represent the shortest wavelength of photon pairs generated in a nanophotonic waveguide reported to date by nearly an octave.

关键词： Periodically poled lithium niobate Photonic entanglement Quantum communications Quantum computation Quantum information Quantum technology

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