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检索条件"任意字段=International Conference on Learning and Teaching in Computing and Engineering"

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Collaborative learning support system in a classroom using ad hoc network of tablet devices 3

Collaborative learning support system in a classroom using a...

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international conference on learning and teaching in computing and engineering

作者： Sasaki, Naoya Hanai, Yuta Akazawa, Noriko Nakayama, Yasuichi Yamaguchi, Ichiro Univ Electrocommun Grad Sch Informat & Engn Tokyo Japan NEC Corp Ltd Cloud Syst Res Labs Kawasaki Kanagawa Japan

ISBN: (纸本)9781479999675

Having students ask and answer questions among themselves can help deepen their understanding of learning content. Tablet devices are advantageous for such application due to their portability and capability to support not only text but also images and sound. A few elementary schools in Japan have already started introducing tablet devices into the classroom. This requires making some changes to the environment, including providing an access point for the tablets to communicate with each other. To aid in the preparation for computer supported learning, we propose using an ad hoc network of tablet devices to deploy a delay tolerant network with the aim of achieving high message reachability over intermittent connections. The results of preliminary experiments show that our system can provide a high delivery rate, although its delivery speed is somewhat slow. We also created a practical application using the ad hoc network that students can use to exchange content.

关键词： ad hoc networks computer aided instruction tablet computers

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Enhancing IT Education: Education Technology for Teacher Training 4

Enhancing IT Education: Education Technology for Teacher Tra...

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4th international conference on learning and teaching in computing and engineering (LaTICE)

作者： Kode, Sandhya Nori, Kesav Vithal Int Inst Informat Technol IIIT Hyderabad EnhanceEdu Ctr Educ Technol & Learning Sci Hyderabad Andhra Pradesh India

ISBN: (纸本)9781509025046

One of the pressing issues in the Indian IT education today is an acute shortage of skilled teachers. While common sense says that we should use IT to do teacher training and student training, it is not clear how that may be done and in how many different ways the teachers can be helped. The project, described in this article, studies contextualized solutions for the improvement of IT education in Higher Education Institutes (HEIs) in India. This project is being conducted at EnhanceEdu, Centre for Educational Technology and learning Sciences at the international Institute of Information Technology, Hyderabad (IIIT-Hyderabad). This project takes an action research (AR) approach in order to design, implement, and study the impact of new support structures for teacher training. These support structures include learning materials, teaching materials, and educational technology tools such as learning by Doing (LbD) online courses, Open Education Resources, automatic assessment and small private online courses. This project is yielding important understanding in organizing teacher training programs, and searching for the best ways to use educational technology as a part of teacher training. The wider future implications include improved teacher training, improved IT education in Indian HEIs, and better equipped graduates from Indian IT universities. This paper describes the current phase and future scope of this project exploration.

关键词： Teacher Training IT Education Education Technology learning by Doing Open Educational Resources Assessment Online courses

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Exploring Language Modeling Techniques for Improved Recommender Systems 1st

Exploring Language Modeling Techniques for Improved Recommen...

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1st international conference on computing and Emerging Technologies, ICCET 2023

作者： Iqbal, Muhammad Junaid Raza, Usman Ahmed Rehman, Faisal Asaf, Muhammad Ahmed, Yawar Nawaz, Usman Iqbal, Muhammad Saqlain Tariq, Ammara Department of Computer Science Lahore Leads University Lahore Pakistan Lahore Pakistan Department of Statistics and Data Science University of Mianwali Mianwali Pakistan Department of Chemistry COMSATS University Islamabad Lahore Campus Lahore54000 Pakistan Department of Electrical and Information Engineering Polytechnic University of Bari Bari Italy Department of Biochemistry and Biotechnology University of Gujrat Punjab Gujrat Pakistan

ISBN: (纸本)9783031776168

Pre-trained language models (PLMs) have revolutionized natural language processing (NLP) and are now being used in recommendation systems. PLMs learn universal representations from large corpora and can be fine-tuned for specific recommendation tasks with minimal data. This paper presents a taxonomy of PLM-based recommender systems, categorizing them by training paradigms and data types. We also discuss different LM learning goals, including pre-training, language generation, and sequence classification, and how they can be applied to recommendation systems. The effectiveness of these paradigms has been shown in various recommendation tasks, but there are still problems to be addressed, such as language bias and fact consistency in language generation tasks, transfer and injection of domain knowledge, and maintaining and updating large-scale models without sacrificing accuracy or efficiency. The paper also discusses open research questions, such as multi-modal recommendations and privacy concerns. This survey provides a structured way to analyze the effectiveness of different approaches to using PLMs for recommendation systems and provides a valuable resource for researchers and practitioners looking to improve their own recommendation systems. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Modeling languages

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Early Diagnosis of Glaucoma and Diabetic Retinopathy Using Fundus Images Based on Ensemble Approach 1st

Early Diagnosis of Glaucoma and Diabetic Retinopathy Using F...

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1st international Research conference on computing Technologies for Sustainable Development, IRCCTSD 2024

作者： Parthasarathy, Arjun Vasu, Harini Palani, Durgadevi Department of Computer Science and Engineering SRM Institute of Science and Technology Tamil Nadu Chennai India

ISBN: (纸本)9783031823886

Detecting eye diseases like Glaucoma and Diabetic Retinopathy early is crucial to prevent irreversible vision loss;these conditions, characterized by optic nerve damage are recognized as leading causes of blindness. Fundus photography involves capturing images of the back of the eye and it plays a crucial role in diagnosing and monitoring various eye conditions, aiding in the early detection and management of these diseases and their subtypes, such as the different stages of glaucoma and diabetic retinopathy. Existing methods for analysing fundus images rely on traditional image processing techniques like filtering and transformation, and classification methods like CNN or SVMs. These methods do not reliably capture data, leading to lower accuracy in identification. In this study, we utilized fundus images from the FundusImage1000 dataset obtained from Kaggle, which contains a comprehensive collection of images capturing various stages of glaucoma and diabetic retinopathy. This study proposes an ensemble method for glaucoma and diabetic retinopathy detection using fundus images. By utilizing Grey-Level Co-occurrence Matrix for texture analysis, this method integrates classification models XGBoost and Light GBM to make accurate predictions for early identification of the subtypes of these two diseases, including the various stages such as Mild, Moderate, Advanced, Proliferative or Nonproliferative. This combination of texture analysis and ensemble learning yields effective results in automated disease identification. The proposed approach also achieves a high accuracy of 99%, offering a valuable tool for medical professionals to improve diagnostic outcomes and patient care. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Image texture

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CFALEA_LSTM: Adaptive Lotus Effect Algorithm Enabled Long Short-Term Memory for Rainfall Prediction Using Time Series Data 1st

CFALEA_LSTM: Adaptive Lotus Effect Algorithm Enabled Long Sh...

引用

1st international conference on Intelligent Systems in computing and Communications, ISCComm 2023

作者： Vijaya, P. Chander, Satish Fernandes, Roshan Rodrigues, Anisha P. Supriya, B. Modern College of Business and Science Bowshar Oman Biral Institute of Technology Mesra Ranchi India NMAMIT Karnataka Karkala India Shayadri College of Engineering and Management Karnataka Mangaluru India

ISBN: (纸本)9783031756047

Rainfall prediction (RP) utilizing machine learning (ML) is an imperative tool for agricultural and economic practices. RP is also considered as a challenging chore in weather forecasting. An accurate RP can assist farmers to make knowledgeable decisions regarding crop planting, harvesting and fertilization. It also helps in the prevention of floods, disaster management and water resource management. Therefore, the prediction of precise rainfall is significant for diverse applications of a country. Here, Adaptive Lotus Effect algorithm-based Long Short-Term Memory (ALEA_LSTM) is presented for RP utilizing time series data (TSD). Initially, TSD is obtained from a specific database and thereafter technical indicators for RP are extracted from the considered input TSD. Afterwards, feature selection (FS) is accomplished to choose suitable features employing mutual information (MI). Then, data augmentation (DA) is conducted by the oversampling method to augment the dimensionality of data. At last, RP is executed by Long Short-Term Memory (LSTM) that is trained by the Adaptive Lotus Effect Algorithm (ALEA). Moreover, ALEA is devised by integrating the adaptive concept with the Lotus Effect Algorithm (LEA). In addition, ALEA_LSTM achieved minimal values of Mean absolute percentage error (MAPE) of about 0.359, Mean squared error (MSE) of about 0.133 and Root mean squared error (RMSE) of about 0.364. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Mean square error

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Proceedings of 2018 IEEE international conference on teaching, Assessment, and learning for engineering (TALE)

Proceedings of 2018 IEEE International Conference on Teachin...

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IEEE international conference on teaching, Assessment and learning for engineering (TALE)

Presents the title page of the proceedings record.

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Computers in Homes (CiH): Enabling Community Access to Internet and ICT?

Computers in Homes (CiH): Enabling Community Access to Inter...

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international conference on teaching and learning in computing and engineering (LaTiCE)

作者： Assadi, Tony Omid Chard, Sue Whitireia Polytech Fac Business & IT Wellington New Zealand

ISBN: (纸本)9781479935918

This paper evaluates the impact on participants and members of their households of access to a free computer and internet at home. Graduates of the Computers in Homes (CiH) programme in Porirua were used for this study. This programme is a Digital Literacy initiative that operates in conjunction with the National Computers in Homes project in New Zealand. This research followed a qualitative approach using an interpretive analysis of semi structured interviews based on a conversational style [1]. The sampling method was one of purposeful selection using an "opportunist" sample [2]. The study participants were drawn from the graduates who successfully completed the CiH programme in Porirua from October 2007 to April 2011. Findings from the study have shown that the active internet users from the programme shared features of confidence, sociability, and showed enthusiasm for internet-use as an additional tool to further enhance the life of the household. learning beyond the CiH graduation was a common theme for these participants and the support they received from family and friends after graduation was a significant factor in improving their digital literacy. Based on the data gathered in this study, there is evidence that internet-use was extending some users social networks in general as well as helping them to be more established in their community.

关键词： Digital Divide Digital Literacy Community computing Community Initiatives in low Decile Communities

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Studies on Patterns and Variations of learning Community of Practices in Global Context 3

Studies on Patterns and Variations of Learning Community of ...

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international conference on learning and teaching in computing and engineering

作者： Kuo, Karen Yi-Chwen Lin, Chi-Syan Natl Univ Tainan Dept Informat & Learning Technol Tainan Taiwan

ISBN: (纸本)9781479999675

The study first claims that learning community of practice play a significant role in the fields of virtual or online learning. But there are few evidences or knowledge so far about how school students behave in the virtual learning environment in terms of learning behaviors and interpersonal interaction. APEC Cyber Academy (ACA) is an international networked learning environment designed specifically for K-12 students. The primary goal of APEC Cyber Academy is to tap in the affordances of ICT to provide learner-centered, collaborative, and international learning experiences to K-12 students and teachers around the world. The study incorporates ACA as the empirical study instrument. For collecting empirical data, the study administers an online international collaborative learning program on ACA. The study explores patterns of community of practice, which is a combination of participants' online learning behaviors and interpersonal interaction, in global context. Ultimately, there are two pillars with respect to the goals of the study. One of the goals is to explore the patterns in interpersonal interaction and how people engage in learning community in the virtual learning space in general. The other goal of the study is to investigate and explore differences among Students across countries in particular in terms of learning behaviors based on the aggregated data from the first pillar. The study responds abovementioned goals with empirical data and statistic measures. Results of the study confirm the asserted theoretical framework and reveal that students of various countries perform differently in terms of community of practice in virtual learning space.

关键词： Community of Practice Virtual learning Environments Project-based learning international Collaborative learning Networked learning Behaviors

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teaching and learning of Divergent and Convergent Thinking through Open-Problem Solving in a Data Structures Course 4

Teaching and Learning of Divergent and Convergent Thinking t...

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4th international conference on learning and teaching in computing and engineering (LaTICE)

作者： Reddy, Patil Deepti Iyer, Sridhar Sasikumar, M. Indian Inst Technol IDP Educ Technol Bombay Maharashtra India CDAC Bombay Maharashtra India

ISBN: (纸本)9781509025046

Divergent thinking is the process of generating multiple solutions for a given problem, while convergent thinking is evaluating and selecting accurate solution based on constraints, assumptions, and pros and cons analysis. Divergent and convergent thinking is an important thinking skill needed to generate novel or innovative solutions to a given problem. According to ABET guidelines, it is also one of the important skill to design an engineering solution to a given open problem. The training in developing both divergent and convergent thinking during multiple phases of problem solving can allow students to design a better solution. In this paper, we propose an intervention to develop divergent and convergent thinking skill through open problem solving in data structures course. The research methodology followed is Design Based Research (DBR) and the intervention proposed in this paper is operationalized and evaluated by following first cycle of DBR. A preliminary study was conducted on second year Computer engineering students to study the effects of intervention. The results show significant improvement in learners' thinking in both divergent and convergent thinking during open-problem solving.

关键词： Divergent thinking Convergent thinking Open problem solving Data Structures Multiple solution generation

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Students' Types of Argumentative Knowledge Construction Process in Social Collaborative learning Environment 5

Students' Types of Argumentative Knowledge Construction Proc...

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5th international conference on learning and teaching in computing and engineering (LaTICE)

作者： Ibrahim, Siti Nur Khadijah Aishah Harun, Jamalludin Univ Teknol Malaysia Fac Educ Utm Johor Bahru 81310 Johor Malaysia

ISBN: (纸本)9781538608920

With the rapid expansion of computer usage technology, working in social collaborative learning environment has been a common teaching and learning techniques to students. Working collaboratively can trigger deeper discussion which may lead into an argumentative debate and the development of knowledge construction in argumentation. This process is known as argumentative knowledge construction and essentially beneficial in understanding the level of students' thinking skills. However, experiencing the process is important before thinking skills can be related to it. In this study, we combine model of online discussion, argumentative knowledge construction process and 3A interaction model to see the types of argumentative knowledge construction process occur in the students' discussion in a social collaborative learning environment. Data are collected from Facebook group discussion and analyzed using content analysis technique. It is hoped that this model can illustrate a pathway to instructor on how to facilitate students' argumentative knowledge construction process especially in social collaborative learning environment and indirectly lead students' thinking skills towards the highest degree.

关键词： argumentative knowledge construction process social collaborative learning environment higher order thinking skills content analysis model

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