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7th Australasian Computing Education Conference, ACE 2005

作者： Moffat, Alistair Hughes, Baden Søndergaard, Harald Gruba, Paul Department of Computer Science and Software Engineering The University of Melbourne VIC 3010 Australia

ISBN: (纸本)1920682244

During the last decade, an increasing emphasis has been placed on the need for carefully planned transition programs to help first-year students integrate into university. In this paper we critically examine our experiences in designing and running successive transition programs for computer science and software engineering students. Over the last three years we have trialled several models. At present, our program requires all entering students to be enrolled in a transition subject, "Making Connections", which runs for half a semester. The subject, led by designated academic staff, serves as a forum for students to learn about each other, the department and the university. The program includes a computer-based language and study skills assessment component, including self-assessment tasks. Students can extend the subject by taking academic skills workshops run by the university's student support services. We have found compulsion to be a useful facilitator of student engagement, and the addition of an objective assessment task has been beneficial. © 2005, Australian computer Society, Inc.

关键词： Students

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Using ChatGPT in Undergraduate computer science and software engineering Courses: A Students' Perspective 54

Using ChatGPT in Undergraduate Computer Science and Software...

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54th IEEE Frontiers in Education Conference, FIE 2024

作者： Andersen-Kiel, Noah Linos, Panagiotis Butler University Computer Science and Software Engineering Dept. IndianapolisIN United States

ISBN: (纸本)9798350351507

This innovative practice full paper presents an empirical study aimed at evaluating the potential of ChatGPT, an advanced AI-driven chatbot, as a supplementary educational tool in undergraduate computer science and software engineering (CSSE) courses. The study, initiated in the summer of 2023, focused on assessing ChatGPT's capabilities in generating accurate and complete computer code, identifying and rectifying code defects (bugs), and its scalability in handling larger programs. To achieve this, we conducted a series of experiments with ChatGPT. In one experiment, we introduced bugs into small programs from introductory CSSE courses. ChatGPT was tasked with detecting these defects and providing recommendations for fixing them. We evaluated ChatGPT's effectiveness in bug detection, the quality of its recommendations, and the completeness of the proposed solutions. We sought answers to questions such as whether ChatGPT found all injected defects, provided appropriate recommendations, and delivered high-quality solutions based on criteria like code completeness, size, complexity, and readability. In another experiment, ChatGPT was asked to generate code for assignments from previous CSSE courses, including Intro to computer science and Programming in C++, Intro to Python Programming, and Object-Oriented Programming and Data Structures using Java. We assessed the generated code's correctness and quality in comparison to student-written code. Similarly, in a third experiment, we evaluated ChatGPT's ability to generate larger programs using requirement specifications from an upper-division CSSE course on Agile software engineering. Analyzing both qualitative and quantitative data from these experiments during the summer, we determined that ChatGPT showed promise as an educational tool. Consequently, we developed a plan to integrate ChatGPT into select CSSE courses for the fall semester of 2023. Specifically, ChatGPT was integrated into two of our introductory CSSE cou

关键词： Object oriented programming

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Supporting casual tutors and demonstrators: A case study in computer science and software engineering

Conferences in Research and Practice in Information Technolo...

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Conferences in Research and Practice in Information Technology Series 2006年 52卷 109-115页

作者： Kirley, Michael Department of Computer Science and Software Engineering The University of Melbourne Melbourne VIC 3010 Australia

ISBN: (纸本)1920682341

This paper describes the implementation and evaluation of a comprehensive Department-based training and support program for casual tutors and laboratory demonstrators at the University of Melbourne. The program provides a structured approach to help casual staff develop an understanding of what is involved in high quality teaching and student learning, which can be applied in a computer science and software engineering context. The program involves a number of different phases, including: training sessions, self assessment, peer observation, academic staff member observations, and quality of teaching surveys. We discuss the strengths and limitations of the program, the implications for the Department and identify future directions. © 2006, Australian computer Society, Inc.

关键词： Personnel training

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First steps toward integrating communication instruction throughout computer science and software engineering curricula

First steps toward integrating communication instruction thr...

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118th ASEE Annual Conference and Exposition

作者： Burge, Janet E. Anderson, Paul V. Carter, Michael Gannod, Gerald C. Vouk, Mladen A. Miami University Computer Science and Software Engineering Department United States Howe Center for Writing Excellence Miami University Ohio United States Department of English Graduate School at NC State University United States Department of Computer Science and Software Engineering Mobile Learning Center Miami University United States Department of Computer Science Information Technology North Carolina State University Raleigh NC United States

The three-year project described here is tackling the ambitious problem of developing a new methodology to better prepare our students for the kinds of communication they will need to be proficient at in order to succeed in the workplace. Our approach is to target six core courses that span the CS and SE curricula as opportunities to integrate reading, writing, speaking, and teaming into their technical instruction. This allows the skills to be taught in context and also serves to reinforce the idea that communication is a necessary component in professional success. Prior to and during the implementation of this project, currently at the half-way point, we have identified numerous challenges to its adoption which can be categorized as curricular (how to best incorporate skills into a larger program and into individual courses), instructional (how to teach and assess communication), logistical (how to incorporate communication into courses at different levels of the curriculum and at institutions with different class sizes), and motivational (how to convince students and faculty of the importance of communication). The project addresses these issues in several ways. For curricular issues, we are developing program and course-level student learning outcomes as a guide for skill distribution and integration and will provide a curriculum spanning set for institutions of two different sizes. For instructional issues, we will provide instructional supports to faculty to assist with instruction and sample rubrics to assist with assessment. For logistical issues, we are working with eight different institutions and will provide sample assignments that have been piloted at these institutions. For motivation, we have teamed with industry professionals to provide their assessment of what skills they need to see in new graduates and we will be using this insight to design assignments that can target these skills. We expect students and faculty to be more receptive to assignmen

关键词： Curricula

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Supporting casual tutors and demonstrators: a case study in computer science and software engineering 06

Supporting casual tutors and demonstrators: a case study in ...

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Proceedings of the 8th Australasian Conference on Computing Education - Volume 52

作者： Michael Kirley Department of Computer Science and Software Engineering The University of Melbourne Victoria Australia

ISBN: (纸本)9781920682347

关键词： professional development activities mentor program tutor training

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Research on helping employment difficulties of students by department of computer science and software engineering,Jincheng college of Sichuan University

Research on helping employment difficulties of students by d...

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2014 International Conference on Information engineering and Education science

作者： Ling Hou Department of Computer Science and Software Engineering Jincheng College of Sichuan University

In developing school,every university should pay full attention to employment-oriented development of each *** outstanding students or stylistic active students,schools should set up the appropriate platform,so that they play a meaningful role,and be demonstrated,especially the employment difficulties faced by the students,they need to be more concerned *** should take effective measures to them,and help needy students to solve the problems pertinently,and then make them back to normal *** article took Sichuan University,Jin Cheng College of computer science and software engineering for example to research helping employment difficulties faced by *** practical work,we explored a classification for students from poor management,and use the bedroom and class structures difficult for students to demonstrate the platform,practical and effective measures to counselor part-time teacher two fold emotional care models.

关键词： help employment difficulties category management class activities part-time teacher

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Using ChatGPT in Undergraduate computer science and software engineering Courses: A Students' Perspective

Using ChatGPT in Undergraduate Computer Science and Software...

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Frontiers in Education (FIE) Conference

作者： Noah Andersen-Kiel Panagiotis Panos Linos Computer Science and Software Engineering Dept. Butler University Indianapolis Indiana USA

ISBN: (数字)9798350351507

ISBN: (纸本)9798350363067

关键词： Surveys Codes Scalability computer bugs Project management Chatbots Object oriented programming Programming profession software engineering Python

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Multi-Scale Feature Optimization Point Cloud Completion Network Integrating SoftPool

IAENG International Journal of Computer Science

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IAENG International Journal of computer science 2025年第1期52卷 233-243页

作者： Zhang, Wanpeng Zhou, Ziwei School of Computer Science and Software Engineering University of Science and Technology LiaoNing Anshan114051 China School of Computer Science and Software Engineering University of Science and Technology LiaoNing Anshan114051 China

Point cloud completion is crucial in point cloud processing, as it can repair and refine incomplete 3D data, ensuring more accurate models. However, current point cloud completion methods commonly face a challenge: they fail to fully utilize multi-scale information from local features, leading to limitations in accuracy and detail preservation. To address this issue, this paper proposes a multi-scale feature optimization algorithm for point cloud completion that integrates SoftPool. Based on DGCNN, the method combines dilated convolution and bottleneck attention mechanisms to extract features at different scales, enhancing the ability to capture detailed information in point clouds. The bottleneck attention mechanism is used to optimize important detail features. The extracted local features are concatenated with their corresponding positional information to form point proxies, enhancing the effective extraction of local geometric features, resulting in more refined completed point cloud shapes. A Transformer architecture is employed to model these features. Finally, SoftPool is introduced for fine-grained feature downsampling, improving the network's ability to recover point cloud details. FoldingNet is used to reconstruct missing structures and output the completed point cloud. To validate the model's completion performance, training and testing are conducted on the PCN and ShapeNet55 datasets. Experimental results demonstrate that the model has better feature detail retention and more accurate completion results. On the PCN dataset, the average CD value is reduced by 6.5% compared to the best-performing model among the comparison methods. On the ShapeNet55 dataset, the average CD value across three difficulty levels is reduced by 6.9% compared to the best-performing model among the comparison methods. Additionally, the model also achieved a 2.1% improvement in F-score. © (2025), (International Association of Engineers). All rights reserved.

关键词： Ability testing

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Improving UAV Image Target Detection: A Novel Approach Using OptiDETR with Swin Transformer

IAENG International Journal of Computer Science

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IAENG International Journal of computer science 2025年第3期52卷 771-780页

作者： Ma, Wenlong Liu, Weisheng School of Computer Science and Software Engineering University of Science and Technology Liaoning Anshan114051 China School of Computer Science and Software Engineering University of Science and Technology Liaoning Anshan114051 China

In the analysis of drone aerial images, object detection tasks are particularly challenging, especially in the presence of complex terrain structures, extreme differences in target sizes, suboptimal shooting angles, and varying lighting conditions, all of which exacerbate the difficulty of recognition. In recent years, the DETR model based on the Transformer architecture has eliminated traditional post-processing steps such as NMS(Non-Maximum Suppression), thereby simplifying the object detection process and improving detection accuracy, which has garnered widespread attention in the academic community. However, DETR has limitations such as slow training convergence, difficulty in query optimization, and high computational costs, which hinder its application in practical fields. To address these issues, this paper proposes a new object detection model called OptiDETR. This model first employs a more efficient hybrid encoder to replace the traditional Transformer encoder. The new encoder significantly enhances feature processing capabilities through internal and cross-scale feature interaction and fusion logic. Secondly, an IoU (Intersection over Union) aware query selection mechanism is introduced. This mechanism adds IoU constraints during the training phase to provide higher-quality initial object queries for the decoder, significantly improving the decoding performance. Additionally, the OptiDETR model integrates SW-Block into the DETR decoder, leveraging the advantages of Swin Transformer in global context modeling and feature representation to further enhance the performance and efficiency of object detection. To tackle the problem of small object detection, this study innovatively employs the SAHI algorithm for data augmentation. Through a series of experiments, It achieved a significant performance improvement of more than two percentage points in the mAP (mean Average Precision) metric compared to current mainstream object detection models. Furthermore, ther

关键词： Decoding

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Adaptive ROI Optimization Pyramid Network: Lane Detection for FSD under Data Uncertainty

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engineering Letters 2025年第2期33卷 282-291页

作者： Cao, Xu Liu, Weisheng Wang, Zhijian College of Computer Science and Software Engineering University of Science and Technology Liaoning Anshan China College of Computer Science and Software Engineering University of Science and Technology Liaoning Co Anshan114051 China

To mitigate the challenges posed by data uncertainty in Full-Self Driving (FSD) systems. This paper proposes a novel feature extraction learning model called Adaptive Region of Interest Optimized Pyramid Network (ARO). Specifically, ARO introduces a novel cross-layer fusion attention mechanism that dynamically assigns weighted attention to feature maps across different levels, facilitating deep feature fusion and enabling the effective extraction and utilization of salient feature information. Furthermore, ARO incorporates a feature replication layer to duplicate and refine feature maps at multiple levels, thereby enhancing its capability to capture fine-grained details and generate richer feature representations. Additionally, a multi-path upsampling strategy preserves fine-grained features during upsampling. Extensive experimental evaluations conducted on the benchmark CuLane and Tusimple datasets demonstrate that ARO achieves an F1 score of 80.60% on the CuLane dataset, outperforming state-of-the-art methods, showcasing the effectiveness of the proposed approach in handling data uncertainty for robust lane detection in autonomous driving. Our code are available at https://***/caoxu0109/lane detect ldfr. © 2025, International Association of Engineers. All rights reserved.

关键词： Attention mechanisms Culane Lane detection Multi-scale fusion network Tusimple

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