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  • 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

Current Issue

    • An incremental case-driven teaching
      method for object-oriented programming
      LIU Wanwei,LI Tun,YIN Liangze,CHEN Liqian
      2018, 40(增刊S1): 1-5. doi:
      Abstract ( 122 )   PDF (582KB) ( 228 )     

      Object-oriented programming (OOP) is an important topic for the students majored in computer science and/or software engineering. We investigate the casedriven teaching approach for OOP, including the principle and pedagogical approach, the iterative and incremental exercise setting, design of comprehensive exercises, as well as testing. In addition, we also make further discussion about the teaching plan of the course.

      Teaching reform of modern optimization
      algorithm courses based on MOOC
      YANG Zhiwei1,ZENG Ping2,TANG Guoming1,YANG Kewei1
      2018, 40(增刊S1): 6-11. doi:
      Abstract ( 131 )   PDF (582KB) ( 181 )     

      Aiming at the problems existing in the traditional teaching of modern optimization algorithm courses, we propose a  new student-centered teaching mode which uses the high-quality resources of the MOOC platform to organize teaching activities. This mode strengthens the interaction between teachers and students and encourages students to cooperate with each other. We take the modern algorithm course as a case to design a teaching plan. Finally, the teaching data of the modern optimization algorithm course from 2016 to 2018 are compared to show the teaching effect of the traditional teaching mode and the new teaching mode based on the MOOC platform, which verifies the feasibility of the latter. Results show that the proposed method can effectively improve teaching effect.

      Building an intelligent virtual experiment platform to
      promote modern educational technology reform
      KUI Xiaoyan1,LIU Weiguo1,GUO Kehua1,DU Huakun2
      2018, 40(增刊S1): 12-15. doi:
      Abstract ( 112 )   PDF (432KB) ( 199 )     
      As an important component of practical teaching in higher education, experimental teaching plays an irreplaceable role in improving students’ practical ability and cultivating students’ creativity. With the development of new engineering education, cultivating innovative talents with highquality engineering practice ability has become one goal of talent training  in colleges and universities. The “White Paper on the Development of a New Generation of Artificial Intelligence” released in 2017  requires that teaching activities for higher education should be more integrated with the idea of artificial intelligence in personnel training, and better promote the reform of modern educational technology and the construction of “Double First Class” universities. We discuss the necessity of constructing an intelligent virtual experiment platform based on the concept of artificial intelligence in new situations, and application cases are used to verify the effectiveness and importance of the proposed intelligent virtual experiment platform. It has good application value, can provide new ideas and is helpful for the reform of experimental teaching and the improvement in teaching quality.
       
      On collaborative practical teaching of
      “Embedded System Practice”
      XIAO Xiaoqiang,NING Weixun
      2018, 40(增刊S1): 16-20. doi:
      Abstract ( 94 )   PDF (417KB) ( 154 )     

      Grouping is a typical organization model for experiment teaching. Generally, random and fixed grouping strategies are not favorable for the experiment effect. Take the “Embedded System Practice” as a case study, based on the analysis of normally used grouping methods, we propose a comprehensive grouping strategy by combining students’ will and their skills, and a dynamic grouping strategy corresponding to different experiment steps is implemented at the same time. With the help of information means and tools, we control experimental procedure through experimental diary and offline mentoring, and propose a formative evaluation mechanism consisted of self-assessment within group, mutual-rating among groups and continuous teacher comment. Teaching practice results show that these methods and strategies can promote collaborative practical teaching.

      Teaching reform experiment of Programming Foundation
      based on the concept of engineering education
       
      CAI Meiling,ZHANG Jin,DOU Yaling,LIU Xiangbin,ZHANG Lixia
      2018, 40(增刊S1): 21-26. doi:
      Abstract ( 125 )   PDF (545KB) ( 214 )     
      We analyze the current situation of experiment teaching and the problems existing in the teaching process of Programming Foundation, and then put forward a teaching reform idea based on the concept of engineering education professional certification. With the support of the network teaching management platform and an online evaluation system, we revise experiment teaching from the aspects of teaching contents, teaching mode and teaching evaluation so as to cultivate students’ programming capability and achieve knowledge and educational objectives.
       
      An introduction to CSE course teaching
      LIU Wanwei,MAO Xiaoguang,ZHANG Chunyuan,LI Tun,ZHOU Huiping
      2018, 40(增刊S1): 27-31. doi:
      Abstract ( 94 )   PDF (474KB) ( 157 )     
      In a pedagogical perspective, the teaching concept of CSE is to integrate the computing methodologies of mathematics and physics into SE courses, as well as to extend the scope of computing with the aid of computer. We review the education reform for CSE during the last two years, and discuss some course design issues in the teaching cases in particular. We finally summarize the lessons we can learn from exploratory course-teaching.
       
      Requirements on engineering ability cultivation during the
      development of domestic operating system and our practice
      LI Shanshan,DONG Wei,LUO Yu,WEN Yanjun,LIAO Xiangke
      2018, 40(增刊S1): 32-36. doi:
      Abstract ( 147 )   PDF (442KB) ( 223 )     

      As one of the core techniques in the IT area, operating systems (OSs) play a critical role in both national and military information security. The development of OSs must be independent and under the control of the country to avoid security threat and limitation of active insurance or update. Considering the importance of maintaining our information systems independent, the development of domestic operating systems draws a higher demand on talent cultivation. We analyze the mismatch between engineering ability of developers and requirements of operating system development, from the aspects of development requirements and existing challenges for graduates and course teaching in universities. On that basis, we revise the talent cultivation scheme and try to improve students’ programming capacity from aspects of code quality and software maintenance, and  apply the BOPPPS model to our curriculum design. Besides, we carry on a number of practical teaching reforms with support of Kylin operating system and the highperformance computing platform provided by Tianhe supercomputer. We aim to further enhance teaching effectiveness and cultivate more innovative talents.

      An approach for the teaching of operating system based
      on the experiments of kernel debugging and analysis
      WEN Yanjun,LUO Yu
      2018, 40(增刊S1): 37-41. doi:
      Abstract ( 94 )   PDF (2125KB) ( 161 )     
      It is difficult to integrate principles with practice in the teaching of operating systems. We propose a teaching approach  to solve this problem. According to this approach, operating system courses are organized based on the experiments of kernel debugging and analysis. The contents about principles and practice are taught alternately in the teaching procedure while they keep the integrity of their own. The approach can enable students to understand both principles and practice well. Experiments in the past few years show that the approach can help to concretize operating system principles, and make it easier for both teaching and studying.

       

       
      A blended teaching model based
      on learning behavior analysis
      BAI Liang1,HU Yanli1,ZHENG Long1,2
      2018, 40(增刊S1): 42-46. doi:
      Abstract ( 107 )   PDF (565KB) ( 121 )     

      Student-centered instruction aims to develop skills and practices of learners to enable independent problem-solving and lifelong learning. How to make good use of learning behaviour data to optimize curriculum design poses severe challenges as well as significant opportunities for blended learning and flipped classroom. We build a behaviour analysis-based blended teaching model and apply it to database courses. The model consists of three core components, namely out-of-class independent learning, behaviour analysis and student profiling, and behaviour analysis-based in-class learning with the help of the teacher and peers. Preliminary results indicate that the model promotes students to study independently and stimulates innovations. Students attended database courses have won national undergraduate training programs for innovation and entrepreneurship.

      Study on data-driven research methods for MOOC
      XIE Zheng,LI Jianping
      2018, 40(增刊S1): 47-50. doi:
      Abstract ( 96 )   PDF (358KB) ( 148 )     

      MOOC learning, a new form of education in the information era, breaks through the spacetime limits and the boundary of schools, and promotes sharing of high quality study resources among universities. In the developing process of MOOCs, massive online learning data have been collected, and analyzing these data can provide support for research on MOOC. Combining qualitative and quantitative methods, data science and theory of education,  statistics and network science, we analyze learning behavior patterns, measure the effectiveness of learning behaviors, establish an effectiveness evaluation model for MOOCs, and explore customized teaching methods. Our data-driven methods have a practical significance for  the national project of constructing excellent online courses, and help to improve “Internet+Education” quality.

      Semi-supervised blending learning and
      teaching practice based on practical-style SPOC
       
      WEI Yingmei,XIE Yuxiang,JIANG Jie
      2018, 40(增刊S1): 51-55. doi:
      Abstract ( 92 )   PDF (459KB) ( 148 )     
      Self-directed learning of MOOC provides an effective way for reducing individual difference of students in taking popular optional practical courses. SPOC which utilizes MOOC resources is suitable for classroom teaching. Since selfdirected learning is up to the consciousness of leaners, we discuss the syllabus organized by application problems and propose a semi-supervised blending learning based on SPOC. Our teaching practice and data in the past 3 years prove the effectiveness of such teaching mode.
       
      Oriental music visual education
      based on knowledge graph
      ZHAO Weiping1,SUN Ning2,YANG Xiaochun3,ZHENG Guozhen4
      2018, 40(增刊S1): 56-62. doi:
      Abstract ( 141 )   PDF (657KB) ( 359 )     
      Based on the current status and problems of contemporary oriental music and culture education, we analyze the basic concepts and design principles of visual education, introduce presentation forms and implementation methods of knowledge visualization, and explain the methods of constructing knowledge graph using data processing and natural language processing techniques. We propose a visual education approach using ancient scores and culture knowledge graph, and depict the typical cases of knowledge graph used in teaching. The results show that knowledge graph can provide feasible technical support for ancient music scores and ancient culture education through information and knowledge visualization methods.
       
      Quantitative analysis of  the teaching effect  of
      operating system  courses based on learning behavior data
      WANG Lei,ZHEN Ziqi,WO Tianyu,JIANG Bo,SUN Hailong,LONG Xiang
      2018, 40(增刊S1): 63-71. doi:
      Abstract ( 102 )   PDF (863KB) ( 191 )     

      System capability is one of the core capabilities of the students majored in computer science, and the operating system courses are the key to cultivating it. There are some typical problems  in the traditional teaching process. Firstly, it is difficult to distinguish the ability gap among students in a fine grained manner, so we cannot provide the students detailed guidance. Secondly, teaching activity design is too general and coarsegrained, and there is lack of iterative feedback mechanism during and after each semester. Thirdly, without finegrained learning behavior data, the rules of competence acquisition cannot be analyzed and discovered at the micro level. We design an integrated experiment environment for operating systems, which can not only realize automatic experiment releasing, code committing and evaluation, but also collect and analyze the behavior data of students during the experimentation process. Thus, we can discover the problems in the teaching process in time. Only 38% of students completed at least 4 labs before the experiment environment  came into use in 2014, which reached 62% in 2015. However, by analyzing the learning behavior data in 2015, we found problems such as code copying, lack of preliminary knowledge, inadequate code reading and the lab2 phenomenon. In response to these problems, we take measures both in the current semester and in the longterm period. Finally, quantitative analysis of learning behavior data for 2015, 2016 and 2017 shows that, these improvement measures  achieved significant effect.

      AI avatar based on cloud services
      and its educational application
      YE Feng1,2,HU Cheng1,HUANG Qian1,CHEN Yong2
      2018, 40(增刊S1): 72-80. doi:
      Abstract ( 118 )   PDF (917KB) ( 184 )     
      In AI age, the virtual and intelligent avater software applications represented by Talking Tom increasingly attract more and more attention. From an educational perspective, they can provide company for children, auxiliary learning and other functions. However, constrained by the complexity of related technologies, hardware and networks, it is very difficult for average education researchers to develop AI avatar applications which can offer rich functions and friendly user experience. Aiming at the problem, we propose a solution to developing a framework for AI avatar applications rapidly. It integrates the multiple cloud services from thirdparty providers, and implements virtual 3D avatar with human face synthesis, speech conversion, speech evaluation and social sharing. System testing and comparison with other related works show that the framework is suitable for common Android mobile devices and has the good response speed and friendly user experience, thus it becomes an auxiliary education teaching tool.
       
      A course pass rate prediction method based
      on large data of MOOC learning behavior
       
      ZHENG Long1,2,ZHOU Zhongbao1,HU Yanli2,CAI Jianguo1
      2018, 40(增刊S1): 81-88. doi:
      Abstract ( 115 )   PDF (822KB) ( 195 )     

      Based on the analysis of the evaluation indexes of the large data from the MOOC platform, we introduce the theory of random graph and probability theory, and establish a probability graph model and an algorithm for course pass rate. Based on the network graph theory and the randomness of learning duration, we analyze the dynamic change process of course pass rate qualitatively through the mutual transformation of probability function between timedomain and frequencydomain. Our model can deal with continuous probability distribution cases and discrete probability distribution cases l, as well as massive course pass rate problems highly effectively. Finally, numerical experiment results on MATLAB illustrate the feasibility and effectiveness of the proposed model and algorithm, which can be applied to university MOOC platforms and show a good application prospect.

      Design and implementation of a learning contract
      guided by the three GB principles
       
      LI Tao,DUAN Bin,KUANG Yi
      2018, 40(增刊S1): 89-93. doi:
      Abstract ( 110 )   PDF (656KB) ( 309 )     
      Subject content planning and learning process tracking usually base on scientific logic in traditional education system, which ignores the original experience and life of learners and individuals. The new round of teaching reform emphasizes studentcentered teaching and cultivation of students’ independent learning ability. Contract learning is an education and teaching form based on the study contract. We propose a learning contract verification model guided by the three principles of “national standard”. Combined with the method of artificial intelligence, we analyze a specific case, and  realize outcomeoriented learning. Moreover, the learning contract design  can be applied in the learning output blockchain.
       
      Contribution of MOOCs to the personnel training of computer
      science majors with the concept of “new engineering”
      XIAO Xiao
      2018, 40(增刊S1): 94-97. doi:
      Abstract ( 79 )   PDF (603KB) ( 167 )     
      For computer science majors, corresponding MOOCs support the development of personnel training with the concept of “new engineering”. In China, the MOOCs on computer science released in the last four years have a range of improvements in quality, structure, applicability, and expansibility. We discuss potential contribution those courses can make to learners in aspects of social responsibility, creative thinking, professional knowledge and engineering capacity, and lifelong learning ability.
       
      Discussion on the programs of postgraduate education in
      top universities—a case study of artificial intelligence course
      ZHOU Yun1,3,ZENG Ping2,DU Zhenguo3,TANG Guoming1,3
      2018, 40(增刊S1): 98-102. doi:
      Abstract ( 172 )   PDF (511KB) ( 197 )     
      The cultivation of highend talents is an important indicator to measure a country’s core competitiveness. At present, China still needs a large number of talents in various fields. It is therefore urgent to improve  postgraduate training programs and enhance their quality in Chinese top universities. We firstly discuss current development of artificial intelligence and its significance in “Made in China 2025” plan. Then we analyze the  postgraduate education programs of artificial intelligence in world top universities from four aspects. These training programs can be used as reference for staffs of academic administration departments in China. Finally, we make projections for  future work.
       
      Block chain design for engineering education learning outcomes
      DUAN Bin,LI Tao,KUANG Yi,XIAO Xiangxiang
      2018, 40(增刊S1): 103-108. doi:
      Abstract ( 104 )   PDF (763KB) ( 182 )     

      We propose a block chain technique based on learning output. Firstly, based on the graduation requirements of professional certification colleges and universities, we establish a smart contract for achievement evaluation. Based on the grades, processes and data, through learning outcomes and smart contracts, we conduct a quantitative and qualitative analysis on the learning output, which is then recorded in the Merkel tree. Only the students who can complete the smart contract through the completion of the course can achieve social consensus, and thus obtain the explicit record of the transformation from the assessment for  curriculum completion to the competence evaluation after work. Moreover, the students' capability evaluation can serve as a feedback for the curriculum, thus realizing a continuous improvement.

      Curriculum analysis of data science and big data specialty
      LI Shasha,ZHOU Jingwen,TANG Jintao,WANG Ting
      2018, 40(增刊S1): 109-113. doi:
      Abstract ( 131 )   PDF (397KB) ( 207 )     
      Data science and big data majors are becoming increasingly important, however, personnel cultivation plans vary and the quality is uneven among universities and colleges. We analyze personnel cultivation plans of 14 representative colleges and universities at home and abroad, make some comparison in terms of cultivation objectives and curriculum setting, summarize the present situation and put forward some suggestions on how to design a proper personnel cultivation plan for data science and big data majors.