以合作学习为导向,探索中职计算机教学

随着我国教育模式的转变,在信息化的背景下,中国教育也逐步进入了信息化网络时代.为了提高计算机网络教学的发展,中职学校在计算机教学中进行了不断的探寻和研究,总结出通过合作学习的教学方式来提升中职计算机教学的教学质量.合作学习在中职计算机教学中的应用,使学生的学习应用能力与社会接轨,并锻炼学生合作意识,加强学生交流、分享能力.本文对合作学习在中职计算机教学中的应用进行研究分析,查找出其存在的问题,并给出了相应的解决策略.     

Adaptive learning algorithm of self-organizing teams

In order to improve the ability of achieving good performance in self-organizing teams, this paper presents a self-adaptive learning algorithm for team members. Members of the self-organizing teams are simulated by agents. In the virtual self-organizing team, agents adapt their knowledge according to cooperative principles. The self-adaptive learning algorithm is approached to learn from other agents with minimal costs and improve the performance of the self-organizing team. In the algorithm, agents learn how to behave (choose different game strategies) and how much to think about how to behave (choose the learning radius). The virtual team is self-adaptively improved according to the strategies’ ability of generating better quality solutions in the past generations. Six basic experiments are manipulated to prove the validity of the adaptive learning algorithm. It is found that the adaptive learning algorithm often causes agents to converge to optimal actions, based on agents’ continually updated cognitive maps of how actions influence the performance of the virtual self-organizing team. This paper considered the influence of relationships in self-organizing teams over existing works. It is illustrated that the adaptive learning algorithm is beneficial to both the development of self-organizing teams and the performance of the individual agent.     

“任务驱动、小组教学、合作学习”在计算机基础课程教学中的应用

为了使学员通过计算机基础课程的学习,更好地掌握计算机知识,提高实用技能,提出"任务驱动、小组教学、合作学习"的新型教学模式,以"立足需求,着眼应用"为原则,从合理设计教学任务、科学划分学习小组、精心组织教学实施、充分利用网络资源四个方面详细介绍教学模式的具体实现。实践证明,这种新型教学模式充分挖掘学员的学习潜力,激发学员的学习欲望,模式的实施能有效提高教学质量,改善教学效果,是一种有意义的教学改革尝试。     

基于改进蚁群算法的协作学习分组研究

协作学习中根据学习者的特征进行有效分组对于提高学习者的学习效率具有重要的作用。基于学习者的学习能力、兴趣爱好和理解水平,在基于蚁群算法的协作学习分组中,以学习者特征相似度值作为启发信息,并针对蚁群算法可能出现的早熟收敛和停滞现象,分别在初期加入判断回退机制和在中后期对启发因子及期望因子进行动态调节以保证分组结果的准确性。模拟实验结果表明该算法在分组性能及准确性上均优于传统算法。     

几种机器学习方法在黑色素瘤计算机辅助诊断中的性能比较

黑色素瘤的计算机辅助诊断是基于激光共聚焦扫描显微镜（CLSM）皮肤图像纹理特征, 并引入机器学习的技术, 为临床应用研发的一种能够准确、有效地识别在体恶性黑色素瘤新医学诊断方法, 将常用的基于机器学习的ID3、分类与回归树（CART）和AdaBoost三种算法应用于良恶性黑色素瘤图像的特征识别, 并对各种学习方法的性能进行比较。实验结果表明, AdaBoost算法具有较好的分类识别性能, 不但提高了恶性黑色素瘤早期诊断的准确度, 降低了良性黑色素瘤的误诊率, 而且为临床上早期发现和诊断提供了客观依据。     

企业合作创新学习效果的计算机仿真研究*

提出了一个企业合作创新的三因素学习效果影响模型,用数值仿真的方法研究了创新任务特征、创新知识特征和创新环境特征对学习效果的影响,得出了企业的专业化程度与创新任务的可分解性特征负相关、与创新知识的替代特性正相关,且创新环境的不确定特征会加剧企业的专业化程度等相关结论。     

Dynamic cooperative learning control of output-feedback systems with output constraints

This paper investigates the dynamic cooperative learning control for high-order output-feedback systems under the output constraints. To avoid complex computation, we use a system transformation strategy in control design. Only one neural network (NN) is employed to approximate the unknown synthetic function for each agent. Subsequently, a NN-based cooperative learning control mechanism is designed by introducing the barrier Lyapunov function (BLF). The proposed mechanism expands the NN approximation domain of the transformed systems, and the output of all subsystems remains constrained. Further, the NNs on identified uncertain system dynamics are used to construct the experience-based controllers to carry out same control tasks. Finally, the theoretical authenticity is demonstrated by a numerical example.     

The impact of team‐based learning on students with different self‐regulated learning abilities

Team‐based learning (TBL) stresses applying knowledge rather than absorbing knowledge in class; studies have investigated the use of TBL and its merits in different teaching courses (e.g., medical science and business). TBL is most effective when students learn autonomously before class. However, the ability of autonomous learning is highly associated with the ability of self‐regulated learning (SRL); most importantly, not every student possesses good (or high) SRL ability. Nevertheless, few studies have compared the effectiveness of TBL in students with different SRL abilities. To address this issue, this study analyzed approximately 90 students, whose course teaching involves office application software (Microsoft Excel). This study also developed an online TBL system (called Online TBL) to facilitate performing TBL and to collect the learning behaviours of students with different (high or low) SRL abilities on each TBL stage. The analytical results show that compared with the low‐SRL students, the high‐SRL students were more prepared for class because they spent more reviewing material and had better scores on personal uploaded Excel and Individual Readiness Assurance Test. From the feedback of the peer evaluation, the results also show that the high‐SRL students received more credits than the low‐SRL students did. The questionnaire survey revealed that both low‐SRL and high‐SRL students had a favourable impression of TBL. Further discussion is given to explain the above results.     

The effects of trust and constructive controversy on student achievement and attitude in online cooperative learning environments

This study investigated the effects of trust and constructive controversy on student achievement and attitude in online cooperative learning environments. Students in one university course were randomly assigned to one of the two treatment groups after they took part in a common initial workshop on general cooperative learning skills. The “trust” and the “constructive controversy” groups received subsequent associated skills training. The overall results indicated that after each group received the treatment during online cooperative group activities, the “trust” groups had significantly higher achievement than the “constructive controversy” groups. In addition, the “trust” groups had significantly more positive attitudes toward online cooperative learning than the “constructive controversy” groups. Specifically, using “trust” building strategies was significantly more effective than using “constructive controversy” strategies for improving the ‘openness and sharing’ and ‘acceptance and support’ components of student attitudes in online cooperative learning environments.     

Mobile learning with a mobile game: design and motivational effects

Abstract Mobile technologies offer the opportunity to embed learning in a natural environment. This paper describes the design of the MobileGame prototype, exploring the opportunities to support learning through an orientation game in a university setting. The paper first introduces the scenario and then describes the general architecture of the prototype. The main part of the paper focuses on the evaluation of design issues and the effects observed in two trials. Design issues include: Supporting work on the move poses difficult interface questions, the accuracy of current outdoor, and indoor positioning systems is still problematic and the game requires near real-time response time. The evaluation of the effects shows that features such as ‘map-navigation’ and ‘hunting and hiding’ lead to excitement and fun. The participants immerse into a mixed reality that augments both physical and social space. The game success is based on the motivating design of the game itself. The paper concludes with open issues for future research, especially with the need to thoroughly evaluate the learning benefits.     

Distributed cooperative reinforcement learning for multi-agent system with collision avoidance

In this work, we present an optimal cooperative control scheme for a multi-agent system in an unknown dynamic obstacle environment, based on an improved distributed cooperative reinforcement learning (RL) strategy with a three-layer collaborative mechanism. The three collaborative layers are collaborative perception layer, collaborative control layer, and collaborative evaluation layer. The incorporation of collaborative perception expands the perception range of a single agent, and improves the early warning ability of the agents for the obstacles. Neural networks (NNs) are employed to approximate the cost function and the optimal controller of each agent, where the NN weight matrices are collaboratively optimized to achieve global optimal performance. The distinction of the proposed control strategy is that cooperation of the agents is embodied not only in the input of NNs (in a collaborative perception layer) but also in their weight updating procedure (in the collaborative evaluation and collaborative control layers). Comparative simulations are carried out to demonstrate the effectiveness and performance of the proposed RL-based cooperative control scheme.     

Internet project-based learning environment: the effects of thinking styles on learning transfer

The purpose of this study, in an environment of Internet project‐based learning, is to undertake research on the effects of thinking styles on learning transfer. In this study, we establish an environment that incorporates project‐based learning and Internet. Within this environment, we divide our sample of elementary school students into four groups: Executive Group, Legislative Group, Judicial Group, and Mixed Group. Taking the learning of ‘Natural Science’ as an example, we investigate the effects of different thinking styles on learning transfer. The results of this study are:

• (a) significant differences between the near transfer of the Executive Group and the Legislative Group,
• (b) no significant differences in far transfer are found among groups of different thinking styles,
• (c) the near transfer of the Mixed Group is superior to that of the Legislative Group and the Judicial Group, and
• (d) the far transfer of the Mixed Group is superior to that of the Legislative Group.

     

染色体核型分析深度学习方法综述

染色体核型分析是细胞遗传学领域重要的实验技术，并逐步在包括生殖医学在内的诸多现代临床领域和科学研究方面得到广泛应用，但即使是经验丰富的细胞遗传学家也需要大量时间才能完成染色体核型分析。基于传统方法的染色体核型自动化分析方法精度较低，仍需要细胞遗传学家花费大量时间、精力校正。目前基于深度学习的染色体核型自动分析方法成果较多，但缺乏对该领域现状的总结、对未来发展的展望等。因此，本文对基于深度学习的染色体核型自动分析方法进行综述，归纳总结了现有的研究分析任务，挑选了具有代表性的方法并梳理解决方案，展望了未来发展方向。通过整理发现，基于深度学习的染色体核型自动化分析方法取得了很多成果，但仍存在一些问题。首先，已有的中文综述性工作仅集中于某一子领域或者调研不够全面和深入。其次，染色体核型分析任务与临床紧密结合，受各种因素制约，任务类型繁多，解决方案复杂，难以窥斑见豹。最后，现有方法主要集中于染色体分类和染色体分割任务，而诸如染色体计数、染色体预处理等任务研究成果较少，需要厘清问题，吸引更多研究人员关注。综上所述，基于深度学习的染色体核型自动分析方法仍有较大发展空间。     

面向对象的竞争合作学习遥感影像聚类算法

目前的遥感图像聚类方法通常存在一些不可避免的缺陷,如类别数难于自动确定、聚类速度缓慢、聚类过程不稳定以及聚类结果存在椒盐噪声等。结合竞争合作学习和面向对象的图像处理技术的优点,提出一种无需事先指定确切类别数的面向对象的竞争合作学习图像聚类算法。为了加快聚类速度并获得稳定的聚类结果,还提出一种基于动态包围空间的中位切分算法,用于选定初始聚类中心。通过对遥感影像的聚类实验,验证了该算法能够自动获得聚类数并得到满意的聚类结果,说明算法具有很好的实用价值。     

基于深度强化学习的边缘网络内容协作缓存与传输方案研究

为了应对第五代无线通信网络中数据吞吐量急剧增加的问题,移动边缘缓存成为了一种有效的解决方案。它通过在边缘设备上存储网络内容,减轻回程链路和核心网络的负担,缩短服务时延。到目前为止,大多数边缘缓存研究主要在协作内容缓存的优化方面,忽略了内容传输的效率。研究超密集网络的内容协作边缘缓存与无线带宽资源的分配问题,通过余弦相似度和高斯相似度求解基站之间总的相似度,将网络中的小基站根据总相似度进行分组,把缓存和无线带宽分配问题建模成一个长期混合整数的非线性规划问题（LT-MINLP）,进而将协作边缘缓存与带宽分配问题转变为一个带约束的马尔可夫决策过程,并利用深度确定性策略梯度DDPG模型,提出了一种基于深度强化学习的内容协作边缘缓存与带宽分配算法CBDDPG。提出的基站分组方案增加了基站之间文件共享的机会,提出的CBDDPG算法的缓存方案利用DDPG双网络机制能更好地捕捉用户的请求规律,优化缓存部署。将CBDDPG算法与三种基线算法（RBDDPG、LCCS和CB-TS）进行了对比实验,实验结果表明所提方案能够有效地提高内容缓存命中率,降低内容传递的时延,提升用户体验。     

关于人机协作的学习控制

从基本出发，对人机协作学习控制所涉及的人的行为模型、人机协作中的信息与知识、人机协作学习控制的扩展等问题及其相互关联展开了深入的讨论．在此基础上，结合组件化的思想，给出了人机协作学习控制的各种模式．     

Inventing motivates and prepares student teachers for computer‐based learning

A brief, problem‐oriented phase such as an inventing activity is one potential instructional method for preparing learners not only cognitively but also motivationally for learning. Student teachers often need to overcome motivational barriers in order to use computer‐based learning opportunities. In a preliminary experiment, we found that student teachers who were given paper‐based course material spent more time on follow‐up coursework than teachers who were given a well‐developed computer‐based learning environment (CBLE), leading to higher learning outcomes. Thus, we tested inventing as an instructional method that may help overcome motivational barriers of teachers' use of computer‐supported tools or learning environments in our main experimental study (N = 44). As a computer‐based environment, we used the ‘Assessment of Learning strategies in Learning journals’. The inventing group produced ideas about criteria to evaluate learning strategies based on student cases prior to the learning phase. The control condition read a text containing possible answers to the inventing problem. The inventing activity enhanced motivation prior to the learning phase and assessment skills as assessed by transfer problems. Hence, the inventing activity prepared student teachers to learn from a CBLE in a motivational as well as cognitive way.     

浅谈合作学习在高职计算机课堂中的实施

目前，合作学习对教学的促进作用已得到了众多教师和学生的认可。作为高职计算机教师，有效地开展合作学习，有助于激发学生的学习兴趣，提高他们的自主学习能力和计算机操作技能，从而取得事半功倍的教学效果。本文简述了信息技术对合作学习的支持作用，分析了教师与学生在合作学习中的角色，并讨论了合作学习在高职计算机课堂中的实施方法。     

Supporting self‐regulated learning in computer‐based learning environments: systematic review of effects of scaffolding in the domain of science education

Despite the widespread assumption that students require scaffolding support for self‐regulated learning (SRL) processes in computer‐based learning environments (CBLEs), there is little clarity as to which types of scaffolds are most effective. This study offers a literature review covering the various scaffolds that support SRL processes in the domain of science education. Effective scaffolds are categorized and discussed according to the different areas and phases of SRL. The results reveal that most studies on scaffolding processes focus on cognition, whereas few focus on the non‐cognitive areas of SRL. In the field of cognition, prompts appear to be the most effective scaffolds, especially for processes during the control phase. This review also shows that studies have paid little attention to scaffold designs, learner characteristics, or various task characteristics, despite the fact that these variables have been found to have a significant influence. We conclude with the implications of our results on future design and research in the field of SRL using CBLEs.