网络科技论文专家评价模型研究

网络科技论文专家评价模型定量指标有:被访次数、被引次数、被下载和打印次数、被转载次数、引文数量、链接数量和相关成果获奖次数等;定性指标有:权威性、准确性、新颖性、全面性和便利性等。可按一定的规范流程对专家评价模型指标进行量化处理。应按确定评价对象、确定专家评价团、确定评分标准、进行数据分析、写评价报告和收集反馈信息的流程实施专家评价模型。表1。参考文献3。     

网络新闻学历史与定义

网络新闻学短短几十年的历史却陷入了说不清道不明的尴尬境地。本文在查证大量文献的基础上,总结出了网络新闻学历史研究中所存在的三种主要版本及其理论依据,同时根据网络新闻学历史的外延范围,在已有的网络新闻学定义基础上对其内涵予以了清晰的界定。     

Reflections of an Online Social Work Professor: Illuminating an Alternative Pedagogy

ABSTRACT

Research in distance education has investigated student satisfaction and learning outcomes, comparing face-to-face with online delivery formats, and tested various technological tools, but has yet to consider alternative pedagogies. Liberatory pedagogy facilitates critical thinking, awareness, reflection and social action around constructs such as race, gender, and class. This paper uses Scholarly Personal Narrative to explore opportunities and challenges of implementing liberatory pedagogy within a virtual classroom. Themes include identity, body, mind, spirit, voice, authenticity, and self-actualization. Liberatory pedagogy emphasizes critical consciousness of oppression, aligns with professional values and ethics, encourages societal well-being, and would appear to enhance online social work education.     

Cognitive and social help giving in online teaching: an exploratory study

While literature suggests that college students may be less reluctant to seek help in online rather than traditional courses, little is known about how online instructors give help in ways that lead to increased student help seeking and academic success. In this study, we used theories and research on learning assistance and scaffolding, teacher immediacy, social presence, and academic help seeking to explore through a cross-case study design how three online instructors differed in their use of cognitive and social supports and how those differences related to student perceptions of support, help seeking, and performance. Primary data sources included all course postings by the instructors, interviews with the instructors, observational field notes on course discussions, student interviews, and final student grades. Archived course documents and student discussion postings were secondary data sources. Data analysis revealed that while all instructors provided cognitive and social support, they varied in their level of questioning, use of direct instruction, support for task structuring, and attention to group dynamics. This variation in teaching presence related to differences across the courses in student perceptions of support, student help seeking in course discussions, and final course grades. Implications for online teaching and suggestions for further research are offered.

Online Celebrity Bashing: Wrecking Ball or Good for You? Adolescent Girls’ Attitudes Toward the Media and Public Bashing of Miley Cyrus and Selena Gomez

Journalists and readers of celebrity news regularly bash celebrities online, a behavior that is easily accepted among adolescents. This study investigates whether these attitudes of acceptance differ according to the perpetrator of the bashing (media versus public) and the likeability of the involved celebrity (liked versus disliked). Using a vignette study, we examine adolescent girls’ attitudes toward media (journalists’) and public (readers’) bashing of a generally disliked celebrity (Miley Cyrus) and a generally liked celebrity (Selena Gomez). All participants read an identical negative news story (media bashing) and two related negative reader comments (public bashing). Participants were randomly assigned to read this information about either Miley Cyrus or Selena Gomez. Results of a mixed-design ANOVA showed that the girls had less negative attitudes toward media bashing compared with public bashing. Moreover, they more easily accepted the bashing of a disliked celebrity than the bashing of a liked celebrity.     

Online portfolio management via deep reinforcement learning with high-frequency data

Recently, models that based on Transformer (Vaswani et al., 2017) have yielded superior results in many sequence modeling tasks. The ability of Transformer to capture long-range dependencies and interactions makes it possible to apply it in the field of portfolio management (PM). However, the built-in quadratic complexity of the Transformer prevents its direct application to the PM task. To solve this problem, in this paper, we propose a deep reinforcement learning-based PM framework called LSRE-CAAN, with two important components: a long sequence representations extractor and a cross-asset attention network. Direct Policy Gradient is used to solve the sequential decision problem in the PM process. We conduct numerical experiments in three aspects using four different cryptocurrency datasets, and the empirical results show that our framework is more effective than both traditional and state-of-the-art (SOTA) online portfolio strategies, achieving a 6x return on the best dataset. In terms of risk metrics, our framework has an average volatility risk of 0.46 and an average maximum drawdown risk of 0.27 across the four datasets, both of which are lower than the vast majority of SOTA strategies. In addition, while the vast majority of SOTA strategies maintain a poor turnover rate of approximately greater than 50% on average, our framework enjoys a relatively low turnover rate on all datasets, efficiency analysis illustrates that our framework no longer has the quadratic dependency limitation.     

基于网络课件的标准应用及界定研究

现代远程教育标准对发展网络远程教育、教学起到了规范和指导的作用,但诸多标准尚处于雏形或发展之中,有许多有待研究和解决的问题。该文立足于网络课件制作、编列、播放的全过程,从功能上就相关的一系列标准应用及如何对其界定进行了探讨。     

Epistemic beliefs in action: Spontaneous reflections about knowledge and knowing during online information searching and their influence on learning

In the present study it was investigated whether high school students are spontaneously able to reflect epistemologically during online searching for information about a controversial topic. In addition, we examined whether activating epistemic beliefs is related to individual characteristics, such as prior knowledge of the topic and argumentative reasoning skill; also whether learning from the Web is influenced by epistemic beliefs in action and the ability to detect fallacies in arguments. The participants (N = 64) were students of Grade 13, who were asked to think aloud during navigation. Qualitative and quantitative analyses were performed. Findings reveal that most participants spontaneously activated beliefs about all four dimensions identified in the literature, that is, about the simplicity/complexity, certainty/uncertainty, justification, and source of knowledge, at different levels of sophistication. Most epistemic reflections were about the source of knowledge. Two patterns of contextualized epistemic beliefs emerged and significantly influenced learning from the Web, which was also affected by participants' ability to identify argumentative fallacies.     

开放教育资源：创新、研究与实践--访阿萨巴斯卡大学罗里·麦格雷尔教授

罗里·麦格雷尔(Rory McGreal)教授是世界上著名的远程教育大学加拿大阿萨巴斯卡大学远程教育中心的教授,也是该校技术促进知识研究所的主任,并曾担任该校主管研究工作的副校长。在国际上,他是联合国教科文组织\英联邦学习共同体等多个国际组织开放教育资源的主席,还是无国界高等教育全球顾问委员会成员和澳大利亚远程教育中心顾问小组的成员。他是开放教育资源知识云(OER Knowledge Cloud)的创使人,开放教育资源基金主任。2013年起担任《国际远程教育研究评论》(International Review of Research in Open and Distance Learning, IRRODL)的合作主编,并兼任多家学术期刊编委和多家学术期刊评审员。他一直致力于远程教育中开放教育资源的研究,由于他在远程教育领域的杰出贡献,于2002年获得在远程教育领域内最具名望的魏德迈奖。其研究兴趣集中在开放教育资源的使用、技术促进学习标准、移动学习以及相关应用的开发等领域。本访谈以“开放教育资源”为核心,对与开放教育资源相关的一系列的研究、创新和实践等进行了深入的访谈,以期为读者呈现一个立体化的、综合的、深入的和最新的国际开放教育资源相关研究与实践的全景图。罗里·麦格雷尔教授首先介绍了MOOCs与开放教育资源的关系,然后深入剖析了开放教育资源之所以要开放的深层次动因;并介绍了在资源泛滥的时代该如何有效地使用和开发开放教育资源以及社会媒体在传播开放教育资源过程中的积极作用;在此基础上介绍了开放教育资源发展过程中面临的阻碍和挑战及其应对策略;并对国际范围内的开放教育资源的最新的实践与创新和研究热点进行了总结。随后,罗里·麦格雷尔教授分享了其需要将开放教育资源与移动学习相结合的原因、阿萨巴斯卡大学在积极参与开放教育资源实践过程中的收获;最后,他推荐了两本开放教育资源相关的著作。