An Experimental Study on the Effectiveness of Individualized Online Intervention for Mental Health Literacy of Community Residents

Background:Understanding how to improve mental health literacy is conducive to maintaining and promoting individuals’mental health and well-being.However,to date,interventions for mental health literacy primarily depend on traditional education and contact interventions,which have limitations with regard to pertinence and individualization.Artificial intelligence(AI)and big data technology have influenced mental health services to be more intellectual and digital,and they also provide greater technical convenience for individualized interventions for promoting mental health literacy.However,there is relatively little research on the effectiveness of individualized online intervention for mental health literacy in the literature.This study aims to fill this void.To verify whether individualized online intervention can improve the level of mental health literacy.Methods:We conducted a pretest–post-test control experiment.The participants were recruited from a large community located in central China.A total of 152 participants completed the research.We use mixed linear model estimation and paired t-tests to analyze the data.Results:Individualized online intervention can effectively improve the mental health literacy level of participants.Specifically,we found that compared with the control group,the mental health literacy in the experimental group was significantly improved after receiving individualized online intervention.Likewise,the mental health literacy of the control group has also improved after receiving individualized online intervention.In addition,we compared the mental health literacy level of the experimental group at Time 3 to those at Time 2 and found that the mental health literacy level at Time 3 had not decreased one month later.This shows that individualized online intervention was not only momentarily effective,but also had long-term efficacy.Conclusion:This study illustrates that the individualized online intervention has both great momentary and long-term effectiveness in improving community residents’mental health literacy.

How does an individual’s default behavior on an online peer-to-peer lending platform influence an observer’s default intention?

Previous studies indicate that individuals’default behaviors on online peer-to-peer(P2P)lending platforms greatly influence other borrowers’default intentions.However,the mechanism of this impact is not clear.Moreover,there is scarce research in regard to which factors influence the relationship between an individual’s default behavior and an observer’s default intention.These important questions are yet to be resolved;hence,we conducted two experiments using the scenario-based research method,focusing on Chinese online P2P lending platforms.Our results indicate that an individual’s default behavior can trigger an observer’s default intention as a result of the imperfect punitive measures as they currently exist on Chinese online P2P lending platforms.Both the observer’s moral disengagement level and pragmatic self-activation level serve as mediating variables.In situations where an observer knows an individual’s default behavior,the level of intimacy between the defaulter and observer positively affects the relationship between their default behavior and intention.The intimacy level also positively influences the relationship between the individual’s default behavior and the two mediator variables.Based on the findings,we provide management suggestions in the context of online P2P lending.Our study sets a foundation for future research to utilize other methods to extend the present research findings to other regions and domains.

Prediction of Online Judge Practice Passing Rate Based on Knowledge Tracing

Programming ability has become one of the most practical basic skills,and it is also the foundation of software development.However,in the daily training experiment,it is difficult for students to find suitable exercises from a large number of topics provided by numerous online judge(OJ)systems.Recommending high passing rate topics with an effective prediction algorithm can effectively solve the problem.Directly applying some common prediction algorithms based on knowledge tracing could bring some problems,such as the lack of the relationship among programming exercises and dimension disaster of input data.In this paper,those problems were analyzed,and a new prediction algorithm was proposed.Additional information,which represented the relationship between exercises,was added in the input data.And the input vector was also compressed to solve the problem of dimension disaster.The experimental results show that deep knowledge tracing(DKT)with side information and compression(SC)model has an area under the curve(AUC)of 0.7761,which is better than other models based on knowledge tracing and runs faster.

Learning Strategies, Motivation and Learners' Perspectives on Online Multimodal Chinese Learning

This mixed-method empirical study investigated the role of learning strategies and motivation in predicting L2 Chinese learning outcomes in an online multimodal learning environment.Both quantitative and qualitative approaches also examined the learners'perspectives on online multimodal Chinese learning.The participants in this study were fifteen pre-intermediate adult Chinese learners aged 18-26.They were originally from different countries(Spain,Italy,Argentina,Colombia,and Mexico)and lived in Barcelona.They were multilingual,speaking more than two European languages,without exposure to any other Asian languages apart from Chinese.The study's investigation was composed of Strategy Inventory for Language Learning(SILL),motivation questionnaire,learner perception questionnaire,and focus group interview.The whole trial period lasted three months;after the experiment,the statistics were analyzed via the Spearman correlation coefficient.The statistical analysis results showed that strategy use was highly correlated with online multimodal Chinese learning outcomes;this indicated that strategy use played a vital role in online multimodal Chinese learning.Motivation was also found to have a significant effect.The perception questionnaire uncovered that the students were overall satisfied and favoring the online multimodal learning experience design.The detailed insights from the participants were exhibited in the transcripted analysis of focus group interviews.

面向充电桩时间分配的在线双边拍卖机制设计

随着新能源汽车的快速发展,充电时间分配问题成为关注的焦点。现有研究主要集中在根据预先规划的驾驶路线选择充电桩,但对于车主的动态需求却没有提供即时解决方案。为解决该问题,文章首先根据车主的需求量、地理位置以及充电完成度等因素设计了一种需求者优先级函数,然后将充电桩的时间分配问题建模为密封竞价在线双边拍卖,在此基础上,提出了一种真实的交易机制。理论分析证明了该机制不仅满足个体理性、预算平衡,还能够引导供需双方报告真实的到达离开时间以及物品估值。最后通过具体的实验证明了该拍卖机制的实用性和有效性。所提出拍卖机制满足双边市场中交易个体的属性偏好和在线环境的交易特征,为当前的在线充电平台提供了有益的参考。

创造力的影响因素与教育应用——第十届全国创造力学术研讨会综述(上)

在2024年的“第十届全国创造力学术大会”上,与会专家就创造力的定义、创造力的影响因素,以及如何在教育中应用和培养创造力等问题进行了深入讨论,以期进一步促进创造力研究的发展,启迪教育实践中的创新思维产出和应用,为教育改革与发展做出贡献。与会专家认为:创造力不仅包括新颖性和有效性,还应被视为一种复杂的认知过程,涉及多个认知领域的整合。包括个人的认知能力、情感状态、社会环境,以及教育体系对创造力的重视程度等。尤其是,教师的教学方法和学生的自主学习能力对于培养创造力发挥着关键作用。教育体系应更加注重创造力的培养,通过课程设计、教学方法改革以及评价体系的创新,来激发学生的创造潜能。此次研讨会对深化创造力研究,共建创造性教育实践具有重要意义。

互联网“捐赠箱”效应:增加“捐赠箱”对个体互联网捐赠意愿的影响

本研究聚焦于当前互联网捐赠转化率普遍较低的问题,基于心理学理论,提出了一个能够影响和促进个体互联网捐赠意愿的潜在因素:增加“捐赠箱”(即,互联网“捐赠箱”效应)。通过1项模拟真实募捐平台的小程序实验和5项控制实验,本研究验证了该策略的有效性并揭示了背后机制:在互联网募捐情境中,增加(vs.未增加)“捐赠箱”为个体提供了一个感知难度较低的初始决策(即,是否“加入捐赠箱”比是否“立即捐赠”的决策难度低),从而提升了他们的决策意愿(即,加入捐赠箱意愿更高)。而这一初始决策会增强个体与之相关的一致性动机,进而提高其后续捐赠意愿。此外,我们识别了互联网“捐赠箱”效应的边界条件:该效应在一致性偏好较低(vs.较高)的个体中将被削弱。本研究丰富和拓展了捐赠行为决策相关的理论研究,并为公益行业从业者开展互联网公益实践提供了重要的启示与参考。

“谣言的内幕”:个体心理视角的网络政治谣言生成与应对

网络政治谣言既是一种政治现象,也是一种传播行为。网络政治谣言的生成与传播与个体存在密切关联,个体是网络政治谣言传播的关键节点,个体行为影响网络政治谣言的传播进程,个体差异塑造出网络政治谣言的多样性特征。基于个体心理审视,个体的信息缺乏与认知偏差、情感激荡与情绪宣泄、立场分歧与“混乱需求”、理性泯灭及来自所属群体的压力,共同影响着个体参与网络政治谣言生成与传播的态度与行为。网络政治谣言不仅能麻痹个体政治思想、削弱政府公信力,还可能威胁到社会秩序稳定甚至损害国家形象,需要从个体素养、信息监管、政府建设和国际传播等方面综合探讨应对策略,从而有效治理网络政治谣言,形成良好网络空间生态。

学生控制源倾向及其它个体差异对在线学习满意度的影响

随着在线学习在高校的逐步拓展,其有效性越来越受到关注。除了对在线学习成绩进行评价外,学生在线学习的满意度也是一项重要的测度指标。学习满意度是一种主观体验,受个体因素的影响,不同的学生由于个体的差异往往对于他们在线学习的经历持有不同的态度和观点。该文采用问卷调查的方法,探讨表征学生个体差异的两类变量:学生的控制源倾向及其它个体特征,对他们在线学习满意度的影响。调查数据来自于美国一所大学的在线课程。通过状态描述、皮尔逊相关分析以及多元回归统计方法的分析发现,学生的控制源倾向及个性特征与他们在线学习的满意度没有统计意义的相关性,表明在大学中开展在线教学对于各类学生都有良好的适应性。

基于多自由度创新实践的“数字逻辑实验”课程改革

文章分析了现行"数字逻辑实验"课程教学存在的问题,提出了一种时空自由、选题自由、方案自由、手段自由的多自由度创新实践教学模式,并应用于"数字逻辑实验"课程教学中。实践表明,该模式能够有效培养学生的创新能力、工程实践能力和自主学习能力,符合以学生为本、因材施教、提升学生综合素质的初衷。该模式在2020年新冠疫情特殊时期展现出较好的适应性,为教育信息化发展及后疫情时代实践教学提供了新思路。

电子商务环境下消费者冲动性购买形成机理研究

消费者网上冲动购买行为是计划性的,而非多数学者所指的"非计划性"购买行为。影响消费者网上冲动性购买的相关因素包括刺激因素、个体性质及限制因素。购买过程是一个短暂复杂的心理过程,构建冲动性购买行为过程模型可为网上店铺引导消费者冲动性购买提供借鉴。

物流服务质量与在线顾客忠诚——个体差异的调节效应

使用结构方程模型方法对180个网购用户数据进行了验证性因子分析,结果表明,物流服务质量通过在线顾客满意和在线顾客信任对在线顾客忠诚产生显著影响;在线顾客满意不仅直接影响在线顾客忠诚,还可以通过提高在线顾客信任间接创造在线顾客忠诚;女性消费者和网购经验丰富的消费者、物流服务质量对在线顾客忠诚的总体影响效应更大、更显著。

在线协作学习对话分析模型构建及应用--基于元认知视角的研究

元认知是对协作过程的监控和调节,对成功的协作学习至关重要。为弥补当前研究对在线协作对话中元认知分析的不足,基于对话学习理论构建了在线协作学习对话分析模型,从认知性、社会性和元认知三个维度共12个指标对在线协作会话进行内容分析。研究发现,该分析模型能全面分析在线协作对话,尤其是元认知对话的成效:认知冲突可促进认知性对话的高水平发展;元认知体验表达不足会限制元认知活动;个体元认知对认知性对话有显著正向促进作用;社会元认知对社会性对话有显著正向促进作用。鉴于此,研究提出了相关建议,以提升在线协作学习成效。

网络体验和个人特征对网络服务满意度的影响--一项基于青少年网络游戏行为的实证研究

本文以青少年的网络游戏消费为研究背景,探讨了网络服务中的体验性变量和个人特征对满意度的影响。根据体验营销和顾客满意理论并结合网络游戏的相关研究提出假设模型,通过问卷调查法收集数据。结构方程模型的检验结果显示,感知可用性、有趣性和控制力体验以及个人技能会增强满意度,而感知风险和个人新奇需求会降低满意度。网络存在感(Telepresence)受到不同体验性变量和个人特征的影响,并且与满意度之间没有显著关系,但是同样能够预测游戏行为。

网络课程的个性化及其构建

网络教育倡导以学习者为中心,个性化的学习方式。文章在分析我国目前网络课程的个性化现状的基础上,针对网络课程普遍缺乏个性化机制等问题,结合中国教育信息化技术标准(CELTS),构建了基于学习对象的网络课程系统框架,并重点讨论了基于学习对象的特性实现网络课程的个性化及其优势。

新媒体视域下个体投资用户的信息获取行为研究

[目的 /意义]研究了大数据环境下个体投资者的信息获取行为偏好,探索新媒体环境对个体投资用户的决策影响。[方法/过程]基于开放式股票投资在线社交网络(OSN)的视角,分析、确定个体投资用户的主要信息获取行为,以及影响个体投资决策的两个重要因素;通过问卷调查收集相关数据,提出研究假设,进行数据分析,并运用回归分析方法进行假设检验,分析个体投资者决策的信息获取行为偏好。[结果/结论]研究发现:不同个体投资者对信息获取行为的选择存在明显差异;并且个人分析能力不同的投资者的行为偏好存在差异;个性化推荐是对个体投资者决策具有较大影响作用的信息获取行为。

“互联网+”时代在线教育发展的新思路

互联网与教育的深度融合,产生了在线教育。该文分析了在线教育发展过程中产生了新的教育理念,催生了个性化教育,形成了人机融合的教与学方式。但是由于对在线教育研究认识不够等原因,在线教育发展过程中遇到一些问题,比如:目前师生的信息素养难以满足要求,学生的人文关怀和情感交流受阻,难以实现教育均衡发展。新时代的在线教育,需要采取混合式学习、消弭数字教育鸿沟、强化立德树人的发展思路,推动在线教育健康发展。

网络环境下图书馆的虚拟参考咨询服务研究

本文揭示了网络环境下图书馆的新型服务方式虚拟参考咨询服务的概念、方式、特点。阐述了虚拟参考咨询服务的内容,并进一步探讨了虚拟参考咨询服务的发展方向。参考文献11。

一个个性化网络教学系统研究

当前,随着科学技术的飞速发展和网络应用的迅速普及,教育已经逐渐从传统的教学模式向着网络和多媒体的方向发展。作为一种新型的教育形式,多媒体网络教学由于其能够突破时间和地域的限制,快捷和及时的信息交互能力,以及丰富多彩的知识表现形式而得到迅速的发展,并且得到了越来越多的重视和研究。目前的网络教学系统普遍存在着交互性较差、智能化程度较低、个性化程度不够等缺点。对此,提出了个性化网络教学系统的概念,通过将自适应技术应用到教学系统中去,从而真正实现"因人而异,量体裁衣"的个性化教学平台,使得教学系统更加人性化。另外,还进一步对该系统的系统结构和组建方式进行了详细的探索和描述。

一种激励相容的多单位在线双边拍卖机制

针对动态环境下诸如证券交易、计算网格资源分配、排污权交易等双边拍卖市场,研究了多单位在线双边拍卖机制.首先描述了多个买家和多个卖家在任意时间进入和离开拍卖平台,且买家和卖家均可交易多单位同质物品的在线双边拍卖问题;然后,针对该问题设计了多单位在线双边拍卖机制,进而,证明了该机制不仅满足个体理性,物质平衡和弱预算平衡,还能引导买卖双方报告真实的进入时间、离开时间和物品估值;最后,通过算例验证了该机制的可行性和合理性.