武术运动员赛前的心理状态及其自我调节

武术运动员在赛前产生不同的心理状态,将会影响运动员技术水平的发挥。在比赛中如何进行自我调节和控制,这是许多教练员和运动员所研究的一项重要课题。我们通过多次的自我体会和实践,总结出数种自我调节的方法,供同行们借鉴。     

我国儿童网络隐私保护研究

我国目前正处于互联网快速发展的时期,上网儿童数量呈快速增长的趋势,但我国对儿童网络隐私权的保护相当薄弱,这和我国互联网快速的现状不相适应。本文主要研究儿童网络隐私权的保护,并根据我国对儿童网络隐私权的保护现状,结合相关地区和国家的做法,提出了自己的几点建议：（1）网络行业自律;（2）网络分级制度;（3）专门针对儿童网络隐私的官方网站;（4）过滤软件;（5）立法保护。     

自我调节研究进展

自我调节是指个人系统地引导自己的思维、情感和行为,使之指向目标实现的一种过程。对自我调节行为认知取向的研究主要包括自我调节的类型、自我调节的过程、自我调节的结构和对自我调节的解释。有关自我调节神经机制的研究表明,额叶控制着自我调节的多方面,但同时自我调节也涉及其他特殊区域。自我调节与人们的生理和心理健康有着密切关系。此外,未来的研究可以从多角度对自我调节以及自我调节与自我的关系做进一步探讨。     

Self-regulatory and demographic predictors of grades in online and face-to-face university cohorts: A multi-group path analysis

Predictors of academic success at university are of great interest to educators, researchers and policymakers. With more students studying online, it is important to understand whether traditional predictors of academic outcomes in face-to-face settings are relevant to online learning. This study modelled self-regulatory and demographic predictors of subject grades in 84 online and 80 face-to-face undergraduate students. Predictors were effort regulation, grade goal, academic self-efficacy, performance self-efficacy, age, sex, socio-economic status (SES) and first-in-family status. A multi-group path analysis indicated that the models were significantly different across learning modalities. For face-to-face students, none of the model variables significantly predicted grades. For online students, only performance self-efficacy significantly predicted grades (small effect). Findings suggest that learner characteristics may not function in the same way across learning modes. Further factor analytic and hierarchical research is needed to determine whether self-regulatory predictors of academic success continue to be relevant to modern student cohorts.

Practitioner Notes

What is already known about this topic

• Self-regulatory and demographic variables are important predictors of university outcomes like grades.
• It is unclear whether the relationships between predictor variables and outcomes are the same across learning modalities, as research findings are mixed.

What this paper adds

• Models predicting university students' grades by demographic and self-regulatory predictors differed significantly between face-to-face and online learning modalities.
• Performance self-efficacy significantly predicted grades for online students.
• No self-regulatory variables significantly predicted grades for face-to-face students, and no demographic variables significantly predicted grades in either cohort.
• Overall, traditional predictors of grades showed no/small unique effects in both cohorts.

Implications for practice and/or policy

• The learner characteristics that predict success may not be the same across learning modalities.
• Approaches to enhancing success in face-to-face settings are not automatically applicable to online settings.
• Self-regulatory variables may not predict university outcomes as strongly as previously believed, and more research is needed.

     

The uses and abuses of boredom in the classroom

Although the educational and psychological hazards of boredom are well documented, an increasing number of researchers have argued that boredom may be a helpful, rather than harmful, emotion for the growing individual. In this paper, we engage with this re-conception of boredom and explore its implications for contemporary education: Can boredom enhance student learning, or support certain forms of it? Can it be put to use in the classroom? What are the risks involved? In addressing these questions, we show that boredom can fulfil several important psychological functions under certain special conditions. At the same time, we argue that careful attention to the moral psychology of boredom reveals that it has significant disadvantages for helping students to develop a meaningful and fulfilling relationship to subject matter in the classroom. Against the backdrop of this analysis, we discuss the concept and experience of aspiration as a potential way of tempering and eventually obviating the psychological pitfalls of boredom. In the final section, we draw out several principles of an aspirational approach to grappling with boredom in education.     

“论康德的”意志就是实践理性

"意志就是实践理性"表达了意志与理性在超验立法层面的等同,也即纯粹意志与纯粹实践理性的等同。这种等同使人的纯粹意志成为规范性法则的来源,进而表明了道德规范的自因性和自律性。纯粹意志自律的过程是规范性法则生成的过程,同时这一过程也可看作纯粹意志的超越性力量在规范性法则上的凝结和确认,换言之,人的内生性的自由力量外化和呈现为道德性的规范法则,进言之,自律概念内部实现着超越性与规范性的转化与统一。康德把纯粹意志作为一种超验的规范意志的做法,使其哲学呈现出浓厚的意志主义色彩,这直接影响了叔本华的意志主义哲学。     

Leveraging complexity frameworks to refine theories of engagement: Advancing self-regulated learning in the age of artificial intelligence

Capturing evidence for dynamic changes in self-regulated learning (SRL) behaviours resulting from interventions is challenging for researchers. In the current study, we identified students who were likely to do poorly in a biology course and those who were likely to do well. Then, we randomly assigned a portion of the students predicted to perform poorly to a science of learning to learn intervention where they were taught SRL study strategies. Learning outcome and log data (257 K events) were collected from n = 226 students. We used a complex systems framework to model the differences in SRL including the amount, interrelatedness, density and regularity of engagement captured in digital trace data (ie, logs). Differences were compared between students who were predicted to (1) perform poorly (control, n = 48), (2) perform poorly and received intervention (treatment, n = 95) and (3) perform well (not flagged, n = 83). Results indicated that the regularity of students' engagement was predictive of course grade, and that the intervention group exhibited increased regularity in engagement over the control group immediately after the intervention and maintained that increase over the course of the semester. We discuss the implications of these findings in relation to the future of artificial intelligence and potential uses for monitoring student learning in online environments.

Practitioner notes

What is already known about this topic

• Self-regulated learning (SRL) knowledge and skills are strong predictors of postsecondary STEM student success.
• SRL is a dynamic, temporal process that leads to purposeful student engagement.
• Methods and metrics for measuring dynamic SRL behaviours in learning contexts are needed.

What this paper adds

• A Markov process for measuring dynamic SRL processes using log data.
• Evidence that dynamic, interaction-dominant aspects of SRL predict student achievement.
• Evidence that SRL processes can be meaningfully impacted through educational intervention.

Implications for theory and practice

• Complexity approaches inform theory and measurement of dynamic SRL processes.
• Static representations of dynamic SRL processes are promising learning analytics metrics.
• Engineered features of LMS usage are valuable contributions to AI models.