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641.
提高能源效率,从而降低能源消耗、控制消费总量是深化节能减排的重要举措,也是实现节能降耗目标的重要途径。本文在对我省节能降耗的趋势与潜力进行分析的基础上,运用能效分解和消费总量目标分解方法对影响我省节能降耗的主要因素以及各市"十二五"时期的节能降耗目标进行测算,并提出实现目标的模式、途径与措施。 相似文献
642.
大脑潜能的蕴藏方式是多样化的,大脑潜能的产生有先天的因素,但主要是后天学习和实践沉淀的结果。判定大脑潜能的蕴藏方式:一是通过大脑蕴藏的信息量、生物电化反应量、大脑两半球的信息交换量以及大脑重要部位信息量来判定其储存信息能量;二是通过促使大脑潜能外化来判定大脑蕴藏的潜能,通常采用心理和管理的方式,即心理蕴藏潜能和管理蕴藏潜能。 相似文献
643.
《机械基础》是机械类专业的一门专业基础课,综合性较强,也是专业基础课程中较难掌握的一门课,根据以培养就业能力为目标,"够用、实用"为原则,针对学生的实际情况,通过分析该课程进行的教改,提出了以理论教学为主,适时安排实践实训为辅,合理使用多媒体教学手段的方法,有利于启发学生思维,提高教学质量,使学生人尽其才,才尽其用。 相似文献
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女大学生依附心理问题及其对策 总被引:1,自引:0,他引:1
依附心理是阻碍个性发展和社会进步的扭曲人格。它不是不可消除的。本文分析了女大学生依附心理的表现、根源及其危害性 ,并提出了可行的对策 相似文献
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吴奎 《重庆第二师范学院学报》2008,21(2):79-82
在高等教育大众化背景下。高考多元化改革应坚持以省市为单位组织领导高考,实行分省自主命题;将高中会考与高考合并,实现取长补短;扩大高校权限,按专业进行分科组合录取;坚持“特才专招”原则,扩大自主招生范围;鼓励成立半官方性质的民间考试机构。参与高考招生等改革措施。 相似文献
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Qi Xia Thomas K. F. Chiu Ching Sing Chai Kui Xie 《British journal of educational technology : journal of the Council for Educational Technology》2023,54(4):967-986
The anthropomorphic characteristics of artificial intelligence (AI) can provide a positive environment for self-regulated learning (SRL). The factors affecting adolescents' SRL through AI technologies remain unclear. Limited AI and disciplinary knowledge may affect the students' motivations, as explained by self-determination theory (SDT). In this study, we examine the mediating effects of needs satisfaction in SDT on the relationship between students' previous technical (AI) and disciplinary (English) knowledge and SRL, using an AI conversational chatbot. Data were collected from 323 9th Grade students through a questionnaire and a test. The students completed an AI basic unit and then learned English with a conversational chatbot for 5 days. Confidence intervals were calculated to investigate the mediating effects. We found that students' previous knowledge of English but not their AI knowledge directly affected their SRL with the chatbot, and that satisfying the need for autonomy and competence mediated the relationships between both knowledge (AI and English) and SRL, but relatedness did not. The self-directed nature of SRL requires heavy cognitive learning and satisfying the need for autonomy and competence may more effectively engage young children in this type of learning. The findings also revealed that current chatbot technologies may not benefit students with relatively lower levels of English proficiency. We suggest that teachers can use conversational chatbots for knowledge consolidation purposes, but not in SRL explorations.
Practitioner notes
What is already known about this topic- Artificial intelligence (AI) technologies can potentially support students' self-regulated learning (SRL) of disciplinary knowledge through chatbots.
- Needs satisfaction in Self-determination theory (SDT) can explain the directive process required for SRL.
- Technical and disciplinary knowledge would affect SRL with technologies.
- This study examines the mediating effects of needs satisfaction in SDT on the relationship between students' previous AI (technical) and English (disciplinary) knowledge and SRL, using an AI conversational chatbot.
- Students' previous knowledge of English but not their AI knowledge directly affected their SRL with the chatbot.
- Autonomy and competence were mediators, but relatedness was not.
- Teachers should use chatbots for knowledge consolidation rather than exploration.
- Teachers should support students' competence and autonomy, as these were found to be the factors that directly predicted SRL.
- School leaders and teacher educators should include the mediating effects of needs satisfaction in professional development programmes for digital education.