Results 281 to 290 of about 7,386,873 (345)

Analisis Hasil Belajar Matematika Peserta Didik Ditinjau dari Self Confidence

Jurnal Cendekia : Jurnal Pendidikan Matematika, 2021
Hasil belajar peserta didik merupakan salah satu tolok ukur keberhasilan dalam dunia pendidikan untuk mengukur kemampuan, pemahaman, dan penguasaan materi setelah melalui proses pembelajaran.
Nida Savira Maulidya, E. Nugraheni
semanticscholar   +1 more source

Social network group decision making: Managing self-confidence-based consensus model with the dynamic importance degree of experts and trust-based feedback mechanism

Information Sciences, 2019
Due to the development of intelligent decision-making, social network group decision-making (SNGDM) has become increasingly valued. Generally, real SNGDM cases involve not only the mathematical formulation of the social network analysis but also the ...
Xia Liu, Yejun Xu, Rosana Montes
exaly   +2 more sources

Collective Self-Confidence:

2021
Organizer and historian Lane Windham chronicles three generations of African American women organizers in the seasonal tobacco industry in North Carolina. She finds a truism that social progress is never inevitable; it grows from collective efforts, and those collective efforts rarely succeed without mindful and careful organizing, something she first ...
openaire   +1 more source

The Impact of Generative AI on Critical Thinking: Self-Reported Reductions in Cognitive Effort and Confidence Effects From a Survey of Knowledge Workers

International Conference on Human Factors in Computing Systems
The rise of Generative AI (GenAI) in knowledge workflows raises questions about its impact on critical thinking skills and practices. We survey 319 knowledge workers to investigate 1) when and how they perceive the enaction of critical thinking when ...
H. Lee, Advait Sarkar, Lev Tankelevitch, Ian Drosos, Sean Rintel, R. Banks, Nicholas Wilson   +6 more
semanticscholar   +1 more source

As Confidence Aligns: Understanding the Effect of AI Confidence on Human Self-confidence in Human-AI Decision Making

International Conference on Human Factors in Computing Systems
Complementary collaboration between humans and AI is essential for human-AI decision making. One feasible approach to achieving it involves accounting for the calibrated confidence levels of both AI and users.
Jingshu Li, Yitian Yang, Q. Liao, Junti Zhang, Yi-Chieh Lee   +4 more
semanticscholar   +1 more source

Consistency improvement for fuzzy preference relations with self-confidence: An application in two-sided matching decision making

Journal of the Operational Research Society, 2020
The fuzzy preference relation with self-confidence (FPR-SC), whose elements are composed of the degree to which an alternative is preferred to another and the self-confidence level about the preference degree, is a useful tool for decision makers to ...
Zhen Zhang, Xinyue Kou, W. Yu, Yuan Gao
semanticscholar   +1 more source

Confidence Improves Self-Consistency in LLMs

Annual Meeting of the Association for Computational Linguistics
Self-consistency decoding enhances LLMs'performance on reasoning tasks by sampling diverse reasoning paths and selecting the most frequent answer. However, it is computationally expensive, as sampling many of these (lengthy) paths is required to increase
Amir Taubenfeld, Tom Sheffer, E. Ofek, Amir Feder, Ariel Goldstein, Zorik Gekhman, G. Yona   +6 more
semanticscholar   +1 more source

ChatGPT-facilitated professional development: evidence from professional trainers’ learning achievements, self-worth, and self-confidence

Interactive Learning Environments
Professional trainers play an important role in helping new recruits adapt to the workplace. In general hospitals, training courses for clinical teachers still adopt the lecture method.
Chun-Chun Chang, Gwo-Jen Hwang
semanticscholar   +1 more source

SaySelf: Teaching LLMs to Express Confidence with Self-Reflective Rationales

Conference on Empirical Methods in Natural Language Processing
Large language models (LLMs) often generate inaccurate or fabricated information and generally fail to indicate their confidence, which limits their broader applications.
Tianyang Xu, Shujin Wu, Shizhe Diao, Xiaoze Liu, Xingyao Wang, Yangyi Chen, Jing Gao   +6 more
semanticscholar   +1 more source

Confidence Matters: Revisiting Intrinsic Self-Correction Capabilities of Large Language Models

arXiv.org
The recent success of Large Language Models (LLMs) has catalyzed an increasing interest in their self-correction capabilities. This paper presents a comprehensive investigation into the intrinsic self-correction of LLMs, attempting to address the ongoing
Loka Li, Guan-Hong Chen, Yusheng Su, Zhenhao Chen, Yixuan Zhang, Eric P. Xing, Kun Zhang   +6 more
semanticscholar   +1 more source