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Development of the Measure of Assessment Self-Efficacy (MASE) for Quizzes and Exams
Kaitlin Riegel, Tanya Evans, Jason M. Stephens
https://arxiv.org/abs/2508.18631 https://

Development of the Measure of Assessment Self-Efficacy (MASE) for Quizzes and Exams
Self-efficacy is a significant construct in education due to its predictive relationship with achievement. Existing measures of assessment-related self-efficacy concentrate on students' beliefs about content-specific tasks but omit beliefs around assessment-taking. This research aimed to develop and test the Measure of Assessment Self-Efficacy (MASE), designed to assess two types of efficacy beliefs related to assessment (i.e., 'comprehension and execution' and 'emotional regulation') in two sc…

AI-enhanced conversational agents for personalized asthma support Factors for engagement, value and efficacy
Laura Moradbakhti, Dorian Peters, Jennifer K. Quint, Bj\"orn Schuller, Darren Cook, Rafael A. Calvo
https://arxiv.org/abs/2507.16735

AI-enhanced conversational agents for personalized asthma support Factors for engagement, value and efficacy
Asthma-related deaths in the UK are the highest in Europe, and only 30% of patients access basic care. There is a need for alternative approaches to reaching people with asthma in order to provide health education, self-management support and bridges to care. Automated conversational agents (specifically, mobile chatbots) present opportunities for providing alternative and individually tailored access to health education, self-management support and risk self-assessment. But would patients enga…

Backdooring Self-Supervised Contrastive Learning by Noisy Alignment
Tuo Chen, Jie Gui, Minjing Dong, Ju Jia, Lanting Fang, Jian Liu
https://arxiv.org/abs/2508.14015 https://

Backdooring Self-Supervised Contrastive Learning by Noisy Alignment
Self-supervised contrastive learning (CL) effectively learns transferable representations from unlabeled data containing images or image-text pairs but suffers vulnerability to data poisoning backdoor attacks (DPCLs). An adversary can inject poisoned images into pretraining datasets, causing compromised CL encoders to exhibit targeted misbehavior in downstream tasks. Existing DPCLs, however, achieve limited efficacy due to their dependence on fragile implicit co-occurrence between backdoor and …

A Standing Support Mobility Robot for Enhancing Independence in Elderly Daily Living
Ricardo J. Manr\'iquez-Cisterna, Ankit A. Ravankar, Jose V. Salazar Luces, Takuro Hatsukari, Yasuhisa Hirata
https://arxiv.org/abs/2508.19816

A Standing Support Mobility Robot for Enhancing Independence in Elderly Daily Living
This paper presents a standing support mobility robot "Moby" developed to enhance independence and safety for elderly individuals during daily activities such as toilet transfers. Unlike conventional seated mobility aids, the robot maintains users in an upright posture, reducing physical strain, supporting natural social interaction at eye level, and fostering a greater sense of self-efficacy. Moby offers a novel alternative by functioning both passively and with mobility support, enabling user…

Determinants of Saving Behavior Among Employees in Dhaka, Bangladesh
Soumita Roy, Md Muntasir Kamal Dihan, Tasnimah Haque, Nafisa Nomani, Sadia Islam Preety
https://arxiv.org/abs/2507.21254

Determinants of Saving Behavior Among Employees in Dhaka, Bangladesh
Purpose With an emphasis on elements like financial knowledge, financial attitude, social influence, financial self-efficacy, and financial management practices, this study explores the factors that influence employees' saving behavior in Dhaka, Bangladesh. We also welcome others to work on saving behavior, which is the main reason for publishing. The purpose is to make others aware of the methods for quantitative financial behavior analysis in Bangladesh. Design/methodology/approach The study …

A self-supervised learning approach for denoising autoregressive models with additive noise: finite and infinite variance cases
Sayantan Banerjee, Agnieszka Wylomanska, Sundar S
https://arxiv.org/abs/2508.12970

A self-supervised learning approach for denoising autoregressive models with additive noise: finite and infinite variance cases
The autoregressive time series model is a popular second-order stationary process, modeling a wide range of real phenomena. However, in applications, autoregressive signals are often corrupted by additive noise. Further, the autoregressive process and the corruptive noise may be highly impulsive, stemming from an infinite-variance distribution. The model estimation techniques that account for additional noise tend to show reduced efficacy when there is very strong noise present in the data, esp…

Queueing for Civility: User Perspectives on Regulating Emotions in Online Conversations
Akriti Verma, Shama Islam, Valeh Moghaddam, Adnan Anwar
https://arxiv.org/abs/2507.11477

Queueing for Civility: User Perspectives on Regulating Emotions in Online Conversations
Online conversations are often interrupted by trolling, which causes emotional distress and conflict among users. Previous research has focused on moderating harmful content after it has been posted, but ways to manage emotions in real-time remain unexplored. This study suggests a comment queuing mechanism that delays comment publishing, encourages self-reflection, and reduces the impact of impulsive and toxic comments. To assess the efficacy of this approach, a mixed-method research design is …

Replaced article(s) found for cs.HC. https://arxiv.org/list/cs.HC/new
[1/1]:
- The Paradox of Spreadsheet Self-Efficacy: Social Incentives for Informal Knowledge Sharing in End...
Qing (Nancy), Xia, Advait Sarkar, Duncan P. Brumby, Anna Cox

Targeting Melanoma-Specific Tyrosinase: Cyclic Peptide Disrupts Actin Dynamics for Precision Apoptosis Induction
Ruoyang Zhao, Xiaowei Wang, Jiajia Hu, Qingqing Sun, Xinmin Zhao, Jun Guo, Feng Zhang, Min Wu
https://arxiv.org/abs/2507.06534

Targeting Melanoma-Specific Tyrosinase: Cyclic Peptide Disrupts Actin Dynamics for Precision Apoptosis Induction
Melanoma is an aggressive and highly metastatic cancer that exhibits stubborn resistance to conventional therapies, highlighting the need for novel treatments. Existing therapeutic strategies often suffer from systemic toxicity, poor efficacy and fast-gained drug resistance. In this study, we designed a cyclic peptide system (c-RGDKYQ) that takes the advantage of the overexpression of tyrosinase in melanoma cells to trigger enzyme-mediated oxidation and self-assembly. The assembled peptide nano…

Fine-Tuning Hydrophilic-Hydrophobic Balance in Stimuli-Responsive PEGPNIPAM Micelles for Controlled Drug Delivery
Ghazal Jamirad, Mahdi Seif, Abbas Montazeri
https://arxiv.org/abs/2508.13206

Fine-Tuning Hydrophilic-Hydrophobic Balance in Stimuli-Responsive PEGPNIPAM Micelles for Controlled Drug Delivery
Temperature-responsive polymeric micelles have great potential in drug delivery, enhancing therapeutic efficacy while minimizing systemic toxicity. This study investigates the self-assembly of poly(ethylene glycol)-poly(N-isopropylacrylamide) (PEG-PNIPAM) block copolymers as nanocarriers for Doxorubicin (DOX) using coarse-grained molecular dynamics (CG-MD) simulations. We systematically examined the effects of polymer chain length and hydrophilic/hydrophobic balance on micelle formation, stabil…