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One-to-one online learning has become pervasive in distance education. However, factors affecting learners' continuance intention toward one-to-one online learning are not well known. This study proposed a model to explain learners' continuance intention toward one-to-one online learning. The model extends previous technology acceptance models and theories by adding instructor-, course-, and system-related factors. A questionnaire was constructed, and a total of 840 samples was collected. Results of hierarchical regression analysis indicated that experience was positively related to continuance intention, and self-efficacy and anxiety were significantly related to perceived ease of use and perceived usefulness. Perceived ease of use, perceived usefulness, attitude toward using the system, facilitating conditions, and social influence were significant predictors of continuance intention to use. Instructor quality, course quality, interaction feedback, and system usability were significantly related to continuance intention toward one-to-one online learning. The proposed model could explain 71.5% of the variance in continuance intention to use one-to-one online learning. The results provided practical implications for the design and improvement of one-to-one online learning systems.

Artificial intelligence (AI) virtual assistants are rapidly growing, permeating people's daily lives and work. However, some trust and risk issues prevent the acceptance and use of AI virtual assistants by users. Thus, understanding the roles of trust and perceived risk in user acceptance of AI virtual assistants is crucial. This study develops a comprehensive research model based on unified theory of acceptance and use of technology (UTAUT) to explain user acceptance of AI virtual assistants. This model extends UTAUT by adding users' perception of trust and risk. The research model and hypotheses are validated through structural equation modeling with a sample of 926 AI virtual assistant users. Results show that gender is significantly related to behavioral intention to use, education is positively related to trust and behavioral intention to use, and usage experience is positively related to attitude toward using. UTAUT variables, including performance expectancy, effort expectancy, social influence, and facilitating conditions, are positively related to behavioral intention to use AI virtual assistant. Trust and perceived risk respectively have positive and negative effects on attitude toward using and behavioral intention to use AI virtual assistants. Trust and perceived risk play equally important roles in explaining user acceptance of AI virtual assistants. Theoretical and practical implications of the current AI virtual assistant acceptance model and directions for future research are discussed. [ABSTRACT FROM AUTHOR]

Online and face-to-face coactions are widely used work organization modes. This study aims to investigate the effect of social comparison direction on task performance when people coact online. A total of 40 individuals were recruited to participate in a 2 (coaction type: online and face to face) × 3 (social comparison direction: upward, downward and no comparison) × 2 (phase: pre-comparison and post-comparison) within-subject experiment. The participants performed visual search tasks while their response time and search accuracy rates were measured. Results showed that the participants were reported to perform faster when they coacted online than face to face. The upward comparison led to a stronger social facilitation effect than the downward and no comparison directions, either in online or face-to-face coaction. These findings provide practical implications in the design of coaction modes for groups and teams working remotely. [ABSTRACT FROM AUTHOR]

Intelligent virtual assistants (IVAs) can help older adults with information queries. Examining older adults' preferences for IVAs' information presentation can help improve user experience and older adults' acceptance of IVAs. This study investigated the effects of information modality and feedback on older adults' social presence, attitudinal outcomes (i.e., perceived enjoyment and satisfaction), and acceptance (i.e., perceived ease of use, perceived usefulness, and behavioral intention to use). A total of 102 subjects were recruited to participate in two experiments. Results show that the visual-auditory bimodality is superior to single visual modality and single auditory modality for older adults based on the perceptions of social presence, attitudinal outcomes, and acceptance. Older adults perceived greater social presence, perceived enjoyment, satisfaction, and acceptance with text feedback than without in IVAs. Social-oriented voice feedback can improve older adults' perceptions of social presence, enjoyment, satisfaction, and acceptance than task-oriented voice feedback. This study provides practical implications in the design of IVAs' information presentation targeted at older adults. [ABSTRACT FROM AUTHOR]

In this study, the silver-exchanged heteropolyacids were prepared by a simple and environmentally friendly ion exchange method, were found to be active in the esterification of oleic acid with methanol to produce biodiesel. The catalysts were characterized by X-ray diffraction (XRD), Fourier transform infrared (FT-IR) and scanning electron microscopy (SEM), separately. The effect of various factors was investigated to optimize the reaction conditions. The results showed that the oleic acid conversion can reach 91.3% after reacting for 3 h at 70°C, with oleic acid to methanol ratio of 1:10 and the amount of catalyst of 5 wt.%. Moreover, the catalyst could be easily separated from the reaction mixture and used repeatedly for five cycles with the oleic acid conversion over 50.1%, due to its relative stability. In particular, this catalyst can also catalyze other esterification of fatty acids with different chain length of carboxylic acid and high acid value non-edible oils, which may provide significant benefits for developing an environmentally benign and continuous process for synthesizing biodiesel in the future. [ABSTRACT FROM AUTHOR]