University Students’ Perception of Video-Based Learning in Times of COVID-19: A TAM/TTF Perspective

International Journal of Human-Computer Interaction, Journal Year: 2020, Volume and Issue: 37(10), P. 903 - 921

Published: Dec. 7, 2020

Physical closure of educational institutes worldwide due to the COVID-19 pandemic has resulted in emergence a new era video-based learning. The current circumstances are unique that have forced students use digital technologies for their learning purpose. However, successful usage such system relies on understanding adoption factors, which an integrated model is proposed based Technology Acceptance Model and Task Fit Model. Additionally, this work considers moderating effects gender inequality. Data collected from 232 all whom taken part full-semester online course times pandemic. A Partial Least Squares method used analyzing data. Results show positively fits into student's perception actual system. effect individual characteristics more than technology task-technology-fit chain. can predict 64.6% variance final dependent variable: Further, while found be significant, inequality non-significant. Finally, theoretical practical implications discussed.

Language: Английский

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Initial expectations, interactions, and beyond with social robots

Computers in Human Behavior, Journal Year: 2018, Volume and Issue: 90, P. 308 - 314

Published: Aug. 25, 2018

Language: Английский

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Design Features of Embodied Conversational Agents in eHealth: a Literature Review

International Journal of Human-Computer Studies, Journal Year: 2020, Volume and Issue: 138, P. 102409 - 102409

Published: Feb. 7, 2020

Embodied conversational agents (ECAs) are gaining interest to elicit user engagement and stimulate actual use of eHealth applications. In this literature review, we identify the researched design features for ECAs in eHealth, outcome variables that were used measure effect these what found effects each variable were. Searches performed Scopus, ACM Digital Library, PsychINFO, Pubmed IEEE Xplore resulting 1284 identified articles which 33 included. The speech and/or textual output its facial gaze expressions most common features. Little research was on agent's looks. measured often perception user's characteristics, relation with agent, system usage, intention use, usability behaviour change. Results show emotion relational seem positively affect characteristics also seems use. However, do not necessarily lead This review showed consensus is far from established. Follow-up should include more all features, especially a long-term, daily life setting, replication studies other contexts than eHealth.

Language: Английский

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Effects of personalization and social role in voice shopping: An experimental study on product recommendation by a conversational voice agent

Computers in Human Behavior, Journal Year: 2020, Volume and Issue: 109, P. 106359 - 106359

Published: April 1, 2020

Language: Английский

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The Cognitive-Affective-Social Theory of Learning in digital Environments (CASTLE)

Educational Psychology Review, Journal Year: 2021, Volume and Issue: 34(1), P. 1 - 38

Published: June 30, 2021

Abstract For a long time, research on individuals learning in digital environments was primarily based cognitive-oriented theories. This paper aims at providing evidence that social processes affect individual with materials. Based these theories and empirical results, social-processes-augmented theory is suggested: the Cognitive-Affective-Social Theory of Learning Environments (CASTLE). CASTLE postulates cues materials activate schemata learners leading to enhanced (para-)social, motivational, emotional, metacognitive processes. To substantiate this theory, socio-cognitive are used, which predict influences Besides, previous findings presented assuming rising number materials, influence increases. Finally, consequences regarding design media discussed.

Language: Английский

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CloChat: Understanding How People Customize, Interact, and Experience Personas in Large Language Models

Published: May 11, 2024

Large language models (LLMs) have facilitated significant strides in generating conversational agents, enabling seamless, contextually relevant dialogues across diverse topics. However, the existing LLM-driven agents fixed personalities and functionalities, limiting their adaptability to individual user needs. Creating personalized agent personas with distinct expertise or traits can address this issue. Nonetheless, we lack knowledge of how people customize interact personas. In research, investigated users impact on interaction quality, diversity, dynamics. To end, developed CloChat, an interface supporting easy accurate customization LLMs. We conducted a study comparing participants CloChat ChatGPT. The results indicate that formed emotional bonds customized engaged more dynamic dialogues, showed interest sustaining interactions. These findings contribute design implications for future systems using

Language: Английский

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A Social-Cognitive Framework for Pedagogical Agents as Learning Companions

Educational Technology Research and Development, Journal Year: 2006, Volume and Issue: 54(6), P. 569 - 596

Published: Nov. 21, 2006

Language: Английский

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Promoting motivation with virtual agents and avatars: role of visual presence and appearance

Philosophical Transactions of the Royal Society B Biological Sciences, Journal Year: 2009, Volume and Issue: 364(1535), P. 3559 - 3565

Published: Nov. 2, 2009

Anthropomorphic virtual agents can serve as powerful technological mediators to impact motivational outcomes such self-efficacy and attitude change. Such anthropomorphic be designed simulated social models in the Bandurian sense, providing influence 'role models'. Of particular value is capacity for designing optimized a target audience context. Importantly, visual presence appearance of have major on motivation affect regardless underlying technical sophistication. Empirical results different instantiations agent are reviewed both autonomous avatars that represent user.

Language: Английский

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Pedagogical agents as learning companions: the impact of agent emotion and gender

Journal of Computer Assisted Learning, Journal Year: 2007, Volume and Issue: 23(3), P. 220 - 234

Published: Jan. 12, 2007

Abstract The potential of emotional interaction between human and computer has recently interested researchers in human–computer interaction. instructional impact this learning environments not been established, however. This study examined the emotion gender a pedagogical agent as companion (PAL) on social judgements, interest, self‐efficacy, learning. Two experiments investigated separately effects PAL's expression empathetic response. Experiment 1 focused (positive vs. negative neutral) (male female) with sample 142 male female college students literacy course. 2 response (responsive non‐responsive) 56 pre‐service teachers. Overall, results yielded main PAL dependent variables. In particular, had positive learner interest self‐efficacy; recall. findings imply that digital could be utilized to optimize students' motivation

Language: Английский

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The design of motivational agents and avatars

Educational Technology Research and Development, Journal Year: 2011, Volume and Issue: 59(2), P. 291 - 300

Published: Feb. 26, 2011

Language: Английский

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