Computers in human behavior reports最新文献_第7页

Supporting adult-learners’ online interaction in computer-mediated learning

IF 4.9 Q1 PSYCHOLOGY, EXPERIMENTAL

Computers in human behavior reports

Pub Date : 2024-12-01 DOI: 10.1016/j.chbr.2024.100551

Nanda van der Stap , Theo van den Bogaart , Ebrahim Rahimi , Stan van Ginkel , Tobey Nelson , Johan Versendaal

Previous studies have revealed numerous benefits of computer-mediated learning, yet the design of such learning programmes are not always supportive for adult-learners. Studies show that higher education adult-learners are wary of the digital environment in computer-mediated courses, and hence refrain from online interaction resulting in lower learning outcomes and lower perceived learning satisfaction. Without an instructional model that supports adult-learners’ online interaction, teachers may fall back on traditional in-class teaching in an effort to make up for missed learning opportunities. To remedy this, design principles, specifically supportive for adult-learners, were co-designed into an instructional model reflecting the concentric dynamics that strengthen said programmes. In order to validate and improve the quality of the model a Delphi study was carried out among experts (n = 8) to evaluate the various components of the model, including its overall supportiveness for adult-learners in computer-mediated learning. The experts were selected based on their expertise and research in blended learning. Two evaluative rounds through surveys in the programme Crowdtech took place until full alignment of the experts’ opinions was had. The resulting model is a concentric one, illustrating how activities are best distributed across the online environment and the in-class environment, and how social presence can be evoked. This study provides insights into the design of computer-mediated learning programmes tailored for higher education adult-learners as it closes the gap in literature on instructional models and blended learning design. This validated instructional model may help course designers in designing or improving computer-mediated learning programmes.

{"title":"Supporting adult-learners’ online interaction in computer-mediated learning","authors":"Nanda van der Stap , Theo van den Bogaart , Ebrahim Rahimi , Stan van Ginkel , Tobey Nelson , Johan Versendaal","doi":"10.1016/j.chbr.2024.100551","DOIUrl":"10.1016/j.chbr.2024.100551","url":null,"abstract":"<div><div>Previous studies have revealed numerous benefits of computer-mediated learning, yet the design of such learning programmes are not always supportive for adult-learners. Studies show that higher education adult-learners are wary of the digital environment in computer-mediated courses, and hence refrain from online interaction resulting in lower learning outcomes and lower perceived learning satisfaction. Without an instructional model that supports adult-learners’ online interaction, teachers may fall back on traditional in-class teaching in an effort to make up for missed learning opportunities. To remedy this, design principles, specifically supportive for adult-learners, were co-designed into an instructional model reflecting the concentric dynamics that strengthen said programmes. In order to validate and improve the quality of the model a Delphi study was carried out among experts (<em>n</em> = 8) to evaluate the various components of the model, including its overall supportiveness for adult-learners in computer-mediated learning. The experts were selected based on their expertise and research in blended learning. Two evaluative rounds through surveys in the programme Crowdtech took place until full alignment of the experts’ opinions was had. The resulting model is a concentric one, illustrating how activities are best distributed across the online environment and the in-class environment, and how social presence can be evoked. This study provides insights into the design of computer-mediated learning programmes tailored for higher education adult-learners as it closes the gap in literature on instructional models and blended learning design. This validated instructional model may help course designers in designing or improving computer-mediated learning programmes.</div></div>","PeriodicalId":72681,"journal":{"name":"Computers in human behavior reports","volume":"16 ","pages":"Article 100551"},"PeriodicalIF":4.9,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143166437","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Designing adaptive learning environments for continuing education: Stakeholders’ perspectives on indicators and interventions 为继续教育设计适应性学习环境：利益相关者对指标和干预措施的看法

IF 4.9 Q1 PSYCHOLOGY, EXPERIMENTAL

Computers in human behavior reports

Pub Date : 2024-12-01 DOI: 10.1016/j.chbr.2024.100525

Yvonne M. Fromm , Dirk Ifenthaler

Adaptive learning environments (ALE) provide great potential for personalizing and supporting learning processes in continuing education (CE). However, valid frameworks for designing ALE for CE have been missing so far. For example, user-centered and empirically-based guidelines for selecting indicators (i.e., information about learners and their contexts that should be collected and analyzed by ALE) and interventions for personalizing and supporting learning processes have not been established yet. Therefore, this paper aims to develop a framework of indicators and interventions for ALE for CE by investigating the perspectives of different stakeholders (i.e., learners, CE specialists, and educational technology specialists). We first conducted an interview study (N = 37) to identify indicators for ALE for CE. Subsequently, we conducted focus group interviews (N = 19) and an online survey (N = 72) to specify and evaluate possible interventions. Several indicators related to internal (e.g., prior knowledge) and external (e.g., time available for learning) conditions of learning as well as corresponding interventions (e.g., adaptation of the general difficulty level and thematic focus, recommendation of timely suitable learning resources) were identified. We developed a framework classifying interventions based on indicators and adaptivity type and providing evaluations of learners’ willingness to use these interventions, perceived learning support, and implementation effort. This framework can be used by researchers, system designers, as well as CE and educational technology specialists to design and implement user-centered and trustworthy ALE for CE.

适应性学习环境（ALE）为继续教育（CE）的个性化和支持性学习过程提供了巨大的潜力。然而，到目前为止，还没有为CE设计ALE的有效框架。例如，尚未建立以用户为中心和以经验为基础的选择指标准则（即由ALE收集和分析的关于学习者及其背景的信息）以及个性化和支持学习过程的干预措施。因此，本文旨在通过调查不同利益相关者（即学习者、CE专家和教育技术专家）的观点，为CE的ALE制定一个指标和干预措施框架。我们首先进行了一项访谈研究（N = 37），以确定ALE对CE的指标。随后，我们进行了焦点小组访谈（N = 19）和在线调查（N = 72），以指定和评估可能的干预措施。确定了与学习的内部（例如，先验知识）和外部（例如，可用于学习的时间）条件以及相应的干预措施（例如，对一般难度水平和主题重点的适应，及时推荐合适的学习资源）相关的几个指标。我们开发了一个框架，根据指标和适应性类型对干预措施进行分类，并对学习者使用这些干预措施的意愿、感知到的学习支持和实施努力进行评估。研究人员、系统设计师以及CE和教育技术专家可以使用该框架为CE设计和实现以用户为中心且值得信赖的ALE。

{"title":"Designing adaptive learning environments for continuing education: Stakeholders’ perspectives on indicators and interventions","authors":"Yvonne M. Fromm , Dirk Ifenthaler","doi":"10.1016/j.chbr.2024.100525","DOIUrl":"10.1016/j.chbr.2024.100525","url":null,"abstract":"<div><div>Adaptive learning environments (ALE) provide great potential for personalizing and supporting learning processes in continuing education (CE). However, valid frameworks for designing ALE for CE have been missing so far. For example, user-centered and empirically-based guidelines for selecting indicators (i.e., information about learners and their contexts that should be collected and analyzed by ALE) and interventions for personalizing and supporting learning processes have not been established yet. Therefore, this paper aims to develop a framework of indicators and interventions for ALE for CE by investigating the perspectives of different stakeholders (i.e., learners, CE specialists, and educational technology specialists). We first conducted an interview study (<em>N</em> = 37) to identify indicators for ALE for CE. Subsequently, we conducted focus group interviews (<em>N</em> = 19) and an online survey (<em>N</em> = 72) to specify and evaluate possible interventions. Several indicators related to internal (e.g., prior knowledge) and external (e.g., time available for learning) conditions of learning as well as corresponding interventions (e.g., adaptation of the general difficulty level and thematic focus, recommendation of timely suitable learning resources) were identified. We developed a framework classifying interventions based on indicators and adaptivity type and providing evaluations of learners’ willingness to use these interventions, perceived learning support, and implementation effort. This framework can be used by researchers, system designers, as well as CE and educational technology specialists to design and implement user-centered and trustworthy ALE for CE.</div></div>","PeriodicalId":72681,"journal":{"name":"Computers in human behavior reports","volume":"16 ","pages":"Article 100525"},"PeriodicalIF":4.9,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142743197","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Human performance in detecting deepfakes: A systematic review and meta-analysis of 56 papers 人类在检测深度造假中的表现：对56篇论文的系统回顾和荟萃分析

IF 4.9 Q1 PSYCHOLOGY, EXPERIMENTAL

Computers in human behavior reports

Pub Date : 2024-12-01 DOI: 10.1016/j.chbr.2024.100538

Alexander Diel , Tania Lalgi , Isabel Carolin Schröter , Karl F. MacDorman , Martin Teufel , Alexander Bäuerle

Deepfakes are AI-generated media designed to look real, often with the intent to deceive. Deepfakes threaten public and personal safety by facilitating disinformation, propaganda, and identity theft. Though research has been conducted on human performance in deepfake detection, the results have not yet been synthesized. This systematic review and meta-analysis investigates human deepfake detection accuracy. Searches in PubMed, ScienceGov, JSTOR, Google Scholar, and paper references, conducted in June and October 2024, identified empirical studies measuring human detection of high-quality deepfakes. After pooling accuracy, odds-ratio, and sensitivity (d') effect sizes (k = 137 effects) from 56 papers involving 86,155 participants, we analyzed 1) overall deepfake detection performance, 2) performance across stimulus types (audio, image, text, and video), and 3) the effects of detection-improvement strategies. Overall deepfake detection rates (sensitivity) were not significantly above chance because 95% confidence intervals crossed 50%. Total deepfake detection accuracy was 55.54% (95% CI [48.87, 62.10], k = 67). For audio, accuracy was 62.08% [38.23, 83.18], k = 8; for images, 53.16% [42.12, 64.64], k = 18; for text, 52.00% [37.42, 65.88], k = 15; and for video, 57.31% [47.80, 66.57], k = 26. Odds ratios were 0.64 [0.52, 0.79], k = 62, indicating 39% detection accuracy, below chance (audio 45%, image 35%, text 40%, video 40%). Moreover, d' values show no significant difference from chance. However, strategies like feedback training, AI support, and deepfake caricaturization improved detection performance above chance levels (65.14% [55.21, 74.46], k = 15), especially for video stimuli.

深度造假是人工智能生成的媒体，旨在看起来真实，通常带有欺骗的意图。深度造假通过助长虚假信息、宣传和身份盗窃，威胁公共和个人安全。虽然已经对人类在深度伪造检测中的表现进行了研究，但结果尚未合成。本系统综述和荟萃分析调查了人类深度伪造检测的准确性。在PubMed， ScienceGov， JSTOR， b谷歌Scholar和论文参考文献中进行的搜索于2024年6月和10月进行，确定了测量人类检测高质量深度伪造的实证研究。在汇总了涉及86155名参与者的56篇论文的准确性、优势比和灵敏度（d'）效应大小（k = 137个效应）后，我们分析了1)整体深度伪造检测性能，2)不同刺激类型（音频、图像、文本和视频）的性能，以及3)检测改进策略的效果。总体深度伪造的检测率（灵敏度）没有显著高于概率，因为95%的置信区间超过50%。总深度造假检测准确率为55.54% （95% CI [48.87, 62.10], k = 67）。音频准确率为62.08% [38.23,83.18],k = 8；对于图像，53.16% [42.12,64.64],k = 18；对于文本，52.00% [37.42,65.88],k = 15；视频为57.31% [47.80,66.57],k = 26。比值比为0.64 [0.52,0.79],k = 62，表明检测准确率为39%，低于概率（音频45%，图像35%，文本40%，视频40%）。d'值与偶然性无显著差异。然而，反馈训练、人工智能支持和深度假漫画化等策略将检测性能提高到机会水平以上（65.14% [55.21,74.46],k = 15），特别是对于视频刺激。

{"title":"Human performance in detecting deepfakes: A systematic review and meta-analysis of 56 papers","authors":"Alexander Diel , Tania Lalgi , Isabel Carolin Schröter , Karl F. MacDorman , Martin Teufel , Alexander Bäuerle","doi":"10.1016/j.chbr.2024.100538","DOIUrl":"10.1016/j.chbr.2024.100538","url":null,"abstract":"<div><div><em>Deepfakes</em> are AI-generated media designed to look real, often with the intent to deceive. Deepfakes threaten public and personal safety by facilitating disinformation, propaganda, and identity theft. Though research has been conducted on human performance in deepfake detection, the results have not yet been synthesized. This systematic review and meta-analysis investigates human deepfake detection accuracy. Searches in PubMed, ScienceGov, JSTOR, Google Scholar, and paper references, conducted in June and October 2024, identified empirical studies measuring human detection of high-quality deepfakes. After pooling accuracy, odds-ratio, and sensitivity (<em>d'</em>) effect sizes (<em>k</em> = 137 effects) from 56 papers involving 86,155 participants, we analyzed 1) overall deepfake detection performance, 2) performance across stimulus types (audio, image, text, and video), and 3) the effects of detection-improvement strategies. Overall deepfake detection rates (<em>sensitivity</em>) were not significantly above chance because 95% confidence intervals crossed 50%. Total deepfake detection accuracy was 55.54% (95% CI [48.87, 62.10], <em>k</em> = 67). For audio, accuracy was 62.08% [38.23, 83.18], <em>k</em> = 8; for images, 53.16% [42.12, 64.64], <em>k</em> = 18; for text, 52.00% [37.42, 65.88], <em>k</em> = 15; and for video, 57.31% [47.80, 66.57], <em>k</em> = 26. Odds ratios were 0.64 [0.52, 0.79], <em>k</em> = 62, indicating 39% detection accuracy, below chance (audio 45%, image 35%, text 40%, video 40%). Moreover, <em>d'</em> values show no significant difference from chance. However, strategies like feedback training, AI support, and deepfake caricaturization improved detection performance above chance levels (65.14% [55.21, 74.46], <em>k</em> = 15), especially for video stimuli.</div></div>","PeriodicalId":72681,"journal":{"name":"Computers in human behavior reports","volume":"16 ","pages":"Article 100538"},"PeriodicalIF":4.9,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142757509","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Longitudinal bidirectional relation between fear of missing out and risky loot box consumption: Evidence for FoMO-Driven loot boxes spiral hypothesis 害怕错过和冒险的战利品盒消费之间的纵向双向关系：fomo驱动的战利品盒螺旋假说的证据

IF 4.9 Q1 PSYCHOLOGY, EXPERIMENTAL

Computers in human behavior reports

Pub Date : 2024-12-01 DOI: 10.1016/j.chbr.2024.100535

Andree Hartanto, K.T.A.Sandeeshwara Kasturiratna

Background

The integration of loot boxes has emerged as a significant factor contributing to the increasing revenue in the video gaming industry. However, this integration has also led to widespread engagement in risky loot box consumption. To understand the mechanism that drives and sustains such maladaptive behavior, we propose the FoMO-Driven Loot Boxes Spiral Hypothesis – positing that fear of missing out (FoMO) not only triggers initial engagement in risky loot box consumption but also perpetuates a self-reinforcing cycle, where such engagement intensifies subsequent FoMO, leading to further risky loot box consumption.

Method and results

We conducted a 13-week longitudinal study of 252 college students with weekly data collection to examine the bidirectional relation. Using random-intercept cross-lagged panel models, we found significant small-to-moderate cross-lagged effects from FoMO to risky loot box consumption and significant moderate-to-large cross-lagged effects from risky loot box consumption to FoMO.

Implications

Our findings support FoMO as an important trigger for initiating risky loot box consumption. Moreover, once players start engaging with risky loot box consumption, they often find themselves trapped in a reinforcing cycle of FoMO and risky loot box consumption. These findings contributes to our understanding of problematic behavior in digital gaming and have implications for the development of targeted interventions and policies aimed at reducing risky loot box consumption.

战利品盒的整合已经成为电子游戏行业盈利增长的重要因素。然而，这种整合也导致了冒险的战利品盒消费的广泛参与。为了理解驱动和维持这种不适应行为的机制，我们提出了FoMO驱动的战利品盒螺旋假说——假设对错过的恐惧（FoMO）不仅触发了冒险的战利品盒消费的最初参与，而且延续了一个自我强化的循环，这种参与加剧了随后的FoMO，导致进一步的冒险的战利品盒消费。方法与结果我们对252名大学生进行了为期13周的纵向研究，每周收集数据，以检验双向关系。使用随机截点交叉滞后面板模型，我们发现从FoMO到冒险战利品盒消费的显著小到中等的交叉滞后效应，以及从冒险战利品盒消费到FoMO的显著中到大的交叉滞后效应。我们的研究结果支持FoMO是启动冒险战利品箱消费的重要触发因素。此外，一旦玩家开始冒险消费战利品盒，他们通常会发现自己陷入FoMO和冒险消费战利品盒的强化循环中。这些发现有助于我们理解数字游戏中的问题行为，并有助于制定针对性的干预措施和政策，以减少冒险的战利品盒消费。

{"title":"Longitudinal bidirectional relation between fear of missing out and risky loot box consumption: Evidence for FoMO-Driven loot boxes spiral hypothesis","authors":"Andree Hartanto, K.T.A.Sandeeshwara Kasturiratna","doi":"10.1016/j.chbr.2024.100535","DOIUrl":"10.1016/j.chbr.2024.100535","url":null,"abstract":"<div><h3>Background</h3><div>The integration of loot boxes has emerged as a significant factor contributing to the increasing revenue in the video gaming industry. However, this integration has also led to widespread engagement in risky loot box consumption. To understand the mechanism that drives and sustains such maladaptive behavior, we propose the FoMO-Driven Loot Boxes Spiral Hypothesis – positing that fear of missing out (FoMO) not only triggers initial engagement in risky loot box consumption but also perpetuates a self-reinforcing cycle, where such engagement intensifies subsequent FoMO, leading to further risky loot box consumption.</div></div><div><h3>Method and results</h3><div>We conducted a 13-week longitudinal study of 252 college students with weekly data collection to examine the bidirectional relation. Using random-intercept cross-lagged panel models, we found significant small-to-moderate cross-lagged effects from FoMO to risky loot box consumption and significant moderate-to-large cross-lagged effects from risky loot box consumption to FoMO.</div></div><div><h3>Implications</h3><div>Our findings support FoMO as an important trigger for initiating risky loot box consumption. Moreover, once players start engaging with risky loot box consumption, they often find themselves trapped in a reinforcing cycle of FoMO and risky loot box consumption. These findings contributes to our understanding of problematic behavior in digital gaming and have implications for the development of targeted interventions and policies aimed at reducing risky loot box consumption.</div></div>","PeriodicalId":72681,"journal":{"name":"Computers in human behavior reports","volume":"16 ","pages":"Article 100535"},"PeriodicalIF":4.9,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142743198","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Gamification of motor imagery brain-computer interface training protocols: A systematic review

IF 4.9 Q1 PSYCHOLOGY, EXPERIMENTAL

Computers in human behavior reports

Pub Date : 2024-12-01 DOI: 10.1016/j.chbr.2024.100508

Fred Atilla , Marie Postma , Maryam Alimardani

Current Motor Imagery Brain-Computer Interfaces (MI-BCI) require a lengthy and monotonous training procedure to train both the system and the user. Considering many users struggle with effective control of MI-BCI systems, a more user-centered approach to training might help motivate users and facilitate learning, alleviating inefficiency of the BCI system. With the increase of BCI-controlled games, researchers have suggested using game principles for BCI training, as games are naturally centered on the player. This review identifies and evaluates the application of game design elements to MI-BCI training, a process known as gamification. Through a systematic literature search, we examined how MI-BCI training protocols have been gamified and how specific game elements impacted the training outcomes. We identified 86 studies that employed gamified MI-BCI protocols in the past decade. The prevalence and reported effects of individual game elements on user experience and performance were extracted and synthesized. Results reveal that MI-BCI training protocols are most often gamified by having users move an avatar in a virtual environment that provides visual feedback. Furthermore, in these virtual environments, users were provided with goals that guided their actions. Using gamification, the reviewed protocols allowed users to reach effective MI-BCI control, with studies reporting positive effects of four individual elements on user performance and experience, namely: feedback, avatars, assistance, and social interaction. Based on these elements, this review makes current and future recommendations for effective gamification, such as the use of virtual reality and adaptation of game difficulty to user skill level.

{"title":"Gamification of motor imagery brain-computer interface training protocols: A systematic review","authors":"Fred Atilla , Marie Postma , Maryam Alimardani","doi":"10.1016/j.chbr.2024.100508","DOIUrl":"10.1016/j.chbr.2024.100508","url":null,"abstract":"<div><div>Current Motor Imagery Brain-Computer Interfaces (MI-BCI) require a lengthy and monotonous training procedure to train both the system and the user. Considering many users struggle with effective control of MI-BCI systems, a more user-centered approach to training might help motivate users and facilitate learning, alleviating inefficiency of the BCI system. With the increase of BCI-controlled games, researchers have suggested using game principles for BCI training, as games are naturally centered on the player. This review identifies and evaluates the application of game design elements to MI-BCI training, a process known as gamification. Through a systematic literature search, we examined how MI-BCI training protocols have been gamified and how specific game elements impacted the training outcomes. We identified 86 studies that employed gamified MI-BCI protocols in the past decade. The prevalence and reported effects of individual game elements on user experience and performance were extracted and synthesized. Results reveal that MI-BCI training protocols are most often gamified by having users move an avatar in a virtual environment that provides visual feedback. Furthermore, in these virtual environments, users were provided with goals that guided their actions. Using gamification, the reviewed protocols allowed users to reach effective MI-BCI control, with studies reporting positive effects of four individual elements on user performance and experience, namely: feedback, avatars, assistance, and social interaction. Based on these elements, this review makes current and future recommendations for effective gamification, such as the use of virtual reality and adaptation of game difficulty to user skill level.</div></div>","PeriodicalId":72681,"journal":{"name":"Computers in human behavior reports","volume":"16 ","pages":"Article 100508"},"PeriodicalIF":4.9,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143166438","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

How whatsappization of the chatbot affects perceived ease of use, perceived usefulness, and attitude toward using in a drive-sharing task 聊天机器人的“whatsappization”如何影响人们对使用的感知易用性、感知有用性以及在驾驶共享任务中使用的态度

IF 4.9 Q1 PSYCHOLOGY, EXPERIMENTAL

Computers in human behavior reports

Pub Date : 2024-12-01 DOI: 10.1016/j.chbr.2024.100546

Nirit Yuviler-Gavish, Rotem Halutz, Liad Neta

With the advent of large language models, a spotlight has been turned onto chatbots. Utilizing the Technology Acceptance Model (TAM), we investigated whether whatsappization of the chatbot – making the conversation more resemble a WhatsApp conversation – improves Perceived Ease of Use, Perceived Usefulness, and Attitude Toward Using. In today's world, given that WhatsApp conversations sometimes substitute for face-to-face communication, borrowing this format for use in another framework was reasonable. Participants, assigned a drive-sharing task, communicated with a textual chatbot via WhatsApp and had to decide whether to take a lift to college with a driver suggested by the chatbot. Whatsappization of the chatbot was done in two ways: Through a dialog-style conversation (Dialog versus No Dialog), and by adding WhatsApp indicators – “Last Seen”, “Connected”, “Read Receipts”, and “Typing …” (Indicators versus No Indicators). The research was full factorial, with a 2 by 2 design. 120 participants were randomly assigned to one of the four groups, with 30 participants in each group. The results, using one-way ANOVAs, demonstrated that the interaction with the chatbot was longer under the Dialog compared to the No Dialog condition, and participants in the Dialog condition had a lower rating for Attitude Toward Using. In addition, both for the Perceived Ease of Use and Perceived Usefulness constructs, participants' ratings were lower under the Indicators compared to the No Indicators condition. Our findings signal that whatsappization of the chatbot decreased user's motivation to use the system. Hence, the current study suggests that a non-human agent should not try to imitate a WhatsApp conversation.

随着大型语言模型的出现，人们开始关注聊天机器人。利用技术接受模型（TAM），我们调查了聊天机器人的whatsappization（使对话更像WhatsApp对话）是否提高了感知易用性、感知有用性和使用态度。在当今世界，考虑到WhatsApp的对话有时会取代面对面的交流，借用这种格式在另一个框架中使用是合理的。参与者被分配了一项拼车任务，通过WhatsApp与文本聊天机器人交流，并必须决定是否与聊天机器人推荐的司机搭便车去大学。聊天机器人的WhatsApp化以两种方式完成：通过对话式的对话（对话与无对话），以及通过添加WhatsApp指标——“上次见”、“已连接”、“阅读收据”和“打字……”（指标与无指标）。该研究采用全因子设计，采用2 × 2设计。120名参与者被随机分配到四组中，每组30名参与者。使用单向方差分析的结果表明，与没有对话条件相比，对话条件下与聊天机器人的交互时间更长，并且对话条件下的参与者对使用态度的评分较低。此外，对于感知易用性和感知有用性构念，与无指标条件相比，参与者在指标条件下的评分较低。我们的研究结果表明，聊天机器人的应用降低了用户使用该系统的动机。因此，目前的研究表明，非人类代理不应该试图模仿WhatsApp的对话。

{"title":"How whatsappization of the chatbot affects perceived ease of use, perceived usefulness, and attitude toward using in a drive-sharing task","authors":"Nirit Yuviler-Gavish, Rotem Halutz, Liad Neta","doi":"10.1016/j.chbr.2024.100546","DOIUrl":"10.1016/j.chbr.2024.100546","url":null,"abstract":"<div><div>With the advent of large language models, a spotlight has been turned onto chatbots. Utilizing the Technology Acceptance Model (TAM), we investigated whether whatsappization of the chatbot – making the conversation more resemble a WhatsApp conversation – improves Perceived Ease of Use, Perceived Usefulness, and Attitude Toward Using. In today's world, given that WhatsApp conversations sometimes substitute for face-to-face communication, borrowing this format for use in another framework was reasonable. Participants, assigned a drive-sharing task, communicated with a textual chatbot via WhatsApp and had to decide whether to take a lift to college with a driver suggested by the chatbot. Whatsappization of the chatbot was done in two ways: Through a dialog-style conversation (Dialog versus No Dialog), and by adding WhatsApp indicators – “Last Seen”, “Connected”, “Read Receipts”, and “Typing …” (Indicators versus No Indicators). The research was full factorial, with a 2 by 2 design. 120 participants were randomly assigned to one of the four groups, with 30 participants in each group. The results, using one-way ANOVAs, demonstrated that the interaction with the chatbot was longer under the Dialog compared to the No Dialog condition, and participants in the Dialog condition had a lower rating for Attitude Toward Using. In addition, both for the Perceived Ease of Use and Perceived Usefulness constructs, participants' ratings were lower under the Indicators compared to the No Indicators condition. Our findings signal that whatsappization of the chatbot decreased user's motivation to use the system. Hence, the current study suggests that a non-human agent should not try to imitate a WhatsApp conversation.</div></div>","PeriodicalId":72681,"journal":{"name":"Computers in human behavior reports","volume":"16 ","pages":"Article 100546"},"PeriodicalIF":4.9,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142759666","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Friendship or feedback? – Relations between computer science students’ goals, technology acceptance, use of an online peer feedback tool, and learning 友谊还是反馈？-计算机科学专业学生的目标、技术接受度、在线同伴反馈工具的使用和学习之间的关系

IF 4.9 Q1 PSYCHOLOGY, EXPERIMENTAL

Computers in human behavior reports

Pub Date : 2024-12-01 DOI: 10.1016/j.chbr.2024.100540

Tuğçe Özbek , Martin Daumiller , Aida Roshany-Tabrizi , Tobias Mömke , Ingo Kollar

Computer-supported peer feedback offers great potential to enhance students' learning. Yet, students sometimes do not use computer-supported peer feedback opportunities, which partially can be the result of low technology acceptance. The UTAUT-model specifies performance expectancy, effort expectancy, and facilitating conditions as decisive factors for the intention to use a technology. From a motivational perspective, however, it can be expected that also students' achievement goals have an impact on the intention to use an online peer feedback tool. Therefore, we investigated the effects of learning approach, appearance approach, appearance avoidance, work avoidance and relational goals (besides performance expectancy, effort expectancy and facilitating conditions) on 155 computer science students' intentions and actual use of an online peer feedback tool and their performance in an end-of-course exam. Results of path modelling the longitudinal, student and log-data informed data showed that students' intentions predicted actual use, which predicted exam performance. Learning approach goals positively predicted the intention to use the tool, while performance and work avoidance goals did not predict intentions. Relational goals, however, negatively predicted intentions and end-of-course performance, shedding light on the importance of students' social motivations when using online peer feedback tools in their studies (e.g., peer feedback might be perceived as a social threat). Thus, the results point to the importance of an appropriate framing of online peer feedback tool use in educational settings as a learning opportunity and to reduce students’ possible concerns about their social relationships when using online peer feedback tools.

计算机支持的同伴反馈为提高学生的学习提供了巨大的潜力。然而，学生有时不使用计算机支持的同伴反馈机会，这在一定程度上可能是技术接受度低的结果。utaut模型将性能预期、工作预期和便利条件指定为使用技术意图的决定性因素。然而，从动机的角度来看，可以预期学生的成就目标也会对使用在线同伴反馈工具的意愿产生影响。因此，我们调查了学习方法、外观方法、外观回避、工作回避和关系目标（以及绩效期望、努力期望和便利条件）对155名计算机科学学生在线同伴反馈工具的意图和实际使用以及他们在期末考试中的表现的影响。纵向、学生和日志数据的路径建模结果表明，学生的意图预测了实际使用，从而预测了考试成绩。学习方法目标正向预测使用工具的意向，而绩效和工作回避目标对意向没有预测作用。然而，关系目标对意图和课程结束时的表现有负面预测，这揭示了学生在学习中使用在线同伴反馈工具时社会动机的重要性（例如，同伴反馈可能被视为一种社会威胁）。因此，研究结果指出了在教育环境中使用在线同伴反馈工具作为学习机会的适当框架的重要性，并减少了学生在使用在线同伴反馈工具时对其社会关系的可能担忧。

{"title":"Friendship or feedback? – Relations between computer science students’ goals, technology acceptance, use of an online peer feedback tool, and learning","authors":"Tuğçe Özbek , Martin Daumiller , Aida Roshany-Tabrizi , Tobias Mömke , Ingo Kollar","doi":"10.1016/j.chbr.2024.100540","DOIUrl":"10.1016/j.chbr.2024.100540","url":null,"abstract":"<div><div>Computer-supported peer feedback offers great potential to enhance students' learning. Yet, students sometimes do not use computer-supported peer feedback opportunities, which partially can be the result of low technology acceptance. The UTAUT-model specifies performance expectancy, effort expectancy, and facilitating conditions as decisive factors for the intention to use a technology. From a motivational perspective, however, it can be expected that also students' achievement goals have an impact on the intention to use an online peer feedback tool. Therefore, we investigated the effects of learning approach, appearance approach, appearance avoidance, work avoidance and relational goals (besides performance expectancy, effort expectancy and facilitating conditions) on 155 computer science students' intentions and actual use of an online peer feedback tool and their performance in an end-of-course exam. Results of path modelling the longitudinal, student and log-data informed data showed that students' intentions predicted actual use, which predicted exam performance. Learning approach goals positively predicted the intention to use the tool, while performance and work avoidance goals did not predict intentions. Relational goals, however, negatively predicted intentions and end-of-course performance, shedding light on the importance of students' social motivations when using online peer feedback tools in their studies (e.g., peer feedback might be perceived as a social threat). Thus, the results point to the importance of an appropriate framing of online peer feedback tool use in educational settings as a learning opportunity and to reduce students’ possible concerns about their social relationships when using online peer feedback tools.</div></div>","PeriodicalId":72681,"journal":{"name":"Computers in human behavior reports","volume":"16 ","pages":"Article 100540"},"PeriodicalIF":4.9,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142743308","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Decoding covert visual attention to motion direction using graph theory features of EEG signals and quadratic discriminant analysis

IF 4.9 Q1 PSYCHOLOGY, EXPERIMENTAL

Computers in human behavior reports

Pub Date : 2024-12-01 DOI: 10.1016/j.chbr.2024.100544

Zeinab Rezaei, Mohammad-Mahdi Mohammadi, Mohammad Reza Daliri

Visual attention is a type of selective attention that plays an important role in prioritizing and processing the information received from the visual scenes around us. The brain is an intricate network composed of numerous regions, each with distinct functions. As different tasks are performed, brain regions regularly synchronize and correlate with each other through intricate networks of connections. The aim of this study is to decode two states of attention by examining the interactions and connections between different brain regions using graph theory. This is demonstrated by EEG recordings from 15 participants who performed visual attention task. Pearson's correlation coefficient and coherence have been used to measure the functional connections between brain regions. In fact, each of these two criteria is regarded as an individual feature, and we perform decoding using each criterion separately. With an optimal selection of 40 connectivity features, the QDA classifier attained accuracies of 79.83% and 83.28% using correlation and coherence features, respectively. The results of attention decoding using the coherence criterion are more promising, indicating the superior effectiveness of coherence-based methods. Therefore, this study employed graph theory to analyse a neural network derived from coherence measurements. The study focused on three graph-theoretical metrics: degree centrality, efficiency, and betweenness centrality. The QDA classifier, using an optimal set of 40 features that includes degree, betweenness, and channel efficiency, achieved an accuracy of 86.46%. In comparison, the QDA classifier with 40 features based solely on degree centrality reached an accuracy of 89.96%. Finally, the results of this research indicate that analysing brain connections and brain network graphs can effectively decode different covert visual attention states.

{"title":"Decoding covert visual attention to motion direction using graph theory features of EEG signals and quadratic discriminant analysis","authors":"Zeinab Rezaei, Mohammad-Mahdi Mohammadi, Mohammad Reza Daliri","doi":"10.1016/j.chbr.2024.100544","DOIUrl":"10.1016/j.chbr.2024.100544","url":null,"abstract":"<div><div>Visual attention is a type of selective attention that plays an important role in prioritizing and processing the information received from the visual scenes around us. The brain is an intricate network composed of numerous regions, each with distinct functions. As different tasks are performed, brain regions regularly synchronize and correlate with each other through intricate networks of connections. The aim of this study is to decode two states of attention by examining the interactions and connections between different brain regions using graph theory. This is demonstrated by EEG recordings from 15 participants who performed visual attention task. Pearson's correlation coefficient and coherence have been used to measure the functional connections between brain regions. In fact, each of these two criteria is regarded as an individual feature, and we perform decoding using each criterion separately. With an optimal selection of 40 connectivity features, the QDA classifier attained accuracies of 79.83% and 83.28% using correlation and coherence features, respectively. The results of attention decoding using the coherence criterion are more promising, indicating the superior effectiveness of coherence-based methods. Therefore, this study employed graph theory to analyse a neural network derived from coherence measurements. The study focused on three graph-theoretical metrics: degree centrality, efficiency, and betweenness centrality. The QDA classifier, using an optimal set of 40 features that includes degree, betweenness, and channel efficiency, achieved an accuracy of 86.46%. In comparison, the QDA classifier with 40 features based solely on degree centrality reached an accuracy of 89.96%. Finally, the results of this research indicate that analysing brain connections and brain network graphs can effectively decode different covert visual attention states.</div></div>","PeriodicalId":72681,"journal":{"name":"Computers in human behavior reports","volume":"16 ","pages":"Article 100544"},"PeriodicalIF":4.9,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143166436","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The thrill of chance: Psychophysiological responses in loot boxes and simulated slot machines 机会的刺激：战利品箱和模拟老虎机中的心理生理反应

IF 4.9 Q1 PSYCHOLOGY, EXPERIMENTAL

Computers in human behavior reports

Pub Date : 2024-12-01 DOI: 10.1016/j.chbr.2024.100545

Francisco J. Sanmartín , Judith Velasco , Fátima Cuadrado , Juan A. Moriana

Loot boxes (LBs) are microtransactions within video games that offer players the opportunity to acquire virtual items randomly. LBs shared structural and psychological features with gambling, especially slot machines. However, one potential shared feature that has been scarcely explored in LBs, is the level of arousal experienced by players. This study explores changes in electrodermal activity (EDA), heart rate (HR) and respiratory rate (RR) during the opening of LBs in FIFA and during simulated slot machine spin in gamblers (n = 14, M = 19.93 years), LB users (n = 13, M = 19.62 years) and a control group (n = 13, M = 21.92 years). Additionally, the study aimed to compare psychophysiological activation levels produced by both dynamics in each group. Results indicated that both gamblers and LB users showed increased EDA during LB opening and slot machine spins, while HR or RR did not exhibit significant changes. The control group showed increased EDA during the slot machine spin, with no changes during LB opening or in other psychophysiological measures. The comparison between LB opening and slot machine spin revealed similar levels of psychophysiological activation for gamblers and LB users. These findings suggest a potential link between gambling and LBs, which could inform the development of policies for safer gaming environments.

战利品箱（LBs）是电子游戏中的微交易，让玩家有机会随机获得虚拟道具。LBs与赌博（尤其是老虎机）具有相同的结构和心理特征。然而，LBs有一个潜在的共同特征却很少被挖掘，那就是玩家体验到的兴奋程度。本研究探讨了《FIFA》中LB开业期间和模拟老角机旋转期间赌徒（n = 14, M = 19.93岁）、LB使用者（n = 13, M = 19.62岁）和对照组（n = 13, M = 21.92岁）的皮电活动（EDA）、心率（HR）和呼吸频率（RR）的变化。此外，该研究旨在比较两种动力在每组中产生的心理生理激活水平。结果表明，赌徒和LB使用者在LB打开和老虎机旋转时EDA增加，而HR或RR没有明显变化。对照组在老虎机旋转过程中显示EDA增加，而在LB打开或其他心理生理测量中没有变化。LB打开和老虎机旋转之间的比较表明，赌徒和LB使用者的心理生理激活水平相似。这些发现表明赌博和LBs之间存在潜在的联系，这可以为制定更安全的游戏环境政策提供信息。

{"title":"The thrill of chance: Psychophysiological responses in loot boxes and simulated slot machines","authors":"Francisco J. Sanmartín , Judith Velasco , Fátima Cuadrado , Juan A. Moriana","doi":"10.1016/j.chbr.2024.100545","DOIUrl":"10.1016/j.chbr.2024.100545","url":null,"abstract":"<div><div>Loot boxes (LBs) are microtransactions within video games that offer players the opportunity to acquire virtual items randomly. LBs shared structural and psychological features with gambling, especially slot machines. However, one potential shared feature that has been scarcely explored in LBs, is the level of arousal experienced by players. This study explores changes in electrodermal activity (EDA), heart rate (HR) and respiratory rate (RR) during the opening of LBs in FIFA and during simulated slot machine spin in gamblers (<em>n</em> = 14, <em>M</em> = 19.93 years), LB users (<em>n</em> = 13, <em>M</em> = 19.62 years) and a control group (<em>n</em> = 13, <em>M</em> = 21.92 years). Additionally, the study aimed to compare psychophysiological activation levels produced by both dynamics in each group. Results indicated that both gamblers and LB users showed increased EDA during LB opening and slot machine spins, while HR or RR did not exhibit significant changes. The control group showed increased EDA during the slot machine spin, with no changes during LB opening or in other psychophysiological measures. The comparison between LB opening and slot machine spin revealed similar levels of psychophysiological activation for gamblers and LB users. These findings suggest a potential link between gambling and LBs, which could inform the development of policies for safer gaming environments.</div></div>","PeriodicalId":72681,"journal":{"name":"Computers in human behavior reports","volume":"16 ","pages":"Article 100545"},"PeriodicalIF":4.9,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142743306","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The opportunities and challenges of using online social platforms after pregnancy loss: A systematic review of qualitative research

IF 4.9 Q1 PSYCHOLOGY, EXPERIMENTAL

Computers in human behavior reports

Pub Date : 2024-11-30 DOI: 10.1016/j.chbr.2024.100547

Stephanie Murphy , Doireann Peelo-Dennehy , Kellie Morrissey , John McCarthy , Sarah Foley

Online social platforms (e.g. social media, online forums) can serve as important sources of support for individuals that have experienced pregnancy loss. However, these platforms also pose potential risks to users (including online victimization and misinformation) which can limit their sense of safety online. This paper argues that interdisciplinary work can play a central role in supporting safer online experiences after pregnancy loss. To critically consider implications for future research in this context, we systematically reviewed existing qualitative research investigating online social platform experiences among this population. We present a thematic synthesis of the findings from 28 studies, in which we identify opportunities and challenges experienced by users after pregnancy loss, and techniques that they used to manage these challenges. We then propose a series of recommendations for how future researchers should further examine and address the issues identified in past literature in order to support safer online platform engagement among this population.

{"title":"The opportunities and challenges of using online social platforms after pregnancy loss: A systematic review of qualitative research","authors":"Stephanie Murphy , Doireann Peelo-Dennehy , Kellie Morrissey , John McCarthy , Sarah Foley","doi":"10.1016/j.chbr.2024.100547","DOIUrl":"10.1016/j.chbr.2024.100547","url":null,"abstract":"<div><div>Online social platforms (e.g. social media, online forums) can serve as important sources of support for individuals that have experienced pregnancy loss. However, these platforms also pose potential risks to users (including online victimization and misinformation) which can limit their sense of safety online. This paper argues that interdisciplinary work can play a central role in supporting safer online experiences after pregnancy loss. To critically consider implications for future research in this context, we systematically reviewed existing qualitative research investigating online social platform experiences among this population. We present a thematic synthesis of the findings from 28 studies, in which we identify opportunities and challenges experienced by users after pregnancy loss, and techniques that they used to manage these challenges. We then propose a series of recommendations for how future researchers should further examine and address the issues identified in past literature in order to support safer online platform engagement among this population.</div></div>","PeriodicalId":72681,"journal":{"name":"Computers in human behavior reports","volume":"17 ","pages":"Article 100547"},"PeriodicalIF":4.9,"publicationDate":"2024-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143147684","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0