Internet and Higher Education最新文献_第3页

The GenAI divide among university students: A call for action 大学生的基因分化：行动呼吁

IF 6.4 1区教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH

Internet and Higher Education

Pub Date : 2025-10-01 Epub Date: 2025-07-09 DOI: 10.1016/j.iheduc.2025.101036

Karley Beckman , Tiffani Apps , Sarah Katherine Howard , Claire Rogerson , Ann Rogerson , Jo Tondeur

The rapid pace of technological change with generative artificial intelligence is accelerating much faster than our capacity to understand and regulate it. Higher education institutions have been firmly focused on the impacts of this innovation on academic integrity while grappling with unknown longer-term impacts on students' academic study and future work. This mixed method study aims to capture student perspectives on their self-reported understanding of GenAI and intentions to use GenAI for their academic study during the critical diffusion stage and policy vacuum. Through a survey with 194 university students, the study explored student's understanding, knowledge, experience and intended use of GenAI tools to support their academic study. The paper presents three distinct student profiles established through cluster analysis of measures of digital and AI literacy, which are then explored in-depth through presentation of qualitative items. Notably, the cluster profiles demonstrate variation across the profiles of novice, cautious and enthusiastic users and patterns related to their knowledge of ChatGPT and intended uses. The paper draws on digital divide empirical literature and explores the potential to repeat digital divides among groups of students based on their access, capabilities, and capacity to leverage these for educational advantage. We propose that building upon a vast existing body of educational research about digital literacy inequalities offers rich insights into the current problems facing education institutions, specifically, what role do universities play in supporting students to understand and harness GenAI, now and in their futures.

人工智能的技术变革速度之快，远远超过了我们理解和管理它的能力。高等教育机构一直坚定地关注这一创新对学术诚信的影响，同时努力应对对学生学术学习和未来工作的未知长期影响。这项混合方法研究旨在捕捉学生的观点，了解他们自我报告的对GenAI的理解，以及在关键扩散阶段和政策真空期间使用GenAI进行学术研究的意图。通过对194名大学生的调查，该研究探讨了学生对GenAI工具的理解、知识、经验和预期使用情况，以支持他们的学术研究。本文通过对数字和人工智能素养措施的聚类分析，提出了三种不同的学生概况，然后通过介绍定性项目对其进行深入探讨。值得注意的是，集群概要文件展示了新手、谨慎用户和热心用户的概要文件之间的差异，以及与他们的ChatGPT知识和预期用途相关的模式。本文借鉴了数字鸿沟实证文献，并根据学生群体的访问、能力和利用这些资源获得教育优势的能力，探讨了在学生群体中重复数字鸿沟的可能性。我们建议，在现有大量关于数字扫盲不平等的教育研究基础上，为教育机构当前面临的问题提供丰富的见解，特别是大学在支持学生理解和利用GenAI方面发挥的作用，无论是现在还是未来。

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引用次数: 0

Promoting inclusive practices with emerging technologies in higher education: Faculty professional development through blended-learning 在高等教育中促进新兴技术的包容性实践：通过混合学习促进教师专业发展

IF 6.4 1区教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH

Internet and Higher Education

Pub Date : 2025-10-01 Epub Date: 2025-05-31 DOI: 10.1016/j.iheduc.2025.101019

Anabel Moriña, Víctor H. Perera

University institutions face the challenge of training faculty in inclusive digital skills to provide quality education for all. This paper presents a study that designed, developed, and evaluated a blended-learning training programme for faculty in Spain, focusing on emerging technologies from an inclusive perspective. A qualitative methodology was employed, incorporating a case study approach with semi-structured interviews conducted with faculty and focus groups with students. The study encompassed a diagnostic evaluation of faculty training needs and an evaluation of the programme's implementation, outcomes and impact. The results revealed that inclusive practices with technologies benefit the faculty and students involved and provide a replicable model for other universities. This study underlines the importance of online training in professional development, as it allows for essential learning opportunities in today's educational context.

大学机构面临着培训教师包容性数字技能的挑战，以便为所有人提供优质教育。本文介绍了一项研究，该研究为西班牙教师设计、开发和评估了一个混合式学习培训计划，从包容性的角度关注新兴技术。采用定性方法，结合案例研究方法，与教师进行半结构化访谈，与学生进行焦点小组访谈。这项研究包括对教员培训需求的诊断性评价和对方案的执行、结果和影响的评价。结果表明，技术的包容性实践使参与其中的教师和学生受益，并为其他大学提供了可复制的模式。这项研究强调了在线培训在职业发展中的重要性，因为它在当今的教育环境中提供了必要的学习机会。

引用次数: 0

Enhancing online college students' self-regulated learning and performance through self-assessments and commitment strategies 通过自我评估和承诺策略提高网络大学生的自主学习和绩效

IF 6.4 1区教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH

Internet and Higher Education

Pub Date : 2025-10-01 Epub Date: 2025-06-18 DOI: 10.1016/j.iheduc.2025.101033

Kun Huang , Anita Lee-Post

This study examines the impact of a combined self-assessment and commitment strategy intervention on college students' self-regulated learning (SRL) and academic performance in asynchronous online learning. Using an ex post facto control design, we compared students' performance and behavioral analytics across three course units in two consecutive years of a large online college course. Compared to the control group, the treatment group demonstrated sustained improvement in both course performance and learning behaviors. Our findings highlight the potential of integrating self-assessment and commitment strategies to enhance SRL and academic outcomes in online education. This research advances the understanding of sustained SRL interventions and offers practical insights for online educators seeking to improve student engagement and performance.

本研究考察了自我评估与承诺策略相结合的干预对大学生异步在线学习中自我调节学习和学业成绩的影响。使用事后控制设计，我们比较了学生在连续两年的大型在线大学课程中三个课程单元的表现和行为分析。与对照组相比，治疗组在课程表现和学习行为方面均表现出持续的改善。我们的研究结果强调了整合自我评估和承诺策略以提高在线教育中SRL和学术成果的潜力。这项研究促进了对持续SRL干预的理解，并为寻求提高学生参与度和表现的在线教育者提供了实用的见解。

引用次数: 0

Changes in online engagement at the within-person level, profiles, dynamics and association with achievement 在线参与在个人层面的变化，概况，动态和与成就的联系

IF 6.4 1区教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH

Internet and Higher Education

Pub Date : 2025-10-01 Epub Date: 2025-06-15 DOI: 10.1016/j.iheduc.2025.101031

Mohammed Saqr, Sonsoles López-Pernas

While the dominant population-based research is immensely useful in revealing the general trends, it falls short of capturing the intraindividual –or within-person – changes on the individual level. Capturing the individualized processes helps create personalized interventions and advance our understanding of the person in which the learning process takes place. This study aimed at modeling the within-person profiles of change in engagement and charting their temporal unfolding and transitions of 307 students, spanning 12 courses —3684 course enrollments in total—, across three years of education. We use a combination of mixture models, sequence and transition analysis, as well as multilevel repeated measures ANOVA to capture such changes, their longitudinal unfolding and how they relate to performance. Our results revealed three within-person profiles of change (up, down, and average). These profiles were plotted, their sequential unfolding was studied by sequence analysis and then we clustered the longitudinal trajectories of these profiles resulting in three distinct trajectories: an ascending, a descending, and a stable trajectory. We found that the baseline average profile represented an attractor state that was indicative of resilience, stability, and high achievement and students who did below their own average were at risk if they did not catch up. Therefore, our results suggest that tracking the within-person changes in engagement at the individual level opens the door for individualized tracking and intervention that require no constraints of samples or averaging across aggregate data

虽然以人口为基础的主流研究在揭示总体趋势方面非常有用，但它无法捕捉到个人层面上的个人内部或个人内部的变化。捕捉个性化的过程有助于创建个性化的干预措施，并促进我们对学习过程发生的人的理解。本研究旨在对307名学生的参与度变化的个人概况进行建模，并绘制其时间展开和转变的图表，涵盖12门课程-总共3684门课程-在三年的教育中。我们结合使用混合模型、序列和过渡分析，以及多水平重复测量方差分析来捕捉这些变化、它们的纵向展开以及它们与绩效的关系。我们的结果揭示了三种个人内部的变化概况（上升、下降和平均）。绘制了这些剖面，通过序列分析研究了它们的顺序展开，然后对这些剖面的纵向轨迹进行聚类，得到了三个不同的轨迹：上升、下降和稳定轨迹。我们发现，基线平均概况代表了一种吸引人的状态，它表明了韧性、稳定性和高成就，而那些成绩低于自己平均水平的学生，如果他们没有赶上来，就有风险。因此，我们的研究结果表明，在个人层面上跟踪参与的个人内部变化为个性化跟踪和干预打开了大门，不需要样本约束或对总数据进行平均

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引用次数: 0

The generation mechanism of teachers' anxiety toward digital human instructors in higher education: A mixed-methods perspective 高等教育中教师对数字化人类讲师焦虑的产生机制：混合方法视角

IF 6.8 1区教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH

Internet and Higher Education

Pub Date : 2025-10-01 Epub Date: 2025-07-31 DOI: 10.1016/j.iheduc.2025.101041

Hao Dong , Yanxun Zhu , Jianglong Shen , Shengze Xue

Digital Human Instructors (DHIs) are revolutionizing higher education by providing personalized and interactive learning experiences. However, the adoption of DHIs also brings about complex challenges related to teacher anxiety, particularly concerning professional security, ethics, and the broader implications of technology in education. Addressing the barriers to DHI adoption is crucial for safeguarding both educational quality and teacher well-being. This study aims to investigate these barriers by developing a theoretical model that integrates elements from Social Ecological Systems Theory, considering both micro-level individual factors (such as neuroticism and personal innovativeness) and meso-level social factors (such as negative word-of-mouth). Data were collected from 500 university teachers and analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) and fuzzy-set Qualitative Comparative Analysis (fsQCA). The PLS-SEM results revealed that neuroticism and negative word-of-mouth (WOM) have a significant positive impact on technology anxiety, while personal innovativeness has no significant direct effect. Moreover, perceived invasiveness plays a key mediating role in the relationships between neuroticism and technology anxiety, as well as between negative WOM and technology anxiety, whereas perceived authenticity does not exhibit a significant mediating effect. The fsQCA findings further revealed that technology anxiety does not stem from a single causal pathway. Instead, four configurations that include the presence and absence of certain conditions can lead to this desirable outcome. These findings not only contribute to the academic discourse on DHI adoption but also provide practical insights for educational managers seeking to mitigate teacher anxiety and enhance user protection in this dynamic educational environment.

数字人类讲师（DHIs）通过提供个性化和互动的学习体验，正在彻底改变高等教育。然而，DHIs的采用也带来了与教师焦虑相关的复杂挑战，特别是在职业安全、道德和技术在教育中的更广泛影响方面。消除采用个人健康指数的障碍对于保障教育质量和教师福祉至关重要。本研究旨在整合社会生态系统理论的要素，结合微观层面的个体因素（如神经质和个人创新）和中观层面的社会因素（如负面的口碑），建立一个理论模型来研究这些障碍。采用偏最小二乘结构方程模型（PLS-SEM）和模糊集定性比较分析法（fsQCA）对500名高校教师的数据进行分析。PLS-SEM结果显示，神经质和负面口碑对技术焦虑有显著的正向影响，而个人创新对技术焦虑没有显著的直接影响。此外，感知侵入性在神经质与技术焦虑、负向WOM与技术焦虑之间的关系中起关键中介作用，而感知真实性在技术焦虑与负向WOM之间的中介作用不显著。fsQCA的研究结果进一步表明，技术焦虑并非源于单一的因果途径。相反，包括存在和不存在某些条件的四种配置可以导致这种理想的结果。这些发现不仅有助于DHI采用的学术论述，而且为教育管理者在这个动态的教育环境中寻求减轻教师焦虑和加强用户保护提供了实践见解。

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引用次数: 0

The affordances of Artificial Intelligence (AI) and ethical considerations across the instruction cycle: A systematic review of AI in online higher education 人工智能（AI）的功能和整个教学周期的伦理考虑：在线高等教育中人工智能的系统回顾

IF 6.4 1区教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH

Internet and Higher Education

Pub Date : 2025-10-01 Epub Date: 2025-07-19 DOI: 10.1016/j.iheduc.2025.101039

Min Zhuang , Siyu Long, Florence Martin, Daniela Castellanos-Reyes

As Artificial Intelligence (AI) advances, discussions regarding its potential in education have attracted significant attention. This systematic review synthesizes AI affordances in online higher education, particularly identifying various ways AI is used throughout the online instruction cycle. We analyzed fifty-five studies focusing on publication trends, research methodology and quality, AI affordances during the design, facilitation, assessment and evaluation stages, and ethical considerations in this context. The findings revealed the applications of AI-empowered systems and Machine Learning (ML) models in various tasks such as establishing learning objectives in design, supporting cognition in facilitation, automatic grading in assessment, and measuring instruction quality in evaluation. We also discussed the trends regarding the limited incorporation of theoretical frameworks, a dominance of quantitative methods, a focus of big data, and a tendency towards personalization and adaptation. The ethical considerations were categorized for each research phase - data collection, analysis, and interpretation and usage, with an emphasis on validation approaches for AI generated outputs. These findings have implications on effectively integrating AI technologies by highlighting possibilities and competencies required for practitioners and inferring potential opportunities for researchers.

随着人工智能（AI）的发展，有关其在教育领域潜力的讨论引起了人们的极大关注。这篇系统综述综合了人工智能在在线高等教育中的应用，特别是确定了人工智能在整个在线教学周期中使用的各种方式。我们分析了55项研究，重点关注出版趋势、研究方法和质量、人工智能在设计、促进、评估和评估阶段的启示，以及在此背景下的伦理考虑。研究结果揭示了人工智能系统和机器学习（ML）模型在各种任务中的应用，例如在设计中建立学习目标，在促进中支持认知，在评估中自动评分，以及在评估中衡量教学质量。我们还讨论了理论框架的有限结合、定量方法的主导地位、大数据的关注以及个性化和适应的趋势。对每个研究阶段的伦理考虑进行了分类-数据收集，分析，解释和使用，重点是人工智能生成输出的验证方法。这些发现通过突出从业者所需的可能性和能力以及推断研究人员的潜在机会，对有效整合人工智能技术具有重要意义。

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引用次数: 0

Maximizing effectiveness of AI-generated instructors through human-like behavior and dynamic visual cues in instructional videos: Evidence from an eye-tracking study 通过教学视频中的类人行为和动态视觉线索最大化人工智能生成教师的有效性：来自眼动追踪研究的证据

IF 6.4 1区教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH

Internet and Higher Education

Pub Date : 2025-10-01 Epub Date: 2025-07-01 DOI: 10.1016/j.iheduc.2025.101034

Tao Xu , Qian Chen , Zhiwei Zhang , Bingyu Dong , Hui Zhang , Jie Bai , Yun Zhou

The rapid advancement of Artificial Intelligence Generated Content (AIGC) has revolutionized the production of instructional videos and lectures in MOOCs, opening a new chapter in their use for education. This technology enables the generation of talking instructors from text and images or clips of real people. However, the impact of behavioral fidelity and visual cues provided by these generated instructors on learning outcomes in instructional videos remains unknown. This study addresses this gap by employing a 2 × 2 within-subjects design (behavioral fidelity: high/low; visual cues: with/without) with 36 college student participants. We assessed learning performance, social presence, satisfaction, cognitive load, humanness, and motivation, and analyzed eye movements. Results revealed that high behavioral fidelity increased social presence and more effectively engages students, leading to better transfer performance. Visual cues were found to facilitate the organization and integration of information. The generated instructors were most effective when resembling human behavior and using dynamic visual cues. However, further refinement is needed for the voice and gestures of these instructors. The findings extend the social agency theory related to animated and human instructors to the context of AI-generated instructors. We recommend using instructors with high behavioral fidelity in instructional videos, featuring realistic beat gestures, body movements, facial expressions, and eye contact. Our study offers valuable insights into the implications of using AIGC in educational settings.

人工智能生成内容（AIGC）的快速发展彻底改变了mooc教学视频和讲座的制作，开启了将其用于教育的新篇章。这项技术可以从文本、图像或真人剪辑中生成会说话的讲师。然而，这些生成的教师提供的行为保真度和视觉线索对教学视频中学习结果的影响尚不清楚。本研究通过采用2x2受试者内设计(行为保真度：高/低；视觉线索：有/没有)36名大学生参与者。我们评估了学习表现、社会存在、满意度、认知负荷、人性和动机，并分析了眼球运动。结果表明，高行为保真度增加了社会存在感，更有效地吸引学生，从而导致更好的迁移绩效。研究发现，视觉线索有助于信息的组织和整合。生成的指导员在模仿人类行为并使用动态视觉线索时最有效。然而，这些教练的声音和手势还需要进一步完善。研究结果将与动画教师和真人教师相关的社会代理理论扩展到人工智能生成教师的背景下。我们建议在教学视频中使用具有高行为保真度的讲师，具有逼真的节拍手势，身体动作，面部表情和眼神交流。我们的研究为在教育环境中使用AIGC的含义提供了有价值的见解。

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引用次数: 0

The interplay among digital distraction, self-regulation of learning tendencies, and motivational influences: A transnational investigation 数字分心、学习倾向自我调节和动机影响之间的相互作用：一项跨国调查

IF 6.4 1区教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH

Internet and Higher Education

Pub Date : 2025-10-01 Epub Date: 2025-05-30 DOI: 10.1016/j.iheduc.2025.101023

Abraham E. Flanigan , Anna C. Brady , Mete Akcaoglu , Yan Dai , Sungjun Won , Bridget K. Daleiden , Kendall Hartley

College students' misuse of mobile devices during class for off-task purposes is a global issue that harms learning. While prior studies examined device misuse frequency within individual countries, no known studies have directly compared transnational differences in this behavior, leaving little known about whether crosscultural differences influence this behavior. This study investigates whether the country where students attend college (United States, South Korea, or Turkey) moderates the relationships among self-regulation of learning (SRL) tendencies, motivational factors (basic psychological needs satisfaction and utility value perceptions), and device misuse. Hierarchical moderated regression analyses revealed consistent patterns across cultures: SRL tendencies had little impact on device misuse, whereas basic needs satisfaction and utility value perceptions served as protective factors. Findings suggest that digital distraction in college classrooms transcends cultural influences that commonly lead to differences in student behavior, emphasizing the need for globally relevant strategies to reduce distractions and enhance student motivation. These results also challenge traditional assumptions that self-regulated learners are less susceptible to digital distraction. Even the more self-regulated participants in the present study regularly misused their devices during class. Such findings indicate that the performance phase of SRL that unfolds during class is riddled with disruptions and device misuse, even for the more self-regulated college students. Findings highlight the importance of fostering motivationally supportive learning environments to curb digital distraction and nourish student engagement.

大学生在课堂上滥用移动设备是一个危害学习的全球性问题。虽然先前的研究调查了单个国家的设备滥用频率，但没有已知的研究直接比较了这种行为的跨国差异，因此对于跨文化差异是否影响这种行为知之甚少。摘要本研究旨在探讨美国、南韩、土耳其等国家是否会调节学习自我调节（SRL）倾向、动机因素（基本心理需求满足与效用价值感知）与设备滥用之间的关系。层次调节回归分析揭示了跨文化的一致模式：SRL倾向对设备滥用的影响很小，而基本需求满足和效用价值感知是保护因素。研究结果表明，大学课堂上的数字干扰超越了通常导致学生行为差异的文化影响，强调需要全球相关策略来减少干扰并增强学生的动机。这些结果也挑战了传统的假设，即自我调节的学习者不太容易受到数字分心的影响。在本研究中，即使是那些更自律的参与者也经常在课堂上滥用电子设备。这些发现表明，在课堂上展开的SRL表现阶段充满了中断和设备滥用，即使对更自律的大学生来说也是如此。研究结果强调了培养激励支持性学习环境的重要性，以遏制数字干扰和培养学生的参与度。

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引用次数: 0

Evaluating the impact of online course development and teaching certificate academy on university faculty teaching practices through student learning experiences and faculty perceptions 通过学生的学习经验和教师的看法来评估在线课程开发和教学证书学院对大学教师教学实践的影响

IF 6.4 1区教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH

Internet and Higher Education

Pub Date : 2025-10-01 Epub Date: 2025-06-02 DOI: 10.1016/j.iheduc.2025.101020

Nedim Slijepcevic, Wanju Huang

This study evaluates the effectiveness of a faculty professional development (PD) course titled – Online Course Development and Teaching Certificate Academy (OTA), which focuses on the technology, pedagogy, and instructional design concepts essential for transitioning to online classrooms. OTA follows the Community of Inquiry principles by integrating social, teaching, and cognitive presences throughout its design and delivery. We evaluated the impact of OTA on faculty online teaching readiness in two phases. Phase 1 used qualitative analysis of the OTA faculty reflections. Phase 2 employed quantitative analysis of student course evaluations from 23 course graduates who taught the same online class before and after completing OTA. Phase 1 findings suggest that faculty reacted positively to PD, gained student perspective and instructional design skills, and experienced immediate personal, online, and face-to-face course transformation. Phase 2 findings reveal statistically significant improvements in course design and no statistically significant improvements in instruction and instructor engagement.

本研究评估了一门名为在线课程开发和教学证书学院（OTA）的教师专业发展（PD）课程的有效性，该课程侧重于向在线课堂过渡所必需的技术、教学法和教学设计概念。在线旅行社遵循探究社区原则，在整个设计和交付过程中整合社会、教学和认知存在。我们分两个阶段评估了在线旅行社对教师在线教学准备的影响。第一阶段对OTA教师反思进行了定性分析。第二阶段对完成OTA前后讲授同一在线课程的23名课程毕业生的学生课程评价进行了定量分析。第一阶段的研究结果表明，教师对PD做出了积极的反应，获得了学生的视角和教学设计技能，并经历了即时的个人、在线和面对面课程转变。第二阶段的调查结果显示，在课程设计方面有统计学上的显著改善，而在教学和教师参与方面没有统计学上的显著改善。

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引用次数: 0

Empowering international PhD students: Generative AI, Ubuntu, and the decolonisation of academic communication 授权国际博士生：生成人工智能，Ubuntu和学术交流的非殖民化

IF 6.8 1区教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH

Internet and Higher Education

Pub Date : 2025-10-01 Epub Date: 2025-07-18 DOI: 10.1016/j.iheduc.2025.101038

Lynette Pretorius , Huy-Hoang Huynh , Anak Agung Ayu Redi Pudyanti , Ziqi Li , Abdul Qawi Noori , Zhiheng Zhou

Generative AI (GenAI) provides distinct affordances that contribute meaningfully to learning. However, there are also several challenges, most notably ethical considerations. While much of the current research on GenAI in academia focuses on technical capabilities or ethical concerns, few studies have examined how GenAI can be leveraged to promote equity and inclusivity, particularly in academic communication. In this study, we adopt the theoretical lens of Ubuntu, a Southern African philosophy that emphasises interconnectedness and community, to reconceptualise GenAI as a democratising force. Five international PhD students in Education and their PhD supervisor (all multilingual users of English) explored their experiences of using GenAI. We used a collaborative autoethnographic approach, incorporating reflective prompting, individual writing, group sharing and refining, and group-based writing. We demonstrate that GenAI reshaped power dynamics and challenged academic hierarchies by providing real-time language support and improving academic writing clarity. This empowered us to participate in academic discourse, disrupting traditional gatekeeping mechanisms. By automating routine tasks, GenAI also shifted our academic focus from technical skills to intellectual contributions, fostering inclusivity and equity. This study highlights the potential of GenAI in terms of knowledge creation and academic discourse, particularly for doctoral scholars navigating linguistic and cultural barriers. Academia is predominantly Anglophone-centric, marginalising non-English-speaking scholars by imposing additional barriers to participation and recognition, perpetuating inequities in knowledge creation and dissemination. We argue that embracing GenAI can help to decolonise these academic practices, thereby promoting epistemic justice and creating a more equitable scholarly environment for all.

生成式人工智能（GenAI）提供了对学习有意义的独特启示。然而，也有一些挑战，最明显的是道德方面的考虑。虽然目前学术界对基因人工智能的研究大多集中在技术能力或伦理问题上，但很少有研究探讨如何利用基因人工智能促进公平和包容性，特别是在学术交流中。在这项研究中，我们采用了乌班图的理论视角，这是一种强调相互联系和社区的南部非洲哲学，将GenAI重新定义为一种民主化力量。5名来自教育部的国际博士生和他们的博士生导师（都是多语种的英语使用者）探讨了他们使用GenAI的经验。我们采用了一种协作式的自我民族志方法，结合了反思提示、个人写作、群体分享和提炼以及基于群体的写作。我们证明，GenAI通过提供实时语言支持和提高学术写作清晰度，重塑了权力动态，挑战了学术等级。这使我们能够参与学术讨论，打破传统的把关机制。通过自动化日常任务，GenAI还将我们的学术重点从技术技能转移到智力贡献上，促进了包容性和公平性。这项研究强调了GenAI在知识创造和学术话语方面的潜力，特别是对于克服语言和文化障碍的博士学者。学术界主要以英语为中心，通过对参与和认可施加额外的障碍，使非英语学者边缘化，使知识创造和传播方面的不平等永续存在。我们认为，接受GenAI可以帮助这些学术实践去殖民化，从而促进认知正义，并为所有人创造一个更公平的学术环境。

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引用次数: 0