Internet and Higher Education最新文献_第6页

Effects of GenAI-empowered interactive support on university EFL students' self-regulated strategy use and engagement in reading genai授权互动支持对大学英语学生自主策略使用和阅读投入的影响

IF 6.4 1区教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH

Internet and Higher Education

Pub Date : 2024-12-19 DOI: 10.1016/j.iheduc.2024.100991

Mengru Pan , Chun Lai , Kai Guo

Reading poses challenges for learners of English as a foreign language (EFL), as it requires strategic engagement with the text through an interactive meaning-making process. Self-regulated learning (SRL) training, which helps learners develop the ability to make strategic efforts to manage their reading process and maintain engagement in reading, has been increasingly used to assist EFL learners. However, one limitation of existing SRL training is the lack of interactive personalised support tailored to the specific needs of individual students. Recent developments in generative artificial intelligence (GenAI) may help address this limitation. This study explores how interactive personalised SRL support via a GenAI chatbot might affect university EFL learners' self-regulated strategy use and engagement in reading. Sixty-one Chinese EFL students from two classes at a university received a 45-min training session on SRL in reading and then engaged in a 12-week self-directed reading using an online reading platform embedded with SRL support. One class (the experimental group, N = 31) had access to the chatbot on the platform to support their self-regulated reading, while the other class (the control group, N = 30) received no chatbot assistance on the platform. Self-regulated reading strategy use and reading engagement were assessed through pre- and post-questionnaires, log data on the platform, and semi-structured interviews. It was found that the intervention significantly improved students' self-regulated reading strategy use and reading engagement, indicating the positive effect of GenAI-enabled interactive personalised SRL support. This study substantiates the value of interactive SRL support in the context of EFL reading.

阅读对作为外语的英语学习者提出了挑战，因为它需要通过互动的意义形成过程与文本进行战略性接触。自我调节学习（SRL）训练帮助学习者发展策略性努力管理阅读过程和保持阅读参与的能力，已越来越多地用于帮助英语学习者。然而，现有的SRL培训的一个限制是缺乏针对个别学生的具体需要量身定制的互动式个性化支持。生成式人工智能（GenAI）的最新发展可能有助于解决这一限制。本研究探讨了通过GenAI聊天机器人提供的交互式个性化SRL支持如何影响大学英语学习者在阅读中自我调节策略的使用和参与。61名来自某大学两个班的中国学生接受了45分钟的SRL阅读训练，然后使用嵌入SRL支持的在线阅读平台进行了为期12周的自主阅读。一个班级（实验组，N = 31）可以使用平台上的聊天机器人来支持他们的自我调节阅读，而另一个班级（对照组，N = 30）没有在平台上获得聊天机器人的帮助。通过问卷前和问卷后、平台上的日志数据和半结构化访谈来评估自我调节阅读策略的使用和阅读参与度。研究发现，干预显著提高了学生的自我调节阅读策略使用和阅读参与，表明基于genai的交互式个性化SRL支持具有积极作用。本研究证实了互动式母语阅读支持在英语阅读中的价值。

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引用次数: 0

Teaching via LLM-enhanced simulations: Authenticity and barriers to suspension of disbelief 通过法学硕士增强模拟教学：真实性和暂停怀疑的障碍

IF 6.4 1区教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH

Internet and Higher Education

Pub Date : 2024-12-10 DOI: 10.1016/j.iheduc.2024.100990

Longwei Zheng , Fei Jiang , Xiaoqing Gu , Yuanyuan Li , Gong Wang , Haomin Zhang

As an innovative method in professional training, simulation-based learning (SBL) has been introduced into teacher education, providing pre-service teacher candidates with experiential learning opportunities. This study explores the efficacy of SBL using large language models (LLMs) to enhance teacher training, focusing on learners' suspension of disbelief (SoD). As a highly advanced form of generative artificial intelligence, LLMs possess robust capabilities in simulating human behavior, which can be harnessed to create simulated students for SBL in teacher training. This instrumental case study examines the experiences of 12 pre-service teachers who participated in a session featuring an LLM-enhanced simulation. The simulation facilitated naturalistic classroom interactions between the participants and simulated students. Our research aimed to understand how pre-service teachers perceive LLM-enhanced SBL, identify factors that influence SoD, and determine the authenticity barriers. Interview data were analyzed using various coding techniques and derived themes from these codes. The findings revealed that LLM-enhanced SBL provided a realistic and engaging environment, significantly benefiting teaching skill development and learning transfer. However, challenges such as lagging responses, weak comprehension of complex contexts, inconsistencies in simulated students' cognition, and incongruent feedback were noted. The primary contribution of this study lies in demonstrating the potential of using LLMs to replace human actors, though significant technical challenges remain. The study also indicates that enhancements in LLM fine-tuning and prompt engineering are needed to improve LLMs' understanding of classroom context and students' cognitive patterns.

本研究利用大型语言模型（large language models, LLMs）来探讨SBL对教师培训的效果，重点关注学习者的暂停怀疑（SoD）。作为一种高度先进的生成式人工智能，法学硕士具有强大的模拟人类行为的能力，可以在教师培训中为SBL创建模拟学生。本工具性案例研究考察了12名职前教师的经历，他们参加了一个以llm增强模拟为特色的会议。模拟促进了参与者与模拟学生之间的自然课堂互动。本研究旨在了解职前教师如何感知llm增强的SBL，识别影响SoD的因素，并确定真实性障碍。使用各种编码技术对访谈数据进行分析，并从这些编码中得出主题。研究结果表明，llm强化的SBL提供了一个真实的、引人入胜的环境，显著有利于教学技能的发展和学习迁移。然而，我们也注意到一些挑战，如反应滞后、对复杂情境的理解不强、模拟学生的认知不一致以及反馈不一致。本研究的主要贡献在于展示了使用法学硕士替代人类参与者的潜力，尽管仍存在重大的技术挑战。该研究还表明，法学硕士需要加强微调和提示工程，以提高法学硕士对课堂情境和学生认知模式的理解。

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引用次数: 0

Information flow solipsism in canvas: An exploration of student privacy awareness 画布上的信息流唯我论：学生隐私意识的探索

IF 6.4 1区教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH

Internet and Higher Education

Pub Date : 2024-11-29 DOI: 10.1016/j.iheduc.2024.100989

Meghan L. Dowell, Spencer P. Greenhalgh

The proliferation of learning analytics (LA) in higher education has relied on data from learning management systems (LMS) like Canvas and Blackboard. Despite widespread LMS usage, students often lack clarity on what specific data is collected and who has access to it. This study explores undergraduate students' understanding of data collection practices within the Canvas LMS. We analyzed survey responses of nearly 600 students, examining students' awareness of the various roles within Canvas and their corresponding data permissions. The results reveal that students exhibit a general awareness of data collection practices but are unsure about the extent of their data's use and misinterpret the use of data analytics, highlighting a a greater need for critical data education in universities and other educational contexts. These findings suggest a critical need for universities to enhance transparency and educate students on data privacy and LMS functionalities.

学习分析（LA）在高等教育中的普及依赖于来自Canvas和Blackboard等学习管理系统（LMS）的数据。尽管LMS被广泛使用，但学生们往往不清楚所收集的具体数据是什么，以及谁可以访问这些数据。本研究探讨了本科生对Canvas LMS中数据收集实践的理解。我们分析了近600名学生的调查反馈，检查了学生对Canvas中各种角色的认识以及相应的数据权限。结果显示，学生对数据收集实践表现出普遍的认识，但不确定他们的数据使用的程度，并误解了数据分析的使用，这突出了在大学和其他教育环境中对关键数据教育的更大需求。这些发现表明，大学迫切需要提高透明度，并对学生进行数据隐私和LMS功能方面的教育。

引用次数: 0

Scaling up online professional development through institution-initiated blended learning programs in higher education 通过高等教育机构发起的混合学习项目，扩大在线职业发展

IF 6.4 1区教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH

Internet and Higher Education

Pub Date : 2024-11-28 DOI: 10.1016/j.iheduc.2024.100988

Jingjing Zhang , Yicheng Huang , Fati Wu , Wei Kan , Xudong Zhu

The impact of Covid-19 has significantly accelerated the digital transformation in higher education worldwide. This study investigates how digital transformation changes the instructional design and implementation of large-scale blended learning programs for better learner experiences. It emphasizes the significance of diverse stakeholders' engagement in institution-initiated blended programs to promote effective online professional development. Utilizing Research-Practice Partnerships (RPPs), this study adopts a case study approach, employing participatory observation, interviews, log data, and online discourses to analyze how interactions across various sectors and levels affect the transformation to blended programs and the professional development of the involved instructors. The findings reveal that the institution-initiated blended learning approach, resembling an apprenticeship model, effectively integrates teaching practice with online professional development. An in-depth analysis of two university courses shows that key events and task-oriented approaches significantly influence instructors' online engagement, enhancing their digital literacy. Teacher Handbooks, driven by real learner data, guide teaching practices effectively, while collaborative research meetings greatly enhance the use of data analytics in teaching. Although this top-down approach presents challenges, this study demonstrates that instructors can innovatively tackle these issues. Institutional support is more likely to foster collaborative learning communities across various sectors and hierarchies. This study contributes to the field by introducing a pioneering framework in the institution's innovative educational reform, creating online professional development communities for faculty members of all ages, and enabling them to quickly and easily adapt to the digital transformation of higher education.

2019冠状病毒病的影响大大加快了全球高等教育的数字化转型。本研究探讨数字化转型如何改变大规模混合学习计划的教学设计和实施，以获得更好的学习者体验。它强调了不同利益相关者参与机构发起的混合项目以促进有效的在线专业发展的重要性。本研究利用研究-实践伙伴关系（RPPs），采用案例研究方法，采用参与式观察、访谈、日志数据和在线话语来分析不同部门和层次的互动如何影响向混合课程的转变以及参与教师的专业发展。研究结果显示，机构发起的混合学习方法，类似于学徒模式，有效地将教学实践与在线专业发展相结合。对两所大学课程的深入分析表明，关键事件和以任务为导向的方法显著影响了教师的在线参与度，提高了他们的数字素养。教师手册由真实的学习者数据驱动，有效地指导教学实践，而合作研究会议大大提高了数据分析在教学中的应用。尽管这种自上而下的方法存在挑战，但本研究表明，教师可以创新地解决这些问题。机构支持更有可能促进跨不同部门和层次的协作学习社区。该研究通过在该机构的创新教育改革中引入开创性框架，为所有年龄段的教师创建在线专业发展社区，使他们能够快速轻松地适应高等教育的数字化转型，从而为该领域做出了贡献。

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引用次数: 0

Promoting university students' situational engagement in online learning for climate education 促进大学生在气候教育在线学习中的情景参与

IF 6.4 1区教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH

Internet and Higher Education

Pub Date : 2024-11-19 DOI: 10.1016/j.iheduc.2024.100987

Elisa Vilhunen , Veli-Matti Vesterinen , Mikko Äijälä , Janne Salovaara , Joula Siponen , Jari Lavonen , Katariina Salmela-Aro , Laura Riuttanen

Disengagement in online learning is known to pose a risk to student learning and wellbeing. In this paper, we first introduce the development and implementation process of a set of online university climate education courses aimed at enhancing student situational engagement through diverse learning activities. Second, engagement (conceptualized here as the co-occurrence of interest, skill, and challenge, i.e., optimal learning moments), and activities during the online courses were examined through ecological momentary assessment, and the relationship between them was investigated through two-level regression models. The results showed that the students were likely to experience optimal learning moments when they were formulating problems and ideating alternatives or designing solutions. Formulating problems and ideating alternatives can promote a student sense of competence, and by designing solutions, students can work with adequately challenging learning tasks. Thus, by implementing such activities in (online) teaching and learning, educators can contribute positively to student engagement.

众所周知，在线学习中的不参与会对学生的学习和身心健康造成威胁。在本文中，我们首先介绍了一套在线大学气候教育课程的开发和实施过程，旨在通过多样化的学习活动提高学生的情景参与度。其次，通过生态学矩阵评估考察了在线课程中的参与度（这里的参与度概念化为兴趣、技能和挑战的共同出现，即最佳学习时刻）和活动，并通过两级回归模型研究了它们之间的关系。结果表明，学生在提出问题、构思替代方案或设计解决方案时很可能经历最佳学习时刻。提出问题和构思替代方案可以增强学生的能力感，而通过设计解决方案，学生可以完成具有足够挑战性的学习任务。因此，通过在（在线）教学中开展此类活动，教育工作者可以积极促进学生的参与。

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引用次数: 0

Enhancing student engagement in online collaborative writing through a generative AI-based conversational agent 通过生成式人工智能会话代理增强学生在线协作写作的参与度

IF 6.4 1区教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH

Internet and Higher Education

Pub Date : 2024-11-17 DOI: 10.1016/j.iheduc.2024.100979

Wanqing Hu , Jirong Tian , Yanyan Li

Promoting student engagement in online collaborative writing (OCW) activities has been a critical concern for educators. Previous research has attempted to design conversational agents (CAs) utilizing retrieval-based models to engage students in collaborative learning. However, few studies have yet explored the design of CAs for OCW based on generative AI (GAI) models. Researchers are calling for investigations into how GAI technology can be better utilized to support learning. Addressing this gap, this study integrates advanced AI technologies (i.e. the retrieval-based model, GAI model, and retrieval-augmented generation) to develop a CA aimed at enhancing students' engagement in OCW activities. Furthermore, a quasi-experiment involving 78 undergraduate students was conducted to explore the effects of this CA on students' engagement (including behavioral, cognitive, and emotional engagement) and group writing performance. The results indicate that the CA did not significantly impact behavioral engagement, emotional engagement, or group writing performance. However, it was found to significantly enhance students' cognitive engagement, particularly by supporting students in sharing opinions, explaining concepts, and engaging in analysis. This research offers both theoretical and practical implications for better utilizing GAI technology to facilitate OCW activities.

促进学生参与在线协作写作（OCW）活动一直是教育工作者关注的一个关键问题。先前的研究试图利用基于检索的模型来设计会话代理（ca），以吸引学生参与协作学习。然而，基于生成式人工智能（GAI）模型的开放式课程CAs设计研究还很少。研究人员呼吁调查如何更好地利用人工智能技术来支持学习。为了解决这一差距，本研究整合了先进的人工智能技术（即基于检索的模型、GAI模型和检索增强生成）来开发旨在提高学生参与开放式课程活动的CA。在此基础上，我们对78名大学生进行了准实验，探讨了这种CA对学生参与（包括行为参与、认知参与和情感参与）和小组写作表现的影响。结果表明，CA对行为投入、情感投入或小组写作表现没有显著影响。然而，研究发现，它可以显著提高学生的认知参与，特别是通过支持学生分享观点、解释概念和参与分析。本研究为更好地利用GAI技术促进开放式课程活动提供了理论和实践意义。

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引用次数: 0

The paradox of self-efficacy and technological dependence: Unraveling generative AI's impact on university students' task completion 自我效能与技术依赖的悖论：解读生成式人工智能对大学生完成任务的影响

IF 6.4 1区教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH

Internet and Higher Education

Pub Date : 2024-11-14 DOI: 10.1016/j.iheduc.2024.100978

Ling Zhang , Junzhou Xu

In the era of proliferating artificial intelligence (AI) technology, generative AI is reshaping educational landscapes, prompting a critical examination of its influence on students' learning processes and their self-efficacy amid concerns over growing technological dependence. This study investigates the nuanced relationship between generative AI use and university students' self-efficacy and technological dependence, illuminating the underlying paradoxes and implications for inclusive education practices. Through a survey of 348 university students, with 200 valid responses analyzed, we uncover the direct and indirect impacts of generative AI usage frequency on AI dependence. Our findings reveal a paradoxical effect: enhanced AI usage significantly amplifies students' confidence and efficiency in learning, yet simultaneously intensifies their dependence on AI. This dual impact both supports and complicates the incorporation of AI technologies into educational settings, underscoring the need for a balanced approach to leveraging AI in teaching and learning. Our study underscores the critical importance of a nuanced understanding of AI's role in education. It highlights the necessity of crafting an educational landscape where technology augments learning processes without compromising independent learning capabilities. By navigating the complex interplay between technological advancement and educational inclusivity, our findings guide the development of AI-assisted learning environments that are not only effective but also equitable and accessible.

在人工智能（AI）技术激增的时代，生成式人工智能正在重塑教育景观，促使人们对其对学生学习过程和自我效能的影响进行批判性审视，同时对日益增长的技术依赖性表示担忧。本研究调查了生成式人工智能的使用与大学生的自我效能感和技术依赖性之间的微妙关系，揭示了潜在的悖论和对全纳教育实践的影响。通过对 348 名大学生的调查（分析了 200 份有效回复），我们揭示了生成式人工智能使用频率对人工智能依赖性的直接和间接影响。我们的研究结果揭示了一种矛盾效应：人工智能使用率的提高显著增强了学生的学习信心和效率，但同时也加剧了他们对人工智能的依赖。这种双重影响既支持了将人工智能技术融入教育环境，也使之变得更加复杂，强调了在教学中利用人工智能需要采取一种平衡的方法。我们的研究强调，细致入微地理解人工智能在教育中的作用至关重要。它强调了精心打造教育环境的必要性，在这样的环境中，技术既能增强学习过程，又不会损害自主学习能力。通过驾驭技术进步与教育包容性之间复杂的相互作用，我们的研究结果为人工智能辅助学习环境的发展提供了指导，这种环境不仅有效，而且公平、无障碍。

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引用次数: 0

Prior online learning experiences as incidental professional development: A cross-sectional survey of online instructor beliefs and strategies 以前的在线学习经历是偶然的专业发展：在线教师信念和策略横断面调查

IF 6.4 1区教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH

Internet and Higher Education

Pub Date : 2024-11-05 DOI: 10.1016/j.iheduc.2024.100977

Kerry J. Burner, Vanessa P. Dennen, Sihan Jian

This study examines how prior experiences as online learners prepare instructors for being online instructors through incidental learning. The study is driven by four research questions, inquiring whether instructors draw upon that experience when teaching online and whether instructors with this online learning experience differ from other online instructors regarding teaching strategies, help-seeking, and use of quality measures. Findings from an online survey show that most instructors with prior online learning experience believe that experience has heavily shaped some of their teaching practices and their desire to teach online. Additionally, these instructors were significantly more likely than their counterparts without online learning experience to find end-of-week summaries, online discussions, and small group activities important. The implications of these and the non-significant findings around help-seeking and quality measures are discussed in the light of professional development programs and meeting the needs of online instructors in higher education environments.

本研究探讨了以前作为在线学习者的经历如何通过偶然学习为教师成为在线教师做好准备。本研究由四个研究问题驱动，询问教师在进行在线教学时是否借鉴了这些经验，以及具有这些在线学习经验的教师在教学策略、寻求帮助和使用质量措施方面是否与其他在线教师有所不同。在线调查结果显示，大多数有过在线学习经验的教师认为，这些经验在很大程度上影响了他们的一些教学实践和在线教学的愿望。此外，与没有在线学习经验的教师相比，这些教师更倾向于认为周末总结、在线讨论和小组活动很重要。我们从专业发展计划和满足高等教育环境中在线教师需求的角度，讨论了这些研究结果的意义，以及有关寻求帮助和质量衡量标准的非显著性研究结果。

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引用次数: 0

Interaction and dialogue: Integration and application of artificial intelligence in blended mode writing feedback 互动与对话：人工智能在混合模式写作反馈中的整合与应用

IF 6.4 1区教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH

Internet and Higher Education

Pub Date : 2024-10-30 DOI: 10.1016/j.iheduc.2024.100975

Yang Jiang

With the rapid advancement of Artificial Intelligence (AI), particularly conversational tools like Chat Generative Pre-trained Transformer (ChatGPT), their application in writing feedback has sparked widespread discussion. While AI writing feedback has proven effective, most research focuses on single feedback methods, with a limited exploration of integrating AI with other approaches. This study uses the Interactive, Constructive, Active, Passive (ICAP) framework to compare hybrid and single feedback in Chinese writing among 86 university students studying in Tibet. The study was conducted in two phases: Phase 1 involved a ten-week quasi-experiment, where the control group received human teacher feedback, and experimental groups received feedback from Kimi.AI (Passive or Active) or a combination of both. In Phase 2, data were collected through semistructured interviews and analyzed using AntConc software. Results showed that combined teacher and AI feedback improved writing skills significantly, highlighting the importance of Rich Interaction and AI's potential to promote educational equity.

随着人工智能（AI）的快速发展，尤其是像聊天生成预训练转换器（ChatGPT）这样的会话工具，它们在写作反馈中的应用引发了广泛的讨论。虽然人工智能写作反馈已被证明是有效的，但大多数研究都集中在单一的反馈方法上，对人工智能与其他方法结合的探索还很有限。本研究采用互动、建构、主动、被动（ICAP）框架，比较了混合反馈和单一反馈在西藏 86 名大学生汉语写作中的应用。研究分两个阶段进行：第一阶段是为期十周的准实验，对照组接受教师的反馈，实验组接受来自 Kimi.AI（被动或主动）或两者结合的反馈。在第二阶段，通过半结构式访谈收集数据，并使用 AntConc 软件进行分析。结果表明，教师和人工智能的联合反馈显著提高了写作能力，突出了丰富互动的重要性和人工智能促进教育公平的潜力。

引用次数: 0

A situated expectancy-value theoretical perspective of teaching presence and student engagement in blended learning environments 从情境期望值理论角度看混合式学习环境中的教学临场感和学生参与度

IF 6.4 1区教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH

Internet and Higher Education

Pub Date : 2024-10-28 DOI: 10.1016/j.iheduc.2024.100974

Jing Ma , Mingmin Zheng , Xiaoxiao Feng

Teaching presence is a key factor affecting student engagement, yet scant research has examined the uniquely longitudinal effect of teaching presence on student engagement. This study, guided by the the processual, situated, and directional lens of Situated Expectancy-Value Theory (SEVT), employed longitudinal structural equation modeling to analyze data from 258 undergraduate students at a Chinese university, investigating how initial teaching presence influenced subsequent motivational constructs (self-efficacy and course value) and student engagement in blended learning environments. Our findings revealed there was an evolving and complex interplay among these constructs. Teaching presence demonstrated a sustained autoregressive effect of itself. Meanwhile, teaching presence acted as a situated catalyst that not only impacted immediate student engagement but also later perceptions of course value and self-efficacy, which in turn increased student engagement levels at the end of the semester. Furthermore, while self-efficacy and course value mediated the relationship between teaching presence and student engagement, the mediating effect of course value was more pronounced. Additionally, the directionality of predicting relationships, revealing a predominant influence from teaching presence to student engagement, rather than a reciprocal relationship. This research underscores the importance of instructional strategies prioritizing a robust teaching presence to initiate a cycle of positive student engagement in blended learning environments. By understanding the longitudinal effects of teaching presence, educators can develop more effective approaches to enhance student engagement and learning outcomes.

教学临场感是影响学生参与度的一个关键因素，但很少有研究探讨教学临场感对学生参与度的独特纵向影响。本研究以情境期望值理论（Situated Expectancy-Value Theory，SEVT）的过程性、情境性和方向性视角为指导，采用纵向结构方程模型分析了来自中国某大学 258 名本科生的数据，探讨了初始教学临场感如何影响混合学习环境中的后续动机建构（自我效能感和课程价值）和学生参与度。我们的研究结果表明，这些建构之间存在着不断发展的复杂相互作用。教学临场感本身表现出持续的自回归效应。同时，教学临场感作为一种情境催化剂，不仅影响了学生的即时参与度，还影响了学生日后对课程价值和自我效能的感知，进而提高了学生在学期末的参与度。此外，虽然自我效能感和课程价值对教学临场感和学生参与度之间的关系起到了中介作用，但课程价值的中介效应更为明显。此外，预测关系的方向性，揭示了教学临场感对学生参与度的主要影响，而不是互惠关系。这项研究强调了教学策略的重要性，即在混合式学习环境中，优先考虑强有力的教学临场感，以启动学生积极参与的循环。通过了解教学临场感的纵向影响，教育工作者可以开发出更有效的方法来提高学生的参与度和学习效果。

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引用次数: 0