Computers & Education最新文献_第7页

Mapping student-AI interaction dynamics in multi-agent learning environments: Supporting personalized learning and reducing performance gaps 在多智能体学习环境中映射学生与人工智能交互动态：支持个性化学习并减少绩效差距

IF 10.5 1区教育学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Education

Pub Date : 2025-10-08 DOI: 10.1016/j.compedu.2025.105472

Zhanxin Hao , Jie Cao , Ruimiao Li , Jifan Yu , Zhiyuan Liu , Yu Zhang

Multi-agent AI systems, which simulate diverse instructional roles such as teachers and peers, offer new possibilities for personalized and interactive learning. Yet, the specific patterns of student-AI interaction and their pedagogical implications remain unclear. This study explores how university students engaged with multiple AI agents during a six-module course, and how these interactions influenced cognitive outcomes (learning gains) and non-cognitive factors (motivation, technology acceptance). Through the analysis of dialogue data, two core engagement patterns were identified: co-construction of knowledge and co-regulation. Students with lower prior knowledge relied more on co-construction of knowledge sequences and showed higher learning gains and post-course motivation. In contrast, students with higher prior knowledge engaged more in co-regulation behaviors but demonstrated limited learning improvement. Technology acceptance increased across all groups. These findings suggest that multi-agent systems can effectively support differentiated engagement and help reduce performance gaps by adapting to students' varying needs. This study makes three innovative contributions to existing research: it is based on a long-term formal curriculum, moving beyond fragmented, short-term interactions; it investigates a multi-agent collaborative mechanism that simulates diverse pedagogical roles (e.g., AI teacher, AI teaching assistance, AI classmates), distinguishing this work from single-agent systems; and it explores differentiated interaction modes based on prior knowledge, providing critical teaching implications for personalized learning.

多智能体人工智能系统模拟了教师和同伴等不同的教学角色，为个性化和互动学习提供了新的可能性。然而，学生与人工智能互动的具体模式及其教学意义仍不清楚。本研究探讨了大学生在六模块课程中如何与多个人工智能代理互动，以及这些互动如何影响认知结果（学习收益）和非认知因素（动机、技术接受度）。通过对对话数据的分析，确定了两种核心参与模式：共同构建知识和共同调节。先验知识水平低的学生更依赖于知识序列的共同构建，表现出更高的学习收益和课后动机。相比之下，具有较高先验知识的学生参与了更多的共同调节行为，但表现出有限的学习进步。所有群体对技术的接受程度都有所提高。这些发现表明，多智能体系统可以有效地支持差异化参与，并通过适应学生的不同需求来帮助缩小绩效差距。这项研究对现有研究做出了三个创新贡献：它基于长期的正式课程，超越了碎片化的短期互动；它研究了一种多智能体协作机制，该机制模拟了不同的教学角色（例如，人工智能教师、人工智能教学辅助、人工智能同学），将这项工作与单智能体系统区分开来；它探索了基于先验知识的差异化互动模式，为个性化学习提供了重要的教学启示。

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引用次数: 0

Instructions of digital media use in higher education: The impact of text abstractness on university teachers’ psychological distance, interest, and motivation to use digital media 高等教育中数字媒体使用的指导：文本抽象性对大学教师使用数字媒体的心理距离、兴趣和动机的影响

IF 10.5 1区教育学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Education

Pub Date : 2025-10-08 DOI: 10.1016/j.compedu.2025.105477

C. Matschke , M. Kehrer , K. Nieder-Steinheuer , A. Thillosen , J. Kimmerle

Research has demonstrated that the use of digital media has great potential to stimulate learning processes and outcomes, especially when purposefully combined with methods that require physical presence, such as in hybrid teaching and learning formats (HTLFs). But so far, the application of HTLFs in higher education does not tap the full potential. One reason is teachers' lack of knowledge and lack of time to acquire the didactical knowledge for digital media use in their teaching. As university teachers acquire their media competencies mostly autodidactically, providing instructions of HTLF on the internet is a pragmatic way to make information about digital media use in teaching accessible to teachers. It remains unclear, however, how instructions should be designed to have a positive impact on teachers' knowledge and application intentions. The current research investigates how the abstractness of HTLF instructions affect psychological distance, interest, self-efficacy, and motivation to apply digital media in teaching. In an experimental study with university teachers (N = 97), we manipulated the abstractness of a description of oral video exams. We found that concrete (compared to abstract) descriptions decreased the hypothetical distance to the method described, which, in turn, increased subsequent acceptance of further information on digital media in teaching, utility expectations, and behavioral intentions to use the method in one's own teaching. The present research demonstrates that even small measures, such as the purposeful design of an instruction, may contribute to setting off processes for the enrichment of teaching and learning methods at universities.

研究表明，数字媒体的使用在促进学习过程和结果方面具有巨大潜力，特别是当有目的地与需要实际存在的方法相结合时，例如混合教学格式（htlf）。但到目前为止，html在高等教育中的应用并没有充分挖掘其潜力。其中一个原因是教师缺乏知识和时间来获取在教学中使用数字媒体的教学知识。由于大学教师的媒体能力大多是通过自学获得的，因此在互联网上提供HTLF指导是一种实用的方法，可以使教师获得有关数字媒体在教学中的使用的信息。然而，如何设计指令才能对教师的知识和应用意图产生积极影响，这一点尚不清楚。本研究探讨HTLF指令的抽象性如何影响心理距离、兴趣、自我效能感和使用数字媒体教学的动机。在一项针对大学教师（N = 97）的实验研究中，我们操纵了口头视频考试描述的抽象性。我们发现，具体的（与抽象的）描述减少了与所描述方法的假设距离，这反过来又增加了随后对数字媒体在教学中的进一步信息的接受程度，实用性期望，以及在自己的教学中使用该方法的行为意图。目前的研究表明，即使是很小的措施，如有目的的教学设计，也可能有助于启动丰富大学教学方法的过程。

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引用次数: 0

Self-regulation plus individual interests? A design-based study on the development of a GenAI-empowered platform for self-directed out-of-class reading 自律加个人利益？基于设计的genai自主课外阅读平台开发研究

IF 10.5 1区教育学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Education

Pub Date : 2025-10-06 DOI: 10.1016/j.compedu.2025.105474

Mengru Pan , Chun Lai , Kai Guo , Jing Huang

Self-directed out-of-class reading contributes to language and general learning, yet many learners struggle with it and need support. Generative Artificial Intelligence (GenAI) holds the potential to provide personalized support that can facilitate self-directed out-of-class reading. This study adopted a design-based research (DBR) methodology to unravel the effective design of GenAI-empowered self-directed out-of-class reading by comparing different ways of integrating a ChatGPT chatbot into an online reading platform in supporting the provision of reading texts and delivering self-regulated learning (SRL) support. The DBR study included three cycles: a conventional approach in Cycle 0 (i.e., a preset pool of reading materials plus human-delivered SRL training), a chatbot-empowered personalized SRL platform in Cycle 1 (i.e., GenAI-recommended reading materials and chatbot-supported personalized SRL training), and a chatbot-empowered interest-based reading with personalized SRL platform in Cycle 2 (i.e., GenAI-recommended interest-based reading materials and chatbot-supported personalized SRL training). This DBR study lasted three semesters, involving one hundred and sixteen English as a foreign language (EFL) students from three classes at a university in China. Qualitative data from open-ended surveys and interviews after each cycle were used to refine the platform design in the subsequent cycle. Quantitative data, including pre- and post-surveys on self-regulated reading strategy use and self-directed reading, along with log data, were analyzed to compare the effects of the platform design on students' self-regulated strategy use and self-directed reading across three cycles. The results indicated that the chatbot-empowered interest-based reading with personalized SRL training showed the greatest potential in enhancing students’ self-regulated reading strategy use and self-directed reading. This study contributes to the existing literature by elucidating the design principles that enhance self-directed out-of-class reading.

自主课外阅读有助于语言和一般的学习，但许多学习者挣扎，需要支持。生成式人工智能（GenAI）具有提供个性化支持的潜力，可以促进自主课外阅读。本研究采用基于设计的研究（DBR）方法，通过比较将ChatGPT聊天机器人集成到在线阅读平台以支持提供阅读文本和提供自我调节学习（SRL）支持的不同方式，揭示了genai授权的自主课外阅读的有效设计。DBR研究包括三个周期：周期0的常规方法（即预设的阅读材料池加上人工交付的SRL训练），周期1的聊天机器人支持的个性化SRL平台（即genai推荐的阅读材料和聊天机器人支持的个性化SRL训练），以及周期2的聊天机器人支持的基于兴趣的阅读和个性化SRL平台（即genai推荐的基于兴趣的阅读材料和聊天机器人支持的个性化SRL训练）。这项DBR研究持续了三个学期，涉及来自中国一所大学三个班的116名英语作为外语（EFL）学生。每个周期后的开放式调查和访谈的定性数据用于改进后续周期的平台设计。定量数据包括自我调节阅读策略使用和自主阅读的前后调查，以及日志数据，分析了平台设计对学生三个周期的自我调节策略使用和自主阅读的影响。结果表明，基于聊天机器人的兴趣阅读与个性化SRL训练在提高学生自主阅读策略使用和自主阅读方面表现出最大的潜力。本研究通过阐明增强自主课外阅读的设计原则，对现有文献有所贡献。

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引用次数: 0

Incremental project-based robot programming: Effects on young children's computational thinking, executive function, and learning behavioral patterns 基于增量项目的机器人编程：对幼儿计算思维、执行功能和学习行为模式的影响

IF 10.5 1区教育学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Education

Pub Date : 2025-10-03 DOI: 10.1016/j.compedu.2025.105471

Yuchen Chen , Xinli Zhang , Lailin Hu , Gwo-Jen Hwang , Haoran Xie , Yun-Fang Tu

Robot programming is an age-appropriate means to cultivate children's computational thinking (CT) and executive function (EF). Project-based learning (PBL) is commonly applied to teach robot programming. PBL involves complex, large-scale projects consisting of multiple sub-projects. Each sub-project introduces new knowledge but offers few opportunities to connect it with previously learned knowledge, thus misaligning with children's cognitive development. In comparison, incremental PBL (IPBL) is a tailored design of PBL that begins with basic knowledge, with each new sub-project building on all learned knowledge from previous sub-projects and progressively adding new knowledge to achieve complete project learning. Hence, this research integrated IPBL into robot programming to develop an incremental project-based robot programming (I-PBRP) approach, and evaluated its effect on young children's CT, EF, and learning behavioral patterns. Ninety-five children aged 5–6 engaged in 12-week interventions. They were randomly assigned to the I-PBRP group and the conventional project-based robot programming (C-PBRP) group. Results manifested that the I-PBRP group achieved better performance than the C-PBRP group in CT and in the three components of EF (inhibition, working memory, and cognitive flexibility) over time. The progressive behavioral analysis manifested that the I-PBRP approach promoted superior performance in robot programming activities and more positive learning behaviors for children. This research has implications for robot programming teaching approaches for young children's CT and EF development.

机器人编程是培养儿童计算思维（CT）和执行功能（EF）的一种适龄手段。基于项目的学习（PBL）是机器人编程教学的常用方法。PBL涉及由多个子项目组成的复杂的大型项目。每个子项目都引入了新知识，但很少有机会将其与以前所学的知识联系起来，从而与儿童的认知发展不一致。相比之下，增量式PBL （IPBL）是一种定制化的PBL设计，从基础知识开始，每个新的子项目都建立在以前子项目的所有知识基础上，并逐步增加新的知识，以实现完整的项目学习。因此，本研究将IPBL整合到机器人编程中，开发了一种基于增量项目的机器人编程（I-PBRP）方法，并评估了其对幼儿CT、EF和学习行为模式的影响。95名5-6岁的儿童参与了为期12周的干预。他们被随机分配到I-PBRP组和传统的基于项目的机器人编程（C-PBRP）组。结果表明，随着时间的推移，I-PBRP组在CT和EF的三个组成部分（抑制、工作记忆和认知灵活性）方面的表现优于C-PBRP组。渐进式行为分析表明，I-PBRP方法促进了儿童在机器人编程活动中的优异表现和更积极的学习行为。本研究对幼儿CT和EF发展的机器人编程教学方法具有启示意义。

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引用次数: 0

Adaptive vs. planned metacognitive scaffolding for computational thinking: Evidence from generative AI-supported programming in elementary education 计算思维的自适应与计划元认知支架：来自基础教育中生成式人工智能支持的编程的证据

IF 10.5 1区教育学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Education

Pub Date : 2025-10-02 DOI: 10.1016/j.compedu.2025.105473

Jinfang Liu , Yi Zhang , Wei Li , Qiyun Wang , Pingxiu Niu , Xue Zhang

Metacognitive scaffolding plays a pivotal role in supporting the development of computational thinking (CT) among elementary students. Compared to planned scaffolding, adaptive scaffolding supported by generative AI (GAI) agents offers a promising option by providing real–time, adaptive and personalized response. This study investigated how adaptive metacognitive scaffolding (AMS) and planned metacognitive scaffolding (PMS) influenced elementary students’ CT in a GAI–supported programming environment. 74 students were assigned to AMS, PMS, or control conditions. Using a mixed-methods approach, we examined CT task performance, CT skill use, metacognitive regulation, and cognitive load through standardized assessments, programming artifacts, discourse logs, video-coded behaviors, classroom observation records, cognitive load ratings. Results showed that AMS significantly enhanced contextualized CT performance and promoted more complex, diverse skill use compared to PMS and control groups. AMS also fostered more recursive metacognitive behaviors and reduced mental efforts, while PMS supported higher meaningful engagement. These findings highlight the potential of adaptive scaffolding powered by GAI to support CT development in elementary programming education.

元认知支架在小学生计算思维发展中起着举足轻重的作用。与计划脚手架相比，由生成式人工智能（GAI）代理支持的自适应脚手架通过提供实时、自适应和个性化的响应，提供了一个很有前途的选择。本研究探讨了在人工智能支持的编程环境下，适应性元认知支架（AMS）和计划性元认知支架（PMS）对小学生CT的影响。74名学生被分配到AMS， PMS或对照条件。采用混合方法，我们通过标准化评估、编程工件、话语日志、视频编码行为、课堂观察记录、认知负荷评级，检查了CT任务表现、CT技能使用、元认知调节和认知负荷。结果显示，与PMS和对照组相比，AMS显著提高了情境化CT表现，促进了更复杂、更多样化的技能使用。AMS还培养了更多的递归元认知行为，减少了心理努力，而PMS支持更高的有意义的投入。这些发现强调了由GAI驱动的自适应脚手架在支持初级编程教育中的CT开发方面的潜力。

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引用次数: 0

Team collaborative norms enhance students’ behavioral engagement in team-based flipped classrooms: A multilevel analysis 团队合作规范在基于团队的翻转课堂中提高学生的行为投入：一个多层次的分析

IF 10.5 1区教育学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Education

Pub Date : 2025-10-01 DOI: 10.1016/j.compedu.2025.105468

Hui-Min Lai , Pi-Jung Hsieh , Fang-Chuan Ou Yang

The flipped classroom (FC) model replaces traditional in-class lectures with student-centered, team-based activities. In the FC model, in-class sessions are typically conducted in teams to promote active participation, group discussion, problem-solving, and collaborative learning. However, a review of previous studies reveals that the factors contributing to behavioral engagement in team-based FCs remain underexplored. Thus, we aim to explore team-based FCs by integrating the theories of expectancy–value and social motivation. Given that collaborative norms are crucial for enhancing students’ behavioral engagement in teams, we propose that team collaborative norms moderate the relationship between individuals’ beliefs (value and competence beliefs) and behavioral engagement. We collected data from 808 students across 238 teams in 28 team-based FCs and used a hierarchical linear model to examine the hypothesized relationships. The results indicated a positive relationship between utility value and students’ behavioral engagement, as well as between interest value and engagement in team-based FCs. Conversely, there was a negative relationship between learning anxiety and students’ behavioral engagement. No significant relationship was found between attainment value and engagement. Additionally, self-efficacy and team collaborative norms were positively associated with students’ behavioral engagement in team-based FCs. Notably, the moderating effect of team collaborative norms on the relationships between utility value and behavioral engagement and between interest value and behavioral engagement was stronger under high team collaborative norms than under low ones. This study contributes to existing research by validating the role of team collaborative norms in students’ behavioral engagement within team-based FCs.

翻转课堂（FC）模式以学生为中心，以团队为基础的活动取代了传统的课堂讲座。在FC模型中，课堂会议通常在团队中进行，以促进积极参与、小组讨论、解决问题和协作学习。然而，对先前研究的回顾表明，在基于团队的fc中，影响行为参与的因素仍未得到充分探索。因此，我们旨在通过整合期望值理论和社会动机理论来探索基于团队的FCs。鉴于协作规范对提高学生在团队中的行为投入至关重要，我们提出团队协作规范调节个人信念（价值信念和能力信念）与行为投入之间的关系。我们收集了来自28个基于团队的fc的238个团队的808名学生的数据，并使用分层线性模型来检验假设的关系。结果表明，在团队型FCs中，效用价值与学生的行为投入存在正相关，兴趣价值与行为投入存在正相关。反之，学习焦虑与学生行为投入呈负相关。学业成就值与敬业度之间无显著关系。此外，自我效能感和团队合作规范与学生的行为投入正相关。值得注意的是，团队协作规范对团队效用价值与行为投入、兴趣价值与行为投入关系的调节作用在高团队协作规范下强于低团队协作规范下。本研究通过验证团队协作规范在团队型FCs中学生行为投入中的作用，为现有研究做出了贡献。

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引用次数: 0

An intelligent recommender system based on K-nearest neighbors to foster self-regulated learning and reduce cognitive load in online higher education 基于k近邻的在线高等教育智能推荐系统促进自主学习，减少认知负荷

IF 10.5 1区教育学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Education

Pub Date : 2025-10-01 DOI: 10.1016/j.compedu.2025.105470

Shao-Chen Chang , Ngoc Diep Dao

Higher education institutions worldwide are increasingly adopting online learning systems to improve instructional quality and offer students flexible, anytime-anywhere access to educational resources. Despite these benefits, online learning environments still face notable challenges. In this learning environment, the major challenge lies in the lack of personalized learning support. The “one-size-fits-all” approach ignores learners' diverse needs, making it difficult for students to regulate their learning effectively. Without tailored guidance, students especially low achievers are more likely to experience cognitive overload, reduced motivation, disengagement, and even dropout. In response to these issues, this study presents an interactive self-regulated learning system built on a comprehensive system architecture that integrates personalized learning path recommendations based on K-nearest Neighbors (KNN) for university students. The system consists of four main components: Content Management System (CMS), Evaluation System, Recommendation System, and User Interface application. This study evaluates the system's perceived effectiveness in the “Introduction to Database Systems” course at a university located in northern Taiwan. It further investigates the system's impact on students' learning behavior, self-regulated learning skills, learning achievement and perceived cognitive load in an online learning environment. The findings suggest that students using the interactive self-regulated learning system with personalized recommendation paths exhibited higher motivation, engagement, learning achievement and self-regulated learning skills. The system also contributed to a noticeable reduction in students'perceived cognitive load.

世界各地的高等教育机构越来越多地采用在线学习系统来提高教学质量，并为学生提供灵活的、随时随地的教育资源。尽管有这些好处，在线学习环境仍然面临着显著的挑战。在这种学习环境下，主要的挑战在于缺乏个性化的学习支持。“一刀切”的做法忽视了学习者的多样化需求，使学生难以有效地调节自己的学习。如果没有量身定制的指导，成绩差的学生更有可能经历认知超载、动力下降、不投入，甚至辍学。针对这些问题，本研究提出了一个基于综合系统架构的交互式自主学习系统，该系统集成了基于k -近邻（KNN）的个性化学习路径推荐。该系统由内容管理系统（CMS）、评价系统、推荐系统和用户界面应用四个主要部分组成。本研究在台湾北部一所大学的“数据库系统导论”课程中，评估系统的感知效能。本研究进一步探讨了系统对在线学习环境下学生学习行为、自我调节学习技能、学习成绩和感知认知负荷的影响。研究结果表明，使用个性化推荐路径的互动自主学习系统的学生表现出更高的学习动机、参与度、学习成就和自主学习技能。该系统还有助于显著减少学生的认知负荷。

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引用次数: 0

Effects of a human-robot collaborative teaching approach on preschoolers’ social-emotional competence and learning behaviors 人机协作教学方式对学龄前儿童社交情绪能力和学习行为的影响

IF 10.5 1区教育学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Education

Pub Date : 2025-09-30 DOI: 10.1016/j.compedu.2025.105469

Jian-Wen Fang , Ting-Ting Ji , Yun-Fang Tu , Gwo-Jen Hwang , Di Zou , Jing Chen

Preschoolers' social-emotional competence is key to their long-term academic success. Developing this competence requires meaningful social interactions and emotional support, which the conventional teaching (CT) approach may not fully provide. This study proposed a human-robot collaborative teaching (HRCT) approach to facilitate preschoolers' social-emotional learning (SEL). A human-robot collaborative teaching system was developed to foster preschoolers' social-emotional competence through collaboration between the humanoid intelligent robot and the teacher. To evaluate the effectiveness of this approach, 96 preschoolers with an average age of 4.6 years were recruited. Of these, 44 were randomly assigned to the experimental group, which utilized the HRCT approach, while 52 were assigned to the control group, which followed the conventional teaching approach. The results indicated that the experimental group outperformed the control group in terms of social interaction skills, emotion comprehension skills, and interpersonal problem-solving skills. Significant differences were also observed in the learning behaviors of preschoolers during activities related to social interaction, emotion comprehension, and interpersonal problem solving. Further analysis of the teacher's perceptions and reflections revealed that, despite some limitations of the robot, its anthropomorphic and embodied features effectively sparked preschoolers' interest and engagement. These features contributed to enhancing their social-emotional competence by simulating and practicing SEL processes.

学龄前儿童的社会情感能力是他们长期学业成功的关键。培养这种能力需要有意义的社会互动和情感支持，而传统的教学方法可能无法完全提供这些。本研究提出了一种促进幼儿社会情绪学习的人机协作教学方法。设计了一种人-机器人协作教学系统，通过类人智能机器人与教师的协作，培养幼儿的社交情感能力。为了评估这种方法的有效性，我们招募了96名平均年龄为4.6岁的学龄前儿童。其中，实验组44人，采用HRCT教学方法；对照组52人，采用常规教学方法。结果表明，实验组在社交能力、情绪理解能力和人际问题解决能力方面均优于对照组。学龄前儿童在社会交往、情绪理解和人际问题解决方面的学习行为也存在显著差异。进一步分析老师的感知和反思，发现尽管机器人有一些局限性，但它的拟人化和具体化的特征有效地激发了学龄前儿童的兴趣和参与。这些特征有助于通过模拟和实践SEL过程来提高他们的社会情感能力。

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引用次数: 0

Evaluating educational technology: Consolidating across multiple impact indicators and rating systems 评估教育技术：跨多个影响指标和评级系统的整合

IF 10.5 1区教育学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Education

Pub Date : 2025-09-29 DOI: 10.1016/j.compedu.2025.105467

Natalia Kucirkova , Per Henning Uppstad , Richard Holeton , Dan Lin , Alison Clark-Wilson , Antonie Chigeda

Procurement of educational technologies (EdTech) requires a research-based rubric with multiple quality indicators that reflect the technology’s impact across various settings. We outline the development of the Multiple EdTech Impact Index (MEII) and an impact benchmarking formula for EdTech tools designed for K12 education. MEII includes fifteen indicators of impact, categorized into three evidence weights (high, medium, low) across five domains: efficacy, effectiveness, ethics, equity, and environment. It calculates a total EdTech impact score, highlighting the strength and relevance of products. MEII integrates evaluations based on diverse national EdTech certification standards and proposes a unified approach for assessment. We demonstrate its value through two models: national EdTech certification systems and a comparative database ranking EdTech tools by impact weight.

教育技术的采购（EdTech）需要一个以研究为基础的标准，其中包含多个质量指标，以反映技术在各种环境中的影响。我们概述了多重教育技术影响指数（MEII）的发展以及为K12教育设计的教育技术工具的影响基准公式。MEII包括15个影响指标，分为三个证据权重（高、中、低），跨越五个领域：疗效、有效性、伦理、公平和环境。它计算EdTech影响总分，突出产品的实力和相关性。综合不同国家教育技术认证标准的评估，提出统一的评估方法。我们通过两个模型来证明它的价值：国家教育技术认证系统和根据影响权重对教育技术工具进行排名的比较数据库。

引用次数: 0

Using eye tracking to explore differences and influencing factors of map reading ability in different problem situation among high school students 运用眼动追踪法探讨高中生在不同问题情境下地图阅读能力的差异及影响因素

IF 10.5 1区教育学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Computers & Education

Pub Date : 2025-09-26 DOI: 10.1016/j.compedu.2025.105466

Xinxin Li , Ping Li , Huiming You , Qiuwen Zhou , Ling Zhao , Yan Huang , Ya Luo

This study uses eye tracking to explore the differences in map-reading ability among high school students in the context of subject knowledge and real-life application. Unlike existing literature, which primarily emphasizes outcome-based assessments, this study integrates process- and outcome-based indicators to quantitatively evaluate high school students' map-reading abilities across different problem situations. Additionally, it comprehensively analyzes the internal and external factors influencing students' map-reading abilities and constructs a conceptual framework to illustrate the pathway through which these factors contribute to differences in performance among the students. The results reveal that in real-life scenarios, students exhibited longer reaction times, engaged in more extensive visual searches, processed information in a complex manner, and achieved low accuracy rates. However, despite these limitations, their cognitive load did not increase significantly. Furthermore, several limitations were highlighted in traditional geography education, particularly in fostering students' spatial reasoning and practical application skills. These findings contribute to the existing research on map-reading abilities, providing a new theoretical foundation and empirical support for advancements in geography education. Moreover, they can help educators better enhance students’ map-reading ability to meet diverse and complex practical needs.

本研究采用眼动追踪的方法，探讨了在学科知识背景和现实应用背景下高中生地图阅读能力的差异。与现有文献主要强调基于结果的评估不同，本研究整合了基于过程和结果的指标来定量评估高中学生在不同问题情境下的地图阅读能力。此外，本文还综合分析了影响学生地图阅读能力的内外部因素，并构建了一个概念框架来说明这些因素导致学生之间表现差异的途径。结果表明，在现实场景中，学生表现出更长的反应时间，参与更广泛的视觉搜索，以复杂的方式处理信息，并且准确率较低。然而，尽管有这些限制，他们的认知负荷并没有显著增加。此外，传统地理教育在培养学生的空间推理能力和实际应用能力方面也存在一定的局限性。这些研究结果对现有的地图阅读能力研究有一定的借鉴作用，为提高地理教育水平提供了新的理论基础和实证支持。此外，它们可以帮助教育者更好地提高学生的地图阅读能力，以满足多样化和复杂的实际需求。

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引用次数: 0