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Enhancing STEM Skills With the Design of Mobile Robots: An Experience With Technical Secondary School Students 用移动机器人的设计提高STEM技能:中专学生的经验
IF 1 Q4 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2025-10-06 DOI: 10.1109/RITA.2025.3616857
Rômulo Afonso L. V. de Omena;John Vitor T. da Silva;Manoel Messias de O. Rodrigues;Maurício Freitas Dos Santos Filho;Sarah Kauane L. Silva;Heshelley Roberta M. L. Costa;Débora Ruthe N. Moraes;Arthur da Rocha Albuquerque;Johnny Guilherme da Silva;Victor Gabriel de Jesus Oliveira;Marina Marra M. de Oliveira;Heloise Rayane da R. Santos;Ana Luisa de P. S. Melo;Hewerton Nascimento da Silva;Mariana Paulino Dos Santos;José Kawê S. M. da Silva;Allisson Luiz N. da Silva;Jacksiel José de Abreu
An education model with pillars on science, technology, engineering, and mathematics (STEM) is increasingly necessary to prepare our students for future jobs. A didactic tool that can engage students in STEM is robotics. A study area of robotics, mobile robotics is a rich tool that generates enthusiasm in students and involves diverse disciplines. While commercial robotic platforms for education exist, their high cost and limited customizability often pose challenges, particularly within the Brazilian public education system. This paper presents an experience with ten technical secondary school students focused on developing two distinct low-cost mobile robots: a differential drive and an omnidirectional one, sponsored by a research foundation. The primary objectives were to investigate the impact of a maker-approach environment on the enhancement of STEM skills and to provide accessible robotic platforms for future educational projects. Students, divided into pairs, worked collaboratively on various aspects of robot development, including chassis design, power supply, motor drive, data acquisition, and simulation and coding, utilizing computational tools like Tinkercad, AutoCAD, Arduino IDE, and ROS 2. This project aimed to answer how such an initiative could foster specific STEM competencies and what challenges and perceptions arise from the students’ perspective. The experience demonstrated that students not only developed STEM skills but also contributed valuable robotic platforms to the academic community. The initiative underscores the importance of foundational support in equipping the Brazilian education system to prepare students with skills vital for future professions.
一种以科学、技术、工程和数学(STEM)为支柱的教育模式对我们的学生为未来的工作做好准备越来越必要。机器人技术是一种能够吸引学生参与STEM的教学工具。作为机器人的一个研究领域,移动机器人是一个丰富的工具,可以激发学生的热情,并涉及不同的学科。虽然存在用于教育的商业机器人平台,但它们的高成本和有限的可定制性经常带来挑战,特别是在巴西的公共教育系统中。本文介绍了十名中专学生的经验,他们专注于开发两种不同的低成本移动机器人:差动驱动和全向驱动,由一个研究基金会赞助。主要目标是研究创客环境对提高STEM技能的影响,并为未来的教育项目提供可访问的机器人平台。学生们分成两组,利用Tinkercad、AutoCAD、Arduino IDE和ROS 2等计算工具,在机器人开发的各个方面进行协作,包括底盘设计、电源供应、电机驱动、数据采集、仿真和编码。该项目旨在回答这样的倡议如何培养特定的STEM能力,以及从学生的角度来看会产生哪些挑战和看法。这次经历表明,学生们不仅发展了STEM技能,而且为学术界贡献了宝贵的机器人平台。该倡议强调了为巴西教育系统提供基础支持的重要性,使学生具备未来职业所需的关键技能。
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引用次数: 0
AI in Higher Education: Initial Teacher Training in the Critical and Didactic Use of Artificial Intelligence 高等教育中的人工智能:人工智能批判性和教学应用的初步教师培训
IF 1 Q4 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2025-10-06 DOI: 10.1109/RITA.2025.3616509
Sebastián Martín-Gómez;Carlos J. González Ruiz
This study was made possible by the University of La Laguna. The Educational Technology courses within the Bachelor’s degrees in Early Childhood Education and in Physical Activity and Sports Sciences (n = 103) were redesigned, integrating AI agents such as ChatGPT, Gemini and Perplexity into six phases for the critical use of these tools—questioning, comparison, critical dialogue, verification, re-elaboration and reflection—which guided students’ reflective interaction with AI. After the intervention, a mixed 23-item questionnaire was administered; descriptive statistics and thematic analysis of the “Evaluation and use of AI” dimension revealed that 88% of students believe AI should be didactically promoted in higher education and 42% identified ChatGPT as the agent providing the best answers. The most developed competencies were comparing outputs from different AI systems (66%), designing effective prompts (63%) and critically analysing responses (52%). The main potentialities highlighted were rapid access to information and time saving, while perceived risks centred on plagiarism and cognitive dependence. The findings corroborate the pedagogical validity of the model for strengthening prompt-engineering skills and critical thinking, yet underscore the need to deepen ethical training and rigorous verification frameworks to address concerns about academic integrity and AI reliability. It is concluded that a reflective and regulated integration of these technologies can significantly enhance teacher education in higher education.
这项研究是由拉古纳大学促成的。重新设计了幼儿教育和体育活动与运动科学学士学位课程中的教育技术课程(n = 103),将ChatGPT、Gemini和Perplexity等人工智能代理整合为六个阶段,用于批判性地使用这些工具——质疑、比较、批判性对话、验证、重新阐述和反思——指导学生与人工智能进行反思性互动。干预后,采用23项混合问卷;对“人工智能的评估和使用”维度的描述性统计和专题分析显示,88%的学生认为人工智能应该在高等教育中得到教学推广,42%的学生认为ChatGPT是提供最佳答案的代理。最发达的能力是比较不同人工智能系统的输出(66%),设计有效的提示(63%)和批判性地分析回应(52%)。强调的主要潜力是快速获取信息和节省时间,而感知到的风险集中在抄袭和认知依赖上。研究结果证实了该模型在加强快速工程技能和批判性思维方面的教学有效性,但也强调了深化道德培训和严格验证框架的必要性,以解决对学术诚信和人工智能可靠性的担忧。结论是,反思和规范地整合这些技术可以显著提高高等教育的教师教育水平。
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引用次数: 0
Integration of Scenario-Based Learning in CyberTOMP With FLECO Studio: Enhancing Situational Awareness Training in Cybersecurity 基于场景的学习在CyberTOMP与FLECO Studio的整合:加强网络安全中的态势感知训练
IF 1 Q4 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2025-10-01 DOI: 10.1109/RITA.2025.3616004
Manuel Domínguez-Dorado;Francisco J. Rodríguez-Pérez;David Cortés-Polo;Jesús Galeano-Brajones;Jesús Calle-Cancho
Situational awareness is crucial in cybersecurity to identify, understand, and anticipate cyber threats, and to make effective decisions during cyber crises. This study evaluates the effectiveness of a hands-on approach based on interactive scenarios using FLECO Studio software, integrated into the holistic management model CyberTOMP, compared to a traditional lecture-based approach framed within the same model. An experiment was designed with 200 participants, divided into a treatment group (70%) and a control group (30%). Both groups received training aimed at increasing their level of situational awareness in cybersecurity, with assessments conducted before and after the training. The treatment group employed the interactive scenario-based approach modeled with FLECO Studio, while the control group received traditional lecture-based training. To mitigate potential biases, preventive measures were implemented during the design and analysis of the study. The statistically analyzed results illustrated a significant improvement (up to 54%) in the situational awareness level of the treatment group, along with a strongly positive perception of effectiveness among the participants. These findings suggest that the interactive scenario-based approach, using tools embedded within a comprehensive holistic framework, significantly enhances the acquisition of situational awareness capabilities in cybersecurity compared to a traditional lecture-based approach.
态势感知在网络安全中至关重要,可以识别、理解和预测网络威胁,并在网络危机期间做出有效决策。本研究评估了基于FLECO Studio软件的交互式场景的实践方法的有效性,并将其集成到整体管理模型CyberTOMP中,与传统的基于讲座的方法在同一模型中进行比较。实验设计200人,分为治疗组(70%)和对照组(30%)。两组都接受了旨在提高网络安全态势感知水平的培训,并在培训前后进行了评估。治疗组采用以FLECO Studio为模型的交互式基于场景的方法,对照组采用传统的以讲座为基础的培训。为了减少潜在的偏差,在研究的设计和分析过程中实施了预防措施。统计分析结果表明,治疗组在情境意识水平上有了显著的改善(高达54%),同时参与者对有效性有了强烈的积极认知。这些发现表明,与传统的基于讲座的方法相比,使用嵌入在综合整体框架中的工具的交互式基于场景的方法显著增强了网络安全态势感知能力的获取。
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引用次数: 0
Data-Driven Learning Analytics and Artificial Intelligence in Higher Education: A Systematic Review 高等教育中的数据驱动学习分析与人工智能:系统综述
IF 1 Q4 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2025-09-29 DOI: 10.1109/RITA.2025.3615512
Laura Icela González-Pérez;Francisco José García-Peñalvo;Amadeo José Argüelles-Cruz
The responsible integration of Artificial Intelligence in Education (AIED) offers a strategic opportunity to align learning environments with the principles of Society 5.0, fostering human–technology synergy in support of quality education and social well-being. This study presents a systematic review of 36 peer-reviewed articles (2021–2025) focused on educational applications that employ learning analytics (LA) through data-driven approaches and integrate machine learning (ML) models as part of their empirical evidence. Each study was analyzed according to three key dimensions: the context of AIED application, the data-driven approach adopted, and the ML model implemented. The findings reveal a persistent disconnect between the AI models employed and the available educational data, which in many cases are limited to access logs or manually recorded grades that fail to capture deeper cognitive processes. This limitation constrains both the effective training of ML models and their pedagogical utility for delivering meaningful interventions such as personalized learning pathways, real-time feedback, early detection of learning difficulties, and monitoring and visualization tools. Another significant finding is the absence of psychopedagogical frameworks integrated with quality standards and data governance, which are essential for advancing prescriptive and ethical approaches aligned with learning goals. It is therefore recommended that educational leaders foster AIED applications grounded in data governance and ethics frameworks, ensuring valid and reliable metrics that can drive a more equitable and inclusive education.
人工智能在教育中的负责任整合(AIED)提供了一个战略机会,使学习环境与社会5.0的原则保持一致,促进人类与技术的协同作用,以支持优质教育和社会福祉。本研究对36篇同行评议文章(2021-2025)进行了系统回顾,重点关注通过数据驱动方法采用学习分析(LA)的教育应用,并将机器学习(ML)模型作为其经验证据的一部分。每个研究都根据三个关键维度进行分析:AIED应用的背景、采用的数据驱动方法和实现的ML模型。研究结果表明,所采用的人工智能模型与可用的教育数据之间存在持续脱节,在许多情况下,这些数据仅限于访问日志或手动记录的成绩,无法捕捉更深层次的认知过程。这种限制既限制了机器学习模型的有效训练,也限制了它们在提供有意义的干预措施(如个性化学习途径、实时反馈、学习困难的早期检测以及监控和可视化工具)方面的教学效用。另一个重要发现是缺乏与质量标准和数据治理相结合的心理学框架,这对于推进符合学习目标的规范性和伦理方法至关重要。因此,建议教育领导者促进基于数据治理和道德框架的AIED应用,确保有效和可靠的指标,从而推动更加公平和包容的教育。
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引用次数: 0
What Determines Student Employability? Educational Data Mining Through Machine and Deep Learning Approach 什么决定学生的就业能力?基于机器和深度学习方法的教育数据挖掘
IF 1 Q4 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2025-09-19 DOI: 10.1109/RITA.2025.3612280
Rasikh Tariq;Diego Gutiérrez Vargas;Farhan Ali;Miguel Gonzalez-Mendoza;Cristina Sofia Torres-Castillo
Employability is vital for graduates to succeed in competitive job markets and reflects higher education institutions’ effectiveness. It is essential to investigate which specific traits contribute to a higher success rate of employability, as understanding these factors can help optimize targeted interventions and improve employment outcomes. The objective of this research is to identify and analyze the key traits that influence student employability using educational data mining techniques integrated with machine learning and deep learning models while providing an explainable framework to inform targeted interventions and enhance job market readiness among graduates. Addressing gaps in existing research, this study integrates a wide range of variables and employs advanced Artificial Intelligence (AI) techniques, specifically Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU), to develop a predictive framework for understanding employability over time. Using data from mock job interviews, the study applies Shapley Additive exPlanations (SHAP) values to assess the impact of traits like Self-Confidence and Ability to Present Ideas. Hyperparameter tuning through Grid Search and k-fold cross-validation is employed to optimize model performance. The LSTM model, configured with three layers, achieved an accuracy of 91.46%, and demonstrated the highest performance among the evaluated models. Its robustness was further supported by a 90.48% accuracy obtained through 3-fold cross-validation. The current findings highlight the importance of soft skills, such as Self-Confidence, Ability to Present Ideas, and General Appearance, identified by SHAP analysis as critical predictors of employability, emphasizing the need for educational institutions to actively integrate soft skills development into their curricula to ensure students are both academically prepared and professionally equipped.
就业能力对于毕业生在竞争激烈的就业市场中取得成功至关重要,反映了高等教育机构的有效性。有必要研究哪些具体特征有助于提高就业成功率,因为了解这些因素有助于优化有针对性的干预措施并改善就业结果。本研究的目的是利用与机器学习和深度学习模型相结合的教育数据挖掘技术,识别和分析影响学生就业能力的关键特征,同时提供一个可解释的框架,为有针对性的干预提供信息,并提高毕业生的就业市场准备程度。为了解决现有研究中的空白,本研究整合了广泛的变量,并采用了先进的人工智能(AI)技术,特别是长短期记忆(LSTM)和门控制循环单元(GRU),以开发一个预测框架,以了解随着时间的推移的就业能力。利用模拟工作面试的数据,该研究应用Shapley加法解释(SHAP)值来评估自信和表达能力等特征的影响。通过网格搜索和k-fold交叉验证进行超参数调整以优化模型性能。LSTM模型配置为三层,准确率为91.46%,在评价模型中表现出最高的性能。通过3倍交叉验证获得90.48%的准确率,进一步支持了其稳健性。目前的研究结果强调了软技能的重要性,如自信、表达想法的能力和总体形象,这些软技能被SHAP分析确定为就业能力的关键预测因素,强调了教育机构积极将软技能发展纳入课程的必要性,以确保学生既能在学术上做好准备,又能在专业上得到装备。
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引用次数: 0
Technology Courses for Non-STEM Degrees: A Project-Based Learning Case Study 非stem学位的技术课程:基于项目的学习案例研究
IF 1 Q4 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2025-09-08 DOI: 10.1109/RITA.2025.3607479
Mihaela I. Chidean;Ana Arboleya;Maria Cerezo-Magaña;Antonio J. Caamaño;Eduardo del Arco;David Cortés-Polo
Actual and future society requires more and more technology-related knowledge. One of the goals of the educational system is to prepare current students and future workers for the different challenges and jobs that they might encounter, even if most future jobs are largely unknown. Although administrations gradually modify education policies that will affect future generations, nowadays, there are students enrolled in non-STEM degrees who require the same opportunities. There are multiple approaches to this issue, such as double major art-engineering degrees or specific technological courses offered for students enrolled in non-STEM degrees. In this work, we present a case study conducted in a mandatory course for an undergraduate design degree in the art and humanities field. The course objective is to teach students basic electronic design and programming with the Arduino platform. To evaluate the previous knowledge and attitude of the students with regard to technology, initial tests were conducted. To evaluate their acquired knowledge, the students’ final projects developed during the course were assessed. The present study analyzes the benefits for this student profile, showing that besides acquiring new expertise they have also broadened their options and opportunities in the labour market.
现实和未来的社会需要越来越多的与技术相关的知识。教育系统的目标之一是让现在的学生和未来的工人为他们可能遇到的不同挑战和工作做好准备,即使大多数未来的工作在很大程度上是未知的。虽然行政部门逐渐修改影响后代的教育政策,但如今,非stem学位的学生也需要同样的机会。有多种方法可以解决这个问题,例如为非stem学位的学生提供双专业艺术工程学位或特定的技术课程。在这项工作中,我们提出了一个在艺术与人文领域的本科设计学位必修课程中进行的案例研究。课程目标是教学生基本的电子设计和编程与Arduino平台。为了评估学生以前对技术的知识和态度,进行了初步测试。为了评估他们所学到的知识,我们对学生在课程中完成的期末项目进行了评估。本研究分析了这种学生形象的好处,表明除了获得新的专业知识外,他们还拓宽了在劳动力市场上的选择和机会。
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引用次数: 0
Innovative Active Blended Learning Pedagogy in Software Requirements Engineering Education 软件需求工程教育中的创新主动混合式学习教学法
IF 1 Q4 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2025-09-02 DOI: 10.1109/RITA.2025.3605317
Williamson Silva;Renato de Souza Garcia;Rodrigo Cargnelutti;Maicon Bernardino
Requirements Engineering (RE) represents a fundamental activity in the software development process. When executed correctly, RE can have a beneficial impact on the final software quality. Given the increasing demand for competent professionals in the software industry, adopting pedagogical strategies that effectively align theory and practice in teaching Requirements Engineering is imperative. This ensures the training of qualified professionals capable of successfully executing software projects. This paper reports our experience designing and enhancing an innovative proposal pedagogy to teach RE through active blended learning. We grounded our proposal on the Problem-Based Learning (PBL) methodology, which enables external community stakeholders to present real-world problems within the classroom environment. Students take on the role of requirements engineers and participate in various RE activities as they design their software solutions. Our pedagogical proposal combines PBL with other methodologies, e.g., Flipped Classroom, Diaries, and Gamification. We also provide evidence from a case study conducted in our course, in which we assess students’ perceptions of our approach. The results indicate increased student engagement, motivation, and performance, as well as improved understanding of RE concepts and their application to real-world problems. Additionally, we improved the active blended learning proposal based on our lessons learned and students’ perceptions. This work concludes that an active blended learning approach can significantly enhance RE education, offering a practical and adaptable strategy to foster both technical and soft skills among software engineering students. The main contributions of this study are (i) the design of a structured and replicable pedagogical framework for teaching RE using blended learning, (ii) the empirical evaluation of this framework through its implementation in two undergraduate cohorts, and (iii) the refinement of the framework based on lessons learned and student feedback.
需求工程(RE)代表了软件开发过程中的一个基本活动。如果执行正确,可重构可以对最终的软件质量产生有益的影响。鉴于软件行业对有能力的专业人员的需求不断增加,在教学需求工程中采用有效地将理论和实践结合起来的教学策略是必要的。这确保了培训合格的专业人员能够成功地执行软件项目。本文报告了我们设计和改进一种创新的提案教学法,通过主动混合学习来教授RE的经验。我们的建议基于基于问题的学习(PBL)方法,该方法使外部社区利益相关者能够在课堂环境中提出现实世界的问题。学生扮演需求工程师的角色,在设计软件解决方案时参与各种RE活动。我们的教学建议将PBL与其他方法相结合,例如翻转课堂、日记和游戏化。我们还提供了在我们的课程中进行的一个案例研究的证据,在这个案例中,我们评估了学生对我们方法的看法。结果表明,学生的参与度、积极性和表现都有所提高,对可再生能源概念及其在现实问题中的应用的理解也有所提高。此外,根据我们的经验教训和学生的看法,我们改进了主动混合式学习方案。这项工作的结论是,一种积极的混合学习方法可以显著地增强软件工程教育,为培养软件工程学生的技术和软技能提供了一种实用的、适应性强的策略。本研究的主要贡献是:(i)设计了一个结构化的、可复制的教学框架,用于使用混合学习进行RE教学;(ii)通过在两个本科生队列中实施该框架进行了实证评估;(iii)根据经验教训和学生反馈对框架进行了改进。
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引用次数: 0
Agile Production of Inclusive Learning Environments With Virtual Reality to Support Bachelor Students With Disabilities 敏捷生产的包容性学习环境与虚拟现实,以支持本科学生残疾
IF 1 Q4 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2025-08-22 DOI: 10.1109/RITA.2025.3601613
Alejandro Moreno-Cruz;Jaime Muñoz-Arteaga;Julio C. Ponce-Gallegos;Francisco L. Gutiérrez-Vela
Students with disabilities at the upper secondary level often encounter significant barriers to accessing and engaging with education. This study examines the use of the Design-Based Research (DBR) methodology to develop a virtual reality (VR) application prototype designed to address these challenges. Conducted within the Care Centers for Students with Disabilities (CAED) in Aguascalientes, Mexico, the project involved 18 students with different types of disabilities and their educators in an iterative design process. By utilizing VR technologies, the study aimed to enhance accessibility, student engagement, and academic outcomes for students with disabilities. The DBR approach facilitated continuous refinement of the prototype through iterative feedback cycles, promoting collaboration among researchers, educators, and students to ensure alignment with user needs. Results indicated increased motivation and academic performance for most participants, although significant visual impairments limited the tool’s effectiveness for two students. This paper details the design, implementation, and evaluation of the VR application, emphasizing the integration principles of inclusive education with advanced technologies. The findings highlight the potential of VR to create immersive, adaptive, and inclusive learning environments, providing valuable guidance for future advancements in educational technology.
高中阶段的残疾学生在接受教育和参与教育方面经常遇到重大障碍。本研究考察了基于设计的研究(DBR)方法的使用,以开发一个虚拟现实(VR)应用原型,旨在解决这些挑战。该项目在墨西哥Aguascalientes的残疾学生护理中心(CAED)内进行,涉及18名不同类型残疾的学生和他们的教育者,他们参与了一个迭代设计过程。通过利用VR技术,该研究旨在提高残疾学生的可访问性、学生参与度和学业成绩。DBR方法通过迭代反馈周期促进了原型的持续改进,促进了研究人员、教育工作者和学生之间的协作,以确保与用户需求保持一致。结果表明,大多数参与者的学习动机和学习成绩都有所提高,尽管严重的视觉障碍限制了该工具对两名学生的有效性。本文详细介绍了虚拟现实应用的设计、实现和评估,强调了融合教育与先进技术的融合原则。研究结果强调了VR在创造沉浸式、适应性和包容性学习环境方面的潜力,为未来教育技术的发展提供了有价值的指导。
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引用次数: 0
Design for Sustainability of Open Education Resources in the Era of AI: A Case Study 人工智能时代开放教育资源的可持续性设计:案例研究
IF 1 Q4 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2025-08-21 DOI: 10.1109/RITA.2025.3599123
Jhonattan Miranda;Johannes Freudenreich;Marie Schneider;Leonardo D. Glasserman-Morales
This study addresses the need to ensure the long-term sustainability of Open Educational Resources (OER) in educational environments shaped by Artificial Intelligence (AI). To respond to this challenge, we present the Design for Sustainability of Open Educational Resources (DfS-OER) model. The model is informed by sustainability literature and educational design theory, and it is structured to support practical application. It incorporates five sustainability dimensions: social, economic, environmental, pedagogical, and technological, each connected to a set of design principles. The model was applied in the design of a low-cost, AI-enhanced university course and validated through empirical implementation. Findings from the case study demonstrate that: (a) the model enabled consistent alignment between sustainability objectives and instructional design decisions; (b) the use of AI tools significantly reduced development time, particularly in translation and content generation; (c) inclusive design elements improved learner engagement and accessibility; and (d) the model supports the vision of Education 5.0 by enabling human-centered, scalable, and adaptive learning environments. The DfS-OER model offers a validated pathway for integrating sustainable design practices into digital education systems at scale.
本研究解决了在人工智能(AI)塑造的教育环境中确保开放教育资源(OER)长期可持续性的需求。为了应对这一挑战,我们提出了开放教育资源可持续性设计(DfS-OER)模型。该模型以可持续性文献和教育设计理论为依据,其结构支持实际应用。它结合了五个可持续性维度:社会、经济、环境、教学和技术,每个维度都与一套设计原则相关联。该模型被应用于低成本、人工智能增强的大学课程设计中,并通过实证实施进行了验证。案例研究的结果表明:(a)该模型使可持续发展目标与教学设计决策之间保持一致;(b)人工智能工具的使用大大缩短了开发时间,特别是在翻译和内容生成方面;(c)包容性设计元素提高了学习者的参与度和可及性;(d)该模型通过实现以人为本、可扩展和自适应的学习环境,支持教育5.0的愿景。DfS-OER模型为将可持续设计实践大规模整合到数字教育系统中提供了一条行之有效的途径。
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引用次数: 0
Empowering Financial Decision-Making With AI Agents: A Case Study on Critical Thinking Development 用人工智能代理授权财务决策:批判性思维发展的案例研究
IF 1 Q4 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Pub Date : 2025-08-19 DOI: 10.1109/RITA.2025.3600114
Karla Bayly-Castaneda;María-Soledad Ramirez-Montoya
Integrating Artificial Intelligence (AI) in education has opened new possibilities for personalized learning, yet its potential to develop higher-order thinking skills in specific domains such as financial literacy remains underexplored. This study investigates the impact of designing and using a personalized AI agent in a mobile application on developing critical thinking, decision-making autonomy, and financial behavior among undergraduate students. A qualitative exploratory case study was conducted with 27 students enrolled in a Personal Finance course at a private university in Mexico. Participants created their own AI-based financial planners using the Poe platform and reflected on the experience in responses to a structured questionnaire. Thematic content analysis using ATLAS.ti revealed that using AI agents produced (a) enhanced critical thinking through scenario-based simulations, (b) greater autonomy in financial planning and decision-making, (c) increased motivation for continued learning in personal finance, and (d) immediate adoption of financial actions to achieve long-term goals. This study contributes to the field by exploring how student-created AI agents can act as instructional tools and perceived catalysts for behavioral change. These findings are relevant for educators, instructional designers, and policymakers aiming to leverage emerging technologies to develop cognitive, and practical competencies in higher education.
将人工智能(AI)整合到教育中,为个性化学习开辟了新的可能性,但它在金融知识等特定领域培养高阶思维技能的潜力仍未得到充分开发。本研究探讨了在移动应用程序中设计和使用个性化人工智能代理对培养大学生批判性思维、决策自主权和金融行为的影响。对墨西哥一所私立大学个人理财课程的27名学生进行了定性探索性案例研究。参与者使用Poe平台创建了自己的基于人工智能的财务规划师,并在回答结构化问卷时反映了他们的经验。利用ATLAS进行专题内容分析。它显示,使用人工智能代理产生(a)通过基于场景的模拟增强批判性思维,(b)更大的财务规划和决策自主权,(c)增加继续学习个人理财的动机,以及(d)立即采取财务行动以实现长期目标。这项研究通过探索学生创建的人工智能代理如何作为教学工具和行为改变的感知催化剂,为该领域做出了贡献。这些发现对旨在利用新兴技术发展高等教育认知和实践能力的教育工作者、教学设计师和政策制定者具有重要意义。
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Revista Iberoamericana de Tecnologias del Aprendizaje
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