IEEE Transactions on Learning Technologies最新文献

{"title":"Corrections to “A Tutorial-Generating Method for Autonomous Online Learning”","authors":"Xiang Wu;Huaqing Hong;Huanhuan Wang;Yongting Zhang;Baowen Zou","doi":"10.1109/TLT.2024.3413121","DOIUrl":"https://doi.org/10.1109/TLT.2024.3413121","url":null,"abstract":"Presents corrections to the article “A Tutorial-Generating Method for Autonomous Online Learning”.","PeriodicalId":49191,"journal":{"name":"IEEE Transactions on Learning Technologies","volume":"17 ","pages":"1761-1761"},"PeriodicalIF":2.9,"publicationDate":"2024-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10574490","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141495235","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ChatGPT-Based Learning Platform for Creation of Different Attack Model Signatures and Development of Defense Algorithm for Cyberattack Detection","authors":"Thulasi M. Santhi;K. Srinivasan","doi":"10.1109/TLT.2024.3417252","DOIUrl":"https://doi.org/10.1109/TLT.2024.3417252","url":null,"abstract":"Cloud adoption in industrial sectors, such as process, manufacturing, health care, and finance, is steadily rising, but as it grows, the risk of targeted cyberattacks has increased. Hence, effectively defending against such attacks necessitates skilled cybersecurity professionals. Traditional human-based cyber-physical education is resource intensive and faces challenges in keeping pace with rapidly evolving technologies. This research focuses on the main advantages of incorporating large language models into cyber-physical education. The ChatGPT platform serves as an online tool to educate students on fundamentals, cyberattacks, and defense concepts, fostering the development of a new generation cybersecurity experts. The proposed learning approach adheres to the ChatGPT-assisted learn–apply–create model. Responding to prompts provided by the learners, the learning phase engages in conceptual learning, the applying phase involves mathematical modeling of various cyberattacks, and the creating phase develops MATLAB program to incorporate attacks into sensor measurements for the experiment and entails developing the necessary attack detection approaches. The effectiveness of the detection method developed by ChatGPT is assessed in both the simulation and real-time scenarios using a J-type thermocouple. The impact of the proposed learning platform over traditional learning methods is evaluated through an extensive comparative feedback analysis on the learner's foundational concepts, computational thinking, programming efficacy, and motivation. The study proved that integrating ChatGPT into engineering education enables students to swiftly learn cyber-physical fundamentals, comprehend and model cyberattacks, create new attack signatures, and contribute to developing detection algorithms. Such integration provides the learners with essential industrial skills crucial in modern industries.","PeriodicalId":49191,"journal":{"name":"IEEE Transactions on Learning Technologies","volume":"17 ","pages":"1869-1882"},"PeriodicalIF":2.9,"publicationDate":"2024-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141500425","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Gamified Platform to Support Educational Activities About Fake News in Social Media","authors":"Sara Capecchi;Antonio Lieto;Federica Patti;Ruggero G. Pensa;Amon Rapp;Fabiana Vernero;Sandra Zingaro","doi":"10.1109/TLT.2024.3410088","DOIUrl":"https://doi.org/10.1109/TLT.2024.3410088","url":null,"abstract":"The amount of news on the web often confuses the ideas of the reader, who struggles to disentangle information that is sometimes contradictory and difficult to decipher. In the face of such an articulated scenario, the role played by schools is absolutely central: the development of critical thinking in young people (and by extension in their families) is a necessary condition for facing the complexity of the reality with the right awareness and control. Providing young people with a thorough understanding of the fake news spreading phenomenon is a first step in combating it. To this end, in this article, we propose a serious game whose objective is to let young people experience the typical interaction scenario when faced to a feed of real and fake news in social media. Our proposal focuses on educational workshops, carried out in secondary schools and dedicated to the correct use of information on the web, with particular attention to logical fallacies and cognitive bias mechanisms that lead to the formulation of erroneous reasoning or prevent a comparison from progressing logically. Thanks to an intuitive interface that helps the teacher supervise the whole game session, the students are invited to assess the truthfulness of a small set of news at different levels and to share them with their friends. At the end of the game session, the teacher is provided with an interactive detailed report of the activities that enables the analysis of all participants' actions and behavior. The teacher can use such a report to conduct a classroom lecture in a more engaging and interactive way, by stimulating discussions among the students and raising their curiosity on the subject. Our educational platform has been tested accurately in a broad experimental study involving 217 middle school students. The results show the suitability of the platform in providing a valuable educational tool for supporting educational activities on fake news analysis.","PeriodicalId":49191,"journal":{"name":"IEEE Transactions on Learning Technologies","volume":"17 ","pages":"1805-1819"},"PeriodicalIF":2.9,"publicationDate":"2024-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10550171","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141447981","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Attention Level Evaluation in Children With Autism: Leveraging Head Pose and Gaze Parameters From Videos for Educational Intervention","authors":"Elizabeth B. Varghese;Marwa Qaraqe;Dena Al-Thani","doi":"10.1109/TLT.2024.3409702","DOIUrl":"https://doi.org/10.1109/TLT.2024.3409702","url":null,"abstract":"In children with autism spectrum disorders (ASDs), assessing attention is crucial to understanding their behavioral and cognitive functioning. Attention difficulties are a common challenge for children with autism, significantly impacting their learning and social interactions. Traditional assessment methods often require skilled professionals to provide personalized interventions, which can be time consuming. In addition, existing approaches based on video and eye-tracking data have limitations in providing accurate educational interventions. This article proposes a noninvasive and objective method to assess and quantify attention levels in children with autism by utilizing head poses and gaze parameters. The proposed approach combines a deep learning model for extracting head pose parameters, algorithms to extract gaze parameters, machine learning models for the attention assessment task, and an ensemble of Bayesian neural networks for attention quantification. We conducted experiments involving 39 children (19 with ASD and 20 neurotypical children) by assigning various attention tasks and capturing their video and eye patterns using a webcam and an eye tracker. Results are analyzed for participant and task differences, which demonstrate that the proposed approach is successful in measuring a child's attention control and inattention. Ultimately, the developed attention assessment method using head poses and gaze parameters opens the door to developing real-time attention recognition systems that can enhance learning and provide targeted interventions.","PeriodicalId":49191,"journal":{"name":"IEEE Transactions on Learning Technologies","volume":"17 ","pages":"1777-1793"},"PeriodicalIF":3.7,"publicationDate":"2024-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141333988","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring ChatGPT's Ability to Classify the Structure of Literature Reviews in Engineering Research Articles","authors":"Maha Issa;Marwa Faraj;Niveen AbiGhannam","doi":"10.1109/TLT.2024.3409514","DOIUrl":"https://doi.org/10.1109/TLT.2024.3409514","url":null,"abstract":"ChatGPT is a newly emerging artificial intelligence (AI) tool that can generate and assess written text. In this study, we aim to examine the extent to which it can correctly identify the structure of literature review sections in engineering research articles. For this purpose, we conducted a manual content analysis by classifying paragraphs of literature review sections into their corresponding categories that are based on Kwan's model, which is a labeling scheme for structuring literature reviews. We then asked ChatGPT to perform the same categorization and compared both outcomes. Numerical results do not imply a satisfactory performance of ChatGPT; therefore, writers cannot fully depend on it to edit their literature reviews. However, the AI chatbot displays an understanding of the given prompt and is able to respond beyond the classification task by giving supportive and useful explanations for the users. Such findings can be especially helpful for beginners who usually struggle to write comprehensive literature review sections since they highlight how users can benefit from this AI chatbot to revise their drafts at the level of content and organization. With further investigations and advancement, AI chatbots can also be used for teaching proper literature review writing and editing.","PeriodicalId":49191,"journal":{"name":"IEEE Transactions on Learning Technologies","volume":"17 ","pages":"1859-1868"},"PeriodicalIF":2.9,"publicationDate":"2024-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141494861","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Embedding Educational Narrative Scripts in a Social Media Environment","authors":"Emily Theophilou;René Lobo-Quintero;Davinia Hernández-Leo;Roberto Sánchez-Reina;Dimitri Ognibene","doi":"10.1109/TLT.2024.3409063","DOIUrl":"https://doi.org/10.1109/TLT.2024.3409063","url":null,"abstract":"The impact of social media on teens’ mental health and development raises the need for educational interventions that equip them with the knowledge and skills to cope with dangerous situations. In spite of the growing effort to expand social media literacy among youngsters, social media interventions still rely on conventional methods that tend to prioritize cognitive skills while overlooking important socio-emotional competencies. To bridge this gap and offer innovative solutions to social media education, this article presents the narrative scripts (NS) approach implemented in a learning technology environment that integrates pedagogical strategies of authentic learning, narratives, and scripted collaborative learning within a simulated educational social media platform. A longitudinal study with 370 high school students in urban schools in Barcelona (Spain) was designed to assess NS in an intervention to foster the development of social media self-protection skills. The findings demonstrated that NS supported the development of social media self-protection skills, while the students expressed positive perceptions of their overall learning experience. The intervention notably enhanced the socio-emotional competencies of responsible decision-making, self-awareness, and social awareness. This research makes a valuable contribution to the design and development of technology aimed at facilitating authentic learning experiences for social media education, with a specific focus on interventions targeting socio-emotional competencies.","PeriodicalId":49191,"journal":{"name":"IEEE Transactions on Learning Technologies","volume":"17 ","pages":"1820-1833"},"PeriodicalIF":2.9,"publicationDate":"2024-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10547444","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141494902","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Leveraging Multi-Criteria Integer Programming Optimization for Effective Team Formation","authors":"Pallavi Singh, Phat K. Huynh, Dang Nguyen, Trung Q. Le, Wilfrido Moreno","doi":"10.1109/tlt.2024.3401734","DOIUrl":"https://doi.org/10.1109/tlt.2024.3401734","url":null,"abstract":"","PeriodicalId":49191,"journal":{"name":"IEEE Transactions on Learning Technologies","volume":"55 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2024-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141063023","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Can Autograding of Student-Generated Questions Quality by ChatGPT Match Human Experts?","authors":"Kangkang Li;Qian Yang;Xianmin Yang","doi":"10.1109/TLT.2024.3394807","DOIUrl":"10.1109/TLT.2024.3394807","url":null,"abstract":"The student-generated question (SGQ) strategy is an effective instructional strategy for developing students' higher order cognitive and critical thinking. However, assessing the quality of SGQs is time consuming and domain experts intensive. Previous automatic evaluation work focused on surface-level features of questions. To overcome this limitation, the state-of-the-art language models GPT-3.5 and GPT-4.0 were used to evaluate 1084 SGQs for topic relevance, clarity of expression, answerability, challenging, and cognitive level. Results showed that GPT-4.0 exhibits superior grading consistency with experts compared to GPT-3.5 in terms of topic relevance, clarity of expression, answerability, and difficulty level. GPT-3.5 and GPT-4.0 had low consistency with experts in terms of cognitive level. Over three rounds of testing, GPT-4.0 demonstrated higher stability in autograding when contrasted with GPT-3.5. In addition, to validate the effectiveness of GPT in evaluating SGQs from different domains and subjects, we have done the same experiment on a part of LearningQ dataset. We also discussed the attitudes of teachers and students toward automatic grading by GPT models. The findings underscore the potential of GPT-4.0 to assist teachers in evaluating the quality of SGQs. Nevertheless, the cognitive level assessment of SGQs still needs manual examination by teachers.","PeriodicalId":49191,"journal":{"name":"IEEE Transactions on Learning Technologies","volume":"17 ","pages":"1600-1610"},"PeriodicalIF":3.7,"publicationDate":"2024-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140826861","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Preserving Both Privacy and Utility in Learning Analytics","authors":"Chen Zhan;Srećko Joksimović;Djazia Ladjal;Thierry Rakotoarivelo;Ruth Marshall;Abelardo Pardo","doi":"10.1109/TLT.2024.3393766","DOIUrl":"10.1109/TLT.2024.3393766","url":null,"abstract":"Data are fundamental to Learning Analytics (LA) research and practice. However, the ethical use of data, particularly in terms of respecting learners' privacy rights, is a potential barrier that could hinder the widespread adoption of LA in the education industry. Despite the policies and guidelines of privacy protection being available worldwide, this does not guarantee successful implementation in practice. It is necessary to develop practical approaches that would allow for the translation of the existing guidelines into practice. In this study, we examine an initial set of privacy-preserving mechanisms on a large-scale education dataset. The data utility is evaluated before and after privacy-preserving mechanisms are applied by fitting into commonly used LA models, providing an evaluation of the utility loss. We further explore the balance between preserving data privacy and maintaining data utility in LA. The results prove the compatibility between preserving learners' privacy and LA, providing a benchmark of utility loss to practitioners and researchers in the education sector. Our study reminds an imminent concern of data privacy and advocates that privacy preserving can and should be an integral part of the design of any LA technique.","PeriodicalId":49191,"journal":{"name":"IEEE Transactions on Learning Technologies","volume":"17 ","pages":"1655-1667"},"PeriodicalIF":3.7,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140799519","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Scaffolding Computational Thinking With ChatGPT","authors":"Jian Liao;Linrong Zhong;Longting Zhe;Handan Xu;Ming Liu;Tao Xie","doi":"10.1109/TLT.2024.3392896","DOIUrl":"10.1109/TLT.2024.3392896","url":null,"abstract":"ChatGPT has received considerable attention in education, particularly in programming education because of its capabilities in automated code generation and program repairing and scoring. However, few empirical studies have investigated the use of ChatGPT to customize a learning system for scaffolding students’ computational thinking. Therefore, this article proposes an intelligent programming scaffolding system using ChatGPT following the theoretical framework of computational thinking and scaffolding. A mixed-method study was conducted to investigate the affordance of the scaffolding system using ChatGPT, and the findings show that most students had positive attitudes about the proposed system, and it was effective in improving their computational thinking generally but not their problem-solving skills. Therefore, more scaffolding strategies are discussed with the aim of improving student computational thinking, especially regarding problem-solving skills. The findings of this study are expected to guide future designs of generative artificial intelligence tools embedded in intelligent learning systems to foster students’ computational thinking and programming learning.","PeriodicalId":49191,"journal":{"name":"IEEE Transactions on Learning Technologies","volume":"17 ","pages":"1668-1682"},"PeriodicalIF":3.7,"publicationDate":"2024-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10508087","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140799691","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"教育学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}