Pub Date : 2023-03-14DOI: 10.1007/s40593-023-00331-8
Marcell Nagy, Roland Molontay
{"title":"Interpretable Dropout Prediction: Towards XAI-Based Personalized Intervention","authors":"Marcell Nagy, Roland Molontay","doi":"10.1007/s40593-023-00331-8","DOIUrl":"https://doi.org/10.1007/s40593-023-00331-8","url":null,"abstract":"","PeriodicalId":46637,"journal":{"name":"International Journal of Artificial Intelligence in Education","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2023-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"52844511","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-28DOI: 10.1007/s40593-022-00322-1
Rebecka Weegar, P. Idestam-Almquist
{"title":"Reducing Workload in Short Answer Grading Using Machine Learning","authors":"Rebecka Weegar, P. Idestam-Almquist","doi":"10.1007/s40593-022-00322-1","DOIUrl":"https://doi.org/10.1007/s40593-022-00322-1","url":null,"abstract":"","PeriodicalId":46637,"journal":{"name":"International Journal of Artificial Intelligence in Education","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42591469","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-14DOI: 10.1007/s40593-023-00330-9
P. Wulff, Lukas Mientus, Ann I. Nowak, Andreas Borowski
{"title":"Correction to: Utilizing a Pretrained Language Model (BERT) to Classify Preservice Physics Teachers’ Written Refections","authors":"P. Wulff, Lukas Mientus, Ann I. Nowak, Andreas Borowski","doi":"10.1007/s40593-023-00330-9","DOIUrl":"https://doi.org/10.1007/s40593-023-00330-9","url":null,"abstract":"","PeriodicalId":46637,"journal":{"name":"International Journal of Artificial Intelligence in Education","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2023-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49514561","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-31DOI: 10.1007/s40593-023-00328-3
K. VanLehn, Fabio Milner, Chandrani Banerjee, Jon Wetzel
{"title":"A Step-Based Tutoring System to Teach Underachieving Students How to Construct Algebraic Models","authors":"K. VanLehn, Fabio Milner, Chandrani Banerjee, Jon Wetzel","doi":"10.1007/s40593-023-00328-3","DOIUrl":"https://doi.org/10.1007/s40593-023-00328-3","url":null,"abstract":"","PeriodicalId":46637,"journal":{"name":"International Journal of Artificial Intelligence in Education","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2023-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47324087","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-25DOI: 10.1007/s40593-022-00325-y
Ramon Mayor Martins, C. G. von Wangenheim, Marcelo Fernando Rauber, J. Hauck
{"title":"Machine Learning for All!—Introducing Machine Learning in Middle and High School","authors":"Ramon Mayor Martins, C. G. von Wangenheim, Marcelo Fernando Rauber, J. Hauck","doi":"10.1007/s40593-022-00325-y","DOIUrl":"https://doi.org/10.1007/s40593-022-00325-y","url":null,"abstract":"","PeriodicalId":46637,"journal":{"name":"International Journal of Artificial Intelligence in Education","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2023-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46082263","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-10DOI: 10.1007/s40593-022-00326-x
Luiz Rodrigues, Paula T Palomino, Armando M Toda, Ana C T Klock, Marcela Pessoa, Filipe D Pereira, Elaine H T Oliveira, David F Oliveira, Alexandra I Cristea, Isabela Gasparini, Seiji Isotani
Personalized gamification aims to address shortcomings of the one-size-fits-all (OSFA) approach in improving students' motivations throughout the learning process. However, studies still focus on personalizing to a single user dimension, ignoring multiple individual and contextual factors that affect user motivation. Unlike prior research, we address this issue by exploring multidimensional personalization compared to OSFA based on a multi-institution sample. Thus, we conducted a controlled experiment in three institutions, comparing gamification designs (OSFA and Personalized to the learning task and users' gaming habits/preferences and demographics) in terms of 58 students' motivations to complete assessments for learning. Our results suggest no significant differences among OSFA and Personalized designs, despite suggesting user motivation depended on fewer user characteristics when using personalization. Additionally, exploratory analyses suggest personalization was positive for females and those holding a technical degree, but negative for those who prefer adventure games and those who prefer single-playing. Our contribution benefits designers, suggesting how personalization works; practitioners, demonstrating to whom the personalization strategy was more or less suitable; and researchers, providing future research directions.
Supplementary information: The online version contains supplementary material available at 10.1007/s40593-022-00326-x.
{"title":"How Personalization Affects Motivation in Gamified Review Assessments.","authors":"Luiz Rodrigues, Paula T Palomino, Armando M Toda, Ana C T Klock, Marcela Pessoa, Filipe D Pereira, Elaine H T Oliveira, David F Oliveira, Alexandra I Cristea, Isabela Gasparini, Seiji Isotani","doi":"10.1007/s40593-022-00326-x","DOIUrl":"10.1007/s40593-022-00326-x","url":null,"abstract":"<p><p>Personalized gamification aims to address shortcomings of the one-size-fits-all (OSFA) approach in improving students' motivations throughout the learning process. However, studies still focus on personalizing to a single user dimension, ignoring multiple individual and contextual factors that affect user motivation. Unlike prior research, we address this issue by exploring multidimensional personalization compared to OSFA based on a multi-institution sample. Thus, we conducted a controlled experiment in three institutions, comparing gamification designs (<i>OSFA</i> and <i>Personalized</i> to the learning task and users' gaming habits/preferences and demographics) in terms of 58 students' motivations to complete assessments for learning. Our results suggest no significant differences among OSFA and Personalized designs, despite suggesting user motivation depended on fewer user characteristics when using personalization. Additionally, exploratory analyses suggest personalization was positive for females and those holding a technical degree, but negative for those who prefer adventure games and those who prefer single-playing. Our contribution benefits designers, suggesting how personalization works; practitioners, demonstrating to whom the personalization strategy was more or less suitable; and researchers, providing future research directions.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1007/s40593-022-00326-x.</p>","PeriodicalId":46637,"journal":{"name":"International Journal of Artificial Intelligence in Education","volume":null,"pages":null},"PeriodicalIF":4.7,"publicationDate":"2023-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9838401/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9147117","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-01-01DOI: 10.1007/978-3-031-36272-9
{"title":"Artificial Intelligence in Education: 24th International Conference, AIED 2023, Tokyo, Japan, July 3–7, 2023, Proceedings","authors":"","doi":"10.1007/978-3-031-36272-9","DOIUrl":"https://doi.org/10.1007/978-3-031-36272-9","url":null,"abstract":"","PeriodicalId":46637,"journal":{"name":"International Journal of Artificial Intelligence in Education","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80931302","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-08DOI: 10.1007/s40593-022-00324-z
G. N. M. Santos, H. E. C. da Silva, Paulo Tadeu Figueiredo, C. R. Mesquita, N. Melo, C. Stefani, A. Leite
{"title":"The Introduction of Artificial Intelligence in Diagnostic Radiology Curricula: a Text and Opinion Systematic Review","authors":"G. N. M. Santos, H. E. C. da Silva, Paulo Tadeu Figueiredo, C. R. Mesquita, N. Melo, C. Stefani, A. Leite","doi":"10.1007/s40593-022-00324-z","DOIUrl":"https://doi.org/10.1007/s40593-022-00324-z","url":null,"abstract":"","PeriodicalId":46637,"journal":{"name":"International Journal of Artificial Intelligence in Education","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2022-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48790910","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This two-year study followed a professional learning community (PLC) of STEM Teachers Leaders, referred to as L-PLC. The onset of the COVID-19 pandemic accelerated changes in the focus of many professional development frameworks from face-to-face to online communication. We sought for new ways and tools to follow the professional development and the dynamics in our L-PLC. In particular, we explored professional knowledge development and social interactions, as derived from its WhatsApp group (43-48 participants) discourse, before and during the COVID-19 pandemic. Data were extracted from 6599 WhatsApp messages issued during four consecutive semesters (March 2019-March 2021), as well as from participant background questionnaires. The analysis incorporated both structure and content examination of the L-PLC WhatsApp discourse, using social network analysis (SNA), and a distinctive coding scheme followed by statistical analysis, heat map, and bar graph visualizations. These provided insights into whole group (macro), subgroups (meso), and individual (micro) profiles. The results indicated that over time, the participants gradually began to use the WhatsApp platform for professional purposes on top of its initial administrative intention. Moreover, the pandemic seemed to lead to a unique adjustment process, denoted by enhanced professional interactions, regarding content knowledge, professional content knowledge, and technological knowledge, and also accelerated the development of productive community behaviors, such as sharing and social support. The research approach enabled us to detect changes in key PLC characteristics, follow their dynamics under the influence of chaotic changes and navigate the community accordingly. Taken together, WhatsApp exchanges can serve as a rich source of data for a noninvasive continuous evaluation of group processes and progress.
Supplementary information: The online version contains supplementary material available at 10.1007/s40593-022-00320-3.
{"title":"WhatsApp Discourse Throughout COVID-19: Towards Computerized Evaluation of the Development of a STEM Teachers Professional Learning Community.","authors":"Zahava Scherz, Asaf Salman, Giora Alexandron, Yael Shwartz","doi":"10.1007/s40593-022-00320-3","DOIUrl":"10.1007/s40593-022-00320-3","url":null,"abstract":"<p><p>This two-year study followed a professional learning community (PLC) of STEM Teachers Leaders, referred to as L-PLC. The onset of the COVID-19 pandemic accelerated changes in the focus of many professional development frameworks from face-to-face to online communication. We sought for new ways and tools to follow the professional development and the dynamics in our L-PLC. In particular, we explored professional knowledge development and social interactions, as derived from its WhatsApp group (43-48 participants) discourse, before and during the COVID-19 pandemic. Data were extracted from 6599 WhatsApp messages issued during four consecutive semesters (March 2019-March 2021), as well as from participant background questionnaires. The analysis incorporated both structure and content examination of the L-PLC WhatsApp discourse, using social network analysis (SNA), and a distinctive coding scheme followed by statistical analysis, heat map, and bar graph visualizations. These provided insights into whole group (macro), subgroups (meso), and individual (micro) profiles. The results indicated that over time, the participants gradually began to use the WhatsApp platform for professional purposes on top of its initial administrative intention. Moreover, the pandemic seemed to lead to a unique adjustment process, denoted by enhanced professional interactions, regarding content knowledge, professional content knowledge, and technological knowledge, and also accelerated the development of productive community behaviors, such as sharing and social support. The research approach enabled us to detect changes in key PLC characteristics, follow their dynamics under the influence of chaotic changes and navigate the community accordingly. Taken together, WhatsApp exchanges can serve as a rich source of data for a noninvasive continuous evaluation of group processes and progress.</p><p><strong>Supplementary information: </strong>The online version contains supplementary material available at 10.1007/s40593-022-00320-3.</p>","PeriodicalId":46637,"journal":{"name":"International Journal of Artificial Intelligence in Education","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2022-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9734941/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10404413","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-12-01DOI: 10.1007/s40593-022-00321-2
Matías Rojas, Cristian Sáez, Jorge A. Baier, M. Nussbaum, Orlando Guerrero, María Fernanda Rodríguez
{"title":"Using Automated Planning to Provide Feedback during Collaborative Problem-Solving","authors":"Matías Rojas, Cristian Sáez, Jorge A. Baier, M. Nussbaum, Orlando Guerrero, María Fernanda Rodríguez","doi":"10.1007/s40593-022-00321-2","DOIUrl":"https://doi.org/10.1007/s40593-022-00321-2","url":null,"abstract":"","PeriodicalId":46637,"journal":{"name":"International Journal of Artificial Intelligence in Education","volume":null,"pages":null},"PeriodicalIF":4.9,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44405610","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}