Resumo
Este artigo apresenta um mapeamento sistemático de literatura (MSL) que classifica os Sistemas Tutores Inteligentes (STI) por áreas de conhecimento, com o objetivo de compreender sua distribuição e aplicação entre 1956 e 2023. Dos 907 casos de aplicações de STI mapeadas, 80% estão concentrados em seis áreas: Matemática, Letras, Ciência da Computação, Medicina, Engenharia Elétrica e Física. Por outro lado, é preocupante observar que 26 áreas de conhecimento não apresentaram qualquer registro de aplicações de STI. Essa ausência sugere uma lacuna de pesquisa e aplicação em uma ampla gama de disciplinas. A análise das publicações mais citadas nas principais áreas de conhecimento revelou obras-chave que influenciaram o campo. As implicações práticas incluem oportunidades para melhorar o aprendizado e o treinamento em diversas disciplinas.
Referências
AUSTRALIAN BUREAU OF STATISTICS (ABS). Australian and New Zealand Standard Research Classification (ANZSRC). 2015. Disponível em: https://www.abs.gov.au/statistics/classifications/australian-and-new-zealand-standard-research-classification-anzsrc/2020. Acesso em: 12 fev. 2024.
ADAMS, D. M.; MCLAREN, B. M.; DURKIN, K.; MAYER, R. E.; RITTLE-JOHNSON, B.; ISOTANI, S.; VAN, V. M. Using erroneous examples to improve mathematics learning with a web-based tutoring system. Computers in Human Behavior, v. 36, p. 401–411, 2014.
ALKHATLAN, A.; KALITA, J. Intelligent Tutoring Systems: A Comprehensive Historical Survey With Recent Developments. International Journal of Computer Applications, v. 181, n. 43, p. 1-20, 2019. Disponível em: https://doi.org/10.5120/ijca2019918451. Acesso em: 12 fev. 2024.
ALLEN, L. K.; CROSSLEY, S. A.; SNOW, E. L.; MCNAMARA, D. S. L2 writing practice: Game enjoyment as a key to engagement. Language Learning & Technology, v. 18, n. 2, p. 124-150, 2014.
AMARAL, L. A.; MEURERS, D. On using intelligent computer-assisted language learning in real-life foreign language teaching and learning. ReCALL, v. 23, n. 1, p. 4–24, 2011.
AMMON, U. Global scientific communication: Open questions and policy suggestions. AILA Review, v. 20, n. 1, p. 123-133, 2007.
ARCHAMBAULT, É.; LARIVIÈRE, V. History of the journal impact factor: Contingencies and consequences. Scientometrics, v. 79, n. 3, p. 635-649, 2009. DOI: https://doi.org/10.1007/s11192-007-2036-x. Acesso em: 10 fev. 2024.
ARROYO, I.; WOOLF, B. P.; BURELSON, W.; MULDNER, K.; RAI, D.; TAI, M. A multimedia adaptive tutoring system for mathematics that addresses cognition, metacognition and affect. International Journal of Artificial Intelligence in Education, v. 24, n. 3, p. 387–426, 2014. Disponível em: https://doi.org/10.1007/s40593-014-0023-y. Acesso em: 13 fev. 2024.
BAAS, J.; SCHOTTEN, M.; PLUME, A.; CÔTÉ, G.; KARIMI, R. Scopus as a curated, high-quality bibliometric data source for academic research in quantitative science studies. Quantitative Science Studies, v. 1, n. 1, p. 377-386, 2020. DOI: https://doi.org/10.1162/qss_a_00019. Acesso em: 11 fev. 2024.
BEAUMONT, I. H. User modelling in the interactive anatomy tutoring system anatomtutor. User Modeling and User-Adapted Interaction, v. 4, n. 1, p. 21–45, 1994.
BOTANA, F.; HOHENWARTER, M.; JANICˇIC´, P.; KOVÁCS, Z.; PETROVIC´, I.; RECIO, T.; WEITZHOFER, S. Automated theorem proving in geogebra: Current achievements. Journal of Automated Reasoning, v. 55, n. 1, p. 39–59, 2015. Disponível em: https://idp.springer.com/authorize/casa?redirect_uri=https://link.springer.com/content/pdf/10.1007/s10817-015-9326-4.pdf&casa_token=x6NOUGWSmrEAAAAA:PMS_Zb6PMbp-nwCkT2ScPwoG3eaot86ZKGwevZtHQTBkjCf1V9MO7tD7QQPvYSikGFS57NUHOJfu-XfGIg. Acesso em: 12 fev. 2024.
BRASIL. Lei nº 14.533 de 11 de janeiro de 2023. Dispões sobre a Política Nacional de Educação Digital (PNED). Brasília, 2023. Disponível em: https://www.planalto.gov.br/ccivil_03/_ato2023-2026/2023/lei/L14533.htm. Acesso em: 23 mar. 2024.
CALVO, R. A.; O’ROURKE, S. T.; JONES, J.; YACEF, K.; REIMANN, P. Collaborative writing support tools on the cloud. IEEE Transactions on Learning Technologies, v. 4, n. 1, p. 88–97, 2010.
CASELLA, G.; MCGRATH, A. R. Reducing bias in observational studies using subclassification on the propensity score. Journal of the American Statistical Association, v. 100, n. 471, p. 516-524, 2005.
CHEN, L.H. Enhancement of student learning performance using personalized diagnosis and remedial learning system. Computers & Education, v. 56, n. 1, p. 289–299, 2011.
CONATI, C.; GERTNER, A.; VANLEHN, K. Using bayesian networks to manage uncertainty in student modeling. User modeling and user-adapted interaction, v. 12, n. 4, p. 371–417, 2002. Disponível em: https://link.springer.com/content/pdf/10.1023/A:1021258506583.pdf Acesso em: 14 fev. 2024.
CNPq - CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO. Classificação das áreas de conhecimento. CNPq. 2020. Disponível em: https://estatico.cnpq.br/bi/CNPQ/DadosAbertos/Tabelas/AreaConhecimento/area_conhecimento.csv. Acesso em: 13 fev. 2024.
CORBETT, A. T.; ANDERSON, J. R. Knowledge tracing: Modeling the acquisition of procedural knowledge. User modeling and user-adapted interaction, v. 4, n. 4, p. 253–278, 1994.
CROW, T.; LUXTON-REILLY, A.; WUENSCHE, B. Intelligent tutoring systems for programming education. Proceedings Of The 20th Australasian Computing Education Conference On - Ace '18, [s.l.], p.53-62, 2018. ACM Press. Disponível em: https://dl.acm.org/doi/10.1145/3160489.3160492. Acesso em 20 mar. 2024.
CROWLEY, R. S.; MEDVEDEVA, O. An intelligent tutoring system for visual classification problem solving. Artificial intelligence in medicine, v. 36, n.1, p. 85–117, 2006.
DE GRANDA-ORIVE, J. I.; ALONSO-ARROYO, A.; ROIG-VÁZQUEZ, F. Which data base should be used for bibliometric analysis of research on tobacco addiction? Web of Science versus SCOPUS. Archivos de Bronconeumología (English Edition), v. 4, n. 47, p. 213, 2011. Disponível em: https://pubmed.ncbi.nlm.nih.gov/21281995. Acesso em: 23 fev. 2024.
D’MELLO, S. A selective meta-analysis on the relative incidence of discrete affective states during learning with technology. Journal of educational psychology, v. 105, n. 4, p. 1082, 2013.
DUFFY, M. C.; AZEVEDO, R. Motivation matters: Interactions between achievement goals and agent scaffolding for self-regulated learning within an intelligent tutoring system. Computers in Human Behavior, v. 52, p. 338–348, 2015. DOI: https://doi.org/10.1016/j.chb.2015.05.041.
DZIKOVSKA, M.; ZDRAVKOVIC, S.; VANLEHN, K. Beetle ii: Deep natural language understanding and automatic feedback generation for intelligent tutoring in basic electricity and electronics. International Journal of Artificial Intelligence in Education, v. 24, n. 2, p. 284–332, 2014.
ESCO - EUROPEAN SKILLS, COMPETENCES, QUALIFICATIONS AND OCCUPATIONS. International Standard Classification of Education Fields of Education and Training. ESCO. 2022. Disponível em: https://esco.ec.europa.eu/en/about-esco/escopedia/escopedia/international-standard-classification-education-fields-education-and/. Acesso em: 23 fev. 2024.
FORBUS, K.D.; WHALLEY, P.B.; EVERETT, J.O.; UREEL, L.; BROKOWSKI, M.; BAHER, J.; KUEHNE, S.E. Cyclepad: An articulate virtual laboratory for engineering thermodynamics. Artificial Intelligence, v.114, n.1-2, p. 297–347, 1999.
GIBBS, W. W. Lost science in the third world. Scientific American, v. 269, n.2, p. 76-83, 2003.
HILLMAYR, D.; ZIERNWALD, L.; REINHOLD, F.; HOFER, S. I.; REISS, K. M. The potential of digital tools to enhance mathematics and science learning in secondary schools: A context-specific meta-analysis. Computers & Education, v. 153, p.103897, 2020.
HOOSHYAR, D.; AHMAD, R. B.; YOUSEFI, M.; FATHI, M.; HORNG, S.J.; LIM, H. Applying an online game-based formative assessment in a flowchart-based intelligent tutoring system for improving problem-solving skills. Computers & Education, v. 94, p.18–36, 2016.
HSIEH, S.J.; YEEHSIEH, P. Integrated virtual learning system for programmable logic controller. Journal of Engineering Education, v. 93, n.2, p.169-178, 2004.
JOHNSON, W. L. Serious use of a serious game for language learning. International Journal of Artificial Intelligence in Education, v. 20, n. 2, p. 175-195, 2007.
KEELE, S. et al. Guidelines for performing systematic literature reviews in software engineering (Tech. Rep.). Technical report, Ver. 2.3 EBSE Technical Report. EBSE. 2007.
KITCHENHAM, B.; CHARTERS, S. et al. Guidelines for performing systematic literature reviews in software engineering. EBSE Technical Report EBSE-2007-01. Keele University and Durham University, UK. 2007.
LACAVE, C.; LUQUE, M.; DIEZ, F. J. Explanation of bayesian networks and influence diagrams in elvira. IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics), v. 37, n. 4, p. 952–965, 2007.
LAMGRIDGE, D. Classificação: uma abordagem para estudantes de Bibliotecnomia. Rio de Janeiro: Interciência, 1978.
LATHAM, A.; CROCKETT, K.; MCLEAN, D. An adaptation algorithm for an intelligent natural language tutoring system. Computers & Education, v. 71, p. 97–110, 2014.
LEE, S.; NOH, H.; LEE, J.; LEE, K.; LEE, G. G.; SAGONG, S.; KIM, M. On the effectiveness of robot-assisted language learning. ReCALL, v. 23, n. 1, p. 25–58, 2011.
LILLIS, T.; CURRY, M. J. (2010). Academic writing in a global context: The politics and practices of publishing in English. Routledge.
MCCARTHY, J.; MINSKY, M. L.; ROCHESTER, N.; SHANNON, C. E. A proposal for the dartmouth summer research project on artificial intelligence, august 31, 1955. AI magazine, v. 27, n. 4, p. 12-14, 2006.
MCNAMARA, D. S.; CROSSLEY, S. A.; ROSCOE, R. Natural language processing in an intelligent writing strategy tutoring system. Behavior research methods, v. 45, p. 499–515, 2013. DOI: https://doi.org/10.3758/s13428-012-0258-1. Acesso em: 23 fev. 2024.
MICHEL, M. S.; KNOLL, T.; KÖHRMANN, K.; ALKEN, P. The uro mentor: development and evaluation of a new computer-based interactive training system for virtual life-like simulation of diagnostic and therapeutic endourological procedures. BJU international, v. 89, n. 3, p. 174–177, 2002.
MITNIK, R.; RECABARREN, M.; NUSSBAUM, M.; SOTO, A. Collaborative robotic instruction: A graph teaching experience. Computers & Education, v. 53, n. 2, p. 330–342, 2009.
MITROVIC, A.; MARTIN, B.; MAYO, M. Using evaluation to shape its design: Results and experiences with sql-tutor. User Modeling and User-Adapted Interaction, v. 12, p. 243– 279, 2002.
MOHAMED, H.; LAMIA, M. Implementing flipped classroom that used an intelligent tutoring system into learning process. Computers & Education, v. 124, p.62–76, 2018. DOI: https://doi.org/10.1016/j.compedu.2018.05.011. Acesso em: 23 fev. 2024.
MOSTOW, J.; BECK, J. Some useful tactics to modify, map and mine data from intelligent tutors. Natural Language Engineering, v.12. n. 2, p.195–208, 2006.
MOUSAVINASAB, E.; ZARIFSANAIEY, N.; R. NIAKAN KALHORI, S.; RAKHSHAN, M.; KEIKHA, L.; GHAZI, S.M. Intelligent tutoring systems: a systematic review of characteristics, applications, and evaluation methods. Interactive Learning Environments, v. 29, n. 1, p. 142–163, 2021.
NWANA, H. S. Intelligent tutoring systems: an overview. Artificial Intelligence Review, v. 4, n. 4, p. 251–277, 1990.
OECD. Manual de Frascati: Proposed standard practice for surveys on research and experimental development. OECD Publishing, 2002. Acesso em: https://www.oecd-ilibrary.org/docserver/9789264239012-en.pdf?expires=1708052022&id=id&accname=guest&checksum=1DD3AA43FF91B9CFE3CB21E0AFC50A7C. Acesso em: 24 fev. 2024.
PAASSEN, B.; MOKBEL, B.; HAMMER, B. Adaptive structure metrics for automated feedback provision in intelligent tutoring systems. Neurocomputing, v. 192, p. 3-13, 2016. DOI: https://doi.org/10.1016/j.neucom.2015.12.108. Acesso em: 23 fev. 2024.
PETERSEN, K.; VAKKALANKA, S.; KUZNIARZ, L. Guidelines for conducting systematic mapping studies in software engineering: An update. Information and software technology, v.64, n. , p.1–18, 2015.
RACHELS, J. R.; ROCKINSON-SZAPKIW, A. J. The effects of a mobile gamification app on elementary students’ spanish achievement and self-efficacy. Computer Assisted Language Learning, v.31, n. 1-2, p. 72–89, 2018.
ROSCOE, R. D.; ALLEN, L. K.; WESTON, J. L.; CROSSLEY, S. A.; MCNAMARA, D. S. The writing pal intelligent tutoring system: Usability testing and development. Computers and Composition, v.34, p.39–59, 2014. DOI: https://doi.org/10.1016/j.compcom.2014.09.002. Acesso em: 26 fev. 2024.
SARRAFZADEH, A.; ALEXANDER, S.; DADGOSTAR, F.; FAN, C.; BIGDELI, A. “How do you know that I don’t understand?” a look at the future of intelligent tutoring systems. Computers in Human Behavior, v.24, n.4, p.1342–1363, 2008.
SHUTE, V. J.; PSOTKA, J. . Intelligent tutoring systems: Past, present, and future. Texas: Armstrong Laboratory, 1994.
STEENBERGEN-HU, S.; COOPER, H. A meta-analysis of the effectiveness of intelligent tutoring systems on college students’ academic learning. Journal of educational psychology, v. 106, n. 2, p. 331, 2014.
SURAWEERA, P.; MITROVIC, A. An intelligent tutoring system for entity relationship modelling. International Journal of Artificial Intelligence in Education, v. 14, n. 3-4, p. 375–417, 2004.
SWALES, J. English as Tyrannosaurus rex. World Englishes, v.16, n.3, p. 373-382, 1997.
UNESCO. International Standard Classification of Education: Fields of education and training 2013 (ISCED-F 2013). 2013. UNESCO. 2013. Disponível em: https://uis.unesco.org/sites/default/files/documents/international-standard-classification-of-education-fields-of-education-and-training-2013-detailed-field-descriptions-2015-en.pdf. Acesso em: 25 fev. 2023.
UNESCO. Relatório de monitoramento global da educação. UNESCO. 2023. Disponível em: http://unesdoc.unesco.org/images/0018/001873/187336por.pdf. Acesso em: 23 fev. 2024.
VANLEHN, K.; JONES, R.; SILER, C.; JORDAN, P.; LITMAN, D.; ROSE, C. The andes physics tutoring system: Lessons learned. International Journal of Artificial Intelligence in Education, v. 15, n. 3, p. 147–204, 2005.
VISSER, M.; VAN ECK, N. J.; WALTMAN, L. Large-scale comparison of bibliographic data sources: Scopus, Web of Science, Dimensions, Crossref, and Microsoft Academic. Quantitative Science Studies, v. 1, n. 1, p. 377-386, 2020. DOI: https://doi.org/10.1162/qss_a_00019. Acesso em: 23 fev. 2024.
WALKER, E.; RUMMEL, N.; KOEDINGER, K. R. Adaptive intelligent support to improve peer tutoring in algebra. International Journal of Artificial Intelligence in Education, v. 24, p. 33–61, 2014. DOI: https://doi.org/10.1007/s40593-013-0001-9. Disponível em: https://link.springer.com/article/10.1007/s40593-013-0001-9. Acesso em: 26 fev. 2024.
WARD, W.; COLE, R. A.; BOLAÑOS, D.; BUCHENROTH, J.; LI, K.; ZHAO, K. My science tutor: A conversational multimedia virtual tutor for elementary school science. ACM Transactions on Speech and Language Processing (TSLP), v. 7, n. 4, p. 1–29, 2011.
WIJEKUMAR, K. K.; MEYER, B. J.; LEI, P. Large-scale randomized controlled trial with 4th graders using intelligent tutoring of the structure strategy to improve nonfiction reading comprehension. Educational Technology Research and Development, v. 60, p. 987–1013, 2012. Disponível em: https://idp.springer.com/authorize/casa?redirect_uri=https://link.springer.com/article/10.1007/s11423-012-9263-4&casa_token=jOwh7fKWpocAAAAA:UiWFICQbp37ZQstMFs1jz-t8i8xIEvtmncWKmjnxR7yLIOfp4bvaONAJlZX8bgjYl3FA4V2elplvKTfNwA. Acesso em: 27 fev. 2024.
WOLFE, C. R.; REYNA, V. F.; WIDMER, C. L.; CEDILLOS, E. M.; FISHER, C. R.; BRUST-RENCK, P. G.; WEIL, A. M. Efficacy of a web-based intelligent tutoring system for communicating genetic risk of breast cancer: A fuzzy-trace theory approach. Medical Decision Making, v. 35, n1, p. 46–59, 2015.
WU, Q. Designing a smartphone app to teach english (l2) vocabulary. Computers & Education, v. 85, p. 170–179, 2015. Disponível em: https://www.sciencedirect.com/science/article/pii/S0360131515000652?casa_token=cvBrpHAoeF4AAAAA:V53ugMSc-YU2bBe-HA3sj0rOKVgE80DqiikoZZvCwi4M_hKqtByLWYTHdkN7ZplEG0vidfJuQmo. Acesso em: 28 fev. 2024.
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