Investigating the learning perspective of Searching as Learning, a review of the state of the art
Resumo
Current search engines are not designed to facilitate learning as they do not lead the user to develop more complex skills. Searching as Learning (SAL) emerged as a research area from the intersection of information search and learning technologies in order to advance the study of searching as a learning process. However, we wonder how have the learning theories and approaches been explored in SAL. Through a systematic review of the literature, we identified 65 papers that report SAL solutions. We analyzed them, seeking to answer (i) which learning theories, approaches and methods support the searching as a learning process, and (ii) what metrics, procedures, or treatments were used to measure learning during the searching process. We uncover the learning perspective in the SAL literature, discussing the learning paradigms, the mechanisms influencing the learning process, the search session design for learning and the knowledge gain measurement strategies.Referências
Al-Tawil, M., Dimitrova, V., and Thakker, D. (2019). Using knowledge anchors to facilitate user exploration of data graphs. Semantic Web, pages 1–30.
Anderson, L. W., Krathwohl, D. R., Airasian, P., Cruikshank, K., Mayer, R., Pintrich, P., Raths, J., and Wittrock, M. (2001). A taxonomy for learning, teaching and assessing: A revision of bloom’s taxonomy.
Anderson, T. (2011). The theory and practice of online learning. AU Press, Athabasca University, Edmonton, Canada, 2th edition.
Azpiazu, I. M., Dragovic, N., Pera, M. S., and Fails, J. A. (2017). Online searching and learning: Yum and other search tools for children and teachers. Information Retrieval Journal, 20:524–545.
Bhattacharya, N. and Gwizdka, J. (2019). Measuring learning during search: Differences in interactions, eye-gaze, and semantic similarity to expert knowledge. In Proceedings of the 2019 Conference on Human Information Interaction and Retrieval, pages 63–71. ACM.
Cho, B.-Y., Woodward, L., Li, D., and Barlow, W. (2017). Examining adolescents’ strategic processing during online reading with a question-generating task. American Educational Research Journal, 54:691–724.
Cho, M.-H. and Shen, D. (2013). Self-regulation in online learning. Distance Education, 34(3):290–301.
Crescenzi, A. (2016). Metacognitive knowledge and metacognitive regulation in timeconstrained in information search. In SAL@ SIGIR, volume 1647.
Freund, L., Kopak, R., and O’Brien, H. (2016). The effects of textual environment on reading comprehension: Implications for searching as learning. Journal of Information Science, 42:79–93.
Gadiraju, U. (2018). A new age of search systems by ujwal gadiraju with martin vesely as coordinator: understanding knowledge gained by users through search. ACM SIGWEB Newsletter, page 4.
Gadiraju, U., Yu, R., Dietze, S., and Holtz, P. (2018). Analyzing knowledge gain of users in informational search sessions on the web. In Proceedings of the 2018 Conference on Human Information Interaction & Retrieval, pages 2–11. ACM.
Ghosh, S., Rath, M., and Shah, C. (2018). Searching as learning: Exploring search behavior and learning outcomes in learning-related tasks. In Proceedings of the 2018 Conference on Human Information Interaction & Retrieval, pages 22–31.
Han, Z., Hansen, P., Xu, H., and Luo, R. (2019). Examining the classification and evolution of novice users’ mental models of an academic database in the search task completion process. Journal of Information Science.
Hansen, P. and Rieh, S. Y. (2016). Recent advances on searching as learning: An introduction to the special issue.
Harasim, L. (2011). Learning Theory and Online Technologies. Routledge, New York, NY, 10001, 1st edition.
Herder, E. and Juvina, I. (2004). Discovery of individual user navigation styles. Proc. Workshop on Individual Differences in Adaptive Hypermedia, Held at AH2004.
Hinostroza, J. E., Ibieta, A., Labbe, C., and Soto, M. T. (2018). Browsing the internet to solve information problems: A study of students’ search actions and behaviours using a ‘think aloud’protocol. Education and Information Technologies, 23:1933–1953.
Hoppe, A., Holtz, P., Kammerer, Y., Yu, R., Dietze, S., and Ewerth, R. (2018). Current challenges for studying search as learning processes. In 7th Workshop on Learning & Education with Web Data (LILE2018), in conjunction with ACM Web Science 2018, Amsterdam, NL, 27 May, 2018.
Ibieta, A., Hinostroza, J. E., and Labbe, C. (2019). Improving students’ information problem-solving skills on the web through explicit instruction and the use of customized search software. Journal of Research on Technology in Education, pages 1–22.
Jansen, B. J., Smith, B., and Booth, D. (2007). Learning as a paradigm for understanding exploratory search. ESI 2007, page 72.
Johnson, F. (2018). From accessibility to assess-ability: An evaluation heuristic based on cognitive engagement in search. In International Conference on Information, pages 487–497. Springer.
Kitchenham, B. and Charters, S. (2007). Guidelines for performing systematic literature reviews in software engineering. Information and software technology.
Kodama, C., Jean, B. S., Subramaniam, M., and Taylor, N. G. (2017). Theres a creepy guy on the other end at google!: engaging middle school students in a drawing activity to elicit their mental models of google. Information Retrieval Journal, 20:403–432.
Komlodi, A. and Caidi, N. (2016). Learning in second-language searching. In SAL@SIGIR, volume 1647.
Lee, H.-J., Lee, J., Makara, K. A., Fishman, B. J., and Hong, Y.-I. (2015). Does higher education foster critical and creative learners? an exploration of two universities in south korea and the usa. Higher Education Research & Development, 34(1):131–146.
Lefrancois, G. (2012). Theories of Human Learning: What the Professor Said. PSY 361 Learning Series. Cengage Learning.
Liu, C., Gwizdka, J., Liu, J., Xu, T., and Belkin, N. J. (2010). Analysis and evaluation of query reformulations in different task types. In Proceedings of the 73rd ASIS&T Annual Meeting on Navigating Streams in an Information Ecosystem - Volume 47, ASIS&T’10, USA. American Society for Information Science.
Liu, C. and Song, X. (2018). How do information source selection strategies influence users’ learning outcomes’. In Proceedings of the 2018 Conference on Human Information Interaction & Retrieval, pages 257–260.
Lu, Y. and Hsiao, I.-H. (2017). Personalized information seeking assistant (pisa): from programming information seeking to learning. Information Retrieval Journal, 20:433–455.
Machado, M., Pinelli, C., and Siqueira, S. (2019). A evolução da área de busca como um processo de aprendizagem com base em um mapeamento sistemático. In Anais dos Workshops do Congresso Brasileiro de Informatica na Educação, pages 833-842. http://dx.doi.org/10.5753/cbie.wcbie.2019.833
Mao, J., Liu, Y., Zhang, M., and Ma, S. (2016). How does domain expertise affect users’ search processes in exploratory searches? In SAL@ SIGIR, volume 1647.
Marchionini, G. (2018). Search, sense making and learning: closing gaps. Information and Learning Science, 120.
Meyers, E. M. (2018). When search is (mis) learning: Analyzing inference failures in student search tasks. Proceedings of the Association for Information Science and Technology, 55:357–366.
Moraes, F., Putra, S. R., and Hauff, C. (2018). Contrasting search as a learning activity with instructor-designed learning. In Proceedings of the 27th ACM International Conference on Information and Knowledge Management, pages 167–176. ACM.
Petticrew, M. and Roberts, H. (2008). Systematic reviews in the social sciences: A practical guide. John Wiley & Sons.
Picciano, A. G. (2017). Theories and frameworks for online education: Seeking an integrated model. Online Learning, 21(3):166–190.
Pinelli, C., Tibau, M., and Siqueira, S. (2019). Google, se reordene e me ajude a aprender: Critérios de relevância para reordenar resultados de busca como um processo de aprendizagem. In Brazilian Symposium on Computers in Education (Simposio Brasileiro de Informática na Educação-SBIE), volume 30, pages 576-585. http://dx.doi.org/10.5753/cbie.sbie.2019.576
Rieh, S. Y., Collins-Thompson, K., Hansen, P., and Lee, H.-J. (2016). Towards searching as a learning process: A review of current perspectives and future directions. Journal of Information Science, 42(1):19–34.
Rieh, S. Y., Kim, Y.-M., and Markey, K. (2012). Amount of invested mental effort (aime) in online searching. Information Processing & Management, 48(6):1136–1150.
Schunk, D. H. (1991). Learning theories: An educational perspective. new york: Merrill.
Smith, C. L. and Rieh, S. Y. (2019). Knowledge-context in search systems: toward information-literate actions. In Proceedings of the 2019 Conference on Human Information Interaction and Retrieval, pages 55–62.
Syed, R. and Collins-Thompson, K. (2016). Optimizing search results for educational goals: Incorporating keyword density as a retrieval objective. In Second International Workshop on Search as Learning co-located with the 39th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2016), volume 1647.
Syed, R. and Collins-Thompson, K. (2018). Exploring document retrieval features associated with improved short- and long-term vocabulary learning outcomes. In CHIIR ’18 Proceedings of the 2018 Conference on Human Information Interaction & Retrieval, pages 191–200.
Taibi, D., Fulantelli, G., Marenzi, I., Nejdl, W., Rogers, R., and Ijaz, A. (2017). Sarweb: A semantic web tool to support search as learning practices and cross-language results on the web. In 2017 IEEE 17th International Conference on Advanced Learning Technologies (ICALT), pages 522–524.
Teixeira, C. P., Tibau, M., Siqueira, S. W. M., and Nunes, B. P. (2020). Reordering search results to support learning. In Popescu, E., Hao, T., Hsu, T.-C., Xie, H., Temperini, M., and Chen, W., editors, Emerging Technologies for Education, pages 361–369, Cham. Springer International Publishing. https://doi.org/10.1007/978-3-030-38778-5_39
Tibau, M., Siqueira, S. W., Nunes, B. P., Bortoluzzi, M., and Marenzi, I. (2018a). Modeling exploratory search as a knowledge-intensive process. In 2018 IEEE 18th International Conference on Advanced Learning Technologies (ICALT), pages 34–38. IEEE. https://doi.org/10.1109/ICALT.2018.00015
Tibau, M., Siqueira, S. W., Nunes, B. P., Bortoluzzi, M., Marenzi, I., and Kemkes, P. (2018b). Investigating users’ decision-making process while searching online and their shortcuts towards understanding. In International Conference on Web-Based Learning, pages 54–64. Springer. https://doi.org/10.1007/978-3-319-96565-9_6
Vakkari, P. (2016). Searching as learning: A systematization based on literature. Journal of Information Science, 42(1):7–18.
Vakkari, P., Volske, M., Potthast, M., Hagen, M., and Stein, B. (2019). Modeling the usefulness of search results as measured by information use. Information Processing & Management, 56:879–894.
Vygotsky, L., Cole, M., John-Steiner, V., Scribner, S., and Souberman, E. (1978). Mind in Society: Development of Higher Psychological Processes. Harvard University Press.
Weingart, N. and Eickhoff, C. (2016). Retrieval techniques for contextual learning. In SAL@ SIGIR.
Williamson, B., Eynon, R., and Potter, J. (2020). Pandemic politics, pedagogies and practices: digital technologies and distance education during the coronavirus emergency. Learning, Media and Technology, 45(2):107–114.
Wilson, M. J. and Wilson, M. L. (2013). A comparison of techniques for measuring sensemaking and learning within participant-generated summaries. Journal of the American Society for Information Science and Technology, 64:291–306.
Wilson, M. L., Ye, C., Twidale, M. B., Grasse, H., Rosenthal, J., and McKittrick, M. (2016). Search literacy: Learning to search to learn. In SAL@ SIGIR, volume 1647.
Wilson, T. D. (1999). Models in information behaviour research. Journal of Documentation, 55:249–270.
Yu, R., Gadiraju, U., and Dietze, S. (2018a). Detecting, understanding and supporting everyday learning in web search. arXiv preprint arXiv:1806.11046.
Yu, R., Gadiraju, U., Holtz, P., Rokicki, M., Kemkes, P., and Dietze, S. (2018b). Predicting user knowledge gain in informational search sessions. In SIGIR ’18 The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval, pages 75–84.
Zapata, A., Menendez, V. H., Prieto, M. E., and Romero, C. (2015). Evaluation and selection of group recommendation strategies for collaborative searching of learning objects. International Journal of Human-Computer Studies, 76:22 – 39.
Zhang, X. (2017). User perceived learning from interactive searching on big medical literature data. Big Data & Information Analytics, 2(2380-6966 2017 5 10):1.
Zhuang, M., Toms, E. G., and Demartini, G. (2016). Search behaviour before and after search success. In CEUR Workshop Proceedings, volume 1647. RheinischWestfaelische Technische Hochschule Aachen* Lehrstuhl Informatik V.
Anderson, L. W., Krathwohl, D. R., Airasian, P., Cruikshank, K., Mayer, R., Pintrich, P., Raths, J., and Wittrock, M. (2001). A taxonomy for learning, teaching and assessing: A revision of bloom’s taxonomy.
Anderson, T. (2011). The theory and practice of online learning. AU Press, Athabasca University, Edmonton, Canada, 2th edition.
Azpiazu, I. M., Dragovic, N., Pera, M. S., and Fails, J. A. (2017). Online searching and learning: Yum and other search tools for children and teachers. Information Retrieval Journal, 20:524–545.
Bhattacharya, N. and Gwizdka, J. (2019). Measuring learning during search: Differences in interactions, eye-gaze, and semantic similarity to expert knowledge. In Proceedings of the 2019 Conference on Human Information Interaction and Retrieval, pages 63–71. ACM.
Cho, B.-Y., Woodward, L., Li, D., and Barlow, W. (2017). Examining adolescents’ strategic processing during online reading with a question-generating task. American Educational Research Journal, 54:691–724.
Cho, M.-H. and Shen, D. (2013). Self-regulation in online learning. Distance Education, 34(3):290–301.
Crescenzi, A. (2016). Metacognitive knowledge and metacognitive regulation in timeconstrained in information search. In SAL@ SIGIR, volume 1647.
Freund, L., Kopak, R., and O’Brien, H. (2016). The effects of textual environment on reading comprehension: Implications for searching as learning. Journal of Information Science, 42:79–93.
Gadiraju, U. (2018). A new age of search systems by ujwal gadiraju with martin vesely as coordinator: understanding knowledge gained by users through search. ACM SIGWEB Newsletter, page 4.
Gadiraju, U., Yu, R., Dietze, S., and Holtz, P. (2018). Analyzing knowledge gain of users in informational search sessions on the web. In Proceedings of the 2018 Conference on Human Information Interaction & Retrieval, pages 2–11. ACM.
Ghosh, S., Rath, M., and Shah, C. (2018). Searching as learning: Exploring search behavior and learning outcomes in learning-related tasks. In Proceedings of the 2018 Conference on Human Information Interaction & Retrieval, pages 22–31.
Han, Z., Hansen, P., Xu, H., and Luo, R. (2019). Examining the classification and evolution of novice users’ mental models of an academic database in the search task completion process. Journal of Information Science.
Hansen, P. and Rieh, S. Y. (2016). Recent advances on searching as learning: An introduction to the special issue.
Harasim, L. (2011). Learning Theory and Online Technologies. Routledge, New York, NY, 10001, 1st edition.
Herder, E. and Juvina, I. (2004). Discovery of individual user navigation styles. Proc. Workshop on Individual Differences in Adaptive Hypermedia, Held at AH2004.
Hinostroza, J. E., Ibieta, A., Labbe, C., and Soto, M. T. (2018). Browsing the internet to solve information problems: A study of students’ search actions and behaviours using a ‘think aloud’protocol. Education and Information Technologies, 23:1933–1953.
Hoppe, A., Holtz, P., Kammerer, Y., Yu, R., Dietze, S., and Ewerth, R. (2018). Current challenges for studying search as learning processes. In 7th Workshop on Learning & Education with Web Data (LILE2018), in conjunction with ACM Web Science 2018, Amsterdam, NL, 27 May, 2018.
Ibieta, A., Hinostroza, J. E., and Labbe, C. (2019). Improving students’ information problem-solving skills on the web through explicit instruction and the use of customized search software. Journal of Research on Technology in Education, pages 1–22.
Jansen, B. J., Smith, B., and Booth, D. (2007). Learning as a paradigm for understanding exploratory search. ESI 2007, page 72.
Johnson, F. (2018). From accessibility to assess-ability: An evaluation heuristic based on cognitive engagement in search. In International Conference on Information, pages 487–497. Springer.
Kitchenham, B. and Charters, S. (2007). Guidelines for performing systematic literature reviews in software engineering. Information and software technology.
Kodama, C., Jean, B. S., Subramaniam, M., and Taylor, N. G. (2017). Theres a creepy guy on the other end at google!: engaging middle school students in a drawing activity to elicit their mental models of google. Information Retrieval Journal, 20:403–432.
Komlodi, A. and Caidi, N. (2016). Learning in second-language searching. In SAL@SIGIR, volume 1647.
Lee, H.-J., Lee, J., Makara, K. A., Fishman, B. J., and Hong, Y.-I. (2015). Does higher education foster critical and creative learners? an exploration of two universities in south korea and the usa. Higher Education Research & Development, 34(1):131–146.
Lefrancois, G. (2012). Theories of Human Learning: What the Professor Said. PSY 361 Learning Series. Cengage Learning.
Liu, C., Gwizdka, J., Liu, J., Xu, T., and Belkin, N. J. (2010). Analysis and evaluation of query reformulations in different task types. In Proceedings of the 73rd ASIS&T Annual Meeting on Navigating Streams in an Information Ecosystem - Volume 47, ASIS&T’10, USA. American Society for Information Science.
Liu, C. and Song, X. (2018). How do information source selection strategies influence users’ learning outcomes’. In Proceedings of the 2018 Conference on Human Information Interaction & Retrieval, pages 257–260.
Lu, Y. and Hsiao, I.-H. (2017). Personalized information seeking assistant (pisa): from programming information seeking to learning. Information Retrieval Journal, 20:433–455.
Machado, M., Pinelli, C., and Siqueira, S. (2019). A evolução da área de busca como um processo de aprendizagem com base em um mapeamento sistemático. In Anais dos Workshops do Congresso Brasileiro de Informatica na Educação, pages 833-842. http://dx.doi.org/10.5753/cbie.wcbie.2019.833
Mao, J., Liu, Y., Zhang, M., and Ma, S. (2016). How does domain expertise affect users’ search processes in exploratory searches? In SAL@ SIGIR, volume 1647.
Marchionini, G. (2018). Search, sense making and learning: closing gaps. Information and Learning Science, 120.
Meyers, E. M. (2018). When search is (mis) learning: Analyzing inference failures in student search tasks. Proceedings of the Association for Information Science and Technology, 55:357–366.
Moraes, F., Putra, S. R., and Hauff, C. (2018). Contrasting search as a learning activity with instructor-designed learning. In Proceedings of the 27th ACM International Conference on Information and Knowledge Management, pages 167–176. ACM.
Petticrew, M. and Roberts, H. (2008). Systematic reviews in the social sciences: A practical guide. John Wiley & Sons.
Picciano, A. G. (2017). Theories and frameworks for online education: Seeking an integrated model. Online Learning, 21(3):166–190.
Pinelli, C., Tibau, M., and Siqueira, S. (2019). Google, se reordene e me ajude a aprender: Critérios de relevância para reordenar resultados de busca como um processo de aprendizagem. In Brazilian Symposium on Computers in Education (Simposio Brasileiro de Informática na Educação-SBIE), volume 30, pages 576-585. http://dx.doi.org/10.5753/cbie.sbie.2019.576
Rieh, S. Y., Collins-Thompson, K., Hansen, P., and Lee, H.-J. (2016). Towards searching as a learning process: A review of current perspectives and future directions. Journal of Information Science, 42(1):19–34.
Rieh, S. Y., Kim, Y.-M., and Markey, K. (2012). Amount of invested mental effort (aime) in online searching. Information Processing & Management, 48(6):1136–1150.
Schunk, D. H. (1991). Learning theories: An educational perspective. new york: Merrill.
Smith, C. L. and Rieh, S. Y. (2019). Knowledge-context in search systems: toward information-literate actions. In Proceedings of the 2019 Conference on Human Information Interaction and Retrieval, pages 55–62.
Syed, R. and Collins-Thompson, K. (2016). Optimizing search results for educational goals: Incorporating keyword density as a retrieval objective. In Second International Workshop on Search as Learning co-located with the 39th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2016), volume 1647.
Syed, R. and Collins-Thompson, K. (2018). Exploring document retrieval features associated with improved short- and long-term vocabulary learning outcomes. In CHIIR ’18 Proceedings of the 2018 Conference on Human Information Interaction & Retrieval, pages 191–200.
Taibi, D., Fulantelli, G., Marenzi, I., Nejdl, W., Rogers, R., and Ijaz, A. (2017). Sarweb: A semantic web tool to support search as learning practices and cross-language results on the web. In 2017 IEEE 17th International Conference on Advanced Learning Technologies (ICALT), pages 522–524.
Teixeira, C. P., Tibau, M., Siqueira, S. W. M., and Nunes, B. P. (2020). Reordering search results to support learning. In Popescu, E., Hao, T., Hsu, T.-C., Xie, H., Temperini, M., and Chen, W., editors, Emerging Technologies for Education, pages 361–369, Cham. Springer International Publishing. https://doi.org/10.1007/978-3-030-38778-5_39
Tibau, M., Siqueira, S. W., Nunes, B. P., Bortoluzzi, M., and Marenzi, I. (2018a). Modeling exploratory search as a knowledge-intensive process. In 2018 IEEE 18th International Conference on Advanced Learning Technologies (ICALT), pages 34–38. IEEE. https://doi.org/10.1109/ICALT.2018.00015
Tibau, M., Siqueira, S. W., Nunes, B. P., Bortoluzzi, M., Marenzi, I., and Kemkes, P. (2018b). Investigating users’ decision-making process while searching online and their shortcuts towards understanding. In International Conference on Web-Based Learning, pages 54–64. Springer. https://doi.org/10.1007/978-3-319-96565-9_6
Vakkari, P. (2016). Searching as learning: A systematization based on literature. Journal of Information Science, 42(1):7–18.
Vakkari, P., Volske, M., Potthast, M., Hagen, M., and Stein, B. (2019). Modeling the usefulness of search results as measured by information use. Information Processing & Management, 56:879–894.
Vygotsky, L., Cole, M., John-Steiner, V., Scribner, S., and Souberman, E. (1978). Mind in Society: Development of Higher Psychological Processes. Harvard University Press.
Weingart, N. and Eickhoff, C. (2016). Retrieval techniques for contextual learning. In SAL@ SIGIR.
Williamson, B., Eynon, R., and Potter, J. (2020). Pandemic politics, pedagogies and practices: digital technologies and distance education during the coronavirus emergency. Learning, Media and Technology, 45(2):107–114.
Wilson, M. J. and Wilson, M. L. (2013). A comparison of techniques for measuring sensemaking and learning within participant-generated summaries. Journal of the American Society for Information Science and Technology, 64:291–306.
Wilson, M. L., Ye, C., Twidale, M. B., Grasse, H., Rosenthal, J., and McKittrick, M. (2016). Search literacy: Learning to search to learn. In SAL@ SIGIR, volume 1647.
Wilson, T. D. (1999). Models in information behaviour research. Journal of Documentation, 55:249–270.
Yu, R., Gadiraju, U., and Dietze, S. (2018a). Detecting, understanding and supporting everyday learning in web search. arXiv preprint arXiv:1806.11046.
Yu, R., Gadiraju, U., Holtz, P., Rokicki, M., Kemkes, P., and Dietze, S. (2018b). Predicting user knowledge gain in informational search sessions. In SIGIR ’18 The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval, pages 75–84.
Zapata, A., Menendez, V. H., Prieto, M. E., and Romero, C. (2015). Evaluation and selection of group recommendation strategies for collaborative searching of learning objects. International Journal of Human-Computer Studies, 76:22 – 39.
Zhang, X. (2017). User perceived learning from interactive searching on big medical literature data. Big Data & Information Analytics, 2(2380-6966 2017 5 10):1.
Zhuang, M., Toms, E. G., and Demartini, G. (2016). Search behaviour before and after search success. In CEUR Workshop Proceedings, volume 1647. RheinischWestfaelische Technische Hochschule Aachen* Lehrstuhl Informatik V.
Publicado
24/11/2020
Como Citar
GIMENEZ, Paulo Jose de Alcantara; MACHADO, Marcelo de Oliveira Costa; PINELLI, Cleber Pinelli ; SIQUEIRA, Sean Wolfgand Matsui.
Investigating the learning perspective of Searching as Learning, a review of the state of the art. In: SIMPÓSIO BRASILEIRO DE INFORMÁTICA NA EDUCAÇÃO (SBIE), 31. , 2020, Online.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2020
.
p. 302-311.
DOI: https://doi.org/10.5753/cbie.sbie.2020.302.
