Publicações
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YOUTUBE: Canal Marcelo Tibau
ARTIGOS CIENTÍFICOS:
15. Marcelo Tibau, Sean Wolfgand Matsui Siqueira, Bernardo Pereira Nunes, Accounting for the knowledge gained during a web search: An empirical study on learning transfer indicators, Library & Information Science Research, Volume 45, Issue 1, 2023, 101222, ISSN 0740-8188, https://doi.org/10.1016/j.lisr.2022.101222. (https://www.sciencedirect.com/science/article/pii/S0740818822000858).
Abstract: Searches with learning intent typically require the users to interact with the searching environment and perform knowledge acquisition features such as scan, read, and process the online content to fulfill their information needs. To capture indicators from searching behaviors that could account for the knowledge gained during a Web search, a qualitative study was performed using the Concurrent Think-Aloud protocol to observe the mechanisms of transfer and map knowledge flows during 78 search sessions. Findings indicate evidence of transfer of learning in the form of sixteen online information searching strategy indicators. This research aids the understanding of how knowledge is gained during search sessions and how to identify behaviors that could indicate that learning has occurred, which could be used to represent knowledge gain on Web search engines. In this way, it can aid search engines to become not only better tools of searching, but also tools of learning.
14. Marcelo Tibau, Sean Wolfgand Matsui Siqueira, and Bernardo Pereira Nunes. 2022. The Impact of Non-Verbalization in Think-Aloud: Understanding Knowledge Gain Indicators Considering Think-Aloud Web Searches. In Proceedings of the 33rd ACM Conference on Hypertext and Social Media (HT ’22). Association for Computing Machinery, New York, NY, USA, 107–120. https://doi.org/10.1145/3511095.3531272
Abstract: Web searching and knowledge gain are intertwined processes that share mental and physical activities at the core of both human cognition and hypertext theory, such as identifying, comparing, linking, and combining different subsets of existing or new information. As a consequence of the improvement of our ability to retrieve information across multiple sources provided by Web search engines, the necessity to understand how a user’s knowledge evolves through a Web search session increased. Previous works focused on understanding the knowledge gained in Web searches by using think-aloud protocols. From the user’s verbalization of her searching procedures, it is possible to identify her cognitive processing. Notwithstanding, we argue that user’s searching and browsing behaviors should be analyzed not only through the verbalization periods, as usually accepted by think-aloud studies, since not all cognitive decisions are made consciously, some are unconscious or subconscious. Hence, it is possible to identify more knowledge gained than it would be attainable focusing solely on what was verbalized. In this sense, we evaluated the statistical significance level derived from the relationship between verbal and non-verbal search periods mapped from online information searching strategy indicators. Then, we identified a positive association regarding non-verbalization and some indicators related to knowledge gain concepts and discovered that the values of non-verbal periods tend to increase as the values of particular indicators related to knowledge gain also increase. The knowledge gain concepts were identified using constructs representing cognitive absorption, comprehension, elaboration, and memory. Concerning the impact of Think-Aloud on knowledge gain processes, we found out that verbalization does affect how participants handle their search tasks. However, our result also showed a predominance of non-verbal periods during metacognitive-based searching activities, which may indicate that Think-Aloud protocols should not only rely on verbalization for indication of knowledge gain. Although verbalization may not disrupt the thought process, it might cut in on the cognitive process as the participant tries to explain her action while performing it. A search engine could use the identified indicators to account for the knowledge gained during search sessions, which would make it more adapted to identify user information needs and promote personalized information-adding.
13. Tibau, Marcelo; Wolfgand Matsui Siqueira, Sean; Pereira Nunes, Bernardo. Mapping Knowledge Flows in Exploratory Web Searches. The Hawaii International Conference on System Sciences (HICSS-55). 04 Jan 2022. ISBN: 978-0-9981331-5-7. URI: http://hdl.handle.net/10125/80007. DOI: 10.24251/HICSS.2022.669
Abstract: This paper provides an understanding of the knowledge flow in exploratory Web searches. Based on the Design Science Research epistemology, we represented the information-gathering behaviour and uncovered the knowledge flow of Web searchers as a Knowledge-intensive Process (KiP). By mapping searchers’ steps and paths during Web searches, representing their search patterns and decision-making process, it was possible to reveal the knowledge flow and infer the resources more likely to be selected to meet the searchers’ information needs. With the help of six teachers, we applied the Think-Aloud method in a scenario where they searched for online (educational) resources on the Web. The application of the Think-Aloud method made knowledge-flow processes explicit throughout Web searches. The results can support new strategies for information retrieval systems and be applied to support expertise exchange and innovation.
12. Marcelo Loutfi, Marcelo Tibau, Sean Wolfgand Matsui Siqueira, and Bernardo Pereira Nunes. 2021. CovidTrends: Identifying Behaviors during the COVID-19 Pandemic: An Analysis based on Google Trends and News. In XVII Brazilian Symposium on Information Systems (SBSI 2021). Association for Computing Machinery, New York, NY, USA, Article 5, 1–8. DOI: https://doi.org/10.1145/3466933.3466938
Abstract: This paper presents the identification of people’s behavioral changes during the Covid-19 pandemic period by analyzing the terms searched on Google’s Trend and news. We developed an artifact, called CovidTrends, used the DSR (Design Science Research) epistemological approach, the Design Science Research Methodology (DSRM), and the document analysis method to list infodemic or people’s behavioral trending of interest on Google and correlating them to news within the timeframe in which the terms’ queries peaked. CovidTrends enabled the identification of three main behaviors, which we verified on news reporting in the media. Then, it proves to be appropriate to support data analysis and identify people’s pandemic behavior.
11. Tibau M., Siqueira S.W.M., Nunes B.P. (2021) Think-Aloud Exploratory Search: Understanding Search Behaviors and Knowledge Flows. In: Visvizi A., Lytras M.D., Aljohani N.R. (eds) Research and Innovation Forum 2020. RIIFORUM 2020. Springer Proceedings in Complexity. Springer, Cham. https://doi.org/10.1007/978-3-030-62066-0_23
Abstract: This paper describes an experiment that uses Concurrent Think-Aloud protocol (CTA) and person-to-person interviews to map searching behaviors and knowledge flows during search sessions. The findings are: (1) the most used searching strategy during exploratory searches was the “Metacognitive Domain”; and (2) online searching experts have a fair ability to deal with ideas prompted by browsing the search results. The main contributions of this research lie in the understanding of the process in which people find, access, decide what content is useful and apply online data to their different information needs.
10. Tibau, M., Siqueira, S., & Nunes, B. (2020). Understanding Web Search Patterns Through Exploratory Search as a Knowledge-intensive Process. In Anais Estendidos do XVI Simpósio Brasileiro de Sistemas de Informação, (pp. 92-92). Porto Alegre: SBC. doi: 10.5753/sbsi.2020.13131
Abstract: To better understand users’ intent, Web search engines need to transcend its information sorter utility and acquire a more relevant ability concerning semantics’ discernment. This master thesis presents the Exploratory Search KiP model, which helps clarify the reasons why a subject is searched and supports the visualization of decision criteria used for choosing a specific search result. It also introduces the ESKiP Taxonomy of Query States; a classification framework that helps to represent the structure and behavior of query reformulation in search systems. As a result, the artifacts allowed to identify Web search and query reformulation patterns. The Exploratory Search KiP model also aided to distinguish three main behaviors involved in exploratory searches: (1) The ability to increase the level of familiarity with the topic and content searched (topic familiarity); (2) The ability to control the search process itself; and (3) The ability to assess the retrieved information relevance. For further reading: [Dias 2019] at UNIRIO’s repository. A summary article from the complete work was submitted to an international Information System Journal and is currently under review
9. Marcelo Tibau, Sean Wolfgand Matsui Siqueira, and Bernardo Pereira Nunes. 2020. Semantic Data Structures for Knowledge Generation in Open World Information System. In XVI Brazilian Symposium on Information Systems (SBSI’20), November 3–6, 2020, São Bernardo do Campo, Brazil. ACM, New York, NY, USA 7 Pages. https://doi.org/10.1145/3411564.3411611
Abstract: As the amount of information grows exponentially online, Information Systems role in support knowledge flows encouraged by linked data increases as a driver to innovation, culture, business practices and people behavior. Web search engines are particularly affected by the open world challenges, notably as part of the growing digital ecosystems of networks and platforms of technology, media, and telecommunications (TMT) companies delivering personalized and customized services (e.g. Amazon in retailing, Uber in ride service hailing, food delivery, and bicycle-sharing system, and Airbnb in lodging). To recognize search intent drawn from user’s behavior allows to provide personalized search results. The work presented in this paper has the purpose of exploring methods to represent semantic relationships between concepts indexed by Web search engines in order to aid them recognize search intent and display results that meet the search intent. The performance of two different types of data structures based on entity-centric indexing was compared. The data structures were: a knowledge base that used an entity-centric mapping of Wikipedia categories and the KBpedia Knowledge Graph. Through analysis of entity ranking and linking, we detected that the Knowledge Graph could identify approximately three times more properties and relationships, which increases Web search engines capability to “understand” what is being asked.
8. Teixeira C.P., Tibau M., Siqueira S.W.M., Nunes B.P. (2020) Reordering Search Results to Support Learning. In: Popescu E., Hao T., Hsu TC., Xie H., Temperini M., Chen W. (eds) Emerging Technologies for Education. SETE 2019. Lecture Notes in Computer Science, vol 11984. Springer, Cham.
Abstract: Although many learning activities involve search engines, their ranking criteria are focused on providing factual rather than procedural information. In the context of Searching as Learning, providing factual information may not be the best approach. In this paper, we discuss the relevance criteria according to traditional learning theories to support search engine results reordering based on content suitability to learning purposes. We proceeded on the investigation by selecting some self-proclaimed search literacy experts to answer thoroughly questions about their views on the reordered results. We take into account that literacy expert’s judgment may reveal issues regarded to technical side on learning supported by search tools. Experienced users claimed a preference for reliable sources and direct answers to what they are looking for, as they have exploratory skills to overcome information incompleteness.
DOI: https://doi.org/10.1007/978-3-030-38778-5_39
7. TIBAU, Marcelo; SIQUEIRA, Sean; NUNES, Bernardo Pereira. A comparison between Entity-Centric Knowledge Base and Knowledge Graph to Represent Semantic Relationships for Searching as Learning Situations. Anais dos Workshops do Congresso Brasileiro de Informática na Educação, [S.l.], p. 823, nov. 2019. ISSN 2316-8889. Disponível em: <https://br-ie.org/pub/index.php/wcbie/article/view/9032>.doi: http://dx.doi.org/10.5753/cbie.wcbie.2019.823.
Abstract: Searching the web with learning intent, known as Searching as Learning (SaL), consists on learners to use Web search engines as a technology to drive their learning process. However, it may be difficult to users to find out relevant information online due to an inability to accurately specify their information need, a situation known as Anomalous State of Knowledge (ASK). To minimize the ASK situation, the continuous flow of data gathering and interaction between user and the search results could be used by search engines to tailor learning-intent search experience. It requires Web search engines to identify such intent and they may use linked data, Knowledge Bases and Graph Databases in order to recognize the meaning of query terms and keywords and use them to predict learning intent. In order to explore the possibility of semantic data structures to represent knowledge that could aid a learning-driven Web search engine to recognize learning intention from user’s queries, the present paper compared the performance of two different types of data structures based on entity-centric indexing to identify properties and semantic relationships. One was a knowledge base that used a entity-centric mapping of Wikipedia categories and the other was the KBpedia Knowledge Graph. The entity ranking and linking of both were analyzed and we discovered that the knowledge graph could identify about three times more properties and relationships.
6. PINELLI, Cleber; TIBAU, Marcelo; SIQUEIRA, Sean. Google, se reordene e me ajude a aprender: Critérios de relevância para reordenar resultados de busca como um processo de aprendizagem. Brazilian Symposium on Computers in Education (Simpósio Brasileiro de Informática na Educação – SBIE), [S.l.], p. 576, nov. 2019. ISSN 2316-6533. Disponível em: <https://br-ie.org/pub/index.php/sbie/article/view/8762>. doi: http://dx.doi.org/10.5753/cbie.sbie.2019.576.
Abstract: As ferramentas de busca podem auxiliar as pessoas na condução de tarefas de aprendizagem informal, contudo os critérios usados para o ranqueamento de seus resultados estão voltados a prover respostas factuais e pouco processuais. Neste contexto, este artigo apresenta critérios de relevância, baseados em teorias de aprendizagem, para apoiar uma reordenação dos resultados da busca quando há intenção de aprendizado. Para avaliar a aplicabilidade da proposta, foi utilizado um questionário contendo um comparativo entre exemplos de páginas de resultado de busca da Google e sua versão modificada. A pesquisa evidenciou que o resultado reordenado foi melhor aceito, sobretudo por aqueles que possuem maior habilidade de busca. Isto pode ser um indicativo de que reorganizar o resultado de buscas com base em teorias de aprendizagem pode apoiar a aprendizagem informal.
5. M. Tibau, S. W. M. Siqueira, B. Pereira Nunes, T. Nurmikko-Fuller and R. F. Manrique, “Using Query Reformulation to Compare Learning Behaviors in Web Search Engines,” 2019 IEEE 19th International Conference on Advanced Learning Technologies (ICALT), Maceió, Brazil, 2019, pp. 219-223.
doi: 10.1109/ICALT.2019.00054
keywords: {query reformulation;query states;searching as learning;Web search engine;exploratory search;knowledge-intensive process},
URL: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8820932&isnumber=8820810
Abstract: Web search engines have gained importance as tools capable of connecting informal and self-learning with formal learning by aiding individuals in retrieving relevant information through the formulation and modification of their queries. Understand the differences between query states and their transitions becomes increasingly important, as doing so makes the optimization of search engines’ results according to educational uses and needs possible. This paper introduces the ESKiP Taxonomy of Query States, a classification framework validated in an experiment involving two different query log datasets. It enables the comparison between the behaviors of users in search for knowledge (learners) and users performing transactional or factual searches in Web search engines.
4. Marcelo Tibau, Sean W. M. Siqueira, Fernanda Baião and Bernardo Pereira Nunes. 2018. Exploratory Search as a Knowledge-intensive Process. Euro American Conference on Telematics and Information Systems (EATIS ’18), November 12–15, 2018, Fortaleza, Brazil, 8 pages.
Abstract: This paper presents an exploratory search model capable of assisting the visualization of search patterns and clarifying best practices associated to users’ decision-making process, with implications in areas related to information retrieval, human-computer interaction, Web searching and educational technology. The Exploratory Search Knowledge-Intensive Process model considers tasks and search activities as part of a chain of actions that help clarify the reasons why a subject is searched. It also supports the visualization on how the information retrieved is used to define decision criteria about which data is worth extracting, to draw inferences, and to create a shortcut to understanding.
DOI: https://doi.org/10.1145/3293614.3293618
3. ALMEIDA, R. S. ; SIQUEIRA, S.W.M. ; TIBAU, M., QUEIROZ, J.. A Correlation Index Between Two Different Text and Web Resource Classification Systems. In: 9th Euro-American Conference on Telematics and Information Systems (EATIS 2018), 2018, Fortaleza. PProceedings of the Euro American Conference on Telematics and Information Systems. Article No. 43
Abstract: Classifying content on the Web has been a common subject of research, since the amount of available data on the Web, especially in text format, grows every day. In this paper it is proposed a correlation index to measure how close a classification system based on Wikipedia categorization is of a service provided by Watson IBM that has the same purpose: text and resourceclassification on the Web.
2. Tibau, M. ; Siqueira, S.W.M. ; Nunes, B. P. ; Bortoluzzi, M. ; Marenzi, I. ; Kemkes, P. . Investigating users’ decision-making process while searching online and their shortcuts towards understanding. In: 17th International Conference on Web-based Learning, 2018, ChiangMai. Advances in Web-Based Learning (ICWL 2018), 17th International Conference, 2018.
Abstract: This paper presents how we apply Exploratory Search KiP model, a model capable of assisting the visualization of search patterns and identifying best practices associated to users’ decision-making processes, to log analysis and how it helps understand the process and decisions taken while carrying out a search. This study aims to model searches performed through web search tools and educational resources portals, to enable a conceptual framework to support and improve the processes of learning through searches. Applying the model to log analysis, we are able: (1) to see how the information retrieved is used to define decision criteria about which data are worth extracting; (2) to draw inferences and shortcuts to support understanding; (3) to observe how the search intention is modified during search activities; and, (4) to analyze how the purpose that drives the search turned into real actions.
DOI: doi.org/10.1007/978-3-319-96565-9_6
1. Tibau, M., Siqueira, S.W.M., Nunes, B.P., Marenzi, I., Bortoluzzi, M.: Modeling exploratory search as a knowledge-intensive process. In: 2018 Proceedings of the 18th IEEE International Conference on Advanced Learning Technologies (ICALT 2018), Mumbai. IEEE, New York (2018).
Abstract: Searching as Learning and Information Seeking require exploratory search to be modeled for supporting learning. The present paper introduces a model of exploratory search that was applied on web searching in language teacher education, which promoted its evolution and validation, and enabled a visualization of search pattern and learning process. This model was able to help clarify best practices associated to users’ decision-making process regarding suitable and not suitable information and to capture the relevance of context variables, personal skills and expertise that users utilize as filters for the search.
MASTER THESIS: Understanding web search patterns through exploratory search as a knowledge-intensive Process. [PDF]. MTV Dias – 2019 – repositorio-bc.unirio.br
Abstract: As data grows exponentially and the Web encompasses most part of the knowledge Human Beings create the seeking for intelligent information systems capable of going beyond keyword searches increases …
Resumo: À medida em que os dados na Web crescem exponencialmente e abrangem a maior parte do conhecimento produzido pela humanidade, a busca por sistemas de informação inteligentes capazes de irem além das buscas por palavras-chave aumenta …
DSc Qualifying: TIBAU, MARCELO. Degree of Knowledge Gain: transfer of learning and information added as measurement of knowledge gained in Web searches. UNIRIO, 2021. 112 páginas. Qualificação para Tese de Doutorado. Departamento de Informática Aplicada, UNIRIO.
Abstract: Searches with learning intent typically require the users to interact with the searching environment and perform knowledge acquisition features such as scan, read and process of online content in order to fulfill their information needs…
Resumo: Buscas com a intenção de aprender normalmente requerem que os usuários interajam com o ambiente de busca e executem tarefas para aquisição de conhecimento, como varredura, leitura e processamento de conteúdo online, para atenderem às suas necessidades de informação…
RELATÓRIOS TÉCNICOS
1. Tibau, M., Wolfgand Matsui Siqueira, S. ., S. N. Nunes, M. A., & Pereira Nunes, B. . (2022). A Systematic Mapping Study on Search Engine Industry’s Patent Innovations Focused on Matching the Search Results to User Intent. RelaTe-DIA, 15(1). URI: http://www.seer.unirio.br/monografiasppgi/article/view/11673
Abstract: This report presents a systematic mapping study to survey patent documents in Brazilian and international databases to characterize the technical state-of-the-art in search engines under the intent matching paradigm as well as to discover the size of academia initiatives as part of the technical state-of-the-art agenda to commercial innovation ventures in the search engine industry. The goal is achieved by the identification of the search engine industry most common innovation claims concerning the intent matching paradigm and by the discussion of important issues regarding its patent application patterns, such as the search engine industry’s proficiency to churn its innovative landscape.
VIDEOS
1. HT’22 (33rd ACM Conference on Hypertext and Social Media): Main Track – Conference Paper: The Impact of Non-Verbalization in Think-Aloud
Description: This is the presentation for the paper entitled “The Impact of Non-Verbalization in Think-Aloud: Understanding Knowledge Gain Indicators Considering Think-Aloud Web Searches”. In the paper, the authors identified a positive association regarding non-verbalization and some indicators related to knowledge gain concepts. They also discovered that the values of non-verbal periods tend to increase as the values of particular indicators related to knowledge gain also increase. The paper is presented by the researcher Marcelo Tibau from the Federal University of the State of Rio de Janeiro (UNIRIO).
Slides (public accessible link): HT22-paper5
Video (public accessible link): https://youtu.be/6bDYtKG1JU0
LIVRO: Conexão do Conhecimento – Conectar para gerar ideias, inovações e aprendizado
Por: R$ 40,43 (ebook: R$ 20,21)
ISBN: 978- 85-7773-840-3 ISBN (ebook): 644-00-0000-002-4
Formato: 14×21
N° de páginas: 156
Estamos em uma nova era da história da humanidade, saímos da Idade Contemporânea e entramos na Idade do Conhecimento. Ela se define por um fato muito simples, é cada vez mais fácil gerar algum tipo de conhecimento e distribuí-lo. Portanto, as pessoas, empresas e países que irão se destacar, serão aquelas que criarem consistentemente propriedade intelectual, conhecimento aplicável. Ao contrário do que se possa imaginar, o que vai crescer não é o conceito do Gerenciamento de Conhecimento e sim o da Conexão do Conhecimento, mesmo porque conhecimento não se gerencia, se difunde. O fato é que uma pessoa só vai compartilhar a sua experiência, que é o que a faz importante individualmente, se achar que vai contribuir e muito para a sua vida. E outra pessoa só vai querer aprender o conhecimento compartilhado por alguém, se este for relevante pra ela. Isso é Conexão e é sobre ela que se trata este livro.
Para comprar, clique no logo da editora (impresso) ou no logo do site Kobo (ebook):
IMAGENS E ESQUEMAS: Conexão do Conhecimento
Imagens e esquemas constantes no livro Conexão do Conhecimento – Conectar para gerar ideias, inovações e aprendizado em um arquivo pdf. O download do arquivo é gratuito, para tal basta clicar no ícone abaixo.
REPORT #1:
A Era da Inovação
Análise do estudo de Robert J. Gordon a respeito do constante fluxo de inovação que revolucionou o modo de vida do mundo entre 1870 e 1970. O download do arquivo é gratuito, para tal basta clicar no ícone abaixo.
INFOGRÁFICO N° 2:
Learning Analytics
Infográfico com o processo do modelo Learning Analytics. Disponibilizado originalmente por OpenColleges e adaptado para o português por tibau.org. O download do arquivo é gratuito, para tal basta clicar no ícone abaixo.
INFOGRÁFICO N° 1:
Flipped Classroom / Project-Based Learning
kit de infográficos com 2 modelos educacionais: Flipped Classroom e Project-Based Learning. O primeiro, estimula o desenvolvimento do pensamento crítico (que é entender o mundo à volta e a sua relação com ele) e o segundo, o pensamento reflexivo (criar algo novo a partir do seu conhecimento). Os infográficos trazem o passo a passo de implementação dos 2 modelos.
Marcelo Tibau 
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