Modeling Exploratory Search as a Knowledge-Intensive Process

Tibau, Marcelo; Siqueira, Sean W. M.; Nunes, Bernardo Pereira; Bortoluzzi, Maria; Marenzi, Ivana

doi:10.1109/icalt.2018.00015

Cited by 6 publications

(3 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…No universo de aprendizagem pela busca, poucos são os trabalhos com o uso de ontologias ou que modelam um experimento CIS. Por exemplo, [Tibau et al 2018] faz uso da ontologia Knowledge Intensive Process Ontology (KIPO) para explorar elementos do conhecimento tácito do processo de aprendizagem. O trabalho apresenta um modelo de busca exploratória na web na formac ¸ão de professores de línguas, evoluindo e validando o modelo.…”

Section: Trabalhos Relacionadosunclassified

Uma ontologia para auxílio em ambientes colaborativos para busca de informações

Silva

David

Barrére

et al. 2021

Anais Do XXXII Simpósio Brasileiro De Informática Na Educação (SBIE 2021)

View full text Add to dashboard Cite

Os mecanismos de busca na web são fonte de estudo e aprendizado. Searching as Learning (SaL) e Collaborative Information Seeking (CIS) são áreas que analisam o aprendizado como um processo, sendo o segundo de forma colaborativa. A literatura demonstra a necessidade de mais estudos nessas áreas e melhor mapeamento do aprendizado dos alunos. O presente trabalho apresenta a CollabSO, uma ontologia que modela o contexto experimental em ambientes de busca colaborativa. Além disso, fornece suporte para persistência e realização da coordenação dos grupos de alunos. A ontologia visa dar suporte para análise pedagógica, ação dos professores e execução de experimentos CIS.

show abstract

Section: Trabalhos Relacionadosunclassified

Uma ontologia para auxílio em ambientes colaborativos para busca de informações

Silva

David

Barrére

et al. 2021

Anais Do XXXII Simpósio Brasileiro De Informática Na Educação (SBIE 2021)

View full text Add to dashboard Cite

show abstract

“…From the behavioral perspective, the use of techniques to reinforce search behavior, which is learningrelated (Harasim, 2011). From the cognitivist perspective, it is usually concerned IX Congresso Brasileiro de Informática na Educação (CBIE 2020) Anais do XXXI Simpósio Brasileiro de Informática na Educação (SBIE 2020) (Lu and Hsiao, 2017), (Zhuang et al, 2016), (Mao et al, 2016), (Moraes et al, 2018), (Wilson and Wilson, 2013) Cognitivist (Kodama et al, 2017), (Moraes et al, 2018), (Taibi et al, 2017), (Wilson et al, 2016), (Syed and Collins-Thompson, 2016), (Bhattacharya and Gwizdka, 2019), (Al-Tawil et al, 2019), (Azpiazu et al, 2017), (Crescenzi, 2016), (Han et al, 2019), (Liu and Song, 2018), (Johnson, 2018), (Jansen et al, 2007), (Smith and Rieh, 2019) Constructivist (Ghosh et al, 2018), (Tibau et al, 2018b), (Freund et al, 2016), (Komlodi and Caidi, 2016), (Weingart and Eickhoff, 2016), (Tibau et al, 2018a), (Yu et al, 2018b), (Al-Tawil et al, 2019) (Ibieta et al, 2019), (Zapata et al, 2015), (Zhang, 2017), (Meyers, 2018), (Cho et al, 2017), (Vakkari et al, 2019), (Ibieta et al, 2019) about information processing, search complexity and cognitive effort. From the constructivist perspective, it can be focused on what the learner can or cannot do without help, known as the zone of proximal development (Vygotsky et al, 1978).…”

Section: Learning Paradigms (Lp)mentioning

confidence: 99%

Investigating the learning perspective of Searching as Learning, a review of the state of the art

Gimenez¹,

Machado²,

Pinelli³

et al. 2020

Anais Do XXXI Simpósio Brasileiro De Informática Na Educação (SBIE 2020)

View full text Add to dashboard Cite

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.

show abstract

“…In this sense, users' behavior and the tasks they choose to perform are of great importance to achieve a successful outcome, that is why user's previous search experiences and background are pivotal to understand search intentions and information acquisition patterns. Under these circumstances, exploratory searches can be considered a Knowledge-Intensive Process (KiP) [Tibau et al 2018] and when applied to Search as Learning context, could be seen within the perspectives of either "searching to learn" and "learning to search" [Rieh et al 2016] [Vakkari 2016].…”

Section: Introductionmentioning

confidence: 99%

A comparison between Entity-Centric Knowledge Base and Knowledge Graph to Represent Semantic Relationships for Searching as Learning Situations

Tibau¹,

Siqueira²,

Nunes³

2019

Anais Dos Workshops Do VIII Congresso Brasileiro De Informática Na Educação (CBIE 2019)

Self Cite

View full text Add to dashboard Cite

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.1 ASK, Anomalous State of Knowledge.

show abstract

Modeling Exploratory Search as a Knowledge-Intensive Process

Cited by 6 publications

References 12 publications

Uma ontologia para auxílio em ambientes colaborativos para busca de informações

Uma ontologia para auxílio em ambientes colaborativos para busca de informações

Investigating the learning perspective of Searching as Learning, a review of the state of the art

A comparison between Entity-Centric Knowledge Base and Knowledge Graph to Represent Semantic Relationships for Searching as Learning Situations

Contact Info

Product

Resources

About