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Sindunuraga Rikarno Putra

dblp:222/1215 · DBLP profile ↗
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2ranked-venue papers
1as first author
0since 2021 · last 2018
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Databases, data management, data science and information retrieval · 2 · 1 first-authorArtificial intelligence and machine learning · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Databases, data mining, and information retrieval
1 paper
Information retrieval · 100%
Human-computer interaction and pervasive computing
1 paper
Collaborative and social computing · 100%

Topics — the 1 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Information retrieval › interactive information retrieval › search interaction
collaborative search
0.312018
SearchX: Empowering Collaborative Search Research · SIGIR 2018
YearPublicationVenuePosition
2018 Contrasting Search as a Learning Activity with Instructor-designed Learning
abstract
The field of Search as Learning addresses questions surrounding human learning during the search process. Existing research has largely focused on observing how users with learning-oriented information needs behave and interact with search engines. What is not yet quantified is the extent to which search is a viable learning activity compared to instructor-designed learning. Can a search session be as effective as a lecture video - our instructor-designed learning artefact - or learning? To answer this question, we designed a user study that pits instructor-designed learning (a short high-quality video lecture as commonly found in online learning platforms) against three instances of search, specifically (i) single-user search, (ii) search as a support tool for instructor-designed learning, and, (iii) collaborative search. We measured the learning gains of 151 study participants in a vocabulary learning task and report three main results: (i) lecture video watching yields up to 24% higher learning gains than single-user search, (ii) collaborative search for learning does not lead to increased learning, and (iii) lecture video watching supported by search leads up to a 41% improvement in learning gains over instructor-designed learning without a subsequent search phase.
Felipe Moraes, Sindunuraga Rikarno Putra, Claudia Hauff
CIKM2
2018 SearchX: Empowering Collaborative Search Research
abstract
Collaborative search has been an active area of research within the IR community for many years. While for "single-user'' research a variety of up-to-date open-source search systems exist, few "multi-user'' search tools are open-source and even fewer are being maintained. In this paper, we present SearchX, an open-source collaborative search system we are currently developing-and using for our research. We designed and built SearchX using the modern Web stack (and are thus not siloed by an operating system or a particular browser type), enabling efficient research across platforms (Desktop, mobile) and with online users (e.g. crowdworkers). A video, describing the demo can be found at https: //www.youtube.com/watch?v=uf24m6p3vts.
Sindunuraga Rikarno Putra, Felipe Moraes, Claudia Hauff
SIGIR1