Investigating query formulation assistance for children

Anuyah, Oghenemaro; Fails, Jerry Alan; Pera, Maria Soledad

doi:10.1145/3202185.3210779

Cited by 7 publications

(8 citation statements)

References 18 publications

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“…We obtained query and query interaction logs from a previous workin-progress study that reported on survey data and processes [16] from a pilot study. The pilot study was conducted over two 40-minute search sessions with 8 children (5 girls, and 3 boys) ages 6-10.…”

Section: Query Suggestion Methodsmentioning

confidence: 99%

“…To our knowledge, there is no de-facto query formulation strategy favored by children. To better understand how existing strategies address children's query formulation problems and the varying ways to help children formulate queries when using search tools, we build upon the results presented by the authors in [16] and ask these research questions:…”

Section: Introductionmentioning

confidence: 99%

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Query Formulation Assistance for Kids

Fails

Pera

Anuyah

et al. 2019

Proceedings of the 18th ACM International Conference on Interaction Design and Children

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Children use popular web search tools, which are generally designed for adult users. Because children have different developmental needs than adults, these tools may not always adequately support their search for information. Moreover, even though search tools offer support to help in query formulation, these too are aimed at adults and may hinder children rather than help them. This calls for the examination of existing technologies in this area, to better understand what remains to be done when it comes to facilitating query-formulation tasks for young users. In this paper, we investigate interaction elements of query formulation-including query suggestion algorithms-for children. The primary goals of our research efforts are to: (i) examine existing plug-ins and interfaces that explicitly aid children's query formulation; (ii) investigate children's interactions with suggestions offered by a general-purpose query suggestion strategy vs. a counterpart designed with children in mind; and (iii) identify, via participatory design sessions, their preferences when it comes to tools / strategies that can help children find information and guide them through the query formulation process. Our analysis shows that existing tools do not meet children's needs and expectations; the outcomes of our work can guide researchers and developers as they implement query formulation strategies for children. CCS CONCEPTS • Information systems → Recommender systems; • Human-centered computing → Human computer interaction(HCI).

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Section: Query Suggestion Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Query Formulation Assistance for Kids

Fails

Pera

Anuyah

et al. 2019

Proceedings of the 18th ACM International Conference on Interaction Design and Children

Self Cite

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“…Anuyah et al [46] compared general purpose interface elements in IR systems with child-specific elements, focusing on query suggestions for children [47,48]. Only three of the eight children in Anuyah et al's [46] study seemed to have noticed the different query suggestions. It was not clear from the study report if children were using query suggestions unprompted.…”

Section: Children's Use Of Information Retrieval Systemsmentioning

confidence: 99%

Children’s query formulation and search result exploration

Vanderschantz

Hinze

2021

Int J Digit Libr

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Our research aims at understanding children's information search and their use of information search tools during educational pursuits. We conducted an observation study with 50 New Zealand school children between the ages of 9 and 13 years old. In particular, we studied the way that children constructed search queries and interacted with the Google search engine when undertaking a range of educationally appropriate inquiry tasks. As a result of this in situ study, we identified typical querycreation and query-reformulation strategies that children use. The children worked through 250 tasks, and created a total of 550 search queries. 64.4% of the successful queries made were natural language queries compared to only 35.6% keyword queries. Only three children used the related searches feature of the search engine, while 46 children used query suggestions. We gained insights into the information search strategies children use during their educational pursuits. We observed a range of issues that children encountered when interacting with a search engine to create searches as well as to triage and explore information in the search engine results page lists. We found that search tasks posed as questions were more likely to result in query constructions based on natural language questions, while tasks posed as instructions were more likely to result in query constructions using natural language sentences or keywords. Our findings have implications for both educators and search engine designers.

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“…Given that providing suitable spelling suggestions in an interactive spellchecker is truly a ranking problem rather than a classification problem, as well as the behavior shown in children to have a propensity to interact with higher ranked alternatives [33,2], we also use the learning-to-rank (LTR) model LambdaMART [8]. While, the use of LTR models has not knowingly been explored for spellchecking, they have proven effective at similar ranking problems such as large scale search, query suggestions, and recommendation [52].…”

Section: Age Of Acquisition (Aoamentioning

confidence: 99%

“…A higher MRR value indicates a higher average ranking for the gold standard. Given children's propensity to click on higher ranked alternatives for spelling suggestions [15] as well as other areas of search [2,33], it is crucial to rank the gold standard highly. Taken together, these two metrics measure how well each spellchecker is at finding the intended word (Hit Rate) and how well it is ranked (MRR).…”

Section: Metricsmentioning

confidence: 99%

Improving Spellchecking for Children

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Children commonly use software applications such as search engines and word processors in the classroom environment. However, a major barrier to using these programs successfully is the ability of children to type and spell effectively. While many programs make use of spellcheckers to provide spelling corrections to their users, they are designed for more traditional users (i.e., adults) and have proven inadequate for children. The aims of this work is twofold: first, to address the types of spelling errors children make by researching, developing, and evaluating algorithms to generate and rank candidate spelling suggestions; and second, to evaluate the impact interactive elements have on children's spellchecking behaviors seeking to improve their user experience. Motivated by children's phonological strategies to spell, a phonetic encoding strategy is used to map words and misspellings to phonetic keys to effectively and efficiently provide spelling correction candidates. Machine learning methods, including Learning to Rank, are used to rank candidates effectively and reveal the importance of phonetic features. Experimental results show this method is able to more accurately provide and rank spelling corrections when handling misspellings generated by children in both essay writing and web search settings when compared to state-of-the-art baselines. The design of an interactive spellchecker reveals children's propensity towards visual and audio cues. A study on visual and audio cues show an influence on children's selection habits and a positive impact on assisting children in selecting correct spelling suggestions.

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Investigating query formulation assistance for children

Cited by 7 publications

References 18 publications

Query Formulation Assistance for Kids

Query Formulation Assistance for Kids

Children’s query formulation and search result exploration

Improving Spellchecking for Children

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