Spellchecking for Children in Web Search: a Natural Language Interface Case-study (2021)

Abstract: Given the more widespread nature of natural language interfaces, it is increasingly important to understand who are accessing those interfaces, and how those interfaces are being used. In this paper, we explore spellchecking in the context of web search with children as the target audience. In particular, via a literature review we show that, while widely used, popular search tools are ill-designed for children. We then use spellcheckers as a case study to highlight the need for an interdisciplinary approach that brings together natural language processing, education, human-computer interaction to address a known information retrieval problem: query misspelling. We conclude that it is imperative that those for whom the interfaces are designed have a voice in the design process.

## introduction the most popular web search engine, google, logs roughly 3.5 billion searches per day. 1 like many other commercial search engines, google's primary interface is very simple: a search box (i.e., a single line text-box) and two buttons. the expected input is a natural language query using text as the primary modality; after the search is initiated, google provides a ranked list of websites, presented also in text form. but how well does this well-used, simple natural language interface (nli) serve everyone, including children whose natural language and user interface understandings is qualitatively different from that of adults? gutnick and @xcite documented that by age 8 two-thirds of children will use the web on a daily basis, but mainstream search engines offer weak support for children's inquiry approaches. while these emergent searchers quickly develop the technical ability to use search engines and may frequently conduct online inquiry tasks, they still might not find relevant information -or information that matches their search intent @xcite . these challenges go beyond just applying "safe search" filters to results; children struggle with the natural language input aspect of the interface for several well-studied reasons: 2 keyword choice. children find it difficult to formulate succinct, meaningful keyword queries @xcite . search terms are generally nouns, a search convention that children have not yet grasped @xcite , which causes children to struggle to find keywords that express their information needs @xcite . this sometimes leads children to favor longer, grammatical natural language queries despite the difficulty they have in typing @xcite . over/under-specified queries. young children favor thematic categorizations, which may lead them to over/under-specify queries. though typing is challenging, some children may over express their search intent and enter a complete sentence to initiate the search process or enter multiple keywords, not all related to their desired result @xcite . spelling. emergent searchers are generally in either the within word pattern or syllables & affixes stages of spelling development, meaning they tend to rely on their knowledge of letter names (rather than letter sounds), struggle to appropriately represent vowel sounds @xcite , and spell words phonetically. all of this can lead to queries that search engines do not process correctly. for example, as @xcite found, a child searching for information about endangered animals may type "ndanged anemls." in this example, the child uses the letter name "n" to represent "en", struggles to represent the short /i/ sound, and omits other vowels @xcite . moreover, @xcite , who investigated children's use of keyword search in homes, shared an example of a child slowly spelling d-o-l-f and pressing the enter key as he searched for "dolphins." in these examples, search engines could assume users meant to type "deranged" or the acronym or first name dolf, missing completely the intent of the query. homonyms & taxonomies. children are only becoming aware that written representations sometimes have different senses @xcite . for example, a jaguar could be an animal or a car. while it might be easy for children to use related words ("dog" -"leash"), they can struggle with abstract categorizations ("dog" -"mammal") because of incomplete understanding of taxonomies and hierarchies @xcite . for example, they may enter "lion," when looking for books about animals, or may enter "fairies," when they are interested in fantasy. in addition to the challenges with input, children also struggle in different ways with the search results, which are displayed as text in a ranked order: query reformulation and prompts. children have difficulty reformulating a query if their initial attempt does not lead to relevant information @xcite . in fact, they are more likely to input one query and read through all retrieved results instead of optimizing their time using new queries @xcite . additionally, children do not always take advantage of the query suggestions that search engines provide @xcite . ## case study: spellcheckers for children in web search settings children make many errors as they learn how to spell, which need to be addressed if search tools are to effectively respond to children's information needs. spelling words incorrectly has potentially harmful implications for children because a word that is auto-corrected by an adult-designed spellchecker can completely change the meaning of the search query, thus affecting search success. in this section, we focus our attention on spellchecking. we first discuss assumptions about spellcheckers and sketch an interdisciplinary approach to resolving issues with spellcheckers for children. lastly, we give examples of recent work on an effective spellchecker for children. assumptions inherent from the task query spelling is a "crucial component of modern search engines" @xcite , as misspelled queries can lead to the retrieval of results that do not respond to the nformation needs of the users, or even no results at all if the misspelling cannot be mapped to common vocabulary. within this context, ir and hci researchers have allocated resources to understanding and addressing the issue of spelling in search @xcite . still, the majority of the literature in this area responds to the needs and interactions of traditional search engine users, i.e., adults @xcite @xcite . in this case, there is an implicit assumption that these user groups would understand the conventions of using the interface of a search system where text is the primary modality of expressing a user's search intent. strategies adopted by ir researchers to address spelling problems -often users' typos or misused words/phrases (li, 2020) -depend on lookup dictionaries or existing adult query-logs. these corrections happen after the query is complete (e.g., "did you mean..." feature in google). these assumptions and challenges are confounded when the user is a child; they do not usually understand the interface conventions and may be confused by corrected spelling mistakes that use a dictionary lookup only after submitting a query. this is a problem as children may not realize that a correction occurred, nor identify that the results are skewed because they do not reflect the original intent of their queries. for example, if a child begins to type "ndanged" but the spell-checker corrects to "danger" instead of "endangered," the reformulated query clearly does not reflect the child's original intent. this poses a concern, especially in light of the fact that young searchers can have misconceptions about the search tools themselves -children expect results, but do not question the relevance of those results @xcite . of note, in the previous example, the child relies upon knowledge of the name of the letter "n" and not the sound the letter makes @xcite a perspective that spellcheckers (designed for adults) generally miss. ## conclusions: lessons for nlp & hci spellchecking (for english) appears to be lowhanging fruit in nlp, but it is clearly not a solved problem for children. in the context of search within ir, spellchecking is necessary for the best search results, but the search task and interface are not well-suited for children. in this paper, we sketched an interdisciplinary approach that combines knowledge from the fields of education, nlp, and hci in an ir task and reviewed recent literature that shows how critical the interdisciplinary approach is for solving spellchecking for children in web search settings. as is the case with spellcheckers, search for children cannot be assumed to be solved because it is already widely adopted and useful for adults. the interface, the input medium, and the audience all need to be taken into account. we can learn an important lesson here from the field of hci that has far-reaching implications: the best way to design an interface that is suitable to a target audience is to involve them in the design and evaluation process. this is becoming more critical as research from the nlp field turns into practical products that face users; nlis are not always natural; they need to be designed with and for the users that they will serve.