{ "paper_id": "2021", "header": { "generated_with": "S2ORC 1.0.0", "date_generated": "2023-01-19T03:35:24.172065Z" }, "title": "Spellchecking for Children in Web Search: a Natural Language Interface Case-study", "authors": [ { "first": "Casey", "middle": [], "last": "Kennington", "suffix": "", "affiliation": { "laboratory": "", "institution": "Boise State University", "location": {} }, "email": "caseykennington@boisestate.edu" }, { "first": "Jerry", "middle": [ "Alan" ], "last": "Fails", "suffix": "", "affiliation": { "laboratory": "", "institution": "Boise State University", "location": {} }, "email": "jerryfails@boisestate.edu" }, { "first": "Katherine", "middle": [ "Landau" ], "last": "Wright", "suffix": "", "affiliation": { "laboratory": "", "institution": "Boise State University", "location": {} }, "email": "katherinewright@boisestate.edu" }, { "first": "Maria", "middle": [ "Soledad" ], "last": "Pera", "suffix": "", "affiliation": { "laboratory": "", "institution": "Boise State University", "location": {} }, "email": "" } ], "year": "", "venue": null, "identifiers": {}, "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 systematic literature review of work that illustrate challenges and limitations, 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.", "pdf_parse": { "paper_id": "2021", "_pdf_hash": "", "abstract": [ { "text": "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 systematic literature review of work that illustrate challenges and limitations, 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.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "Abstract", "sec_num": null } ], "body_text": [ { "text": "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 Green and Holloway (2014) 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 (Anuyah et al., 2019; Bilal and Huang, 2019) . 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 (Broch, 2000; Duarte Torres et al., 2012) . Search terms are generally nouns, a search convention that children have not yet grasped (Bilal and Ellis, 2011) , which causes children to struggle to find keywords that express their information needs (Aspray and Bernat, 2000) . This sometimes leads children to favor longer, grammatical natural language queries despite the difficulty they have in typing (Druin et al., 2009) .", "cite_spans": [ { "start": 636, "end": 673, "text": "Gutnick and Green and Holloway (2014)", "ref_id": null }, { "start": 1077, "end": 1098, "text": "(Anuyah et al., 2019;", "ref_id": "BIBREF0" }, { "start": 1099, "end": 1121, "text": "Bilal and Huang, 2019)", "ref_id": "BIBREF5" }, { "start": 1307, "end": 1308, "text": "2", "ref_id": null }, { "start": 1402, "end": 1415, "text": "(Broch, 2000;", "ref_id": "BIBREF6" }, { "start": 1416, "end": 1443, "text": "Duarte Torres et al., 2012)", "ref_id": "BIBREF15" }, { "start": 1535, "end": 1558, "text": "(Bilal and Ellis, 2011)", "ref_id": "BIBREF4" }, { "start": 1649, "end": 1674, "text": "(Aspray and Bernat, 2000)", "ref_id": "BIBREF1" }, { "start": 1804, "end": 1824, "text": "(Druin et al., 2009)", "ref_id": "BIBREF12" } ], "ref_spans": [], "eq_spans": [], "section": "Introduction", "sec_num": "1" }, { "text": "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 (Kammerer and Bohnacker, 2012; Schacter et al., 1998) .", "cite_spans": [ { "start": 338, "end": 368, "text": "(Kammerer and Bohnacker, 2012;", "ref_id": "BIBREF23" }, { "start": 369, "end": 391, "text": "Schacter et al., 1998)", "ref_id": "BIBREF29" } ], "ref_spans": [], "eq_spans": [], "section": "Introduction", "sec_num": "1" }, { "text": "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 (Bear et al., 2016) , and spell words phonetically. All of this can lead to queries that search engines do not process correctly. For example, as Spink et al. (2010) 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 (Bear et al., 2016) . Moreover, Druin et al. (2010) , 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.", "cite_spans": [ { "start": 271, "end": 290, "text": "(Bear et al., 2016)", "ref_id": "BIBREF3" }, { "start": 417, "end": 436, "text": "Spink et al. (2010)", "ref_id": "BIBREF30" }, { "start": 668, "end": 687, "text": "(Bear et al., 2016)", "ref_id": "BIBREF3" }, { "start": 700, "end": 719, "text": "Druin et al. (2010)", "ref_id": "BIBREF13" } ], "ref_spans": [], "eq_spans": [], "section": "Introduction", "sec_num": "1" }, { "text": "Homonyms & Taxonomies. Children are only becoming aware that written representations sometimes have different senses (Large et al., 2008) . 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 (Nguyen and Murphy, 2003) . For example, they may enter \"lion,\" when looking for books about animals, or may enter \"fairies,\" when they are interested in fantasy.", "cite_spans": [ { "start": 117, "end": 137, "text": "(Large et al., 2008)", "ref_id": "BIBREF25" }, { "start": 398, "end": 423, "text": "(Nguyen and Murphy, 2003)", "ref_id": "BIBREF28" } ], "ref_spans": [], "eq_spans": [], "section": "Introduction", "sec_num": "1" }, { "text": "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:", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "Introduction", "sec_num": "1" }, { "text": "Query Reformulation and Prompts. Children have difficulty reformulating a query if their initial attempt does not lead to relevant information (Gossen et al., 2014; Kammerer and Bohnacker, 2012) . In fact, they are more likely to input one query and read through all retrieved results instead of optimizing their time using new queries (Gossen et al., 2014) . Additionally, children do not always take advantage of the query suggestions that search engines provide (Druin et al., 2009) .", "cite_spans": [ { "start": 143, "end": 164, "text": "(Gossen et al., 2014;", "ref_id": "BIBREF17" }, { "start": 165, "end": 194, "text": "Kammerer and Bohnacker, 2012)", "ref_id": "BIBREF23" }, { "start": 336, "end": 357, "text": "(Gossen et al., 2014)", "ref_id": "BIBREF17" }, { "start": 465, "end": 485, "text": "(Druin et al., 2009)", "ref_id": "BIBREF12" } ], "ref_spans": [], "eq_spans": [], "section": "Introduction", "sec_num": "1" }, { "text": "Connection of Results with Query. Children are not trained to identify suitable resources from among those that their favored search engines retrieve (Bilal and Ellis, 2011) , nor are they trained to understand the direct connection between their queries and retrieved results (Karatassis, 2017) .", "cite_spans": [ { "start": 150, "end": 173, "text": "(Bilal and Ellis, 2011)", "ref_id": "BIBREF4" }, { "start": 277, "end": 295, "text": "(Karatassis, 2017)", "ref_id": "BIBREF24" } ], "ref_spans": [], "eq_spans": [], "section": "Introduction", "sec_num": "1" }, { "text": "Quality & Comprehension of Results. Children step through retrieved resources, though children rarely judge those resources for quality (Graham and Metaxas, 2003; Walker, 2013) . The average readability level of the (snippets of) resources retrieved by search engines is the 10thgrade level (typically children 15-16 in the United States) (Azpiazu et al., 2016; Anuyah et al., 2019) . This level is far beyond that appropriate for emergent searchers. As such, children may not be able to comprehend retrieved resources, thus making these results irrelevant (Bilal and Ellis, 2011; Graham and Metaxas, 2003; Walker, 2013) .", "cite_spans": [ { "start": 136, "end": 162, "text": "(Graham and Metaxas, 2003;", "ref_id": "BIBREF18" }, { "start": 163, "end": 176, "text": "Walker, 2013)", "ref_id": "BIBREF31" }, { "start": 339, "end": 361, "text": "(Azpiazu et al., 2016;", "ref_id": "BIBREF2" }, { "start": 362, "end": 382, "text": "Anuyah et al., 2019)", "ref_id": "BIBREF0" }, { "start": 557, "end": 580, "text": "(Bilal and Ellis, 2011;", "ref_id": "BIBREF4" }, { "start": 581, "end": 606, "text": "Graham and Metaxas, 2003;", "ref_id": "BIBREF18" }, { "start": 607, "end": 620, "text": "Walker, 2013)", "ref_id": "BIBREF31" } ], "ref_spans": [], "eq_spans": [], "section": "Introduction", "sec_num": "1" }, { "text": "As indicated above, the input and results elements of the search task for children have components that relate directly to natural language processing. However, these elements cannot be addressed individually and purely from a traditional natural language processing perspective. Additionally, the obvious must be stated: children are not simply small adults, which has implications for all interfaces that children use that frequently are designed for (and by) adults. Addressing these search challenges for children requires an interdisciplinary approach that sits at the crossroads of information retrieval (IR-the search task) and human-computer interaction (HCI-the interface), both with focus on children as users, as well as natural language processing (NLP-the medium) and education (Eddevelopmental understanding of the user).", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "Introduction", "sec_num": "1" }, { "text": "In this paper, we use Spelling as a case study for applying this interdisciplinary approach to illustrate that an interface as commonplace as web search and a basic operation such as automatic spellchecking are not yet effective tools when children are the users, and applying an interdisciplinary approach can result in important research and technological advances that impact users.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "Introduction", "sec_num": "1" }, { "text": "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.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "Case Study: Spellcheckers for Children in Web Search Settings", "sec_num": "2" }, { "text": "Assumptions Inherent from the Task Query spelling is a \"crucial component of modern search engines\" (Li, 2020) , 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 (Spink et al., 2010; Druin et al., 2010) . Still, the majority of the literature in this area responds to the needs and interactions of traditional search engine users, i.e., adults (Chang and Deng; Duan and Hsu, 2011; Li et al., 2012; Gupta et al., 2019) . 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 (Halavais, 2017; Anuyah et al., 2019) . 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 (Bear et al., 2016) a perspective that spellcheckers (designed for adults) generally miss.", "cite_spans": [ { "start": 100, "end": 110, "text": "(Li, 2020)", "ref_id": "BIBREF26" }, { "start": 447, "end": 467, "text": "(Spink et al., 2010;", "ref_id": "BIBREF30" }, { "start": 468, "end": 487, "text": "Druin et al., 2010)", "ref_id": "BIBREF13" }, { "start": 629, "end": 645, "text": "(Chang and Deng;", "ref_id": "BIBREF7" }, { "start": 646, "end": 665, "text": "Duan and Hsu, 2011;", "ref_id": "BIBREF14" }, { "start": 666, "end": 682, "text": "Li et al., 2012;", "ref_id": "BIBREF27" }, { "start": 683, "end": 702, "text": "Gupta et al., 2019)", "ref_id": "BIBREF20" }, { "start": 2030, "end": 2046, "text": "(Halavais, 2017;", "ref_id": "BIBREF22" }, { "start": 2047, "end": 2067, "text": "Anuyah et al., 2019)", "ref_id": "BIBREF0" } ], "ref_spans": [], "eq_spans": [], "section": "Case Study: Spellcheckers for Children in Web Search Settings", "sec_num": "2" }, { "text": "As evidenced from our discussion above, tackling misspellings in children's query is not something that the IR community can undertake alone. Spellcheckers are not just the underlying technical mechanism that identifies the spelling mistakes, they are at the forefront, fostering interactions with the interface. Moreover, spelling correction and learning is an educational endeavor that can be addressed by combining NLP, HCI, and Ed. NLP is needed because the primary medium is text, albeit often not grammatical, and searching often happens across multiple turns, which is similar to interactive, spoken dialogue -a sub-field of NLP. We should treat spellchecking with children as an interactive, multi-turn process. Ed is needed because the interactive, multi-turn process and the spellchecker itself should apply a more principled model of spelling correction based upon educational research in spelling development so spelling mistakes can inform the system how to act, which is where HCI is needed. For example, spelling suggestions could be displayed, highlighting spelling differences, to draw the child's attention to the specific spelling mistake made, and providing an option to alter their input (i.e., in potential query reformulations). This naturally makes the process more interactive, drawing the query over several turns between the user and the system, and informs the child that query reformulation is a part of the search process. HCI expertise leverages researched principles and guidelines in addition to participatory design practices (Fails et al., 2013) to help design intuitive displays which can provide scaffolding in the form of visual cues to guide child users to describe their search intent accurately.", "cite_spans": [ { "start": 1560, "end": 1580, "text": "(Fails et al., 2013)", "ref_id": "BIBREF16" } ], "ref_spans": [], "eq_spans": [], "section": "Sketch of an Interdisciplinary Approach", "sec_num": "2.1" }, { "text": "In Downs et al. (2019) , we examined what children actually expect from spellcheckers in search tools. We did so via participatory design (specifically using the Cooperative Inquiry method (Druin, 1999; Fails et al., 2013) ) in order to involve children in designing the spellchecker. The main take-away from this research was the need for visual cues to act as scaffolding for the children to use as they learn to navigate the spellchecker's interface to identify and correct spelling mistakes. What otherwise appears to be a solved task for NLP is far from solved when children are the users. These efforts informed the modeling of the spellchecker KidSpell we introduced in Downs et al. (2020a) . KidSpell is highly influenced by established Educational research in spelling development which led to the design of a phonetic-based spellchecker because children tend to make mistakes with the phonetic mappings of sounds to alphabet symbols. The authors evaluated their spellchecker on mistakes made in the context of handwritten writing samples (that were digitally transcribed) as well as spelling mistakes made during web search tasks. The phonetic spellchecker worked better for children than the current stateof-the-art spellcheckers used by adults (including Bing's spellchecker 3 , and Aspell 4 ), despite being a more parsimonious, rule-base approach. An example of the spellchecker in use is depicted in Figure 1 , with visual cues showing the parts of the word that differ phonetically from what the child spelled. The development and advancement of KidSpell included a multi-faceted approach that included algorithmic advances and user-interface enhancements (Downs et al., 2019 (Downs et al., , 2020a . Algorithm advances (applying NLP research) included evaluating input, identifying misspellings, and generating ranked spelling suggestions. With regards to the user interface, research included multiple participatory design sessions with an intergenerational design team consisting of children ages 6-11 and adult researchers (applying HCI research). The team collaboratively designed various approaches that could convey to children when a word was misspelled and enable them to better select the intended word from the suggested spelling corrections. 5 We then investigated the effectiveness of various cues within a web-search task (applying HCI and IR research). One cue was images that prototypically represented the word in question (e.g., if a child typed dinsoer and the spellchecker suggested dinosaur, then hovering over dinosaur with the mouse would display an image of a dinosaur, as depicted in Figure 2 . Another cue we evaluated was speech synthesis; for the dinosaur example, hovering over it would play a synthesized voice reading the word over the speakers. We also looked at the combination of the two and showed that both cues had impact, but synthesized speech especially helped guide the children to select the correctly spelled word. 3 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.", "cite_spans": [ { "start": 3, "end": 22, "text": "Downs et al. (2019)", "ref_id": "BIBREF9" }, { "start": 189, "end": 202, "text": "(Druin, 1999;", "ref_id": "BIBREF11" }, { "start": 203, "end": 222, "text": "Fails et al., 2013)", "ref_id": "BIBREF16" }, { "start": 677, "end": 697, "text": "Downs et al. (2020a)", "ref_id": "BIBREF8" }, { "start": 1672, "end": 1691, "text": "(Downs et al., 2019", "ref_id": "BIBREF9" }, { "start": 1692, "end": 1714, "text": "(Downs et al., , 2020a", "ref_id": "BIBREF8" }, { "start": 2270, "end": 2271, "text": "5", "ref_id": null } ], "ref_spans": [ { "start": 1415, "end": 1423, "text": "Figure 1", "ref_id": "FIGREF0" }, { "start": 2625, "end": 2633, "text": "Figure 2", "ref_id": "FIGREF1" } ], "eq_spans": [], "section": "Recent work on Interdisciplinary Modeling and Evaluation of Child-directed Spellcheckers", "sec_num": "2.2" }, { "text": "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.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "Recent work on Interdisciplinary Modeling and Evaluation of Child-directed Spellcheckers", "sec_num": "2.2" }, { "text": "https://www.internetlivestats.com/ google-search-statistics/", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "", "sec_num": null }, { "text": "Note that few of these studies are recent. This is partially due to the fact that public data sets and benchmarks are not available (children are a protected population), so there is less research in the area of child-oriented information retrieval.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "", "sec_num": null }, { "text": "https://www.microsoft.com/en-us/bing/ apis/bing-spell-check-api 4 http://aspell.net/ 5 The spellchecker is active on http://cast. boisestate.edu.", "cite_spans": [], "ref_spans": [], "eq_spans": [], "section": "", "sec_num": null } ], "back_matter": [ { "text": "This research was partially supported by NSF Award 1565937 as well as NSF Award 1763649. 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