In this vision paper, we spotlight children as often underserved users in the digital ecosystem. With online search as a use case, we discuss the need for a multi-perspective approach to designing interactive interfaces and technologies that can enable information access systems to better respond to children's requirements while respecting the cultural and social norms impacting their upbringing.@en

In this paper, we take a step towards understanding how to design search engine results pages (SERP) that encourage children's engagement as they seek for online resources. For this, we conducted a participatory design session to enable us to elicit children's preferences and determine what children (ages 6-12) find lacking in more traditional SERP. We learned that children want more dynamic means of navigating results and additional ways to interact with results via icons. We use these findings to inform the design of a new SERP interface, which we denoted CHIRP. To gauge the type of engagement that a SERP incorporating interactive elements-CHIRP-can foster among children, we conducted a user study at a public school. Analysis of children's interactions with CHIRP, in addition to responses to a post-task survey, reveals that adding additional interaction points results in a SERP interface that children prefer, but one that does not necessarily change engagement levels through clicks or time spent on SERP.@en

In this paper, we take a step towards understanding how to design search engine results pages (SERP) that encourage children's engagement as they seek for online resources. For this, we conducted a participatory design session to enable us to elicit children's preferences and determine what children (ages 6-12) find lacking in more traditional SERP. We learned that children want more dynamic means of navigating results and additional ways to interact with results via icons. We use these findings to inform the design of a new SERP interface, which we denoted CHIRP. To gauge the type of engagement that a SERP incorporating interactive elements-CHIRP-can foster among children, we conducted a user study at a public school. Analysis of children's interactions with CHIRP, in addition to responses to a post-task survey, reveals that adding additional interaction points results in a SERP interface that children prefer, but one that does not necessarily change engagement levels through clicks or time spent on SERP.@en

In this paper, we present BiGBERT, a deep learning model that simultaneously examines URLs and snippets from web resources to determine their alignment with children’s educational standards. Preliminary results inferred from ablation studies and comparison with baselines and state-of-the-art counterparts, reveal that leveraging domain knowledge to learn domain-aligned contextual nuances from limited input data leads to improved identification of educational web resources.@en

Children's ability to spell effectively is a major barrier to using search engines successfully. While search engines 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 specific target of children for this research are those with early literacy skills (whose are typically ages 6–12). The aim 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 English spelling suggestions for children; and second, to improve children's user experience when using our proposed spellchecker by involving them in the design process through participatory design and evaluating the impact of interactive elements on children's spellchecking behaviors. The outcomes of our studies and assessments result in a phonetic-based spelling correction model (KidSpell) that can more accurately correction children's spelling errors than existing state-of-the-art models. Further, we learned that visual and audio cues have a positive impact on children's ability to find their intended word from a list of spelling suggestions.@en

Readability is a core component of information retrieval (IR) tools as the complexity of a resource directly affects its relevance: a resource is only of use if the user can comprehend it. Even so, the link between readability and IR is often overlooked. As a step towards advancing knowledge on the influence of readability on IR, we focus on Web search for children. We explore how traditional formulas–which are simple, efficient, and portable–fare when applied to estimating the readability of Web resources for children written in English. We then present a formula well-suited for readability estimation of child-friendly Web resources. Lastly, we empirically show that readability can sway children’s information access. Outcomes from this work reveal that: (i) for Web resources targeting children, a simple formula suffices as long as it considers contemporary terminology and audience requirements, and (ii) instead of turning to Flesch-Kincaid–a popular formula–the use of the “right” formula can shape Web search tools to best serve children. The work we present herein builds on three pillars: Audience, Application, and Expertise. It serves as a blueprint to place readability estimation methods that best apply to and inform IR applications serving varied audiences.@en

Misspellings in queries used to initiate online searches is an everyday occurrence. When this happens, users either rely on the search engine's ability to understand their query or they turn to spellcheckers. Spellcheckers are usually based on popular dictionaries or past query logs, leading to spelling suggestions that often better resonate with adult users because that data is more readily available. Based on an educational perspective, previous research reports, and initial analyses of sample search logs, we hypothesize that existing spellcheckers are not suitable for young users who frequently encounter spelling challenges when searching for information online. We present early results of our ongoing research focused on identifying the needs and expectations children have regarding spellcheckers.@en

Misspellings in queries used to initiate online searches is an everyday occurrence. When this happens, users either rely on the search engine's ability to understand their query or they turn to spellcheckers. Spellcheckers are usually based on popular dictionaries or past query logs, leading to spelling suggestions that often better resonate with adult users because that data is more readily available. Based on an educational perspective, previous research reports, and initial analyses of sample search logs, we hypothesize that existing spellcheckers are not suitable for young users who frequently encounter spelling challenges when searching for information online. We present early results of our ongoing research focused on identifying the needs and expectations children have regarding spellcheckers.@en

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.@en

For help with their spelling errors, children often turn to spellcheckers integrated in software applications like word processors and search engines. However, existing spellcheckers are usually tuned to the needs of traditional users (i.e., adults) and generally prove unsatisfactory for children. Motivated by this issue, we introduce KidSpell, an English spellchecker oriented to the spelling needs of children. KidSpell applies (i) an encoding strategy for mapping both misspelled words and spelling suggestions to their phonetic keys and (ii) a selection process that prioritizes candidate spelling suggestions that closely align with the misspelled word based on their respective keys. To assess the effectiveness of KidSpell, we compare the model's performance against several popular, mainstream spellcheckers in a number of offline experiments using existing and novel datasets. The results of these experiments show that KidSpell outperforms existing spellcheckers, as it accurately prioritizes relevant spelling corrections when handling misspellings generated by children in both essay writing and online search tasks. As a byproduct of our study, we create two new datasets comprised of spelling errors generated by children from hand-written essays and web search inquiries, which we make available to the research community.@en

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.@en

We introduce a re-ranking model that augments the functionality of standard search engines to aid classroom search activities for children (ages 6–11). This model extends the known listwise learning-to-rank framework by balancing risk and reward. Doing so enables the model to prioritize Web resources of high educational alignment, appropriateness, and adequate readability by analyzing the URLs, snippets, and page titles of Web resources retrieved by a mainstream search engine. Experimental results demonstrate the value of considering multiple perspectives inherent to the classroom when designing algorithms that can better support children's information discovery.@en

Current approaches in automatic readability assessment have found success with the use of large language models and transformer architectures. These techniques lead to accuracy improvement, but they do not offer the interpretability that is uniquely required by the audience most often employing readability assessment tools: teachers and educators. Recent work that employs more traditional machine learning methods has highlighted the linguistic importance of considering semantic and syntactic characteristics of text in readability assessment by utilizing handcrafted feature sets. Research in Education suggests that, in addition to semantics and syntax, phonetic and orthographic instruction are necessary for children to progress through the stages of reading and spelling development; children must first learn to decode the letters and symbols on a page to recognize words and phonemes and their connection to speech sounds. Here, we incorporate this word-level phonemic decoding process into readability assessment by crafting a phonetically-based feature set for grade-level classification for English. Our resulting feature set shows comparable performance to much larger, semantically- and syntactically-based feature sets, supporting the linguistic value of orthographic and phonetic considerations in readability assessment.@en

Purpose: This paper investigates how school teachers look for informational texts for their classrooms. Access to current, varied and authentic informational texts improves learning outcomes for K-12 students, but many teachers lack resources to expand and update readings. The Web offers freely available resources, but finding suitable ones is time-consuming. This research lays the groundwork for building tools to ease that burden. Design/methodology/approach: This paper reports qualitative findings from a study in two stages: (1) a set of semistructured interviews, based on the critical incident technique, eliciting teachers' information-seeking practices and challenges; and (2) observations of teachers using a prototype teaching-oriented news search tool under a think-aloud protocol. Findings: Teachers articulated different objectives and ways of using readings in their classrooms, goals and self-reported practices varied by experience level. Teachers struggled to formulate queries that are likely to return readings on specific course topics, instead searching directly for abstract topics. Experience differences did not translate into observable differences in search skill or success in the lab study. Originality/value: There is limited work on teachers' information-seeking practices, particularly on how teachers look for texts for classroom use. This paper describes how teachers look for information in this context, setting the stage for future development and research on how to support this use case. Understanding and supporting teachers looking for information is a rich area for future research, due to the complexity of the information need and the fact that teachers are not looking for information for themselves.@en

Popular search engines (SE) favored by children are optimized neither to respond to their search behavior and abilities, nor retrieve resources that align with classroom standards. Further, attempts to adapt SE to support children's inquiries have been one-dimensional, e.g., satisfy users' reading skills or search expertise. To ease the process of locating resources relevant to children in the classroom, we introduce KORSCE, a ranking strategy designed to complement the functionality of existing SE. KORSCE employs a multi-objective approach to re-rank resources retrieved by popular SE to fit a specific target audience and setting based on varied criteria: appropriateness, readability, objectivity, and curriculum-alignment. Experimental results and insights from an expert appraiser showcase KORSCE'S ability to prioritize resources that assist children's information-seeking activities at school.@en

Popular search engines (SE) favored by children are optimized neither to respond to their search behavior and abilities, nor retrieve resources that align with classroom standards. Further, attempts to adapt SE to support children's inquiries have been one-dimensional, e.g., satisfy users' reading skills or search expertise. To ease the process of locating resources relevant to children in the classroom, we introduce KORSCE, a ranking strategy designed to complement the functionality of existing SE. KORSCE employs a multi-objective approach to re-rank resources retrieved by popular SE to fit a specific target audience and setting based on varied criteria: appropriateness, readability, objectivity, and curriculum-alignment. Experimental results and insights from an expert appraiser showcase KORSCE'S ability to prioritize resources that assist children's information-seeking activities at school.@en

Spellchecking functionality embedded in existing search tools can assist children by offering a list of spelling alternatives when a spelling error is detected. Unfortunately, children tend to generally select the first alternative when presented with a list of options, as opposed to the one that matches their intent. In this paper, we describe a study we conducted with 191 children ages 6-12 in order to offer empirical evidence of: (1) their selection habits when identifying spelling suggestions that match the word they meant to type, and (2) the degree of influence multimodal cues, i.e., synthesized speech and images, have in prompting children to select the correct spelling suggestion. The results from our study reveal that multimodal cues, primarily synthesized speech, have a positive impact on the children's ability to identify their intended word from a list of spelling suggestions.@en

This forum provides a space to engage with the challenges of designing for intelligent algorithmic experiences. We invite articles that tackle the tensions between research and practice when integrating AI and UX design. We welcome interdisciplinary debate, artful critique, forward-looking research, case studies of AI in practice, and speculative design explorations@en

As an initial step towards enabling the adaptation of (popular, and widely used) web search environments so that they can better serve children and ease their path towards information discovery, we introduce Recognizing Young Searchers (RYSe). RYSe leverages lexical, syntactical, spelling/punctuation, and vocabulary features that align with the Concrete Operational stage of development (originally identified by Jean Piaget) in an attempt to identify users that are in this stage. The concrete operational stage is commonly associated with children ages 7-11. Findings emerging from our initial empirical exploration using single queries formulated by children and sample queries from adults showcase the feasibility of relying on different cognitive traits inferred from the short text of a single query to distinguish those that are formulated by younger searchers. @en