In this manuscript, we argue for the need to further look at search as learning (SAL) with children as the primary stakeholders. Inspired by how children learn and considering the classroom (regardless of the teaching modality) as a natural educational ecosystem, we posit that scaffolding is the tie that can simultaneously allow for learning to search while searching for learning. The main contribution of this work is a list of open challenges focused on the primary school classroom for the IR community to consider when setting up to explore and make progress on SAL research with and for children and beyond.

In this manuscript, we discuss the findings from an introductory survey conducted with more than 50 teachers in Italy. We inquired about teachers’ opinions of educational technology used in the classroom, in particular search tools. Qualitative and quantitative data inferred from collected responses provide us with a multifaceted picture of the different roles teachers perform in the classroom when interacting with technology, their preferences, skills, perceptions of the needs for training, in addition to the principles and motivations that guide them. Findings emerging from this survey serve as a foundation for an international study that would allow us to better model teachers’ needs and the barriers they face when using search tools in the classroom.

In this paper, we examine the roles children play when using web search engines in the classroom context by revisiting, not replicating, a seminal work set in the home context. In particular, we describe how we juxtaposed performance indicators inferred from a combination of search logs (collected over two years) and expert grading of completed inquiry assignments to discern emerging search roles among children in primary four and five (aged 9 to 11). In light of the COVID-19 pandemic, we also explore differences when a traditional classroom is replaced by online instruction at home. Lastly, we discuss future research directions that we see as pivotal to advance research in Information Retrieval to and for children.

Recent developments in the mobile app industry have resulted in various types of mobile apps, each targeting a different need and a specific audience. Consequently, users access distinct apps to complete their information need tasks. This leads to the use of various apps not only separately, but also collaboratively in the same session to achieve a single goal. Recent work has argued the need for a unified mobile search system that would act as metasearch on users’ mobile devices. The system would identify the target apps for the user’s query, submit the query to the apps, and present the results to the user in a unified way. In this work, we aim to deepen our understanding of user behavior while accessing information on their mobile phones by conducting an extensive analysis of various aspects related to the search process. In particular, we study the effect of task type and user demographics on their behavior in interacting with mobile apps. Our findings reveal trends and patterns that can inform the design of a more effective mobile information access environment.

We discuss the exploratory study we conducted to better understand children's ability to recognise relevant results when searching in the classroom. Teachers in two European schools sharing thesame language assigned their students (ages 10 and 11) an online information discovery exercise about a history topic covered in class. For this, children used a classic search interface and two novel ones enriched with emojis associated to relevant vs. irrelevant results. At the end of the exercise, children filled out a post-task questionnaire meant to elicit their perception on usability ofthe interfaces. Guided by four lenses, we analyse our findings and discuss whether (i) emoji-enriched interfaces lead to better performance for children using a search engine in the classroom and (ii) "actions speak louder than words'' when looking at children's search experience. We learnedvarious lessons from our examination of children's search behaviour that will guide the design of future interfaces, including the fact that emoji-enriched interfaces result in significant improvement in terms of children identifying relevant resources.

We explore the facets of relevance that guide children when assessing materials retrieved by search engines when looking for information in the classroom. We involved children in a collaborative exercise and asked them to design innovative icons to point their peers towards useful results. We also asked them to complete a survey meant to capture explicit motivators guiding their design. This resulted in a rich set of metaphors. Analysis of the emerging metaphors is what allowed us to identify and discuss the many interpretations of relevance children naturally assign to resources they find in response to school-related information discovery tasks.

We report on the exploration we conducted to understand better children's needs for the design of Search Engine Result Pages (SERP) that can help them notice relevant resources when performing online inquiry tasks in a classroom context. We analyse children's interactions with traditional and emoji-enriched SERP and look for trends linking children's engagement with SERP and search success (based on experts' assessments). We also identify areas remaining to be interpreted and considered in future studies. On this mixed ground, we discuss the complexity of this design space and the need to bypass the one-size-fits-all approach in favor of adaptive SERP to cater to children's different and ever-evolving skills in searching and recognising useful results if we aim to support learning.

In this past year, the role of technology to support education has been more prominent than ever. This has prompted us to focus the 5th Edition of the International and Interdisciplinary Perspectives on Children & Recommender and Information Retrieval Systems (KidRec) around a major stakeholder when it comes to technology adoption for the classroom: the teacher. Much like in the previous editions of the workshop, our priority remains understanding what is good when it comes to information retrieval systems for children, this time from the perspectives of teachers. In order to control scope of our discussion and continue to advance knowledge in this area, we focus on technology that enables information discovery in the classroom context: search and recommendation systems. Expected outcomes from this workshop remain building community in this important area of work and extend the framework we have been defining to enable design and evaluation of good information retrieval systems for children.

Over 20 years ago, Information Retrieval (IR) researchers began their quest for sound IR systems for children. The path was not straightforward. Challenges posed by interface design, relevance determination, diverse contexts, ethics, and many more, were taken up and explored from different perspectives. Large projects such as Puppy-IR and the International Children's Digital Library gave this field a certain boost; still, there is neither a sound solution for children in the search area in 2021 nor a roadmap to get there. What is the reason for this Does the field cry out for specific IR solutions developed on a small scale for very small sub-fields and specific target groups Are there some significant unforeseen barriers that hinder researchers What about obstacles natural to areas of study such as this one that require a multidisciplinary approach or involve protected populations With this workshop, we want to bring together as many key experts as possible from research and industry who focus on IR for children to understand why, unlike other IR areas, this one has not flourished and look for the biggest challenges for the next 10 years. We are not only thinking of traditional researchers and designers but also of those who develop and use IR systems for fields, such as in music, film, and education, as a way to push past this immobility and look at the problem from new, and perhaps more stimulating, perspectives.

In this extended abstract, we present an overview of our ongoing project. Specifically, we briefly discuss the motivation for our research agenda, research goals in the short and long term, and the body of work we have published thus far that serves as the foundation upon which we build the next steps related to Information Retrieval and Children in the Classroom Setting.

Search Engine Result Pages (SERP) include snippets of retrieved resources as a means to help searchers select the ones that satisfy their information needs. This way, result relevance can be determined by scanning through snippets, an exercise that requires experience with reading, understanding, and assessing the value of a document. These are skills that primary school children are still developing and thus are not yet proficient with. As web search tools are essential to support children learning at school and home, we explore how to help young searchers in making informed relevance assessments while conducting searches in a classroom. In this paper, we describe a collaborative design exercise involving primary school children as co-designers: we asked them to examine interfaces with combinations of different emojis to help them assess the usefulness of results in SERP-a crucial factor to determine relevance for the classroom. This activity made our child experts engage with the design exercise while enabling us to collect their judgments so as to get a better sense of the user requirements for this age group. Here we discuss the main design issues emerging from the analysis of children's preferences, the rationale behind them, comments and concerns raised, and alternative proposals children sketched.

Data about people are constantly collected and stored to help understand patterns which can then be leveraged by information retrieval systems (IRS), such as search engines or recommender systems, to identify and rank resources that respond to diverse users' needs. As a significant group of technology users, children's data are also collected for IRS. In the 4th edition of our proposed workshop, we seek to continue to build professional community connected to children's IRS and expand on the framework identified in the 3rd KidRec that outlines how to evaluate good IRS. This time, we are particularly interested in exploring how design, research, and practice perspectives can cohesively define policy in this area.

Children turn to online search tools to complete classroom-related assignments. Unfortunately, these tools are rarely explicitly tailored to meet children's needs and skills. We seek to design a Search Agent (SA) for children in the context of education; one that can foster natural, effective and rewarding interactions in the educational context. To do so, we build on previous explorations of children's interactions with search tools and study how they imagine a SA that can help with assignments required online quests: What are the pragmatic and hedonistic qualities of such SA? Also, do previous experience and familiarity with search technology affect children's preferences? We involved in our study children ages 10-11 and inquired on factors that define their overall experience with a SA. We outline the steps of our research and the emerging lessons learned so that they can guide the design of a SA.

In the classroom, children mainly use general search systems such as Google, Baidu or Bing. For many years and from different perspectives, a call has been made that it is necessary to provide children in an educational context with child-friendly search systems. Research responding to this call often focuses on the relevance, readability and reliability of the retrieved documents. Instead, inspired by a recent study based on adult users on the role emotions play in web search, we explore whether and how children searching in a school context react to the emotional content often part of Search Engine Result Pages. We do so by examining emotions inferred from queries and corresponding retrieved resources in query logs produced by children ages 9 to 11 in a classroom setting in 3 different countries. We also consider teachers' observations that contextualize this analysis.

Recommender systems (RS) in their majority focus on an average target user: adults. We argue that for non-traditional populations in specific contexts, the task is not as straightforward-we must look beyond existing recommendation algorithms, premises for interface design, and standard evaluation metrics and frameworks. We explore the complexity of RS in an educational context for which young children are the target audience. The aim of this position paper is to spell out, label, and organize the specific layers of complexity observed in this context.

Children struggle with translating their information needs into effective queries to initiate the search process. In this paper, we explore the degree to which the use of a Vocal Assistant (VA) as an intermediary between a child and a search engine can ease query formulation and foster completion of successful searches. We also examine the potential influence VA can have on the search process when compared to a traditional keyboard-driven approach. This comparison motivates the second contribution of our work, an evaluation framework that covers 4 dimensions: (1) a new search strategy (VA) for (2) a specific user group (children) given (3) a particular task (answering questions) in (4) a defined environment (school). The proposed framework can be adopted by the research community to conduct comprehensive assessments of search systems given new interaction methods, user groups, contexts, and tasks.

In this exploratory paper, we study the usage of recommendations by and for children (ages 9 to 11) in an educational setting. From our preliminary analysis, it becomes apparent that recommender systems (RS) could provide extra support to and help children successfully complete inquiry tasks. Nonetheless, children have difficulty in recognizing the role of RS, in terms of aiding information discovery for classroom assignments. Findings from our study set a foundation that can inform future design and development of RS for children that support classroom-related work.

Reading and literacy are on the decline among children. This is compounded by the fact that children have trouble with the discovery of resources that are appropriate, diverse, and appealing. With technology becoming an evermore presence in children’s lives, tools that can minimize choice overload and ease access to online resources become a must. A powerful but underutilized tool in regards to children that could assist in this situation is a recommender system (RS). We posit that RS could be used to impact children’s learning, using them to not only suggest what children might like but what they need in regards to learning. At the same time, if scoped inappropriately, outcomes from RS could be used to alter children’s outlook. The goal instead is to strive for RS that offer suggestions based off children’s evolving knowledge, preferences, reading level, etc., so that with the proper intervention from an expert-in-the-loop (e.g., parents/teachers) could impact not only children’s educational performance, but help them to reach the goal of learning to learn.

Today's children spend considerable time online, searching and receiving information from various websites and apps. While searching for information, e.g. for school or hobbies, children use search systems to locate resources and receive site recommendations that might be useful for them. The call for good, reliable, child-friendly systems has been made many times and the thesis that the algorithms of "adult" information systems are not necessarily suitable or fair for children is widely accepted. However, there is still no clear and balanced view on what makes one search/recommendation system for children good or better than other systems, nor on what content should be considered "good enough to be retrieved" or recommended. The goal of this workshop is to bring together researchers and practitioners in education, child-development, computer science, and more who can address this questions while considering issues related to education, algorithms, ethics, privacy, evaluation.