We discuss the foundation of a collaborative effort to explore AI's role in supporting (teachers and) children in their learning experiences. We integrate principles of educational psychology, AI, and HCI, and align with best practices in education while undertaking a human-centered focus on design and development that puts the student at the centre and keeps the expert-in-the-loop. Initially, we study assessment items - questions or tasks tied to a learning target. These items vary in complexity, serve as indicators of students' grasp of specific concepts and spotlight areas where support may be needed. This preliminary analysis will help us outline a framework to guide the design and evaluation of AI technology for K-12 education. Such a framework would ensure that assessment item generation technology goes beyond the current one-dimensional approach by incorporating multifaceted, adaptable perspectives that consider the variegated landscape of learners' needs, subject matter complexities, and pedagogical goals.

In this work, we reason how focusing on Information Retrieval (IR) for children and involving them in participatory studies would benefit the IR community. The Child Computer Interaction (CCI) community has embraced the child as a protagonist as their main philosophy, regarding children as informants, co-designers, and evaluators, not just users. Leveraging prior literature, we posit that putting children in the centre of the IR world and giving them an active role could enable the IR community to break free from the preexisting bias derived from interpretations inferred from past use by adult users and the still dominant system-oriented approach. This shift would allow researchers to revisit complex foundational concepts that greatly influence the use of IR tools as part of socio-technical systems in different domains. In doing so, IR practitioners could provide more inclusive, and supportive information access experiences to children and other understudied user groups alike in different contexts.

Information Retrieval (IR) remains an active, fast-paced area of research. However, most advances in IR have predominantly benefited the so-called “classical” users, e.g., English-speaking adults. We envision IR4U2as a forum to spotlight efforts that, while sparse, consider diverse, and often understudied, user groups when designing, developing, assessing, and deploying the IR technologies that directly impact them. The key objectives for IR4U2 are: (1) raise awareness about ongoing efforts focused on IR technologies designed for and used by often understudied user groups, (2) identify challenges and open issues impacting this area of research, (3) ignite discussions to identify common frameworks for future research, and (4) enable cross-fertilization and community-building by sharing lessons learned from research catering to different audiences by researchers and (industry) practitioners across various disciplines.

In this work, we present the results of a preliminary exploration aiming to understand whether the use of ChatGPT in an educational context can be an asset to meet the specific needs of the students. In particular, we focus on the possibility of adapting the responses to online inquiries related to the primary school curriculum to meet the expectations of readers with different literacy levels. The analysis of feedback elicited from children (9- to 10-year-olds) in three 4th grade classrooms indicates that ChatGPT can adapt its responses to the 4th grade level. However, it still needs improvement to reach the right level of readability. Outcomes from this work can inspire future research directions involving technologies like ChatGPT to adapt learning paths to suit a broad range of students with varied cognitive skills. The potential of such tools to support teachers in their effort to adapt to individual learning needs is still to be fully exploited.

The influence of ChatGPT and similar models on education is being increasingly discussed. With the current level of enthusiasm among users, ChatGPT is envisioned as having great potential. As generative models are unpredictable in terms of producing biased, harmful, and unsafe content, we argue that they should be comprehensively tested for more vulnerable groups, such as children, to understand what role they can play and what training and supervision are necessary. Here, we present the results of a preliminary exploration aiming to understand whether ChatGPT can adapt to support children in completing information discovery tasks in the education context. We analyze ChatGPT responses to search prompts related to the 4th grade classroom curriculum using a variety of lenses (e.g., readability and language) to identify open challenges and limitations that must be addressed by interdisciplinary communities.

This paper contributes to the discussion initiated in a recent SIGIR paper describing a gap in the information retrieval (IR) literature on query understanding–where they come from and whether they serve their purpose. Particularly the connection between query variability and search engines regarding consistent and equitable access to all users. We focus on a user group typically underserved: children. Using preliminary experiments (based on logs collected in the classroom context) and arguments grounded in children IR literature, we emphasize the importance of dedicating research efforts to interpreting queries formulated by children and the information needs they elicit. We also outline open problems and possible research directions to advance knowledge in this area, not just for children but also for other often-overlooked user groups and contexts.

Informed by existing literature, in addition to lessons learned from ongoing research work pertaining to online information seeking, in this contribution, we discuss our view of how information pollution affects a critical yet understudied user group: children. We first highlight the need to take into account the unique characteristics of children’s search context, which can be defined in terms of various factors, from children’s age, abilities, skills, and cognitive development to the fuzzy line separating learning and fun. We then describe the importance of good design in assisting children in the different roles they play as searchers so that they can recognize and distinguish harmful and helpful content. Lastly, we discuss guidelines for effectively engaging teachers, parents, and children in the design, introduction, and use of search tools to support young users not only in accessing the information available online but also taking advantage of and learning safely from it. The focus on children not only helps us move forward to help a target group but, more importantly, it is a great starting point for further investigating a broad range of information pollution issues.

Focused on children and the learning context, we argue for the importance of designing artificial intelligence (AI) technologies that take a holistic view of their target users. Rather than prioritize system performance, these smart technologies can be tuned to assist users throughout the task completion process. We argue that considering children's diverse cultural, social, and emotional backgrounds is critical to pursuing inclusive and adaptive technologies that foster children's personalised learning and development.

The role that technology plays in supporting children at school and at home is more prominent than ever before due to the global COVID-19 pandemic. This has prompted us to focus the 6th International and Interdisciplinary Perspectives on Children & Recommender and Information Retrieval Systems (KidRec) workshop on what the lasting changes will be to the design and development of child information retrieval systems. After two years, are information retrieval systems used more in and out of the classroom? Are they more interactive, more or less personalized? What is the impact on the research and business community? Are there long-term and unexpected changes on the design, ethics, and algorithms? The primary goal of our workshop continues to be to build community by bringing together researchers, practitioners, and other stakeholders from various backgrounds and disciplines to understand and advance information retrieval systems for children.

In the classroom, search tools enable students to access online resources. While these tools have many benefits in theory, in practice there are also ethical issues to consider. In this article, we discuss a number of ethics-related problems teachers are faced with and they need to find solutions for. Based on our own research experience developing and deploying information discovery tools for the classroom (both in a traditional classroom setting and on the Internet due to the ongoing outbreak of COVID-19), we share insights about ethics and the role of the expert-in-the-loop, teachers, both as co-design partners and liaisons between search tools and students. Furthermore, we introduce a set of guidelines, EMILIA, to assist teachers in recognizing and reflecting on ethical issues that arise from their use of search tools in the classroom.

We study the effect of visual cues on children searching in the classroom. We do so by examining whether Search Engine Result Pages (SERP) enhanced with emojis, unlike standard SERP, affect children's search behaviour. To capture search behaviour, we use well-known metrics, in addition to users' success in identifying relevant results on SERP. Outcomes from our work reveal that a one-size-fits-All approach for SERP does not befit students who are searching for learning. Thus, we discuss the implications of our findings and suggest directions for future research, focused on the design and evaluation of information retrieval systems that can better support the classroom setting.

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.

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 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.

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.

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 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.

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.