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1. Programming as a language for young children to express and explore mathematics in school

   https://doi.org/10.1111/bjet.13080  

   Goldenberg, E. Paul ; Carter, Cynthia J. ( May 2021 , British Journal of Educational Technology)

   Natural language helps express mathematical thinking and contexts. Conventional mathematical notation (CMN) best suits expressions and equations. Each is essential; each also has limitations, especially for learners. Our research studies how programming can be a advantageous third language that can also help restore mathematical connections that are hidden by topic‐centred curricula. Restoring opportunities for surprise and delight reclaims mathematics' creative nature. Studies of children's use of language in mathematics and their programming behaviours guide our iterative design/redesign of mathematical microworlds in which students, ages 7–11, use programming in their regular school lessonsas a language for learning mathematics. Though driven by mathematics, not coding, the microworlds develop the programming over time so that it continues to support children's developing mathematical ideas. This paper briefly describes microworlds EDC has tested with well over 400 7‐to‐8‐year‐olds in school, and others tested (or about to be tested) with over 200 8‐to‐11‐year‐olds. Our challenge was to satisfy schools' topical orientation and fit easily within regular classroom study but use and foreshadow other mathematical learning to remove the siloes. The design/redesign research and evaluation is exploratory, without formal methodology. We are also more formally studying effects on children's learning. That ongoing study is not reported here.

   What is already known

   Active learning—doing—supports learning.

   Collaborative learning—doingtogether—supports learning.

   Classroom discourse—focused, relevantdiscussion, not just listening—supports learning.

   Clear articulation of one's thinking, even just to oneself, helps develop that thinking.

   What this paper adds

   The common languages we use for classroom mathematics—natural language for conveying the meaning and context of mathematical situations and for explaining our reasoning; and the formal (written) language of conventional mathematical notation, the symbols we use in mathematical expressions and equations—are both essential but each presents hurdles that necessitate the other. Yet, even together, they are insufficient especially for young learners.

   Programming, appropriately designed and used, can be the third language that both reduces barriers and provides the missing expressive and creative capabilities children need.

   Appropriate design for use in regular mathematics classrooms requires making key mathematical content obvious, strong and the ‘driver’ of the activities, and requires reducing tech ‘overhead’ to near zero.

   Continued usefulness across the grades requires developing children's sophistication and knowledge with the language; the powerful ways that children rapidly acquire facility with (natural) language provides guidance for ways they can learn a formal language as well.

   Implications for policy and/or practice

   Mathematics teaching can take advantage of the ways children learn through experimentation and attention to the results, and of the ways children use their language brain even for mathematics.

   In particular, programming—in microworlds driven by the mathematical content, designed to minimise distraction and overhead, open to exploration and discoveryen routeto focused aims, and in which childrenself‐evaluate—can allow clear articulation of thought, experimentation with immediate feedback.

   As it aids the mathematics, it also builds computational thinking and satisfies schools' increasing concerns to broaden access to ideas of computer science.

    

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2. Youth invisible work: the sociocultural and collaborative processes of online search and brokering between adolescents and English-language learning families

   https://doi.org/10.1108/ILS-01-2022-0004  

   Yip, Jason ; Roldan, Wendy ; Gonzalez, Carmen ; Pina, Laura R. ; Ruiz, Maria ; Vanegas, Paola ( July 2022 , Information and Learning Sciences)

   This study aims to investigate the collaboration processes of immigrant families as they search for online information together. Immigrant English-language learning adults of lower socioeconomic status often work collaboratively with their children to search the internet. Family members rely on each other’s language and digital literacy skills in this collaborative process known as online search and brokering (OSB). While previous work has identified ecological factors that impact OSB, research has not yet distilled the specific learning processes behind such collaborations. Design/methodology/approach: For this study, the authors adhere to practices of a case study examination. This study’s participants included parents, grandparents and children aged 10–17 years. Most adults were born in Mexico, did not have a college-degree, worked in service industries and represented a lower-SES population. This study conducted two to three separate in-home family visits per family with interviews and online search tasks. Findings: From a case study analysis of three families, this paper explores the funds of knowledge, resilience, ecological support and challenges that children and parents face, as they engage in collaborative OSB experiences. This study demonstrates how in-home computer-supported collaborative processes are often informal, social, emotional and highly relevant to solving information challenges. Research limitations/implications: An intergenerational OSB process is different from collaborative online information problem-solving that happens between classroom peers or coworkers. This study’s research shows how both parents and children draw on their funds of knowledge, resilience and ecological support systems when they search collaboratively, with and for their family members, to problem solve. This is a case study of three families working in collaboration with each other. This case study informs analytical generalizations and theory-building rather than statistical generalizations about families. Practical implications: Designers need to recognize that children and youth are using the same tools as adults to seek high-level critical information. This study’s model suggests that if parents and children are negotiating information seeking with the same technology tools but different funds of knowledge, experience levels and skills, the presentation of information (e.g. online search results, information visualizations) needs to accommodate different levels of understanding. This study recommends designers work closely with marginalized communities through participatory design methods to better understand how interfaces and visuals can help accommodate youth invisible work. Social implications: The authors have demonstrated in this study that learning and engaging in family online searching is not only vital to the development of individual and digital literacy skills, it is a part of family learning. While community services, libraries and schools have a responsibility to support individual digital and information literacy development, this study’s model highlights the need to recognize funds of knowledge, family resiliency and asset-based learning. Schools and teachers should identify and harness youth invisible work as a form of learning at home. The authors believe educators can do this by highlighting the importance of information problem solving in homes and youth in their families. Libraries and community centers also play a critical role in supporting parents and adults for technical assistance (e.g. WiFi access) and information resources. Originality/value: This study’s work indicates new conditions fostering productive joint media engagement (JME) around OSB. This study contributes a generative understanding that promotes studying and designing for JME, where family responsibility is the focus.

    

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3. Query Formulation Assistance for Kids: What is Available, When to Help & What Kids Want

   https://doi.org/10.1145/3311927.3323131  

   Fails, Jerry Alan ; Pera, Maria Soledad ; Anuyah, Oghenemaro ; Kennington, Casey ; Wright, Katherine Landau ; Bigirimana, William ( June 2019 , Proceedings of the 18th ACM International Conference on Interaction Design and Children)

   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. 

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4. Structured Data Representation in Natural Language Interfaces

   Yutong Shao, Arun Kumar ( September 2022 , A Quarterly bulletin of the Computer Society of the IEEE Technical Committee on Data Engineering)

   A Natural Language Interface (NLI) enables the use of human languages to interact with computer systems, including smart phones and robots. Compared to other types of interfaces, such as command line interfaces (CLIs) or graphical user interfaces (GUIs), NLIs stand to enable more people to have access to functionality behind databases or APIs as they only require knowledge of natural languages. Many NLI applications involve structured data for the domain (e.g., applications such as hotel booking, product search, and factual question answering.) Thus, to fully process user questions, in addition to natural language comprehension, understanding of structured data is also crucial for the model. In this paper, we study neural network methods for building Natural Language Interfaces (NLIs) with a focus on learning structure data representations that can generalize to novel data sources and schemata not seen at training time. Specifically, we review two tasks related to natural language interfaces: i) semantic parsing where we focus on text-to-SQL for database access, and ii) task-oriented dialog systems for API access. We survey representative methods for text-to-SQL and task-oriented dialog tasks, focusing on representing and incorporating structured data. Lastly, we present two of our original studies on structured data representation methods for NLIs to enable access to i) databases, and ii) visualization APIs. 

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5. Navigating the FDA Medical Device Regulatory Pathways for Pediatric Lower Limb Exoskeleton Devices

   https://doi.org/10.1109/JSYST.2020.3025111  

   Eguren, David ; Contreras-Vidal, Jose Luis ( October 2020 , IEEE Systems Journal)

   null (Ed.)

   There have been significant advances in the technologies for robot-assisted lower-limb rehabilitation in the last decade. However, the development of similar systems for children has been slow despite the fact that children with conditions such as cerebral palsy (CP), spina bifida (SB) and spinal cord injury (SCI) can benefit greatly from these technologies. Robotic assisted gait therapy (RAGT) has emerged as a way to increase gait training duration and intensity while decreasing the risk of injury to therapists. Robotic walking devices can be coupled with motion sensing, electromyography (EMG), scalp electroencephalography (EEG) or other noninvasive methods of acquiring information about the user’s intent to design Brain-Computer Interfaces (BCI) for neuromuscular rehabilitation and control of powered exoskeletons. For users with SCI, BCIs could provide a method of overground mobility closer to the natural process of the brain controlling the body’s movement during walking than mobility by wheelchair. For adults there are currently four FDA approved lower-limb exoskeletons that could be incorporated into such a BCI system, but there are no similar devices specifically designed for children, who present additional physical, neurological and cognitive developmental challenges. The current state of the art for pediatric RAGT relies on large clinical devices with high costs that limit accessibility. This can reduce the amount of therapy a child receives and slow rehabilitation progress. In many cases, lack of gait training can result in a reduction in the mobility, independence and overall quality of life for children with lower-limb disabilities. Thus, it is imperative to facilitate and accelerate the development of pediatric technologies for gait rehabilitation, including their regulatory path. In this paper an overview of the U.S. Food and Drug Administration (FDA) clearance/approval process is presented. An example device has been used to navigate important questions facing device developers focused on providing lower limb rehabilitation to children in home-based or other settings beyond the clinic. 

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