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This paper aims to discuss research and design of learning activities involving activity tracking and wearable activity tracking technology.

Three studies are summarized as part of a program of research that sought to design new learning activities for classroom settings. The first used data from a qualitative interview study of adult athletes who self-track. The second used video excerpts from a designed learning activity with a group of fifth grade elementary students. The third study draws largely on quantitative assessment data from an activity tracking unit enactment in a rural sixth grade class.

Activity tracking appears to provide opportunities for establishing benchmarks and calibration opportunities related to intensity of physical activities. Those features of activity tracking can be leveraged to develop learning activities where elementary students discover features of data and how data are affected by different distributions. Students can show significant improvement related to statistical reasoning in classroom instructional units that centralize the use of self-tracked data.

As activity tracking is becoming a more ubiquitous practice with increased pervasiveness and familiarity with mobile and wearable technologies, this paper demonstrates a topical intersection between the information and learning sciences, illustrates how self-tracking can be recruited for instructional settings, and it discusses concerns that have emerged in the past several years as the technology related to activity tracking begins to be used for educational purposes.

In light of growing interest in the maker movement and electronic textiles (e-textiles) as an educational technology, the purpose of this paper is to characterize competence change in undergraduate students who participated in a semester-length course that used e-textiles.

This qualitative and exploratory research study used semi-structured pre- and post-interviews with undergraduate students (N=7) thinking aloud through novel tasks in order to understand their learning from a semester-long course involving e-textiles. This design was intended to elicit student thinking with commercial toys that differed from the types of projects they had completed in their course. A coding scheme was developed and organized into an analytical rubric to map depth of understanding in the three spheres of circuitry, computation, and crafting. Select cases of pre-post change were identified to illustrate growth in specific content spheres.

Students’ ability to reason through novel tasks showed growth in each sphere, provided that the student did not begin with a full level of sophistication in a particular area during the pre-interview. Although students may not reach normative or expert-like competence, there are demonstrable indications of growth for each of the dimensions.

As e-textiles are increasingly turned to educationally, the creation and presentation of a rubric for describing competence in three spheres, especially the previously understudied area of crafting knowledge in e-textiles, is itself a useful contribution to the field. This is also an extension of e-textiles learning research into undergraduate instruction, an as-yet understudied setting for maker education.

With increased focus on data literacy and data science education in K-12, little is known about what makes a data set preferable for use by classroom teachers. Given that educational designers often privilege authenticity, the purpose of this study is to examine how teachers use features of data sets to determine their suitability for authentic data science learning experiences with their students.

Interviews with 12 practicing high school mathematics and statistics teachers were conducted and video-recorded. Teachers were given two different data sets about the same context and asked to explain which one would be better suited for an authentic data science experience. Following knowledge analysis methods, the teachers’ responses were coded and iteratively reviewed to find themes that appeared across multiple teachers related to their aesthetic judgments.

Three aspects of authenticity for data sets for this task were identified. These include thinking of authentic data sets as being “messy,” as requiring more work for the student or analyst to pore through than other data sets and as involving computation.

Analysis of teachers’ aesthetics of data sets is a new direction for work on data literacy and data science education. The findings invite the field to think critically about how to help teachers develop new aesthetics and to provide data sets in curriculum materials that are suited for classroom use.

This paper aims to introduce and explores the use of electrodermal activity (EDA) data as a tool for obtaining data about youth engagement during maker learning activities.

EDA and survey data were collected from a yearlong afterschool maker program for teens that met weekly and was hosted at a children’s museum. Data from four youth who were simultaneously present for eight weeks were examined to ascertain what experiences and activities were more or less engaging for them, based on psychophysiological measures.

Most of the focal youth appeared to show higher levels of engagement by survey measures throughout the program. However, when examined by smaller time intervals, certain activities appeared to be more engaging. Planning of maker activities was one space where engagement was higher. Completing sewing projects with minimal social interaction appeared to be less engaging. Specific activities involving common maker technologies yielded mixed levels of engagement.

Some research is emerging that uses EDA data as a basis for generating inferences about various states while participating in maker learning activities. This paper provides a novel analysis building on some techniques established in the still emergent body of prior research in this area.

This paper aims to be a think piece that promotes discussion around the design of coding toys for children. In particular, the authors examine three different toys that have some sort of block-based coding interface. The authors juxtapose three different design features and the demands they place on young children learning to code. To examine the toys, the authors apply a framework developed based on Gibson’s theory of affordances and Palmer’s external representations. The authors look specifically at the toys: interface design, intended play scenario and representational conventions for computational ideas.

As a research team, the authors have been playing with toys, observing their own children play with the toys and using them in kindergarten classrooms. In this paper, the authors reflect specifically on the design of the toys and the demands they place on children.

The authors make no claims about whether one toy/design approach is superior to another. However, the differences that the authors articulate should serve as a provocation for researchers and designers to be mindful about what demands and expectations they place on young children as they learn to code and use code to learn in any given system.

As mentioned above, the authors want to start a discussion about design of these toys and how they shape children's experience with coding.

There is a push to get coding and computational thinking into K-12, but there is not enough research on what this looks like in early childhood. Further, while research is starting to emerge on block-based programming vs text-based for older children and adults, little research has been done on the representational form of code for young children. The authors hope to start a discussion on design of coding toys for children.

Much remains unknown about how young children orient to computational objects and how we as learning scientists can orient to young children as computational thinkers. While some research exists on how children learn programming, very little has been written about how they learn the technical skills needed to operate technologies or to fix breakdowns that occur in the code or the machine. The purpose of this study is to explore how children perform technical knowledge in tangible programming environments.

The current study examines the organization of young children’s technical knowledge in the context of a design-based study of Kindergarteners learning to code using robot coding toys, where groups of children collaboratively debugged programs. The authors conducted iterative rounds of qualitative coding of video recordings in kindergarten classrooms and interaction analysis of children using coding robots.

The authors found that as children repaired bugs at the level of the program and at the level of the physical apparatus, they were performing essential technical knowledge; the authors focus on how demonstrating technical knowledge was organized pedagogically and collectively achieved.

Drawing broadly from studies of the social organization of technical work in professional settings, we argue that technical knowledge is easy to overlook but essential for learning to repair programs. The authors suggest how tangible programming environments represent pedagogically important contexts for dis-embedding young children’s essential technical knowledge from the more abstract knowledge of programming.

Purpose – Driver distraction and other forms of driver inattention remain significant road safety problems. The purpose of this chapter is to explore recent developments in theoretical and empirical research on driver distraction and inattention and provide the reader with a sense for, and understanding of, the key issues.

Methodology – Key references from the literature are reviewed and discussed.

Findings – First, we discuss one way of conceptualising the distinction between driver distraction and other forms of inattention, as well as the mechanisms which may underlie these forms of inattention. Second, we underscores how driver distraction may derive from a plethora of sources, and how the potential for performance degradation deriving from driver interaction with these sources may be moderated by a range of factors. Third, we review recent literature on the types of impairments in driving performance and safety associated with driver distraction. Fourth, we outline recent literature on driver distraction and inattention in the realm of highly automated vehicles that will drive the transport future. Finally, we discuss some promising strategies aimed at preventing and mitigating the impact of driver distraction.

Research implications – There are many gaps in the driver distraction literature that need to be addressed. In addition, further research needs to be undertaken to examine the role of driver distraction in the realm of highly automated vehicles.

Practical implications – The findings point towards of a range of injury prevention countermeasures that have potential to prevent and mitigate driver distraction.

This paper examines the port of Mombasa’s attempted implementation of computer-based terminal operating systems (TOS); the challenges faced and the outcomes. In addition to enhancing its operations efficiency, a key motivation for the technology was to facilitate better integration and connectivity to the Belt and Road as a key gateway along the key route. It utilised a qualitative single-case methodology, involving a combination of semi-structured interviews, non-participant observations and content analysis of relevant policy documents and reports provided by the port. The paper finds that the attempt to adopt and implement TOS at the port mostly failed as a result of a complex combination of technological, organisational and environmental factors. Most importantly, the wider business environment was ill equipped with the necessary information communication technology (ICT) infrastructure to support effective implementation. There was also a general lack of appropriately skilled workers to support and drive the same.