Insights Into Young Children's Coding With Data Analytics

Understanding Learning Analytics

Assessing children's knowledge is a challenge, and when we isolate computational thinking as our measure, the challenge becomes even greater. Computational thinking is a thought process, rather than a right or wrong answer on a test, and therefore our question extends beyond ‘how to assess children's knowledge’ and becomes more ‘how to measure a child's way of thinking’. In this chapter, we explore how Learning Analytics is used to try to answer this question. Learning Analytics is the process of collecting and analyzing data from learners in order to better understand and optimize their learning processes (Gašević et al., 2015). While Learning Analytics does not solve the issue of how to measure learning, it does offer another angle to look at a children's learning process. Combined with other assessments, Learning Analytics can provide a richer view of a child's learning process.

Learning Analytics collects a wide variety of data, all of which are outcomes of learners’ interactions with learning platforms. Learning platforms include online games, applications, learning management systems, and Massive Open Online Courses (MOOCs), such as Khan Academy, (Fischer et al, 2020; Gašević et al., 2015). A user interaction can be many things including number of clicks, the number of logins, and the duration in completing a lesson. Learning Analytics help educators to identify where a student is in their learning process, which allows the educators to better meet the needs of students of all different types of learning styles and paces (Baker and Siemens, 2014). Learning Analytics is most commonly used in higher education to measure school completion and learning performances (Ifenthaler & Yau, 2020). By collecting this information, higher education institutions can better identify needs of students and therefore work to address those needs.

While Learning Analytics is used more commonly in higher education, it can be applied to early childhood education as well. One example is LAP: A Learning Analytics Platform prototype developed by PBS KIDS, a US public broadcasting service catered to children (Roberts et al, 2016). In this study, the main functions of LAP were to track, store, and analyze children’s (ages 2-8 years) interactions with the PBS KIDS math and literacy content including broadcasts, online videos, games, and offline activities. Children’s anonymous usage data were collected and packaged into custom reports for parents on how to better support their children’s learning needs. LAP measured learning in multiple ways. One way in which LAP assessed math was by reporting the accuracy and speed in answering mathematical problems. It was found that LAP measures were able to predict a reliable level of children’s math proficiency compared to the TEMA-3 scale, which is a standardized mathematics test for children from 3-8 years old (Ginsburg & Baroody, 2003). From this example, we see that usage data, collected from a Learning Analytics tool can successfully predict specific learning outcomes—even when the users are young children.

Another way in which Learning Analytics can be used, is to evaluate the appropriateness of the learning tools. In the case of Vatavu et al. (2015), Learning Analytics were used to assess the usability of touch screen devices. In the study, researchers asked 89 children (ages 3-6 years) to complete various tasks such as tapping, dragging, and dropping graphics on the touch-screen device. They found that children’s sensorimotor abilities, as measured by a validated sensorimotor evaluation, were correlated with touch performance such as task completion and accuracy rate (Vatavu et al., 2015). This study helps us to better understand young children’s ability to interact with touch screens, which in turn help us to create better age-appropriate touch interface designs. This is particularly relevant now, as many educational tools designed for young children come in the form of touchscreen apps. In this chapter, we explore one such app for children called ScratchJr, a freely downloadable tablet app that engages children ages 5-7 years in computer programming.