Tangible Interaction and Learning: The Case for a Hybrid Approach

Research involving tangible interaction and children has often focused on how tangibles might sup- port or improve learning compared to more traditional methods. In this paper, we review three of our research studies involving tangible computer programming that have addressed this question in a variety of learning environments with a diverse population of children. Through these studies, we identify situations in which tangible interaction seems to offer advantages for learning; how- ever, we have also identify situations in which tangible interaction proves less useful and an alternative interaction style provides a more appropriate medium for learning. Thus, we advocate for a hybrid approach—one that offers teachers and learners the flexibility to select the most appropriate interaction style to meet the needs of a specific situation

A Curriculum Unit on Programming and Robotics

The Tangible Kindergarten project studies how, when given age-appropriate tools, young children can actively engage in computer programming and robotics in a way that is consistent with developmentally appropriate practice. This research project explores the creation of novel human computer interaction techniques to support learning with technology in early elementary school, with a focus on kindergarten. Since many modern graphical user interfaces are not designed with the developmental needs of such young learners in mind, they are generally ill-suited for use in early elementary school classrooms, especially for computer programming activities. To overcome this problem, this research project has created a tangible-graphical hybrid programming language specifically for young children, the Creative Hybrid Environment for Robotics Programming, or CHERP

A Normative Analysis of the TechCheck Computational Thinking Assessment

TechCheck is an assessment of Computational Thinking (CT) for early elementary school children consisting of fifteen developmentally appropriate unplugged challenges that probe six CT domains. The first version of TechCheck showed good psychometric properties as well as ease of administration and scoring in a validation cohort of 768 children between 5 and 9 years of age. To increase sensitivity and reduce possible ceiling and floor effects, grade-specific versions of TechCheck (K, 1, 2) were subsequently created. In the present study, we explored how CT skills could be compared across grades when grade-specific versions of TechCheck are administered. First, we examined TechCheck raw score distributions and responses within CT domains in a representative sample of students from the three grades. Grade-specific Z-scores and percentile rankings were then calculated. To show utility of this normalization system, we used percentiles to compare CT outcomes between first and second graders who participated in a ScratchJr coding educational intervention. While TechCheck change scores suggested an unexpected 42.74% difference in CT outcomes between first and second grade, application of the normative scoring system indicated a more plausible 5.17 percentile rank difference between grades. Normative analysis may provide a more meaningful way to compare results across grades when grade-specific versions of TechCheck are used. Implications for the future use of the TechCheck CT assessments are discussed

Comprehension of computer code relies primarily on domain-general executive brain regions

Computer programming is a novel cognitive tool that has transformed modern society. What cognitive and neural mechanisms support this skill? Here, we used functional magnetic resonance imaging to investigate two candidate brain systems: The multiple demand (MD) system, typically recruited during math, logic, problem solving, and executive tasks, and the language system, typically recruited during linguistic processing. We examined MD and language system responses to code written in Python, a text-based programming language (Experiment 1) and in ScratchJr, a graphical programming language (Experiment 2); for both, we contrasted responses to code problems with responses to content-matched sentence problems. We found that the MD system exhibited strong bilateral responses to code in both experiments, whereas the language system responded strongly to sentence problems, but weakly or not at all to code problems. Thus, the MD system supports the use of novel cognitive tools even when the input is structurally similar to natural language.National Science Foundation (Grant 1744809

Tangible interaction and learning: the case for a hybrid approach

Research involving tangible interaction and children has often focused on how tangibles might sup- port or improve learning compared to more traditional methods. In this paper, we review three of our research studies involving tangible computer programming that have addressed this question in a variety of learning environments with a diverse population of children. Through these studies, we identify situations in which tangible interaction seems to offer advantages for learning; how- ever, we have also identify situations in which tangible interaction proves less useful and an alternative interaction style provides a more appropriate medium for learning. Thus, we advocate for a hybrid approach—one that offers teachers and learners the flexibility to select the most appropriate interaction style to meet the needs of a specific situation