This paper presents findings from a thinking-aloud protocol exploring mental models in 28 elementary school math teachers during their initial attempt at composing and testing trigger-action rules for a smart tangible educational device. In the study, two sets of event-driven primitives were implemented in an End-User Development platform for guiding teachers with no programming experience in defining new functions of the device: "concrete", based on actual actions performed on the device, and "abstract", based on general definitions of events/actions. With a thematic analysis, we identified three different metaphors that drive participants’ interaction with the device. We discuss how the metaphors influenced performance and how the order of exposition to the two primitive sets impacted their grasping of the trigger-action logic. Our findings suggest the importance of guiding teachers in assuming effective metaphors for performing End-User Development tasks, to empower them to adopt an active role toward digital devices in education.

In this paper, we describe an empirical evaluation of the user's perceived usefulness of recommendations for configuration tasks in a smart home scenario. Our results suggest that while overall recommendations help improve the performance in the task, the psychological traits of Self-efficacy and Need for Cognition play an important role in determining the perceived usefulness of the recommendations. These effects are somehow different from those reported in other studies where recommendations are provided for a choice task rather than a constructive task. Thus, our results offer evidence regarding the importance of incorporating the evaluation of personality traits into the design of configuration constructive tasks in order to make informed decisions on whether and how to provide users with recommendations. Additionally, they show that it is crucial to take into account the nature of the task and, where possible, individual competencies.

Trigger-Action Programming is a commonly used paradigm in End-User Development interfaces, allowing users without programming experience to create new automation systems. Even if considered easy to grasp, this approach poses some challenges: non-programmers often confuse events (instantaneous occurrences) and states (prolonged occurrences), leading to critical errors in the definition of triggers. Although past research has already questioned the effectiveness of the typical if-then structure, there is a limited exploration of which specific linguistic cues might help or hinder users from distinguishing between events and states. Our study, involving 85 non-programmers, examines a broader pool of linguistic aspects, investigating (i) preferences for conjunctions and verbs when describing events and states and (ii) which conjunctions help users accurately differentiate these occurrences. Our results indicate that while participants tended to prefer temporally specific language, such as ” when ” for events and ” while ” for states, some of these conjunctions, like ” when ”, may not support users in accurately identifying and differentiating events from states, similar to the generic ” if ”. These findings underscore the role of specific language on non-programmers’ comprehension and mental representations of triggers. Designing interfaces with more easily graspable linguistic cues and mapping them at the system level may help guide non-programmer users in correctly structuring trigger-action rules.

Personalized learning methods have revolutionized education by allowing tailored teaching approaches to meet individual students’ needs. This approach, supported by educational technologies, aims to engage learners with diverse expertise levels by adapting content and methods accordingly. This demo introduces an End-User Development system that empowers teachers to create and define interactive behaviors of educational tools using Trigger-Action Programming (TAP). The system facilitates the creation of "vocabularies" specific to each learning subject and translates them into verbal primitives for trigger-action rule definition. These rules are then used in the customization of interfaces. This demo presents examples using a tangible device and a web-based educational game aimed to enrich education activities in elementary schools. Future directions include studying teachers’ appropriation of the use of TAP to customize learning material as well as adaptation in new domains and with different devices.

In this paper, we present a study aimed at evaluating how ChatGPT-4 understands end-users’ natural language instructions to express automation rules for smart home applications and how it translates them into Python code ready to be deployed. Our study used 34 natural language instructions written by end users who were asked to automate scenarios presented as visual animations. The results show that ChatGPT-4 can produce coherent and effective code even if the instructions present ambiguities or unclear elements, understanding natural language instructions and autonomously resolving 94% of them. However, the generated code still contains numerous ambiguities that could potentially affect safety and security aspects. Nevertheless, when appropriately prompted, ChatGPT-4 can subsequently identify those ambiguities. This prompts a discussion about prospective interaction paradigms that may significantly improve the immediate usability of the generated code.

Gamification and tangible user interfaces have been shown to enhance pupils’ engagement and their learning experiences. This study presents an evaluation of a simple gamified version of a tangible Internet of Things device (SMARTER) to support math learning. Twenty-one elementary school children participated in a workshop, interacting with the system and providing feedback. Results indicate good usability and a positive attitude toward the system. Children generally liked all the aspects, although the focus on mathematics was slightly lower appreciated. The study highlights the potential of integrating tangible user interfaces and gamified systems to enhance pupils’ engagement in education.

This paper presents a pilot study for an initial assessment of a tangible tool to support end-user programming (EUP) by teachers to facilitate learning mathematics in primary school. The study aimed to explore teachers’ reasoning strategies and mental representations during trigger-action rules composition. The pilot study provided initial insight into the strengths and weaknesses of this approach and useful hints for designing a larger and more robust study

In this paper, we present the preliminary implementation of SMARTER, a tangible tool for supporting children in learning the basics of mathematics, which has been loosely inspired by the Cuisenaire rods. The tool exploits the power of tangible manipulation offered by physical materials coupled with the possibility of providing contextual and engaging feedback provided by digital tools. An original and important goal of the SMARTER tool is to allow teachers to fully customize the experience of use by exploiting end-user development.

The Internet of Things is a pervasive technology widely adopted in several contexts ranging from smart homes to automotive cars. In this context, the End User Development is gaining momentum: different solutions support non-technical users to define the smart objects behavior to better satisfy their needs. This workshop aimed to stimulates participants in providing discussions in line with the workshop themes and goals, for example, user mental models, acceptance of EUD solutions, the role of AI in EUD tools, humanoid robots were discussed.