Syntax remains a major barrier for novices. Although block-based systems reduce or eliminate syntax errors, conditionals still challenge learners, likely because their semantics remain implicit. In this paper, we address this problem by introducing a semantics-first, state-visible programming approach inspired by the classic visual language Stagecast Creator. To demonstrate its usefulness, we designed Elephant, a unified, Karel-like research platform that supports three equally expressive programming paradigms: (i) semantics-first programming, (ii) block-based programming with the Blockly library, and (iii) text-based programming in JavaScript with domain-specific libraries. We then deployed Elephant in two within-subjects studies with secondary-school students (N = 39) to compare semantics-first programming to textual and block-based baselines, keeping the program semantics constant across modes and reducing cross-tool confounds. Results indicate, among other things, that semantics-first programming yields significantly higher task performance, suggesting that increasing the visibility of the program state during program composition could support greater outcomes in secondary computing education.

This paper presents a comparative study of Algot, a visual programming language designed to bridge the syntax-semantics gap via liveness and programming by demonstration, and the textual programming language Python. We conducted an experimental, within-subjects study with 24 undergraduate computer science students who performed recursion-based tasks in each language while their cognitive load was measured using an electroencephalogram and a validated survey instrument. The students received a brief introduction to Algot, but were all familiar with Python. The students performed significantly better when programming in Algot, but the cognitive load levels were similar according to both instruments. Our results provide evidence that within the domain that was tested, Algot can be quickly learned, and that students do not find it more cognitively demanding than working in a familiar language.

This paper examines whether undergraduate students perform better and experience lower cognitive load when programming in Algot, a visual programming language that supports programming by demonstration, than in the textual programming language Python. We recruited 38 first-semester computer science university students who had received prior instruction in the programming language Python but were unfamiliar with Algot. Participants reviewed a 12-minute video tutorial about Algot and performed the same programming tasks in Python and Algot. We graded student submissions, estimated cognitive load through physiological measures and a validated post-test survey, and evaluated free-form feedback. Our results indicated that students experienced lower negative (extraneous and intrinsic) and higher positive (germane) cognitive load when programming in Algot. Additionally, students programming in Algot scored an average grade of 5.8 out of 10, compared to an average grade of 3.4 when using Python for the same tasks, and according to the free-form feedback, Algot is perceived as well-designed and easy to learn.

In this paper we present a new initiative to promote collaborative learning through industry partnered, interdisciplinary, student and user centred projects. This was achieved through the development of rehabilitation devices augmented with gamified software. Today development of software systems often requires people from different specialities who can work in multidisciplinary teams to achieve a common objective. A key challenge, therefore, is producing graduates with an understanding of a number of disparate skills across many discipline boundaries. Undergraduates may be knowledgeable in one specific discipline but will not be aware of the issues brought to bear by other relevant disciplines. In an effort to overcome this limitation, a cross-discipline course “Serious Games and Welfare Technology” was developed that allows students from different disciplines to work together to produce innovative, technology- supported health solutions. The course, an EU funded Erasmus+ initiative, was supported by a MOOC and enabled multi- disciplined and multinational teams to produce solutions for leading Health technology companies in the areas of rehabilitation and aging support. Following the first year of offering the course with a cohort of students from 5 countries, we report on the experiences and outcomes achieved from a number of viewpoints.