The integration of Artificial Intelligence (AI) literacy into college curricula is a pressing but complex challenge, particularly in non-technical fields like business. This paper presents a case study of a pedagogical intervention designed to embed AI literacy within a required college mathematics course. The intervention employed a Problem-Based Learning (PBL) framework where 120 business students used tools like ChatGPT and matrix calculators to solve an authentic data-driven business problem. We analyzed data from the final assessment artifact – a digital magazine – to evaluate the development of specific AI literacy competencies. Initial findings from this pilot implementation indicate that the PBL approach was effective in developing students’ skills in data-driven argumentation, critical evaluation of AI-generated outputs, and the ability to connect abstract mathematical models to practical AI applications. The study demonstrates a promising replicable model for integrating AI literacy into foundational courses, but also highlights key challenges, including the need for explicit scaffolding in critical AI evaluation. This paper contributes empirical insights from an initial implementation, offering a practical framework and actionable lessons for educators designing AI literacy curricula.
Due to technological advancements, robotics is findings its way into the classroom. However, workload for teachers is high, and teachers sometimes lack the knowledge to implement robotics education. A key factor of robotics education is peer learning, and having students (near-)peers teach them robotics could diminish workload. Therefore, this study implemented near-peer teaching in robotics education. 4 K10-11 secondary school students were teachers to 83 K5-6 primary school students. The intervention included 4 3-hour robotics lessons in Dutch schools. Primary school students completed a pre- and post-intervention questionnaire on their STEM-attitudes and near-peer teaching experience, and a report on their learning outcomes. Interaction with near-peer teachers was observed. After the lessons, a paired-samples t-test showed that students had a more positive attitude towards engineering and technology. Students also reported a positive near-peer teaching experience. Conventional content analysis showed that students experienced a gain in programming and robotics skill after the lessons, and increased conceptual understanding of robotics. The role the near peer teachers most frequently fulfilled was formative assessor. Near-peer teachers could successfully fulfil a role as an engaging information provider. This study shows that near-peer teachers can effectively teach robotics, diminishing workload for teachers. Furthermore, near-peer robotics lessons could lead to increased STEM-attitudes.
In recent years, Artificial Intelligence (AI) has shown significant progress and its potential is growing. An application area of AI is Natural Language Processing (NLP). Voice assistants incorporate AI by using cloud computing and can communicate with the users in natural language. Voice assistants are easy to use and thus there are millions of devices that incorporates them in households nowadays. Most common devices with voice assistants are smart speakers and they have just started to be used in schools and universities. The purpose of this paper is to study how voice assistants and smart speakers are used in everyday life and whether there is potential in order for them to be used for educational purposes.
Computer science concepts have an important part in other subjects and thinking computationally is being recognized as an important skill for everyone, which leads to the increasing interest in developing computational thinking (CT) as early as at the comprehensive school level. Therefore, research is needed to have a common understanding of CT skills and develop a model to describe the dimensions of CT. Through a systematic literature review, using the EBSCO Discovery Service and the ACM Digital Library search, this paper presents an overview of the dimensions of CT defined in scientific papers. A model for developing CT skills in three stages is proposed: i) defining the problem, ii) solving the problem, and iii) analyzing the solution. Those three stages consist of ten CT skills: problem formulation, abstraction, problem reformulation, decomposition, data collection and analysis, algorithmic design, parallelization and iteration, automation, generalization, and evaluation.
The Computer Science Unplugged activities and project has been an influential STEM (Science, Technology, Engineering & Mathematics) initiative, providing enrichment and teaching activities supporting computational thinking. Many of its activities are suitable for children. One of the most popular Unplugged activities is "Kid Krypto", invented by Mike Fellows and Neal Koblitz. Kid Krypto demonstrates the mathematics underlying public-key cryptography without using advanced mathematics. The paper gives an example of a Kid Krypto-style encryption system that is based on disjoint cycles in a graph or network and which is accessible to a very young audience. Also described is the original Kid Krypto system which is based on a version of dominating set called perfect code. The paper urges research scientists to participate in mathematical sciences communication and outreach.