Yeter, Ibrahim H.

The purpose of this study was to investigate how the “Making a Makerspace” (MM) program can enhance children’s maker literacy and teachers’ understanding of maker education in makerspaces. The program was carried out in two kindergartens in China for three months and involved 407 children and 24 teachers. Six classrooms in each kindergarten were either assigned to the Makerspace condition or the control condition. Results from teacher questionnaires and observations of the children’s maker activities showed significant improvements in problem finding & solving, hands-on, creative design, and communication skills among the children in the Makerspace condition compared to the control condition. The study revealed that children in 4- and 5-year-old classes were proficient in using the Engineering Design Process in maker activities, but this was not the case for 3-year-old classes. The teachers also reported positive experiences with the MM program. This study highlights the effectiveness of makerspaces in early childhood education and provides a practical case for implementing makerspaces in kindergarten classrooms.

Biomimicry is an interdisciplinary field that aims to provide sustainable solutions to technical issues. However, learners often encounter challenges in the application of biomimicry due to the multidisciplinary requisites and abstract thinking skills required. Although multiple hands-on activities and teaching strategies have been explored, significant obstacles remain. Recently, generative artificial intelligent tools have become readily accessible to the general public, among which is ChatGPT. ChatGPT is known for generating detailed responses to user inquiries and has demonstrated efficacy in enhancing learning, although its specific application to biomimicry education has yet to be explored. To bridge this knowledge gap, this study seeks to evaluate the capabilities of ChatGPT in helping its users identify biomimetic solutions. It is found that the effectiveness of ChatGPT in biomimicry education significantly depends on the user’s ability to formulate knowledgeable and effective prompts. Although, a novice user can use ChatGPT to get a fundamental overview of the technical challenge and explore potential sources of bioinspiration. The study proposes a theoretical framework to guide users in the effective use of ChatGPT for biomimicry education and application. In addition, users are cautioned against ChatGPT responses and advised to employ it as a tool to complement their own knowledge gaps. The results from this study can offer insights for teachers and self-directed learners on the effective use of prompts in ChatGPT for biomimicry education. Future investigations will seek to validate this framework by evaluating users’ experiences and feedback on its application in creating prototypes.

Biomimicry is an interdisciplinary design approach that provides solutions to engineering problems by taking inspiration from nature. Given the established importance of biomimicry for building a sustainable world, there is a need to develop effective curricula on this topic. In this study, a workshop was conducted twice in Singapore: once with 14 students from a local high school in Singapore, and once with 11 undergraduate students in engineering from the United States. The workshop aimed to better understand how students conceptualize biomimicry following the bottom-up and top-down biomimetic methods. The workshop contained a lecture and laboratory session, and data were collected via questionnaires, field observation, and participant presentations at the end of the laboratory session. A qualitative analysis revealed that the top-down biomimetic approach was initially understood using vague and generic terms. In contrast, the students described the bottom-up approach using precise and technical vocabulary. By naming the themes highlighting the students’ conceptualizations, it was concluded that strengthening the principle that makes the natural object unique and increasing interdisciplinary knowledge are needed to help them perform the top-down approach. The results from this work should be confirmed with a more significant number of participants, and they could help develop a curriculum to teach the two approaches effectively by providing tools to help the students generalize their ideas and abstract meaning from systems.

This preliminary study proposes the Engineering Pedagogy Scale (EPS), a means of measuring PCK characteristics that may be important for effective engineering instruction. The EPS aims to be used for the evaluation, description, and categorization of the domains and indicators that represent the practices that an ideal teacher exhibits while teaching engineering practices in elementary classrooms. Throughout this project, existing instruments were investigated thoroughly, however, and none were suitable for the engineering context. This study exploring and developing relevant initial indicators is part of a series of studies; subsequent studies will provide specific indicators for each domain and describe field testing and analysis of the EPS. After iteratively designed discussions throughout the project, the preliminary findings indicated that the proposed observational instrument resulted in seven distinctive main domains. These domains included (1) unit-specific content knowledge, (2) engineering design process (EDP), (3) productive failure and success, (4) interdisciplinary applications, (5) questioning, (6) teamwork, and finally (7) discussion, feedback, and reflection. This study has both theoretical and practical implications. Theoretically, the study will contribute to the engineering education literature by extending the concept of PCK (Shulman, 1986) to the engineering education field and its theoretical viability in the elementary school setting. Practically, it is paramount that administrators, professional developers, curriculum specialists, and teachers come to understand what skills, pedagogies, and practices are needed to facilitate the successful implementation and improvement of engineering instruction. As such, a standard instrument that evaluates teachers’ E-PCK would help to identify where improvement is needed.

The notion of teaching experts’ habits of mind (e.g., computational thinking and scientific thinking) to novices seems to have inspired many educators and researchers worldwide. In particular, a great deal of efforts has been invested in computational thinking (CT) and its manifestations in different fields. However, there remain some troubling spots in CT education as far as how to teach it at different levels of education. The same argument applies to teaching scientific thinking (ST) skills. A remedy has been suggested to narrow CT and ST skillsets down to core cognitive competencies so they can be introduced in early and middle grades and continue to be nurtured during secondary and post-secondary years. Neuroscientists suggest that the act of (computational) thinking is strongly linked to the acts of information storage/retrieval by our brain. Plus, years of research have shown that retrieval practices promote not only knowledge retention but also inductive reasoning and deductive reasoning. Not surprisingly, these reasoning skills are core elements of both CT and ST skillsets. This article will mesh the findings of a teacher professional development with the existing literature to lay a claim that retrieval practices enhance CT and ST skills. The study offered training to secondary school teachers (n = 275) who conducted classroom action research to measure the impact of retrieval practices on teaching and learning of STEM and CT concepts. We used a quasi-experimental research design with purposeful sampling and a sequential mixed-methods approach focusing on the impact of professional development on teacher outcomes and, in turn, on student outcomes. A survey of teacher participants showed that the majority (96%) of survey respondents (n = 232) reported a good understanding of retrieval strategies, and how relevant ideas can be implemented and tested in the classroom. A large number of action research (target-control) studies by teachers (n = 122) showed that students who learned STEM and CS concepts through retrieval practices consistently scored 5–30% higher than those using the usual blocked practice. In most cases, the difference was statistically significant (p < 0.05). While the study contributes to retrieval practices literature, those looking for best practices to teach core CT and ST skills should benefit from it the most. The study concludes with some recommendations for future research based on the limitations of its current findings.

This research is to practice a full paper that discusses ethics in engineering. Engineering graduates are expected to have ethical critical thinking and problem-solving skills to tackle real-world complex problems in the workplace. Course curriculum could benefit from more authentic learning and interdisciplinary teaching focused on engineering design and problem-solving. This pilot project incorporates a research-based design thinking framework EDIPT (Empathize, Define, Ideate, Prototype, Test), developed by Stanford University to guide students through conceptualization-to-production processes in a newly designed engineering course at an internationally-renowned university in Singapore. The study aims to equip students for ethical problem-solving, support more innovative and feasible ideas and products, and allow students to better exhibit knowledge and accomplish the Engineering Accreditation Board (EAB) requirements. 36 third-year engineering students (39% female and 61% male) participated in this study through hybrid online/offline course activities and working with industry partners for real-world problem-solving. While the entire project implements an exploratory sequential mixed method research design, with multi-layered research data including student interviews and in-course and post-course reflections, this paper focuses on the participants’ open-ended pre-course survey responses about ethics in engineering. We conducted qualitative inductive analysis using an open coding technique and created descriptive codes. Preliminary findings suggest five emergent themes of ethical considerations, namely 1) client-centered responsibility, 2) intellectual property infringement/originality, 3) macro ethical considerations, 4) professionalism, and 5) others. Findings from this study will help to bolster research on ethical considerations in design thinking for the engineering field, as well as the applicability of foreign research frameworks in local practice contexts. Findings will also contribute to determining the best approach for improving the teaching framework for future iterations of the engineering courses, as well as assessing the suitability of applying design thinking to similar capstone courses within the university.

This work-in-progress reports on a project to establish differences between STEM education, and specifically Engineering Education, and other education fields/disciplines based on empirical observations. In this study we report on first steps towards a literature overview of such differences and on the development of an analytical framework to analyze the publications.

Artificial intelligence (AI) has permeated most facets of life in the 21st century and has rapidly transformed various aspects of modern society. From entertainment to education, these advanced technologies have achieved a high level of competency in skills that once necessitated human involvement. Given AI's potential impact, ensuring students are literate in AI will support the careful integration of these advanced technologies to achieve sustainable development goals. This review hence examines the avenues for integrating AI literacy into elementary education by analyzing current global initiatives focused on implementing AI literacy education. The purpose is to support innovations within the educational framework to develop a universally accessible AI literacy education program. In line with this purpose, this study explores worldwide AI literacy initiatives that use hands-on activities, collaborative learning, and project-based learning to introduce AI fundamentals to diverse learners. Limitations on the provision of AI literacy education are also discussed, including professional development, openness to AI tools, and other challenges. This review aims to inform global efforts to support universal access to AI literacy education, which can ensure equitable outcomes for all learners, emphasizing the need for collaborative efforts to support the development and delivery of quality AI literacy education.

As Computational Thinking (CT) becomes an increasingly necessary skill, it is crucial to examine how CT can be taught in the classroom. Pedagogical Content Knowledge (PCK) is a practical concept to examine how CT education can be developed. This systematic literature review presents the discussion of K-8 teachers’ PCK in the implementation of CT- related activities in the classroom. Studies were extracted from Google Scholar’s database. Among these studies, 14 articles were deemed to be relevant for a more in-depth examination. Findings from this preliminary literature review suggest that teachers have clear purposes and goals for teaching CT and various instructional strategies for teaching CT. However, the existing studies lacked information about teachers’ knowledge and beliefs regarding the methods for assessing students’ CT. Practical implications and future directions to enhance K-8 teachers’ PCK on CT are discussed in this study.

This paper presents the results of an investigation on pre-service teacher' conceptions of computational thinking (CT) in Singapore prior to a two-hour introductory module on CT. Of 407 teachers, 280 provided valid responses to the pre-survey, which included questions on teachers' school subjects, current understandings of CT, confidence in their understandings of CT, and sources of the understandings. We deductively coded the open-ended responses through thematic analysis using four categories from a synthesis review on teachers' preconceptions of CT. The participants were classified into three groups, including STEM (primarily sciences and mathematics), non-STEM (e.g., humanities and languages), and mixed-disciplines (e.g., science and English language arts). The findings of the pre-survey showed that 42% of respondents (n=118) reported no prior knowledge of CT. Among the remaining 162 responses, the most popular view of CT was problem solving using various kinds of thinking, such as "logic", "abstraction", "step-by-step", and "decomposition" (n=106). STEM and mixed disciplines teachers (33%) reported higher levels of confidence compared to non-STEM teachers (15%). A higher percentage of STEM (64%) and mixed-disciplines (60%) pre-service teachers indicated learning about CT from formal courses during their university studies or teacher training, compared to non-STEM teachers (52%). This suggests that schools of education can play a bigger role in expanding CT awareness among pre-service teachers from non-STEM backgrounds. Finally, implications for teacher education are widely discussed.