Explore the vast range of titles available.

The advent of generative artificial intelligence (AI) offers transformative potential in the field of education. The study explores three main areas: (1) How did ChatGPT answer questions related to science education? (2) What are some ways educators could utilise ChatGPT in their science pedagogy? and (3) How has ChatGPT been utilised in this study, and what are my reflections about its use as a research tool? This exploratory research applies a self-study methodology to investigate the technology. Impressively, ChatGPT’s output often aligned with key themes in the research. However, as it currently stands, ChatGPT runs the risk of positioning itself as the ultimate epistemic authority, where a single truth is assumed without a proper grounding in evidence or presented with sufficient qualifications. Key ethical concerns associated with AI include its potential environmental impact, issues related to content moderation, and the risk of copyright infringement. It is important for educators to model responsible use of ChatGPT, prioritise critical thinking, and be clear about expectations. ChatGPT is likely to be a useful tool for educators designing science units, rubrics, and quizzes. Educators should critically evaluate any AI-generated resource and adapt it to their specific teaching contexts. ChatGPT was used as a research tool for assistance with editing and to experiment with making the research narrative clearer. The intention of the paper is to act as a catalyst for a broader conversation about the use of generative AI in science education.

Educational researchers and practitioners assert that supportive school and classroom climates can positively influence the academic outcomes of students, thus potentially reducing academic achievement gaps between students and schools of different socioeconomic status (SES) backgrounds. Nonetheless, scientific evidence establishing directional links and mechanisms between SES, school climate, and academic performance is inconclusive. This comprehensive review of studies dating back to the year 2000 examined whether a positive climate can successfully disrupt the associations between low SES and poor academic achievement. Positive climate was found to mitigate the negative contribution of weak SES background on academic achievement; however, most studies do not provide a basis for deducing a directional influence and causal relations. Additional research is encouraged to establish the nature of impact positive climate has on academic achievement and a multifaceted body of knowledge regarding the multilevel climate dimensions related to academic achievement.

Virtual and augmented (VAR) technology is in the early stages of being adopted as a teaching platform in higher education. The technology can facilitate immersive learning in environments that are not usually physically accessible to students via 3D models and interactive 360° videos. To date, adoption rates of VAR technology for teaching have not been well described across a higher education institution. Further, there is an absence of information on the optimal VAR laboratory designs and cost per student. In this study, a purpose designed virtual reality laboratory was formed in 2017 at The University of Sydney, housing 26 Oculus Rift headset units. An evaluation was conducted on the design, costs, rates of teaching adoption and student experiences over five teaching periods (2.5 years). Over this period, 4833 students were taught in the laboratory across 7952 student visits. The laboratory was used most by the Faculty of Engineering (53%), followed by the Faculty of Arts & Social Science (23.8%) and Faculty of Science (23.2%). For engineering, the units of study using the laboratory represented only 1.4% of annual faculty subjects offered. This confirms that adoption was in the initial stage of innovation diffusion. The laboratory saw a 250% increase in student numbers over the period of evaluation and 71.5% of students surveyed (n = 295) reported enhanced learning outcomes. The cost per visit was only AU$ 19.50. These findings give confidence to higher education institutions that the right VAR technology infrastructure is a sound educational investment for the future.

This qualitative study examines how pre-service teachers incorporate asset-based, multilingual and equity-focused pedagogies, prioritizing students’ funds of knowledge and advocating for culturally relevant and sustaining approaches. Through an analysis of 92 social studies unit plans developed by pre-service teachers in the final semester of their teacher credential program, the study highlights students’ efforts in integrating locally relevant curriculum, translanguaging, and inclusive pedagogies in their teaching. The study emphasizes the transformative potential of integrating linguistic and cultural resources into content area teaching to cultivate inclusive and equitable learning environments for emergent bilinguals.

In this article, I argue that academic language is a raciolinguistic ideology that frames racialized students as linguistically deficient and in need of remediation. I propose language architecture as an alternative framing of language that can serve as a point of entry for resisting these raciolinguistic ideologies in both research and practice. I use this framework as a lens for analyzing the literacy demands of the Common Core State Standard (CCSS). Using data collected as part of a larger ethnographic study, I illustrate how Latinx children from bilingual communities have unique opportunities for engaging in the language architecture called for in the standards. I then describe a unit plan that I developed from this perspective. I end with a call for situating language architecture within broader political struggles seeking to dismantle the political and economic inequities that are the root causes of deficit perspectives of Latinxs and other racialized students.

The use of generative artificial intelligence (GenAI) in academia is a subjective and hotly debated topic. Currently, there are no agreed guidelines towards the usage of GenAI systems in higher education (HE) and, thus, it is still unclear how to make effective use of the technology for teaching and learning practice. This paper provides an overview of the current state of research on GenAI for teaching and learning in HE. To this end, this study conducted a systematic review of relevant studies indexed by Scopus, using the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. The search criteria revealed a total of 625 research papers, of which 355 met the final inclusion criteria. The findings from the review showed the current state and the future trends in documents, citations, document sources/authors, keywords, and co-authorship. The research gaps identified suggest that while some authors have looked at understanding the detection of AI-generated text, it may be beneficial to understand how GenAI can be incorporated into supporting the educational curriculum for assessments, teaching, and learning delivery. Furthermore, there is a need for additional interdisciplinary, multidimensional studies in HE through collaboration. This will strengthen the awareness and understanding of students, tutors, and other stakeholders, which will be instrumental in formulating guidelines, frameworks, and policies for GenAI usage.

BackgroundFew tools or rubrics exist to assess the quality of integrated STEM curricula, and existing tools focus on checklists of characteristics of integrated STEM. While such instruments provide important information about the presence and quality of certain curricular components, they do not assess the level and nature of integration of the curriculum as a whole. Thus, this study explores the development of a process focused to understand the nature of integration within a STEM curriculum unit.FindingsA conceptual flow graphic (CFG) was constructed for 50 integrated STEM curriculum units. Patterns in the nature of the interdisciplinary connections were used to categorize and understand the nature of integration and curricular coherence within each unit. The units formed four broad types of integrated STEM curricula: (i) coherent science unit with loosely connected engineering design challenge (EDC), (ii) engineering design-focused unit with limited connections to science content, (iii) engineering design unit with science content as context, and (iv) integrated and coherent STEM units. All physical science units were in the integrated and coherent category with strong conceptual integration between the main science concepts and the EDC. Curricula based in the Earth and life sciences generally lacked conceptual integration between the science content and the EDC and relied on the engineering design process to provide a coherent storyline for the unit.ConclusionsOur study shows that engineering practices can serve as a contextual integrator within a STEM unit. The utilization of an EDC also provides the potential for conceptual integration because engineering is grounded in the application of science and mathematics. Integrated STEM curricula that purposefully include science and mathematics concepts necessary to develop solutions to the EDC engage students in authentic engineering experiences and provide conceptual integration between the disciplines. However, the alignment of grade-level science standards with the EDC can be problematic, particularly in life science and Earth science. The CFG process provides a tool for determining the nature of integration between science and mathematics content and an EDC. These connections can be conceptual and/or contextual, as both forms of integration are appropriate depending on the instructional goals.

Although Machine Learning (ML) is integrated today into various aspects of our lives, few understand the technology behind it. This presents new challenges to extend computing education early to ML concepts helping students to understand its potential and limits. Thus, in order to obtain an overview of the state of the art on teaching Machine Learning concepts in elementary to high school, we carried out a systematic mapping study. We identified 30 instructional units mostly focusing on ML basics and neural networks. Considering the complexity of ML concepts, several instructional units cover only the most accessible processes, such as data management or present model learning and testing on an abstract level black-boxing some of the underlying ML processes. Results demonstrate that teaching ML in school can increase understanding and interest in this knowledge area as well as contextualize ML concepts through their societal impact.

Objective. To review mastery learning and provide recommendations for implementation in a competency-based curriculum. Findings. Mastery learning, introduced in the 1960s, was developed to ensure all students reach a desired level of mastery or competency. In this model, students acquire knowledge, skills, or attitudes and then complete formative assessments on that learning. If they achieve the desired level, they can proceed to enrichment activities. Students who do not meet the desired level of mastery proceed through corrective activities and retesting. Evidence suggests students within a mastery learning model perform better academically than those in nonmastery learning models with moderate effect sizes. Mastery learning may result in better performance due to several theoretical reasons, including aspects of motivation, testing, and feedback. Conclusion. We make several recommendations on how to modernize mastery learning for apply it to the pharmacy education, including the recommendation to use more cumulative testing and assessment of baseline knowledge and skills. In addition, models of successive relearning may be applied to this model.

This research paper is based on a broader exploratory case study of a sustainability tour that the authors undertook. The larger study explored “the concept of learning application through the case of a sustainability tour” (Gillard, 2016, p. 226 ). The tour was part of a certificate program for sustainable community development offered to mid-career professionals through a continuing education unit at a large Canadian academic institution. Employing qualitative methods, the authors conducted semi-structured interviews, then analyzed the data, including course documents, to garner participants’ perceptions of what they learned “on tour” as well as how their learning had subsequently been applied. The study also identified salient features of the tour and the ways in which the tour format (or other contextual factors) may have inhibited learning and its subsequent application. This research paper presents some relevant findings, practical implications, and lessons learned regarding the sustainability tour pedagogy. Cet article de recherche s’appuie sur une étude de cas exploratoire plus large d’une excursion durable entreprise par l’équipe de recherche. L’étude plus large a exploré « le concept de l’application pédagogique par le cas d’une excursion durable » (Gillard, 2016, p. 226). L’excursion faisait partie d’un programme de certificat en développement communautaire durable offert aux personnes professionnelles de mi-carrière par l’unité de formation continue au sein d’un grand établissement universitaire canadien. À l’aide de méthodes qualitatives, l’équipe de recherche a mené des entrevues semi-dirigées, puis a analysé les données, y compris les documents de cours, pour observer à la fois les perceptions des personnes participantes de ce qu’elles avaient appris pendant l’excursion et l’application subséquente de ces apprentissages. L’étude a aussi relevé les principales caractéristiques de l’excursion et en quoi le format (ou d’autres facteurs contextuels) de celle-ci auraient pu empêcher l’apprentissage et son application subséquente. Cet article de recherche présente plusieurs résultats pertinents, implications pratiques et leçons tirées relatifs à la pédagogie de l’excursion durable.