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Science education aims to foster knowledge-in-use, which is supported by the integration of scientific ideas. To study knowledge integration effectively, network analysis provides a valuable tool for visualizing and understanding how ideas are connected. Successful knowledge integration requires following a learning progression that leads to increasingly sophisticated connections between ideas. However, traditional learning progression models have limitations, as they often fail to account for the nonlinear and individualized nature of learning. This study explores the potential of digital learning environments and AI techniques to address these limitations by enabling frequent, high-resolution data collection and analysis in order to uncover individual students’ learning trajectories at a high resolution. We analyze a case study of middle school students’ learning about energy to investigate patterns and variations in their learning trajectories. Additionally, we explore how different learning trajectories influence the development of knowledge-in-use, leading to either productive or unproductive learning outcomes. Our findings aim to guide instruction for teachers and instructional designers, providing insights on how to develop more effectively adaptive learning environments that support diverse student learning trajectories.

Education systems worldwide have encouraged data use initiatives with the aim of improving student learning through data-driven decision making (DDDM). Despite this, the adoption of DDDM practices by Australian teachers has been slow. Investigating current organisational activities at a micro level is imperative for any change initiative to gain momentum and adoption. To examine the underlying factors contributing to the minimal change in teachers' data practices, the study examines primary teachers' perspectives on issues relating to their ability to collect and analyse student assessment data. The study also adopts an inter-disciplinary lens through the use of a business process change management framework. Drawing on data from twenty-three semi-structured interviews with experienced teachers, sixteen salient factors are identified as affecting teachers' use of student assessment data to guide instruction. This paper argues that addressing these factors is the precursor to incorporating lasting changes in teachers' data practices.

We systematically compared two coding approaches to generate training datasets for machine learning (ML): (i) a holistic approach based on learning progression levels and (ii) a dichotomous, analytic approach of multiple concepts in student reasoning, deconstructed from holistic rubrics. We evaluated four constructed response assessment items for undergraduate physiology, each targeting five levels of a developing flux learning progression in an ion context. Human-coded datasets were used to train two ML models: (i) an 8-classification algorithm ensemble implemented in the Constructed Response Classifier (CRC), and (ii) a single classification algorithm implemented in LightSide Researcher’s Workbench. Human coding agreement on approximately 700 student responses per item was high for both approaches with Cohen’s kappas ranging from 0.75 to 0.87 on holistic scoring and from 0.78 to 0.89 on analytic composite scoring. ML model performance varied across items and rubric type. For two items, training sets from both coding approaches produced similarly accurate ML models, with differences in Cohen’s kappa between machine and human scores of 0.002 and 0.041. For the other items, ML models trained with analytic coded responses and used for a composite score, achieved better performance as compared to using holistic scores for training, with increases in Cohen’s kappa of 0.043 and 0.117. These items used a more complex scenario involving movement of two ions. It may be that analytic coding is beneficial to unpacking this additional complexity.

This study was conducted with 37 11th grade secondary school students and had as its focus to verify the different levels of sophistication in students’ explanations regarding the propagation of sound in air. A pre- and a post-test were conducted after a one-month intervention, focusing on learning about sound propagation in air. Data analysis allowed for comparing the progressions in the sophistication of students’ explanations and validating the proposed categorical structure of the hierarchical levels of learning progressions (LPs). The validity was confirmed by the consistency of the category hierarchy, assessed in terms of the difficulty coefficients of LPs levels, which were distinct in the two tests but maintained the established order in the construct maps. In the pre-test, the more sophisticated levels of LPs were not elucidated, but after instruction, in the post-test, there were explanations at all levels. The results also reveal the importance of instruction focused on LPs, so that students can present more sophisticated explanations, and their utility for future investigations using this approach.

Learning progressions have become increasingly prevalent in mathematics education as they offer a fine-grain map of possible learning pathways a child may take within a particular domain. However, there is an opportunity to build upon this research in ways that consider learning from multiple perspectives. Many current forms of learning progressions describe learning pathways without explicit consideration of how related skills and contexts directly or indirectly enhance or influence learning. That is, the structured and unstructured learning contexts that can help children develop conceptual understanding in a range of STEM contexts. We consider learning progressions from multiple perspectives, which will be particularly important for supporting learning in early years, play-based contexts. We propose a novel theoretical perspective, termed Bounded Learning Progressions (BLP), which demonstrates the connection and influence ways of reasoning have on the progression of learning in specific domains, bounded by the context in which learning develops. We suggest that this approach provides a broader perspective of children’s learning capabilities and the possible connections between such abilities, acknowledging the critical role context plays in the development of learning.

Incorporating formative assessment strategies in classroom instructional practices is challenging for teachers. This study investigates how a learning progression for the particle model of matter can be used to scaffold teachers in enacting formative assessment practices in their classrooms. Lesson observations of four teachers who participated in the study were conducted to capture teachers’ classroom practices. Also, semi-structured interviews were conducted with the teachers to determine their views and understandings of formative assessment, and to assess their views on using a learning progression to support the design of formative assessment. Thereafter, teachers participated in a professional development programme based on the Formative Assessment Design Cycle (FADC) that was aimed at empowering teachers with knowledge and skills to design and implement formative strategies in classrooms. Lesson observations were also conducted post-intervention to determine changes in teachers’ classroom formative assessment practices. The study found that teachers had limited understanding of formative assessment, had no knowledge of how a learning progression can be used to support design of formative assessment practices. While the teachers’ knowledge of formative assessment and their formative assessment practices improved after engaging in professional teacher development programme, there were still gaps in their knowledge and practices.

Learning progressions describe how students can explain a concept at successive levels of increasing sophistication based on coherent ideas, instruction, and prior experiences. Most of the research on learning progressions begins with the development of the construct map, and this study will explore the processes for its development. The study presents how different levels of sophistication of students’ explanations for the propagation of sound in the air can be described. 126 students from 7th to 12th grade participated in this study, which focused on describing students’ explanations for the propagation of sound in the air at different levels of sophistication. An open-ended question test and a semi-structured interview seeking to capture evidence of the different levels of explanation for the propagation of sound in the air were conducted. The consistency between the preliminary construct map with evidence from tests and interviews was checked. The data displayed consonance between the construct map and the explanations provided by the students. Through the concrete evidence of how students explain this phenomenon, it has been possible to describe the levels of the construct map. This has enabled the presentation of a tool to support teachers in developing strategies and practices in learning progressions approach. For future studies in learning progressions, seek to find evidence of the paths taken by students to attain more sophisticated explanations.

This article centers on the Next Generation Science Standards (NGSS) and their implications for teacher development, particularly at the undergraduate level. After an introduction to NGSS and the influence of standards in the educational system, the article addresses specific educational shifts-interconnecting science and engineering practices, disciplinary core ideas, crosscutting concepts; recognizing learning progressions; including engineering; addressing the nature of science, coordinating with Common Core State Standards. The article continues with a general discussion of reforming teacher education programs and a concluding discussion of basic competencies and personal qualities of effective science teachers.

The coupled influences of scholarship in the fields of Psychology, Philosophy, and Pedagogy beginning in the 1950s, set in motion the emergence of new images, methodological perspectives, theories, and design principles about learners and learning. Advances in cognitive and sociocultural psychology, shifting images of the nature of science, recognition of the importance of disciplinary discourse practices in learning, the scaffolding of learning by tools and technologies, along with the adoption of ‘assessment for learning’ instructional strategies are among the factors that have led researchers and practitioners to advance positions that learning ought to be coordinated and sequenced along conceptual trajectories, developmental corridors, and learning progressions (LP). Following opening Introduction and LP Research Framework sections that provide an overview of the runup to LP research and development, I then turn to future research discussions and implications targeting five LP domains: Using Knowledge with Scientific Practices; Instructional Pathways – Early Childhood Learning; Teaching Experiments – Science and Mathematics; Upper/Lower Anchors for Measuring Progress; and Concepts & Practices. The Conclusion section points to overarching challenges for researchers, planners, and teachers in STEM education. There is much to learn for all!

There is growing interest in mathematics learning progressions in early childhood education. Counting is a skill usually developed early in life. The application of the counting principles in early childhood typically entails counting objects. This poses challenges for learning about zero. Indeed, the word “zero” is seldom used in the context of early childhood education. Early childhood educators could purposefully introduce children to zero as a concept and facilitate children’s understanding that zero is a number and more than just the absence of something. “Zero” is introduced in school, but little guidance is provided to teachers within the Australian Curriculum for Mathematics in the Foundation year. This study contributes to a small corpus of research that has investigated preschool children’s understanding of the concept of zero. Unlike other studies, the method employed to elicit children’s knowledge was informal and more similar to educator-child conversations that occur within a playbased curriculum and contribute to formative assessment. Data are presented from 20 children, aged from three to five years, participating in a regional early learning centre. Six children demonstrated familiarity with the symbol for zero (“0”) and/or the concept that zero describes a numerical quantity. Asking a follow-up question encouraged children to share their thinking. The importance of early childhood educators purposefully supporting children’s familiarity with the word zero along as well as the concept of zero is proposed.