Welcome to the Camtree Digital Library
The Camtree Digital Library publishes peer-reviewed research reports produced by educators from around the world. Library content is freely available to all readers.
Camtree supports educators to reflect on their practice and conduct research to improve learning in their own contexts and organisations, through its website at https://www.camtree.org. Camtree is based at Hughes Hall, University of Cambridge.
Recent Submissions
Item Using Python to analyse experimental data in high school physics: a study based on external aggregate assessment exams(2025)Background and purpose: This research addresses the need for improved analytical skills in high school physics students, particularly in the context of interpreting experimental data - a critical skill assessed in final, external summative examinations. Traditional teaching methods often lack interactive, hands-on data analysis tools, limiting students’ understanding of error analysis, graph interpretation, and other experimental techniques. Integrating Python programming into the curriculum offers a modern approach to bridge this gap, equipping students with practical, analytical skills that enhance both their classroom learning and performance in high-stakes assessments. Aims: This study specifically focused on enhancing students' ability to analyse experimental data through Python programming. The goal was to improve their understanding of error margins, linear relationships, and data visualization techniques. Study design or methodology: The participants were 12th-grade physics students (ages 17-18), with a sample size of 12. The research took place in a high school classroom setting, where students engaged with experimental data and Python programming for data analysis. Data collection involved both pre- and post-intervention assessments, alongside qualitative observations and a student survey on their experience. Custom Python scripts and datasets were provided as resources to guide analysis exercises, particularly focusing on error analysis and graphing. Findings: Key findings indicate that Python-based data analysis significantly improved students' comprehension of experimental data concepts. Students demonstrated greater accuracy in calculating errors, plotting graphs, and interpreting data trends. Survey feedback showed increased confidence in handling data and understanding statistical concepts. Conclusions, originality, value and implications: This study contributes to the field by illustrating how integrating Python programming into physics education can enhance analytical skills, adding value to both classroom practice and digital learning resources. The approach offers a scalable model for other educators to implement programming in experimental data analysis, fostering students' readiness for data-intensive tasks in advanced studies and careers.Item Development of argumentative statements through analysis of information and use of structured tables(2025)Background and Purpose: This study examines the development of students' argumentative statements through the use of structured tables to analyse and organize information. The research was conducted as a Lesson Study with 12 Grade 10 students (aged 15–16) in the subjects of Kazakh, English, and World History. A key challenge observed was that students struggled to form well-reasoned statements, provide appropriate evidence and examples, identify key points in texts, and recognize cause-and-effect relationships. The study aimed to address these difficulties by introducing tables as a structured tool for organizing textual analysis and improving argumentation skills. Aims: The primary goal was to develop students’ analytical thinking skills by improving their ability to compare, generalize, construct logical reasoning, fully comprehend texts, and draw conclusions based on textual analysis using structured tables. Study Design or Methodology: This research followed a Lesson Study approach, involving the observation of three lessons. A qualitative research design was applied, including classroom observations, student interviews, and a pre-study survey. Before starting the research, a survey was conducted to assess students' challenges in working with texts, particularly in identifying key ideas, structuring arguments, and providing evidence-based reasoning. The term ‘difficulty working with texts’ refers to students’ struggles in extracting relevant information, organizing their thoughts logically, and articulating well-supported arguments. Findings: The structured tables implemented for analysing information in texts were effective, as students learned to systematically identify key ideas, organize supporting evidence, and construct well-reasoned arguments. The study found that students developed critical thinking by recognizing their own opinions, reflecting on different perspectives, and using relevant argumentative evidence. Students generated their own argumentative statements based on the structured analysis, rather than relying on pre-prepared responses. Conclusions, Originality, Value, and Implications: The findings suggest that structured tables can be a valuable tool for improving students’ argumentation skills across multiple subjects. The approach provided a clear framework that helped students move from basic comprehension to higher-order thinking skills, which are essential for academic success. These results indicate that similar strategies could be effectively applied in other disciplines and educational settings. The study highlights the need for structured scaffolding in teaching argumentation, with a gradual transition toward independent analysis and reasoning. Future practice will focus on refining this approach and exploring its effectiveness in different learning contexts.Item Joint Planning of Subject and Language Teachers to Implement CLIL (Content and Language Integrated Learning) in Chemistry Lessons(2025)Background and purpose: This study addresses the challenges and opportunities of implementing Content and Language Integrated Learning (CLIL) strategies at Nazarbayev Intellectual School (NIS) in Uralsk, Kazakhstan. As part of the school’s trilingual education model, CLIL integrates subject knowledge and academic language across Kazakh, Russian, and English. Despite its importance, challenges such as inconsistent joint planning (JP) and misalignment of linguistic and content objectives persist. Research by Mehisto et al. (2017) and Coyle et al. (2010) highlights the transformative potential of collaboration between subject and language teachers in enhancing CLIL. However, little is known about these processes in Kazakhstan’s multilingual education context. This study explores how systematic collaboration improves teaching practices and student outcomes. Aims: This study aimed to explore how joint lesson planning and co-teaching enhance students' academic language proficiency in Chemistry. It investigated the impact of collaborative instructional strategies, shared resources, and structured scaffolding on student learning across different ability levels. The research also sought to refine teaching approaches that help students construct clear, well-structured scientific explanations and effectively use subject-specific terminology in multiple languages. Study design: The study was conducted with Chemistry and language teachers at NIS, involving nine Year 11 students (aged 16-17) in a series of three research lessons (RL1, RL2, RL3). Data were collected through teacher interviews, classroom observations, and student assessments. Collaborative lesson planning sessions were held to co-develop instructional materials, including structured writing templates, terminology guides, and guided questioning strategies. The impact of these interventions was measured by comparing pre- and post-intervention student performance in Chemistry-related analytical writing and scientific discussions. Findings: The study revealed notable improvements in students’ ability to integrate Chemistry-specific academic language into structured responses. Students demonstrated enhanced comprehension and writing skills, particularly in lab reports and extended explanations. The use of scaffolding techniques, peer discussions, and co-teaching strategies contributed to this progress. High-achieving students displayed strong analytical writing skills, while average and struggling learners benefited from structured templates and guided questioning to improve clarity and coherence Conclusions, originality, value and implications: The research provides a practical model for integrating content and language objectives. Future teaching will prioritize structured collaboration and shared resource development, with regular JP sessions to strengthen CLIL practices. These findings offer valuable insights for further development of effective CLIL strategies across subjectsItem Using Principles of Cognitive Science as a Framework for Retrieval Practice in A Level Psychology(2025)Background and purpose: The linearisation of A Level Psychology require students to recall and apply knowledge from the entire course in one set of final exams, this means that students need effective strategies to retain information over a longer period and the need for sustained revision techniques has become more critical. Aims: The aim of the inquiry was to formalise and strategically provide students with retrieval practice over a 30-week period with the goal to improve outcomes in exams using 4 principles outlined by Cattrell (2024; Educational Endowment Foundation). The cognitive science principles used to inform these activities include tasks that engage the long-term memory (LTM), are challenging, are repeated and have opportunities for feedback. Design or methodology: A long-term strategy for retrieval was devised which coordinated with mock exams, this involved breaking down the academic year into weeks, providing students with past paper questions to assess knowledge and weekly assignments to be uploaded to Teams. Findings: In order to assess the effectiveness of the retrieval activities the current 2025 (n=64) cohort sat the same mock exam paper sat by the previous cohort in 2024 (n = 38). Findings indicate that there was an 11% increase in the average assessment outcome following the implementation of the retrieval plan with the average score increasing to 54% from 43%. The results revealed a statistically significant difference in exam scores (U = 818.5, p < 0.05) for a one-tailed test demonstrating that the use of retrieval activities significantly improved outcomes on assessments for Psychology students. Conclusions, originality, value and implications: The assessment outcomes and student feedback demonstrate the effectiveness of the retrieval plan and therefore will continue to be implemented. Designing a retrieval plan requires consideration to ensure that activities are engaging the LTM in a consistently challenging format where opportunities for feedback are provided to ensure misconceptions do not become embedded.Item Investigating the Integration of Parson's Programming Puzzles into a Lesson Study Framework in Computer Science Education(2025)Background and purpose: Research indicates that students often struggle with coding logic, experiencing frustration and disengagement. This study explores the integration of Parson’s Programming Puzzles into computer science education as a pedagogical tool, through lesson study. By placing scrambled lines of code into the correct sequence, Parson’s Puzzles aim to reduce frustration and highlight the core logic of programming in a more game-like format. The interactive and hands-on nature of these puzzles aims to make programming more accessible, engaging, and effective for diverse learners. Aims: The primary aim of this research is to evaluate the impact of integrating Parson’s Programming Puzzles on student engagement in computer science lessons, perseverance in solving coding problems, and understanding of coding logic and programming skills. A secondary aim is to investigate how collaborative lesson planning and reflection (the lesson study approach) can further optimize these teaching strategies. Study design or methodology: Participants in the study included 15 secondary school students (aged 15–17) enrolled in computer science classes at Nazarbayev Intellectual School, Atyrau, Kazakhstan. Three research lessons were observed over a period of three weeks. Lessons were designed collaboratively by a team of educators using Parson’s Puzzles to address specific learning objectives. Data collection methods included classroom observations to evaluate student engagement and interaction, pre- and post-assessments to measure improvement in problem-solving and coding skills, and student surveys and interviews to gather qualitative feedback on their learning experiences. The collected data were analysed using both quantitative (assessment scores) and qualitative (thematic analysis of interviews and surveys) methods. Findings: Group A (High Performers) demonstrated significant improvement in problem-solving strategies and actively engaged with complex puzzles. Group B (Intermediate Learners) developed a better understanding of coding logic and structure, finding the puzzles a balance between challenge and support. Group C (Lower Performers) reported reduced frustration with coding and increased persistence in completing tasks. Conclusions, originality, value and implications: Integrating Parson’s Programming Puzzles within a lesson study framework fosters engagement, persistence, and improved coding outcomes in diverse learner groups. This approach provides educators with an innovative, hands-on method to address common challenges in programming education. The findings contribute to instructional practices, highlighting the value of collaborative lesson planning and innovative tools in enhancing computer science education. Future research could explore the long-term impact of this method and the integration of puzzles of varying complexity.
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