This research investigates the Models of eighth-grade students in Turkey pertaining to magnets and magnetic interactions, while also examining the consistency of these models within themselves. Additionally, a comparative assessment is conducted by comparing the current data with data collected from eighth-grade students a decade earlier. The…

Science education is crucial for fostering knowledge across academic disciplines. Past efforts to enhance science achievement at the elementary level have explored various instructional strategies. Among these, the Understanding by Design (UbD) model has shown notable potential in improving science achievement outcomes compared to traditional…

In this study, we propose an integrated hierarchical model of computational estimation strategies (IHMCES), which can be used to organize a set of computational estimation strategies, used by a group of individuals, in strategy ranges. IHMCES can be used for the description of the repertoire, profile and flexibility of individuals regarding the…

The aim of this study was to compare the 5E learning model with traditional learning methods in terms of their effect on students' conceptual understanding of water subtopics. The participants of the study were grade 8 students of 2021 academic year. While 27 of them were randomly assigned to the experimental group, the other 27 were assigned to…

This study explores the use of Large Language Models (LLMs), specifically GPT-4, in analysing classroom dialogue--a key task for teaching diagnosis and quality improvement. Traditional qualitative methods are both knowledge- and labour-intensive. This research investigates the potential of LLMs to streamline and enhance this process. Using…

This study explores using transfer learning in machine learning for natural language processing (NLP) to create generic automated essay scoring (AES) models, providing instant online scoring for statewide writing assessments in K-12 education. The goal is to develop an instant online scorer that is generalizable to any prompt, addressing the…

This article concerns the synergy between science learning, understanding complexity, and computational thinking (CT), and their impact on near and far learning transfer. The potential relationship between computer-based model construction and knowledge transfer has yet to be explored. We studied middle school students who modeled systemic…

This study aimed at designing instructional material named Biotechnology Instruction Module (BIM) which is enriched with active learning methods to enhance the 8th grade students' learning of the topic. The development of the teaching materials proceeded within the stages of the ADDIE instructional design model. The final form of the instructional…

This paper demonstrated how to apply Machine Learning (ML) techniques to analyze student interaction data collected in an online mathematics game. Using a data-driven approach, we examined 1) how different ML algorithms influenced the precision of middle-school students' (N = 359) performance (i.e. posttest math knowledge scores) prediction and 2)…

Students should be provided with more meaningful learning experiences to attract more students to STEM careers, Out-of-School learning environments can offer students exciting and motivating learning opportunities that formal environments cannot provide. Therefore, national education reforms in many countries that are working on popularizing STEM…

This paper aims to determine the predictive relationships between achievement goals and learning approaches in the context of social studies teaching and to compare the goal orientation models (3x2, 2x2) in the context of their relationships with learning approaches. The study utilized the multi-factorial predictive correlational design. The study…

Our research addresses the issue of teaching and learning concepts in science education as an empirical question. We study the process of conceptualization by closely examining the unfolding of classroom lesson sequences. We situate our work within the practice turn line of research on epistemic practices in science education. We also adopt a…

The gold-standard for evaluating the effect of an educational intervention on student outcomes is running a randomized controlled trial (RCT). However, RCTs may often be small due to logistical considerations, and resulting treatment effect estimates may lack precision. Recent methods improve experimental precision by incorporating information…

This paper demonstrated how to apply Machine Learning (ML) techniques to analyze student interaction data collected in an online mathematics game. Using a data-driven approach, we examined: (1) how different ML algorithms influenced the precision of middle-school students' (N = 359) performance (i.e. posttest math knowledge scores) prediction; and…

The present research examined the joint effects of social, dimensional, and temporal comparisons on students' academic self-concepts and parents' beliefs about their children's competencies during students' transition phase from elementary school to junior high school. To this end, we tested the newly developed 2I/E model using longitudinal data…