Individualised learner-centred teaching requires the continuous monitoring of students’ individual learning progress. A promising approach that uses recurrent short tests to measure individual learning progress and report the progress to teachers (and students) is learning progress monitoring (LPM). Although some findings suggest that LPM may positively impact student performance, there is also a large heterogeneity in prior results. The present meta-analysis examines the conditions under which LPM effectively improves students’ academic performance compared to business-as-usual instruction. We included 87 effect sizes from 25 studies published before June 2024, including a total of 7,379 students. These studies show a small positive effect (g = 0.30) of LPM on students’ reading, writing, and mathematics performance. Moderator analyses showed that the effect of LPM on academic performance was greater when (i) ongoing consultation was provided for teachers during the implementation of LPM and (ii) teachers received data-specific support on how to adjust their teaching. Moreover, our findings suggest that LPM tests should be administered at least weekly to be effective. Overall, our results show that LPM is well suited to addressing the challenges of student heterogeneity for students with and without educational needs. However, further research is needed to investigate in more detail the mechanisms underlying the effectiveness of LPM, particularly concerning the specific content and the extent of the support that needs to be provided to teachers to maximise the potential of LPM.

Selecting a proof for teaching is a frequent task for teachers. However, it is so far unclear, which factors are considered by teachers when selecting proofs. Is the selection based on task and proof characteristics such as the didactical type of proof? Or based on class characteristics such as students’ algebraic skills? Or do teachers’ characteristics such as their proof skills govern their decision? Or is the selection too non-generic for these characteristics to show a meaningful impact? To address these questions, a quasi-experimental study with N = 183 pre-service teachers was conducted to evaluate the influence of each of these factors on their selection of proofs for teaching. Results highlight several significant effects of the abovementioned characteristics and underline that—even at the pre-service level—the selection of proofs is more nuanced than often assumed in prior research and that teachers deliberately and adaptively select proofs for their teaching based on these factors.

Abstract: An adequate on-the-fly assessment of relevant learner characteristics is an essential professional ability for effective teaching. However, this task is challenging, particularly for teacher students, as they often struggle in applying conceptual knowledge and lack perception of personal value and utility of study contents. Video-based simulations enable the acquisition of practice-oriented abilities for student assessment in initial teacher education. Implementing additional scaffolding in simulations can increase learning gains. The present study examines whether a utility value intervention and conceptual knowledge prompts can effectively support the assessment of relevant learner characteristics and how such effects are influenced by success expectancy. The study participants were N = 108 pre-service teachers, who completed a validated video-based simulation. They were randomly assigned to both interventions (utility value intervention, conceptual prompts) in a 2 × 2 design. The results showed that conceptual prompts improved judgment accuracy effectively. The utility value intervention yielded only descriptive improvements that require further investigations. The combination of both interventions was least effective. Furthermore, the results suggest that participants with low success expectancy benefited more from conceptual prompts. These results suggest that conceptual knowledge prompts and tentatively also utility value interventions can be used as effective scaffolds in simulations in the context of assessment skills. However, they also tentatively suggest that more processing and reflection time might be required for the combined scaffold to be effective. In addition, the differential effectiveness of both scaffolds emphasizes that an adaptation of scaffolds based on, for example, success expectancy can support additional learning gains.

An adequate on-the-fly assessment of relevant learner characteristics is an essential professional ability for effective teaching. However, this task is challenging, particularly for teacher students, as they often struggle in applying conceptual knowledge and lack perception of personal value and utility of study contents. Video-based simulations enable the acquisition of practice-oriented abilities for student assessment in initial teacher education. Implementing additional scaffolding in simulations can increase learning gains. The present study examines whether a utility value intervention and conceptual knowledge prompts can effectively support the assessment of relevant learner characteristics and how such effects are influenced by success expectancy. The study participants were N = 108 pre-service teachers, who completed a validated video-based simulation. They were randomly assigned to both interventions (utility value intervention, conceptual prompts) in a 2 x 2 design. The results showed that conceptual prompts improved judgment accuracy effectively. The utility value intervention yielded only descriptive improvements that require further investigations. The combination of both interventions was least effective. Furthermore, the results suggest that participants with low success expectancy benefited more from conceptual prompts. These results suggest that conceptual knowledge prompts and tentatively also utility value interventions can be used as effective scaffolds in simulations in the context of assessment skills. However, they also tentatively suggest that more processing and reflection time might be required for the combined scaffold to be effective. In addition, the differential effectiveness of both scaffolds emphasizes that an adaptation of scaffolds based on, for example, success expectancy can support additional learning gains.

Simulation-based learning is being increasingly implemented across different domains of higher education to facilitate essential skills and competences (e.g. diagnostic skills, problem-solving, etc.). However, the lack of research that assesses and compares simulations used in different contexts (e.g., from design perspective) makes it challenging to effectively transfer good practices or establish guidelines for effective simulations across different domains. This study suggests some initial steps to address this issue by investigating the relations between learners' experience in simulation-based learning environments and learners' diagnostic accuracy across several different domains and types of simulations, with the goal of facilitating cross-domain research and generalizability. The findings demonstrate that used learners' experience ratings are correlated with objective performance measures, and can be used for meaningful comparisons across different domains. Measures of perceived extraneous cognitive load were found to be specific to the simulation and situation, while perceived involvement and authenticity were not. Further, the negative correlation between perceived extraneous cognitive load and perceived authenticity was more pronounced in interaction-based simulations. These results provide supporting evidence for theoretical models that highlight the connection between learners' experience in simulated learning environments and their performance. Overall, this research contributes to the understanding of the relationship between learners’ experience in simulation-based learning environments and their diagnostic accuracy, paving the way for the dissemination of best practices across different domains within higher education.

Background Scaffolding pre-service teachers' assessment process in video-based simulations can enhance their acquisition and refinement of assessment skills, for example, needed for accurate judgments of students' mathematical proof skills. Adapting this scaffolding to learners’ individual learning processes, for example, based on text data during the assessment process, brings potential for increased learning gains. Aims In this study, we investigated the effectiveness of adaptive scaffolding based on real-time process data, specifically targeting pre-service mathematics teachers' assessment skills regarding students’ mathematical proof skills in geometry. Sample Participants were 245 pre-service teachers. Methods In a pre- and post-test, participants completed a video-based simulation to measure their assessment skills regarding students’ mathematical proof skills. During the intervention, participants were randomly assigned to complete the video-based simulation (i) without scaffolding, (ii) with non-adaptive scaffolding, or (iii) with adaptive scaffolding. Results We did not find significant benefits of adaptive scaffolding in enhancing pre-service teachers’ judgment accuracy, aligning with prior research. For an in-depth analysis, we developed and applied a scheme to systematically validate design decisions for adaptive support. This scheme focuses on the selection and measurement of the source of adaptation and the employed support mechanisms. Applying this scheme pointed towards effects of adaptive scaffolding during the assessment process. Conclusions This study highlights the need for proximal measures to describe learning in short interventions, explores the intricacies of adaptive scaffolding, such as overlapping with design-loop adaptivity or the accuracy of automated coding, and provides a scheme for an in-depth evaluation of the adaptivity of scaffolding.

This meta-analysis builds on 217 empirical studies in higher education and investigates the role of the different forms of adaptivity and adaptability as personalization strategies in simulation-based learning environments for complex skills in higher education. The strategies used to personalize scaffolding and task progression were the central point in this meta-analysis. We identified conditions under which personalization advances complex skills in higher education. The results indicate that whereas adaptivity (i.e., computer makes decisions) is more effective for scaffolding, adaptability (the decisions made by individual learners) seem more beneficial for task progression. We conclude that adaptivity and adaptability can be effectively used to personalize simulation-based learning environments in higher education to better address needs of learners with different learning needs. We also discuss the potential of artificial intelligence for empowering personalization in simulation-based learning.

To support professional competence development in teacher education, learning environments should allow learners to engage with professional tasks. It is crucial for knowledge and skill transfer in such learning environments to real-life context that preservice teachers perceive the task as authentic. However, due to a lack of prior knowledge, novices may have difficulties in recognizing relevant elements of practice. It is thus assumed that different factors may guide their perception of task authenticity independently of the task that has to be mastered. Such factors could be, for example, overt design features of the learning environments on a physical level or the familiarity with the learning context and learning prerequisites, which act as important links for knowledge acquisition. In this study, preservice teachers’ perception of task authenticity is contrasted between two implementation types (video vs. role-play) of the same simulation aiming to foster diagnostic competence. The two types differ in approximating real-life practice concerning the professional task that has to be mastered. In an experimental, longitudinal study, N = 119 mathematics preservice teachers participated online in one type of the simulation four times during one semester (n = 66 video, n = 53 role-play). Perceived task authenticity was higher for the video simulation type and increased with repeated participation in the simulation independently of the implementation type. Further, preservice teachers’ task utility value positively influenced their perception of task authenticity. The results illustrate the role of learning prerequisites as well as familiarity with the task for novices’ perception. Also, they could be an initial indication that, depending on the level of learners’ professional development, the way of approximating real-life practice in simulations might influence the perception of task authenticity.

Assessing students' understanding is central for teachers. While research has focused on factors affecting accuracy as a main performance measure of diagnosing, less is known about teachers' diagnostic process. This study investigated the diagnostic process of pre-service teachers in a simulation using a person-centered approach. We examined the frequency of the diagnostic processes describing, explaining, and decision-making as well as their relation to dispositions and diagnostic performance. Findings show that participants' varying engagement in the diagnostic process is related to different levels of knowledge, task value, and accuracy. We discuss consequences for the adaptive support of learning to diagnose.

Since the 1980s, the learning sciences have been an emerging field of research that focuses on learning of individuals and groups in authentic social, material, and digital contexts from a multi-level perspective. The learning sciences have substantially advanced theoretical conceptions of learning and its support as well as methodological approaches, for example by introducing design-based research. The article provides an overview of the history, important theories and concepts of learning and guidance, as well as methods of the learning sciences. The concluding part sketches potentially important areas for future research in the learning sciences.

Video-based simulations are considered authentic approximations of practice that can support pre-service teachers' acquisition of diagnostic skills. Still, there is insufficient knowledge on the (differential) effectiveness of different types of prompts on learning in such environments. The presented study experimentally compared the effects of two types of prompts on participants' judgment accuracy and diagnostic processes in a video-based simulation for diagnostic skills in the context of secondary mathematical argumentation skills. The prompts focused learners either on one indicator of argumentation skills (conceptual prompts) or two indicators and their relation (interconnecting prompts). Results indicate that the prompts effectively supported learning in short interventions. While conceptual prompts led to generally higher learning, interconnecting prompts showed a differential effectiveness based on prior knowledge. Besides highlighting a prototypical video-based simulation for diagnostic skills and prompts to support these, results give indications for teaching diagnostic skills and the adaptive use of prompts for simulation-based learning.

Math learning programs were expected to revolutionize students' learning, but their effects so far have mostly been disappointing. Following the debate about why to continue research on math learning programs, we aimed to reformulate this question into how to continue this research. Investigations to date have neither considered a sufficiently wide set of outcome variables nor differentiated between performance measures (e.g., measuring addition and subtraction performance separately) and affective-motivational variables. Moreover, as students can only benefit from a program if they use it, researchers need to take practice behavior into account. Thus, we investigated whether the adaptive arithmetic learning program Math Garden fostered students' addition and subtraction performance, their math self-concept, and a reduction of their math anxiety. We also investigated how practice behavior (practiced tasks/weeks) affected these outcomes. We used a randomized pretest-posttest control group design with 376 fifth-grade students in Germany. Students in the experimental condition practiced with Math Garden for 20.7 weeks and had an increase in math self-concept. The more subtraction tasks the students practiced, the more they improved their subtraction performance. We found no effects on math anxiety. The results are discussed in terms of providing a starting point for new directions in future research.

Assessing students’ learning processes and products is considered a core requirement of effective teaching. As such, it is an object of research in several disciplines and research areas. To structure the various corresponding research perspectives and provide a broader, yet still systematic view of the field, we propose an overarching framework that allows for systematizing foci of interest, goals, methodologies, and theoretical premises as four integral aspects of conducting research in this area. We demonstrate the benefits of the overarching framework by using it as a tool to analyze and systematize previous research from four different research perspectives. Based on this framework, we discuss the strengths and limitations of existing studies and, in particular, highlight theoretical premises that are rarely explicitly addressed but become more obvious by using the overarching framework. In addition, we provide directions for future research by drawing connections within and between research perspectives. Our analyses illustrate how the overarching framework can provide a foundation for research synthesis and inform future studies.

The purpose of this study was to measure and describe students’ learning development in mental computation of mixed addition and subtraction tasks up to 100. We used a learning progress monitoring (LPM) approach with multiple repeated measurements to examine the learning curves of second-and third-grade primary school students in mental computation over a period of 17 biweekly measurement intervals in the school year 2020/2021. Moreover, we investigated how homogeneous students’ learning curves were and how sociodemographic variables (gender, grade level, the assignment of special educational needs) affected students’ learning growth. Therefore, 348 German students from six schools and 20 classes (10.9% students with special educational needs) worked on systematically, but randomly mixed addition and subtraction tasks at regular intervals with an online LPM tool. We collected learning progress data for 12 measurement intervals during the survey period that was impacted by the COVID-19 pandemic. Technical results show that the employed LPM tool for mental computation met the criteria of LPM research stages 1 and 2. Focusing on the learning curves, results from latent growth curve modeling showed significant differences in the intercept and in the slope based on the background variables. The results illustrate that one-size-fits-all instruction is not appropriate, thus highlighting the value of LPM or other means that allow individualized, adaptive teaching. The study provides a first quantitative overview over the learning curves for mental computation in second and third grade. Furthermore, it offers a validated tool for the empirical analysis of learning curves regarding mental computation and strong reference data against which individual learning growth can be compared to identify students with unfavorable learning curves and provide targeted support as part of an adaptive, evidence-based teaching approach. Implications for further research and school practice are discussed.

This study investigates difficulty-generating item characteristics (DGICs) in the context of basic arithmetic operations for numbers up to 100 to illustrate their use in item-generating systems for learning progress monitoring (LPM). The fundament of the item-generating system is based on three theory-based DGICs: arithmetic operation, the necessity of crossing 10, and the number of second-term digits. The Rasch model (RM) and the linear logistic test model (LLTM) were used to estimate and predict the DGICs. The results indicate that under the LLTM approach all of the three hypothesized DGICs were significant predictors of item difficulty. Furthermore, the DGICs explain with 20% a solid part of the variance of the RM’s item parameters. The identification and verification of the DGICs under the LLTM approach provide important insights into how to address the challenges in the development of future LPM tests in mathematics.

Purpose To advance the learning of professional practices in teacher education and medical education, this conceptual paper aims to introduce the idea of representational scaffolding for digital simulations in higher education. Design/methodology/approach This study outlines the ideas of core practices in two important fields of higher education, namely, teacher and medical education. To facilitate future professionals’ learning of relevant practices, using digital simulations for the approximation of practice offers multiple options for selecting and adjusting representations of practice situations. Adjusting the demands of the learning task in simulations by selecting and modifying representations of practice to match relevant learner characteristics can be characterized as representational scaffolding. Building on research on problem-solving and scientific reasoning, this article identifies leverage points for employing representational scaffolding. Findings The four suggested sets of representational scaffolds that target relevant features of practice situations in simulations are: informational complexity, typicality, required agency and situation dynamics. Representational scaffolds might be implemented in a strategy for approximating practice that involves the media design, sequencing and adaptation of representational scaffolding. Originality/value The outlined conceptualization of representational scaffolding can systematize the design and adaptation of digital simulations in higher education and might contribute to the advancement of future professionals’ learning to further engage in professional practices. This conceptual paper offers a necessary foundation and terminology for approaching related future research.

Mathematical argumentations and proofs cause difficulties for secondary school students (Healy and Hoyles, 2000). Teachers’ diagnostic skills are essential for adapting their teaching to students’ specific needs in order to facilitate students’ understanding of proofs (Südkamp and Praetorius, 2017). We developed a video-based simulation to investigate and promote pre-service teachers’ diagnostic skills. Participants encountered a diagnostic task with short, scripted video clips showing simulated students working on a geometry proof with a teacher. Observing student-teacher interactions served as the basis for the pre-service teacher participants’ diagnoses of students’ individual argumentation skills. This simulation is first used to investigate pre-service teachers’ diagnostic performance and the quality of their diagnoses and diagnostic processes. In a second step, the simulation will be expanded into a learning environment to investigate how pre-service teachers’ diagnostic skills can be supported through different kinds of scaffolds.

Assessing students on-the-fly is an important but challenging task for teachers. In initial teacher education, a call has been made to better prepare pre-service teachers for this complex task. Advances in technology allow this training to be done through authentic learning environments, such as video-based simulations. To understand the learning process in such simulations, it is necessary to determine how cognitive and motivational learner characteristics influence situative learning experiences, such as the perception of authenticity, cognitive load, and situational motivation, during the simulation and how they affect aspects of performance. In the present study, N = 150 pre-service teachers from German universities voluntarily participated in a validated online video-based simulation targeting on-the-fly student assessments. We identified three profiles of learner characteristics: one with above average knowledge, one with above average motivational-affective traits, and one with below average knowledge and motivational-affective traits. These profiles do not differ in the perception of the authenticity of the simulation. Furthermore, the results indicate that the profiled learners navigate differently through the simulation. The knowledgeable learners tended to outperform learners of the other two profiles by using more learning time for the assessment process, also resulting in higher judgment accuracy. The study highlights how learner characteristics and processes interact, which helps to better understand individual learning processes in simulations. Thus, the findings may be used as a basis for future simulation research with a focus on adaptive and individual support.