A dynamic assessment tool was developed and validated using Mokken scale analysis to assess the extent to which kindergartners are able to construct unconfounded experiments, an essential part of scientific reasoning. Scientific reasoning is one of the learning processes happening within science education. A commonly used, hands-on, experimentation task was adapted to dynamically assess the use of the so-called control of variables strategy (CVS) by children 4 to 6 years of age. In this task, the children were challenged to design experiments using two ramps with up to four independent variables: weight of the ball, steepness of the slope, place of the starting gate, and surface texture of the slope. There were two scores of CVS use: experiment and variable correct score. The analysis showed it was possible to assess CVS use in a reliable and valid manner with the new assessment tool. Irrespective of the number of variables children were allowed to set, experiments validly measured CVS use. Given that the number of variables to be set increased the difficulty of the experiment, this can be used to scale children's CVS use. In other words, it is possible to differentiate between children on the basis of their CVS use. The children's use of CVS positively related to both their age and nonverbal reasoning ability. The present results thus show that it is feasible to evaluate the ability of kindergartners to construct unconfounded experiments using dynamic assessment. This means that kindergartners can use the CVS and might be seen as natural scientists, who can and will try to unravel the physical world around them. Their explorations appear to need sufficient guidance (i.e. within their zone of proximal development) to design multivariable experiments.

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Inquiry-based lessons have been demonstrated to improve children's scientific thinking (i.e. reasoning abilities and domainspecific knowledge). Although empirical evidence shows that inquiry-based learning requires instruction, research comes from two approaches that have not been bridged yet: direct instruction of scientific reasoning and teacher training of verbal support. We investigated how these two types of instruction separately or combined strengthened children's scientific thinking by comparing four conditions: baseline, direct instruction, verbal support, and a combined approach. Effectiveness of an inquirybased lesson series on scientific reasoning abilities, vocabulary, and domain-specific knowledge (near and far transfer) were studied among 301 fourth graders. Results showed that both approaches strengthened different components of scientific reasoning abilities, and that a combination of instructions was most effective for scientific reasoning abilities, vocabulary, and domain-specific knowledge. Domain-specific knowledge acquisition was strengthened only when both instructions were provided. It can thus be concluded that each type of instruction has unique contributions to children's science learning and that these instructions complement each other. Our study thus showed that inquiry-based lesson series when preceded by direct instruction of scientific reasoning and scaffolded with verbal support are most effective. ARTICLE HISTORY

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It has been widely theorized and empirically proven that self-regulated learning (SRL) is related to more desired learning outcomes, e.g., higher performance in transfer tests. Research has shifted to understanding the role of SRL during learning, such as the strategies and learning activities, learners employ and engage in the different SRL phases, which contribute to learning achievement. From a methodological perspective, measuring SRL using think-aloud data has been shown to be more insightful than self-report surveys as it helps better in determining the link between SRL activities and learning achievements. Educational process mining on the basis of think-aloud data enables a deeper understanding and more fine-grained analyses of SRL processes. Although students’ SRL is highly contextualized, there are consistent findings of the link between SRL activities and learning outcomes pointing to some consistency of the processes that support learning. However, past studies have utilized differing approaches which make generalization of findings between studies investigating the unfolding of SRL processes during learning a challenge. In the present study with 29 university students, we measured SRL via concurrent think-aloud protocols in a pre-post design using a similar approach from a previous study in an online learning environment during a 45-min learning session, where students learned about three topics and wrote an essay. Results revealed significant learning gain and replication of links between SRL activities and transfer performance, similar to past research. Additionally, temporal structures of successful and less successful students indicated meaningful differences associated with both theoretical assumptions and past research findings. In conclusion, extending prior research by exploring SRL patterns in an online learning setting provides insights to the replicability of previous findings from online learning settings and new findings show that it is important not only to focus on the repertoire of SRL strategies but also on how and when they are used.

In recent years, unobtrusive measures of self-regulated learning (SRL) processes based on log data recorded by digital learning environments have attracted increasing attention. However, researchers have also recognised that simple navigational log data or time spent on pages are often not fine-grained enough to study complex SRL processes. Recent advances in data-capturing technologies enabled researchers to go beyond simple navigational logs to measure SRL processes with multi-channel data. What multi-channel data can reveal about SRL processes, and to what extent can the addition of peripheral and eye-tracking data with navigational log data change and improve the measurement of SRL are key questions that require further investigation. Hence, we conducted a study and collected learning trace data generated by 25 university students in a laboratory setting, that aimed to address this problem by enhancing navigational log data with peripheral and eye-tracking data. We developed a trace-based measurement protocol of SRL, which interpreted raw trace data from multi-channel data into SRL processes. Specifically, the study compared the frequency and duration of SRL processes detected, how much duration and times of occurrences of the detected SRL processes were affected or refined. We also used a process mining technique to analyses how temporal sequencing of the detected SRL processes changed by enriching navigational log data with peripheral and eye-tracking data. The results revealed that by adding new data channels, we improved the capture of learning actions and detected SRL processes while enhancing the granularity of the measurement. In comparison to the use of navigational logs only, the completeness of temporal sequencing relationships between SRL processes with multi-channel data improved. In addition, we concluded that eye-tracking data is valuable for measuring and extracting SRL processes, and it should receive more attention in the future.

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