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Comprehension of expository texts is an important prerequisite for self-regulated learning. Processes of passive validation and metacognitive monitoring are thought to be involved in building a coherent situation model of a text. Inconsistency tasks are often used to measure these processes. Several studies have shown longer reading times for inconsistent sentences than for consistent sentences. However, it remains unclear whether the additional time arises from passive disruptions of the reading process when encountering an inconsistency or from metacognitive processes of reanalysis of previous text. To address this issue, we recorded the reading behavior of 96 university students with an eye-tracker while they read inconsistent and consistent expository texts. We analyzed first-pass reading (first-pass reading time, lookbacks) and reanalysis (rereading time, revisits) at the level of the (in)consistent target word, at the sentence-final word of the target sentence, and in the pre-target text. Our results did not strongly support the hypothesis that immediate changes in reading behavior when inconsistencies are first encountered influence the detection and processing of inconsistencies. Our results partially supported the hypothesis that processes of text reanalysis, specifically of the source of inconsistency, increase the probability of identifying an inconsistency. The findings indicate that a purposeful reanalysis of passages that appear inconsistent to readers improves situation model construction for (short) expository texts about conceptually difficult topics. Learning from texts thus requires metacognitive comprehension monitoring beyond passive validation processes.
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Although curriculum materials are essential for implementing instructional innovations, little is known about how exactly they support teachers’ enactment of innovative approaches and how explicitly they must integrate their key components. The paper contributes to reducing this research gap for one instructional innovation: explicit strategy instruction for word problem comprehension strategies. In our qualitative video study, teachers participated in a professional development on explicit strategy instruction and experimented with it in their classrooms. We compared the teachers’ enactment of strategy instruction in two implementation conditions: in the strong material support condition, teachers received curriculum materials in which components of strategy instruction were explicitly integrated. In the weak material support condition, the curriculum materials only provided the sequence of word problems, but the teachers had to implement explicit strategy instruction themselves. In the qualitative analysis of four cases of teachers’ videorecorded enactment, we unpacked how one teacher with weak support provided only limited learning opportunities by non-targeted enactment, with limited measurable student strategic learning gains. However, in the same condition, another teacher provided productive learning opportunities by explicit and targeted strategy instruction in spite of weak material support. In the strong material support condition, learning opportunities were assured even in a case of partially non-targeted enactment (yet high measurable student strategic learning gains). The findings bear consequences for combining curriculum materials with strong support and professional development.
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Although curriculum materials are essential for implementing instructional innovations, little is known about how exactly they support teachers’ enactment of innovative approaches and how explicitly they must integrate their key components. The paper contributes to reducing this research gap for one instructional innovation: explicit strategy instruction for word problem comprehension strategies. In our qualitative video study, teachers participated in a professional development on explicit strategy instruction and experimented with it in their classrooms. We compared the teachers’ enactment of strategy instruction in two implementation conditions: in the strong material support condition, teachers received curriculum materials in which components of strategy instruction were explicitly integrated. In the weak material support condition, the curriculum materials only provided the sequence of word problems, but the teachers had to implement explicit strategy instruction themselves. In the qualitative analysis of four cases of teachers’ videorecorded enactment, we unpacked how one teacher with weak support provided only limited learning opportunities by non-targeted enactment, with limited measurable student strategic learning gains. However, in the same condition, another teacher provided productive learning opportunities by explicit and targeted strategy instruction in spite of weak material support. In the strong material support condition, learning opportunities were assured even in a case of partially non-targeted enactment (yet high measurable student strategic learning gains). The findings bear consequences for combining curriculum materials with strong support and professional development.
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In ihrem neuen Gutachten „Lehrkräftegewinnung und Lehrkräftebildung für einen hochwertigen Unterricht“ empfiehlt die Ständige Wissenschaftliche Kommission der Kultusministerkonferenz (SWK) Maßnahmen für ein wissenschaftsbasiertes, klar strukturiertes Qualifikationssystem für Lehrkräfte in Studium, Vorbereitungsdienst und während des Berufs. Für den zweiten Weg ins Lehramt hat die SWK Modelle für einen Master mit anschließendem Vorbereitungsdienst entwickelt.
Sie empfiehlt außerdem eine Fortbildungsverpflichtung von 30 Stunden pro Jahr für alle

Heute, am 1. August 2024, startet am IPN das von der Telekom Stiftung mit über 700.000 Euro geförderte interdisziplinäre Projekt GENIUS (Generative Intelligence Utilized in Schools) mit einer Laufzeit von drei Jahren. Ziel ist es, Beurteilungs- und Feedbackprozesse in schulischen Lernsituationen mit Hilfe von Künstlicher Intelligenz (KI) effektiver zu gestalten. Die Projektgruppe unter der Leitung von Dr. Thorben Jansen wird mit GENIUS die naturwissenschaftliche Argumentationskompetenz von Schülerinnen und Schülern stärken und gleichzeitig neue Maßstäbe für den Einsatz von Künstlicher Intelligenz in schulischen Lernprozessen setzen.
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Background Teachers are expected to create an effective learning environment in their classroom while keeping an eye on classroom disruptions. This requires high monitoring competences as part of their noticing and professional vision. However, novice teachers often struggle dealing with critical situations and show ineffective monitoring behavior. Aims Using dynamic scanpath analyses, this eye-tracking study examined monitoring strategies of novice and expert teachers to understand how classroom disruptions affect teachers’ gaze behavior and what constitutes effective monitoring. Sample The sample consisted of 15 expert and 18 novice teachers. Methods Participants watched a short classroom video in which several minor and one major disruption occurred while their eye movements were recorded with an eye tracker. We analyzed their scanpaths by comparing Shannon entropy values to investigate the predictability of gaze transitions and the stability of their gaze patterns. Results Compared to novices, experts showed higher transition probabilities in their gaze behavior, both before and after the major disruption. Similarly, experts showed lower entropy scores, indicating more stable gaze behavior, whereas novices with higher entropy scores showed exploratory gaze behavior. In general, experts showed more adaptive monitoring strategies, returning to their routine gaze behavior more quickly than novices after an unexpected disruption. Conclusions This study enriches the cognitive theory of visual expertise by adding new expertise characteristics of teachers’ dynamic gaze behavior and situation-specific skills in disruptive classroom events. At the same time, the results reveal monitoring strategies that can be addressed in teacher education to enhance professional vision and classroom management.
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Background Teachers are expected to create an effective learning environment in their classroom while keeping an eye on classroom disruptions. This requires high monitoring competences as part of their noticing and professional vision. However, novice teachers often struggle dealing with critical situations and show ineffective monitoring behavior. Aims Using dynamic scanpath analyses, this eye-tracking study examined monitoring strategies of novice and expert teachers to understand how classroom disruptions affect teachers’ gaze behavior and what constitutes effective monitoring. Sample The sample consisted of 15 expert and 18 novice teachers. Methods Participants watched a short classroom video in which several minor and one major disruption occurred while their eye movements were recorded with an eye tracker. We analyzed their scanpaths by comparing Shannon entropy values to investigate the predictability of gaze transitions and the stability of their gaze patterns. Results Compared to novices, experts showed higher transition probabilities in their gaze behavior, both before and after the major disruption. Similarly, experts showed lower entropy scores, indicating more stable gaze behavior, whereas novices with higher entropy scores showed exploratory gaze behavior. In general, experts showed more adaptive monitoring strategies, returning to their routine gaze behavior more quickly than novices after an unexpected disruption. Conclusions This study enriches the cognitive theory of visual expertise by adding new expertise characteristics of teachers’ dynamic gaze behavior and situation-specific skills in disruptive classroom events. At the same time, the results reveal monitoring strategies that can be addressed in teacher education to enhance professional vision and classroom management.
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Continuous professional development of science teachers is closely related to their ability to reflect on their science lessons. For teachers to effectively reflect on their lesson, they need opportunities to make meaningful teaching-related experiences and receive guiding feedback for their reflections during initial teacher education. A sensible means to provide reflection opportunities for teachers is through written reflection assignments. However, assessing written reflections is conceptually challenging and resource-intensive. Recent developments suggest that artificial intelligence (AI) might provide novel opportunities for science teacher education and assessing written reflections. Consequently, we investigate ways in which AI in the form of a large language model can be utilized in a specific science teacher training program. The potential of AI for the use in higher education have been highlighted in recent years. However, it is noted that large language models oftentimes are too generic to be useful in specific science teacher education contexts. To address this issue, we used a pre-trained large language model and fine-tuned it to provide individualized feedback for pre-service physics teachers’ written reflection and investigated to which degree contextual factors impact the classification accuracy. Our results show that the pre-trained language model allowed a sufficient classification and that the classification accuracy can be improved by context specification. Our study highlights opportunities and challenges when utilizing AI, in particular large language models, for reflective writing analytics in science education.
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The aim of this research was to enhance understanding of how students’ socioeconomic status (SES) relates to their information and communication technology (ICT) literacy in specific aspects. Although social disparities in ICT literacy have been subject of research for more than two decades, little is known about which family characteristics determine these and how these disparities are mediated. Therefore, first, the effects of multiple SES indicators (parents` educational level, occupational status of parents, cultural capital) on ICT literacy were examined. Based on scholarly cultural theory and recent research, it was expected that cultural capital (i.e., the number of books at home) would show a stronger correlation with ICT literacy compared to other SES factors. Second, ICT usage motives were investigated as mediators of the relationship between various SES indicators (i.e., cultural capital in particular) and ICT literacy. This gap was addressed by using data from a comprehensive study involving German 15-year-olds (N = 14,436) and analyzing both cross-sectional and longitudinal impacts on ICT literacy over three years. The results provide strong support for the hypothesized framework, i.e. they stress the importance of cultural capital as well as the role of ICT usage motives as mediating variables for the development of ICT literacy. Longitudinally, ICT usage motives could account for over a quarter (28%) of the cultural capital to ICT literacy association. Nevertheless, the findings point to open questions which primarily refer to processes of parental media socialization.
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Background Field-specific ability beliefs (FABs) reflect the perception that success in academic fields depends on innate, unteachable abilities. These beliefs affect teaching practices and student motivation. However, little is known about their longitudinal development during teacher education. Aims This study examines how FABs evolve during university teacher education and whether longitudinal trajectories differ across academic disciplines, particularly between STEM and non-STEM subjects. Sample The sample included 1734 preservice teachers (22.11 years old on average in the first study year, 69.8% female) from a German university, studying across 21 subjects, categorized into six groups: languages; arts and philosophy; social sciences; physical education; biology, chemistry and computer science and mathematics-intensive subjects. Methods FABs were measured annually over four years using a validated scale. Applying latent growth modelling, we examined overall changes and differences in trajectories across subject domains, controlling for gender and prior academic achievement. Results FABs changed over time, with five of the six subject groups showing a decline. Mathematics-intensive subjects and physical education exhibited the highest initial FAB levels. While mathematics-intensive subjects showed the steepest decline, FABs in physical education increased. FABs in social sciences and languages remained relatively stable. Gender predicted initial FAB levels but was unrelated to changes over time. Prior achievement did not predict either initial levels or longitudinal changes in FABs. Conclusions Teacher education appears to reduce FABs, particularly in STEM fields, yet persistent and increasing FABs in certain disciplines highlight the need for targeted interventions to foster growth-oriented beliefs in preservice teachers.
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