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The ability to write argumentative essays is an important requirement in EFL curricula in Germany and Switzerland, with grammar and lexis serving as indispensable elements of this task. The literature shows that acquiring advanced grammatical and lexical skills is challenging for students, especially genre-specific lexical abilities. In this longitudinal study, we investigate how grammatical and lexical skills develop in two educational systems among learners at upper secondary schools (operationalized as number of grammatical and lexical errors). Based on texts from n = 470 learners at two time points at the beginning and end of Year 11, it shows that learners in both countries made more lexical than grammatical errors (partial η2 = .17). There were no differences between the countries. Longitudinal analyses revealed moderate positive developments in both grammatical and lexical skills over the course of one school year (partial η2 = .08). The study confirms the importance of vocabulary for advanced L2 writers, which seems to pose a larger challenge than grammar and warrants special attention in EFL writing at upper secondary school. Implications for teacher education and classroom practice such as the emulation of model texts are discussed, with a focus on lexical chunks typical of argumentative writing.
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In der neusten Folge des IPN-Podcasts „Im Dialog“ diskutieren hochkarätige Expert:innen das Potenzial von Large Language Models (LLMs) wie ChatGPT für das deutsche Bildungssystem. Der Anlass für diese fokussierte Diskussion ist das von der Ständigen Wissenschaftlichen Diskussion (SWK) kürzlich veröffentlichte Impulspapier „Large Language Models und ihre Potenziale im Bildungssystem“, das richtungsweisende Empfehlungen zur Integration von LLMs in Schulen enthält. Ein praxisnaher Leitfaden zum Thema „KI und Schule“ wurde zuvor von der Deutschen Telekom Stiftung herausgegeben, der eine Fülle an praktischen Impulsen bietet.
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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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Having to deal with uncertainty is familiar to scientists working in fields that range from the life sciences to data science, but it can be difficult to support students to embrace and make sense of uncertainty in the middle school classroom. In this article, we argue that teaching about uncertainty in science education is not only beneficial but necessary for helping students develop a deeper understanding of scientific reasoning and data analysis. We introduce the ABCs of Data-Account for what you know, Be open to evidence, and Consider your confidence – a framework designed to help students evaluate their knowledge and update their understanding based on evidence. To support this process, we present the Confidence Updater, a free online tool that guides students in quantifying their confidence in a hypothesis, interpreting to what extent evidence such as data supports their hypothesis, and adjusting their confidence accordingly. We also demonstrate how these strategies integrate into OpenSciEd materials. We conclude with a brief discussion of the value in making uncertainty something your students can comfortably and confidently navigate.
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Having to deal with uncertainty is familiar to scientists working in fields that range from the life sciences to data science, but it can be difficult to support students to embrace and make sense of uncertainty in the middle school classroom. In this article, we argue that teaching about uncertainty in science education is not only beneficial but necessary for helping students develop a deeper understanding of scientific reasoning and data analysis. We introduce the ABCs of Data-Account for what you know, Be open to evidence, and Consider your confidence – a framework designed to help students evaluate their knowledge and update their understanding based on evidence. To support this process, we present the Confidence Updater, a free online tool that guides students in quantifying their confidence in a hypothesis, interpreting to what extent evidence such as data supports their hypothesis, and adjusting their confidence accordingly. We also demonstrate how these strategies integrate into OpenSciEd materials. We conclude with a brief discussion of the value in making uncertainty something your students can comfortably and confidently navigate.
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Existing estimators of parameters of item response theory (IRT) models exploit the likelihood function. In small samples, however, the IRT likelihood oftentimes contains little informative value, potentially resulting in biased and/or unstable parameter estimates and large standard errors. To facilitate small-sample IRT estimation, we introduce a novel approach that does not rely on the likelihood. Our estimation approach derives features from response data and then maps the features to item parameters using a neural network (NN). We describe and evaluate our approach for the three-parameter logistic model; however, it is applicable to any model with an item characteristic curve. Three types of NNs are developed, supporting the obtainment of both point estimates and confidence intervals for IRT model parameters. The results of a simulation study demonstrate that these NNs perform better than Bayesian estimation using Markov chain Monte Carlo methods in terms of the quality of the point estimates and confidence intervals while also being much faster. These properties facilitate (1) pretesting items in a real-time testing environment, (2) pretesting more items and (3) pretesting items only in a secured environment to eradicate possible compromise of new items in online testing.
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Assessing conceptual understanding in mathematics education requires students to explain meanings and to make connections between concept elements explicit. However, many students struggle with written answers to open-ended questions in assessments, but are able to explain their thought processes orally. The growing availability of devices capable of automatic speech recognition (ASR) and the improved performance of ASR models calls for research on integrating speech input into digital formative assessments. This study explores how speech-input answers (n = 354) from 53 Grades 5 and 6 students differed from typed answers (n = 595) in a between-group comparison and analyses in detail which individual and item factors shaped the features of the speech-input answers. Results from multi-level models indicated that speech input answers were substantially longer, belonged more often to an everyday language register, but were richer, including more arguments and explanative discourse practices so that shallow understanding became more visible. Especially for low-achieving students, speech input seemed to be beneficial, independent from the chosen input format, for both dictation tools and voice messages.
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Das vorliegende Aktionsheft möchte Jugendlichen im Alter von 10 bis 16 Jahren eine handlungsorientierte Auseinandersetzung mit dem Themenkomplex Meere und Ozean im Allgemeinen und dem Plastikmüllproblem in den Meeren und Fließgewässern im Speziellen geben. Zentrale Fragestellungen der Plastic Pirates sind dabei: Wie stark sind europäische Fließgewässer und Meere mit Plastikmüll belastet? Welche Arten von Kunststoffen lassen sich besonders häufig in der Umwelt finden und welche Auswirkungen hat das auf unsere Meere und unseren Ozean? Dieses Aktionsheft dient den Jugendlichen dabei als Hilfestellung und Orientierung für die Exkursion sowie als wissenschaftliche Anleitung zur Datenerhebung. Das Aktionsheft richtet sich in der Ansprache an die Jugendlichen selbst. Es ist so angelegt, dass diese weitestgehend selbstständig die einzelnen Schritte der Aktion durchlaufen können. Helfen Sie als pädagogische Begleitung den Jugendlichen bei der Durchführung! Das Aktionsheft ist für den Einsatz in einer Gruppe von 6 bis maximal 30 Jugendlichen konzipiert – egal ob Schulklasse, Arbeitsgemeinschaft oder Vereinsgruppe. Der Zeitaufwand für die Durchführung liegt, inklusive Vor- und Nachbereitung, bei etwa drei Tagen bzw. sechs bis acht Unterrichtsstunden zuzüglich ca. zwei Stunden für die Probennahme. Da die einzelnen Schritte unterschiedlich zeitintensiv gestaltet werden können, lässt sich das Aktionsheft aber auch gut in eine Projektwoche integrieren.
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Samples: We analyzed educational large-scale assessment data, covering all public
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The ability to write argumentative essays is an important requirement in EFL curricula in Germany and Switzerland, with grammar and lexis serving as indispensable elements of this task. The literature shows that acquiring advanced grammatical and lexical skills is challenging for students, especially genre-specific lexical abilities. In this longitudinal study, we investigate how grammatical and lexical skills develop in two educational systems among learners at upper secondary schools (operationalized as number of grammatical and lexical errors). Based on texts from n = 470 learners at two time points at the beginning and end of Year 11, it shows that learners in both countries made more lexical than grammatical errors (partial η2 = .17). There were no differences between the countries. Longitudinal analyses revealed moderate positive developments in both grammatical and lexical skills over the course of one school year (partial η2 = .08). The study confirms the importance of vocabulary for advanced L2 writers, which seems to pose a larger challenge than grammar and warrants special attention in EFL writing at upper secondary school. Implications for teacher education and classroom practice such as the emulation of model texts are discussed, with a focus on lexical chunks typical of argumentative writing.
Karriere Leichte Sprache Gebärdensprache EnglishDeutsch Startseite Forschen Alle