TY - JOUR A1 - Riese, Josef A1 - Vogelsang, Christoph A1 - Schröder, Jan A1 - Borowski, Andreas A1 - Kulgemeyer, Christoph A1 - Reinhold, Peter A1 - Schecker, Horst T1 - The development of lesson planning skills in the subject of physics T1 - Entwicklung von Unterrichtsplanungsfähigkeit im Fach Physik BT - What influence does professional knowledge have? BT - Welchen Einfluss hat Professionswissen? JF - Zeitschrift für Erziehungswissenschaft N2 - One main goal of university teacher education is the first acquisition of skills for theory-driven lesson planning. According to models of teachers' professional competence, it is assumed that the acquired professional knowledge represents an essential basis for the development of planning skills. Learning opportunities to apply this professional knowledge often occur in school internships, usually in advanced semesters of teacher education programs. It is also assumed that practical experience within lesson planning supports the formation of professional knowledge. However, the relationship between the extent of professional knowledge and the development of skills to plan a lesson lacks evidence. There is a particular challenge in measuring lesson planning skills both authentically and standardized. To evaluate the mentioned relationship, a longitudinal pre-post-study with prospective physics-teachers (N = 68 in the longitudinal section) was conducted at four German universities. Pre-service physics teachers' skills to plan a lesson were assessed with a standardized performance assessment at the beginning and at the end of a longterm-internship. This assessment consists of planning a physics lesson, conveying Newton's third Law, in a simulated and standardized way with limited time. In addition, content knowledge, pedagogical content knowledge and pedagogical knowledge has been assessed using standardized instruments. Furthermore, additional information about the internship and the amount of learning opportunities was collected at the end of the internship. During the internship, both lesson planning skills and all components of professional knowledge increased. Cross-Lagged-Panel-Analyses reveal that in particular pre-service teachers' pedagogical content knowledge as well as pedagogical knowledge at the beginning of the internship influences the development of lesson planning skills. N2 - Im Lehramtsstudium sollen Studierende grundlegende Fähigkeiten zur theoriegeleiteten Unterrichtsplanung erwerben. In Übereinstimmung mit Modellen zur professionellen Handlungskompetenz von Lehrkräften wird hierbei meist angenommen, dass das im Studienverlauf erworbene Professionswissen eine wesentliche Grundlage für den Aufbau von Fähigkeiten zur Unterrichtsplanung bildet. Lerngelegenheiten zur Anwendung dieses Professionswissens bieten vor allem schulpraktische Phasen im fortgeschrittenen Studienverlauf. Es wird aber ebenso angenommen, dass gerade Erfahrungen mit der Unterrichtsplanung den Aufbau von Professionswissen unterstützen. Der Zusammenhang zwischen dem Ausmaß des Professionswissens und der Entwicklung von Planungsfähigkeit ist bisher unzureichend empirisch geklärt. Eine besondere methodische Herausforderung besteht darin, Planungsfähigkeiten sowohl möglichst authentisch als auch auf standardisierte Weise zu erfassen. Zur Untersuchung des genannten Zusammenhangs wurde eine längsschnittliche Studie im Prä-Post-Design bei angehenden Physiklehrkräften (N = 68 im Längsschnitt) an vier Universitäten durchgeführt. Die Unterrichtsplanungsfähigkeit wurde mit Hilfe eines standardisierten Performanztests vor und nach dem Absolvieren eines Praxissemesters erfasst, indem als Standardsituation der Entwurf einer Unterrichtsstunde zum 3. Newton’schen Axiom unter definierten Zeitvorgaben im Praxissemester simuliert wurde. Zusätzlich wurden das fachliche, fachdidaktische und pädagogische Wissen der Studierenden mit Hilfe standardisierter Instrumente zu beiden Zeitpunkten erhoben, sowie die einschlägigen Lerngelegenheiten im Praxissemester über einen Fragebogen erfasst. Sowohl für Unterrichtsplanungsfähigkeit als auch für alle Wissensvariablen können Zuwächse im Praxissemester beobachtet werden. Cross-Lagged-Panel-Analysen zeigen, dass insbesondere die Ausprägung des fachdidaktischen und pädagogischen Wissens der Studierenden am Beginn des Praxissemesters die Entwicklung von Unterrichtsplanungsfähigkeit begünstigt. KW - teacher education KW - physics KW - lesson planning KW - performance assessment KW - professional knowledge KW - longitudinal study KW - Lehrerbildung KW - Physik KW - Unterrichtsplanung KW - Performanztest KW - Professionswissen KW - Längsschnittstudie Y1 - 2022 U6 - https://doi.org/10.1007/s11618-022-01112-0 SN - 1434-663X SN - 1862-5215 IS - 4 SP - 843 EP - 867 PB - Springer VS/Springer Fachmedien Wiesbaden GmbH CY - Wiesbaden ER - TY - JOUR A1 - Mientus, Lukas A1 - Nowak, Anna A1 - Wulff, Peter A1 - Borowski, Andreas ED - Mientus, Lukas ED - Klempin, Christiane ED - Nowak, Anna T1 - Unterrichtsanalyse und Reflexion BT - Ableitung eines Workshopangebots für die zweite und dritte Phase der Lehrkräftebildung JF - Reflexion in der Lehrkräftebildung: Empirisch – Phasenübergreifend – Interdisziplinär (Potsdamer Beiträge zur Lehrerbildung und Bildungsforschung ; 4) N2 - Schulpraktische Phasen stellen eine bedeutende praxisnahe Lerngelegenheit im Lehramtsstudium dar, da sie Raum für umfangreiche Reflexionen der eigenen Lernerfahrung bieten. Das im Studium erworbene theoretisch-formale Wissen steht hierbei dem praktischen Wissen und Können gegenüber. Mit der professionellen Entwicklung im Referendariat, besonders im Kompetenzbereich des Unterrichtens, kann geschlussfolgert werden, dass sich eine Reflexion über eher fachliche Aspekte unter den Studierenden im Referendariat auf eine Reflexion über eher überfachliche und pädagogische Aspekte weitet. Infolge der Analyse von N = 55 schriftlichen Fremdreflexionen von angehenden Physiklehrkräften aus Studium und Referendariat konnte diese Hypothese für den Bereich der Unterrichtsanalyse und -reflexion unterstützt werden. Weiter wurde aus der Videovignette ein Workshopangebot für Lehrkräfte der zweiten und dritten Phase der Lehrkräftebildung entwickelt, erprobt und evaluiert. KW - Reflexion KW - Unterrichtsanalyse KW - Referendariat KW - Fortbildung Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-632005 SN - 978-3-86956-566-8 SN - 2626-3556 SN - 2626-4722 IS - 4 SP - 445 EP - 452 PB - Universitätsverlag Potsdam CY - Potsdam ER - TY - JOUR A1 - Wulff, Peter A1 - Buschhüter, David A1 - Westphal, Andrea A1 - Mientus, Lukas A1 - Nowak, Anna A1 - Borowski, Andreas T1 - Bridging the gap between qualitative and quantitative assessment in science education research with machine learning BT - a case for pretrained language models-based clustering JF - Journal of science education and technology N2 - Science education researchers typically face a trade-off between more quantitatively oriented confirmatory testing of hypotheses, or more qualitatively oriented exploration of novel hypotheses. More recently, open-ended, constructed response items were used to combine both approaches and advance assessment of complex science-related skills and competencies. For example, research in assessing science teachers' noticing and attention to classroom events benefitted from more open-ended response formats because teachers can present their own accounts. Then, open-ended responses are typically analyzed with some form of content analysis. However, language is noisy, ambiguous, and unsegmented and thus open-ended, constructed responses are complex to analyze. Uncovering patterns in these responses would benefit from more principled and systematic analysis tools. Consequently, computer-based methods with the help of machine learning and natural language processing were argued to be promising means to enhance assessment of noticing skills with constructed response formats. In particular, pretrained language models recently advanced the study of linguistic phenomena and thus could well advance assessment of complex constructs through constructed response items. This study examines potentials and challenges of a pretrained language model-based clustering approach to assess preservice physics teachers' attention to classroom events as elicited through open-ended written descriptions. It was examined to what extent the clustering approach could identify meaningful patterns in the constructed responses, and in what ways textual organization of the responses could be analyzed with the clusters. Preservice physics teachers (N = 75) were instructed to describe a standardized, video-recorded teaching situation in physics. The clustering approach was used to group related sentences. Results indicate that the pretrained language model-based clustering approach yields well-interpretable, specific, and robust clusters, which could be mapped to physics-specific and more general contents. Furthermore, the clusters facilitate advanced analysis of the textual organization of the constructed responses. Hence, we argue that machine learning and natural language processing provide science education researchers means to combine exploratory capabilities of qualitative research methods with the systematicity of quantitative methods. KW - Attention to classroom events KW - Noticing KW - NLP KW - ML Y1 - 2022 U6 - https://doi.org/10.1007/s10956-022-09969-w SN - 1059-0145 SN - 1573-1839 VL - 31 IS - 4 SP - 490 EP - 513 PB - Springer CY - Dordrecht ER - TY - JOUR A1 - Wulff, Peter A1 - Mientus, Lukas A1 - Nowak, Anna A1 - Borowski, Andreas T1 - Utilizing a pretrained language model (BERT) to classify preservice physics teachers' written reflections JF - International journal of artificial intelligence in education N2 - Computer-based analysis of preservice teachers' written reflections could enable educational scholars to design personalized and scalable intervention measures to support reflective writing. Algorithms and technologies in the domain of research related to artificial intelligence have been found to be useful in many tasks related to reflective writing analytics such as classification of text segments. However, mostly shallow learning algorithms have been employed so far. This study explores to what extent deep learning approaches can improve classification performance for segments of written reflections. To do so, a pretrained language model (BERT) was utilized to classify segments of preservice physics teachers' written reflections according to elements in a reflection-supporting model. Since BERT has been found to advance performance in many tasks, it was hypothesized to enhance classification performance for written reflections as well. We also compared the performance of BERT with other deep learning architectures and examined conditions for best performance. We found that BERT outperformed the other deep learning architectures and previously reported performances with shallow learning algorithms for classification of segments of reflective writing. BERT starts to outperform the other models when trained on about 20 to 30% of the training data. Furthermore, attribution analyses for inputs yielded insights into important features for BERT's classification decisions. Our study indicates that pretrained language models such as BERT can boost performance for language-related tasks in educational contexts such as classification. KW - Reflective writing KW - NLP KW - Deep learning KW - Science education Y1 - 2022 U6 - https://doi.org/10.1007/s40593-022-00290-6 SN - 1560-4292 SN - 1560-4306 IS - 33 SP - 439 EP - 466 PB - Springer CY - New York ER - TY - JOUR A1 - Mientus, Lukas A1 - Wulff, Peter A1 - Nowak, Anna A1 - Borowski, Andreas T1 - Algorithmen als Dozierende? BT - Akzeptanz von KI-basierten Lernangeboten in der Physik-Lehrkräftebildung JF - PSI-Potsdam: Ergebnisbericht zu den Aktivitäten im Rahmen der Qualitätsoffensive Lehrerbildung (2019-2023) (Potsdamer Beiträge zur Lehrerbildung und Bildungsforschung ; 3) N2 - Auf maschinellem Lernen basierende Tools haben schon längst Einzug in unseren Alltag gefunden und so konnten auch in der Lehrkräftebildung erste Anwendungen entwickelt, erprobt und evaluiert werden. Im Teilprojekt Physikdidaktik des Schwerpunktes 2 „Schulpraktische Studien“ wurden auf Basis eines Rahmenmodells für Reflexion (Nowak et al., 2019) automatisierte Analysemethoden (Wulff et al., 2020) entwickelt und fanden Einzug in universitäre fachdidaktische Lehre (Mientus et al., 2021a). Mit dem Projekt konnten Potenziale KI-basierter Unterstützung aufgezeigt und verstetigt sowie spezifische Herausforderungen identifiziert werden. Dieser Beitrag skizziert ausgewählte Anwendungsmöglichkeiten und weiterführende Forschungen unter dem Gesichtspunkt der Akzeptanz computerunterstützter Lehre. N2 - Tools based on machine learning have entered our everyday lives, and so it has been possible to develop, test and evaluate first applications in teacher training. In the physics education research group of the focus project 2 “Practical School Studies”, automated analysis methods were developed (Nowak et al., 2019) on the basis of a reflection-supporting model (Wulff et al., 2020). These analysis methods were then employed in university teacher teaching (Mientus et al., 2021a). With this project, potentials of machine learning-based feedback were explored, and challenges were identified. This article outlines selected applications and further research with regards to the acceptance of computer-supported teaching. KW - Reflexion KW - Feedback KW - Lehrkräftebildung KW - KI-Anwendung KW - reflexion KW - feedback KW - teacher training KW - application of artificial intelligence Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-616407 SN - 978-3-86956-568-2 SN - 2626-3556 SN - 2626-4722 IS - 3 SP - 117 EP - 129 PB - Universitätsverlag Potsdam CY - Potsdam ER - TY - JOUR A1 - Wulff, Peter A1 - Mientus, Lukas A1 - Nowak, Anna A1 - Borowski, Andreas T1 - KI-basierte Auswertung von schriftlichen Unterrichtsreflexionen im Fach Physik und automatisierte Rückmeldung JF - PSI-Potsdam: Ergebnisbericht zu den Aktivitäten im Rahmen der Qualitätsoffensive Lehrerbildung (2019-2023) (Potsdamer Beiträge zur Lehrerbildung und Bildungsforschung ; 3) N2 - Für die Entwicklung professioneller Handlungskompetenzen angehender Lehrkräfte stellt die Unterrichtsreflexion ein wichtiges Instrument dar, um Theoriewissen und Praxiserfahrungen in Beziehung zu setzen. Die Auswertung von Unterrichtsreflexionen und eine entsprechende Rückmeldung stellt Forschende und Dozierende allerdings vor praktische wie theoretische Herausforderungen. Im Kontext der Forschung zu Künstlicher Intelligenz (KI) entwickelte Methoden bieten hier neue Potenziale. Der Beitrag stellt überblicksartig zwei Teilstudien vor, die mit Hilfe von KI-Methoden wie dem maschinellen Lernen untersuchen, inwieweit eine Auswertung von Unterrichtsreflexionen angehender Physiklehrkräfte auf Basis eines theoretisch abgeleiteten Reflexionsmodells und die automatisierte Rückmeldung hierzu möglich sind. Dabei wurden unterschiedliche Ansätze des maschinellen Lernens verwendet, um modellbasierte Klassifikation und Exploration von Themen in Unterrichtsreflexionen umzusetzen. Die Genauigkeit der Ergebnisse wurde vor allem durch sog. Große Sprachmodelle gesteigert, die auch den Transfer auf andere Standorte und Fächer ermöglichen. Für die fachdidaktische Forschung bedeuten sie jedoch wiederum neue Herausforderungen, wie etwa systematische Verzerrungen und Intransparenz von Entscheidungen. Dennoch empfehlen wir, die Potenziale der KI-basierten Methoden gründlicher zu erforschen und konsequent in der Praxis (etwa in Form von Webanwendungen) zu implementieren. N2 - For the development of professional competencies in pre-service teachers, reflection on teaching experiences is proposed as an important tool to link theoretical knowledge and practice. However, evaluating reflections and providing appropriate feedback poses challenges of both theoretical and practical nature to researchers and educators. Methods associated with artificial intelligence research offer new potentials to discover patterns in complex datasets like reflections, as well as to evaluate these automatically and create feedback. In this article, we provide an overview of two sub-studies that investigate, using artificial intelligence methods such as machine learning, to what extent an evaluation of reflections of pre-service physics teachers based on a theoretically derived reflection model and automated feedback are possible. Across the sub-studies, different machine learning approaches were used to implement model-based classification and exploration of topics in reflections. Large language models in particular increase the accuracy of the results and allow for transfer to other locations and disciplines. However, entirely new challenges arise for educational research in relation to large language models, such as systematic biases and lack of transparency in decisions. Despite these uncertainties, we recommend further exploring the potentials of artificial intelligence-based methods and implementing them consistently in practice (for example, in the form of web applications). KW - Künstliche Intelligenz KW - Maschinelles Lernen KW - Natural Language Processing KW - Reflexion KW - Professionalisierung KW - artificial intelligence KW - machine learning KW - natural language processing KW - reflexion KW - professionalization Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-616363 SN - 978-3-86956-568-2 SN - 2626-3556 SN - 2626-4722 IS - 3 SP - 103 EP - 115 PB - Universitätsverlag Potsdam CY - Potsdam ER - TY - JOUR A1 - Kulgemeyer, Christoph A1 - Borowski, Andreas A1 - Buschhüter, David A1 - Enkrott, Patrick A1 - Kempin, Maren A1 - Reinhold, Peter A1 - Riese, Josef A1 - Schecker, Horst A1 - Schröder, Jan A1 - Vogelsang, Christoph T1 - Professional knowledge affects action-related skills BT - the development of preservice physics teachers' explaining skills during a field experience JF - Journal of research in science teaching : the official journal of the National Association for Research in Science Teaching N2 - Professional knowledge is an important source of science teachers' actions in the classroom (e.g., personal professional content knowledge [pedagogical content knowledge, PCK] is the source of enacted PCK in the refined consensus model [RCM] for PCK). However, the evidence for this claim is ambiguous at best. This study applied a cross-lagged panel design to examine the relationship between professional knowledge and actions in one particular instructional situation: explaining physics. Pre- and post a field experience (one semester), 47 preservice physics teachers from four different universities were tested for their content knowledge (CK), PCK, pedagogical knowledge (PK), and action-related skills in explaining physics. The study showed that joint professional knowledge (the weighted sum of CK, PCK, and PK scores) at the beginning of the field experience impacted the development of explaining skills during the field experience (beta = .38**). We interpret this as a particular relationship between professional knowledge and science teachers' action-related skills (enacted PCK): professional knowledge is necessary for the development of explaining skills. That is evidence that personal PCK affects enacted PCK. In addition, field experiences are often supposed to bridge the theory-practice gap by transforming professional knowledge into instructional practice. Our results suggest that for field experiences to be effective, preservice teachers should start with profound professional knowledge. KW - enacted PCK KW - field experience KW - instructional explanation KW - instructional KW - quality KW - practicum KW - professional knowledge KW - school internship Y1 - 2020 U6 - https://doi.org/10.1002/tea.21632 SN - 0022-4308 SN - 1098-2736 VL - 57 IS - 10 SP - 1554 EP - 1582 PB - Wiley CY - Hoboken ER - TY - JOUR A1 - Kranjc Horvat, Anja A1 - Wiener, Jeff A1 - Schmeling, Sascha A1 - Borowski, Andreas T1 - Learning goals of professional development programs at science research institutions BT - a Delphi study with different stakeholder groups JF - Journal of science teacher education : the official journal of the Association for the Education of Teachers in Science N2 - Effective professional development programs (PDPs) rely on well-defined goals. However, recent studies on PDPs have not explored the goals from a multi-stakeholder perspective. This study identifies the most important learning goals of PDPs at science research institutions as perceived by four groups of stakeholders, namely teachers, education researchers, government representatives, and research scientists. Altogether, over 100 stakeholders from 42 countries involved in PDPs at science research institutions in Europe and North America participated in a three-round Delphi study. In the first round, the stakeholders provided their opinions on what they thought the learning goals of PDPs should be through an open-ended questionnaire. In the second and third rounds, the stakeholders assessed the importance of the learning goals that emerged from the first round by rating and ranking them, respectively. The outcome of the study is a hierarchical list of the ten most important learning goals of PDPs at particle physics laboratories. The stakeholders identified enhancing teachers' knowledge of scientific concepts and models and enhancing their knowledge of the curricula as the most important learning goals. Furthermore, the results show strong agreement between all the stakeholder groups regarding the defined learning goals. Indeed, all groups ranked the learning goals by their perceived importance almost identically. These outcomes could help policymakers establish more specific policies for PDPs. Additionally, they provide PDP practitioners at science research institutions with a solid base for future research and planning endeavors. KW - Teacher professional development KW - Delphi study KW - multi-stakeholder KW - analysis KW - pedagogical content knowledge Y1 - 2021 U6 - https://doi.org/10.1080/1046560X.2021.1905330 SN - 1046-560X SN - 1573-1847 VL - 33 IS - 1 SP - 32 EP - 54 PB - Routledge, Taylor & Francis Group CY - Abingdon ER - TY - JOUR A1 - Massolt, Joost Willem A1 - Borowski, Andreas T1 - Perceived relevance of university physics problems by pre-service physics teachers BT - personal constructs JF - International journal of science education N2 - Pre-service physics teachers often do not recognise the relevance for their future career in their university content knowledge courses. A lower perceived relevance can, however, have a negative effect on their motivation and on their academic success. Several intervention studies have been undertaken with the goal to increase this perceived relevance. A previous study shows that conceptual physics problems used in university physics courses are perceived by pre-service physics teachers as more relevant for their future career than regular, quantitative problems. It is however not clear, what the students' meaning of the construct 'relevance' is: what makes a problem more relevant to them than another problem? To answer this question, N = 7 pre-service teachers were interviewed using the repertory grid technique, based on the personal construct theory. Nine physics problems were discussed with regards to their perceived relevance and with regards to problem properties that distinguish these problems from each other. We are able to identify six problem properties that have a positive influence on the perceived relevance. Physics problems that are based on these properties should therefore potentially have a higher perceived relevance, which can have a positive effect on the motivation of the pre-service teachers who solve these problems. KW - Motivation KW - physics education KW - pre-service teachers KW - repertory grid Y1 - 2020 U6 - https://doi.org/10.1080/09500693.2019.1705424 SN - 0950-0693 SN - 1464-5289 VL - 42 IS - 2 SP - 167 EP - 189 PB - Routledge, Taylor & Francis Group CY - Abingdon ER - TY - JOUR A1 - Mientus, Lukas A1 - Hume, Anne A1 - Wulff, Peter A1 - Meiners, Antoinette A1 - Borowski, Andreas T1 - Modelling STEM teachers’ pedagogical content knowledge in the framework of the refined consensus model BT - A systematic literature review JF - Education Sciences : open access journal N2 - Science education researchers have developed a refined understanding of the structure of science teachers’ pedagogical content knowledge (PCK), but how to develop applicable and situation-adequate PCK remains largely unclear. A potential problem lies in the diverse conceptualisations of the PCK used in PCK research. This study sought to systematize existing science education research on PCK through the lens of the recently proposed refined consensus model (RCM) of PCK. In this review, the studies’ approaches to investigating PCK and selected findings were characterised and synthesised as an overview comparing research before and after the publication of the RCM. We found that the studies largely employed a qualitative case-study methodology that included specific PCK models and tools. However, in recent years, the studies focused increasingly on quantitative aspects. Furthermore, results of the reviewed studies can mostly be integrated into the RCM. We argue that the RCM can function as a meaningful theoretical lens for conceptualizing links between teaching practice and PCK development by proposing pedagogical reasoning as a mechanism and/or explanation for PCK development in the context of teaching practice. KW - pedagogical content knowledge (PCK) KW - refined consensus model (RCM) KW - pedagogical reasoning KW - teaching practice KW - science teaching KW - literature review Y1 - 2022 U6 - https://doi.org/10.3390/educsci12060385 SN - 2227-7102 VL - 12 SP - 1 EP - 25 PB - MDPI CY - Basel, Schweiz ET - 6 ER -