TY - JOUR A1 - Buschhüter, David A1 - Spoden, Christian A1 - Borowski, Andreas T1 - Physics knowledge of first semester physics students in Germany BT - a comparison of 1978 and 2013 cohorts JF - International journal of science education N2 - Over the last decades, the percentage of the age group choosing to pursue university studies has increased significantly across the world. At the same time, there are university teachers who believe that the standards have fallen. There is little research on whether students nowadays demonstrate knowledge or abilities similar to that of the preceding cohorts. However, in times of educational expansion, empirical evidence on student test performance is extremely helpful in evaluating how well educational systems cope with the increasing numbers of students. In this study, we compared a sample of 2322 physics freshmen from 2013 with another sample of 2718 physics freshmen from 1978 at universities in Germany with regard to their physics knowledge based on their results in the same entrance test. Previous results on mathematics knowledge and abilities in the same sample of students indicated that there was no severe decline in their average achievement. This paper compares the physics knowledge of the same two samples of students. Contrary to their mathematics results, their physics results showed a substantial decrease in physics knowledge as measured by the test. KW - University physics KW - entrance test KW - generational comparison Y1 - 2017 U6 - https://doi.org/10.1080/09500693.2017.1318457 SN - 0950-0693 SN - 1464-5289 VL - 39 IS - 9 SP - 1109 EP - 1132 PB - Routledge, Taylor & Francis Group CY - Abingdon ER - TY - JOUR A1 - Kirschner, Sophie A1 - Borowski, Andreas A1 - Fischer, Hans E. A1 - Gess-Newsome, Julie A1 - von Aufschnaiter, Claudia T1 - Developing and evaluating a paper-and-pencil test to assess components JF - International journal of science education N2 - Teachers’ professional knowledge is assumed to be a key variable for effective teaching. As teacher education has the goal to enhance professional knowledge of current and future teachers, this knowledge should be described and assessed. Nevertheless, only a limited number of studies quantitatively measures physics teachers’ professional knowledge. The study reported in this paper was part of a bigger project with the broader goal of understanding teacher professional knowledge. We designed a test instrument to assess the professional knowledge of physics teachers (N = 186) in the dimensions of content knowledge (CK), pedagogical content knowledge (PCK), and pedagogical knowledge (PK). A model describing the relationships between these three dimensions of professional knowledge was created to inform the design of the tests used to measure CK, PCK, and PK. In this paper, we describe the model with particular emphasis on the PCK part, and the subsequent PCK test development and its implementation in detail. We report different approaches to evaluate the PCK test, including the description of content validity, the examination of the internal structure of professional knowledge, and the analysis of construct validity by testing teachers across different school subjects, teachers from different school types, pre-service teachers, and physicists. Our findings demonstrate that our PCK test results could distinguish physics teachers from the other groups tested. The PCK test results could not be explained by teachers’ CK or PK, cognitive abilities, computational skills, or science knowledge. KW - Pedagogical content knowledge KW - physics education KW - teacher knowledge KW - quantitative research Y1 - 2016 U6 - https://doi.org/10.1080/09500693.2016.1190479 SN - 0950-0693 SN - 1464-5289 VL - 38 SP - 1343 EP - 1372 PB - Royal Society of Chemistry CY - Abingdon 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 - 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 - Liepertz, Sven A1 - Borowski, Andreas T1 - Testing the Consensus Model BT - professional knowledge, interconnectedness of content structure and student achievement JF - International journal of science education N2 - The structure and definition of professional knowledge is a continuing focus of science education research. In 2012, a pedagogical content knowledge (PCK) summit was held and it suggested a model of professional knowledge and skill including PCK, which was later often called the Consensus Model (Gess-Newsome, 2015. A model of teacher professional knowledge and skill including PCK: Results of the thinking from the PCK summit. In A. Berry, P. J. Friedrichsen, & J. Loughran (Eds.), Teaching and learning in science series. Re-examining pedagogical content knowledge in science education (1st ed., pp. 28–42). New York, NY: Routledge). The Consensus Model proposes a potential powerful framework for the relations among teachers’ different professional knowledge bases, but to date it has neither been investigated empirically nor systematically. In this study, we investigated the relationships suggested by the Consensus Model among different aspects of teachers’ knowledge and skill. A sample of 35 physics teachers and their classes participated in the investigation; both teachers and their students in these classes took paper-and-pencil tests. Furthermore, a lesson taught by each of the teachers was videotaped and analysed. The video analysis focused on the interconnectedness of the content structure of the lesson as representation of the in-class actions of the teachers. The interconnectedness is understood as a direct result of the application of professional knowledge of the teachers to their teaching. The teachers’ knowledge showed no significant influence on the interconnectedness of the lesson content structure. However, the results confirmed the influence of interconnectedness and certain aspects of professional knowledge on students’ outcomes. Therefore, interconnectedness of content structure could be verified as one indicator of teachers’ instructional quality. KW - Professional knowledge KW - PCK KW - the Consensus Model Y1 - 2018 U6 - https://doi.org/10.1080/09500693.2018.1478165 SN - 0950-0693 SN - 1464-5289 VL - 41 IS - 7 SP - 890 EP - 910 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 - 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 - Buschhüter, David A1 - Westphal, Andrea A1 - Nowak, Anna A1 - Becker, Lisa A1 - Robalino, Hugo A1 - Stede, Manfred A1 - Borowski, Andreas T1 - Computer-based classification of preservice physics teachers’ written reflections JF - Journal of science education and technology N2 - Reflecting in written form on one's teaching enactments has been considered a facilitator for teachers' professional growth in university-based preservice teacher education. Writing a structured reflection can be facilitated through external feedback. However, researchers noted that feedback in preservice teacher education often relies on holistic, rather than more content-based, analytic feedback because educators oftentimes lack resources (e.g., time) to provide more analytic feedback. To overcome this impediment to feedback for written reflection, advances in computer technology can be of use. Hence, this study sought to utilize techniques of natural language processing and machine learning to train a computer-based classifier that classifies preservice physics teachers' written reflections on their teaching enactments in a German university teacher education program. To do so, a reflection model was adapted to physics education. It was then tested to what extent the computer-based classifier could accurately classify the elements of the reflection model in segments of preservice physics teachers' written reflections. Multinomial logistic regression using word count as a predictor was found to yield acceptable average human-computer agreement (F1-score on held-out test dataset of 0.56) so that it might fuel further development towards an automated feedback tool that supplements existing holistic feedback for written reflections with data-based, analytic feedback. KW - reflection KW - teacher professional development KW - hatural language KW - processing KW - machine learning Y1 - 2020 U6 - https://doi.org/10.1007/s10956-020-09865-1 SN - 1059-0145 SN - 1573-1839 VL - 30 IS - 1 SP - 1 EP - 15 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 -