Preservice Science Teachers’ Strategies in Scientific Reasoning: the Case of Modeling

The development of scientific reasoning competencies is a key goal of science education. To better understand the complex construct of scientific reasoning, which includes modeling as one style of reasoning, thorough investigations of the underlying processes are needed. Therefore, in this study, a typology of preservice science teachers’ modeling strategies was developed. Thirty-two preservice science teachers were videotaped while engaging in the modeling task of investigating a black box. Following a qualitative content analysis, sequences of modeling activities were identified. By transforming these sequences of modeling activities into state transition graphs, six types of modeling strategies were derived, differing in the homogeneity and complexity of their modeling processes. The preservice science teachers engaged in activities of (1) exploration only; (2a) exploration and development with a focus on development; (2b) exploration and development with a focus on exploration; (2c) exploration and development, balanced; (3a) exploration, development, and drawing predictions from a model once; or (3b) exploration, development, and repeatedly drawing predictions from a model. Finally, this typology is discussed regarding the process of its development and its potential to inform and guide further research as well as the development of interventions aiming to foster competencies in scientific modeling

Investigating the dimensions of modeling competence among preservice science teachers: Meta-modeling knowledge, modeling practice, and modeling product

Worldwide, teachers are expected to engage their students in authentic practices, like scientific modeling. Research suggests that teachers experience challenges when integrating modeling in their classroom instruction, with one explanation that teachers themselves lack the necessary modeling competence. Currently, theoretical conceptualizations structure the modeling competence into three dimensions: meta-modeling knowledge, modeling practice, and modeling products. While each of these dimensions is well researched on its own and the three dimensions are commonly expected to be highly positively related, studies investigating their specific relationships are widely lacking. Aiming to fill this gap, the present study investigated the meta-modeling knowledge, modeling practice, and modeling products of 35 secondary preservice biology teachers engaging in a black box modeling task. Data were collected with an established pen-and-paper questionnaire consisting of five constructed response items assessing meta-modeling knowledge and by videotaping the participants engaging in the black box modeling task. Herein, the three dimensions of modeling competence were operationalized as five variables including decontextualized and contextualized meta-modeling knowledge, complexity, and homogeneity of the modeling processes and a modeling product score. In contrast to our expectations and common assumptions in the literature, significant relationships between the five variables were widely lacking. Only the complexity of the modeling processes correlated significantly with the quality of the modeling products. To investigate this relationship further, a qualitative in-depth analysis of two cases is presented. Implications for biology teacher education are discussed

What Is Difficult in Modeling? the Identification and Description of Challenges Pre-service Science Teachers Encounter in Modeling Processes

Die Entwicklung von Modellkompetenz im naturwissenschaftlichen Unterricht kann potenziell zur Erreichung vielfältiger Ziele naturwissenschaftlicher Bildung beitragen. Studien deuten allerdings darauf hin, dass Modellierungsprozesse, in denen Modelle kritisch reflektiert oder als Werkzeuge zur Erkenntnisgewinnung eingesetzt werden, im Unterricht eher selten umgesetzt werden und dass Lehrkräfte in Bezug auf Fähigkeiten des naturwissenschaftlichen Modellierens weitere Förderung benötigen. Das Ziel der vorliegenden Studie ist die Identifikation und Beschreibung von Hindernissen, die in Modellierungsprozessen von Lehramtsstudierenden naturwissenschaftlicher Fächer auftreten. Hierzu wurden die Modellierungsprozesse von 36 Lehramtsstudierenden naturwissenschaftlicher Fächer bei der Untersuchung einer Blackbox qualitativ-inhaltsanalytisch ausgewertet. Es konnten 13 verschiedene Hinderniskategorien identifiziert und beschrieben werden. Die identifizierten Hinderniskategorien weisen teils Parallelen zum Experimentieren und naturwissenschaftlichen Arbeiten allgemein auf: Spezifische Hinderniskategorien für das Modellieren ergeben sich dagegen beim Umgang mit Analogien und Erfahrungen und treten vor allem beim Testen des entwickelten Modells auf. Basierend auf vorherigen Arbeiten wurden zudem die Modellierungsprozesse der Lehramtsstudierenden analysiert und sechs typischen Modellierungsstrategien zugeordnet. Es scheint kein eindeutiger Zusammenhang zwischen den identifizierten Hindernissen und den Modellierungsstrategien vorzuliegen, da ProbandInnen, die ähnlichen Hindernissen begegnen, sich hinsichtlich ihrer Modellierungsstrategien teils deutlich unterscheiden. Es wird diskutiert, inwiefern die identifizierten Hinderniskategorien für die weitere Entwicklung von Diagnoseinstrumenten und zur gezielten Planung von Förderangeboten genutzt werden können.The development of modeling competence can potentially support the achievement of diverse goals in science education. However, studies suggest that modeling processes in which models are critically reflected or used as epistemic tools are rarely implemented in educational settings. Other studies propose a need to promote science teachers’ abilities regarding scientific modeling. The present study aims to identify and describe challenges, which pre-service science teachers encounter while modeling. Therefore, the modeling practice of 36 pre-service science teachers engaging in a blackbox activity was analyzed using a qualitative content analytic approach. 13 different challenges were identified and described. Some of the identified challenges show parallels to previously identified challenges related to experimentation and scientific practices in general. In contrast, challenges, which seem to be specific for modeling are related to the use of analogies and occur mostly when the developed models are tested. Based on previous results, the pre-service science teachers’ modeling practices were assigned to one of six types of modeling strategies. The identified challenges and the type of modeling strategy used by the pre-service science teachers seem not to be related, as pre-service science teachers encountering similar challenges can utilize very different modeling strategies. It is discussed, how the identified challenges can be used to support the development of diagnostic instruments as well as targeted interventions of modeling competence

Qualitative Content Analysis in Science Education Research Under the Consideration of Quality Criteria: a Review

Im Rahmen ihrer Entwicklung und Etablierung als empirisch arbeitende Disziplinen findet in den Naturwissenschaftsdidaktiken vermehrt eine Auseinandersetzung mit methodischen und methodologischen Fragen statt. Hierzu gehört unter anderem die Frage danach, was gute fachdidaktische Forschung überhaupt ausmacht. Obwohl die qualitative Inhaltsanalyse in der naturwissenschaftsdidaktischen Forschung als ein etabliertes Verfahren gilt, unterscheiden sich Vorschläge hinsichtlich anzulegender Gütekriterien und umzusetzender Maßnahmen der Qualitätssicherung. Im Sinne einer exemplarischen Sammlung erprobter Forschungspraxis wird in diesem Beitrag ein Überblick über die in der deutschsprachigen naturwissenschaftsdidaktischen Forschung etablierten Gütekriterien und Maßnahmen zur Qualitätssicherung bei der Umsetzung von Verfahren der qualitativen Inhaltsanalyse gegeben. Hierzu werden 50 in der Zeitschrift für Didaktik der Naturwissenschaften publizierte Artikel, die eine qualitative Inhaltsanalyse umsetzen, mit einem deduktiv-induktiv erstellten Kategoriensystem untersucht. Es werden 11 Gütekriterien identifiziert, wobei vorwiegend die klassischen Gütekriterien Validität, Reliabilität und Objektivität in den untersuchten Artikeln beschrieben werden. Von 16 identifizierten Maßnahmen der Qualitätssicherung werden am häufigsten die Modi der Kategorienbildung und die Interrater-Übereinstimmung beschrieben. Es ergibt sich ein signifikant positiver Zusammenhang zwischen dem Publikationsjahr und der Zahl der durchschnittlich beschriebenen Maßnahmen zur Qualitätssicherung. Allerdings werden die einzelnen Maßnahmen der Qualitätssicherung, über alle Artikel hinweg betrachtet, nicht konsistent jeweils einem Gütekriterium zugeordnet. Die Ergebnisse sollen die Diskussion in den Fachdidaktiken anregen und zur weiteren Etablierung und Systematisierung des Verfahrens der qualitativen Inhaltsanalyse in der naturwissenschaftsdidaktischen Forschung beitragen.In the course of developing and establishing the field of science education, methodical and methodological questions have become increasingly important. This includes questioning what poses as good qualitative research. Although, qualitative content analysis is considered an established method in science education research, there are different ideas regarding which quality criteria and measures of quality control have to be taken into account. To give an exemplary collection of reliable research practice, the present article reviews the quality criteria and measures of quality control used in science education publications utilizing a qualitative content analysis. 50 publications of the German journal Zeitschrift für Didaktik der Naturwissenschaften were investigated with a coding scheme, that was deductively-inductively developed. 11 quality criteria were identified, with validity, reliability and objectivity being the most common. 16 measures of quality control were identified, whereby descriptions of the development process of the categories and interrater-agreement were most commonly described. Also, there is a significant positive correlation between the year of publication and the number of measures of quality control described. However, these measures of quality control are inconsistently assigned to quality criteria, when all publications are taken into account. These results may spark further discussion in the science education community and support utilizing the method of qualitative content analysis more systematically

Pre-service Biology Teachers’ Responses to First-Hand Anomalous Data During Modelling Processes

In this research project we investigate the role of responses to anomalous data during modelling processes. Modelling is seen as a comprehensive practice that encompasses various aspects of scientific thinking; hence, it is an important style of scientific thinking, especially if analysed from a process-based perspective. Therefore, it provides the opportunity to understand the role of anomalous data on scientific thinking from a broader perspective. We analysed how pre-service biology teachers (N = 11) reacted to self-generated anomalous data during modelling processes induced by investigating a water black box. The videotaped and transcribed modelling processes were analysed using qualitative content analysis. If anomalous data were recognised, a majority of explanations were based on methodical issues. This finding supports results from previous studies investigating responses to first-hand anomalous data. Furthermore, we found four response patterns to anomalous data during modelling processes: no recognition, no explanation, methodical explanation, and model-related explanation. Besides, our study indicates by trend a systematic relation between response patterns to anomalous data and modelling strategies. Consequently, the improvement of responses to anomalous data could be a promising way to foster modelling competencies. We are convinced that an integrated approach to anomalous data and modelling could lead to deeper insights into the role of data in scientific thinking processes

Developing a typology of pre-service science teachers' modeling strategies

Modelle und das Modellieren sind in den Naturwissenschaften von zentraler Wichtigkeit und auch in der Lehre der Naturwissenschaften unverzichtbar. Dabei haben Modelle viele Anwen-dungszwecke; besonders epistemische Perspektiven auf Modelle und das Modellieren werden in Curricula weltweit betont. Um die curricularen Vorgaben erreichen zu können, benötigen Lehr-kräfte der Naturwissenschaften selbst die entsprechende Modellierkompetenz, allerdings ist bis-her kaum erforscht, wie Lehrkräfte der Naturwissenschaften selbst Modellieren. Die vorliegende Untersuchung nahm daher eine empirische Beschreibung individueller Modellierungsstrategien in den Fokus, indem fallbasiert und prozessorientiert eine Typologie von Modellierungsstrate-gien 36 Lehramtsstudierender der Biologie entwickelt wurde. Basierend auf dem Auftreten, der Häufigkeit und der Abfolge der Tätigkeiten wurden sechs typische Modellierungsstrategien dif-ferenziert und detailliert beschrieben. Die Ergebnisse der Untersuchung erweitern die bislang vorwiegend produktbasierten Kenntnisse naturwissenschaftsdidaktischer Forschung zu Modellen und dem Modellieren um eine Prozessfacette. Neben der erarbeiteten Typologie wurden zudem Erkenntnisse über die Dimensionalität und Extensionalität der Modellierkompetenz gewonnen, indem Zusammenhänge zwischen den identifizierten Modellierungsstrategien und weiteren Vari-ablen untersucht wurden. Hierbei zeigte sich, dass verbreitete theoretische Annahmen über die Dimensionalität und Extensionalität der Modellierkompetenz selten empirisch gestützt werden konnten.Models and modeling are of grave importance to science and the teaching of science. While var-ious purposes can be pursued with models and modeling, curricula worldwide focus on epistem-ic perspectives on models and modeling. To achieve these requirements, science teachers need sufficient modeling competence themselves, however, studies describing the modeling processes of science teachers are widely lacking. Therefore, the present study aimed to describe individual modeling strategies of 36 pre-service biology teachers empirically, by doing a case based and process-oriented analysis. Based on the occurrence, frequency and sequence of individual mod-eling activities, six typical modeling strategies were differentiated and described in detail. The results extend the formerly product-oriented state of research regarding models and modeling. Additionally, the dimensionality and extensionality of the theoretical construct of modeling competence was further explored, as relations between the identified modeling strategies and various variables were investigated. Hereby, it was shown that common theoretical assumptions regarding the dimensionality and extensionality of modeling competence may lack empirical validity

Pre-service Biology Teachers’ Responses to First-Hand Anomalous Data During Modelling Processes

In this research project we investigate the role of responses to anomalous data during modelling processes. Modelling is seen as a comprehensive practice that encompasses various aspects of scientific thinking; hence, it is an important style of scientific thinking, especially if analysed from a process-based perspective. Therefore, it provides the opportunity to understand the role of anomalous data on scientific thinking from a broader perspective. We analysed how pre-service biology teachers (N = 11) reacted to self-generated anomalous data during modelling processes induced by investigating a water black box. The videotaped and transcribed modelling processes were analysed using qualitative content analysis. If anomalous data were recognised, a majority of explanations were based on methodical issues. This finding supports results from previous studies investigating responses to first-hand anomalous data. Furthermore, we found four response patterns to anomalous data during modelling processes: no recognition, no explanation, methodical explanation, and model-related explanation. Besides, our study indicates by trend a systematic relation between response patterns to anomalous data and modelling strategies. Consequently, the improvement of responses to anomalous data could be a promising way to foster modelling competencies. We are convinced that an integrated approach to anomalous data and modelling could lead to deeper insights into the role of data in scientific thinking processes.Peer Reviewe