Next Article in Journal
Towards a Pedagogy of Trauma: Experiences of Paramedics and Firefighters in a COVID-19 Era and Opportunities for Transformative Learning
Previous Article in Journal
Rewilding Play: Design Build Interventions
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Education Sciences
Volume 12
Issue 10
10.3390/educsci12100654
education-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Using the Plan–Teach–Reflect Cycle of the Refined Consensus Model of PCK to Improve Pre-Service Biology Teachers’ Personal PCK as Well as Their Motivational Orientations

by
Franziska Behling
*,
Christian Förtsch
and
Birgit J. Neuhaus
Faculty of Biology, Biology Education, LMU Munich, 80797 Munich, Germany
*
Author to whom correspondence should be addressed.
Educ. Sci. 2022, 12(10), 654; https://doi.org/10.3390/educsci12100654
Submission received: 19 August 2022 / Revised: 21 September 2022 / Accepted: 23 September 2022 / Published: 27 September 2022
(This article belongs to the Section Teacher Education)
Browse Figures
Versions Notes

Abstract

:
In this article, we analyse how to improve pre-service biology teachers’ pPCK (personal Pedagogical Content Knowledge), professional values and motivational orientations in the field of academic and scientific language. On the basis of the theory of the Refined Consensus Model of PCK (RCM), we made a two-month quasi-experimental intervention study with 32 pre-service biology teachers. As a treatment, we trained the participants in the Plan–Teach–Reflect Cycle of enacted PCK in a school class, in the framework of a seminar. In the control group, the teaching of the cycle was replaced by presentations of their lesson plans. As dependent variables, we analysed participants’ pPCK, professional values and motivational orientations. Our results showed an increase in pre-service biology teachers’ pPCK (F(1,28) = 3.51, p = 0.04, part. η2 = 0.11, d = 0.70) and motivational orientations (F(1,23) = 29.68, p < 0.01, part. η2 = 0.56, d = 2.26) in both groups, but no effects on participants’ professional values. The teaching experience in a school class strengthened the effects both in participants’ pPCK (F(1,28) = 2.92, p = 0.04, part. η2 = 0.10, d = 0.67) and motivational orientations (F(1,23) = 7.64, p < 0.01, part. η2 = 0.25, d = 1.15). We recommend integrating the use of the Plan–Teach–Reflect Cycle of ePCK into science teacher education programmes.

1. Introduction

Recent PISA measures have demonstrated that German students’ average science performance follows an increasingly negative trend across PISA assessments [1]. What is the problem? Possibly the fact that students need to have scientific language proficiency in solving PISA scientific literacy tasks [2] and that it is impossible to perform in science without having the appropriate language proficiency [3]. Students’ achievement in biology indirectly depends on teachers’ pedagogical content knowledge (PCK; [4]), which is considered to be most relevant for teaching and, therefore, for students’ educational success [5,6,7]. The focus in science education research has been on teachers’ PCK since the 1980s when Shulman [8] proposed his idea of teachers’ knowledge of students’ (pre-)conceptions and how to deal with them, as well as useful forms of representation to make content comprehensible for learners. Hereby, he thinks of teachers’ PCK as an overlap between their pedagogical knowledge (PK) and their content knowledge (CK) [8]. For several years, researchers have suggested adding a further component to this model, technological knowledge (TK, e.g., [9,10]). Therefore, the component of technological pedagogical content knowledge results from the overlap between teachers’ PCK and their TK [9,11]. Following Shulman’s [8] definition of PCK, Carlson and Daehler [7] described the Refined Consensus Model of PCK (RCM), in which several international researchers brought together the different models of teachers’ PCK. In describing the RCM, they also assumed that several factors influence teachers’ construction of PCK, e.g., their attitudes and beliefs [7], which are also called professional values and motivational orientations [12]. Since there are hints that there is a lack of biology teachers’ PCK in the field of academic and scientific language [13], we briefly describe the RCM and use it as a basis for an intervention study designed to examine pre-service biology teachers’ professional values and motivational orientations and to improve their PCK in the field of academic and scientific language.

1.1. The Refined Consensus Model of PCK (RCM)

The RCM [7] describes teachers’ PCK in the form of a concentric circle with three realms of PCK lying within each other (Figure 1): collective PCK (cPCK, PCK shared among the science education community) as an outer circle, personal PCK (pPCK, each teacher’s assimilated PCK) as a middle circle, and enacted PCK (ePCK, each teacher’s applied PCK appearing only in a concrete teaching situation) as an inner circle.
Collective PCK (cPCK). The science education community permanently collects, shares and publishes PCK; teaching experience documented by teachers contribute to this collection of PCK, adding to the professional knowledge bases content knowledge and pedagogical knowledge [8,12]. This kind of PCK is called cPCK [7].
Personal PCK (pPCK). When teachers are confronted with cPCK, e.g., in the framework of teacher training sessions or communication situations with colleagues, they integrate (parts of) it into their own knowledge and construct an internalised form of PCK, which is called pPCK [7]. When teachers share their pPCK with the science education community, e.g., by articulating their knowledge and experiences, pPCK will be transformed into cPCK.
Teachers’ attitudes and beliefs, which are also known as professional values and motivational orientations [12], are considered to play decisive roles as so-called filters in the transformation process between cPCK and teachers’ pPCK [7]. In the following text, we use the terms professional values and motivational orientations.
Professional values address moral aspects such as teachers’ care and responsibility for students, fairness and integrity [14,15,16,17], their dealing with their own prejudices, and the power they possess over their students [18,19,20,21]. It is assumed that teacher’s professional values influence their professional performance, but it has not yet been clarified in which way they exactly do that [14,17,22]. The inverse is also assumed; that a person’s (professional) values can be changed by external influences [23,24,25], e.g., teaching situations or dealing with one’s own power and prejudices [26].
Motivational orientations describe teachers’ ability beliefs and enthusiasm [12,27,28]. They determine the intensity, quality and duration of teachers’ behaviour [27,28,29]. Teachers having strong ability beliefs use more innovative and effective methods and seem to be more resilient in their professional life [28,30]. Teachers’ enthusiasm—for their profession and the subject they teach—is considered an important characteristic of effective teaching [31,32]. Research results indicate that motivational orientations are not stable personality traits but vary depending on the learning group or the professional context [28,33], which indicates that they can be enhanced by teaching situations or teacher training.
Enacted PCK (ePCK). In any teaching situation, teachers have to apply their pPCK by choosing teaching strategies, teaching materials or tasks to structure students’ learning process. This applied PCK, which only occurs in action, is called ePCK [7]. Since each teaching situation is unique and not repeatable, ePCK is unique and not repeatable either. That is why Alonzo et al. [5] differentiate between the three steps of teaching: in the first step, teachers plan their lessons and therefore generate ePCKP. In the next step they use their lesson plan to teach the lesson in class, which is when they generate ePCKT. In the final step, they reflect on the lesson taught and generate ePCKR. This reflection feeds into their next lesson planning process—the Plan–Teach–Reflect Cycle of ePCK is complete. Each expression of ePCK influences and develops teachers’ pPCK.
Teachers’ pedagogical reasoning, also known as knowledge-based reasoning [34], is thought to moderate the transformation process between teachers’ pPCK and ePCK [7,35].
The visualisation of the RCM as concentric circles (Figure 1) shows the close relationships between the three realms of PCK: the Plan–Teach–Reflect Cycle of ePCK builds the core of PCK symbolised by the inner circle; this is embedded in pPCK, symbolised by the middle circle, and enclosed by cPCK, symbolised by the outer circle ([7]; Figure 1).
Since we are going to apply the RCM to pre-service biology teachers’ PCK in the field of academic and scientific language, we briefly introduce the importance of language in teaching and learning biology.

1.2. Language in Teaching and Learning Biology

It is impossible to access cognitively demanding learning subjects without language proficiency [2,3,36]. Several studies have shown that students’ social background and, in particular, academic language skills are the most relevant predictors of educational success [37,38,39]. What are these “academic language skills”? For science education, three so-called language registers, areas of language characterised by specific vocabulary and grammar [40], are considered relevant: the everyday register, the academic register and the science register [37,41,42].
The biology-specific science register is characterised by specific forms of representation and technical terms [43,44]. Students weak in language struggle especially with technical terms having different meanings in the science register than they do in the everyday register [45], e.g., the term “niche” in everyday language describes a small space, but in biology-specific scientific language, it relates to habitat adaption. Biology lessons often contain models or schemes to make abstract concepts and processes accessible for students [46], so students have to be enabled to use and to create such forms of representation themselves.
The academic register, to which “academic language skills” are related, is particularly characterised by such grammatical structures as passive constructions, nominalisations and a high level of abstraction and information density [42,47,48,49]. Academic language skills are necessary for understanding articles in newspapers or news programmes, reading texts in school books, and understanding exam questions. Since academic language proficiency is the greatest impact factor for educational success [38,49] and forms the basis of scientific language proficiency [36,50], students weak in language are at risk of being excluded from learning subjects [21,51,52], and not all students attend school prepared well enough to engage in the academic register [53].
The everyday register relates to everyday contexts where (oral) communication usually takes place between physically present persons. In these situations, it is not necessary to use especially precise language since one can use gestures and miming [47].
Students need to be able to switch between these registers in an appropriate way and to understand and produce texts themselves [41] for them to be able to achieve scientific literacy. There are many demands to support students’ academic language proficiency [52,53,54,55,56,57,58].

1.3. The RCM and the Language in Biology

Since teachers’ PCK indirectly influences students’ performance [4], biology teachers need appropriate PCK in the field of academic and scientific language to improve their students’ academic and scientific language proficiency. They, therefore, need biology-related linguistic knowledge for teaching biology adequately (described for chemistry by Markic [59]) and in the areas of knowledge about language registers, language-related learning difficulties and appropriate scaffolding strategies.
Many science teachers are not aware that language education might be one of their tasks [60,61]. Furthermore, the German school system, in particular, is characterised by the so-called monolingual habitus [62,63], the phenomenon that teachers expect their students to speak one language, in this case, German, while multilingualism has long been a reality in German schools [62,64,65] as well as in many other countries. Teachers do not tend to appreciate this fact and rank students’ languages according to their social prestige: there are prestigious languages such as English and French, and languages considered to have linguistic deficits that need to be “remedied”, such as Bosnian and Turkish [20,51,64,66]. We assume these aspects to be very important for the teachers’ task of improving their students’ performance in academic and scientific language and suggest considering teachers’ professional values regarding multilingualism and responsibility for language education when using the RCM to determine teachers’ development of PCK in the field of academic and scientific language. Since teachers’ enthusiasm and ability beliefs influence their achievement choices, their professional performance, effort and persistence [12,67,68], teachers’ motivational orientations to implement language-sensitive biology instruction should influence their development of PCK in the field of academic and scientific language as well. These assumptions are congruent with the findings of Mönch and Markic [61], who identified teachers’ awareness of scientific language and their own role in students’ learning process in this field as an important factor for the transformation process between cPCK and pPCK in the field of scientific language. Since it is assumed that both professional values [23,24,26] and motivational orientations [22,28,33] can be influenced by teaching situations, they should also be influenced by teachers’ PCK in the field of academic and scientific language and associated classroom experiences.
Considering the importance of academic and scientific language proficiency for students’ learning in biology (e.g., [3,37,45,49]), we strongly need appropriate teacher education programmes to improve (future) biology teachers’ PCK in the field of academic and biology-specific scientific language as well as their professional values regarding multilingualism and responsibility for language education and motivational orientations to implement language-sensitive biology instruction.

2. Research Questions and Hypotheses

Within this study, we varied the use of the Plan–Teach–Reflect Cycle of ePCK [6] as independent variable and analysed its effects on pre-service biology teachers’ (a) pPCK, (b) professional values and (c) motivational orientations (Figure 2). We were interested in the following research questions and hypotheses:
Research Question 1: How does the training of the Plan–Teach–Reflect Cycle of ePCK as a whole or in part influence pre-service biology teachers’ pPCK, professional values and motivational orientations?
Hypothesis 1:
Training the Plan–Teach–Reflect Cycle of ePCK to pre-service biology teachers enhances their …
H1a: 
… pPCK.
H1b: 
… professional values regarding multilingualism and responsibility for language education.
H1c: 
… motivational orientations to implement language-sensitive biology instruction.
Research Question 2: How important is the Teach component in the Plan–Teach–Reflect Cycle of ePCK?
Hypothesis 2:
Training the whole Plan–Teach–Reflect Cycle of ePCK has a higher effect on pre-service biology teachers than replacing the Teach component with oral presentations of lesson plans. This higher effect can be assumed for pre-service biology teachers’ …
H2a: 
… pPCK.
H2b: 
… professional values.
H2c: 
… motivational orientations.

3. Methods

3.1. Setting

In this study, we tested our hypotheses in an obligatory beginners’ seminar for pre-service biology teachers in the framework of our teacher education programme. This seminar imparts biology-specific PCK, including academic and scientific language. The pre-service teachers had to use it to plan parts of biology lessons, e.g., an introduction or the elaborate use of a model. The seminar’s duration was 90 min, once a week for two months. Three ECTS credits (European Credit Transfer and Accumulation System; one ECTS-credit corresponds to 25–30 working hours) can be acquired.

3.2. Design and Procedure

The quasi-experimental study was conducted in a pre-post-test design (Figure 3). As an independent variable, the Plan–Teach–Reflect Cycle of ePCK [5] was varied as described below. As the dependent variable, we measured pre-service biology teachers’ pPCK, professional values and motivational orientations before and after the intervention.
The pre-test took place at the beginning of the seminar, and the post-test at the end of the seminar (Figure 3). At both times, participants’ pPCK, professional values and motivational orientations were tested by using paper-and-pencil tests. Between these tests, pre-service biology teachers joined a two-month biology education seminar.

3.3. Sample

Participants of the study were 32 pre-service teachers, on average, in their 5th semester (M = 5.59; SD = 1.81). The group was divided into a treatment group (N = 15; 7 female, 8 male; all with German as first language, 2 bilingual) and a control group (N = 17; 10 female, 7 male; all with German as first language, 3 bilingual). As the seminar was obligatorily scheduled and there were two time slots owing to organisational reasons, they decided themselves which time slot and thereby which group they joined.

3.4. Intervention

In the treatment group, pre-service biology teachers taught parts of biology lessons at school as part of the Plan–Teach–Reflect Cycle of ePCK [5]: the participants had to plan parts of biology lessons to generate ePCKP. These parts could be the introduction, the elaborate use of a model to test a hypothesis or the work with a diagram. The concrete part of a lesson and the lesson topic were decided randomly. Afterwards, each pre-service biology teacher would teach the planned parts of a biology lesson with students to generate ePCKT. During the following joint reflections, which focused on academic and scientific language, the participants generated ePCKR. Thereafter they were asked to describe the observed classroom situations, especially those regarding academic and scientific language, to explain their relevance to students’ learning and to propose alternative instruction strategies. Teaching and reflecting on their biology lessons was possible because of a partner school, which is a secondary school with about 900 students largely having first languages other than German. In this school, we could use a biology classroom once a week where the teaching situations were videotaped and live-broadcast to a neighbouring observation room where the fellow pre-service teachers and the lecturer observed them. In this way, the pre-service teachers were trained in the whole Plan–Teach–Reflect Cycle of ePCK once a week.
In the control group, pre-service biology teachers only made oral presentations of their planned parts of biology lessons to the seminar group instead of teaching them in a school class. All other aspects of the seminar were the same, including the reflection: the pre-service teachers had to describe the planned classroom situation, especially those involving academic and scientific language; to explain their relevance for students’ learning; and to propose alternative instruction strategies. That way, the pre-service teachers were trained only in two parts of the Plan–Teach–Reflect Cycle of ePCK once a week: the Teach component was replaced by oral presentations of lesson plans.

3.5. Test Instruments

pPCK, professional values and motivational orientations were measured from standardised paper-and-pencil tests. All test instruments showed acceptable values for objectivity and for homogeneity (except professional values; Table 1). We used Rasch theory to compute values for reliability, which enables conversion of the non-linear raw scores from our measurements to linear person ability scores that can be used for data analysis [69]. The person’s ability scores were converted to a range from 0–100 [70]. We used the programme Winsteps [71], and all data met the desired requirements [71,72,73].
In the following, each scale is described in more detail:
pPCK. We measured pre-service biology teachers’ pPCK with a focus on academic and biology-specific scientific language by paper-and-pencil tests with 12 items (7 multiple choice and 5 open response), which took the participants 20 min. The test was based on a proven test [74] adapted to our content area of PCK. For content validity, we followed the recommendations of Reeves and Marbach-Ad [75]: based on a literature review (e.g., [37,42,43,45,59]), the content area of language in biology education and learning objectives for pre-service biology teachers were defined [76], and theory-based items according to those of Author 3 [74] were constructed. For construct validity, we used the Wright map of the Rasch analysis [77,78], which showed an even distribution of item difficulties. Thereby, items that were easier to agree with were located at the lower end of the Wright map, e.g., “Assign the respective language register to the example.”, and items that were more difficult to agree with were located at the upper end of the Wright map, e.g., “Highlight characteristics of academic language in the following text.” The open-response items were based on the Rasch Partial Credit Model (PCM; [71,79]), which allows consideration of multiple-level items. The test included seven multiple-choice items about the three classroom-relevant language registers [40,42,80], two items requesting highlighting of characteristics of academic and scientific language in a schoolbook’s text, one item asking for as many terms as possible with different meanings in everyday and biology-specific scientific language, and two items requesting lightening the linguistic load of a biology task in a well-founded way [45,81,82]. For objectivity, 10% of the sample was double-coded by two independent researchers, showing a high agreement (ICC(59,59) = 0.91, p < 0.001). After the application of the Rasch PCM, the scale showed acceptable values for homogeneity (item reliability = 0.97, person reliability = 0.88), and all items showed good fit values (Table 1).
Professional Values. We measured participants’ professional values regarding multilingualism and responsibility for students’ language development on a four-point Likert scale (ranging from strongly disagree to strongly agree) paper-and-pencil test with 20 items, which took the pre-service teachers five minutes. This test instrument was developed in the context of this study since there were no existing test instruments at the time [75]. During the development process, former freshly graduated students with a non-German native language were first interviewed about their experiences at school, especially in biology class and with biology teachers. In the second step, literature about language-and-migration-related discrimination was consulted (e.g., [51,66]). This procedure formed the basis for the development of 20 items: attitude towards their own responsibility for language education in their classes (5 items; [21]; e.g., “If there are language difficulties in biology lessons, it is my job as a biology teacher to take care of them.”), attitude towards the coincidence of linguistic and content-specific proficiency (4 items; [2,36]; e.g., “If a student struggles in my biology lessons, it could be that the necessary linguistic tools for the content have not been addressed.”), attitude towards multilingualism among their students (6 items; [18,21]; e.g., “Only German is spoken in my lessons.”), attitude towards the teaching of scientific language as a goal of biology lessons (5 items; [83]; e.g., “The aim of biology lessons is to master the biology-specific science language accurately.”). To strengthen content validity, we gave the items to a group of in-service biology teachers and asked them to write down their thoughts, e.g., if the questions were clear, if they missed anything important according to the topic, or if they would recommend another wording. For construct validity, we used the Wright map of the Rasch analysis [77,78], which showed an even distribution of item difficulties. Thereby, items that were easier to agree with were located at the lower end of the Wright map, e.g., “If students struggle with science language it is my task as a biology teacher to care about it.”, and items that were more difficult to agree with were located at the upper end of the Wright map, e.g., “Students are allowed to use their non-German first language such as Turkish or Arabic in my classes when working in a group.” Data were analysed using the Rasch PCM and showed partly acceptable values for homogeneity (item reliability = 0.97, person reliability = 0.36) and good item fit values (Table 1).
Motivational Orientations. Pre-service biology teachers’ motivational orientations to implement language-sensitive biology instruction were measured by a paper-and-pencil questionnaire with 36 items on a five-point Likert scale (ranging from strongly disagree to strongly agree), which took the participants ten minutes. The test was based on the expectancy-value-theory of achievement motivation [68,84] and was adapted to language-sensitive biology instruction [85], whereby only the term “Language-sensitive” replaced the original term “concept-orientated”: the expectation of success (5 items; e.g., “If I offer language-sensitive classes, I will get more recognition from students and parents.”), ability beliefs (5 items; e.g., “I am able to develop language-sensitive tasks.”), perception of task demands (6 items; e.g., “There are enough subjects during teacher education on the topic of language-sensitive teaching.”), utility value (8 items; e.g., “Language-sensitive lessons are more structured than others.”), intrinsic value (4 items; e.g., “I enjoy teaching language-sensitive lessons.”), personal cost (8 items; e.g., “In order to offer language-sensitive lessons, I have to invest a lot of time to familiarise myself with the concept myself.”). For construct validity, we used the Wright map of the Rasch analysis [77,78], which showed an even distribution of item difficulties. Thereby, items that were easier to agree with were located at the lower end of the Wright map, e.g., “There are enough subjects during teacher education on the topic of language-sensitive teaching.”, and items that were more difficult to agree with were located at the upper end of the Wright map, e.g., “I am so well versed in the idea of language-sensitive teaching that I can pass it on to fellow pre-service teachers.” The Rasch PCM was applied to analyse data, which showed acceptable values for homogeneity (item reliability = 0.93, person reliability = 0.89), as well as good item-fit values (Table 1).

3.6. Data Analysis

3.6.1. Descriptive Analyses

We used mean values and standard deviations of all resulting person ability scores (Table 2) and calculated Pearson correlations and coefficients of determination between all measured variables (Table 3). Unpaired t-tests for all variables between the treatment group and control group were calculated to make sure the two groups would not differ significantly (Table 4).

3.6.2. ANOVA

To check our hypotheses, three mixed ANOVAs were calculated with the described intervention as an independent variable and pre-service teachers’ pPCK, professional values and motivational orientations as dependent variables (Table 5). To test Hypothesis 1, we interpreted the effects of time as the effects of training the Plan–Teach–Reflect Cycle of ePCK to pre-service biology teachers, which we did both in the treatment and the control group. To test Hypothesis 2, we focused on interaction effects to identify the effect of the training of the full Plan–Teach–Reflect Cycle of ePCK in comparison with replacing the Teach component with oral presentations of lesson plans.

4. Results

The descriptive results of all measured variables are shown in Table 2.

4.1. Correlations

We found no correlations between pre-service biology teachers’ pPCK and their professional values (r = 0.27, R2 = 0.07, p = 0.17), between their pPCK and their motivational orientations (r = −0.09, R2 = 0.01, p = 0.67) or between their professional values and their motivational orientations (r = 0.33, R2 = 0.11, p = 0.11; Table 3).

4.2. Unpaired t-Tests

There was a significant difference in the pre-test motivational orientations of pre-service biology teachers’ person ability scores between the treatment group (M = 48.92, SD = 0.45, Min = 48.10, Max = 49.57) and the control group (M = 48.36, SD = 0.35, Min = 47.61, Max = 49.00); the unpaired t-test displayed a large effect (t(26) = −0.63, p = 0.001, d = 1.37, 70). Thus, the treatment group’s mean person ability score was higher than the control group’s; no other group differences were significant (Table 4).

4.3. Mixed ANOVAs

To analyse the treatment effect of our intervention described above, we calculated three mixed ANOVAs with the described intervention as an independent variable and pre-service biology teachers’ pPCK, professional values and motivational orientations as dependent variables (Table 5).
According to Hypothesis 1, we interpreted the effect of time, which would allow a statement about the effect of training in the Plan–Teach–Reflect Cycle of ePCK on pre-service biology teachers in both the treatment and the control groups. Results showed a medium effect of time on pre-service biology teachers’ (a) pPCK (F(1,28) = 3.51, p = 0.04, part. η2 = 0.11, d = 0.70), no effect of time on their (b) professional values (F(1,24) = 0.05, p = 0.41), and a strong effect of time on their (c) motivational orientations (F(1,23) = 29.68, p < 0.001, part. η2 = 0.56, d = 2.26; Table 5).
To check Hypothesis 2, we interpreted the interaction effect between treatment and time. This allows a statement if training in the full Plan–Teach–Reflect Cycle of ePCK to pre-service biology teachers enhances their pPCK, their professional values and their motivational orientations in comparison with replacing the Teach component with oral presentations of lesson plans. Results showed a medium interaction effect on pre-service biology teachers’ (a) pPCK (F(1,28) = 2.92, p = 0.04, part. η2 = 0.10, d = 0.67), no interaction effect on their (b) professional values (F(1,24) = 0.47, p = 0.25), and a strong interaction effect on their (c) motivational orientations (F(1,23) = 7.64, p < 0.01, part. η2 = 0.25, d = 1.15; Table 5).

5. Discussion

The results of our study indicate that training in the Plan–Teach–Reflect Cycle of ePCK [5] as a whole or in parts enhances pre-service biology teachers’ pPCK in the field of academic and scientific language and their motivational orientations to implement language-sensitive biology instruction. Including the Teach component in the Cycle improves the effectiveness of the Plan–Teach–Reflect Cycle of ePCK (Figure 4).
We further hypothesised that training in the Plan–Teach–Reflect Cycle of ePCK [5] to pre-service biology teachers would enhance their professional values regarding multilingualism and responsibility for language education and that this effect would be strengthened by teaching parts of a biology lesson at school, neither of which we were able to prove.
The variables professional values and motivational orientations were not correlated. These are both affective components assumed to play a decisive role in the transformation process between cPCK and pPCK [7,35]; the subscales “attitude towards their own responsibility for language education” [21], “utility value” and “intrinsic value” [68,84] in particular refer to a similar mindset. From these and the fact that values influence motivational goals [86], one might have assumed a strong correlation. However, they are also described as separate constructs [12], and our results would support this assumption.
We are convinced that especially their professional values have a decisive influence on teachers’ behaviour in class [17,22,86] and on the transformation process between cPCK and pPCK in the field of academic and scientific language [61]. There was no measurable change in pre-service biology teachers’ professional values, although these are considered to be changeable [23,25]. Values, teachers’ professional values as well, often function as schemes, also called “truisms”: people tend to ignore things that are incongruent with their internalised schemes [23] and do not question their truisms [87]. Education, as well as teacher education, influences people’s values [17,88], but to introduce changes in value commitments, people have to become aware of their own implicit value commitments [20,26,89]. We assume this to be the decisive factor: the setting of our study did not arrange an explicit confrontation with one’s own professional values. Furthermore, it takes time to change value commitments since they are more persistent than beliefs [90], so we perhaps should consider eight weeks not to be long enough for such change processes.
Further research would be useful to examine the nature of science teachers’ professional values regarding multilingualism and responsibility for language education in greater depth by examining the individual subscales since they are considered to play a decisive role in their PCK in the field of academic and scientific language [61]. On this basis, effective strategies influencing pre-service teachers’ professional values in a positive way can be developed. We suggest setting an intervention over a longer period, e.g., according to Bardi and Goodwin’s [23] theoretical routes to value change or Derman-Sparks’ [26] Anti-Bias Curriculum.
We assumed and found an increase in pre-service teachers’ motivational orientations to implement language-sensitive biology instruction after their training in the Plan–Teach–Reflect Cycle of ePCK [5]. This was strengthened by the teaching of a biology lesson at school: focusing on academic and scientific language proficiency as a biology teachers’ task, and providing knowledge about linguistic hurdles and scaffolding strategies for both treatment and control group, led to stronger motivational orientations. The practical experience and lesson observation at school were able to strengthen this effect, which is in agreement with other authors’ results [68,84,91]. The teaching experience at school seems to help pre-service biology teachers to be better prepared for (linguistic) diversity at school, which is something they wish for [32].
We expected to find an increase in pre-service biology teachers’ pPCK in the field of academic and scientific language. Training in the Plan–Teach–Reflect Cycle of ePCK [5] enhanced pre-service teachers’ pPCK, which was strengthened by teaching parts of a biology lesson at school. We explain the finding of the increase in participants’ pPCK due to the training in the Plan–Teach–Reflect Cycle of ePCK by the fact that we imparted cPCK in this field in the framework of the seminar, and the focus on academic and scientific language during the joint reflection of the presented or taught parts of biology lessons. We explain the finding of the strengthening due to teaching parts of a biology lesson at school by the experience of the direct interaction with (multilingual) students at school, the responsibility (pre-service) teachers feel for their students [16,92], and the experience of existing linguistic hurdles [21,93]. These results indicate that our approach helps foster pre-service biology teachers’ pPCK in the field of academic and scientific language and encourages us to continue our approach.
Until now, research about PCK in the field of academic and scientific language has concentrated more on the question of which needs students have and which concrete strategies help them in the classroom [37,57,94,95]. In our opinion, there is a great need to examine more closely the nature of PCK in the field of academic and scientific language, as started by Mönch and Markic [61], and its impact on students’ performance. Therefore, we recommend future research: in the first step, the correlations between pre-service as well as in-service science teachers’ (1) PCK in the field of academic and scientific language, (2) their professional values regarding multilingualism and responsibility for language education, and their (3) motivational orientations to implement language-sensitive instruction should be detected, as started by [35], and thereby it should be verified if there is a difference between pre-service and in-service teachers. In the second step, the three components of the Plan–Teach–Reflect Cycle of ePCK [5] and how they influence each other should be investigated, as started by [96]. In the third step, the impact of (1), (2) and (3) on students’ performance in science should be explored. Since science teachers’ TPACK is assumed to be a predictor of the quality of their lesson plans with technology integration [97], further research should include this component.

6. Limitations of the Research

We are aware of several limitations of our study: first, the sample size is quite small; therefore, the study does not provide representative results. To collect representative data, more than one cohort of pre-service teachers should be included in the study. Second, we were not able to provide fully experimental conditions: the distribution of the participants between the treatment and control group was not random since the pre-service teachers decided themselves which group they joined, mostly due to the timeslot which was appropriate for them. The t-test explored a significant difference in participants’ PCK between the treatment and control group. Nevertheless, our results showed an effect of time as well as an intervention effect. Third, the RCM [7] formed the theoretical basis of our research, which describes the PCK of in-service teachers, whereas the participants of our study were pre-service teachers. Although it can be anticipated that there are differences in the PCK, professional values and motivational orientations of in-service and pre-service teachers, we do not assume that this makes a difference for our measurements: we did not explore the nature of the three constructs but tried to identify strategies to enhance them. Fourth, the person reliability scores of the professional-values test were at the lower end, so the test instrument only was able to distinguish between two groups of pre-service teachers, those with high and those with low professional values. Therefore, all results on pre-service teachers’ professional values should be regarded with caution. For future research, more items should be added [98].

7. Implications for Teacher Education

Teachers’ PCK influences students’ performance indirectly [4], and their motivational orientations determine the intensity, quality and duration of teachers’ behaviour [27,28,29]. Therefore, if we want to increase our students’ performance in science, we should start with the science teachers’ PCK in the field of academic and scientific language and their motivational orientations to implement language-sensitive biology instruction to improve students’ academic and scientific language proficiency. Therefore, we suggest focusing on academic and scientific language in science teacher education programmes for pre-service as well as for in-service science teachers.
Our study is related to biology teacher education, but we consider our results to be applicable to chemistry and physics education as well: although the biology-specific science register differs from the chemistry- and physics-specific science register, the way of thinking is the same as is the way of constructing knowledge.
We acted within the framework of the structural conditions of the German teacher education system to explore a realistic and permanent possibility of integrating our approach into existing science teacher education programmes. This approach provides neither a large sample size nor fully experimental conditions, but it does provide high ecological validity. This is why we are convinced that the approach will also work for biology, chemistry and physics teacher education programmes in other countries. Therefore, we recommend the use of the Plan–Teach–Reflect Cycle of ePCK [5] in the framework of teacher education programmes to enhance pre-service teachers’ pPCK and motivational orientations, if possible, including teaching situations at school, which have to be guided by a university to be most effective [99].

Author Contributions

Conceptualization, F.B., C.F. and B.J.N.; methodology, F.B., C.F. and B.J.N.; formal analysis, F.B. and C.F.; writing—original draft preparation, F.B.; writing—review and editing, C.F. and B.J.N.; project administration, B.J.N.; funding acquisition, B.J.N. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the German Federal Ministry of Education and Research (Bundesministerium für Bildung und Forschung—BMBF), grant number 01JA1510.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki, and Ethical review and approval were waived.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

Information and queries on the data can be obtained from the authors of this article.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. OECD. PISA 2018 Results (Volume I). What Students Know and Can Do; OECD Publishing: Paris, France, 2018. [Google Scholar]
  2. Gogolin, I. Chancen und Risiken nach PISA—Über Bildungsbeteiligung von Migrantenkindern und Reformvorschläge. In Schieflagen im Bildungssystem; Die Benachteiligung der Migrantenkinder; Auernheimer, G., Ed.; Springer Fachmedien: Wiesbaden, Germany, 2013; pp. 33–50. [Google Scholar]
  3. Osborne, J. Science without Literacy: A Ship without a Sail? Camb. J. Educ. 2002, 32, 203–218. [Google Scholar] [CrossRef]
  4. Förtsch, C.; Werner, S.; Kotzebue, L.v.; Neuhaus, B.J. Effects of Biology Teachers’ Professional Knowledge and Cognitive Activation on Students’ Achievement. Int. J. Sci. Educ. 2016, 38, 2642–2666. [Google Scholar] [CrossRef]
  5. Alonzo, A.C.; Berry, A.; Nilsson, P. Unpacking the Complexity of Science Teachers’ PCK in Action: Enacted and Personal PCK. In Repositioning Pedagogical Content Knowledge in Teachers’ Knowledge for Teaching Science; Hume, A., Cooper, R., Boroswki, A., Eds.; Springer: Singapore, 2019; pp. 271–286. [Google Scholar]
  6. Alonzo, A.C.; Kim, J. Declarative and Dynamic Pedagogical Content Knowledge as Elicited through Two Video-Based Interview Methods. J. Res. Sci. Teach. 2016, 53, 1259–1286. [Google Scholar] [CrossRef]
  7. Carlson, J.; Daehler, K.R. The Refined Consensus Model of Pedagogical Content Knowledge in Science Education. In Repositioning Pedagogical Content Knowledge in Teachers’ Knowledge for Teaching Science; Hume, A., Cooper, R., Boroswki, A., Eds.; Springer: Singapore, 2019; pp. 77–92. [Google Scholar]
  8. Shulman, L.S. Those Who Understand: Knowledge Growth in Teaching. Educ. Res. 1986, 15, 4–14. [Google Scholar] [CrossRef]
  9. Koehler, M.J.; Mishra, P.; Cain, W. What Is Technological Pedagogical Content Knowledge (TPACK)? Cite J. 2009, 9, 60–70. [Google Scholar] [CrossRef]
  10. Koehler, M.J.; Mishra, P.; Kereluik, K.; Shin, T.S.; Graham, C.R. The Technological Pedagogical Content Knowledge Framework. In Handbook of Research on Educational Communications and Technology; Spector, J.M., Merrill, D.M., Elen, J., Bishop, M.J., Eds.; Springer: Singapore, 2014; pp. 101–111. [Google Scholar]
  11. Von Kotzebue, L. Two is better than one—Examining biology-specific TPACK and its T-dimensions from two angles. J. Res. Technol. Educ. 2022, 1–18. [Google Scholar] [CrossRef]
  12. Baumert, J.; Kunter, M. Das Kompetenzmodell von COACTIV. In Professionelle Kompetenz von Lehrkräften; Kunter, M., Baumert, J., Blum, W., Klusmann, U., Krauss, S., Neubrand, M., Eds.; Waxmann: Münster, Germany, 2011; pp. 29–54. [Google Scholar]
  13. Matt, A. Professionelle Kompetenz von Lehrkräftem—Was wissen und denken Lehrkräfte über sprachsensiblen Unterricht? In Schriftliche Hausarbeit gem. §29 der LPO I am Lehrstuhl für Didaktik der Biologie; LMU München: München, Germany, 2020. [Google Scholar]
  14. Baumert, J.; Kunter, M. Stichwort: Professionelle Kompetenz von Lehrkräften. ZfE 2006, 9, 469–520. [Google Scholar] [CrossRef]
  15. Flynn, T.; Bruce, C.D. Action Research as Professional Learning for Educators. In The Wiley Handbook of Action Research in Education; Mertler, C.A., Ed.; John Wiley & Sons: Hoboken, NJ, USA, 2019; pp. 273–294. [Google Scholar]
  16. Oser, F. Wann lernen Lehrer ihr Berufsethos? In Die Institutionalisierung von Lehren und Lernen; Leschinsky, A., Ed.; Beltz: Weinheim, Germany, 1996; pp. 235–243. [Google Scholar]
  17. Sunley, R.; Locke, R. Exploring UK secondary teachers’ professional values: An overview of the literature since 2000. Educ. Res. 2010, 52, 409–425. [Google Scholar] [CrossRef]
  18. Mecheril, P.; Quehl, T. Die Sprache der Schule. Eine migrationspädagogische Kritik der Bildungssprache. In Sprache und Bildung in Migrationsgesellschaften: Machtkritische Perspektiven auf ein prekarisiertes Verhältnis; Thoma, N., Knappig, M., Eds.; Transcript: Bielefeld, Germany, 2015; pp. 151–177. [Google Scholar]
  19. Paulsel, M.L.; Chory-Assad, R.M.; Dunleavy, K.N. The Relationship between Student Perceptions of Instructor Power and Classroom Justice. Commun. Res. Rep. 2005, 22, 207–215. [Google Scholar] [CrossRef]
  20. Schmidt, B. Den Anti-Bias-Ansatz zur Diskussion stellen. Beitrag zur Klärung theoretischer Grundlagen in der Anti-Bias-Arbeit; BIS-Verlag der Carl von Ossietzky Universität: Oldenburg, Germany, 2009. [Google Scholar]
  21. Tajmel, T.; Hägi-Mead, S. Sprachbewusste Unterrichtsplanung. Prinzipien, Methoden und Beispiele für die Umsetzung; Waxmann: Münster, Germany; New York, NY, USA, 2017. [Google Scholar]
  22. Palermo, C.; Thomson, M.M. Large-Scale Assessment as Professional Development: Teachers’ Motivations, Ability Beliefs, and Values. Teach. Dev. 2019, 23, 192–212. [Google Scholar] [CrossRef]
  23. Bardi, A.; Goodwin, R. The Dual Route to Value Change: Individual Processes and Cultural Moderators. J. Cross Cult. Psychol. 2011, 42, 271–287. [Google Scholar] [CrossRef]
  24. Gollan, T. Sozialer Einfluss auf Werthaltungen und seine Konsequenzen für kulturelle Diffusion. Ph.D. Thesis, Universität Hamburg, Hamburg, Germany, 2012. [Google Scholar]
  25. Ryndak, V.G.; Saldaeva, O.V. The Revival of Values and Meanings of the Teacher Education: Reflexive-Creative Approach. Cypriot J. Educ. Sci. 2019, 14, 266–277. [Google Scholar] [CrossRef]
  26. Derman-Sparks, L. Anti-Bias Curriculum. Tools for Empowering Young Children; National Association for the Education of Young Children: Washington, DC, USA, 1989. [Google Scholar]
  27. Han, J.; Yin, H. Teacher Motivation: Definition, Research Development and Implications for Teachers. Cogent Educ. 2016, 3, 1217819. [Google Scholar] [CrossRef]
  28. Kunter, M. Motivation als Teil der professionellen Kompetenz—Forschungsbefunde zum Enthusiasmus von Lehrkräften. In Professionelle Kompetenz von Lehrkräften; Kunter, M., Baumert, J., Blum, W., Klusmann, U., Krauss, S., Neubrand, M., Eds.; Waxmann: Münster, Germany, 2011; pp. 259–275. [Google Scholar]
  29. Mitchell, T.R. Matching Motivational Strategies with Organizational Contexts. Res. Organ. Behav. 1997, 19, 57–149. [Google Scholar]
  30. Brouwers, A.; Tomic, W. A Longitudinal Study of Teacher Burnout and Perceived Self-Efficacy in Classroom Management. Teach. Teach. Educ. 2000, 16, 239–253. [Google Scholar] [CrossRef]
  31. Helmke, A. Unterrichtsqualität: Erfassen, Bewerten, Verbessern; Kallmeyersche Verlagsbuchhandlung: Seelze, Germany, 2003. [Google Scholar]
  32. Woolfolk Hoy, A.; Davis, H.; Pape, S.J. Teacher Knowledge and Beliefs. In Handbook of Educational Psychology; Alexander, P.A., Winne, P.H., Eds.; Routledge: New York, NY, USA, 2006; pp. 715–737. [Google Scholar]
  33. Ryan, R.M.; Deci, E.L. Intrinsic and Extrinsic Motivations: Classic Definitions and New Directions. Contemp. Educ. Psychol. 2000, 25, 54–67. [Google Scholar] [CrossRef] [PubMed]
  34. Seidel, T.; Stürmer, K. Modeling and Measuring the Structure of Professional Vision in Preservice Teachers. Am. Educ. Res. J. 2014, 51, 739–771. [Google Scholar] [CrossRef]
  35. Behling, F.; Förtsch, C.; Neuhaus, B.J. The Refined Consensus Model of Pedagogical Content Knowledge (PCK): Detecting Filters Between the Realms of PCK. Educ. Sci. 2022, 12, 592. [Google Scholar] [CrossRef]
  36. Prediger, S. Sprachbildung im Fachunterricht, ja klar, aber was genau, und wie? Überblicke und Einblicke in mathematikspezifische empirische Studien. In Fachgespräch, Ludwig-Maximilians; Universität München: München, Germany, 2017. [Google Scholar]
  37. Childs, P.E.; Markic, S.; Ryan, M.C. The Role of Language in the Teaching and Learning of Chemistry. In Chemistry Education: Best Practices, Opportunities and Trends; Garcia-Martinez, J., Serrano-Torregrosa, E., Eds.; Wiley-VCH: Weinheim, Germany, 2015; pp. 421–446. [Google Scholar]
  38. Prediger, S.; Wilhelm, N.; Büchter, A.; Gürsoy, E.; Benholz, C. Sprachkompetenz und Mathematikleistung—Empirische Untersuchung sprachlich bedingter Hürden in den Zentralen Prüfungen 10. J. Für Math. -Didakt. 2015, 36, 77–104. [Google Scholar] [CrossRef]
  39. Watermann, R.; Baumert, J. Entwicklung eines Strukturmodells zum Zusammenhang zwischen sozialer Herkunft und fachlichen und überfachlichen Kompetenzen: Befunde national und international vergleichender Analysen. In Herkunftsbedingte Disparitäten im Bildungswesen:Differenzielle Bildungsprozesse und Probleme der Verteilungsgerechtigkeit; Vertiefende Analysen im Rahmen von PISA 2000; Baumert, J., Stanat, P., Watermann, R., Eds.; VS Verlag für Sozialwissenschaften: Wiesbaden, Germany, 2006; pp. 61–94. [Google Scholar]
  40. Halliday, M.A.K. Learning How to Mean: Explorations in the Development of Language; Arnold: London, UK, 1975. [Google Scholar]
  41. Moschkovich, J.N. Academic Literacy in Mathematics for English Learners. J. Math. Behav. 2015, 40, 43–62. [Google Scholar] [CrossRef]
  42. Riebling, L. Heuristik der Bildungssprache. In Herausforderung Bildungssprache—Und wie man sie Meistert; Gogolin, I., Lange, I., Michel, U., Reich, H.H., Eds.; Waxmann: Münster, Germany, 2013; pp. 106–153. [Google Scholar]
  43. Nitz, S.; Nerdel, C.; Prechtl, H. Entwicklung eines Erhebungsinstruments zur Erfassung der Verwendung von Fachsprache im Biologieunterricht. Z. Für Didakt. Der Nat. 2012, 18, 117–139. [Google Scholar]
  44. Nitz, S.; Prechtl, H.; Nerdel, C. Survey of classroom use of representations: Development, field test and multilevel analysis. Learn. Environ. Res. 2014, 17, 401–422. [Google Scholar] [CrossRef]
  45. Drumm, S. Sprachbildung im Biologieunterricht; De Gruyter Mouton: Berlin, Germany, 2016. [Google Scholar]
  46. Taber, K.S. Exploring the Language(s) of Chemistry Education. Chem. Educ. Res. Pract. 2015, 16, 193–197. [Google Scholar] [CrossRef]
  47. Gogolin, I. Durchgängige Sprachbildung. Qualitätsmerkmale für den Unterricht; Waxmann: Münster, Germany, 2011. [Google Scholar]
  48. Lange, I. Bildungssprache. In Handbuch Mehrsprachigkeit und Bildung; Gogolin, I., Hansen, A., McMonagle, S., Rauch, D.P., Eds.; Springer VS: Wiesbaden, Germany, 2020; pp. 53–58. [Google Scholar]
  49. Snow, C.E. Academic language and the challenge of reading for learning about science. Science 2010, 328, 450–452. [Google Scholar] [CrossRef] [PubMed]
  50. Lange, I. Von ‘Schülerisch’ zu Bildungssprache. Übergänge zwischen Mündlichkeit und Schriftlichkeit im Konzept der Durchgängigen Sprachbildung. In Interkulturelle Pädagogik und Sprachliche Bildung; Fürstenau, S., Ed.; VS Verlag für Sozialwissenschaften: Wiesbaden, Germany, 2012; pp. 123–142. [Google Scholar]
  51. Mecheril, P.; Castro Varela, M.d.M.; Dirim, İ.; Kalpaka, A.; Melter, C. Migrationspädagogik; Beltz: Weinheim, Germany; Basel, Switzerland, 2010. [Google Scholar]
  52. Moore, F.M. Language in Science Education as a Gatekeeper to Learning, Teaching, and Professional Development. J. Sci. Teach. Educ. 2007, 18, 319–343. [Google Scholar] [CrossRef]
  53. Schleppegrell, M.J. Academic Language in Teaching and Learning. Elem. Sch. J. 2012, 112, 409–418. [Google Scholar] [CrossRef]
  54. Gogolin, I. “Bildungssprache”—The Importance of Teaching Language in Every School Subject. In Science Education Unlimited: Approaches to Equal Opportunities in Learning Science; Tajmel, T., Starl, K., Eds.; Waxmann: Münster, Germany, 2009; pp. 91–102. [Google Scholar]
  55. Kniffka, G. Scaffolding. Möglichkeiten, im Fachunterricht sprachliche Kompetenzen zu vermitteln [Scaffolding. Possibilities to impart linguistic competences in the subject]. In Grundlagen der Sprachdidaktik. Deutsch als Zweitsprache; [Basics of Language Education. German as a Second Language]; Kuchenreuther, M., Michalak, M., Eds.; Schneider Hohengehren: Baltmannsweiler, Germany, 2012; pp. 208–225. [Google Scholar]
  56. Phillips Galloway, E.; McClain, J.B.; Uccelli, P. Broadening the Lens on the Science of Reading: A Multifaceted Perspective on the Role of Academic Language in Text Understanding. Read. Res. Q. 2020, 55, S331–S345. [Google Scholar] [CrossRef]
  57. Prediger, S.; Wessel, L. Brauchen mehrsprachige Jugendliche eine andere fach- und sprachintegrierte Förderung als einsprachige? Z. Für Erzieh. 2018, 21, 361–382. [Google Scholar] [CrossRef]
  58. Tajmel, T.; Starl, K.; Schön, L.-H. Detect the Barriers and Leave Them Behind—Science Education in Culturally and Linguistically Diverse Classrooms. In Science Education Unlimited: Approaches to Equal Opportunities in Learning Science; Tajmel, T., Starl, K., Eds.; Waxmann: Münster, Germany, 2009; pp. 67–84. [Google Scholar]
  59. Markic, S. Chemistry Teachers’ Pedagogical Scientific Language Knowledge. In Research, Practice and Collaboration in Science Education, Proceedings of ESERA 2017; Finlayson, O.E., McLoughlin, E., Erduran, S., Childs, P., Eds.; Dublin City University: Dublin, Ireland, 2018; pp. 178–185. [Google Scholar]
  60. Markic, S. Heterogeneity—Challenge and/or Opportunity in Science Education. Sisyphus 2014, 2, 32–47. [Google Scholar]
  61. Mönch, C.; Markic, S. Science Teachers’ Pedagogical Scientific Language Knowledge—A Systematic Review. Educ. Sci. 2022, 12, 497. [Google Scholar] [CrossRef]
  62. Gogolin, I. Der monolinguale Habitus der multilingualen Schule; Waxmann: Münster, Germany, 1994. [Google Scholar]
  63. Gogolin, I. The”Monolingual Habitus” as the Common Feature in Teaching in the Language of the Majority in Different Countries. Per Ling. 1997, 13, 38–49. [Google Scholar] [CrossRef]
  64. Dirim, İ.; Springsits, B. “Wenn du ihn heute fragst: ‘Wie heißt das auf Ungarisch?’, will er’s nicht sagen.”—Zusammenhänge zwischen Sprache(n), Positionierung und Bildung. In Handeln in Organisationen der Migrationsgesellschaft; Mecheril, P., Rangger, M., Eds.; Springer Fachmedien: Wiesbaden, Germany, 2022; pp. 343–358. [Google Scholar]
  65. Gogolin, I. Stichwort: Mehrsprachigkeit. Z. Für Erzieh. 2010, 13, 529–547. [Google Scholar] [CrossRef]
  66. Mecheril, P.; Quehl, T. Sprache und Macht. Theoretische Facetten eines (migrations-)pädagogischen Zusammenhangs. In Die Macht der Sprachen: Englische Perspektiven auf die Mehrsprachige Schule; Mecheril, P., Quehl, T., Eds.; Waxmann: Münster, Germany, 2006; pp. 355–381. [Google Scholar]
  67. Lazarides, R.; Buchholz, J.; Rubach, C. Teacher Enthusiasm and Self-Efficacy, Student-Perceived Mastery Goal Orientation, and Student Motivation in Mathematics Classrooms. Teach. Teach. Educ. 2018, 69, 1–10. [Google Scholar] [CrossRef]
  68. Wigfield, A.; Eccles, J.S. Expectancy-Value Theory of Achievement Motivation. Contemp. Educ. Psychol. 2000, 25, 68–81. [Google Scholar] [CrossRef]
  69. Boone, W.J.; Staver, J.R.; Yale, M.S. Rasch Analysis in the Human Sciences; Springer Netherlands: Dordrecht, The Netherlands, 2014. [Google Scholar]
  70. Linacre, J.M. USCALE= the User-Scaled Value of 1 Logit = 1. Available online: https://winsteps.com/winman/uscale.htm (accessed on 13 July 2022).
  71. Linacre, J.M. User’s Guide to Winsteps®Ministeps Rasch-Model Computer Programs. Program Manual 5.2.4. Available online: https://www.winsteps.com/a/Winsteps-Manual.pdf (accessed on 13 July 2022).
  72. Boone, W.J.; Noltemeyer, A. Rasch Analysis: A Primer for School Psychology Researchers and Practitioners. Cogent Educ. 2017, 4, 1416898. [Google Scholar] [CrossRef]
  73. Wright, B.D.; Linacre, J.M. Reasonable Mean-Square Fit Values. Rasch Meas. Trans. 1994, 8, 370. [Google Scholar]
  74. Jüttner, M.; Boone, W.; Park, S.; Neuhaus, B.J. Development and Use of a Test Instrument to Measure Biology Teachers’ Content Knowledge (CK) and Pedagogical Content Knowledge (PCK). Educ. Assess. Evaluation Account 2013, 25, 45–67. [Google Scholar] [CrossRef]
  75. Reeves, T.D.; Marbach-Ad, G. Contemporary Test Validity in Theory and Practice: A Primer for Discipline-Based Education Researchers. CBE Life Sci. Educ. 2016, 15, rm1. [Google Scholar] [CrossRef]
  76. Wiggins, G.P.; McTighe, J. Understanding by Design; Association for Supervision and Curriculum Development: Alexandria, VA, USA, 2005. [Google Scholar]
  77. Aryadoust, S.V. Mapping Rasch-Based Measurement onto the Argument-Based Validity Framework. Rasch Meas. Trans. 2009, 23, 1192–1193. [Google Scholar]
  78. Boone, W.; Rogan, J. Rigour in Quantitative Analysis: The Promise of Rasch Analysis Techniques. Afr. J. Res. Math. Sci. Technol. Educ. 2005, 9, 25–38. [Google Scholar] [CrossRef]
  79. Planinic, M.; Boone, W.J.; Susac, A.; Ivanjek, L. Rasch Analysis in Physics Education Research: Why Measurement Matters. Phys. Rev. Phys. Educ. Res. 2019, 15, 020111. [Google Scholar] [CrossRef]
  80. Leisen, J. Handbuch Fortbildung Sprachförderung im Fach. Sprachsensibler Fachunterricht in der Praxis; Ernst Klett Sprachen: Stuttgart, Germany, 2017. [Google Scholar]
  81. Beese, M.; Kleinpaß, A.; Krämer, S.; Reschke, M.; Rzeha, S.; Wiethoff, M. Praxishandbuch Sprachbildung in Biologie: Sprachsensibel unterrichten—Sprache Fördern; Klett: Stuttgart, Germany, 2015. [Google Scholar]
  82. Behling, F.; Förtsch, C.; Neuhaus, B.J. Sprachsensibler Biologieunterricht—Förderung professioneller Handlungskompetenz und professioneller Wahrnehmung durch videogestützte live-Unterrichtsbeobachtung. Eine Projektbeschreibung. Z. Für Didakt. Der Nat. 2019, 25, 307–316. [Google Scholar] [CrossRef]
  83. Nitz, S.; Enzingmüller, C.; Prechtl, H.; Nerdel, C. Fachsprache im naturwissenschaftlichen Unterricht—Eine empirische Untersuchung zur Einstellung angehender Lehrkräfte. Unterrichtswissenschaft 2011, 39, 245–262. [Google Scholar]
  84. Eccles, J.S.; Adler, T.F.; Futterman, R.; Goff, S.B.; Kaczala, C.M.; Meece, J.L.; Midgley, C. Expectancies, Values, and Academic Behaviors. In Achievement and Achievement Motives. Psychological and Sociological Approaches; Spence, J.T., Ed.; W.H.Freeman: San Francisco, CA, USA, 1983; pp. 75–146. [Google Scholar]
  85. Förtsch, C.; Sczudlek, M.; Neuhaus, B.J. Kompetenzorientierung und Aufgabenkultur im Natur-und-Technik-Unterricht. Eine Videostudie. In Erkenntnisweg Biologiedidaktik 12; Krüger, D., Schmiemann, P., Möller, A., Dittmer, A., Zabel, J., Eds.; Universitätsdruckerei: Kassel, Germany, 2013; pp. 75–88. [Google Scholar]
  86. Hitlin, S.; Piliavin, J.A. Values: Reviving a Dormant Concept. Annu. Rev. Sociol. 2004, 30, 359–393. [Google Scholar] [CrossRef]
  87. Maio, G.R.; Olson, J.M. Values as Truisms: Evidence and Implications. J. Pers. Soc. Psychol. 1998, 74, 294–311. [Google Scholar] [CrossRef]
  88. Alwin, D.F. Trends in Parental Socialization Values: Detroit, 1958–1983. Am. J. Sociol. 1984, 90, 359–382. [Google Scholar] [CrossRef]
  89. Brady, L. Teacher Values and Relationship: Factors in Values Education. Aust. J. Teach. Educ. 2011, 36, 56–66. [Google Scholar] [CrossRef]
  90. Corrigan, D.; Smith, K. The Role of Values in Teaching and Learning Science. In Inclusive Pedagogy across the Curriculum; Deppeler, J.M., Loreman, T., Smith, R., Florian, L., Eds.; Emerald Group Publishing Limited: New Delhi, India, 2015; pp. 99–117. [Google Scholar] [CrossRef]
  91. Berger, J.-L.; Girardet, C.; Vaudroz, C.; Crahay, M. Teaching Experience, Teachers’ Beliefs, and Self-Reported Classroom Management Practices: A Coherent Network. SAGE Open 2018, 8. [Google Scholar] [CrossRef]
  92. Biesta, G.; Priestley, M.; Robinson, S. The Role of Beliefs in Teacher Agency. Teach. Teach. 2015, 21, 624–640. [Google Scholar] [CrossRef]
  93. Taylor, Z.W. Linguistic Hurdles Faced by English L2 Speakers Pursuing U.S. Higher Education: What the Research Tells Us and Pathways Forward. Essays Educ. 2021, 27, 4. [Google Scholar]
  94. Childs, P.E.; Ryan, M. LiSP: The Language in Science Project. In Research, Practice and Collaboration in Science Education. Proceedings of ESERA 2017; Finlayson, O.E., McLoughlin, E., Erduran, S., Childs, P., Eds.; Dublin City University: Dublin, Ireland, 2018; pp. 186–195. [Google Scholar]
  95. Markic, S.; Childs, P.E. Language and the Teaching and Learning of Chemistry. Chem. Educ. Res. Pract. 2016, 17, 434–438. [Google Scholar] [CrossRef]
  96. Behling, F.; Förtsch, C.; Neuhaus, B.J. Using the Refined Consensus Model of Pedagogical Content Knowledge to Improve Pre-Service Biology Teachers’ Lesson Planning. J. Sci. Teach. Educ. 2022, submitted.
  97. Kotzebue, L.v. Beliefs, Self-reported or Performance-Assessed TPACK: What Can Predict the Quality of Technology-Enhanced Biology Lesson Plans? J. Sci. Educ. Technol. 2022, 31, 570–582. [Google Scholar] [CrossRef]
  98. Linacre, J.M. Reliability and Separation of Measures. Available online: https://www.winsteps.com/winman/reliability.htm (accessed on 14 September 2022).
  99. Santagata, R.; Yeh, C. Learning to Teach Mathematics and to Analyze Teaching Effectiveness: Evidence from a Video- and Practice-Based Approach. J. Math. Teach. Educ. 2014, 17, 491–514. [Google Scholar] [CrossRef]
Education 12 00654 g001 550
Figure 1. The Refined Consensus Model of Pedagogical Content Knowledge (RCM) based on Carlson and Daehler [7] with the Plan–Teach–Reflect Cycle of ePCK in the centre: the white circles symbolise the assumed filters between the three realms of PCK.
Figure 1. The Refined Consensus Model of Pedagogical Content Knowledge (RCM) based on Carlson and Daehler [7] with the Plan–Teach–Reflect Cycle of ePCK in the centre: the white circles symbolise the assumed filters between the three realms of PCK.
Education 12 00654 g001
Education 12 00654 g002 550
Figure 2. Graphical illustration of hypotheses 1 & 2.
Figure 2. Graphical illustration of hypotheses 1 & 2.
Education 12 00654 g002
Education 12 00654 g003 550
Figure 3. Research design and procedure.
Figure 3. Research design and procedure.
Education 12 00654 g003
Education 12 00654 g004 550
Figure 4. Graphical illustration of the research findings.
Figure 4. Graphical illustration of the research findings.
Education 12 00654 g004
Table
Table 1. Summary of test instruments.
Table 1. Summary of test instruments.
VariableNumber of ItemsAll Item Infit MNSQAll Item Outfit MNSQItem ReliabilityPerson ReliabilityICC (Unjust)
pPCKN = 12<1.4<1.50.970.88ICC (59,59) = 0.91, p < 0.001
Professional ValuesN = 20<1.5<1.50.970.36-
Motivational OrientationsN = 36<1.5<1.50.930.89-
Table
Table 2. Summary of mean scores (pre- and post-test).
Table 2. Summary of mean scores (pre- and post-test).
VariableMean of Person Ability ScoreSDMinMax
GroupTreatmentControlTreatmentControlTreatmentControlTreatmentControl
pPCKpre47.3647.801.220.4443.9246.7848.4148.31
pPCKpost48.2547.810.481.4247.2042.5849.3152.83
Professional Valuespre51.9051.850.350.4451.5251.1752.8352.63
Professional Valuespost52.0051.850.490.4951.4150.8153.4352.67
Motivational Orientationspre48.9248.360.450.3548.1047.6149.5749.00
Motivational Orientationspost49.4949.470.670.8348.4547.7950.6351.28
Table
Table 3. Summary of intra-correlations between the measured variables (pre-test).
Table 3. Summary of intra-correlations between the measured variables (pre-test).
VariablepPCKpreProfessional ValuespreMotivational Orientationspre
pPCKpre1
Professional Valuespre0.271
Motivational Orientationspre−0.090.331
Table
Table 4. Summary of unpaired t-tests (pre-test).
Table 4. Summary of unpaired t-tests (pre-test).
VariablepPCKpreProfessional ValuespreMotivational Orientationspre
GroupTreatmentControlTreatmentControlTreatmentControl
tT(17.18) = 1.33T(26) = −0.35T(26) = −0.63
p0.100.730.001
d--1.37
95%CI[−0.2578, 1.1399][−0.3657, 0.2596][−0.8691, −0.2410]
Table
Table 5. Summary of mixed ANOVAs.
Table 5. Summary of mixed ANOVAs.
Hypothesis Dependent VariableFp (One-Tailed)Part. η2d
H1 Effect of time
H1apPCKF(1,28) = 3.510.040.110.70
H1bProfessional ValuesF(1,24) = 0.050.41--
H1cMotivational OrientationsF(1,23) = 29.68<0.0010.562.26
H2 Interaction effect
H2apPCKF(1,28) = 2.920.040.100.67
H2bProfessional ValuesF(1,24) = 0.470.25--
H2cMotivational OrientationsF(1,23) = 7.64<0.010.251.15
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Behling, F.; Förtsch, C.; Neuhaus, B.J. Using the Plan–Teach–Reflect Cycle of the Refined Consensus Model of PCK to Improve Pre-Service Biology Teachers’ Personal PCK as Well as Their Motivational Orientations. Educ. Sci. 2022, 12, 654. https://doi.org/10.3390/educsci12100654

AMA Style

Behling F, Förtsch C, Neuhaus BJ. Using the Plan–Teach–Reflect Cycle of the Refined Consensus Model of PCK to Improve Pre-Service Biology Teachers’ Personal PCK as Well as Their Motivational Orientations. Education Sciences. 2022; 12(10):654. https://doi.org/10.3390/educsci12100654

Chicago/Turabian Style

Behling, Franziska, Christian Förtsch, and Birgit J. Neuhaus. 2022. "Using the Plan–Teach–Reflect Cycle of the Refined Consensus Model of PCK to Improve Pre-Service Biology Teachers’ Personal PCK as Well as Their Motivational Orientations" Education Sciences 12, no. 10: 654. https://doi.org/10.3390/educsci12100654

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop