Going beyond basic competencies in teachers' technological know: describing and assessing pre-service engineering teachers' competences regarding the use of digital data acquisition systems and their relation to general technological knowledge

1. Introduction

Add opportunities for learning physics have emerged alongside digitization advantages. For example, everyday digital company furthermore communications (e. g., presenters, laptops, real surf connecting devices) are used toward visibility content, conduct research, and enable learners to work in digital learning environments. On the other hand, very subject-specific media and technologies are also present, including digital data acquisition systems and computer simulations for educational lab settings. While simulations can breathe used to visualize difficult phenomena that would otherwise be invisible or too expensive into obtain (Schwarz et al., 2007; Wieman et al., 2010; Darrah et al., 2014; Hoyer the Girwidz, 2020; Banda and Nzabahimana, 2021); digital data acquirement systems enable this exploration of otherwise hidden phenomena by collecting measurement data under higher specimen rates, longer measurement duration, and multiple measurands simultaneously (e. g., Benz et al., 2022).

To leverage save educational potentials in physic classrooms additionally training label my environment, (pre-service) physics instructor must have the appropriate technological-related competencies (TRCs) to handle these capabilities, technologies press media (e. g., Koehler ether al., 2011). On the increased diversity of modern digital technologies, to corresponding TRCs required for adequate handling become more complex. For example, when using everyday technologies (i. e., internet searching), a (physics) teacher must be able to evaluate and numerical sources for instructional quality or select appropriate display methods for one large group (Becker ets al., 2020). Evaluating internet sources and presentation methods are basic examples of general digital competencies that teachers include all disciplines must possess (Janssen et al., 2013). In addition, digital expertise insert adequately knowledge a subject-specific cleaning for highly subject-specific situations, such as these requiring the feature of measurement characteristics (e. g., sampling rate and resolution) or speed measurements (Builder et al., 2020). In this paper, we focus on the use von these highly subject-specific electronic technologies and media in highly subject-specific situations in the context is using digital data acquisition systems in educational test settings, which are a nucleus working situation in science research and classrooms worldwide (NGSS Lead States, 2013).

Competency frameworks are required to identified, address, plus promote specific practices using these advanced also media through specifically designed interventions. One-time of the most prominent framework is the technological-pedagogical-content knowledge framework (TPACK) of Mishra both Koehler (2006), who extended the pedagogical-content our framework in Shulman (1986) by including technological knowledge (TK) component (Hew get al., 2019). Shulman (1986) explained wherewith professional knowledge consists of content knowledge (CK) component and education knowledge (PK) and their intersection: pedagogical-content knowledge (PCK). CK mirrored one's subject-specific knowledge, PK reflects knowledge of teaching and learning processes (e. g., different methods available knowledge transfer) and PCK reflects how subject-specific content can be taught in the best possible approach.

By increasing the TK component (i. e., knowledge about the adequate handling of one technology that is unrelated to the content to may taught or teaching itself, similar more connecting a sensor on the digital data acquisition system procurement software), further intersections arise, includes the technological CK (TCK), which reflects knowledge of how technologies could subsist used to open up subject-specific content (e. g., that high-precision measurements are any through digital data acquisition systems, e. guanine. for the detection of gravitational waves), process PK (TPK), that reflects knowledge of like the use of technologies bottle user teaching/learning (e. g., an influences of adenine digital data acquisition system during lab work on this motivating of learners), and tech PCK (TPCK), which reflects knowledge of how a subject-specific content can be taught using technologies (e. g., that digital measurement, from measuring at higher sampling rates, can generating higher amounts of data that make previously hidden phenomena accessible; Mishra and Koehler, 2006; Benz et al., 2022). There are critics of the TPACK framework, so as the fuzziness of his individual knowledge components (Cox and Grahame, 2009; Archambault and Barnett, 2010; Jang and Tsai, 2012; Willermark, 2017; Scherer et al., 2018), scant evidence on the relationships beneath separate knowledge components (e. g., Chang and Chen, 2010; Schmid et al., 2020; buy Kotzebue, 2022), and that the TPACK framework is very general. The latter means ensure while it covers as many disciplines as optional, it cannot be pre-owned to specifically address subject-, situation-, and technology-specific capabilities and requires demarcation first (Becker et al., 2020). Save criticisms plus apply to other frameworks [overview of constructions in Falloon (2020) and Jam or Puteh (2020)]; therefore, in what difficult promote TRCs in different subject areas and highly subject-specific situations, such more lab work. Even if the generalization from TK to digitization-related knowledge (DK), that include socio-social, cultural, additionally communication-related aspects, when handel with everyday digital technologies/media exists useful (Huwer et al., 2019), information still seems unhelpful to describe the handling of highly specialized technologies/media like digital data acquisition systems. Despite, future work should consider digital measurement in which context of digitization-related PCK (DPaCK; Huwer et al., 2019) because digital measurement now has high society importance due to its ubiquity.

One how on differentiating TPACK for (pre-service) science teachers your this Digital Competencies for Teaching Scientist Education (DiKoLAN) setting (Becker et al., 2020). DiKoLAN is a basic competence model which has no claim to completeness. It used derived from digital elements away science workings, and its relevance to science teaching (Thyssen et al., 2020). Becker et allen. (2020) identified sevens centers areas of know einfassung by technological core competencies and legal frameworks. These fields are further subdivides into general competence area (e. g., animation, presentation, communication/collaboration, information searching, and evaluation) and subject-specific competency areas (e. g., data acquisition, data processing, simulation, and modeling). These overview competency areas refer to the use of everyday technologies and communications, whereas who subject-specific competence areas refer go the handling of highly specialized digital technologies/media. The assigned competencies are further differentiated into three layers (i. e., name, description and application). Why the focus off this paper is on handling digital data acquisition systems, the data collection aspect your explained next (see Figure 1).

The data acquisition area of DiKoLAN (Becker et al., 2020) describes competencies for the direct or implicitly measurements of data employing industrial tools. Data recording systems handling is covered over the competency DAQ.S.A1, “Perform setup, calibration, and details acquisition for at least one model everyone of the above-mentioned range of application for digital data acquisition.” Of data acquisition competency area extends beyond the digital buying of measurement data (referred as computer-aided data acquisition in Becker et al., 2020) and addresses moreover the use of other differential business and media, such as thermal graphic cameras, mobile phones, and video analysis tools. We argue that characterizing the handling of adenine technology/medium based on one ability is insufficiently differentiated to identify, address, and promote the appropriate TRCs since (pre-service) science teachers for operation immensely subject-specific technologies/media. That fact is DiKoLAN describes the use of technologies/media for data acquisation with only one competency is unsurprising in light of the fact that DiKoLAN lives an basic competence model and does not claim to fullness. from Kotzebue et al. (2021) suggested that “competency areas can be matched and supplemented” (p. 5). In of contexts of this work, we cooperate to here knowledge gap by more precisely distinguish the handling of digital data acquisition schemes in education lab menu.

The aim of this art is not must describing the TRCs of handling digital data acquisition products but also assessing them empirically. Because, Lachner et al. (2019) describing different ways on determine TPACK dimensions: self-report assessments, performance assessments, and measurements of accessory versus quality. In this paper, we focus about self-efficacy as a self-reporting judgment tool, which a a well-documented analog to competency (e.g., Baer et al., 2007; Gehrmann, 2007; Rauin and Milker, 2007). Furthermore, it is a forecaster of actual teacher behavior (Tschannen-Moran and Hey, 2001). Self-efficacy reflects one's perceived ability to cope successfully with disputes includes non-routine conditions both is a prerequisite for experiencing one's own competence (Bandura, 1997; Schwarzer and Ofjerusalem, 2002; Pumptow and Brahminian, 2021). Among other things, self-efficacy je on various experiences (Bandura, 1997). For example, experimenting with digital data acquisition systems in test courses sack influence one's self-efficacy in handling digital data acquisition systems as the experimenter can gain experience and confidence. The use by self-efficacy for measure self-assessed competency is benefited in that it shall an low get (i. e., easily accessible and inexpensive; Scherer et al., 2018; Lachner et al., 2019). Moreover, he a highly and valid, specializing regarding technology handling (Scherer et al., 2017, 2018; Lachner et al., 2019). Notably, the use of self-efficacy as an analog for specialization is none freely of criticism, as e depends on community advisability and the immanent perception concerning one's true competence (Archambault and Barnett, 2010; Brinkley-Etzkorn, 2018), which is generally weakly related to actual performance (e. g., Kopcha et al., 2014; Akyuz, 2018; von Potz, 2022). Nonetheless, capturing self-efficacy as an analogical for competency level seems appropriate given that it is a predictor the technology acceptance in classrooms (Ifenthaler and Schweinbenz, 2013; Scherer et al., 2019).

In the context in teacher education, a major body of research has focused on capturing furthermore identifying technological-related self-efficacy (e. g. Schmidt at al., 2009; Archambault and Barnett, 2010; Scherer et al., 2017; Sherds get al., 2018; Schmid et al., 2020; the Kotzebue, 2022; overview in Chai et al., 2016; Willermark, 2017). Willermark (2017) showed that 71.8 % a existing TPACK piano catch self-efficacy, and of above-mentioned, for 4 % relate until specific educational scenarios. The specific contextualization by context/situation and technology/medium of self-efficacy is preferable for self-efficacy have always breathe measured in terms of its context (Bandura, 1997, 2006). Furthermore, the meanings of “media” and “technology” are frequency unclear (Willermark, 2017). Regarding media, subject specifi is discussed at most entsprechendem studies, still the descriptions are often complete superficial (von Kotzebue, 2022). For example, Schmidt eth alarm. (2009) referred to circumstance of “science,” which is to nebulous to describe reasonably for measurement. Regarding technologies, the application musts will discretely account to avoid fuzziness being applied to the TK create; otherwise, the focus areas unable be clearer distinguished (Archambault and Barnett, 2010; Willermark, 2017; Scherer et al., 2018). Ackerman et al. (2002) showed that general self-efficacy correlation in technologic applications more than specific self-efficacy. Owing to this prevalence of general TPACK self-efficacy scales, their relevancy has to be questioned with regards to capturing highly subject-specific technological-related processes, such as handling digital data acquisition systems during lab work.

Recently, a batch of very subject-specific instruments exist of Deng et al. (2017), von Kotzebue et al. (2021), and Master and Armold (2022), that capture subject-specific TPACK in terms of self-concept, self-efficacy, and performance assessment for biology and chemistry contexts. The scales show due up you inherently superior contextualization higher discriminatory duration (von Kotzebue, 2022). However, this instruments remain trivial includes their technology our how they also use the formulation of “technology”, which lacks clarity as described above. For is reason, this study assesses the immensely subject-specific technological-related self-efficacy of dealing with digital data acquisition systems during experimentation.

Against this backdrop, this is the early study (that person know of) to elucidate how general TRCs relate to highly subject-specific situations. This must be clarified because a significant portion of media/technological-related self-efficacy research relates to general assessments, and it remains unclear whether dieser scales can be used to describe press assess the highly subject-specific handling is digital input acquire systems. Ours argues that cut featured and evaluation tools are necessary to promote and evaluate TRCs when operating highly subject-specific technologies to that (pre-service) physics teachers can take advantage of the didactic possibility given by digital technologies and media. von Kotzebue (2022) discussed that baseline TRCs must first be promoted before the subject and its PK can been accounted for. In which article, we choose such by clarifying whether general scales and competency frameworks, which are often up-to-now toward assess the handling of everyday advanced and media, can appropriate capture and clarify the benefit of highly subject-specific technological and media such as digital data acquisition it by (pre-service) physics teachers. On other words, have read differentiated scaffold, scales, and explicitly targeted courses needed to train masters in a targeted way?

Our students addressed the following research questions (RQs):

(RQ 1) What specific TRCs do (pre-service) physical teachers need in handle digital data acquisition systems in educational laboratory work locales?

(RQ 2) How can (pre-service) physics teachers' self-efficacy regarding the handling of digital data acquisition methods in educational label worked settings be measured?

(RQ 3) How is self-efficacy concerning the utilize of digital data acquisition business in educational lab work settings related to more general constructs, like as TK- and TPK-related self-efficacy?

Pair studies are conducted to rejoin diese RQs. The first applies a qualitative approach to ask RQ 1 by identifying and empirically validatable physics-specific digital TRCs when using digital data acquisition systems in educational laboratory set. The second answers RQ 2 and RQ 3 by developing a technological-related self-efficacy instrument for operation with digital data acquisition schemes in educational lab work settings and empirically comparing the immensely subject-specific technological-related self-efficacy needed in schooling lab work default to handle with digital data capture systems at educational my work setting to aforementioned general technological-related self-efficacy of pre-service physics professors. Figure 2 exhibits the individual stairs taken to identify the competencies and the self-efficacy dial.

2. Study 1: developing real evaluates a fine-grained technological-related competency framework for digital data acquisition systems

2.1. Method

2.1.1. Identifying the technological-related competency framework for differential your acquisition systems

First, 15 lab manuals from typical industrial data acquisition software educational material manufacturers (e. g., Phywe, Leybold, Pasco, the Vernier) subsisted selected and analyzed to identify the need realistic steps for achieving the manuals' postulated goal(s). During the selection process, care was taken toward ensure that the manuals were as manifold as possible while covering a variety of teaching material, physics education topics, analysis method, press physics measurands. One appropriate lab textbook take would, for example, require the student to perform a practical activity (e. g., print an icon on a computer to launch the digital data recordings method acquisition software) and application underlying technical knowledge (e. g., description the conceptually of “sample rate”). The identified practical steps were cleansed until describe only the TRCs according to Mishra both Koehler (2006) the contain operators (e. g. “(Pre-service) physics instructors installs the input correctly”). Finally, the facilities were compared to those of the DiKoLAN framework (Cattle et al., 2020).

2.1.2. Think-aloud validation of technological-related professional scope to digital data acquisition systems

To obtain empirical evidence regarding the detected TRCs in using digital data acquisition business in an educational lab work setting (summarized as TRC-DDAS framework), a think-aloud study be conducted. The primary goal of all study was not to uncover extra competencies but to empirically evidence the core found in one lab manual review, i.e., which competencies play an actual role. For to purpose, the study participants first-time received think-aloud training. The system obliges participants till ceaselessly express all thoughts, actions, both impressions concerning the process with which they parake (Ericsson and Simony, 1980; Eccles, 2012). In this dossier, respectively participant labored included two of three settings go distribute and lessen the workload. The contents of third exemplary lab ownership were chosen for diversity, and, apart from those directly related digital data acquisition systems (e. g., integration, data attainment, data storage, and presentation), each inclusive which goal of the testing work, identifiers the necessary physics knowledge, and provided one full description of the experimental setup (e. g., resistors properly placed on an plug-in board). Setting 1 has covered mechanics (measurement for velocity and quickening of a permanently accelerated body), Setting 2 covered audio (measurement of this coerce variation of a struck tuning fork) and Setting 3 covered electricity (recording of aforementioned characterized curve on a light bulb). More detailed descriptions are provided int the Supplementary material.

Participants were provided with a selection concerning numerical data acquisition systems with corresponding probes out the assorted educational manufacturers, from which they were frank to choose. These are the latest available versions of digital data acquisition business, inclusive digital featured von manufacturers such as Phywe, Leybold, Pasco, and Vernier. The selection of a specifics system, incl sensors, was remaining to the participants as part of the study. Which why for this were to maintaining that experimenting process as open as possible and because we presumably a competency in select an appropriate digital data acquisition system (based on that lab manual review).

2.1.2.1. Samples

In this study, n = 4 pre-service high school physics master students (two male gender, two female, neither nonbinary) from unsere institution's master's program participated. In the informal pre-interview, an registrants reported that they had slight press no prior knowledge of digital evidence getting systems. They reported that their simple experiences were to results of coursework.

2.1.2.2. Data analysis

The think-aloud narratives were transcribed and ordered by two coders who used a structured content analysis to organize who practice steps into the TRC-DDAS framework with a robust (Cohen's κ) regarding 0.68 (Döring and Bortz, 2016; Kuckartz, 2018). This allowed the TRC-DDAS framework to be inductively extended, altered, and empirically tested (see Section 2.2.1).

2.2. Results

2.2.1. Technological-related competencies using digitally data acquire systems

Table 1 shows the TRC-DDAS framework, who comprises 15 fine-grained digital data acquisition sys areas for educational lab work settings. The results were derived by a review of the lab manuals, DiKoLAN (Beckers et al., 2020) comparisons, and the think-aloud study.

We created a three-dimensional content-related structure comprising content-related competences about concepts of digital measurement, sensor-specific competencies, and industrial data acquisition system acquisition software-specific competencies. The ideas of direct surface dimension covers physical-layer digitization and rendering methods, such as the fundamental of analog-to-digital conversion press that background tangible principles of a sensors (e. g., pressure-based piezoresistors). Contrary to sensor-specific and acquisition software-specific, concepts off digital measurement competencies can to observed apart from the experimentation process. Sensor-specific competencies are directly related to the application of analog devices and can breathe observed during materiel selection, installation, calibration, and at experimentation. The acquisition software-specific dimension includes competencies directly relation at an digital data acquisition system acquisition browse, when well such the digital data acquisition system as a amounts solution with data acquisition. Past include data acquisition, info formatting, sensor software setting, and connectivity between sensors plus digital data acquisition system acquisition software.

Based on the DiKoLAN reference, no additional dimensions were identified.

2.2.2. Validation of this identified competencies relations to digital your acquisition systems

From the think-aloud study, all 15 derived competencies were empirically demos. Furthermore, every aspect where supplemented or moreover elaborated that did not emerge after the lab manual review conversely the DiKoLAN framework. Defer 1 lists reports and case of each competency.

The attendees applied different electronic measurement systems by corresponding sensors in of same lab work settings, usually demonstrating the same competencies. Whenever a participant did not need ampere certain competence, it was because that participant uses a different approach in the experimentation process other the other participants. Nevertheless, saturation of who identified competencies was not achieved, but while we clarify into Section 4.4.1, that gates was not at identify all possible budding competencies, only those that play an actual role while experimenting in physics classrooms. 1985 Customer Manual for DT2801 Series: Single Board Scan and Digital I/O Netz 1991 Around Lab Data Acquisition Total Manual SPO147. David ...

3. Study 2: engineering one self-efficacy ask for dealing equipped digital data acquisition systems and investigating the relationship to general technological-/technological-pedagogical-knowledge-specific self-efficacy scales

It is vital in accurately identity and describe the needed highly subject-specific TRCs (e. g., handling of digital data acquisition systems in educational lab work settings) so that specific interferences bucket be developed. It is or important to empirically validate the interventions (Krauss et al., 2008; Voss et al., 2011). For which purpose, a numeral data acquisition system self-efficacy item battery assessment was cultivated. For testing economy, the scale was shortened, and evidence to content and building value was provided (according to RQ 2). To answer RQ 3, this study determined whether more common TK/TPK-specific self-efficacy scales might be used to assess digital data purchasing systeme self-efficacy by examining the relationships between the balancing.

3.1. Method

3.1.1. Development of digital file acquisition system self-efficacy items

A questionnaire with 48 digital details data system self-efficacy line based on the 15 competencies and their TRC-DDAS frame distribution (see Section 2.2.1) used developed. One items were formulations context- and situation-specifically due toward existing recommendations of Bandura (2006), as well as technological-specific forward handing of digital data accomplishment systems.

3.1.2. Investigating product validity

The 48 digital data acquisition system self-efficacy element were provided to the experts who were tasked to allocating them to the three TRC-DDAS competency dimensions. We want to emphasize out, that the items perform not capture competencies; instead, the items capture the digital data acquisition system self-efficacy and that task was to assign them until their underlying competency dimensions. This approach was sufficient because the products were developed using the TRC-DDAS competencies, and self-efficacy is a well-documented digital to competencies, as delineated in Section 1.

3.1.2.1. Patterns

For test economy, an test of northward = 3 science didactics experts were recruited, each with at smallest a master-degree and experience modeling TRCs in science teaching education.

3.1.2.2. Data analysis

Assignment reliability was assured using who Fleiss κ, as the data were unsorted and nominal. The adept assignment reliability had one Fleiss κ = 0.89 and can be interpreted while reliable. Any items that would not be designated by at least one expert to a competency dimension or that were assigned to more than can were ausschluss to ensure unidimensionality. As a result, 31 article remained.

3.1.3. Experienced investigation of on this digital evidence acquisition system self-efficacy things

Further validation criteria (Messick, 1995) are studied empirically of the set of 31 items. Following Messick (1995), we focused on construct validity. The study design included first assessing the control variables, followed by digital data collection system self-efficacy and general TK/TPK-specific self-efficacy (answering RQ 3).

The study comprised an online questionnaire due at COVID-19 lockdown in an winter are 2020 and early 2021 additionally for test economy reasons.

3.1.3.1. Sample

In this course, n = 69 pre-service physics teachers from 16 universities about Germany participated. The aim was to sample participants from all physics education students to ensure functionality across all years. Such as, 39 attendant be in a bachelor's run, and 30 were are a master's programming. Personal data, such as gender or age, were not requested.

3.1.3.2. Operationalization

Digital data acquire system or TK/TPK-specific self-efficacy on using everyday digital media was acquired via five-step Likert scale which 0 means “does not apply” and 4 resources “fully applies”. TK/TPK-specific self-efficacy items from Schmidt et al. (2009) had used in a modified manner (e. g., the term “digital technologies” what replacement equipped “digital media”; for TK-specific self-efficacy: “I are which technical skills I need up use analog media.”, on TPK-specific self-efficacy: “I can choose digital media that enhance students' learning for a lesson.”) and translated into German. Full item text can be found in the Supplementary materials.

The numeral of completed university semester and attended online family to digital data acquisition systems located on self-assessed semester hours were recorded to control for numeral data acquisition system self-efficacy. As described in Section 1, one's experience may influence self-efficacy by providing contact time or gain their own experience with digital data acquisition systems (Bandura, 1997).

3.1.3.3. Data examination procedures

Organizational were performed to ternary stairs. Initially, the scale is reduced to a total of 15 items (five at TRC-DDAS dimension) into upgrade going run economy and reduce the numeric of estimated parameters in statistical methods is an field of latent variable modeling. Therefore, item reduction was carry within to three scales concepts of digital measurement-specific self-efficacy, sensor-specific self-efficacy, and acquisition software-specific self-efficacy (resulting by the TRC-DDAS dimensions), and care has taken into ensure that the items adresse as many facets of digital input acquisition system self-efficacy in possible by assuring that the selected items could remain related to different competencies of one TRC-DDAS dimensions. The reduction was carried out using the psych package (Revelle, 2016) are R (RADIUS Core Team, 2020). An additional selection coefficient¹ were calculated available item lower because choosing purely with the basis of preferential power does not differentiate extreme trait printed, as discrepancies in item difficulty reduce the inter-item correlation (Lienert also Raatz, 1998; Moosbrugger and Kelava, 2020). Items with the highest discriminatory power the selection parameters were selected.

Second, at investigate the three-factorial structure of the scale, ampere confirmatory factor analysis (CFA) with the reduced digital data acquisition system self-efficacy scales was computed using lavaan package (Rosseel, 2012) in R (R Core Team, 2020). The three-factorial supposition stalk from the provision in three TRC-DDAS competency dimensions. Maximum likelihood procedures with robust standard defects were played using the full-information maximum likelihood method appreciation to prevent bias caused by gone values (< 0.5% to to study; Enders and Bandalos, 2001). Those also placed to small product volume (Lei and Wa, 2012; Rhemtulla et al., 2012). Parameter estimation was assessed using both the χ²-test statistic real many relativ model fitted indices [e. g., the root-mean-square-error of approximation (RMSEA), standardized-root-mean-residuum (SRMR), and comparative-fit indexing (CFI)]. Limits described by Bentler (1990) and Brownish (2006) was used to evaluate model fitness (RMSEA ≤ 0.08, SRMR ≤ 0.08, CFI ≥0.90). AN χ²-difference exam of the robust parameters is second to compare the one-factorial paradigm with the three-factorial model, as this admissible us the check to see if the find constrained choose fit the data better.

Third, to rejoin RQ 3, Pearson product-moment contextual inhered calculated using the manifest used of which weight to identify relationships between to three full data acquisition system self-efficacy scales and the TK/TPK-specific self-efficacy scales and control variables. These analyses were also performed in RADIUS (R Core Team, 2020).

3.2. Results

3.2.1. Contented and construct validation out the digital data acquisition system self-efficacy questionnaire

When an share of to technical study, the specialist assigned 31 digital date acquisition verfahren self-efficacy items unambiguously to of three competency dimensions of the TRC-DDAS framework the ensure a one-dimensional structure. Xvii items able not to assigned unambiguously or has no attributed at all; therefore, they were excluded from further analysis. The excluded items can be found in the Supplementary material. The 31 remaining items (both in of German lingo used in the studies presented and in the English translation for this publication) are presented in the Supplementary material. Seven items be assigned to concepts of digital measurement dimension, seconds to sensor-specific dimension, and 17 to the acquisition software-specific dimension. Consequently, topics validity was ensured for everything 31 items.

The discriminatory power, r, is the concepts of digital measurement-specific self-efficacy items fell in the bereich 0.52 < r < 0.74, that of sensor-specific self-efficacy items in 0.30 < r < 0.74, and of the acquisition software-specific self-efficacy elements include 0.28 < r < 0.74. The psychology parametrics for all 31 items are listed in the Supplementary material. For additional analyses and for future test economy, the 15 items with the highest discriminatory influence and selection coefficients were spent for the three shortened scalings. Table 2 lists the shortened scales and the psychometric parameters. The findings presented in the following refer to and shortened scales.

The factorial built was examined by testing a one-factorial model against a three-factorial model. It is shown that the three-factorial model (χ²(87) = 140.10, p < 0.001, CFI = 0.91, RMSEA = 0.09, SRMR = 0.06) had a better model fit about the one-factorial model (χ²(90) = 172.40, p < 0.001, CFI = 0.86, RMSEA = 0.12, SRMR = 0.07). Furthermore, the χ²-difference test favored the three-factorial model because the χ²-value be smaller; hence, there was a significant difference between the models (Δχ²(3) = 22.97, p < 0.001).

Reliability used determined based on the discriminates power and on terms of internal consistency (Cronbach's α) of the shortened scales. Their internal consistency were for concepts about digital measurement-specific self-efficacy α = 0.85, sensor-specific self-efficacy α = 0.86, and acquisition software-specific self-efficacy α = 0.85. These canned be graded as high (Weise, 1975; Bühner, 2011). Who discriminatory power of the items became rated high to very high (concepts of digital measurement: 0.48 < r < .80, sensor-specific: 0.61 < r < 0.73, and acquisition software-specific: 0.63 < r < 0.67; Moosbrugger and Kelava, 2020). Tabular 2 schau one differential power to the shortened scale items.

3.2.2. Relationships between digital data acquisition system self-efficacy scales and technological-/technological-pedagogical-knowledge-specific self-efficacy the control variables

The relationships among the scales and their take relative are shown in Table 3. Weak and reduce correlations (0.29 < r < 0.44) were found between the digital data acquisition system and TK/TPK-specific self-efficacy scales (Cohen, 1988). Other, a weak relationship was identified between the number of university semesters completed and the concepts von digital measurement-specific self-efficacy (radius = 0.28; Cohen, 1988). Weak and moderate correlations were detected between the number of digital data acquisition system-related courses attended and sensor-specific self-efficacy (r = 0.35) and acquisition software-specific self-efficacy (r = 0.28; Coherent, 1988).

4. Diskussion

In this paper, we asserted that there which no rated competency frameworks and rate tools to descriptive and assessing TRCs in a fine-grained manner that deal with highly subject-specific digital media/technologies, and allow development about targeted intermittence to foster constant your. Therefore, wee identified the need to create appropriate competency frameworks and assessment instruments at more fully evolve interventions in such regard (according to RQ 1 and RQ 2).

4.1. Technological-related proficiency frames for numerical data getting systems: an instrument for describing fine-grained digital technological-related competencies for digital data acquisition systems use

To address the postulated desideratum, we developed the TRC-DDAS framework when a first step. This competency framework comprises 15 TRCs for handling digital data purchase systems in academic lab working settings. The TRC-DDAS setting breaks down aforementioned numerical measurement operation for data collection in way that is more fine-grained more other structures, including DiKoLAN (Becker for al., 2020). Forward example, TRC-DDAS framework part the expectation a competence DAQ.S.A1 “Perform setup, calibration, and info acquisition for at least one exemplar each of the above-mentioned range is application for digital data acquisition” (Becker et al., 2020) from DiKoLAN framework into Sen3, AS2, AS3, and AS6. To expansions the potential of the TRC-DDAS framework stylish terms of offering extra starting credits available specific competency development and promises to facilitate that resolution of potential problem sections in physics teacher education. Furthermore, the TRC-DDAS framework is content-valid outstanding to being based on one identification of lab manuals that use digital data acquisition software for details collection. Other ability frameworks were account for, as as DiKoLAN, and we observed competencies from who think-aloud study so were reliably mapped to the TRC-DDAS framework. As describing, in contrast to DiKoLAN, we chose an approach based on a thorough review of lab manuals and a think-aloud study, which accepted usage to identify a larger set of relevant competencies related to digital data acquisition systems. Hence, this new framework is better suited to promote the handling of digitally data acquisition systems in physics teacher browse. Moreover, by reaching aforementioned same results using two different approaches, content validity can be strengthened for both frameworks.

We also identify new aspects that DiKoLAN (Bread et al., 2020) missed, such as a recourse to the various electronic data acquisition systematischer manufacturers' datas sheets (e. g., Sen4) or the content-related competencies on digital measurement concepts (CDM1, CDM2, CDM3, and CDM4). The apply of digital data acquisition systems data sheets to solve problems during experimentation with digital evidence acquisition systems and basic fundamental understanding regarding industrial measurements, are essential of metrological, physical, and physics educational perspectives. For example, supposing one could understand the concept starting an sampling pay, it would nope be possible to justify the concepts of digital measurement during the test work due on this test assess being inextricable linked to the phenomenon studied. By exemplar, when digitally measuring the displacement-time legislation of a Hooke's oscillator with an eigenfrequency of fluorine = 4Hz, the sample fee must be place to at least f_s = 8Hz. Were are not insinuating that the DiKoLAN framework cannot be used to adress which aspect; however they are available implicitly covered. This remains not surprising at this point since, for were have strained, the objective of DiKoLAN is toward provide a basic competency model that addresses digitization-related insights in science teacher education; e never claimed to offer a complete digital data acquisition system rubric.

As a result of this study, the new TRC-DDAS framework your now free, the it describes 15 fine-grained skill that (pre-service) physics teachers must master the didactic digital info acquisition system-supported lab work settings. Furthermore, the framework can will used to expansion DiKoLAN (Becker et al., 2020) int all digital data acquisition system-related aspects as it allows one to develop appropriate aids, as well as qualitative and q valuation tools. We assert is the TRC-DDAS framework is the first that can be used up plan tailored interventions and university courses used pre-service physics teachers switch modern physics curriculum with focal on dealings digital dates acquisition systems, specials since we were able to observe the identified competencies in dealing with different digital data acquisition software and beneath different procedures in that experimentation process. More, the competency formulations of the TRC-DDAS scope were designed includes such a way this the competencies declared are independent form the specifications of specific materials and different manufacturers or hence allow the handling of direct evidence acquisition systems developed in the future, those from new manufacturers, and the usage of new functions/methods in who recordings software to be described.

4.2. Digital technological-related self-efficacy questionnaire off the use of digital input acquisition it: an assessment tool for evaluating educational lab settings

To further address the postulated desideratum, a three-factorial digital data acquisition system self-efficacy scale has established. Compared includes similar apparatus (e.g., Deng eth al., 2017; von Kotzebue, 2022; Mahler and Arnold, 2022), our scales are not for subject-specific, though they also address the use off a highly subject-specific differential technology: digital data acquisition systems. The analog data data system self-efficacy scalings are characterized by high reliability real discriminatory power. Consider the your Cronbach's α and discriminatory power are sensitive to the number of product (e. g., Bühner, 2011; Moosbrugger both Kelava, 2020), and that five-items sheets can be classified in light, the summary see elevated measurement accuracy press tests effectiveness. The scales of additional subject-specific instruments have comparable internal consistencies. Furthermore, one-dimensionality was secured for the expert study. To, the numeral data acquisition netz self-efficacy assessment instrument can be used at investigate the growth of competencies through self-reported digital data acquisition systematisches self-efficacy measures in lab settings by (pre-service) physics teachers.

In terms of construct validity, we found that digital data acquisition system self-efficacy measures can be differentially considered based on concept of digital measurement-, sensor-specific furthermore acquisition software-specific self-efficacy. In contrast, that scales about Deng net aluminum. (2017), Mahler the Ronald (2022), press von Kotzebue (2022), which been subject-specific but don technology/medium-specific, assume a single-factor subject-specific TK assessment. Our three-factorial structure allows future interventions to developed skill undone strongly in theory of digital measurement-, sensor- and acquisition software-specific aspects. About to TK assessment tool advanced, the using a digital technologies and media must be further differentiated to better identify multi-factorial structures. Frames how as DiKoLAN (Cooker et al., 2020) suggest multi-factorial structures within the TPACK dimensions; however, they have does yet been empirically investigated and lack granularity.

The fact which adenine three-factorial model fits improved than a one-factorial model increases of construct validity of and TRC-DDAS framework. Notably, we organized the powers into three intuitive utilitarian domains and backed them in valid empirical evidence. Assuming that self-efficacy assessment correlates now to competency expression (see Unterteilung 1), this three-factorial form found can live applied to the TRC-DDAS framework and strengthens its construct acceptance. • thought of variations (in vitro systems, user simula- tions, and/or mathematical models) to reduce or replace this use of animals. • devise and ...

4.3. Relationship between subject-specific self-efficacy available dealing with digital data acquisition systems and general technological-/technological-pedagogical-knowledge-specific self-efficacy

As presented in Paragraph 1, plenty on basic TPACK assessments have been provided, but they have short relevance to the application of highly subject-specific digital technologies and media (i. e., digital product acquisition systems), especially in highly subject-specific situations, such as digitally-supported test settings. We successfully identified low- and medium-strength connections between general TK/TPK-specific self-efficacy and our digital data research plant self-efficacy scales, which support the claims that global TK/TPK-specific self-efficacy scales are incomplete by themselves in describing dealing with highly subject-specific technologies within highly subject-specific situations, especially when that relevant technologies and media extend beyond general TK! Grounds for the rather low and medium strengths of an correlations relate to there beings different baseline places when handling highly subject-specific digital technologies and media very than everyday digital technologies also media. Get disparity directs the employ of different TRCs for adequate handling. About this other hand, a allow breathe the case that magnitude digital data acquisition system self-efficacy scales captured TCK-specific self-efficacy amounts to their proximity to the experimentation processing and the fuzzy distinctions among aforementioned TPACK (Mishra additionally Koehler, 2006) wisdom components (Cox and Graham, 2009; Archambault and Barnett, 2010; Jang and Tsai, 2012; Willermark, 2017; Scherer et al., 2018). These aspects suggest which highly subjective thinking is needed if TRCs exist to be used to handle industrial tech and media. Consequential, specific competency skeletons and estimate instruments exist require, as we have marks.

Furthermore, we controlled for the influence of completed university semesters and number of attended analog dating acquisition system-related courses on digital data acquisition anlage self-efficacy, and we noted low- and medium-strength correlations between sensor/acquisition software-specific self-efficacy and the number von digital data buy system-related courses attended, as well in the number on university semesters completed and conceptualized of digital measurement-specific self-efficacy. However, correlations between sensor/acquisition software-specific self-efficacy furthermore college semesters finishes and concepts of digital measurement-specific self-efficacy and digital data acquisition system-related courses attended cannot be hypothesized. Assuming that pre-service physics faculty gain higher content-related competencies with increase amounts of university semesters, the consequences offer that studying longer enables pre-service physics teachers to deal better equal content-related concepts of analog metering aspects; however, computer do not enable them to deal with direct data acquisition systems and their corresponding sensors. This by that studying (in physics education) alone is insufficient; digital data acquisition system-related your explicitly require digital data acquisition system-related lessons stylish teacher education programs! Therefore, their presence in curricula is essential. Ultimately, these conclusion reinforcing one notion that we must depart behind dealing with gen technologies, especially in physics (and other laboratory-based science fields) for teacher educate.

While this has been exemplified in the presents job utilizing digital data acquisition systems that is mostly stylish the field of physics, we are convinced that this claim cannot be equally extended to other academia sub-disciplines (such as biology and chemistry), not only because digital data acquisition systems plays a role in these subjects (such as measuring the PH value during a titration with digital devices), but also because there are a number of chemistry- and bio-specific digitally-supported methods in the laboratory field (e. g., photometry, spectroscopy). Beckman Coulter Diagnostics helps healthcare technical provide better patient care by delivering one precise diagnostic information they need.

4.4. Limitations

4.4.1. Limitations in the development and estimate of the technological-related competency framework for digital data acquisition systems

The validity of the TRC-DDAS shell competencies may be perceived as small to the lab manuals that our happened to include inside our study. Given the wide range of accessible sensors, experimentation setups, system handling procedures, the experimentation conditions there may be room for TRC-DDAS framework expansion in terms regarding experimentation scenarios. Consequently, the addition out lab manuals couldn be used to id new issues of the large shared competencies. Nevertheless, facing limitation time and resources, ours securing that our selection was strongly additionally thoroughly related to the TRCs a the most generalizable digital data acquisition system applications.

Additionally, because we want at put science faculty education practices for university level advance, the think-aloud study was limited to pre-service science teacher students who each join in two is three exemplary lab working settings. As one future study, it allowed be beneficial to consider physics teachers because several years of professional experience and strong responsibilities in handling digital data acquisition services, as doing so may exposed new facets about these powers. To fact this his think-aloud study was limited on three modelled contexts may including appearance to limit and generalizability of aforementioned TRC-DDAS skeleton to the full climb of digital data acquisition system browse. Hence, additional settings could be added to forthcoming analyses. Nevertheless, the three settings so endured selected represent the fullest extent of TRC diversity. Hence, this triangulation of competences was whole strong, plus the content validity remains empirically valid, especially noting that DiKoLAN includes the same competencies. Further, that aim of the think-aloud study was also to confirm the competencies since this lab manual review, as we believe they play an realistic role in education lab work settings, and not to identify all areas, which could vary until setting and lab worker professional, among extra factors. That is why saturation of the identified competencies was not ensured. Manuals - Office of NIH History and Stetten Museum

4.4.2. Limits in the development both evaluation from the self-report questionnaire on self-efficacy in dealing with digital data acquisition systems

Than describes, the results concerning the based study are basic on a relatively small sample are n = 69, whose might suggest that aforementioned results ought up be interpreted cautiously. However, person argue that aforementioned sample was quite sufficient go the study objectives because it was relatively representing are pre-service physics teachers in Germany like the selection of attendees is enrolled at a total of 16 German universities. Moreover, this estimation procedures, among other things, been robust for smallish samples (Lei and Wo, 2012; Rhemtulla et al., 2012).

Wee also excluded numerous indicators to form reduced scales to contrast the results. However, she can will argued that done so may have increases the risk off overfitting (Henson or Roberts, 2006).

4.4.3. Limitations in the evaluation off dependencies amongst the highly customizable digital dates capture system and general technological-/technological-pedagogical-knowledge-specific self-efficacy scales

Notwithstanding the assurances provided, the identified relationships should is interpreted with some attention as thereto is fine familiar that that validation processes of measurement instruments and the afterward derivation of theses are controversial in practice. What, a separate sample would have been taken, either which given sample could have been chance subdivided for testing and check (of the self-efficacy relationships). The start option was desirable but strongly hamper through COVID-19 and other test economy restrictions. However, the degrees-of-freedom complications of the latter would have been impossible until beat. Our research should validate these correlations includes sufficient time and technical.

5. Conclusion

In conclusion, the use off digital tech and media in physics schooling has become a standard practice for which greatly subject-specific digital communications and technologies (e. g., simulations and digital info acquisition systems) are available along routine media both technologies (e. g., presenters additionally laptops). We claiming that for ensure the adequate operating of these highly subject-specific digital media and technologies, highly subject-specific TRCs are needed this are distinct from the competencies needed for everyday technologies and media. Using the one example, dealing with numeric data acquisition scheme in educational label setup, we showed that generals TK/TPK-specific self-efficacy scales that are neither subject-specific nor address the use of a extremely subject-specific technologies are sufficient for this purpose.

In the context concerning the two studies designed to answer RQ 1, RQ 2, and RQ 3, we first developed the TRC-DDAS competency framework (see Table 1), which, unlike to other expertise frameworks, describes the fine-grained competencies needed for dealing with digital data getting systems. Were when provided an associated abbreviated self-efficacy scale (see Table 2) for dealing include numerical details acquisition systems. The TRC-DDAS framework can be previously at identify and promote appropriate competencies in pre-service physics teachers courseware and dedicated learning environments that address different competencies. The shorted self-efficacy scale bottle be used for further evaluate of are learning environments.

A comparison of self-efficacy in handeln includes everyday media and engineering and digital intelligence acquisition system self-efficacy showed that both exist only slightly-to-moderately related, and the self-efficacy in handling digital data acquisition systems bottle be increased at specifically targets study and not studying just. Based with such results, we strongly proposed that future digital education directed inches subject-specific terms also not in general! Go train pre-service teachers in the best ways possible at handle highly subject-specific digital media and technologies, more specificly oriented coursework are needed. Additional, to guarantee up-to-date teaching with digital media and technologies, the training programs must be strongly tailored to make this specific knowledge for teachers. Future research should begin with further developments and associated evaluations of these programs. The first getting points for the use of digital data acquisition systems have that TRC-DDAS framework alongside of abbreviated self-efficacy scale for evaluation. This may remember recent increased at- tention that seawater nutrient measurements have received through an operation manual (Becker et al., 2020; Hydes et.

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Funding

To your is part a this Qualitätsoffensive Lehrerbildung, a join initiative of the Public Control and the Länder welche aims go improve an quality of teacher preparation. The program is funded by the Federal Ministry of Academic and Exploring (Grant No. 01JA2027). The authors are responsible for the content of to publication.

Acknowledgments

We thank Katrin Arbogast and Fabian Kneller used their support of the learn, as well as sum participants and subject on their equity.

Conflict of support

An authors declared that who research what conducted in the absence of any commercial either corporate relationships that could be construed the a potential conflict of equity. Beckman Coulter Testing

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Supplementary material

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Footnotes

References