Search

During the last years, the “Great Online Transition” has brought to light large variation in teachers' readiness for online teaching and learning (OTL). Drawing from an international sample of 731 higher-education teachers, we examined gender differences in OTL readiness as a source of this variation. Currently, in the field of OTL, better evidence is needed to understand the associated dimensions and effects of gender on teachers’ experiences and perceptions of readiness, to provide better support and professional learning opportunities in transitioning to an online and blended practice. To provide such evidence, we first evaluated the measurement bias in the readiness measures and found support for strong gender invariance. Second, we quantified the gender differences in readiness levels: Women reported higher readiness for cognitive activation practices (d = +0.15); men reported higher self-efficacy in technological content knowledge (d = −0.20). These gender differences were small, varied across readiness constructs, and were due to a gender gap in OTL experience. Third, construct associations involving perceived institutional support were weaker for women. To improve the quality, robustness, and validity of the respective evidence, we argue that studying gender divides in OTL readiness needs to consider measurement bias, OTL experience, and construct associations.

In the present study, we tested the common assumption that teachers with more experience consider themselves better prepared for online teaching and learning (OTL). Utilizing the data from an international survey of 731 teachers in higher education at the beginning of the COVID-19 pandemic in 2020, we performed structural equation modeling to quantify the experience-readiness relationship. The survey contained an assessment of teachers’ OTL readiness which was measured by their perceptions of the institutional support, online teaching presence, and TPACK self-efficacy. In contrast to the linearity assumption “the more experienced, the better prepared”, we found robust evidence for a curvilinear relationship. Teachers’ readiness for OTL increased first and then decreased with more experience—this applied especially to the self-efficacy dimension of readiness. Further analyses suggested that the experience-readiness relationship does not only exist at the level of aggregated constructs but also at the level of indicators, that is, specific areas of knowledge, teaching, and support. We argue that both novice and experienced teachers in higher education could benefit from experience-appropriate, pedagogical, and content-related support programs for OTL.

Meta-analyses and international large-scale assessments (ILSA) are key sources for informing educational policy, research, and practice. While many critical research questions could be addressed by drawing evidence from both of these sources, meta-analysts seldom integrate ILSAs, and the current integration practices lack methodological guidance. The aim of this methodological review is therefore to synthesize and illustrate the principles and practices of including ILSA data in meta-analyses. Specifically, we (a) review systematically whether and how existing meta-analyses included ILSA data; (b) present four inclusion approaches (i.e., analytic steps, potential, challenges); and (c) illustrate the application of these approaches. Seeing the need for meta-analyses on educational inequalities, we situated the review and illustration in the context of gender differences and socioeconomic gaps in student achievement. Ultimately, we propose an analytic framework outlining the steps meta-analysts could take to utilize the potential and address the challenges of ILSA data for meta-analyses in education.

Computer coding—an activity that involves the creation, modification, and implementation of computer code and exposes students to computational thinking—is an integral part of today's education in science, technology, engineering, and mathematics (STEM) (Grover and Pea, 2013). As technology is advancing, coding is becoming a necessary process and much-needed skill to solve complex scientific problems efficiently and reproducibly, ultimately elevating the careers of those who master the skill. With many countries around the world launching coding initiatives and integrating computational thinking into the curricula of higher education, secondary education, primary education, and kindergarten, the question arises, what lies behind this enthusiasm for learning to code? Part of the reasoning is that learning to code may ultimately aid students' learning and acquiring of skills in domains other than coding. Researchers, policy-makers, and leaders in the field of computer science and education have made ample use of this argument to attract students into computer science, bring to attention the need for skilled programmers, and make coding compulsory for students. Bill Gates once stated that “[l]earning to write programs stretches your mind, and helps you think better, creates a way of thinking about things that I think is helpful in all domains” (2013). Similar to the claims surrounding chess instruction, learning Latin, video gaming, and brain training (Sala and Gobet, 2017), this so-called “transfer effect” assumes that students learn a set of skills during coding instruction that are also relevant for solving problems in mathematics, science, and other contexts. Despite this assumption and the claims surrounding transfer effects, the evidence backing them seems to stand on shaky legs—a recently published paper even claimed that such evidence does not exist at all (Denning, 2017), yet without reviewing the extant body of empirical studies on the matter. Moreover, simply teaching coding does not ensure that students are able to transfer the knowledge and skills they have gained to other situations and contexts—in fact, instruction needs to be designed for fostering this transfer (Grover and Pea, 2018). In this opinion paper, we (a) argue that learning to code involves thinking processes similar to those in other domains, such as mathematical modeling and creative problem solving, (b) highlight the empirical evidence on the cognitive benefits of learning computer coding that has bearing on this long-standing debate, and (c) describe several criteria for documenting these benefits (i.e., transfer effects). Despite the positive evidence suggesting that these benefits may exist, we argue that the transfer debate has not yet to be settled.

This study aims at investigating the profiles of teacher educators in order to explore their ability to prepare preservice teachers for technology integration in education. Specifically, the current study examines whether teacher educators can be grouped on the basis of their attitudes toward ICT (in education), their ICT self‐efficacy to design ICT‐rich learning environments, their competencies to use ICT in their teaching practice and the strategies they use to prepare preservice teachers for technology integration. These strategies are included in the SQD (Synthesis of Qualitative Data) model and comprise: (1) teacher educators as role models, (2) reflecting on the role of technology in education, (3) learning how to use technology by design, (4) collaboration with peers, (5) scaffolding authentic technology experiences and (6) providing continuous feedback. Data were collected from a sample of 284 teacher educators in Flanders, the Dutch‐speaking part of Belgium, and submitted to latent profile analysis. The added value of the current study lies in the account of how SQD strategies and a typical set of determinants of ICT integration can be associated within teacher educators' profile. Based on the profiles emerging from this study, teacher training institutions should consider their teacher educators to be gatekeepers when preparing future generations of teachers for the learning environments of the twenty‐first century. In the discussion section, the implications for practice and future research are discussed. [ABSTRACT FROM AUTHOR]

The extent to which teachers adopt technology in their teaching practice has long been in the focus of research. Indeed, a plethora of models exist explaining influential factors and mechanisms of technology use in classrooms, one of which—the Technology Acceptance Model (TAM) and versions thereof—has dominated the field. Although consensus exists about which factors in the TAM might predict teachers’ technology adoption, the current field abounds in some controversies and inconsistent findings. This meta-analysis seeks to clarify some of these issues by combining meta-analysis with structural equation modeling approaches. Specifically, we synthesized 124 correlation matrices from 114 empirical TAM studies (N = 34,357 teachers) and tested the fit of the TAM and its versions. Overall, the TAM explains technology acceptance well; yet, the role of certain key constructs and the importance of external variables contrast some existing beliefs about the TAM. Implications for research and practice are discussed.

The objective of this article is twofold: (i) to provide a valid and reliable instrument to measure teachers' digital competence on the basis of the European Framework for the Digital Competence of Educators (also referred to as DigCompEdu) and (ii) to examine the relation between in-service teachers' digital competence and personal and contextual factors. For this purpose, a study was conducted with 1071 in-service teachers. The instrument was validated with respect to its factorial structure, and the relation between teachers' digital competence and personal and contextual factors was analysed using three different analyses: (i) simple linear regression, (ii) multiple linear regression, and (iii) machine learning. The results show that all the analyses conducted confirm the prevalence of personal factors over contextual ones, as well as their stronger predictive capacity. Gender and age differences were found, but the number of tools used for teaching and learning was the strongest predictor of teachers' digital competence, followed by ease of use, confidence in using digital technology, and openness to new technology. The article shows the soundness of the DigCompEdu framework and provides knowledge that could benefit teacher training programmes and inform policy and practice.

In a very short time, secondary school education across the globe transitioned to online learning and teaching, in response to the Covid-19 pandemic. This study aims at identifying teacher profiles in secondary education to better understand perceptions of both individual and institutional readiness to transition to online teaching. To do this, the current study grouped teachers on the basis of their TPACK self-efficacy beliefs, online presence and perceived institutional support for online teaching. To date, data have been collected from teachers (N = 222) from 20 countries. The data were submitted to latent profile analysis to identify readiness profiles. The added value of the current study lies in the combined view of individual and institutional readiness and the uniqueness of the dataset. It provides a large-scale international perspective and a wide range of possible experiences. Findings inform how education institutions can personalise and support transitions to online teaching.

In the literature on mission-oriented innovation supply side and tech-oriented approaches have been complemented by broader and more inclusive societal approaches. Here, it is highlighted that both directionality and broad anchoring of diverse stakeholders across private, public, and civic domains are key to successful implementation. Still, it is unclear how these dimensions relate and unfold in practice. Using digital literacy in education as an example of mission-oriented innovation, this paper investigates what prerequisites and capabilities are needed to envision and govern such processes. Based upon a case study of innovative teaching practices in twenty-five classes at ten primary schools in Norway, the paper finds that the motivation, dedication, and engagement of the teachers is not primarily related to the digital technologies themselves, but to the professional and pedagogical anchoring of the digital teaching tools. The mobilization of the professionalism of the teachers is enabled by a process of balanced empowerment.

The COVID-19 pandemic has forced a shift to online teaching and learning (OTL) in colleges and universities across the globe, requiring teachers to adapt their teaching in a very short time—independent of whether they were prepared. Drawing from an international sample of N = 739 higher education teachers in 58 countries, the present study sheds light on teachers' readiness for OTL at the time of the pandemic by (a) identifying teacher profiles based on a set of key dimensions of readiness; (b) explaining profile membership by individual teacher characteristics, contextual aspects of the shift to OTL, and country-level indicators representing educational innovation and cultural orientation. We conducted latent profile analysis and identified three teacher profiles with consistently high or low readiness or an inconsistent readiness profile—hence, teachers in higher education are not a homogeneous group. Importantly, key individual and contextual variables, such as teachers’ gender and prior OTL experience, the context of the OTL shift, the innovation potential in education, and cultural orientation, explained profile membership. We discuss these findings with respect to the nature of the profiles, how they can be understood with respect to key determinants, and their implications for OTL in higher education.

This meta-analysis maps the evidence on the effectiveness of instructional approaches and conditions for learning computer programming under three study conditions: (a) Studies focusing on the effectiveness of programming interventions per se, (b) studies focusing on the effectiveness of visualization and physicality, and (c) studies focusing on the effectiveness of dominant instructional approaches. Utilizing the data from 139 interventions and 375 effect sizes, we found (a) a strong effect of learning computer programming per se (Hedges’ g ‾ = 0.81, 95% CI [0.42, 1.21]), (b) moderate to large effect sizes of visualization ( g ‾ = 0.44, 95% CI [0.29, 0.58]) and physicality interventions ( g ‾ = 0.72, 95% CI [0.23, 1.21]), and (c) moderate to large effect sizes for studies focusing on dominant instructional approaches ( g ‾ s = 0.49–1.02). Moderator analyses indicated that the effect sizes differed only marginally between the instructional approaches and conditions—however, collaboration in metacognition instruction, problem solving instruction outside of regular lessons, short-term interventions focusing on physicality, and interventions focusing on visualization through Scratch were especially effective. Our meta-analysis synthesizes the existing research evidence on the effectiveness of computer programming instruction and, ultimately, provides references with which the effects of future studies could be compared.

Technology acceptance has been widely discussed and examined in educational contexts. Despite the variety of models and measures describing teachers' technology acceptance, two key assumptions persist in the existing body of literature: First, the technology acceptance construct can be represented by a set of diverse, yet correlated attitudes and beliefs. Second, the effects of technology acceptance on the intentions to use technology and technology use—two commonly studied outcome variables—follow a cascade. The existing evidence backing these assumptions is, however, diverse, as the considerable between-study variation in the relations between the technology acceptance and outcome variables shows. This variation remained largely unexplained, and the present study offers an explanation from the perspective of construct validity. Analyzing a large meta-analytic sample (N = 37211 teachers) obtained from a previous meta-analysis, we synthesized the correlations among measures of teachers' technology acceptance and found support for the existence of a common trait that underlies all technology acceptance variables. This finding remained even after distinguishing between different teacher samples (i.e., pre-vs. in-service teachers) and types of technology (i.e., technology in general vs. specific technologies). There was no convincing evidence for the hypothesized cascade of effects, due to a weak and insignificant link between usage intentions and technology use. Our findings provide evidence for the representation of teachers' technology acceptance as a single latent variable and consequently offer a way to describe its relations to usage intentions and technology use without compromising the validity of the inferences drawn from them.

Although integrating technologies for teaching has received much attention, research demonstrated that teachers rarely use technologies likely because of low levels of technology-related motivation. Theories on teacher motivation such as Expectancy-Value Theory and Technology Acceptance models differ in how they conceive the influence of motivation on technology integration. To investigate these conflicting assumptions, we conducted a survey study within one-to-one technology-enhanced schools with N = 524 in-service teachers. Findings from structural equation modeling showed that rather than being mutually exclusive, the two perspectives should be integrated to inform research and practitioners about the implication of teacher motivation for technology integration.

The present investigation aims to fill some of the gaps revealed in the literature regarding the limited access to more advanced and novel assessment instruments for measuring students' ICT literacy. In particular, this study outlines the adaption, further development, and validation of the Learning in Digital NetworksICT literacy (LDN-ICT) test. The LDN-ICT test comprises an online performance-based assessment in which real-time student-student collaboration is facilitated through two different platforms (i.e., GoogleDocs and chat). The test attempts to measure students ability in handling digital information, to communicate and collaborate during problem solving. The data are derived from 144 students in grade 9 analyzed using item response theory models (unidimensional and multidimensional Rasch models). The appropriateness of the models was evaluated by examining the item fit statistics. To gather validity evidence for the test, we investigated the differential item functioning of the individual items and correlations with other constructs (e.g., self-efficacy, collective efficacy, perceived usefulness and academic aspirations). Our results supported the hypothesized structure of LDN-ICT as comprising four dimensions. No significant differences across gender groups were identified. In support of existing research, we found positive relations to self-efficacy, academic aspirations, and socio-economic background. In sum, our results provide evidence for the reliability and validity of the test. Further refinements and the future use of the test are discussed. The Learning in Digital Networks (LDN-ICT) test is comprised of multiple dimensions.Multidimensional Rasch model shows better fit than Unidimensional Rasch model.Evidence for reliability and validity of the LDN-ICT test is established.LDN-ICT is positively related to students' self-efficacy and academic aspirations.Differences in LDN-ICT across socio-economic status exit, yet not across gender.

This article has been accepted for publication and undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process, which may lead to differences between this version and the Version of Record. This article is protected by copyright. This meta-analysis synthesized the relation between measures of socioeconomic status (SES) and students' information and communication technology (ICT) literacy—a skillset that has found its way in educational curricula. Using three-level random-effects modeling across 32 independent K-12 student samples that provided 75 correlation coefficients, we identified a positive, significant, and small correlation, = 0.214, 95% CI [0.184, 0.244]. This correlation varied between studies and was moderated by the type of SES measure, the type of ICT literacy assessment, the broad categories of ICT skills assessed, the assessment of test fairness, and the sampling procedure employed. The findings of this meta-analysis suggest that students’ ICT literacy differs between socioeconomic status groups, thus pointing to a gap in the domain of ICT. However, the relation between SES and ICT literacy was weaker than those reported in other educational domains, such as mathematics and reading. Carefully designed studies and measures for which a validity argument has been crafted are needed when studying achievement gaps in the domain of ICT in future studies.

Does computer programming teach students how to think? Learning to program computers has gained considerable popularity, and educational systems around the world are encouraging students in schools and even children in kindergartens to engage in programming activities. This popularity is based on the claim that learning computer programming improves cognitive skills, including creativity, reasoning, and mathematical skills. In this meta-analysis, we tested this claim performing a 3-level, random-effects meta-analysis on a sample of 105 studies and 539 effect sizes. We found evidence for a moderate, overall transfer effect (g = 0.49, 95% CI [0.37, 0.61]) and identified a strong effect for near transfer (g = 0.75, 95% CI [0.39, 1.11]) and a moderate effect for far transfer (g = 0.47, 95% CI [0.35, 0.59]). Positive transfer to situations that required creative thinking, mathematical skills, and metacognition, followed by spatial skills and reasoning existed. School achievement and literacy, however, benefited the least from learning to program. Moderator analyses revealed significantly larger transfer effects for studies with untreated control groups than those with treated (active) control groups. Moreover, published studies exhibited larger effects than gray literature. These findings shed light on the cognitive benefits associated with learning computer programming and contribute to the current debate surrounding the conceptualization of computer programming as a form of problem solving. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

The study of gender differences in academic achievement has been one of the core topics in education, especially because it may uncover possible gaps and inequalities in certain domains. Whereas these differences have largely been examined in traditional domains, such as mathematics, reading, and science, the existing body of empirical studies in the domain of ICT literacy is considerably smaller, yet abounds in diverse findings. One of the persistent findings however is that boys consider their ICT literacy to be higher than that of girls. This meta-analysis tests whether the same pattern holds for students’ actual performance on ICT literacy tasks, as measured by performance-based assessments. In total, 46 effect sizes were extracted from 23 empirical studies using a random-effects model. Overall, the gender differences in ICT literacy were significant, positive, and favored girls (g = + 0.12, 95 % CI = [0.08, 0.16]). This effect varied between studies, and moderation analyses indicated that the grade level students were taught at moderated its magnitude—effect sizes were larger in primary school as compared to secondary school. In conclusion, our findings contrast those obtained from previous meta-analyses that were based on self-reported ICT literacy and suggest that the ICT gender gap may not be as severe as it had been claimed to be.

The main aim of this two-step mixed-method study was to explore the effectiveness of the strategies used to prepare pre-service teachers for technological pedagogical content knowledge (TPACK). Specifically, we focused on the strategies included in the synthesis of qualitative evidence (SQD) model: (1) using teacher educators as role models, (2) reflecting on the role of technology in education, (3) learning how to use technology by design, (4) collaboration with peers, (5) scaffolding authentic technology experiences, and (6) providing continuous feedback. To explore the relation between the perceived occurrences of the SQD-strategies and TPACK (controlled for pre-service teachers’ general attitudes towards technology), survey data were collected from a sample of 688 final-year pre-service teachers in Belgium. In a next step, 16 telephone interviews and 6 in-depth interviews were conducted to gain a more in-depth insight into the nature of the 6 strategies and their influences on TPACK. The quantitative analyses indicated positive correlations between the SQD-strategies and TPACK, controlled for general attitudes towards technology. The findings from the qualitative analyses showed that teachers acknowledged the importance of the six strategies. However, the respondents emphasized that some of the six strategies are often underutilized. Based on the quantitative and qualitative results, the discussion provides recommendations to improve the potential of pre-service training to enhance future teachers’ TPACK.

This study systematically reviews literature on assessment instruments of primary and secondary school students' ICT literacy. It has three objectives: (1) Describe the development and characteristics of the assessments; (2) Present a synthesis of the facets of ICT literacy measured; and (3) Investigate to what extent information about reliability and validity is provided. A total of 38 tests reported in 66 studies were included. The results indicate that most of the tests target lower secondary students, comprise multiple-choice item designs, and are evaluated by quantitative methodology. The majority of the tests measure facets such as searching, retrieving, and evaluating digital information, and technical skills. In particular, the access to tests measuring digital communication, collaboration, safety, and problem solving is limited. This review demonstrates that an adequate norm for documenting and reporting test quality is lacking. Our findings point to potential future directions in developing and reporting assessments of ICT literacy.

The aim of this study is to validate an instrument measuring students’ academic behavioral skills and engagement—skills identified as vital for student achievement. We inspect the reliability and validity of the survey with respect to item fit, factorial structure, relations with academic performance, and the fairness of the items across student groups. The fairness analyses are critical to making valid comparisons between groups and across countries. Data comprising 8520 grade 10 students from four countries were analysed using item response theory. We found that both scales were multidimensional, acted fairly across students’ gender, country, immigrant-, and socio-economic background (after removing four items), and were positively and significantly correlated with self-reported and performance-based academic performance.

Modern technology permeates almost every area in society and thus necessitates the development of new skillsets--including computer coding. Many leaders around the world consequently encourage students to learn to code, as this may help them to develop other skills, including problem solving, reasoning, and numeracy. The current study, based on a meta-analysis, puts to test this largely accepted claim that learning how to code improves other cognitive skills. We identified 105 relevant studies that examined the transfer of coding skills to other cognitive skills, such as reasoning, problem solving, creativity, literacy, and numeracy. These studies provided more than 150 effect sizes and followed experimental and quasi-experimental designs across all educational levels. A three-level random-effects model was specified to the resultant dataset to summarize the transfer effects. Hedges' g formed the basis for this modelling approach. The aggregated size of the transfer effects--independent of the context of transfer--was positive and mediocre (g = 0.49, 95% CI = [0.37, 0.61]), and showed considerable variation within and between studies. At the same time, this effect differed across transfer contexts--for skills closer to computer coding, effects were larger (near transfer) than for skills that overlap only marginally with coding (far transfer). Moreover, the purpose of coding moderated the overall effects. Our response to the question whether learning to code improves other cognitive skills is positive: Indeed, positive transfer effects can be detected. Nevertheless, learning to code has differential rather than uniform effects on other cognitive skills.

A large body of literature suggests that attitudes toward technology and its educational use are important determinants of technology acceptance and integration in classrooms. At the same time, teachers' Technological, Pedagogical, and Content Knowledge (TPACK) facilitates the meaningful use of technology for educational purposes. Overall, attitudes toward technology and TPACK play a critical role for technology integration and have been in the focus of many empirical studies. Albeit the attention that has been paid to these two concepts, their relation has not been fully understood. The present study contributes to the advancement of this understanding by examining the relations between three core technology attitudes (i.e., general attitudes towards ICT, attitudes towards ICT in education, and ease of use) and TPACK self-efficacy beliefs, based on a sample of N = 688 Flemish pre-service teachers in 18 teacher-training institutions. Using a variety of structural equation modeling approaches, we describe the TPACK-attitudes relations from multiple perspectives and present a substantive-methodological synergism. The analyses revealed that the attitudes toward technology and TPACK self-beliefs were positively related; yet, differences across the attitudes and TPACK dimensions existed, pointing to the delineation of general and educational perspectives on the use of ICT.

Studies on teachers' acceptance and use of information and communication technology (ICT) have revealed perceived usefulness to be a crucial determinant for integrating ICT in classrooms. In consequence, the present study focuses on teachers' perceived usefulness of ICT for teaching and learning and is aimed at describing its structure and relations to self-efficacy, ICT use, and teachers' age. By means of Bayesian analysis, we specified confirmatory factor-analytic and structural equation models to a large-scale data set of N?=?1190 Norwegian teachers. Our results supported the hypothesized four-factor structure of teachers' perceived usefulness of ICT, signifying different facets of ICT-related teaching goals in classrooms. Moreover, it was possible to disentangle general and specific components of the construct in nested factor models. In support of existing research, we found positive relations to self-efficacy and ICT use, but a negative relation to teachers' age. Our study provides evidence on a multidimensional conceptualization of teachers' perceived usefulness of ICT for teaching and learning, and verifies the relations to teacher-related characteristics. Implications for the measurement and modeling of the construct, and future research directions are discussed. Teachers' perceived usefulness of ICT for teaching and learning is multifaceted.A general factor and specific factors can be distinguished.Bayesian models with cross-loadings represent the structure of the construct.Perceived usefulness is positively related to self-efficacy and ICT use.Perceived usefulness is negatively related to teachers' age.

In large-scale assessments such as the PISA study, there is a current shift from traditional paper-and-pencil towards computer-based assessments of students' literacy in reading, math, and science. Thus, research has focused on examining the comparability of test scores and motivational factors across the different assessment types. However, it is currently unclear whether the negative effect of school-average ability on students' individual self-concept (i.e., the Big-Fish-Little-Pond Effect, BFLPE) is also robust against the shift in assessments. In the present investigation, we consequently evaluate the relations between math self-concept, school-average ability, and the type of assessment. Based on the Norwegian PISA 2012 data set (N?=?4686), we employed multilevel structural equation modeling and found that (a) the BFLPE existed for both assessments with a slightly higher effect size for the computer-based assessment; (b) math anxiety moderated the BFLPE, whereas self-efficacy, the availability and use of information and communication technology (ICT) did not. Our results support the robustness of the BFLPE across the different assessments of mathematical literacy and point out that computer-based assessments involve similar social comparisons as traditional paper-and-pencil tests. Students' self-concept is negatively related to school-average achievement.The BFLPE is robust against the type of assessment (paper-vs. computer-based).Math anxiety intensifies the BFLPE.Self-efficacy and ICT-related constructs do not moderate the BFLPE.Social comparisons among students are involved in computer-based assessments.

Collaborative problem solving (ColPS) skills are considered crucial to succeed in work, education, and life in a knowledge-rich society. Nevertheless, research on the assessment of ColPS is at its initial stage; specifically, assessments of synchronous student-student ColPS in digital environments have been scarcely investigated, and there is an ample need for valid and reliable assessments to measure ColPS. The present study attempts to fill this gap by proposing a novel ColPS task and investigating students' ColPS skills with the help of think-aloud protocols while they were taking an online performance-based test. The task was developed on the basis of a ColPS framework, and principles emphasized in the research literature on students’ interaction, collaboration, and problem solving were implemented. A real-world problem mimicking a common teaching and learning situation formed the context of this task. The empirical evidence obtained from the think-aloud protocols of eleven Norwegian students displayed the strengths and weaknesses of the task, and strengthened the feasibility to assess ColPS. Implications for the future design of ColPS tasks are discussed.

The Technological, Pedagogical, and Content Knowledge (TPACK) framework – a framework which proposes a set of knowledge domains that are essential for effective teaching with technology – has gained considerable attention in the domain of education and technology. With the efforts to conceptualize these knowledge domains comes the question to what extent they can be distinguished empirically. Hence, the present study examines a measure that assesses pre-service teachers' self-efficacy in the technology-related TPACK dimensions (“T-dimensions”). In pursuit of crafting a validity argument, we investigated its factor structure and tested it for measurement invariance across gender and educational tracks, two subgroups that may indicate considerable differences. By means of multi-group confirmatory factor analysis, the data of N = 665 pre-service teachers in 18 teacher training institutions in Flanders (Belgium) revealed a nested factor structure of the TPACK measure, which comprised a general factor and a specific factor of pre-service teachers’ technological knowledge. This factor structure was fully invariant across gender and educational tracks. Mean differences between educational tracks did not occur; yet, substantial differences were found across gender in favor of male pre-service teachers. This study sheds light on critical aspects of crafting a validity argument for the measurement of the T-dimensions in the TPACK framework and reports relevant subgroup differences.

This study aims to identify profiles of pre-service teachers in order to explore their readiness to integrate technology in education. The assumption is that pre-service teacher characteristics such as technological pedagogical content knowledge (TPACK), go together with the influence of their teacher training. Specifically, this study examines whether pre-service teachers can be clustered on the basis of their TPACK, a typical set of ICT-related characteristics (e.g., general ICT attitudes, attitudes towards ICT in education, ease of use, ICT self-efficacy), and the perceived support at their training institution to adequately integrate ICT in education. Data were collected from a sample of 688 last-year pre-service teachers in 18 teacher training institutions in Flanders (the Dutch-speaking part of Belgium). Using correlational and latent profile analysis, the results suggest that: (1) two profiles can be distinguished, (2) TPACK and other individual ICT-related characteristics are positively correlated, and (3) pre-service teachers in a profile with strong TPACK, attitudes, and self-efficacy scores also report high scores on the support they perceive at their teacher training institution. Implications for the role of teacher training institutions are discussed with a specific focus on how to close the gap between the two identified profiles.

The main aim of this study is to validate an instrument to measure teachers' emphasis on the development of students' digital information and communication skills (TEDDICS), a construct that describes a qualitative aspect of ICT use beyond mere frequency reports. TEDDICS was conceptualized by focusing on digital skills such as accessing, evaluating, and sharing and communicating digital information. We validated TEDDICS with respect to its factorial structure, relations to further teacher-related variables (e.g., ICT self-efficacy), background characteristics (age and gender), and main subject differences. The Norwegian International Computer and Information Literacy Study (ICILS) 2013 teacher sample (N = 1072) showed that TEDDICS: (a) comprises three factors which can be identified by exploratory structural equation modeling (ESEM); (b) is positively related to ICT self-efficacy, the frequency of ICT use, and perceived usefulness of ICT; (c) differs across main subjects but not across gender groups. In addressing our research aims, we show that ESEM represents TEDDICS more appropriately than confirmatory factor analysis. Our results provide strong evidence on the construct validity and point out to the importance of looking at the degree to which teachers emphasize digital skills in classrooms beyond the frequency of using ICT.

Additional file 1. Additional material.

The main objective of this study is to develop a self-report instrument to measure pre-service teachers' perceptions of the extent to which they experience the necessary support and training in order to integrate technology into classroom activities. The questionnaire items of this instrument were drawn up on the basis of a synthesis of 19 qualitative studies (Tondeur, van Braak, Sang, Voogt, Fisser, & Ottenbreit-Leftwich, 2012) and were reviewed by experts in the field. In order to study its reliability and aspects of validity, data were collected and analysed consisting of a sample of 688 pre-service teachers in Flanders (Belgium). The resulting scale showed highly satisfactory psychometric properties. Item response theory revealed a good fit of the measurement to a Rating Scale Model for 22 out of 24 items. The results also indicate that the items differ in their degree of difficulty. It seems that helping pre-service teachers to design ICT-rich lessons and providing adequate feedback can be considered more challenging for teacher training institutions. Recommendations are given regarding how the new scale can be useful for both teacher training institutions and schools in developing approaches to equip pre-service teachers with the competencies needed to integrate technology in teaching and learning processes. Item response modelling was used to validate an instrument.The instrument measures the adoption of strategies to prepare future teachers for ICT-use.A single construct underlies the adoption of effective strategies used in TTIs.Items on strategies to prepare pre-service teachers can be ordered from easy to hard.This instrument is essential for valid and reliable benchmarking in TTIs.

I denne mastergradsoppgaven undersøker jeg ikke-vestlige elevers interesser innen naturfag og teknologi. Jeg har basert mitt arbeid på studien The Relevance of Science Education (ROSE). ROSE er en internasjonal undersøkelse som har kartlagt 15-åringers holdninger, interesser, erfaringer, forestillinger og framtidsplaner i forhold til naturvitenskap, teknologi, miljøutfordringer, forskning og forskere. ROSE-spørreskjemaet består av omtrent 250 spørsmål som tar til sikte å beskrive ulike perspektiver ved elevers forhold til naturvitenskap og teknologi (heretter kalt NT) i skole og samfunn. Denne studien er blitt gjennomført i rundt 40 land i Europa, Asia, Afrika og Sør-Amerika. Jeg benytter data fra de 108 spørsmålene i ROSE-spørreskjemaet som omhandler elevenes interesser, videre kalt ACE-spørsmålene. Jeg har i min oppgave analysert data fra fire ikke-vestlige land: Ghana, Uganda, Malaysia samt Trinidad og Tobago, og sammenliknet mine funn med den elevtypologien som Camilla Schreiner beskriver i sin dr-avhandling og Fredrik Jensen i sin Masteroppgave. Disse studiene er også basert på ROSEs ACE-spørsmål, men knyttet til høyt utviklede land. Mine forskningsspørsmål er: 1. Kan ungdommene i hvert av de utvalgte landene deles inn i karakteristiske og forskjellige interesseprofiler innen NT, basert på interessespørsmålene i ROSE-spørreskjemaet? 2. Vil det i så fall være like, eller liknende, sett av interesseprofiler i hvert av de utvalgte landene? 3. Vil interesseprofilene være sammenfallende eller forskjellige fra de Schreiner beskriver for Norge? 4. Er interesseprofilene sammenfallende eller forskjellige fra de Jensen beskriver for vestlige land (Finland, England og Sverige)? Jeg har ved hjelp av algoritmen ’K-Means Cluster Analysis’ i statistikkprogrammet SPSS, forsøkt å dele elevene inn i meningsfulle grupper (clustere) basert på deres respons på ACE-spørsmålene. Respondenter som plasseres i samme cluster har svart relativt likt på spørsmålene, og ved å studere hvert clusters interesseprofiler, kan en se hva de forskjellige elevgruppene er interessert i (eller ikke interessert i). Siden jeg har valgt å undersøke relativt forskjellige land, måtte jeg velge litt ulike tilnærmingsmåter for å prøve å forstå resultatene for de ulike landene. Som mål på landets utviklingsnivå har jeg brukt FNs Human Development Index (HDI). Ghana og Uganda er land med lave HDI-verdier, henholdsvis 0,553 og 0,505. For begge disse endte jeg opp med to clustere som mest meningsgivende. Disse har fått navnene Veldig interessert og Selektiv middels interessert. Disse to profilene angir grad av interesse, der den førstnevnte er veldig interessert i de fleste ACE-spørsmålene, mens den sistnevnte er middels interessert og mer selektiv i sin respons. Begge profilene har en relativt jevn kjønnsfordeling. Elevenes kjønn har altså begrenset betydning for kategoriseringen i profiler. Malaysia samt Trinidad og Tobago er begge industrialiserte land med middels HDI-verdier, henholdsvis 0,811 og 0,814. Jeg valgte fire clustere som mest karakteristiske for begge disse landene. Tre av interesseprofilene, som jeg kaller Lite interessert, Middels interessert og Veldig interessert, angir grad av interesse. Disse har en nokså jevn fordeling av gutter og jenter. I begge landene finner jeg også én kjønnsspesifikk profil. For Malaysia kaller jeg den Selektiv gutt, og for Trinidad og Tobago Selektiv jente. Basert på interessespørsmålene i ROSE, har Camilla Schreiner utviklet en norsk elevtypologi med fem ulike elevtyper. Hun kaller disse Selektiv gutt, Selektiv jente, Motvillig, Ubestemt og Entusiast. De tre sistnevnte elevtypenes interesseprofiler følger hverandre, og representerer tre ulike grader av interesse. Motvillig viser lav grad av interesse for det meste innen naturvitenskap og teknologi, for Entusiasten gjelder det motsatte. Ubestemt plasserer seg midt mellom disse to. Selektiv gutt og Selektiv jente er kjønnsspesifikke profiler, og disse interesserer seg for temaer innen NT som kan sies å være henholdsvis guttete og jentete. Hun tolker sine resultater ved hjelp av teorier om senmoderne samfunn og identitetskonstruksjon. Jensen fant liknende elevtyper som Schreiner for hvert av landene han undersøkte: Sverige, England og Finland. Jeg tolker mine funn i lys av teorier om samfunn og samfunnsutvikling. Interesseprofilene forstås da som et uttrykk for behov og interesser som springer ut av landenes kultur, nærmiljø og samfunnets tidsånd. Jeg bruker Maslow og Ingleharts teorier til å forklare interesseprofilene i de fire landene jeg har undersøkt. En sammenlikning av mine, Jensens og Schreiners funn viser en sammenheng mellom økende grad av uttalte svarresponser og kjønnsspesifikke clustere, med økende HDI-verdier. Jensen og Schreiner fortolker sine clustre som elevtyper, der elevene gjennom sin respons på ACE-spørsmålene uttrykker sin identitet. Clusterene jeg har funnet, uttrykker ikke i like stor grad forskjellige identiteter. Jeg kaller de derfor interesseprofiler og ikke elevtyper. Clusteranalyser av dataene for Ghana og Uganda ga to interessante interesseprofiler, men var ikke fruktbart hvis man ønsker å se dypere på hva disse interessene innebærer. Derfor valgte jeg å se på gjennomsnittsverdier for hver av de 108 ACE-spørsmålene. Jeg fant ut at elevene i Uganda og Ghana er mest interessert i spørsmål som har med helse og teknologi å gjøre. Det er også en del ACE-spørsmål som de ugandiske elevene ikke har forstått, disse spørsmålene er til en viss grad mer vestlig orienterte, for eksempel spørsmål om spiseforstyrrelser, slanking, plastisk og kosmetisk kirurgi, drivhuseffekt og kloning. Elevene i de afrikanske landene gir uttrykk for at de ikke forstår hva det spørres etter og/eller synes spørsmålene er uinteressante. Ved å sammenlikne ROSE-spørsmålene som jeg tolker som ”vestlige” med de frigitte PISA og TIMSS oppgavene, fant jeg noen likheter. Flere av PISA-spørsmålene likner de vestlig orienterte ROSE-spørsmålene som de afrikanske elevene åpenbart ikke forstår. Mine, Jensens og Schreiners analyser av ROSE-data for forskjellige land viser at elevers interesser er ulike ut ifra hvilket samfunn de vokser opp i. Elevenes interesser og holdninger påvirkes av den gjeldende tidsånd og de uttrykker seg ulikt i ulike kulturer. For å stimulere elevenes interesse og respekt for NT, samt øke rekrutteringen er det viktig å arbeide mot et naturfag som føles meningsfullt, interessant og relevant for dagens elever. Naturfaglæreplaner bør derfor tilpasses lokale forhold. Det betyr ikke at vi skal endre naturfagenes innhold. Naturvitenskapens teorier er felles og universelle, men vi kan og bør velge eksempler som er meningsfulle og viktige i ulike kulturer. Det er viktig at konteksten det naturfaglige innholdet settes inn i er relevant og kjent for elevene, slik at mulighetene for å kunne tilegne seg kunnskapen blir større.